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Applying Lean in Process Innovation in Healthcare: The Case of Hip Fracture

Manuel francisco morales-contreras.

1 Department of Management, ICADE, Universidad Pontificia Comillas, ICADE, 28015 Madrid, Spain

Pedro Chana-Valero

2 Fundación San Juan de Dios, Centro de CC de la Salud San Rafael, Universidad Nebrija, 28036 Madrid, Spain; se.ajirben@anahcp (P.C.-V.); se.ajirben@agicrage (E.G.G.)

Manuel F. Suárez-Barraza

3 International Business Department, School of Business and Economy, Universidad de las Américas Puebla (UDLAP), Puebla 72810, Mexico; [email protected]

Andrés Saldaña Díaz

4 Hospital San Juan de Dios León, 24010 León, Spain; moc.liamg@zaidlasna

Elena García García

Academic literature and practitioners acknowledge that there is a need to improve efficiency and service quality in the healthcare industry. In Spain, osteoporotic fractures represent a great cost in socio-economic and morbi-mortality terms, hip fracture being the surgical pathology with the second highest consumption of resources. The research questions that govern this study concern the use of Lean principles to identify waste, and an evaluation of the application of an innovative approach in the hip fracture surgery process. A research design based on a case study and action research was developed. Findings relate to (i) the identification of the main types of waste or muda (being the most frequent delay, transportation, over-processing and defects); (ii) the analysis of existing processes based on a Lean approach (identifying opportunities for improvement as a reduction of the number of steps and participants, improving communication, automation, standardization, etc.); and (iii) the application of an innovative process based on the Lean approach and action research in the healthcare industry. This research provides insights for academia, practitioners, management, and society: waste identification and process redesign helps to continue the improvement of operations, increase efficiency, reduce costs, and enhance services, providing benefits to patients, families, hospital employees, and the healthcare system.

1. Introduction

Among the high-risk industries, healthcare is the most poorly managed of all and is very late in coming to recognize the importance of the system factors that underlie adverse events [ 1 ], making a healthcare system analysis and support for patients and staff an absolute priority [ 2 ]. Overtreatment, undertreatment, overdiagnosis, underdiagnosis, uncontrolled costs and budgets, and medical treatment errors have been reported in health systems across the developed world [ 3 ]. Medical error can be defined as a deviation from the process of care that may or may not cause harm to the patient [ 4 ]. In the USA, medical errors are the third cause of death after cancer and heart disease. In Spain, it is estimated that medical errors were involved in 25.9% of court verdicts, 98.5% of them resulted in compensation awards [ 5 ], leading to an increase in healthcare costs. But not only medical errors impact patient experience and lack of efficiency in healthcare; other examples are: delays, long waiting times, waiting lists for service delivery, lack or excess of capacity, lack or excess of inventory, patients going to the hospital several times until a service is provided, unsatisfied patients, etc. The management of a healthcare organization needs to be able to make decisions on the value delivered to patients and relatives, so patient value must be the key to making responsible decisions as a health system. Porter defines patient value as the patient-relevant medical outcome divided by cost [ 3 ].

Funding and efficiency in the health sector becomes a priority issue in the context of an ageing population [ 6 ]. To address the crisis, the NHS (National Health Service, UK) has turned to the use of different “quality improvement” methodologies, often discovered outside the health sector, Lean management systems being one of them [ 7 ].

The term Lean applied to production or management systems was used for the first time by Womack et al. [ 8 ] It was derived from the Toyota Production System, which was oriented to the continuous improvement of quality, productivity, and efficiency, as well as to the reduction of costs and delivery times within the Japanese automotive industry [ 8 , 9 , 10 , 11 , 12 ]. Lean is doing more with less and refers to a methodology that pursues the identification and elimination of waste ( Muda in Japanese) [ 8 ]. Waste is defined as any activity that does not add any value from the customer perspective, thus reducing the efficiency of a process and increasing its costs [ 9 , 11 ]. Literature states that seven types of waste could be found in any process: defects, movements, process, inventory, overproduction, transportation, and time [ 8 , 9 , 11 , 12 ].

Although Lean management systems were originated within the manufacturing sector, there is a growing interest for its implementation in service companies [ 13 ]. There are many opportunities of finding waste in the service sector as the processes tend to be slow, and tend to include high values of work in process (or customers waiting), which has an impact on the costs, service quality, and customer satisfaction [ 14 ].

Lean practices, with the aim of improving medical care processes, can help to achieve more reliable healthcare systems by addressing the three steps for reducing system errors in healthcare, proposed by Makary et al., in 2016 [ 15 ]: making errors more visible (facilitate a culture of speaking up), responding to error (support clinician needs), and making errors less frequent (foster culture of safety). Lean has been implemented in different areas in healthcare as intensive care units, X-Ray, cardiology surgery, oncology, mental health units, and clinical laboratories [ 7 , 16 , 17 , 18 , 19 , 20 ]. A national survey in the United States found that 70% of hospitals used Lean healthcare or related methodologies to deal with both quality and cost issues [ 21 ]. Gonzalez-Aleu et al. in 2018 analysed the critical success factors when implementing continuous improvement projects in hospitals [ 22 ]. But there is not enough evidence to address its sustainability in broad healthcare adoption as well as its impact in quality healthcare [ 7 ] and achieve both effectiveness and efficiency improvements [ 18 ]. Thus, it remains a “challenge for academics and practitioners to evaluate Lean healthcare under a more critical perspective” [ 17 ].

Hip fracture is one of the leading pathologies in terms of resource consumption [ 23 ], with a progressive increase in the estimate of new cases per year [ 24 ] and a high-risk patient profile. Applying Lean to this scenario, with the aim of identifying barriers, sensitized with the patient’s needs and mapping the experience of the different actors involved, can improve quality of care and increase the efficiency of processes, helping managers and staff address more complex issues and deepen our understanding of how Lean works in healthcare [ 25 ].

The main research questions that govern the study are:

• RQ1. → What types of waste or muda could be identified around a hip fracture surgery process?
• RQ2. → How a process innovation methodology using Lean techniques is applied in healthcare, in particular in a hip fracture surgery processes?

With the aim of answering these research questions, we decided to conduct a methodology based on a case study and action research, by involving the research team in the process evaluation and redesign. The article is structured as follows: (i) an introduction; (ii) a literature review and theoretical framework; (iii) a description of the research methodology; (iv) the case study results; (v) discussion; and (vi) conclusion.

2. Theoretical Framework

Hip fractures are potentially catastrophic (deadly) events with adverse outcomes including alteration in function, institutionalization, and death [ 26 ]. Mortality rates have increased in ageing patients who live alone and who have poor pre-fracture mental status and mobility [ 26 , 27 , 28 ], other associated factors being: white race, osteoporosis, previous hip fracture, level of physical functioning, medication use, and hormonal and dietary factors [ 29 ]. Osteoporosis fractures are the fourth leading cause of chronic disease morbidity. Over 2 million women and 750,000 men are estimated to suffer osteoporosis at the level of the femoral neck, with an expected prevalence of 24.2% in women between 70 and 80 years old. The cost to the Spanish healthcare system related to osteoporosis fractures amounted to 4.2 billion euros in 2017 and is expected to increase to 5.5 billion in 2030 [ 30 ].

More than 500,000 acute hip fractures will occur annually by 2040; each year at least 300,000 old people are hospitalized by hip fractures [ 24 ]. The number of geriatric hip fractures is expected to rise annually all over the world related to the elderly population ages, which will significantly increase care costs for healthcare systems, patients, relatives, and societies. The incidence of this complication for the elderly in the United States is expected to grow to half a million by 2040, with a worldwide incidence of geriatric hip fractures reaching up to 4.5 million by 2050 [ 31 , 32 , 33 ]. In Spain, hip fractures are the second highest obstetric and surgical condition in resource consumption after colorectal and anal cancer regarding the average costs of the Diagnosis Related Groups (DRG) [ 23 ], with an estimation of 263,351 new hip fractures in women and 84,213 in men between 2010 and 2020, with an existing tendency to increase in older age groups (>80 years) [ 34 ]. In the 2018 National Registry of Hip Fractures (RNFC) report, the overall profile, of the 11,431 patients included from the 72 participating hospitals, described a profile of patients with an average age greater than 87 years, usually living at home, with 76% being women [ 35 ].

Looking for efficiency in the process at hand, with a mortality rate within the first year at 20–33% (that may persist beyond 5 years) is a priority, as is relying on value-based healthcare models [ 31 , 32 ]. In the first three months after surgery, older adults have an eight times higher risks of dying of a hip fracture compared with people who have not suffered from it, continuing the risk of death still in the first ten years [ 36 ]. Related to functional outcomes, which directly impact the patient´s social dimension, it is important to describe functional outcomes such as the inability to walk independently (40% of hip fractures patients), the situation of vulnerability, needing assistance to perform daily tasks (60%) and patients who become totally dependent requiring a nursing home one year after fracture.

Social impact is relevant, according to a study published in the British Medical Journal, which detected 80% of women over 75 years who would prefer to die rather than experience the loss of independence and living in a nursing home after hip fracture discharge [ 37 ].

According to Bradeanu et al., health and social care for hip fractures in the elderly in one year amounts to two billion euros in the UK, where the annual incidence was 79,243 euros in 2019, expecting to increase to 104,000 cases by 2025. Dementia incidence will reach 75.6 million in 2030 and 135.46 in 2050 in the whole population, but doubles every five years among people aged 65 to 90. They also highlight the social impact that both pathologies together have on the caregivers, including depression, a higher risk of developing anxiety, and more hours per day spent helping patients. Furthermore, hip fractures are associated with the development of disability, depression, and cardiovascular diseases in the elderly, with additional cost for society [ 36 ].

Therefore, with an increasing incidence and associated poor clinical outcomes, it is relevant to evaluate the impact of hip fractures in the elderly not only on the healthcare system but also in terms of the social impact that is generated by patients as well as by their relatives, the society and the environment [ 32 ]. Living in changing times regarding healthcare, political agendas, budgetary limitations, and new leaderships contributes to demanding from professionals the provision of greater value with fewer resources, promoting a bigger impact on patients and other stakeholders [ 38 ].

Nowadays, patients are increasingly demanding immediate, high-quality, and individualized care to their specific needs. To meet these demands, strategies are needed to combine sustainable quality improvement with increased efficiency [ 39 ]. Improving and ensuring effectiveness of clinical procedures is necessary, but so is improving healthcare performance using appropriate indicators: what works, for whom, and in which circumstances? This must be addressed to not leave anyone behind [ 40 , 41 ].

In a progressive ageing population scenario, indicators that measure the social value of interventions are becoming key indicators to be analyzed in a process of quality continuous improvement. It is important to detect key performance indicators during the process analysis so that, once improvements have been implemented, they can be measured; because collecting data is not enough, they must be used to improve healthcare [ 40 ].

Despite being the focus on which to work, currently the most important indicators to measure the performance of the health care process are the length of hospital stay (LOS), i.e., the number of days comprised between the date of a patient admission and the discharge date [ 42 ], as well as the intra-hospital, 30-day, and year-round survival. Exploring Lean healthcare on patient flow, the main outcomes categorized related to the utilization of services and access to services [ 21 , 43 ] are the length of stay, mean waiting time to see a doctor, mean waiting time to get treatment, median time for daily treatment, median waiting time to see a professional (nurse preparation), and the median process time of being discharged. Therefore, LOS and shorter waiting times after Lean healthcare intervention were the most common measures related to process outcomes. Related to the hip fracture care pathway, usual measurements are time to surgery, duration of surgery, detection of complications, hospital cost, allogenic transfusion rate, thirty-day readmission, and in-hospital mortality [ 44 , 45 ].

The provision of quality health services depends on an adequate and efficient execution of each of the processes in which not only clinical activities exist, but also in which a series of non-clinical support activities are executed by different types of resources, which varies from one organization to another. These processes are highly complex and dynamic, and it is becoming increasingly common to design them ad hoc with a multi-disciplinary character but, seeking a balance in the improvement of processes between the generation of impact on patient´s quality of life on the one hand and the need to reduce costs, reduce waiting times, and to improve the productivity of each resource on the other, is not an easy task [ 46 ].

In 2012, the European Commission proposed a new cooperation framework for innovation in the field of active and healthy ageing, adopting the “Quadruple Helix” innovation model, which aims to generate shared value involving and benefiting civil society, private companies, academia, and the public sector, thus creating a powerful innovation ecosystem [ 47 ]. Designing strategies to implement effective solutions according to this model requires the use of specific tools that can trigger improvements in the management and handling of risks, including psychosocial risk management and, subsequently, better well-being [ 48 ]. A useful method is the “design thinking” or user-centred design, proposed by the Stanford University Institute of Design, which establishes five unavoidable phases in the process of designing a digital solution, so that it is finally adopted by the target audience: empathizing, defining, devising, prototyping, and evaluating [ 47 ].

A more sceptical and scientifically rigorous approach to the development, evaluation, and dissemination of quality improvement methodologies is required, combined with the demand of more robust evidence for the methods and approaches that they use, in those areas of knowledge where a mix of theoretical, empirical, and experimental evidence is used to enable guidance and planning for their application [ 49 ].

Strategies focused on the improvement of care quality, waiting times, resource consumption, etc., with the aim of assuring sustainable high-quality care, are needed. For instance, innovative methods such as design thinking combined with Lean. Lean has proved to be a method that has become, in the past decade, one of the most commonly used as a quality improvement approach in healthcare settings to improve delivery of care [ 25 , 50 ], guaranteeing the improvement of the effectiveness and efficiency of health care delivery, and providing an impetus for establishing the best practice within an organization [ 42 ].

The Lean methodology approach was developed in the car manufacturing industry, and was later adopted in the healthcare field with the aim of improving quality of care and the efficiency of processes [ 25 , 39 , 51 ]. The first authors to carry out research on Lean in health were Young et al. in 2004, and Spear in 2005 [ 52 , 53 ]. Both argue that carrying out Kaizen and Lean Thinking efforts in health systems can help eliminate errors, delays, inadequate processes, duplications, and all kinds of MUDA in the activities of health services. Another pioneering research work on the subject was that of Kollberg and Dahlgaard et al., in 2007, who emphasize in their article that continuous improvement techniques help to significantly improve the performance of processes and services in health systems (specifically in Sweden in this case) [ 54 ]. Drotz and Poksinska also confirm the benefits of implementing Lean and Kaizen in health organizations because it generates positive effects on the positions and roles of medical personnel, moving from a bureaucratic style to an approach of agile processes and teamwork [ 20 ]. On the other hand, authors such as Bortolotti et al. have found 14 specific factors that increase the ability of employees to solve problems when using Kaizen in health systems [ 55 ]. The clarity of goals, the degree of the difficulty of objectives, the autonomy of the work teams, and the support of the top managers are critical to the success of the application of Kaizen according to these researchers.

On the other hand, Ortíz-Barrios and Alfaro-Saiz (2020) carried out a literature review of the application of process improvement in emergency processes in health hospitals [ 56 ]. The selected papers were categorized considering the leading ED problems and publication year. Two hundred and three (203) papers distributed in 120 journals were found to meet the inclusion criteria. In Latin America, Brazilian authors such as Coehlo et al. (2015) present a case study of process improvement, in which the performance improvement of the total workspace was 75% and the reduction in waiting for patient care went from 2 h to 30 min [ 57 ]. Coelho et al. (2015) also point out that Lean and Kaizen’s efforts can eliminate at least three hours a day of overtime in hospitals in Brazil. Curatolo et al., in 2014, also performed a literature review indicating that a Lean approach with a high-methodological maturity level that includes the 11 characteristic activities of process innovation or Business Process Improvement has never been reported [ 58 ]. Considering this, the paper suggests a meta model for a high-methodological maturity-level Lean method based on the characteristic activities of Business Process Improvement. Finally, Meyer et al. present the successful application of Lean Six Sigma, a set of quality improvement (QI) tools, to streamline their processes and uncover the root causes of program inefficiencies. All this for a hospital that performs treatments for cancer patients by Tobacco [ 59 ].

Godley et al. affirmed that quality improvement studies improving timeliness in healthcare are essential for reducing delays in care and for improving quality [ 60 ]. In 2018, Woodnutt et al. carried out a systematic literature review on the Lean sustainable method in NHS hospitals, finding that waiting times were the most common area in which Lean practices could have an effect [ 7 ]. In the management of patients undergoing hip replacement surgery, recent studies applying Lean methodology in combination with other strategies improved quality and at the same time reduced costs, resource consumption, and waiting times [ 42 , 44 ]. Moreover, interventions aimed at improving pre-fracture function and post-fracture social support could increase health perception following hip fracture [ 61 ] and there is evidence that psychological and social factors, particularly social support, influence recovery and post-fracture quality of life [ 62 ].

Therefore, Lean methodology, with the aim of identifying fundamental areas of delay and inefficiency throughout the process, has not been fully implemented to hip fracture care individually or combined with other methodologies [ 44 ], such as design thinking. This would enable the mapping of the patient’s experience (journey map) during hospital admission and subsequent discharge from the perspective of what he/she sees, hears, and feels at each phase of the process [ 63 ].

Lean methodology is used to increase value in healthcare, but it is seen that the determination of value is variable. It is not easily quantified under evaluation of healthcare-related services, maybe because much of this value is not based on clinical outcomes but on social ones, which are difficult to describe, capture, and translate into a decision-maker´s language, usually financial [ 38 ]. There is no standardized way to capture the social value inherent in healthcare programs, but we must work to obtain not only the direct and indirect costs, but also to determine the impacts they are creating.

Lean and Kaizen are focused on improving processes towards an ideal state, with the focus always on adding value to the client (patients), identifying waste (tasks that do not benefit or add value), reducing costs, and improving the work of professionals [ 7 , 48 ]. The origins of business process innovation could be traced back to the seminal works of Harrington [ 64 ] and Davenport and Short [ 65 ]. Davenport and Short defined processes as “a set of logically-related tasks performed to achieve a defined business outcome”, and they stated that a company should redesign such processes when they prove to be inefficient or ineffective [ 65 ]. Their research proposed a methodology consisting on five steps: (i) Develop the business vision and process objectives; (ii) Identify the processes to be redesigned; (iii) Understand and measure the performance of existing processes; (iv) Identify IT levers; and (v) Design and build a process prototype and implement improvements (Davenport and Short, 1990). Harrington defined business process innovation as “a systematic methodology developed to help significant advances in the way its business processes operate”. His model is composed of five stages: (i) Organising for quality; (ii) Understand the process; (iii) Rationalise processes; (iv) Implement, measure, and monitor, and (v) Continuous Improvement [ 64 ]. The literature also presents different approaches for business process improvement (Hammer and Champy [ 66 ]; Elzinga et al., [ 67 ]; Lee and Chuah [ 68 ]; Gardner [ 69 ]; Alange and Steiber [ 70 ]; Page [ 71 ]; and [ 72 ], among others).

The next section describes the methodology of this research paper, including a justification for the selected business improvement process framework.

3. Methodology

The objective of this research is to develop and apply a process of innovation methodology based on Lean principles in the healthcare industry, in particular in hip fracture processes. In order to pursue the objective, a research design based on a case study and action research (AR) was developed.

A qualitative case study methodology is appropriate when there is an interest in knowing the “how” and “why” of a phenomenon and it is focused in contemporary events [ 73 ]. Theory built from cases is likely “to have important strengths like novelty, testability, and empirical validity, which arise from the intimate linkage with empirical evidence” [ 74 ], and it is also likely to be interesting, accurate and testable, as they use a wide range of data sources such as interviews, documentation, quantitative data, and direct observations [ 75 ].

Greenwood and Levin defined AR as “the research in which the validity and value of the research results are tested through collaborative insider-professional researcher knowledge generation and application processes in projects of social change that aim to increase fairness, wellness, and self-determination”. AR allows collaboration between professional researchers and community and organizational stakeholders in “defining the objectives, constructing the research questions, learning research skills, pooling knowledge and efforts, conducting the research, interpreting the results, and applying what is learned to produce positive social change” [ 76 ]. An AR methodology aims at simultaneously generating an action and building knowledge related to this action; thus, the results are both the action or intervention and the research itself [ 77 , 78 ]. Empirical AR is carried out, as the researchers document a current phenomenon, follow the process and share the results. It is also a participatory research, as the researchers maintain active and close contact with agents within the organization, as both are part of the research team [ 77 ]. AR is research in action, participative, concurrent with action and consisting of a sequence of events with a focus on problem solving [ 78 ].

Alfaro and Avella in 2013 proposed to conduct a preliminary stage in AR which consists of the identification of the problem or opportunity that the research team pretends to study; this should be done as a teamwork activity among researchers and practitioners [ 77 ]. Once the study topic has been identified, the six main steps in AR are data gathering, data feedback, data analysis, action planning, implementation, and evaluation [ 78 ].

A private general medical surgical hospital has been chosen as a case study. It is located in a +120,000 habitants city in the North of Spain, in a sparsely populated region. This study focuses on optimization and improvement in the design of hip fracture surgery processes in the above-mentioned hospital. The justification for the case study lies in the fact that the hospital is located in a region with a clear aging population and consequently there is a high prevalence of hip fracture cases. The hospital decided to start offering the service “hip fracture surgery” in 2019; thus, operating rooms were assigned, and professionals were hired for this purpose. Before 2019, this service was only provided in particular and punctual cases; since 2019 the demand forecast is 150 surgeries per year.

The case study hospital has a long trajectory of working according to high quality standards (as it is certified ISO 9001 and EFQM 500+). Moreover, it shows a strong commitment towards continuous improvement, as the new service “hip fracture surgery” implies high values of LOS of patients, as well as high resource consumption. This justifies the interest, both for the hospital and for the Public Health system, in studying, analysing, and proposing improvements in the process with the aim of improving the quality of the services provided, the efficiency of the operations, and the experience of the patients and their quality of life once they have left the hospital facilities.

In this research, AR is ensured by the collaboration of researchers (expert in Lean, process innovation, and healthcare) with hospital management and professionals (doctors, nurses, technicians), who jointly defined the research objectives, conducted the research, analysed and discussed the results, and planned for action implementation and the next steps.

The research team decided to use the framework based on process innovation by Suárez-Barraza et al. (2019) [ 72 ]. The main justification for this is that the selected model is based on Kaizen and Lean management systems [ 8 , 9 ] with a gradual and continuous improvement focus. On the other hand, other models are closer to engineering and are more appropriate for manufacturing operations, and are more oriented to breakthrough or radical innovation. Lean management systems originated in Toyota’s automotive factories, and they are used today in countless companies and organizations, both in manufacturing and services, having begun to be used in the healthcare sector in recent years [ 16 , 19 , 20 ]. Lean management systems seek to analyse production processes with the aim of identifying the activities that add value to the customer, and then minimizing or eliminating all the activities that do not add any value, called waste ( muda , in Japanese).

The process innovation framework consists of the following stages [ 72 ], as shown in Figure 1 : (1) process selection and understanding the process, (2) mapping the process, (3) process measurement, (4) process analysis, (5) process redesign [ 72 ].

Process innovation framework.

Data analysis and collection

We selected the 2019 and 2020 years for observation because we wanted to know the details of the complete process related to hip fracture. Data and statistics were collected during 2019 and 2020. The field work and analytical phase occurred from November 2019 to March 2020. We combined the statistical analysis of the hip fracture patient’s dataset attended over 2019 and 2020 with process innovation and Lean healthcare analysis, including user experience ones. In this case, the study combined administrative data, experts’ point of view, and an observational process review.

4. Case Study: Hip Fracture Surgery Description

In this section we present a general description of the hospital case study, as well as a summary of descriptive statistics about the hip fracture surgery process in 2019 and 2020.

The special features that make the case study relevant are related to the aging of the population, the depopulation of this region, social isolation, and the lack of rural doctors and health care centers. The importance of the management of patient´s admission after hip fracture and discharge is undeniable. The case study hospital counts with over 300 beds, and provides medical services in close to 40 disciplines, which include traumatology, geriatrics, and cardiology, among others.

The hospital, immersed in a process of continuous quality improvement, analyzed the 2019 data and consequently took some actions oriented to improve them. Actions consisted of standardizing the medical-surgical process, consolidating an orthogeriatrics team, and carrying out an exhaustive follow-up. According to the data described below, a high impact was achieved, resulting in a reduction in average stays and mortality. The research described in this paper comes as the next step in this process of continuous improvement at the case study hospital, and consists of the analysis with Lean methodology with the aim of detecting potential points of improvement, within the real possibilities of the process at hand.

Hip fracture surgery at the hospital provides a service to 150 hip interventions annually as mentioned above in the case study justification in the Methodology section ( Section 3 ).

A descriptive statistical analysis has been carried out to describe the population:

Total patient population . We reviewed 148 clinical record histories in 2019, from 39 men and 109 women. In 2020, we reviewed 106 clinical records, from 26 men and 80 women.

Age . Related to age, in 2019, the average age was 86.5 years, the minimum being 68.5 years and the maximum being 99.9 years. In 2020, the average was 85.5 years, the minimum being 66 years and the maximum being 101 years. By gender, in 2019 women/men average ages were 87/85 years, and in 2020 women/men average ages were 87/81 years.

In-hospital mortality . In 2019, in-hospital mortality was about 6.77% of admissions or 8.78% of patients (13 patients). Discharge due to death occurs at different times, on average two weeks after admission, although half of the deaths occur before 9 days. Moreover, 30 days after discharge, the mortality rate is 1.35% (2 patients). In 2020, in-hospital mortality was reduced to 3.7%.

Total hospitalization time. Total hospitalization time refers to the total process cycle time, from patient arrival to the hospital to the moment when the patient is discharged and leaves the hospital. In 2019, half of patients (median value for cycle times) were discharged within 11.9 days, the average being 15.9 days; 25% of patients were discharged at 16 days or more. In 2020, the LOS median value was 9 days, the average being 9.41 days (40.97% less than 2019 data).

Presurgical time . The average presurgical time (from patient admission to surgery) was approximately 4 days in 2019, half of patients underwent surgery in 3.16 days or less. During 2020, presurgical time was 3.15 days.

Post-surgical average stay. The average length of stay after surgery in 2019 was 10.12 days. A length of stay after surgery of more than 20 days could be considered exceptional. On the other hand, during 2020, the average post-surgical time was reduced to 5.25 days, a reduction of approximately 50%.

A summary of the descriptive statistics is shown in Table 1 below:

Summary of descriptive statistical analysis.

5. Applying Lean in Process Innovation in Hip Fracture: Results

5.1. process selection and understanding the process.

The quality management system at the case study hospital has been built based on the analysis and understanding of the different needs and expectations of all the involved stakeholders (patients, society, suppliers, collaborators, finance clients) with the aim of providing them with the highest level of satisfaction. The system classifies internal processes in strategic processes, care processes, and support processes. Appendix A Figure A1 presents a detailed map of all of them.

Strategic processes refer to external relations of the hospital, to the management and planning, and to the continuous improvement.

Care processes refer to health attention, psychological attention, and social attention. Health attention consists of all the processes oriented to provide a health service to the patients, involving health operational steps (such as emergency, admissions, external medical consultations, hospitalization, surgery, rehabilitation), but also to diagnosis support (laboratory, image, other tests), clinical support (pharmacy, sterilization, blood reserves, nutrition, and dietetics) and care support (patient care, social work, volunteering, spiritual and religious care, bioethics, and patient safety). Psychological attention consists of all the processes oriented to provide a psychological rehabilitation service. Social attention consists of all the processes oriented to provide a service to homeless patients.

Support processes refer to information technologies, procurement and logistics, human resources, administration, and other processes.

5.2. Mapping the Process

The research team conducting this project is formed by the paper authors, two of them being experts in healthcare processes (in particular, in hip fracture) and two of them being experts in Lean management and innovation process methodologies. Collaboration with hospital management and hospital professionals (technicians, nurses, doctors) has been necessary in this research; in particular, the collaboration of a traumatologist doctor who is in charge of hip fracture surgery. Mapping the process refers to the documentation of the present situation and to the identification of flow.

Documenting the present situation must be done as it is in reality and not under ideal conditions. This has been conducted in two steps: first, the experts in hip fracture wrote the flow or sequence of activities from the first to the last step, i.e., from the first moment a patient enters the hospital until the moment the same patient leaves the facilities of the mentioned hospital. Second, a mixed team (expert in hip fracture and expert in Lean implementation) visited the hospital and followed the process from the first to the last activity, taking notes and pictures, asking questions to the different participants in the process activities, and walking the distances all along the path.

The results of these two steps are the design of a block diagram (which provides a general description of the sequence of the process) and, based on it, the detailed process mapping using flow diagrams. Figure 2 shows a block diagram, which is the first step in the process analysis. The flow diagram of the hip fracture process uses symbols according to the American National Standard Institute (ANSI). Figure 3 presents an excerpt of a flow diagram of the process. This first excerpt contains only 7 activities of a total of 236. The complete flow diagram can be found in Appendix B Figure A2 . The flow diagram was built on 23 pages that can be seen in Appendix B , showing that the hip care process map is a complex process in its current situation.

Block diagram.

Flow diagram (partial) showing the existing process.

5.3. Process Measurements

Measuring the existing process implies identifying different indicators related to the process with the aim of quantifying them. Process redesign will propose some initiatives oriented to improve the values of the proposed metrics. The indicators that we consider are:

The total number of activities resulted in 236.

The number of participants is 18 (*).

They are grouped in different areas (see detail in Table 2 ).

Detail of areas and participants in hip fracture surgery processes.

Note (*): It is important to acknowledge that the traumatologist doctor also acts as the surgeon.

• (iii) Process cycle times. This refers to the total process time, from patient arrival at the hospital to the moment that the patient is discharged and leaves the hospital (also known as total hospitalization times or LOS). Total process cycle times in 2020 are reported above in the case study description, the average being 9.41 days (40.97% less than 2019 data), the median being 9 days, the standard deviation being 4.17, the minimum being 0 days, and the maximum value being 32 days.

5.4. Process Analysis

The process analysis is carried out in two steps:

Analysis of hip fracture process activities.

• Defects: errors or defects when performing a task, producing a service or making a product.
• Overprocessing: repeating tasks or activities during the process.
• Overproduction: producing more than necessary.
• Movement: unnecessary or inadequate movement of personnel to execute a task (related to ergonomics or efficiency of movements).
• Transportation: carrying out or moving materials or patients from one location to a different location where a new task will be performed. This also refers to the transportation of employees.
• Inventory: excess of materials or goods which are cumulated in case they are needed.
• Delay: additional waiting time when the process stops more than usual.
• Unused Talent: underused qualified workers (it could also be—but not in this case—a bad attitude from employees affecting the process results).

Our analysis shows that 60 opportunities for potential muda have been identified in 54 activities (i.e., 6 activities present 2 types of muda ). Table 4 shows a summary of the different types of Muda . Appendix C Table A1 provides the details of all of them.

Summary of the different types of Muda: ( a ) Data, ( b ) Pareto chart.

5.5. Process Redesign

AR is involved in the teamwork activities carried out between researchers and practitioners. Process measurements and analysis have been conducted by the research team (based on its experience in Lean, process innovation, and healthcare) with the collaboration of the hospital director, hospital employees (nurses, technicians), and mainly by the active support and involvement of a traumatologist doctor who is also in charge of hip fracture surgery at the hospital.

After process analysis has been conducted by the research team in collaboration with hospital professionals (management, doctors, nurses), process redesign will consist of the proposal and implementation of some initiatives oriented to enhance value creation from the patient point of view, i.e., reducing waste, increasing efficiency, improving patient experience, and improving the values of the process metrics. Table 5 below summarizes a list of actions that have been proposed for further implementation, identifying the type of muda that could be impacted by them:

List of proposals.

As a next step, beyond the scope of this research paper, the authors suggest that an implementation plan could be designed, scheduled, executed, and evaluated. A new multidisciplinary team (involving researchers and hospital professionals) could be formed with the aim of guaranteeing that expected results are confirmed.

6. Discussion

The results of the care activity of the case study hospital are similar in average age to those found in the national hip fracture registry in Spain, with an average age of 87 years [ 35 ]. The average LOS of this registry is 10 days, slightly higher than the LOS of the analysed hospital.

The research questions that govern this study are (i) to try to identify the types of waste or muda , and (ii) to evaluate the application of a process innovation approach in healthcare, in particular in the hip fracture surgery process.

This research allowed us to identify 60 muda opportunities along the hip fracture surgery process, which is composed of 236 activities and where 18 participants interact. It is relevant to point out that 18 participants does not refer to 18 people, but to 18 job positions, each of them being performed by 1 or more people. For instance, one position is a nurse; if the patient stays at the hospital for 2 weeks, there will be different people working as nurses to take care of him (the nursing team is composed of more than 10 employees per shift, morning, evening, and night, 24 h a day).

The following different types of muda have been identified along the process: defects, overprocessing, overproduction, movement, transportation, inventory, delay, and unused talent. Some of them occur punctually, but others (we consider them as critical muda ) are more repetitive all along the process; these are the ones that we are going to discuss. Although three types of muda represent 72% of the total (enough for critical muda discussion), we also decided to consider the fourth type (which only represents 10% of the total).

Delay is the most frequent waste in the hip fracture surgery process. Delay represents 33% of all cases, the most common being as follows: (i) the patient needs to wait because the clinical process requires it (for instance, the patient needs to be stabilized—pulse, temperature, blood pressure, etc.—before being transferred to the next stage); (ii) the patient needs to wait because of a lack of available resources (no available hospital porter for transfer) or because all resources are busy (for example, X-Ray is being provided to a different patient; (iii) delays produced because an employee has forgotten or neglected a task, or presents a bad attitude. Type (i) is normal; type (ii) needs to be minimized (better resource planning); type (iii) needs to be eradicated. Communication between employees patients is crucial in each case because, even if the delay cannot be avoided, the patient experience could be positive if there is a clear explanation and justification for it.

Transportation is the second type of waste. In general, transportation refers to transferring the patient from one location to a different location, and, although frequent, it is not very relevant, as distances within the hospital are not big. When referring to transportation of employees (doctors, nurses, porters, etc.) there is evidence of inefficiency (repeated distances are walked to supervise, take care, provide service etc., to patients). Spaghetti charts and cause-and-effect analyses could be used to study this type of muda in detail.

Overprocessing waste could happen when (i) some tasks need to be repeated; (ii) the process is not well- or properly defined; or (iii) lack of resources or when employees perform tasks that are not supposed to be carried out by them. Waste reduction could be achieved by different means such as automation (e.g., when initiating the hip fracture process the system automatically requests a bed, avoiding the need to phone or call a floor supervisor), process standardization with poka-yokes or checklists (e.g., to avoid repeating blood tests or X-Rays), better planning (e.g., to avoid repeating the pre-surgery preparation); or better maintenance planning (e.g., reliable maintenance plans avoid equipment and machinery failures).

Defect refers to waste when the results of an activity are not right, i.e., when an error is produced. Errors could be clinical, or cause by service, attention, etc. Causes of errors could be diverse, but if clinical errors are excluded, many are related to miscommunication (too many participants in the process), a lack of a standardized processes (every employee adopts his/her own criteria to execute an activity or to take a decision), or to an excessive workload (attention and concentration decrease). A leaner process with less participants, standardized processes (process defines, trained employees, checklists, and poka-yokes) and a planned workload will reduce waste opportunities.

An inventory of materials is necessary at many stages in the process: labels, paper and bracelets in admissions; and X-Ray plates, medicines, and medical goods in emergency areas, rooms, UCEs, and operating rooms. Every supervisor is responsible for inventory management (inventory levels, keeping control, placing the orders). No specific method (economic order quantity, fixed period ordering, first in first out, etc.), nor software is used, but a manual control is carried out according to his/her own criteria. Lack or excess of an inventory has been reported, an excess of it being more frequent due to the fact that healthcare deals with patient lives and risks should be minimized. There is a pharmacy inside the hospital, in case of any material need.

Movement waste in this process deals mainly with patient manipulation to be transferred from a stretcher to accommodate a mattress, the handling of X-Rays, electrode tests, blood test sampling, or movement inside the operating room. Process standardization according to different patient types (weight, volume, health condition) would help to minimize this muda .

Different types of muda according to the literature [ 8 , 9 , 11 , 12 ] have been identified in the process, being delay the most frequent. This agrees with Godley et al. [ 60 ] and Woodnutt [ 7 ], who identified delay and waiting times as the relevant types of waste that should be addressed with the aim of optimizing processes. The literature shows different examples of authors who have studied the different types of muda in the same way. In the educational sector, Doman indicates that with process innovation efforts, the graduate and graduate management processes can be improved [ 79 ]. Walters et al. identified specific areas of internal production waste including defects and waiting, and in the process of our investigation, identified a significant shift in process efficiency due to resource allocation [ 80 ] focusing on 1040 financial norms. In fact, Ann Douglas et al. similarly identified the 8 types of muda in Higher Education [ 81 ] and Suárez-Barraza et al. also identified three new types of muda in the 21st century such as unnecessary emails, excess work meetings, and technological distractors [ 82 ]; processes in hospitals cannot be free of these three new types of muda either.

Finally, Coelho et al. present evidence of process innovation in health processes, for example, they reduced the cancer outpatient chemotherapy process cycle time from 2 h to 30 min [ 57 ].

Close collaboration between clinical staff, hospital management, and researchers allowed the collection of precise data, as well as information sharing, which is very valuable for the process analysis and redesign. A new process design presents the following advantages, which are aligned with the literature [ 31 , 42 , 44 , 60 ]:

For patients, a reduction of LOS, potential errors, and, as a consequence, an improvement in patient satisfaction and experience. Quality improvement impacts directly on the quality of life of the patient, including both psychological and social aspects related to the social isolation in which the patient returns after discharge.

For hospital management, an increase in efficiency and better planning, thus a cost reduction, a capacity increase, and, as a consequence, a potential increase of activity.

For hospital employees, waste reduction (times, overprocessing, potential errors, etc.) and standardized processes will reduce the workload, stress and fatigue, increasing their satisfaction, thus, their motivation and commitment.

The above-mentioned findings justify the selection of this process innovation framework, as it has a clear focus on waste identification and Lean operations redesign [ 72 ]. The identification of changes in the analyzed process with the proposed methodology involves a second phase of analysis and reflection with the orthogeriatric team to go in depth into the findings, and to identify those that can really undergo an improvement process.

7. Conclusions

The research examines the identification of waste or muda in a hip fracture surgery process in healthcare. Eight types of muda have been identified, the most frequent being delay, transportation, overprocessing, and defects, and actions based on them for improvement have been proposed.

The application of a process innovation approach has also been examined in this research, the result being that, although innovative, this approach is appropriate for the healthcare sector, as it is appropriate in any other service industry. Applying the process innovation methodology represents an effort of the Kaizen philosophy in critical processes in the health sector. In fact, it allows crystallizing redesigns and changes to eliminate muda from the activities of health processes. In our case study, all the proposals will lower the muda percentage by at least 30% for all hip process activities in the current situation.

This research is innovative on the implementation of the technical approach, and its contributions on the implementation side can be summarized by a set of proposals that have been done including: process standardization, reduction of the number of participants in the process, techniques to improve communication, automation initiatives, training, implementation of inventory management techniques, the implementation of some tools (such as 5 s, checklists, or poka-yokes), including new performance indicators, as well as patient satisfaction measurement systems, among others.

This research is also innovative on the action-research process itself, as it brings the following contributions: (1) although not common, we succeeded in obtaining a formal collaboration among clinical personnel (doctors, nurses, etc.), service managers, and researchers to carry out a joint research project; (2) a research team (expert in Lean and process innovation, as well as in healthcare) entering the hospital and visiting the whole detailed process overcoming potential problems or communication barriers; (3) the advantages of documenting and recording observations and results (the power of direct observation in the gemba , the Japanese word for “place”); (4) fruitful discussions among specialists, experts, managers, and researchers towards sharing knowledge and ideas aiming at process improvement; (5) the adaptation of a process innovation approach within the healthcare sector, which is different from other service industries due to different needs, priorities, and vocabulary, as well as differences between private or public hospitals.

When the average stay data is adjusted to normal [ 35 ], it can be complex to introduce improvements that contribute to the sustainability of the service and increase the impact on the patient. Therefore, an exhaustive analysis of each one of the mudas found before their implantation is necessary.

This research also offers some practical implications for healthcare managers:

• (i) the identification of all different types of muda all along the hip fracture surgery process provides hospital managers with an opportunity for continuous improvement, by trying to eliminate or minimize them;
• (ii) some initiatives have been proposed to redesign the process, which allows the management to take action towards gaining efficiency and service quality, which in turn impacts on operating costs and patient satisfaction;
• (iii) the observation and the analysis have been carried out by researchers, but a basic training and a checklist (an audit tool) would help employees to carry out this assessment any time they need in the future.

Finally, some limitations of the research are: (i) the data cannot be generalized due to its qualitative nature; (ii) the findings refer to the specific context of hip fracture surgery in a case study in Spain; (iii) process redesign initiatives have been proposed for implementation, but have not been evaluated yet. Future studies could be carried out with the objective of evaluating the effectiveness of the implemented actions and their outcome, as well as by using data analysis techniques to better understand the variability of data dispersion. Other future areas for research could be initiated using several years of data history in the case study, and by using a larger sample of hospitals, as well as other geographical areas.

Acknowledgments

Hospital management and personnel that kindly participated and collaborated with the research team.

Main Process s at case study hospital.

Source: Hospital Quality Management System.

Hip Fracture Process Flowcharts.

Analysis of different types of muda .

Author Contributions

All authors made a proportional contribution. Conceptualization, M.F.M.-C., E.G.G.; methodology, M.F.M.-C., M.F.S.-B.; validation, P.C.-V., M.F.S.-B.; formal analysis, M.F.M.-C., M.F.S.-B.; investigation, M.F.M.-C., P.C.-V., A.S.D., E.G.G.; resources, A.S.D.; data curation, M.F.M.-C., P.C.-V., A.S.D., E.G.G.; writing—original draft preparation, M.F.M.-C., P.C.-V., M.F.S.-B., E.G.G.; writing—review and editing, M.F.M.-C., P.C.-V., E.G.G.; visualization, M.F.M.-C., P.C.-V., E.G.G.; supervision, M.F.M.-C., E.G.G.; project administration, E.G.G. All authors have read and agreed to the published version of the manuscript.

This research received no external funding.

Conflicts of Interest

The authors declare no conflict of interest.

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Lean Process Improvements at Cleveland Clinic

By: Izak Duenyas

This case study teaches students about lean process improvement projects at the Cleveland Clinic, one of the world's leading hospital systems. The majority of the case focuses on one lean improvement…

• Length: 20 page(s)
• Publication Date: May 14, 2009
• Discipline: Operations Management
• Product #: W87C95-PDF-ENG

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This case study teaches students about lean process improvement projects at the Cleveland Clinic, one of the world's leading hospital systems. The majority of the case focuses on one lean improvement project and leads the student step-by-step through the Kaizen events, and the tools, approaches and outcomes of the project. The case study ends with two short mini-cases on additional process improvement projects at the Cleveland Clinic. The detailed and concise case is ideal for a discussion about lean process improvement in the services industry.

Learning Objectives

After discussing this case study, students will be able to:

1.) describe appropriate business terms and principles appropriate to this case

2.) apply critical concepts from earlier learning to define a solution to the case

3.) successfully articulate data and information in support of the solution proposed

4.) critically analyze and discuss other responses and solutions to the case

5.) draw lessons from the case analysis

6.) generalize the learnings of this case to other business challenges and decisions in organizations other than the one analyzed in this case study

7.) demonstrate leadership and scholarship in analysis.

May 14, 2009

Discipline:

Operations Management

Geographies:

United States

Industries:

Healthcare service industry, Scientific and technical services

WDI Publishing at the University of Michigan

W87C95-PDF-ENG

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• Research article
• Open access
• Published: 28 August 2021

Lean adoption in hospitals: the role of contextual factors and introduction strategy

• Angelo Rosa 1 ,
• Giuliano Marolla   ORCID: orcid.org/0000-0002-2095-8641 1 ,
• Federico Lega 2 &
• Francesco Manfredi 1  

BMC Health Services Research volume  21 , Article number:  889 ( 2021 ) Cite this article

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In the scientific literature, many studies describe the application of lean methodology in the hospital setting. Most of the articles focus on the results rather than on the approach adopted to introduce the lean methodology. In the absence of a clear view of the context and the introduction strategy, the first steps of the implementation process can take on an empirical, trial and error profile. Such implementation is time-consuming and resource-intensive and affects the adoption of the model at the organizational level. This research aims to outline the role contextual factors and introduction strategy play in supporting the operators introducing lean methodology in a hospital setting.

Methodology

The methodology is revealed in a case study of an important hospital in Southern Italy, where lean has been successfully introduced through a pilot project in the pathway of cancer patients. The originality of the research is seen in the detailed description of the contextual elements and the introduction strategy.

The results show significant process improvements and highlight the spontaneous dissemination of the culture of change in the organization and the streamlined adoption at the micro level.

The case study shows the importance of the lean introduction strategy and contextual factors for successful lean implementation. Furthermore, it shows how both factors influence each other, underlining the dynamism of the organizational system.

Peer Review reports

Over the last decade, healthcare has been called upon to respond to the increasing pressures arising from changes in demand – due to epidemiological changes and the demand for quality and safety – and increased costs due to the introduction of new technologies [ 1 , 2 ]. These major challenges are exacerbated by the shrinking resources available in health systems and, for most countries, by the principle of universal access to patient care. In order to meet the patients’ needs, a hospital must utilize a number of scarce resources at the right time: beds, technological equipment, staff with appropriate clinical skills, medical devices, diagnostic reports, etc. [ 1 , 2 ].

One of the most relevant issues for the management of a healthcare provider is the management of patient flows in order to purchase, make available, and use these scarce resources at the right time and in the right way, and to ensure the best possible care [ 3 , 4 , 5 ]. In this scenario, hospitals need to focus on the patient pathways in order to ensure fast, safe, and high-quality service [ 3 , 6 , 7 , 8 ]. The search for solutions to these challenges has extended beyond the boundaries of healthcare practices to study organizational methods and paradigms that have been successfully implemented in other sectors [ 3 , 5 ]. Among these, lean thinking has proven to be one of the most effective solutions for improving operational performance and process efficiency and for reducing waste [ 5 , 9 ]. Lean is a process-based methodology focused on improving processes to achieve a customer ideal state and the elimination of waste [ 10 ]. Waste is defined as the results of unnecessary or wrong tasks, actions or process steps that do not directly benefit the patient. The taxonomy of waste is: overproduction, defects, waiting, transportation, inventory, motion, extra-processing and unused talent [ 3 , 4 , 5 ]. In addition, lean addresses other key service issues such as continuous improvement and employee empowerment, whether healthcare professionals or managers [ 1 , 11 , 12 ]. Lean healthcare is defined as a strategic approach to increasing the reliability and stability of healthcare processes [ 7 , 13 , 14 ].

The first documented cases of lean applications in a hospital setting (HS) date back to the late 1990s. These aimed at improving patient care processes, interdepartmental interaction, and employee satisfaction [ 1 , 2 ]. The Virginia Mason Medical Center is one of the first and most emblematic examples of a successful migration of lean methodology from the manufacturing sector to healthcare. The hospital, based on the principles of the Toyota Production System, created the Virginia Mason Production System, a holistic management model in continuous evolution that not only had a strong impact on the quality of the services provided and on the reduction of lead time, but it also led to a decrease in operating costs [ 14 , 15 ]. Over time, many hospitals have followed in the footsteps of the Virginia Mason Medical Center [ 8 , 16 , 17 ]. The lean paradigm crossed the US border and spread to other countries such as Canada and England [ 5 , 12 ]. It was not until the early 2000 that the model was introduced in European hospitals [ 12 , 16 ].

The implementation of the lean paradigm in HS environments has increasingly attracted the attention of researchers and professionals. The interest in lean in HSs was fostered by the idea that the paradigm was particularly suitable for hospitals because its concepts are intuitive, compelling, and, therefore, easy for medical staff to use [ 18 , 19 ]. However, over time, alongside the evidence of successful implementation of lean in HSs, much of the research has shown failures in adopting the paradigm [ 5 , 20 , 21 ]. Moreover, a literature review showed that most of the cases were characterized by a partial implementation of lean methodologies and concerned single processes in the value chain or restricted technical applications [ 20 , 22 ]. Even today, few hospitals apply lean principles at a systemic level [ 23 , 24 ].

The failure of lean implementation is a hot topic. Many authors who have focused their studies on social and managerial issues have highlighted the existence of factors that either enable or hinder the implementation of lean. These factors are mostly related to the context and the implementation strategies [ 5 , 16 , 25 , 26 , 27 ]. Lean implementation is not self-evident, and the process of transforming an organization into a lean organization requires a long-term strategic vision, a commitment by management, and a culture of change in the entire organization [ 5 , 16 , 26 ]. Contextual factors influence successful implementation and introduction strategy; lean adoption, in turn, changes contextual factors. A lean transformation must be planned and managed; it is not a quick solution, but a strategic plan in constant evolution [ 5 , 28 , 29 ]. From this point of view, the introduction phase plays a fundamental role in implementation because it facilitates the dissemination of the lean principle in hospitals and enables the contextual elements that support change. Although most researchers have recognized the role of the introduction step, the impact of this phase on contextual factors has been poorly reported on in the literature [ 5 , 12 , 20 ]. Most of the articles have focused more on the benefits of this phase than on how to manage it.

In light of this, it is necessary to examine how hospitals introduce lean into their clinical pathways in order to explain the success of the lean implementation. Starting with an in-depth analysis of the contextual factors discussed in the literature, the document helps to clarify what drives success in lean implementation within the hospital. The research has therefore undertaken a critical study of the introduction of lean in the case study of the haematology ward at a university hospital in the south of Italy. The objective is to highlight: (a) the role of contextual factors for successful lean introduction and implementation in a hospital ward; (b) how the pilot project has improved the pathway of a cancer patient undergoing chemotherapy infusion; and, (c) how the success of the pilot project modified the contextual factors, facilitating the spread of lean within the organization.

The study has the merit of detailing all the lean introduction phases. The analysis period is about 2 years. The lean introduction started in May 2018 and lasted 7 months. The pilot project results refer to the follow-up period of December 2018 to May 2020, while the dissemination results refer to the period from December 2019 to May 2020.

The paper is structured as follows: In the following section, the theoretical background is provided. Section 3 describes the research methods, while Section 4 presents the results of the pilot project. Finally, Section 5 presents the conclusion, highlights some limitations of this study, and proposes some directions for further research.

Theoretical background

Most authors point out that the introduction phase is a crucial moment in lean implementation [ 10 , 12 , 16 ]. This phase reduces distrust of the method and organizational resistance to change. It shows the benefits of lean and assesses the organization’s ability to undertake continuous improvement. Many case studies report the success of lean in HSs by describing the use of lean instruments [ 8 , 30 , 31 ]. They offer the practitioners some methodological support, but not in a structured way since they do not provide a clear implementation roadmap [ 5 , 32 , 33 ]. Some authors have tried to fill this gap in the literature by offering guidelines for implementation. Augusto and Tortorella [ 33 ] suggests carrying out a feasibility study focused on the desired performance before implementing continuous improvement activities. The author suggests defining the techniques, roles, and results related to the improvement path. Curatolo et al. [ 5 ] argue that the improvement procedure has to take into account six core operational activities of business process improvement and five support activities. The six core operational activities are: selecting projects, understanding process flows, measuring process performance, process analysis, process improvement, and implementing of lean solutions. The five support activities are: monitoring, managing change, organizing a project team, establishing top management support, and understanding the environment. These studies, while offering further guidance on the process of introducing lean into a hospital, do not describe either the organizational context in which the method is being implemented or the strategies for its implementation [ 5 , 12 , 25 ]. The introduction of lean into a HS is not an easy task; there are many organizational issues to be addressed. Among these, the analysis of the context and the definition of the implementation strategy are the ones with the greatest impact on the success of the introduction [ 16 , 26 , 34 ].

The contextual elements are the special organizational characteristics that must be considered to understand how a set of interventions may play out [ 35 , 36 ]. They interact and influence the intervention and its effectiveness [ 34 , 36 ]. Two of the most cited contextual element are the drive to improve processes and the level of maturity [ 5 , 10 ]. The drive for improvement is represented by the exogenous and endogenous needs that act as triggers for the introduction of improvement methodologies [ 25 , 26 , 35 , 37 ]. The level of maturity refers to knowledge and experience in process improvement initiatives. It includes knowledge of methodologies and tools, experience gained, confidence, trust, and dissemination within the organization. Where the maturity is low, there is a risk of lean introduction failure in both the processes and the organization as a whole [ 5 , 16 , 38 ]. As long as the organization does not reach a fair level of maturity, the rate of change tends to be slow and sometimes frustrating. However, as the degree of maturity increases, lean implementation becomes a “day-to-day job” rather than a series of projects that take place at discreet moments [ 10 , 21 , 39 ]. Hasle et al. [ 39 ] highlighted that a high level of maturity allows for the implementation of principle-driven lean. Contextual elements include organizational and technological barriers such as resistance to change, lack of motivation, skepticism, and a lack of time and resources that inhibits the introduction and the implementation process [ 4 , 8 , 21 , 40 ]. The lean introduction process in HS is also complicated by the organizational context and the double line of clinical and management authority in hospitals [ 41 , 42 ].

With regard to internal contextual factors, many authors explored the readiness and sustainability factors influencing the adoption of lean. Readiness factors are those elements that improve the chances of lean implementation success; they provide the necessary skills and knowledge to enable organizational change [ 23 , 43 , 44 , 45 ]. The readiness and sustainability factors include any practices or characteristics that allow organizational transformation by reducing or nullifying potential inhibitors of success. High commitment and strong leadership of managers and physicians, continuous training, value flow orientation, and the hospital’s involvement in continuous improvement are just some of the most discussed topics [ 5 , 10 , 16 , 43 ]. Other examples include understanding employees needs, identifying the organization’s strategic objectives, project management, and teamwork [ 5 , 12 , 16 , 46 ].

From the study of the contextual elements described so far, some authors have developed models to assess the impact of context on the implementation of organizational improvement activities. Kaplan et al. [ 36 ] put forth the Model for Understanding Success in Quality (MUSIQ). The authors identified 25 key contextual factors at different organizational levels that influence the success of quality improvement efforts. They defined five domains: the microsystem, the quality improvement team, quality improvement support and capacity, organization, and the external environment. Kaplan et al. [ 36 ] suggest that an organization that disregards contextual factors is doomed to fail in implementing an improvement program; an organization that adopts a context-appropriate implementation strategy can change the outcome by triggering implementation enablers. Previous studies of lean adoption in HSs suggest that the fit between the approach taken and the circumstances will influence the chances of success [ 3 , 12 , 34 ].

There are two strategies for introducing lean in a HS, and they are characterized by the implementation level. The level of implementation refers to either micro or meso implementation. Brandao de Souza [ 16 ] defined meso-level implementation as the condition under which lean is spread throughout the organization and is implemented at the strategic level, while micro-level implementation is where lean is implemented at a single process level in discrete moments. Meso-level implementation is crucial for long-term success because a lack of integration in a lean system can lead to the achievement of local rather than global objectives and can also affect the sustainability of the paradigm [ 23 , 26 , 47 ]. However, organizations that want to implement lean at the strategic level often do not recognize the need for a long-term implementation program and introduce lean as a “big-bang initiative”. This leads in many cases to a failure to introduce the method [ 16 , 47 ]. Many researchers suggest introducing the lean approach through a pilot project run by a specially formed lean team [ 12 , 16 , 48 , 49 ]. The pilot project should be challenging, involve a process relevant to the organization, and require the use of a systemic approach. In particular, it should not be limited to the application of “pockets of good practice” or lean tools, but should include the systemic adoption of improvement programs such as the Plan-Do-Check-Act (PDCA) cycle [ 21 , 48 ]. Brandao de Souza [ 16 ] asserts that the first initiative should be tested on a relevant patient pathway. The lean team should be composed of clinical and non-clinical staff actively involved in the patient pathway. A pilot project that meets these conditions is a useful tool for increasing the maturity of the method within the organization [ 21 , 39 ]. It can increase the confidence of the team and staff in the lean approach and can promote the learning of lean methodologies and techniques [ 21 , 39 ]. Moreover, the pilot project activates the contextual elements, enabling the introduction of the model [ 10 , 12 ]. The successes of the pilot initiative must be celebrated and communicated within the organization [ 10 ]. When the first initiative leads to visible and easily quantifiable results, the method has a greater chance of spreading throughout the organization [ 10 , 12 , 16 ]. In light of these considerations, the lean implementation requires that the contextual elements and the introduction strategy be assessed at the same time. In addition, it would seem fair to assume that as contextual factors influence the introduction strategy, the results of the implementation strategy will influence the contextual factors.

In Fig.  1 , we propose an adaptation of the MUSIQ model [ 36 ] that shows the impact that the lean implementation strategy has on the contextual elements.

Our adaptation of the MUSIQ model

Study setting and design

This is an explanatory single-case study of the introduction of lean at a university hospital in Southern Italy. In particular, the introduction of lean in the pathway of a cancer patient undergoing infusion chemotherapy in a haematology ward will be discussed. This study was designed to evaluate how the contextual elements discussed so far have influenced the introduction of the method and how the successful pilot project has enhanced the internal context. We used the adaptation of the MUSIQ model [ 36 ] proposed in Fig. 1 to systematically trace the antecedents of the lean introduction and to explain how the success of the implementation strategy changes the contextual elements.

The work covers four periods over 2 years (Fig.  2 ). The first period concerns lean introduction and implementation strategy. The second is related to the pilot project implementation in the haematology ward. The third shows the pilot project results. The last assesses the impact of the pilot project on the dissemination of lean within the organization.

Stages of data analysis

Data collection

Different data sources and data collection methods are used with the aim of improving data validity through triangulation. The data sources are lean training documents, direct observations and nonparticipant observations, process performance reports, process data recorded by patients, and two questionnaires submitted to the hospital staff (the questionnaires assess the “pre” and “post” lean dissemination phases and the difference regards three open questions) (Fig. 2 ). The second author is the consultant who trained the lean team and coordinated the pilot project, and the first author conducted approximately 50 h of nonparticipant observations. The questionnaire was delivered to 25 medical department staff members in September 2018 and in May 2020. The first questionnaire focused on contextual factors that existed before the introduction of lean, and the second investigated changes in the contextual elements - in particular trust, maturity and lean dissemination. The semi-annual performance reports from 2017 to 2020 for the clinical pathway under examination include daily averages of the number of chemotherapies per chemo chair (MT), the patients’ length of stay (LOS), and the daily average of the percentage of patients undergoing chemotherapeutic infusion within 3 hours of hospital admission (P3). Each day, from September 2018, a document containing all the steps of the clinical pathway was given to each patient. For each activity, the patient recorded the start and end time, and a signature of the doctor or nurse was required. In the period of September 2018 – May 2020, the medical staff collected more than 1.250 reports from patients. The study also draws on 10 semi-structured interviews. The hospital CEO, the chief of the medical department, the nurse supervisor, the chief of the antiblastic chemotherapy handling units, and the chief of the clinical laboratory were interviewed in September 2018 and May 2020. The interviews focused on the contextual elements either enabling or inhibiting lean introduction or its dissemination, and ranged from 30 min to 1 hour in duration.

Data analysis

The factors described in Fig. 1 were used to systematically analyse the antecedents of the results and to understand their causal influence on the lean introduction. This data collection allows for the description of the case study. In addition, it simplifies the interpretation of the evidence that emerged through the study of the factors listed. The authors carried out a content analysis to classify the data by theme. The content analysis followed an inductive approach based on the identification of meaning units at the semantic level and the encoding of results [ 49 , 50 ]. Whenever researchers did not agree on semantic meaning, a new unit of analysis was proposed. The principle of consensus among all panel members was used to determine the interpretation, addition or deletion of elements of analysis. The discussion of the case study focuses on four themes: (a) contextual elements enabling or hindering lean introduction, (b) implementation strategy, (c) pilot project results, and (d) lean dissemination and adoption in hospital. These themes were submitted for review by the interviewees; their feedback was used to improve the accuracy of the case study description.

Case study presentation

The university hospital is a model of excellence in Italy for pre-clinical, translational, and clinical research and care activities. It is equipped with 110 beds to treat all types of oncological pathologies in adults. There are 115 researchers working there. The hospital is structured into six departments, of which three are clinical (Medical Area, Diagnosis and Imaging Therapy, Surgical Area), two are services, and one is an administrative/management department. The medical area includes four wards: medical oncology for thoracic pathology, medical oncology, haematology, medical oncology for oncology patient care. In 2015, the institute was accredited as a clinical cancer centre according to the Organization of European Cancer Institutes (OECI). Since 2015, evidence-based medicine and patient-centred care methodologies have been successfully implemented in the hospital, but no process improvement methodology has been used. In 2017, the hospital became a hub for oncological diseases, which led to an increased demand for care and services. The hospital has received national funds dedicated to hubs and has made investments in infrastructure improvements and the purchase of new innovative medical equipment.

Contextual factors enabling or hindering lean introduction

The description of the external and internal contextual factors, as revealed in the first questionnaire and the interviews, is given in Table  1 . Below is a brief description of each item.

External context and organizational elements driving lean introduction in the haematology ward

The analysis of the context revealed external and internal elements influencing the introduction of lean. Starting with the external elements, the most frequently discussed motivators that led to the search for methodologies for process improvement include the continuous increase in patient volume and the benchmark of process performance with other providers. Although the clinical results were above the national average, the increase in demand - especially in the medical area - highlighted the inability to manage the increasing flow of patients. The inability to manage the increasing number of patients also affected the performance of the process in the diagnostic area.

Internal elements driving the lean introduction were related to dissatisfaction with inefficient work practices within the medical area and the dissatisfaction of many patients who complained about long wait times and lengths of stay.

The choice of lean methodology derives from the desire to follow the example of certain Tuscan hospitals that have been using lean at a strategic level since 2015. These hospitals are considered the benchmark for continuous process improvement. One of these hospitals was already included in the 2013 OASI Report, edited by CERGAS - Bocconi, among the six Italian companies that were the first and best to successfully implement Lean Thinking in healthcare. In addition, the methodology was strongly sponsored by the clinical director and the general director of the hospital. They had participated in a 60-h regional training course on lean healthcare in the second half of 2017. During the training course, they studied case studies of excellence in lean implementation.

When, in May 2018, the hospital directorate proposed the introduction of lean methodology in the medical area, the head physicians showed strong resistance because of the resources that would need to be allocated to the implementation process. In addition, some doctors did not trust the method. This brought up some conflicts with the medical area managers. The haematology staff, represented by their head physician, were the only ones who explicitly agreed to implement the lean introduction. The department, as in most Italian hospitals, is structured as a clinical area where the physicians - in contrast to other professionals - were members of the ward organizationally. Haematology staff were strongly motivated to do research and achieve excellent process performance. They were interested in taking the opportunity to define excellent clinical pathways, as the ward was undergoing managerial and layout restructuring. In addition, the haematology staff believed that lean could further improve clinical performance and improve the patient-centred and evidence-based approach. Until mid-2017 the ward was part of oncology; afterward, it was made independent and new areas of the hospital were assigned to it. Since the ward became independent, one head physician, three doctors and four nurses have been hired. The department is equipped with the most modern medical equipment. The layout of the ward was not yet fully defined, and some rooms that could have potentially been assigned to medical, diagnostic and therapeutic activities had not been assigned to process activities. The ward shares the Antiblastic Chemotherapy Handling Unit (UMACA) and the analysis laboratory with the other four medical department wards in the hospital, so the staff needed to coordinate clinical processes so as not to create bottlenecks.

Since haematology is a strategic ward for the hospital, and in the last 2 years the demand for treatment has increased more than in other wards, the managers of the medical area have deemed it appropriate to introduce lean there. Haematology ward is considered strategic due to its high attractiveness and high immigration rates of patients from outside the region. These phenomena derive from the excellent reputation of the department in relation to the quality of care. Although the clinical pathways were characterized by excellent clinical outcomes, qualitative benchmarking activities (based on testimonials from physicians and patients) showed that the organization of the haematology patient pathway was very different compared to the benchmark (a Tuscan hospital) and that the patients’ perception of non-clinical service quality was lower. Although no investigation was carried out with respect to the ratio of equipment and personnel available per number of patients and amount of activities regarding the hospitals taken as benchmarks, the testimonials prompted management to come up with new specific, measurable, attainable, relevant and time - bound (SMART) goals (Table  2 ). The goals will be described in the next section.

Internal contextual elements enabling and hindering lean introduction in the haematology ward

At the organizational level, hospital management has strongly supported the introduction of the method. Since the haematology staff had no experience in process improvement activities, management provided the budget for an external consultant. In addition, three non-clinical personnel were allocated part-time to support the implementation of visual management systems and communication. The organizational structure of the ward has been modified to a matrix form. A team of three haematology ward physicians and two nurses was established and the ward’s head physician was elected project manager. The project manager had formal authority over the team and the personnel employed in the process to be improved; this reduced conflicts due to the double line of hierarchical authority. In this phase, the top-down decision-making approach was crucial to the successful restructuring of the organizational structure and the definition of the new organizational roles. The lean advisor supported the group for 8 months through training and project supervision. He coordinated two meetings per week and carried out Kata coaching activities. The theoretical training activity, lasting 5 week ends (in June 2018), was differentiated to accommodate technical and managerial competency needs. The team project manager and the medical area manager were trained on topics such as project management, team management, leadership, and the dissemination of lean. The members of the lean group were trained in lean techniques and tools. The key principles of lean thinking, the PDCA cycle methodology and lean assessment were taught to all participants. The most difficult barrier to overcome was the time available. The team agreed to spend 8 hours per week on training and pilot project implementation. The management of the team was facilitated by the experience gained with the implementation of the patient-centred care and evidence-based medicine. The motivation of the medical staff–microsystem element–and the focus on team management were key success factors for the involvement of team members. The culture of change introduced by patient-centred and evidence-based medicine was another enabling factor.

Implementation strategies

Pilot project definition.

Hospital managers and lean team members, who had experience in implementing patient-centred care methodologies, suggested starting a pilot project for the lean introduction. The consultant agreed. The team, with the support of the expert, analysed the clinical pathways in haematology. Six pathways emerged: a) diagnostic visits, b) biopsies, c) check-up visits, d) transfusions, e) infusion chemotherapies, and f) oral chemotherapies. Hospital managers argued that the pathway of the patient undergoing infusion chemotherapy was the most critical for patient and organization value. This process is the only one that involves several departments and requires a large amount of materials and time-consuming resources. In the first and second half of 2017 and 2018, there was a significant increase in the number of chemotherapeutic preparations. LOS, P3, and MT performance decreased during the same periods (Table  2 ). In addition, outpatient visits and the number of biopsies also increased. The medical staff stated that the increase in demand in the medical area had particularly affected the infusion therapy activities because they involved technical and instrumental resources that are shared with other departments (Table  2 ). The length of stay was analysed for patients undergoing short (LOS s ) and long-term infusion (LOS l ) chemotherapy. The first has a minimum duration of 90 min and a maximum of 180 min, and the second has a minimum duration of 181 min and a maximum of 360 min. Each patient was assigned to one of the infusion treatment classes. Process data were collected and analysed by the Department Management Control Office. The process performance data collection and reports were established in 2015 for the implementation of evidence-based medicine.

Pilot project implementation

The pilot project started in June 2018. The first month was dedicated to Gemba Walk, Methods-Time Measurement (MTM) and implementation of the 5S. In addition, the consultant trained the project manager, department managers and lean team members. There were many difficulties during the training period, especially with regard to process mapping and the concept of value, the latter being interpreted by doctors as clinical output. The non-medical staff dedicated to the project assisted the team in the drawing of the visual management material. A room in the medical department was dedicated for team meetings, and some notice boards were installed to post the materials developed during the project. The project activities were organized according to the Report A3 scheme. It followed the phases of the consolidated Deming cycle: Plan-Do-Check-Act (PDCA). Implementing the approach proposed by Deming allowed for the trial-and-error empirical method to be abandoned in favour of the “scientific” one. The PDCA allowed accurate planning of objectives and activities and their monitoring. The departmental managers and the consultant through the study of the national publications and explicit requests to colleagues in other hospitals - considered virtuous - identified the benchmark (Table  2 ). They took into account the hospital’s specific characteristics, such as the policy of not accepting haematochemical reports from outside for fragile patients. This choice is dictated by the risk management plan and affects P3 and MT performance. Time for blood sampling and haematochemical analysis is added to the cycle time; however, it eliminates many risks associated with clinical treatment.

The existing care process was mapped through Value Stream Mapping (VSM) based on the patient reports, Gemba walks, interviews, and direct observation. For instance, Fig.  3 shows the pathway of a patient undergoing short-term infusion chemotherapy. The cycle time in Fig. 3 was calculated over an observation period of 1 week and included 51 patients. In addition, the application of the Demand Map and the Spaghetti Chart were used to evaluate the ward nodes activated by the patients and the ward’s layout. These tools were useful in defining the possible sources of waste in the process. The application of these tools lasted more than 2 months and required several revisions. Once completed, the results were posted in the meeting room and were used for discussions with colleagues in the medical department. The lean team requested support from the consultant for the drafting of the VSM and for the layout analysis. In addition, the consultant was asked to simplify negotiations with staff from other departments who were reluctant to be subjected to time and method measurements. The negotiation activity required a degree of organizational effort. The facilitating elements were manifold: they enabled the involvement of staff opposed to the introduction of measuring instruments. In particular, the most effective were: the intervention of the directorate general, the delegation of hierarchical authority to the project manager and finally the endorsement of trade union committees. Moreover, during the planning phase, many difficulties emerged, including the selection of a unique and standardised measurement system, the coordination of work and meeting schedules, and the deadlines set by the project Gantt. Although the project manager was able to manage the team, he did not have enough experience in lean tools. The external consultant played a key role in managing these activities.

As-is process represented by VSM

At the end of the as-is analysis process, an Ishikawa diagram was used for the definition of root causes. Four root causes emerged from the meetings and interviews. They were patient flow management, coordination activities with other departments, layout, and Information Technology equipment (IT).

Patient flow management concerned the absence of priority in the management of patients based on the clinical path and the arrival of patients in the early hours of the morning. The lack of coordination with other departments led to delays in the preparation of infusion chemotherapy and blood test reports. The layout was such that the flow of doctors and nurses crossed the flow of patients, and this caused great inconvenience to the doctors and nurses. Also, the computer software was not compatible, which meant that the same data had to be recorded several times.

After some meetings and rigorous brainstorming, the lean team suggested changes to be made in the existing pathway. This was done by considering how patients could be divided into clusters so that the infusion activity could start as soon as possible without affecting other occurrences. Moreover, it is made possible to simplify the coordination between diagnostic units. The patient flow has been managed in such a way that long-term patients are given priority (first to be accepted and blood sampled), followed by patients needing biopsies, first visit, follow-up visit. Finally, short-term patients are treated in a way that limits waiting time and does not affect the activities of other departments. Theories of queues and operational research methodologies were implemented to address chemo chair saturation. A chemo chair activities plan was implemented through pull logic. In addition, the hospital engineer was involved in making sure the information systems were compatible. Whenever integrating the software was not possible, a data entry person was assigned to prevent medical staff from wasting their time on low-value activities. The ward layout has been modified to prevent patient flows from intersecting with the flows of doctors and nurses. In addition, the use of one room has been changed from a small warehouse to a blood collection room to increase the value of the activities carried out within it. The waiting rooms were moved outside the ward and, during the first 2 hours of the working day, the biopsy room was reassigned to blood collection activities to speed up the requests for therapies in UMACA. Patient intake, blood collection, and tube labelling activities have been paralleled to be performed simultaneously in the same room. The routes and modalities for the delivery of blood samples to the laboratories were revised in order to reduce the time and distance travelled by non-clinical staff. Tablet reporting systems were installed. Finally, a patient chemo chair allocation system was developed.

The resources needed for these changes were determined. The team tested and modified the changes during December 2018 and January 2019. The tests were evaluated based on the performance data, patient reports and the team’s expertise.

Pilot project results

In January 2019, it was decided to implement the new standard procedures that were tested in order to improve performance. The team met once a week for 6 months. On a monthly basis, performance was reviewed and new changes were tested. Clinical and nonclinical personnel from other wards and departments were invited to each weekly meeting to share with them the results of the pilot project, and to involve them in the lean methodology.

Every morning, the team leader investigated the impact of organizational changes in order to avoid conflicts. Organizational problems that emerged were discussed and resolved by consensus. In the follow-up phase, the consultant performed supervisory activities. Each week, the team leader performed the Kata coaching. During the first 6 months, the monitoring of activity was very frequent to prevent a return to old operating modes. Subsequently, when the staff had learned the new procedures, monitoring was reduced to once a month.

Table  2 and Fig.  4 shows the results achieved through the implementation of the pilot project. The objectives were not reached for all indicators; however, the results improved over time.

Figure  5 shows the to-be state of the same process analysed in Fig. 3 . From the cycle time analysis of each process step, the areas of waste eliminated are clear.

To-be process represented by VSM

The incremental improvements in process performance over time are explained by the need for staff to learn new procedures in the early period. In addition, the patients’ resistance to changing their habits also slowed down the improvement in performance. Patients have been educated over time, through an intense communication activity based on visual management systems and telephone reminders.

In addition to the results showed in Table  2 , the pilot project had a positive impact on the performance of other patient pathways in the medical department. The cycle time variability reduction and the levelling of the service demand allowed the UMACA and the analysis laboratory to better plan their activities. The new layout reduced waste due to unnecessary movement. Nurses walk 2 km less per day and doctors 1.5 km less per day. Software integration has reduced data logging time by 35 min per day for each doctor. Patients have evaluated the change positively. In particular, they have experienced a drastic reduction in wait times, and greater attention from the medical staff. Increased privacy and a precise time of service are other improvements reported by patients.

Finally, the clinical staff was satisfied with the new procedures because they reduce overloads and allowed for better planning of activities. They say that dividing patients into time slots based on clinical priority reduces stress and simplifies the coordination of activities with other departments. The success of the project was communicated internally and externally to the organization. In June 2019 the results were celebrated with a formal team award ceremony. The resulting Report A3 was posted on the bulletin boards in the hospital wards and in the reception area. By means of an internal circular sent to all medical directors, the directorate officially thanked the members of the lean team and highlighted the excellent results achieved in terms of waiting lists and process time reduction. In addition, the directorate funded the lean team’s participation to national conferences in order for the team to discuss the project. The improvement activities and results were described and summarized in an official report sent to the regional health authority and cancer patient associations (the latter were also given an evaluation form and an invitation to observe the optimised process in the field). Reporting was carried out by the hospital directorate and the project manager.

Lean dissemination and adoption in the hospital

Following several meetings between the directors and the primary doctors of the medical area, it became clear that there was a willingness to implement further improvement projects in other medical wards. The feedback from the pilot project team was a strong convincing factor. Moreover, the results of the external communication of the pilot project played a critical role in increasing the desire for emulation. The regional authorities requested for the project team to co-design the diagnostic and therapeutic care pathways (PDTA) of the haematology patient pathway inside the regional network. The patient association lobbied for similar projects to be implemented in other clinical oncology pathways. The change of internal context and enabling factors were of great importance at this stage. The drive to disseminate lean was characterized by both the need to improve process performance and to the desire to emulate the success of the project pilot. In addition, increased trust in the lean method has prompted the directors to provide a peer internal training program in the medical area. In June 2019, members of the pilot project lean team were promoted to the position of lean champions. Their role was to disseminate the lean methodology in the medical area and to train colleagues. The hospital directorate set up the Lean Support Office and assigned to it the three non-clinical resources that had already supported the pilot project. The first methodology to spread throughout the medical department was 5S. According to the lean sponsors, this methodology was a prerequisite for implementing lean methodologies in all wards and for facilitating inter-process lean implementation. Visual management systems have been implemented to facilitate changes and standardization of activities and to guide the patient through the hospital. The 5S methodology and visual management, which was initially underestimated by the medical staff, has solved many problems in the working environment. Increasing the availability of tools, simplifying the transmission of documentation, reducing errors in medical records and nursing diaries, reducing the duplication of requests and medical documentation, creating flexible workplaces, less movement and transportation in the hospital, and increasing patient autonomy are just some of the improvements achieved. However, the most important result to be achieved was an improvement in workplace wellbeing. Among the most used tools for 5S implementation and visual management are: checklists, one point lessons, kaizen forms, horizontal and vertical marking, red tags, Kanban, spaghetti charts. Finally, the demand map was implemented to trace the patient flow across the departments of the medical area and the vertical swim lanes and the resources/process matrix were utilized to identify staff involved in several processes and the potential bottlenecks (in addition to the UMACA and the blood chemistry laboratory). As of August 2019 many other lean projects have launched sometimes spontaneously and sometimes at the demand of department heads or project managers (Fig.  6 ). In August 2019, three projects were undertaken in the medical oncology for thoracic pathology and the medical oncology wards. Two of them concerned the same clinical pathway addressed in the pilot project, and the last one was the harmonization of protocols for caring for an oncological patient between departments. Each project has been implemented following the PDCA cycle (using the A3 report framework) with the support of one of the lean champions, who was assigned the role of project manager. Teams of three doctors and one nurse were dedicated to each project. In the planning phase, the tools adopted in each project were: spaghetti charts, VSM, Gemba Walk, standardized data collection sheets (both for patients and physicians), control charts, 5 Why or alternatively the Fishbone Diagram, definition of SMART objectives. In the “Do” phase, the solutions adopted for the resolution of problems are derived from Just in Time and agile approaches (especially for software’s’ integrations management). The pilot project A3 report was used as a knowledge management tool and resulted to be of great value to guide the implementation of the three projects. The members of the pilot project team supported their colleagues during the implementation of the three projects. This resulted in a positive impact on the quality and timing of the data collection activities, the drafting of the VSM, the definition of the KPIs and especially the root cause analysis. Even though the negotiation was simplified by peer training, support from more experienced colleagues and project management by a doctor, organizational and structural barriers emerged. The difficulty in getting the new procedures accepted, the impossibility of optimizing the layouts and the “not always respecting” the authority of the project manager limited the performance improvement. Although not all potential solutions have been implemented, the results obtained are evidence of the success of the projects.

Lean projects and dissemination activities

In September 2019 the diagnostic department started 5S and visual management implementation initiatives. In October 2019 the same initiatives were undertaken in the surgical department. These initiatives were spontaneously implemented. The managers of these departments have asked the hospital director to introduce lean in their departments. Given the maturity of the method and the number of doctors trained, hospital managers did not consider it possible to undertake systemic improvement pathways in all departments. However, they have changed the organizational structures of the departments into matrix structures. Two doctors with lean experience, per department, have been assigned the role of project manager. The project managers have sponsored peer training and Kaizen blitz activities throughout the hospital departments. In the period October to December 2019 more than 60 doctors and nurses were trained in 40-h courses by their colleagues (Fig. 6 ). Three Kaizen blitz projects in the diagnostic department and two Kaizen blitz projects in the surgical area were carried out (Fig. 6 ). In addition, a PDCA cycle project was implemented in the medical area for the stocking and tracking of drugs and instruments. Moreover, the two bin Kanban systems, drug tracking tools, optimisation of the position in the storage layout and systems for the analysis of consumption time series were implemented.

In December 2019, in all the departments discussed so far, doctors were involved in continuous improvement activities, with projects structured through the use of both PDCA cycle and Kaizen blitz. The activities were undertaken spontaneously without the supervision of a manager and without any impact on daily clinical activity. The maturity of the methodology, the support of colleagues, and trust were enabling elements. However, some barriers such as infrastructural constraints and coordination of doctors and nurses and information systems have frequently affected the implementation of the method and two projects failed.

Due to the success of implementations at the micro level, managers have attempted to implement the lean methodology at the meso level. Hospital managers discussed, formalized and communicate in organization the Lean Strategic Plan. In January 2020, the Lean Support Office was transformed into a lean projects control room and renamed as the Operations Management Office. The role of this office is to define lean development policies and to supervise continuous improvement activities. The office has been placed in line with the strategic direction. Two lean project managers, two hospital managers, and three administrative officers have been assigned to it. Lean assessment, to evaluate the degree of lean maturity in organization, and Honshi Kanri, to strategically govern change activities, were implemented to the organizational level. While the lean assessment revealed an increase in both advance in the use of lean tools and the principles behind them, the governance of strategic implementation through Honshi Kanri did not seem to provide the foreseen results. Operations management office project managers did not always agree with hospital directorate on project prioritization. In addition, there often were disagreements between the Operations Management Office staff and departmental project managers about when to launch a project and how to manage it and communicate project results. Although there were many process improvement projects underway, these have not always been decided harmoniously between the Operation Management Office and the hospital departments. Moreover, many projects undertaken spontaneously by lean teams were not communicated to the Operations Management Office, which was therefore unable to govern the dissemination of the method. Medical leadership in departments seemed to dominate over managerial leadership; thus, there is great difficulty in strategically governing continuous improvement.

The marked differences in the responses to the closed questions of the questionnaires submitted provide significant evidence of how lean has spread throughout the organization (Fig.  7 ).

Responses to the closed questions of the questionnaire

The marked differences in the responses to the closed questions of the questionnaires presented provide significant evidence of how lean has spread throughout the organization. In particular, the results show how standardisation, self-assessment, time for improvement and peer-to-peer training have become part of everyday working practice. Furthermore, problem solving and collaborative decision-making show significant improvements. These improvements were witnessed not only by management but also by doctors, nurses and technical staff in the medical area.

After the pilot project and the initial push for implementation by management, internal contextual factors changed radically within the organization. While initially sponsorship and management involvement were necessary for lean implementation, today the methodology is independently disseminated. In particular, small improvement groups have emerged that are able to address various challenges. Process vision and patient focus have become part of the hospital culture. Doctors claim that continuous improvements simplify daily work, save time, and increase the level of service and the number of services provided. However, although these changes occurred at the micro level, the organization failed to direct change at the strategic level. Thus, harmonization of lean projects according to the strategic direction of the facility has yet to be achieved.

In accordance with the findings of many researchers [ 10 , 16 ], this case study showed how a careful, context-driven lean introduction strategy facilitated the dissemination of lean - at micro level - within the hospital. The decision to implement lean was precipitated by external factors, including the need to improve the performance of processes in the medical area and to follow the example of other successful hospitals. The in-depth training by an external specialist and the pilot project, characterized by interdepartmental activities, the need for a systemic approach based on the Deming Cycle and the constant support of the external consultant, allowed the participants to acquire the necessary skills to support - sufficiently - the lean implementation in the clinical pathways of the medical department and to train their colleagues. The results of this project have been manifold. At the process level, there was a significant reduction in the patients’ length of stay, the wait times for haematological patients, the process time variability, and an increase in the number of daily chemotherapy therapies performed. At the medical area level, a spontaneous spread of the culture of improvement has emerged. Directorate commitment, motivation of the medical department staff and management, and the presence of a consultant were the main enabling factors for the success of the pilot project. In turn, the results of the pilot project were the trigger for the spread of lean in the hospital. The pilot project itself, and the changes made to standard procedures that were inspired by the intervention, altered the contextual elements, mirroring the MUSIQ model [ 18 , 26 , 36 ]. Moreover, as trust and maturity raised, the speed of lean dissemination increased. This confirms that knowledge of the lean method tends to reduce organizational barriers and resistance [ 5 , 21 , 51 , 52 ]. Kata training and coaching were other key elements for the dissemination of the methodology. Initially, the consultant carried out the training activity, and after the pilot project, the team members became trainers and project managers; in this way, lean spread in the organization spontaneously. Moreover, as stated by many researchers [ 12 , 21 , 46 ], the matrix structure and project managers helped the staff to support and better coordinate process improvement. The many projects activated in the period July 2019–March 2020 are the measure of the diffusion itself.

However, some issues have arisen. For the new working procedures, the willingness of and the acceptance by the staff is crucial to achieving and sustaining the results of lean initiatives; where this did not occur, conflicts arose and the speed of change slowed. In addition, although in the early stages of implementation the bottom-up approach must prevail over a top-down approach to facilitate consensus and trust among physicians, nurses, and all workers, during the dissemination phase a greater equilibrium between the two decision-making approaches must be achieved. In accordance with [ 2 , 5 , 10 ], this case study demonstrates the importance of the right balance between bottom-up and top-down approaches. Medical leadership tends to dominate managerial leadership such that continuous improvement, even though it takes place in clinical processes, does not follow the strategic organizational guidelines. This leads to conflicts between managers and medical staff. Organizational, technical and infrastructural obstacles have hindered the adoption of the methodology. It is clear from what has been found that the introduction strategy was correct, but that the implementation at the strategic level has not yet taken place. The context has changed considerably from an organizational point of view, but some barriers have not been overcome. The management, which strongly sponsored and supported the introduction and implementation of lean, was subsequently unable to guide the implementation at the strategic level.

Our adaptation to the MUSIQ model is useful for interpreting the relationship between lean introduction strategies and changing contextual elements. Looking backward through this model allows us to understand the links between contextual elements, lean implementation and outcomes.

Conclusions

This study revealed that the strategy of introducing lean has improved readiness, sustainability and confidence in the method within the organization. The growing maturity of the organization has encouraged lean dissemination. However, the choice of strategy depends heavily on contextual factors. The two factors, therefore, influence each other. Although the introduction strategy may facilitate the introduction of lean, it may be less important when certain organizational, technical and infrastructural barriers remain. This is particularly relevant for systemic implementation. Contextual elements, which changed over time, influenced the success of the implementation at micro-level. At the meso-level, however, the organization has not reached the maturity for a systemic implementation of the method.

As has already been shown in the literature, the determining factors for introducing the methodology refer to external and internal pressures. The level of commitment of both the leadership and management are decisive for the success of the implementation only if the staff is motivated. Furthermore, the analysis shows that managing lean implementation at the micro and meso-levels requires different types of efforts. While the level of maturity speeds up the adoption of lean at the clinical level, it is not true that the dissemination of lean at the operational level inevitably translates into its application at the strategic level. Medical leadership, reinforced by the success of lean project implementations, could instead undermine proper implementation at the meso-level. This experience strengthens the MUSIQ model and complements it by showing the importance of the lean introduction strategy and its impact on contextual factors.

Limitations and future research

The main limitations concern the complexity of detecting and analysing all the relevant social and organizational aspects that have characterized the introduction and dissemination phases and the observation period of the dissemination phase. Moreover, the expert content analysis could introduce opportunities for misinterpretation of the data. The relationship between the contextual elements and the pilot project results were mainly assessed through participant and patient reports, document studies, and observations. The authors used data triangulation and a review of hospital staff to overcome the limits of the content analysis. Given the specificity of the hospital’s contextual factors and strategic choices, it is also clear that the case study cannot be generalized.

The sustainability aspect of lean was not considered because the observational study was conducted over a period of only 2 years. To understand this issue, the authors will investigate the socio-technical aspects of lean and how the context supports continuous improvement over time.

Availability of data and materials

The datasets used and/or analysed during the current study available from the corresponding author on reasonable request.

Abbreviations

Hospital Setting

Information Technology

Length of stay

Number of chemotherapies per chemo chair

Methods-Time Measurement

Model for Understanding Success in Quality

Organization of European Cancer Institutes

Patients undergoing chemotherapeutic infusion within three hours of hospital admission

Plan-Do-Check-Act

Antiblastic Chemotherapy Handling Unit

Value Stream Mapping

Godman B, Novakovic T, Tesic D, Oortwijn W, Martin AP, Parker M, et al. Addressing challenges for sustainable healthcare in central and Eastern Europe. Exp Rev Pharmacoecon Outcomes Res. 2016;16(6):685–7. https://doi.org/10.1586/14737167.2016.1165610 Epub 2016 Mar 30. PMID: 26966924 .

Article   Google Scholar  

Teisberg E, Wallace S, O’Hara S. Defining and implementing value-based health care: A strategic framework. Acad Med. 2020;95(5):682–5. https://doi.org/10.1097/ACM.0000000000003122 PMID: 31833857; PMCID: PMC7185050.

Article   PubMed   Google Scholar  

Lum B, Png HM, Yap HL, Tan C, Sun B, Law YH. Streamlining workflows and redesigning job roles in the theatre sterile surgical unit. MJ Open Qual. 2019;8(3):e000583. https://doi.org/10.1136/bmjoq-2018-000583 .

Radnor Z, Holweg M, Waring J. Lean in healthcare: the unfilled promise? Soc Sci Med. 2012;74(3):364–71. https://doi.org/10.1016/j.socscimed.2011.02.011 .

Curatolo N, Lamouri S, Huet J, Rieutord A. A critical analysis of lean approach structuring in hospitals. Bus Process Manag J. 2014;20(3):433–54. https://doi.org/10.1108/BPMJ-04-2013-0051 .

Roemeling O, Land M, Ahaus K. Does lean cure variability in health care? Int J Oper Prod. 2017;37(9):1229–45. https://doi.org/10.1108/IJOPM-07-2015-0452 .

Chiarini A, Bracci E. Implementing lean six sigma in healthcare: issues from Italy. Public Money Manag. 2013;33(5):361–8. https://doi.org/10.1080/09540962.2013.817126 .

Parkhi SS. Lean management practices in healthcare sector: a literature review. Benchmarking. 2019;26(4):1275–89. https://doi.org/10.1108/BIJ-06-2018-0166 .

Joosten T, Bongers I, Janssen R. Application of lean thinking to health care: issues and observations. Int J Qual Health Care. 2009;21(5):341–7. https://doi.org/10.1093/intqhc/mzp036 .

Article   PubMed   PubMed Central   Google Scholar  

Womack JP, Jones DT. Lean consumption. Harv Bus Rev. 2005;83(3):58–68 148. PMID: 15768676 .

PubMed   Google Scholar  

Spear SJ. Fixing health care from the inside, today. Harv Bus Rev. 2005;83(9):78–91 158. PMID: 16171213 .

D’Andreamatteo A, Iannia L, Lega F, Sargiacomo M. Lean in healthcare: a comprehensive review. Health Policy. 2015;119(9):1197–209. https://doi.org/10.1016/j.healthpol.2015.02.002 .

Mazzocato P, Holden RJ, Brommels M, Aronsson H, Bäckman U, Elg M, et al. How does lean work in emergency care? A case study of a lean-inspired intervention at the Astrid Lindgren children’s hospital, Stockholm, Sweden. BMC Health Serv Res. 2012;12(28). https://doi.org/10.1186/1472-6963-12-28 .

Andersen H, Røvik KA. Lost in translation: a case-study of the travel of lean thinking in a hospital. BMC Health Serv Res. 2015;15(401). https://doi.org/10.1186/s12913-015-1081-z .

Goodridge D, Westhorp G, Rotter T, Dobson R, Bath B. Lean and leadership practices: development of an initial realist program theory. BMC Health Serv Res. 2015;15(1):362. https://doi.org/10.1186/s12913-015-1030-x .

Brandao de Souza L. Trends and approaches in lean healthcare. Leadersh Health Serv. 2009;22(2):121–39. https://doi.org/10.1108/17511870910953788 .

Ulhassan W, von Thiele SU, Thor J, Westerlund H. Interactions between lean management and the psychosocial work environment in a hospital setting - a multi-method study. BMC Health Serv Res. 2014;14(1):480. https://doi.org/10.1186/1472-6963-14-480 .

Kaplan HC, Brady PW, Dritz MC, Hooper DK, Linam WM, Froehle CM, et al. The influence of context on quality improvement success in health care: a systematic review of the literature. Milbank Q. 2010;88(4):500–59. https://doi.org/10.1111/j.1468-0009.2010.00611.x .

Nelson-Peterson DL, Leppa CJ. Creating an environment for caring using lean principles of the Virginia Mason production system. J Nurs Adm. 2007;37(6):287–94. https://doi.org/10.1097/01.NNA.0000277717.34134.a9 .

Mazzocato P, Savage C, Brommels M, Aronsson H, Thor J. Lean thinking in healthcare: a realist review of the literature. Qual Saf Health Care. 2010;19(5):376–82. https://doi.org/10.1136/qshc.2009.037986 Epub 2010 Aug 19. PMID: 20724397 .

Brandao De Souza L, Pidd M. Exploring the barriers to lean health care implementation. Public Money Manag. 2011;31(1):59–66. https://doi.org/10.1080/09540962.2011.545548 .

Kaplan GS, Patterson SH, Ching JM, Blackmore CC. Why lean doesn’t work for everyone. BMJ Qual Saf. 2014;23(12):970–3. https://doi.org/10.1136/bmjqs-2014-003248 Epub 2014 Jul 23.

Al-Balushi S, Sohal AS, Singh PJ, Al Hajri A, Al Farsi YM, Al AR. Readiness factors for lean implementation in healthcare settings--a literature review. J Health Organ Manag. 2014;28(2):135–53. https://doi.org/10.1108/JHOM-04-2013-0083 .

Article   CAS   PubMed   Google Scholar  

Henrique DB, Filho MG. A systematic literature review of empirical research in lean and six sigma in healthcare. Total Qual Manag Bus Excell. 2020;31(3–4):429–49. https://doi.org/10.1080/14783363.2018.1429259 .

Coles E, Wells M, Maxwell M, Harris FM, Anderson J, Gray NM, et al. The influence of contextual factors on healthcare quality improvement initiatives: what works, for whom and in what setting? Syst Rev. 2017;6(1):168. https://doi.org/10.1186/s13643-017-0566-8 .

Kaplan HC, Froehle CM, Cassedy A, Provost LP, Margolis PA. An exploratory analysis of the model for understanding success in quality. Health Care Manag Rev. 2013;38(4):325–38. https://doi.org/10.1097/HMR.0b013e3182689772 .

Tay HL, Singh PJ, Bhakoo V, Al-Balushi S. Contextual factors: assessing their influence on flow or resource efficiency orientations in healthcare lean projects. Oper Manag Res. 2017;10(3–4):118–36. https://doi.org/10.1007/s12063-017-0126-3 .

Hussain M, Malik M. Prioritizing lean management practices in public and private hospitals. J Health Organ Manag. 2016;30(3):457–74. https://doi.org/10.1108/JHOM-08-2014-0135 PMID: 27119397 .

Fournier PL, Jobin MH. Understanding before implementing: the context of lean in public healthcare organizations. Public Money Manag. 2017;38(1):37–44. https://doi.org/10.1080/09540962.2018.1389505 .

Chiarini A. Risk management and cost reduction of cancer drugs using lean six sigma tools. Leadersh Health Serv. 2012;25(4):318–30. https://doi.org/10.1108/17511871211268982 .

Gonzalez ME. Improving customer satisfaction of a healthcare facility: reading the customers’ needs. Benchmarking. 2019;26(3):854–70. https://doi.org/10.1108/BIJ-01-2017-0007 .

Terra JDR, Berssaneti FT. Application of lean healthcare in hospital services: a review of the literature (2007 to 2017). Prod. 2018;28(0):e20180009. https://doi.org/10.1590/0103-6513.20180009 .

Augusto BP, Tortorella GL. Literature review on lean healthcare implementation: assessment methods and practices. Int J Serv Oper Manag. 2019;32(3):285–306. https://doi.org/10.1504/IJSOM.2019.10019746 .

Fournier PL, Jobin MH. Medical commitment to lean: an inductive model development. Leadersh Health Serv. 2018;31(3):326–42. https://doi.org/10.1108/LHS-02-2018-0015 Epub 2018 Jul 3. PMID: 30016920 .

Improta G, Romano M, Di Cicco MV, Ferrero A, Borrelli A, Verdolina C, et al. Lean thinking to improve emergency department throughput at AORN Cardarelli hospital. BMC Health Serv Res. 2018;18(1):265–78. https://doi.org/10.1186/s12913-018-3654-0 .

Kaplan HC, Provost LP, Froehle CM, Margolis PA. The model for understanding success in quality (MUSIQ): building a theory of context in healthcare quality improvement. BMJ Qual Saf. 2012;21(1):13–20. https://doi.org/10.1136/bmjqs-2011-000010 .

Kringos DS, Sunol R, Wagner C, Mannion R, Michel P, Klazinga NS, et al. The influence of context on the effectiveness of hospital quality improvement strategies: a review of systematic reviews. BMC Health Serv Res. 2015;15:277. https://doi.org/10.1186/s12913-015-0906-0 PMID: 26199147; PMCID: PMC4508989.

Hasle P, Bojesen A, Jensen PL, Bramming P. Lean and the working environment: a review of the literature. Int J Oper Prod. 2012;32(7):829–49. https://doi.org/10.1108/01443571211250103 .

Hasle P, Nielsen PA, Edwards K. Application of lean manufacturing in hospitals- the need to consider maturity, complexity, and the value concept. Hum Factors Ergon Manuf. 2016;26(4):430–42. https://doi.org/10.1002/hfm.20668 .

Narayanamurthy G, Gurumurthy A, Subramanian N, Moser R. Assessing the readiness to implement lean in healthcare institutions – a case study. Int J Prod Econ. 2018;197:123–42. https://doi.org/10.1016/j.ijpe.2017.12.028 .

Bijl A, Ahaus K, Ruël G, Gemmel P, Meijboom B. Role of lean leadership in the lean maturity - second-order problem-solving relationship: a mixed methods study. BMJ Open. 2019;9(6):e026737. https://doi.org/10.1136/bmjopen-2018-026737 .

Waring JJ, Bishop S. Lean healthcare: rhetoric, ritual and resistance. Soc Sci Med. 2010;71(7):1332–40. https://doi.org/10.1016/j.socscimed.2010.06.028 .

Arumugam V, Antony J, Kumar M. Linking learning and knowledge creation to project success in six sigma projects: an empirical investigation. Int J Prod Econ. 2013;141(1):388–402. https://doi.org/10.1016/j.ijpe.2012.09.003 .

Wilson WJ, Jayamaha N, Frater G. The effect of contextual factors on quality improvement success in a lean-driven New Zealand healthcare environment. Int J Lean Six Sigma. 2018;9(2):199–220. https://doi.org/10.1108/IJLSS-03-2017-0022 .

Gonzalez-Aleu F, Van Aken EM, Cross J, Glover WJ. Continuous improvement project within kaizen: critical success factors in hospitals. TQM J. 2018;30(8):335–55. https://doi.org/10.1108/TQM-12-2017-0175 .

Stanton P, Gough R, Ballardie R, Bertram T, Bamber GJ, Sohal A. Implementing lean management/six sigma in hospitals: beyond empowerment or work intensification? Int J Hum Res Manag. 2014;25(21):2926–40. https://doi.org/10.1080/09585192.2014.963138 .

McIntosh B, Sheppy B, Cohen I. Illusion or delusion--lean management in the health sector. Int J Health Care Qual Assur. 2014;27(6):482–92. https://doi.org/10.1108/IJHCQA-03-2013-0028 .

Jimmerson C, Weber D, Sobek DK 2nd. Reducing waste and errors: piloting lean principles at Intermountain Healthcare. Jt Comm J Qual Patient Saf. 2005;31(5):249–57. https://doi.org/10.1016/s1553-7250(05)31032-4 .

Drotz E, Poksinska B. Lean in healthcare from employees' perspectives. J Health Organ Manag. 2014;28(2):177–95. https://doi.org/10.1108/JHOM-03-2013-0066 .

Morgan SJ, Pullon SRH, Macdonald LM, McKinlay EM, Gray BV. Case study observational research: a framework for conducting case study research where observation data are the focus. Qual Health Res. 2017;27(7):1060–8. https://doi.org/10.1177/1049732316649160 Epub 2016 May 22. PMID: 27217290 .

van Rossum L, Aij KH, Simons FE, van der Eng N, Ten Have WD. Lean healthcare from a change management perspective. J Health Organ Manag. 2016;30(3):475–93. https://doi.org/10.1108/JHOM-06-2014-0090 .

Savage C, Parke L, von Knorring M, Mazzocato P. Does lean muddy the quality improvement waters? A qualitative study of how a hospital management team understands lean in the context of quality improvement. BMC Health Serv Res. 2016;16(588). https://doi.org/10.1186/s12913-016-1838-z .

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Lean UX: definition, process, and a detailed case study

Scott Adams, the creator of the Dilbert comic strip, has spent the past 30 years making fun of inefficiency in business—including our efforts to reduce inefficiency.

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The truth is, it’s hard to get everyone on the same page in any organization, big or small. That’s why  Doodle , a Software as a Service (SaaS) company with just over 50 employees and 250 million active users, turned to Lean UX to improve its products in an efficient, evidence-based, customer-centric way. In other words,  Lean UX principles help Doodle’s product teams make the changes their customers want in a smart, efficient way, so they can grow faster and boost their bottom line .

I recently sat down with   Jack Berglund, Chief Product Officer at Doodle , to talk about his product development strategy. He was very transparent, so if you’re looking for a real-life example of how to use Lean UX for digital product design, you’ve come to the right place.

Table of contents

Lean ux case study: what is doodle and who is jack berglund, what is lean ux, 3 phases of lean ux: think, make, check, lean ux development process at doodle, lean ux: a simple roadmap to get started.

Doodle is an online tool that helps people schedule meetings more efficiently. It syncs with all the major calendaring systems (Google, Outlook, Apple’s iCal, etc.), and it lets users poll meeting invitees to find a time that works for everyone.

Founded in 2007, Doodle is headquartered in Zurich with offices in Berlin, Tel Aviv, Israel, and Belgrade. Today, more than 250 million people use Doodle each year, and it’s available in more than 25 languages.

As Doodle’s Chief Product Officer, Jack Berglund uses Lean UX to guide agile, cross-functional teams to develop products that customers love.

Does that sound a little too jargon-heavy? Don’t worry, I’ll unpack it all for you… and I promise it won’t sound so much like a Dilbert cartoon by the time we’re done.

Lean User Experience (UX) Design is a user-centered design process that embraces Lean and Agile development methodology to reduce waste and build products centered around the users. Lean user experience design relies on a collaborative approach and rapid experimentation/prototyping, to get user feedback by exposing a minimum viable product (MVP) to users as early as possible.

The Lean UX process grew out of earlier  process management  systems like  Lean Manufacturing , which has been used by major companies (such as Intel, Nike, Toyota, and Ford) to eliminate waste in production. Lean UX took principles that were originally designed for physical products and adapted them for software development.

LEAN UX TAKES ITS ROOTS IN LEAN MANUFACTURING, WHICH IS USED BY MAJOR COMPANIES ACROSS THE WORLD.

What makes software production different? For one thing, you don’t have to follow the old “measure twice, cut once” idea. Instead, your Agile product teams (which are composed of experts from different departments) can come up with ideas, test them out quickly, and revise them based on customer responses and usability.

As Jeff Gothelf puts it in  Lean UX: Designing Great Products with Agile Teams , “You can measure once, cut once, measure once, cut once, measure once, cut once, forever.”  That’s the luxury that SaaS and e-commerce product design teams have. Since they work in a virtual space, they just don’t have the same physical restrictions to user experience design as Toyota or Nike.

How so? If you’re Toyota, you can’t try out five different steering wheels in one month to see which one  improves the customer experience . But if you’re Doodle, you can add a new checkbox to the 'Make a Poll' product, see if it gets any use, and tweak it accordingly.

Lean UX in action:  Doodle saw a 54% increase in the number of free trial signups by changing the language on their homepage to focus on business use-cases, which was a greater increase than expected.

In the Lean UX model, product teams are usually made up of members from different departments (e.g., engineers, product managers, UX designers). Each team works to improve a specific product by focusing on improving processes that cycle through three phases: Think, Make, and Check.

THE LEAN UX MODEL FOLLOWS A THREE-PHASE CYCLE: THINK, MAKE, AND CHECK.

Teams brainstorm possible areas for improvement based on  customer feedback , customer research, competitor comparisons, and observing their product in use. They develop a problem statement, then decide which areas they want to improve.

Designers and developers build a new feature that will (hopefully) solve a problem and/or improve the product.

Product teams test the new feature, using tools like  UX surveys  and  A/B testing , to figure out whether their hypothesis was correct. If customers respond well to the new feature, it becomes part of the new design. If it doesn’t improve the customer experience, they return to the Think phase and try something new.

The Doodle team uses Lean UX to anticipate their users’ needs. This design-thinking approach allows them to build cutting-edge products their customers will gladly pay for, and keeps them one step ahead of the competition.

They have five product teams, and each team is usually composed of at least one  product manager , one product designer, and a collection of engineers—possibly including data scientists or data engineers, as needed.

A TYPICAL PRODUCT TEAM AT DOODLE INCLUDES A PRODUCT MANAGER, A PRODUCT DESIGNER, A DATA SCIENTIST, AND MULTIPLE ENGINEERS.

The idea is to create a cross-functional team (meaning, teams from different departments) who come together to work on specific product improvements (such as Doodle’s 'MeetMe' product, Polls, etc.). Each team has a slightly different makeup depending on the product they manage.

Lean UX in action:  Doodle tested out a new calendar invite feature that put the agreed-upon meeting time in all attendees’ calendars, and 40% of their customers used the first version of this feature. This demonstrated how strong the demand was for the feature, and gave the team a clear sense of where to go next because there was already plenty of room for improvement on that initial version.

What does the lean UX process begin with? Here’s how Doodle approaches their Think, Make, Check phases:

Step 1: the thinking phase at Doodle

Doodle uses  Airtable  to maintain their 'idea bank,' which is a collection of all ideas submitted for improvement and, at the time we talked, contained 175 ideas.

DOODLE USES AIRTABLE TO COLLECT IDEAS AND PRIORITIZE THEM.

“We use the idea bank to capture all ideas, wherever they come from. Even if we think they're terrible ideas, we still write them down, and that serves two purposes. One, we want the person who made the suggestion to know that it's been captured and it's up for consideration. Two, we do this because what might not be a great idea now, for whatever reason, might become a great idea in the future.”

Of course, ideas don’t come out of thin air! The product teams at Doodle use the following tools to gather  qualitative research  from their customers and capture ideas for product improvement.

3 lean UX tools Doodle uses to find areas for improvement

Google Analytics : “Google Analytics is a good source for us in terms of user behavior within the product,” says Jack. Doodle uses Google Analytics for cohort analysis , which is all about breaking users down into groups (cohorts) and studying the behavior of each group. For example, Doodle can tell whether a user who connected through their Calendar Connect product is retained better than those who have not. They have their own data warehouse to complement this information.

Desk.com: Desk.com , a Salesforce product, allows Customer Success (CS) to tag different types of issues that arise. “For obvious bugs,” Jack says, “it’s a bit easier: if something isn’t working the way it’s supposed to, it’s pretty obvious that you need to fix it. Where it becomes more complicated is when you receive input, either from research or CS, that speaks to something that isn’t so black and white, like a feature we could add down the line. At that point, it goes from an engineering/problem-solving matter to a question of prioritizing and using your judgment,” he says. In the next section, I’ll talk about how Doodle prioritizes projects like these.

Hotjar : Doodle uses Hotjar Feedback to have users rate their level of satisfaction and describe their experience using website feedback . If the customers provide an email address, someone responds. “However,” Jack says, “even the anonymous feedback can be helpful.”

Doodle collects feedback from different types of users, segmenting the data according to each group. In particular, they want to know which product the respondents are using (e.g., MeetMe, Polls), whether they are the ones who created the poll or simply participated in it, and whether they’re using the paid version of the product.

DOODLE USES HOTJAR FEEDBACK TO COLLECT FEEDBACK FROM USERS AT SCALE AND IN CONTEXT.

Product managers and product designers read the replies and look for patterns, but at the moment they don’t have a formal system in place to review this data.

Where Doodle did take a more organized approach to Voice-of-the-Customer feedback was when they redesigned their website in 2017. This was a complete redesign, going from a late-90s style to something much more modern, and they used Hotjar Feedback to figure out what their users liked, disliked, and needed.

Categorizing projects according to goals

Once they submit ideas, Doodle’s project teams categorize each one based on the goals they want to achieve, and those goals are grouped into Objectives and Key Results (OKRs). OKRs, in short, describe big-picture objectives, such as “convert more users after the trial ends.” To learn more about organizing by OKRs, take a look at  this article   by   Jeff Gothelf  (the author of  Lean UX , mentioned above).

DOODLE USES OBJECTIVES AND KEY RESULTS (OKRS) TO MEASURE THEIR PROJECTS.

Doodle uses OKRs to identify their larger goals. Then they break their OKRs down by Objectives and Key Results, which identify the smaller goals that will hopefully help them achieve their Objectives. For example, the “convert more users after the trial period ends” Objective might be achieved by encouraging users to create more polls since Doodle’s research shows that users who create polls are more likely to convert.

Therefore, “get users to create a poll during the trial period” could become a Key Result, and that KR would fall under the “convert more users” Objective.

AN EXAMPLE OF AN OBJECTIVE (CONVERT MORE USERS) AND KEY RESULTS ATTACHED TO IT.

As the team captures more ideas, they tag them according to the appropriate OKR. Then, when they discuss plans for reaching those goals, they can use Airtable to filter the results, only showing those that relate to certain Objectives and Key Results.

Idea generation and problem-solving: a tale of two meetings

In the beginning, the product teams would brainstorm new ideas  and  discuss the progress they’d made on current projects at one meeting, but that got confusing.

These days, they have two separate meetings: one for brainstorming and generating new ideas (monthly), and the other. for discussing their progress on current projects (weekly).

“To get a balance there, we have two different versions of the same meeting. One is weekly, where we go through the stuff we're working on, making sure that it's progressing. And then there’s a separate meeting where we generate ideas and talk about what we want to do next.”

Step 2: the make phase at Doodle

In the make phase, a team of designers and developers builds a new feature to address previously highlighted problems and/or improve the product. But when ideas abound, as is likely to be the case, a crucial step is choosing  what  to build first.

How Doodle prioritizes projects

During the monthly meetings, whoever owns or champions an idea gives a 60-second talk about the idea, the data related to it, and how they might approach it as an improvement project. After the team reviews all new ideas they take a vote, pick the two or three most promising ideas, set deliverables, and really dive into them. The best ideas get added to the list of active projects.

The ICE framework

Doodle uses a system called ICE, designed by Sean Ellis. ICE stands for Impact, Certainty, and Effort, and potential projects are evaluated on these qualities. Here’s what the ideal project would look like in the ICE model:

Impact (on User Experience) : High

Certainty (whether it will work) : High

Effort (what it would take to make the change and test it) : Low

Of course, most projects aren’t so straightforward.  Jack says, “There are ones where you say, ‘Look, the effort is significant. We think the impact is high, but we're not completely sure.’ In that case, before we spend that full effort, we see if there’s something simpler we can work on.”

Jack stressed that they don’t take anything for granted when they assess certainty. If the idea’s champion thinks it’s a great project to work on, that counts for .01 on a certainty scale of 0 to 10. If the stakeholders love the idea and think it’s brilliant, that might bump you up another 0.1, but you’re still a long way from a 1, much less a 10.

THE DOODLE TEAM PRIORITIZES IDEAS USING THE ICE FRAMEWORK.

“What I really like about this approach,” he concludes, “is that it pushes us to do the necessary things to validate our ideas.” Whether it’s asking very specific questions to customers, bringing out specific data, or doing more A/B tests (see below), this framework allows Jack and his teams to save a lot of time down the line and make sure that all the work they are doing counts. That said, the ICE model isn’t a rigid scoring system. It’s a simple tool that gives you a rough idea of what to prioritize.

Curious to see how Hotjar prioritizes projects? Check out  Mastering the art of prioritization: how Hotjar decides what to work on next .

Step 3: the check phase at Doodle

Lean UX doesn’t rely on gut feel to decide whether a change has been successful, and neither does Jack Berglund. The teams at Doodle test their changes to see how users respond and later refine their approach accordingly.

If you have a lot of traffic to your website,  A/B tests (or split tests)  are a great way to validate your hypotheses scientifically and determine if the changes you made are working. Once you’ve got that result, you can go ahead and implement the changes confidently.

“We have a good amount of traffic, so we can do a lot of A/B testing. And if we're smart about the tests we run, we can save ourselves a lot of time by not implementing things that are basically low confidence,” says Jack.

Example #1: An 800% increase in the use of a feature

Sometimes the results can be surprising—like, “an eight-fold increase in feature use” surprising. When users create a poll, which they send to meeting invitees to determine which date works best for everyone, they can add a “Yes, if need be” option. This allows invitees to select their preferred date (the green checkmark) along with any dates that are less-than-ideal but would still work (the yellow checkmark).

Originally, this was an advanced option, meaning that it didn’t pop up in the 'Make a Poll' wizard that the average user sees. The product team assumed most users wouldn’t be interested in that feature, but they questioned their assumptions and tested it out by adding it to the wizard as a checkbox.

The result? They saw an 800% increase in the use of that feature. Who knew?

Example #2: The fake door that got them nowhere

Jack shared this with me as a cautionary tale—the story of a time they set out to study a problem with A/B testing but ended up studying the wrong thing. They didn’t get the information they needed to move to the next steps, but they learned a valuable lesson.

Doodle wanted to see whether having a 'Poll Deadline' button, which allowed poll creators to set a deadline for respondents to reply, would get any traction. They set up a  fake door , which is a button that offers a feature that isn’t actually available, so the UX team can see whether people will use it before spending the time and money to develop it. When users click on a fake door, they receive a message telling them: “Sorry! This feature is not yet available.”

Doodle showed the fake door to a portion of their users, and people clicked, but the team soon realized they had no way of knowing  how  useful the feature would be to their clients. Sure, they got plenty of clicks… but was the button valuable enough to influence buying behavior? Would it increase conversions? They couldn't tell from this A/B test.

To answer that question, Doodle went back to the drawing board. They’re currently planning to run a test that measures how likely this feature is to influence a user’s decision to start a free trial, which is a more complicated and business-focused question than whether or not a user will click.

“The core lesson is that we need to measure behavior change that demonstrates real value to the user.”

By designing smart, strategic A/B tests that answer basic questions about buying behavior, the teams at Doodle can prioritize their tasks and focus on those that offer a greater return.

Starbucks tests

It’s not always practical to do A/B testing, even when you have a ton of traffic, because sometimes you need to move quickly to see if an idea is worth looking into at all. You can always do more structured testing later if an idea shows promise after ‘guerilla testing’ it (an idea that Jeff Gothelf introduces in  Lean UX ).

Guerilla tests are ‘quick and dirty’ user tests that give you a sense of how your ideal users  might  respond. Much like focus groups, which advertising agencies have been using for more than 70 years, guerilla testing gives you quick feedback when you need it.

Since Doodle has 250 million users (that’s the population of Indonesia, by the way), and since many of these users are similar to people the Doodle team members rub shoulders with at their local Starbucks, they like to use Starbucks for guerilla testing new features. They go down to the Starbucks near their office and offer people a voucher for a free cup of coffee to test out new features.

“If you ever want to try to get a Starbucks voucher for a free cup of coffee, just hang out at the Starbucks near the Doodle office in Zurich. You never know!”

Starbucks testing is just one form of anecdotal feedback they use. Doodle also goes to customers, employees (including marketers), and product management stakeholders to get their input.

The guerrilla testing approach of Lean UX works better for SaaS and eCommerce than it does for companies that build physical products because, again, you can make changes quickly and reverse them if they don’t work. And in many ways, that points to the basic difference between Lean Manufacturing and Lean UX.

Lean UX is all about agility, experimentation, testing, and reassessing in a continuous cycle. It has allowed companies like Doodle to scale to 250 million active users—and it’s helped them thrive in a competitive market.

Lean UX in Action:  Doodle had the 'Settings' page automatically appear as the third step in their poll creation wizard, which increased the number of free trial signups by 25%, boosted the use of their 'Ask Attendees for Contact Information' option by 300%, and increased the use of the 'Hidden Polls' feature (which allows the creator to keep poll results hidden) by 400%.

If you were inspired by Jack's story or simply want to give Lean UX a try in your own business, here is a simple 3-step roadmap to get started:

Step 1: think phase

Gather customer feedback using tools like Feedback from Hotjar and reviewing insights from your Customer Success or sales team.

Process this info in an idea bank using a simple spreadsheet or a tool like Airtable.

Step 2: make phase

3.  Set up a meeting to prioritize projects according to their Impact, Certainty, and Effort  (keeping in mind that certainty is determined by facts, not stakeholder opinions).

Step 3: check phase

4.  Use guerilla testing  to get quick feedback where appropriate.

5.  Use A/B testing , if your traffic is large enough, to get scientifically valid results.

FAQs about lean UX

What is agile and lean ux.

Agile and lean UX involves applying the principles of these methodologies to the sphere of UX. Agile and lean both focus on creating quick iterations of products and features, testing them with users, and creating a tight feedback loop between users and product teams as they iterate in the future.

What are the benefits of lean UX?

Applying the lean methodology to UX creates a user-centered approach that forces product teams to rapidly generate and test ideas in the real-world to find what works. This prototyping model speeds up the  UX design  process, minimizes waste, and grounds it in the perspectives and experiences of real users.

What is an example of lean UX?

Online scheduling tool Doodle uses the lean UX approach to generate a backlog of ideas for new features or improvements. It then prioritizes the ideas that are estimated to have the most impact, and then conducts sprints where product & design teams create iterations that are A/B tested with users. During these prototyping tests, the product team observes how users interact with the new features and determines which ones they actually use and find helpful. They then repeat this process indefinitely to continuously improve the product.

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Applying lean methodology to curriculum revision and internship placement process – a case study

Journal of Research in Innovative Teaching & Learning

ISSN : 2397-7604

Article publication date: 27 April 2020

Issue publication date: 12 July 2021

The purpose of this paper is to study, examine and apply lean management principles to the curriculum revision and internship placement process in an academic program at an institution of higher education.

Design/methodology/approach

This paper consists of two sections. The first section reviews the literature on lean principles, lean tools, nonvalue-added activities and the application of lean methodology to academic settings. The second section presents a case study, where a team of faculty members applied lean principles to the process of curriculum revision and internship placement at an academic institution.

Lean principles can be successfully applied to curricular revision and the internship placement process. By applying the concepts of value, identification of value stream, removal of wasteful activities to achieve flow and creation of a pull-based system, faculty and program leaders can streamline processes at academic institutions. Furthermore, ongoing data collection helps to foster the culture of continuous improvement and ensure that processes are revisited and adapted to meet the needs of customers.

Practical implications

This paper is of value to faculty members and college administrators interested in applying lean principles to academic processes. Usage of lean methodology may lead to the identification and elimination of waste in curriculum and the field placement process.

Originality/value

This manuscript can provide a structure for the application of lean in academic processes at institutions of higher education.

• Lean management
• Internship placement
• Value stream

Singh, J. (2021), "Applying lean methodology to curriculum revision and internship placement process – a case study", Journal of Research in Innovative Teaching & Learning , Vol. 14 No. 2, pp. 288-305. https://doi.org/10.1108/JRIT-05-2019-0055

Emerald Publishing Limited

Copyright © 2020, Jitendra Singh

Published in Journal of Research in Innovative Teaching & Learning . Published by Emerald Publishing Limited. This article is published under the Creative Commons Attribution (CC BY 4.0) licence. Anyone may reproduce, distribute, translate and create derivative works of this article (for both commercial and non-commercial purposes), subject to full attribution to the original publication and authors. The full terms of this licence may be seen at http://creativecommons.org/licences/by/4.0/legalcode

In the rapidly changing world of health care management, students are looking for high quality academic programs that would help them to enhance their skill set to lead and manage increasingly complex health organizations. The students working in the field of health care management hold highly responsible positions as they have to make important decisions about the delivery of health care services. They have an obligation to provide high quality, safe and efficient care to patients and the communities they serve ( Parand et al. , 2019 ). The duties of health administration students, once they join the workforce, include but are not limited to management of a hospital/senior care facility; various departments, such as emergency departments and care units and other key areas in a health care organization. These individuals are also involved with policy initiatives, new program planning and the smooth running of operations in a health care entity. A firm understanding of health practices, evidence-based methods and the changing health care environment enables health managers to redesign and build a safer health care system for patients [1] .

Growth in the elderly population, scarcity of resources, technological advancements and illness trends require administrators to constantly think about innovative ways they can deliver what is most value-added to their customers. Health care policies, reimbursement methods, treatment options and everything in between is constantly changing [2] . Thus, it is extremely important to build a high quality, organized educational program so that students can get exposed to a variety of topics/subject areas in the field of health administration. Once admitted to the health administration program, students must be exposed to different fields so they can develop the skill set required to work in a high-paced environment. More specifically, students should learn about health care delivery, business practices to run health care organizations and the political environment that impacts decision-making and planning on a regular basis. Professionals in the field of health administration should have sound knowledge of leadership skills, financial methods, privacy laws surrounding patient care processes and other important practices [1] [2] .

Because of ongoing changes in the field of health care, it is important to make revisions and updates to the existing curriculum and course offerings. Curriculum development and revision are not only important from a quality improvement perspective they also allow students to learn the most current concepts in the field of health care. Furthermore, a regular review of the curriculum and teaching methods can help to ensure that courses remain applicable and current in times of rapid change [3] . This will also appeal to students as these revisions/updates will help them prepare for future employment in the field of health care administration. From a faculty standpoint, however, curricular revision means labor intensive activities, such as program review, data collection, changes to existing curricula, new sets of reports and additional meetings. Faculty members who play an important role in revising curricula may not get enough time to engage in scholarly activities and research projects. It is also important to note that university leadership may not take such duties into account when important decisions regarding tenure and promotion are made ( Collins, 1997 ).

Health care environment is ever-changing. Cost, quality and access continue to create challenging situation for the practice of health care delivery. Recent research suggests that academic settings still emphasize isolated topics rather than interprofessional team-based approach that encourages students to build skill set needed to practice in real world health care setting. Furthermore, there is evidence suggesting top leadership in health care organizations have consistently expressed dissatisfaction with traditional health administration programs at academic settings. Leaders have expressed need for health administrators who are able to work with diverse teams and are equipped with problem-solving skills ( Frenk et al. , 2010 ; Herzlinger et al. , 2015 ).

Having worked in academia and lean health care for several years, this author believes that the curriculum revision process may appear to be a daunting task to faculty members. This can be even more challenging for faculty members who are new to academia. However, the adoption of a process-oriented approach, such as lean methodology, may help simplify the entire project. The usage of lean principles also enables programs to implement a culture of continuous improvement in ongoing activities on a more regular basis. While many academic institutions have successfully implemented various administrative processes ( Balzer, 2016 ; Krehbiel et al. , 2015 ; McKinney, 2017 ; Wilson, 2011 ), there is still a paucity of research that shows lean principles can be successfully applied to curricular revision and other academic processes in programs at institutions of higher education. This paper presents the case of a health administration program at a public university in Minnesota, United States, where lean methodology was utilized to improve and streamline curriculum and the internship placement process in an academic program.

Because there is still a scarcity of research on the application of lean principles to the processes/activities noted above, this research can have wide practical applications. Usage of lean principles may allow faculty to examine current programs, existing data collection and the reporting process and support mechanisms available at academic institutions to support programs and students. The dissemination of findings can also help program directors, department chairs and faculty members as they plan for program review and accreditation.

Lean philosophy and principles

Lean is a customer-driven approach that emphasizes waste reduction and continuous process improvement. Organizations eliminate waste inherent in work processes by applying five lean principles as follows: defining value from the customer's perspective, identifying value streams, eliminating unnecessary activities (flow), applying pull and perfection ( Womack and Jones, 2003 ).

Defining value from the end user's perspective is a very important critical starting point for lean thinking. Organizations that create product would like to learn about their customer and what that customer would want from the product. Emiliani (2004) indicated that the customer is someone who is using and paying for the services/products they have purchased. Evidence also suggests the customer would only like to pay for activities/products that add value to them. Thus, nonvalue-added activities should be eliminated [4] .

The second principle involves mapping the value stream to achieve value as identified by the customers. Creation of a value stream map requires process owners or stakeholders to investigate their processes and identify/uncover waste in the system. Once waste has been uncovered, it is important to examine current/existing practices that do not add value to the overall process [9] . The third lean principle, flow, allows one to see how the work is progressing through a system. Efforts should be made to remove nonvalue-added activities/work identified during value stream mapping to create products that meet or exceed the customer's expectations. Furthermore, team members or individuals who have a role in the process should be given a chance to look at existing processes and identify bottlenecks or activities that create barriers to producing what customers want from the process [9] . Once team members recognize the importance of removing waste in the process, they will participate in process improvement activities more proactively [4] .

The fourth lean principle, pull, highlights the importance of customer pull. More specifically, goods or products should only be produced if the customer asks for them. This will allow manufacturers to practice the pull approach, rather than pushing previously manufactured product onto customers. Process owners and manufacturers should make efforts related to what the customer actually wants from the process before creating products for them ( Pinkney et al. , 2016 ). The fifth lean principle, perfection, requires key stakeholders to consider ongoing assessment activities to further improve processes. Identification and use of metrics allow individuals to focus on continuous improvement activities with suggestions so lean becomes a “cultural way of life” ( Pinkney et al. , 2016 ).

Lean tools, also known as lean building blocks, can help to reduce waste/nonvalue-added activities to the process. Usage of these tools helps to identify waste and time spent on activities that do not add value (redundant activities), which, in turn, results in identification of methods to improve workflow, processes, enhance productivity and reduce costs. Usage of these tools helps to reduce administrative expenses, streamline processes and enhance workforce participation in day-to-day activities ( Gupta et al. , 2014 ; Singh et al. , 2010 ). Table 1 briefly describes lean building blocks and how they can be used to improve current processes.

Lean wastes

According to lean methodology, there are seven types of waste. Under the lean approach, waste can be defined as all the nonvalue-added activities or steps in the process that have an adverse impact on quality, add to wait times and add to cost of the final product ( Ahmed-Soliman, 2017 ). Table 2 illustrates seven lean wastes that should be minimized as a result of process improvement activities ( Ahmed-Soliman, 2017 ; Kang and Manyonge, 2014 ).

Application of lean principles

Lean methodology has been successfully applied across a variety of industries. More specifically, organizations, such as Taco Bell, Southwest Airlines, Virginia Mason Medical Center (VMMC), Thedacare, Walmart and educational institutions have applied lean principles to improve quality, efficiency and the flow of services to customers ( Leite and Vieira, 2015 ).

Lean principles require organizations to think about what customers want, where they want the services, potential wait times and how to solve problems in case there are problems with the products/services being delivered. For example, shopping centers open stores so that customers can easily reach out to them. Several food chains and airline companies have implemented lean principles to improve their customer processes. Furthermore, adoption of lean practices at health care organizations has led to the elimination of medical errors, reduction in wait times and significant cost savings ( Leite and Vieira, 2015 ). Evidence suggests that the application of lean principles have allowed VMMC to save $2m in construction costs and successfully eliminate waiting times for patients [5] . Another health care system, Thedacare, saved an amount equal to 5% of their annual revenue and doubled the operating margin within three years of lean implementation ( Toussaint, 2009 ).

As noted above, the application of lean principles across different industries shows promising results. Kang and Manyonge (2014) reported data that showed the implementation of lean methodology could improve productivity, enhance flow, reduce mistakes and decrease waiting times for customers. Evidence also suggests that all the processes can be improved, and approximately 80% of the steps in any given process are unnecessary. Careful examination of the process and defining what the customer needs from the process efforts can be made to identify and eliminate wasteful activities. The higher education system is full of processes. Lean methodology can be applied in higher education settings to improve current practices, create flow, reduce variation and reduce unnecessary delays ( Ziskovsky and Ziskovsky, 2007 ). Table 3 highlights cases of successful lean implementation in administrative processes at academic institutions.

Description of health administration program

In 1995, the original Health Services Administration (HSAD) program was developed to meet the need for health administration education in Minnesota and North Dakota, United States. The program serves a variety of students, including traditional students seeking a four-year undergraduate degree, students who plan to take the Nursing Home Administrator (NHA) examination in Minnesota and North Dakota and practice and students interested in gaining knowledge of a broad field of health services administration [7] . The program offers a curriculum focused on health care issues, including specialized health management courses. Elective courses allow the students to specialize in a variety of health care delivery fields, such as acute care management, long-term care, public health management and community health initiatives. In order to graduate from the program, students are required to complete a practicum/internship in a health care facility. While students specializing in the field of long-term care administration have to complete 1,000h of internship in a skilled nursing facility, other students only need 240h of practical experience at a health care organization.

The HSAD program received the initial BENHA, MN accreditation in 2005 for a period of 10 years. In these 10 years, faculty turnover and lack of leadership created a huge void in the program. These problems also contributed to a decline in the number of students in the program. In 2015, a new faculty member was hired to serve as a full-time faculty and coordinator/director of the program. Upon hire, one of the first tasks the program director undertook was the extensive review of curriculum, instruction and assessment activities within the program. Because of an extensive background in lean methodology, the program director utilized lean principles to streamline and update these processes in the program.

Methodology – how lean principles were integrated

Defining value from a customer's perspective is the starting point in the lean journey. Emiliani (2004) indicated that the customer is someone who uses and pays for the services/products he/she has purchased. It is important to collect the customer's feedback and pay attention to the voice of the customer as it can help to enhance products or services provided by the organization. At academic institutions, students and employers can be considered customers. While students are considered direct customers, it is also important to understand value from the employer's perspective as they hire students/graduates from these educational programs. Furthermore, many employers also provide tuition assistance ( Emiliani, 2004 ) or have other employee assistance programs in place to offset the cost of tuition. This author feels that accreditation bodies and their requirements are also taken into consideration when any program level changes are made. Accreditation brings a gold seal of approval to any academic program, and evidence suggests that students give preference to accredited programs when they select programs to further their education [1] .

In an effort to answer the question, “What do our customers want from a health administration program at the university,” faculty adopted a three-fold approach. After consulting with college and school leadership, faculty established an employer advisory board and student and alumni council. Furthermore, the program director also met with representatives from the accreditation body to understand the new accreditation requirements. Figure 1 highlights customers of the program.

Formation of an employer advisory board

Faculty members in the health administration program reached out to major health care employers in Minnesota and North Dakota and invited them to serve on the community advisory board. Approximately 15 representatives from a variety of health care organizations agreed to serve on this board. Board meetings were organized regularly to obtain feedback on program curriculum and coursedelivery methods. This committee examined the curriculum and helped to make much needed changes to the program. The need to include additional classes and/or content in areas related to process improvement, quality improvement, interprofessional education, leadership and research methods was highlighted. In addition, members of the advisory board highlighted the need to include activities/assignments in classes so that students can improve their verbal and written communication skills. The importance of teamwork and collaboration in health care was also highlighted.

Meeting with the accreditation body

The program director arranged several meetings with members of the accreditation body to ensure that the requirements are correctly understood. The Board of Examiners of Nursing Home Administrators (BENHA) requires accredited programs to maintain a high standard in education and experiential preparation of administrators who wish to serve in a senior-care setting. The curriculum of the accredited program should provide adequate coverage of organizational management, managerial accounting, gerontology, health care and medical needs, long-term care support and services, human resources, regulatory management and quality measurement and performance improvement. Furthermore, accredited programs needed to include 1,000h of practicum/internship experience within the academic program structure. It is important to note that these requirements, both coursework and internship, were significantly different from the time the program received initial approval from BENHA. These meetings helped the program director understand the concept of “value” from the accreditation body's standpoint.

Formation of a student and alumni advisory council

In order to collect students' feedback on current curriculum, a team consisting of current students and graduates of the programs was constituted. This team met on a regular basis (twice a year) and provided feedback on curriculum in the program. More specifically, this committee provided feedback on content, course delivery methods and skills/knowledge that were considered essential to function in a health care environment. The need for more online classes was indicated to accommodate the need for working professionals who may not have the time to come to a college campus to attend classes. In addition, the students indicated that the internship placement process needs to be streamlined as the current process is unclear and leads to confusion among students.

Once the value had been identified, second and third step typically requires a thorough examination of the existing process to find waste in the current system. Examination of the process helps people see the flow of the process from beginning to end and better understand areas where waste may exist ( Kim et al. , 2006 ). After collecting feedback from employers, students, alumni and the accreditation body, the program director summarized all the information and made a presentation to the school and college leadership. Faculty members who had a major role in the program were also invited to the presentation. This presentation allowed the leadership and faculty members to see that a gap existed in the current curriculum and that efforts should be made to further improve the program by making necessary changes. It is noteworthy that both the faculty members and leadership felt that changes to the program would not only help to secure accreditation but also help with improving curriculum and course delivery methods.

Formation of a faculty committee

A program council comprising faculty members in the undergraduate health administration program, graduate health administration program and adjunct faculty members was constituted. It is important to note that faculty members in the health administration programs had prior experience working in health care leadership roles at a variety of health care settings. The team met to reevaluate the entire curriculum based on feedback received from the accreditation body, employee advisory board, student and alumni advisory board.

A document called a current program map was created by the faculty members and advisors to make the structure of the current program visible to all the team members. Another document that described content of all the courses in the program was created to make sure that the faculty team was able to look at courses during committee meetings. Efforts were made to include course sequencing, as well, so that team members were able to see classes the students took from the beginning to the end in the program. These documents served as a powerful tool that allowed team members to see the actual value stream and recognize waste in the current process.

The team also identified coursework/classes that have become irrelevant or obsolete due to the ever-changing nature of the field. Furthermore, the team also identified nonvalue-added activities in the internship placement process that led to dissatisfaction from students and preceptors. Lack of a process-centered approach resulted in unclear expectations, unnecessary motion and other wasteful activities in the process. Figure 2 highlights the Fishbone analysis completed by the faculty.

Table 4 below highlights issues/problems/waste in the program (as identified by faculty members).

The team then brainstormed ideas for improvement and proposed changes to the curriculum to eliminate waste from the existing program. By including feedback provided by the advisory boards and accreditation bodies, a complete new set of classes were proposed. Once changes were identified, efforts were made to prepare the future state curriculum for the program. The entire program curriculum was revised to meet the new accreditation requirements. The revised program provided adequate coverage for all the core areas required by BENHA. In addition, the revised program also provided in-depth coverage of US health care, population/community health, organizational development, issues related to cultural competency in health care, operation assessment and improvement, health informatics, health care law, policy, economics, postacute care, health care finance, marketing and ethics in business clinical decision-making. These changes were made to include the most recent and updated curriculum in the field of health administration. Table 5 presents changes that were made to include customers' feedback.

Using the pull system for online classes

In accordance with undergraduate education standards, students are required to complete 120 credit hours at institutions of higher education. Liberal arts and sciences are an integral component of education and must be completed in order to graduate from baccalaureate degree programs. Out of the 120 credit hours students have to complete, 42 credit hours are required in areas related to communication, natural science, mathematics, social sciences and humanities [8] . While evaluating the program curriculum, the faculty committee selected several online options that students could take in case they did not want to attend on-campus classes. Furthermore, the committee started to examine technology tools to begin exploring online and/or hybrid course offerings for online health administration classes. Efforts were made to ensure that the advisors were aware of the online options as they helped students select course options during the registration process. The new process was implemented based on the concept of the pull system in lean. This new system allowed faculty to select classes based on actual demand by students who want to register for online classes. Rather than working with a list of predetermined classes, faculty members were able to implement the just-in-time (JIT) approach for students. This helped to produce a list of classes based on actual demand, rather than working with anticipated demand. Figure 3 highlights the Pull-based System for Online Classes.

Pull system for internship placement

New internship approach.

The Health Services Administration program offers students several internship options. The program also works with several health care organizations so that students can complete their internship at these sites. Students who wish to work in health care settings other than skilled nursing facilities needed to complete 240 internship hours. On the other hand, students interested in earning their license to practice as the administrator of a skilled nursing facility need to complete 1,000 internship hours. It is also important to note that these students have to complete specific requirements outlined by the NHA licensure board, in addition to undergraduate program requirements by the university. Initially, the internship coordinator met with students during advising sessions and provided them with information about the different types of program internships. Students received “too much” information in a limited timeframe. Because of the different requirements, this information session often led to confusion and dissatisfaction among the students. Lack of communication between faculty and the internship preceptor often led to multiple phone calls, prolonged wait times and excess motion. The faculty team adopted a pull-based approach to streamline the internship placement process. Rather than provide internship information to students during advising sessions, usage of the pull-based system allowed faculty members to achieve a higher level of work flow efficiency in the internship placement process. Figure 4 highlights the pull-based system for the internship placement process.

Preinternship class and new internship website

Emiliani (2016) indicated that faculty creates class modules based on the concept that they possess the “best solution” to the problem presented to them by students and prepare the teaching modules using the material they think students should learn. Usage of the pull system allows instructors to build a class platform based on students' needs. Creation of a supermarket in learning management helps instructors implement the pull-based system ( Emiliani, 2016 ).

Instructors utilized the concept of pull and supermarket while creating the preinternship class. Content related to the different types of internships, expectations from students, the role of instructors during the internship and process background checks that should be completed prior to beginning the internship experience were included in the learning management system. The students were required to review the material and pull information from this supermarket based on their needs. For example, if a student is interested in completing an internship at a skilled nursing facility for a nursing home administration license, she/he can pull information related to the internship from this supermarket. Students were given five weeks to examine the course material and identify questions they wanted to ask the instructor. On-campus and online meetings with students were held after five weeks to answer questions they had about their internship at a health care facility. In addition, the internship website was created, and incoming/new students were directed to the website in case they had questions about internship requirements. Figure 5 highlights the pull-based system for the preinternship class.

The fifth and final step in lean implementation requires consistent effort to pursue perfection so that lean thinking becomes part of the everyday culture. In order to sustain the changes that were made, a number of measurement strategies were implemented. A variety of assessment activities, such as a student program survey, exit survey, alumni survey, employer advisory board survey and faculty survey were included to continuously monitor the changes that were made. This allowed faculty members to pay attention to the voice of the customers and adopt a culture of continuous improvement.

This study’s goal was to describe how lean principles were utilized to revise the curriculum and internship placement process of the health administration program at an academic institution. A rapidly changing health care environment requires instructors to continuously evaluate and update their curriculum so students can learn the most current concepts and skills required to function in today's environment [1] [2] . Evidence suggests that lean methodology has been successfully applied across processes at a variety of institutions ( Balzer, 2016 ). Pusca and Northwood (2016) successfully implemented the lean methodology to improve course design, instruction methods and assessment methodology in engineering education. The application of lean principles to courses in business schools has resulted in improved quality and customer satisfaction ( Emiliani, 2004 ). However, there is a scarcity of research that shows lean principles can be successfully utilized to enhance curriculum and standardize the internship placement process for the health administration program. This case study shows how lean principles can be integrated to streamline the health administration curriculum, including the internship placement process. The main goal of education is to produce satisfied customers. In the case of an accredited program, these customers include students, current employers and future employers. Usage of lean methodology may lead to better processes and a value-added experience for students and other customers.

Recommendations for future work

The purpose of this paper was twofold. The first part of the paper examined recent literature in the field of lean management. The second part presented a case where lean principles are applied to curriculum revision and the internship placement process in a health administration program. Efforts should be made to apply lean principles in core academic processes, such as course planning, delivery of classes, earning academic accreditation and similar activities to reduce waste and avoid problems that lead to dissatisfaction among customers. As online education continue to grow, application of lean principles may result in streamlined processes and better system for students who may not be able to come to university campus for classes. Furthermore, this may also help in enhancing retention of students at academic settings. It is also important to examine issues surrounding lean implementation and training needs that faculty may have before they start applying this methodology in day-to-day processes at academic institutions. More data-driven (qualitative and quantitative) research projects should be conducted to add to the existing body of work in the field of education.

Beginning with an in-depth literature review on lean principles and the use of lean methodology in an academic setting, this paper presented the case of a health administration program where lean principles were implemented. The successful application of lean principles led to the identification of wasteful activities and elements in the curriculum and the internship placement process. A new streamlined approach based on the pull system has been presented. By continuously focusing on the reduction of nonvalue-added steps, lean can create a win-win situation for students, instructors, employers and administrators at institutions of higher education. Furthermore, the lean philosophy, when correctly applied to core academic processes, may lead to the reduction or elimination of issues that lead to dissatisfaction among customers. As academic institutions work toward expanding online course offerings, application of lean methodology may help in creating better systems for students. The information and tools included in this paper will allow instructors and academic administrators to see how lean principles can be applied to improve the quality of curriculum and standardize existing processes.

Value - customers

Fishbone analysis

Pull-based system

Pull-based internship process

Pull-based supermarket system – pre-internship class

Lean approach in the administrative processes at academic settings

Waste in the health administration program

Changes made based on customer's feedback

https://www.healthcareadministrationdegrees.org/degrees/bachelors/ .

https://healthcaremba.gwu.edu/blog/how-we-can-expect-the-healthcare-industry-to-change-in-the-future/ .

https://www.jisc.ac.uk/guides/how-can-i-keep-the-curriculum-relevant-in-a-time-of-rapid-chang.e .

https://online.kettering.edu/news/2016/07/19/using-takt-time-and-cycle-time-your-advantage .

http://www.ihi.org/resources/Pages/ImprovementStories/.VirginiaMasonMedicalCenterImplementsLeanManagementPrinciplestoDriveOutWaste.aspx .

https://www.universities-scotland.ac.uk/wp-content/uploads/2016/02/Working-Smarter-2015-final-no-spreads.pdf .

https://www.mnstate.edu/health-services/ .

https://www.ohe.state.mn.us/pdf/baccalaureate.pdf .

https://www.asme.org/topics-resources/content/5-lean-principles-every-should-know .

Adnan , A.N.B. , Jaffar , A.B. , Yusoff , N. and Halim , N.H.B.A. ( 2013 ), “ Implementation of just-in-time production through Kanban system ”, Industrial Engineering Letters , Vol. 3 No. 6 , pp. 11 - 20 .

Aguilar-Escobar , V.G. , Bourque , S. and Godino-Gallego , N. ( 2015 ), “ Hospital kanban system implementation: evaluating satisfaction of nursing personnel ”, Investigaciones Europeas de Dirección y Economía de la Empresa , Vol. 21 No. 3 , pp. 101 - 110 .

Ahmed-Soliman , M.A. ( 2017 ), “ A comprehensive review of manufacturing wastes: Toyota production system Lean principle ”, Emirates Journal of Engineering Research , Vol. 22 No. 2 , pp. 1 - 10 .

Balzer , B. ( 2016 ), “ What is Lean higher education? ”, ODHE Efficiency Advisory Committee Meeting 2016 , available at: https://www.asme.org/engineering-topics/articles/manufacturing-design/5-lean-principles-every-should-know ( accessed 12 February 2019 ).

Collins , M. ( 1997 ), “ Issues of accreditation: a dean's perspective ”, Online Journal of Issues in Nursing , Vol. 2 No. 3 , available at: https://ojin.nursingworld.org/MainMenuCategories/ANAMarketplace/ANAPeriodicals/OJIN/TableofContents/Vol21997/No3Aug97/IssuesofAccreditationADeansPerspective.html ( accessed 15 January 2019 ).

Dighe , S.B. and Kakirde , A. ( 2014 ), “ Lean manufacturing implementation using value stream mapping: a case study of pumps manufacturing company ”, International Journal of Science and Research , Vol. 3 No. 6 , pp. 2492 - 2498 .

Emiliani , M.L. ( 2004 ), “ Improving business school courses by applying lean principles and practices ”, Quality Assurance in Education , Vol. 12 No. 4 , pp. 175 - 187 .

Emiliani , M.L. ( 2016 ), “ Evolution in lean teaching ”, International Journal of Productivity and Performance Management , available at: https://bobemiliani.com/wp-content/uploads/2016/09/elt_paper.pdf , ( accessed 18 March 2019 ).

Frenk , J. , Chen , L. , Bhutta , Z.A. , Cohen , J. , Crisp , N. , Evans , T. , Finberg , H. , Garcia , P. , Ke , Y. , Kelley , P. , Kistnasamy , B. , Meleis , A. , Naylor , D. , Pablos-Mendez , A. , Reddy , S. , Scrimshaw , S. , Sepulveda , J. , Serwadda , D. and Zurayk , H. ( 2010 ), “ Health professionals for a new century: transforming education to strengthen health systems in an interdependent world ”, Vol. 376 No. 9756 , pp. P1923 - P1958 .

Gupta , R.K. , Singh , M.P. and Sharma , L.K. ( 2014 ), “ Reduction of waste using value stream mapping: case study ”, International Journal of Research in Mechanical Engineering and Technology , Vol. 4 No. 2 , pp. 52 - 55 .

Herzlinger , R. , Kumar , V. , Schulman , K.A. and Staman , K. ( 2015 ), “ Innovation in health care education: a call to action ”, Health Affairs , available at: https://www.healthaffairs.org/do/10.1377/hblog20150129.044213/full/ ( accessed 5 February, 2019 ).

Kanamori , S. , Sow , S. , Castro , M.C. , Matsuno , R. , Tsuru , A. and Jimba , M. ( 2015 ), “ Implementation of 5S management method for lean healthcare at a health center in Senegal: a qualitative study of staff perception ”, Global Health Action , Vol. 8 No. 27256 , pp. 1 - 9 .

Kang , P.S. and Manyonge , L.M. ( 2014 ), “ Exploration of Lean principles in higher educational institutes – based on degree of implementation and indigence ”, International Journal of Scientific and Engineering Research , Vol. 5 No. 2 , pp. 831 - 838 .

Kim , C.S. , Spahlinger , D.A. , Kin , J.M. and Billi , J.E. ( 2006 ), “ Lean health care: what can hospitals learn from a world-class automaker? ”, Journal of Hospital Medicine , Vol. 1 No. 3 , pp. 191 - 199 .

Krehbiel , T.C. , Ryan , A.W. and Miller , D.P. ( 2015 ), “ Lean learning: university's challenges lead to $27.2 million in cost improvements ”, Quality Progress , Vol. 48 No. 2 , pp. 39 - 45 .

Leite , H.d.R. and Vieira , G.E. ( 2015 ), “ Lean philosophy and its applications in the service industry: a review of the current knowledge ”, Production , Vol. 25 No. 3 , pp. 529 - 541 .

McKinney , C. ( 2017 ), UI Wins Top Efficiency Awards from Lean Consortium , The University of Iowa , available at: https://now.uiowa.edu/2017/10/ui-wins-iowa-lean-consortium-awards , ( accessed 12 August 2018 ).

Parand , A. , Dopson , S. , Renz , A. and Vincent , C. ( 2019 ), “ The role of hospital managers in quality and patient safety: a systematic review ”, BMJ Open , Vol. 4 No. 9 , pp. 1 - 15 .

Pinkney , J. , Rance , S. , Benger , J. , Brant , H. , Joel-Edgar , S. , Swancutt , D. , Westlake , D. , Pearson , M. , Thomas , D. , Holme , I. , Endacott , R. , Anderson , R. , Allen , M. , Purdy , S. , Campbell , J. , Sheaff , R. and Byng , R. ( 2016 ), “ How can frontline expertise and new models of care best contribute to safely reducing avoidable acute admissions? A mixed-methods study of four acute hospitals ”, Health Services and Delivery Research , Vol. 4 No. 3 , available at: https://www.ncbi.nlm.nih.gov/books/NBK338859/pdf/Bookshelf_NBK338859.pdf ( accessed 20 March 2019 ).

Pusca , D. and Northwood , D. ( 2016 ), “ Can lean principles be applied to course design in engineering education? ”, Global Journal of Engineering Education , Vol. 18 No. 3 , pp. 173 - 179 .

Ronney , E. , Olfe , P. and Mazur , G. ( 2000 ), “ Gemba research in the Japanese cellular phone market ”, available at: http://www.mazur.net/works/nokia_gemba_research_in_japanese_cellular_market.pdf ( accessed 24 August 2018 ).

Singh , B. , Garg , S.K. , Sharma , S.K. and Grewal , C. ( 2010 ), “ Lean implementation and its benefits to production industry ”, International Journal of Lean Six Sigma , Vol. 1 No. 2 , pp. 157 - 168 .

Toussaint , J. ( 2009 ), “ Writing the new playbook for US health care: lessons from Wisconsin ”, Health Affairs , Vol. 28 No. 5 , pp. 1343 - 1350 .

Williams , P.M. ( 2001 ), “ Techniques for root cause analysis ”, Baylor University Medical Center Proceedings , Vol. 14 No. 2 , pp. 154 - 157 .

Wilson , T. ( 2011 ), “ UCO earns national innovation award for lean processes ”, available at: https://www3.uco.edu/press/prdetail.asp?NewsID=10849 , ( accessed 22 March 2018 ).

Womack , J.P. and Jones , D.T. ( 2003 ), Lean Thinking: Banish Waste and Create Wealth in Your Corporation , Simon and Schuster , New York, NY .

Ziskovsky , B. and Ziskovsky , J. ( 2007 ), “ Doing more with less – going lean in education ”, available at: https://www.lean.org/Search/Documents/398.pdf (accessed on 2 March) 2) .

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Integration of Lean Six Sigma with Internet of Things (IoT) for productivity improvement: a case study of contactor manufacturing industry

• CASE STUDIES
• Published: 04 July 2023
• Volume 14 , pages 1990–2018, ( 2023 )

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• Santosh B. Rane 1 ,
• Sandesh Wavhal 1 &
• Prathamesh R. Potdar   ORCID: orcid.org/0000-0001-8896-5322 2  

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In today's era of digitalization and competitive market environment, organizations are more focused on manufacturing quality products at optimum cost to capture maximum business as a variety of options are available to customers for purchasing goods and services. In this scenario, the latest technologies-based productivity improvement can help organizations to achieve set targets of production and ensure the quality of products. In this study, the contactor manufacturing industry has been considered to demonstrate integrated Lean Six Sigma with the Internet of Things (IoT) approach for productivity improvement. A systematic literature survey was performed to understand the concept of Lean Six Sigma (LSS), Define Measure Analysis Improve Control approach and IoT technology. The implementation of the LSS approach reduced the rejection rate of contactors and saved the total production cost (Rs. 51,88,260/-) annually. The annual consumption of grinding wheels has been reduced by 8 quantities to produce the same quantity of contactors. The surface quality of magnets has been identified as a root cause for contactor rejections as it contributes 53.4% of total rejections. The improvement measures are recommended based on the expert's suggestions as grinding wheel dressing must be performed after the completion of a batch of 20,000 parts. The condition monitoring and IoT approach implementation are done by monitoring grinding speed (650–950 RPM), grinding wheel thickness reduction by 0.4–0.6 mm after dressing and dressing of grinding wheel after completion of 20,000 for reducing rejections. This study concluded that industries should implement the Lean Six Sigma approach with the latest technologies and appropriate tools at each stage to set processes to world-class standards and industries should identify opportunities for process and product improvement.

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Abrol SA, Bhargava C, Sharma PK (2021) Reliability analysis and condition monitoring of polymer based dye sensitized solar cell: a DOE approach. Mater Res Express 8:045309. https://doi.org/10.1088/2053-1591/abf629

Article   Google Scholar  

Alaba FA, Othman M, Hashem IAT, Alotaibi F (2017) Internet of Things security: a survey. J Netw Comput Appl 88:10–28. https://doi.org/10.1016/j.jnca.2017.04.002

Ali SM, Hossen MdA, Mahtab Z, Kabir G, Paul SK, ulAdnan ZH (2020) Barriers to Lean Six Sigma implementation in the supply chain: An ISM model. Comput Ind Eng 149:106843. https://doi.org/10.1016/j.cie.2020.106843

Alimohammadlou M, Mohammadi S (2016) Evaluating the productivity using malmquist index based on double frontiers data. Proced Soc Behav Sci 230:58–66. https://doi.org/10.1016/j.sbspro.2016.09.008

Antony J (2012) A SWOT analysis on six sigma: some perspectives from leading academics and practitioners. Int J Product Perform Manag 61:691–698. https://doi.org/10.1108/17410401211249229

Arias Velásquez RM (2020) Root cause analysis for inverters in solar photo-voltaic plants. Eng Fail Anal 118:104856. https://doi.org/10.1016/j.engfailanal.2020.104856

Arias Velásquez RM, Mejía Lara JV (2020) Root cause analysis improved with machine learning for failure analysis in power transformers. Eng Fail Anal 115:104684. https://doi.org/10.1016/j.engfailanal.2020.104684

Arias Velásquez RM, Mejía Lara JV (2020) Root cause analysis methodology for circuit breaker associated to GIS. Eng Fail Anal 115:104680. https://doi.org/10.1016/j.engfailanal.2020.104680

Bahari Z, Elgadi M, Rivet J, Dugué J (2009) Experimental study of the ternary Ag–Cu–In phase diagram. J Alloy Compd 477:152–165. https://doi.org/10.1016/j.jallcom.2008.10.030

Barot RS, Patel J, Sharma B, Rathod B, Solanki H, Patel Y (2020) Lean Six Sigma feasibility and implementation aspect in cast iron foundry. Mater Today Proc 28:1084–1091. https://doi.org/10.1016/j.matpr.2020.01.087

Belhadi A, Kamble SS, Zkik K, Cherrafi A, Touriki FE (2020) The integrated effect of big data analytics, Lean Six Sigma and green manufacturing on the environmental performance of manufacturing companies: the case of North Africa. J Clean Prod 252:119903. https://doi.org/10.1016/j.jclepro.2019.119903

Bidikar SG, Rane SB, Potdar PR (2022) Product development using design for six sigma approach: case study in switchgear industry. Int J Syst Assur Eng Manag 13:203–230. https://doi.org/10.1007/s13198-021-01199-4

Boutora S, Bentarzi H (2019) Ferroresonance study using false trip root cause analysis. Energy Proced Emerg Renew Energy Gener Autom 162:306–314. https://doi.org/10.1016/j.egypro.2019.04.032

Broder JS, Al-Jarani B, Lanan B, Brooks K (2020) Pigtail catheter insertion error: root cause analysis and recommendations for patient safety. J Emerg Med 58:464–472. https://doi.org/10.1016/j.jemermed.2019.10.003

Caro Teller JM, Pablos Bravo S, Serrano Garrote O, Ojeda García C, Carro Ruiz AM, Guede González AM, Ferrari Piquero JM (2020) Implementación Lean Six Sigma en la mejora del circuito de dispensación de medicación. J Healthc Qual Res 35:364–371. https://doi.org/10.1016/j.jhqr.2020.04.005

Chang DS, Kuo YC, Chen TY (2008) Productivity measurement of the manufacturing process for outsourcing decisions: the case of a Taiwanese printed circuit board manufacturer. Int J Prod Res 46:6981–6995. https://doi.org/10.1080/00207540701429934

Chaudhari SS, Bhole KS, Rane S (2023a) Comparison on conventional and digital technology assisted design methodologies of process heater radiant section. Int J Interact Des Manuf. https://doi.org/10.1007/s12008-023-01201-2

Chaudhari SS, Bhole KS, Rane S (2023b) An application of IIoT framework in system design, performance monitoring and control for industrial process heater. Int J Interact Des Manuf. https://doi.org/10.1007/s12008-023-01235-6

Cheah CK, Prakash J, Ong KS (2020) Overall equipment effectiveness: a review and development of an integrated improvement framework. IJPQM 30:46–71. https://doi.org/10.1504/IJPQM.2020.107240

Chi C-F, Sigmund D, Astardi MO (2020) Classification scheme for root cause and failure modes and effects analysis (FMEA) of passenger vehicle recalls. Reliab Eng Syst Saf 200:106929. https://doi.org/10.1016/j.ress.2020.106929

Costa LBM, Godinho Filho M, Fredendall LD, Gómez Paredes FJ (2018) Lean, six sigma and Lean Six Sigma in the food industry: a systematic literature review. Trends Food Sci Technol 82:122–133. https://doi.org/10.1016/j.tifs.2018.10.002

Costa LBM, Godinho Filho M, Fredendall LD, Ganga GMD (2020) The effect of Lean Six Sigma practices on food industry performance: Implications of the Sector’s experience and typical characteristics. Food Control 112:107110. https://doi.org/10.1016/j.foodcont.2020.107110

Costa LBM, Godinho Filho M, Fredendall LD, Devós Ganga GM (2021) Lean Six Sigma in the food industry: construct development and measurement validation. Int J Prod Econ 231:107843. https://doi.org/10.1016/j.ijpe.2020.107843

Dandage R, Mantha SS, Rane SB (2018a) Ranking the risk categories in international projects using the TOPSIS method. Int J Manag Proj Bus 11:317–331. https://doi.org/10.1108/IJMPB-06-2017-0070

Dandage RV, Mantha SS, Rane SB, Bhoola V (2018b) Analysis of interactions among barriers in project risk management. J Ind Eng Int 14:153–169. https://doi.org/10.1007/s40092-017-0215-9

Dandage RV, Mantha SS, Rane SB (2019) Strategy development using TOWS matrix for international project risk management based on prioritization of risk categories. Int J Manag Proj Bus 12:1003–1029. https://doi.org/10.1108/IJMPB-07-2018-0128

Darmawan MA, Putra MP, Wiguna B (2014) Value chain analysis for green productivity improvement in the natural rubber supply chain: a case study. J Clean Prod 85:201–211. https://doi.org/10.1016/j.jclepro.2014.01.098

Darmawan MA, Widhiarti RP, Teniwut YK (2018) Green productivity improvement and sustainability assessment of the motorcycle tire production process: a case study. J Clean Prod 191:273–282. https://doi.org/10.1016/j.jclepro.2018.04.228

de Marques PA, Matthé R (2017) Six Sigma DMAIC project to improve the performance of an aluminum die casting operation in Portugal. Int J Qual Reliab Manag 34:307–330. https://doi.org/10.1108/IJQRM-05-2015-0086

Dias J, Nunes E, Sousa S (2020) Productivity improvement of transmission electron microscopes-a case study. Proced Manuf 51:1559–1566. https://doi.org/10.1016/j.promfg.2020.10.217

Djatna T, Munichputranto F (2015) An analysis and design of mobile business intelligence system for productivity measurement and evaluation in tire curing production line. Proced Manuf 4:438–444. https://doi.org/10.1016/j.promfg.2015.11.060

Duan P, He Z, He Y, Liu F, Zhang A, Zhou D (2020) Root cause analysis approach based on reverse cascading decomposition in QFD and fuzzy weight ARM for quality accidents. Comput Ind Eng 147:106643. https://doi.org/10.1016/j.cie.2020.106643

Dweiri F, Ishaq S (2020) Cable insulation productivity improvement using Lean Six Sigma. IJPQM 30:488–508. https://doi.org/10.1504/IJPQM.2020.108573

Ferreras-Higuero E, Leal-Muñoz E, García de Jalón J, Chacón E, Vizán A (2020) Robot-process precision modelling for the improvement of productivity in flexible manufacturing cells. Robot Comput-Integr Manuf 65:101966. https://doi.org/10.1016/j.rcim.2020.101966

Fritz M, Berger PD (2015) Comparing two designs (or anything else!) using paired sample T-tests. In: Fritz M, Berger PD (eds) Improving the user experience through practical data analytics. Morgan Kaufmann, Boston, pp 71–89. https://doi.org/10.1016/B978-0-12-800635-1.00003-3

Chapter   Google Scholar  

Gavareshki MHK, Abbasi M, Karbasian M, Rostamkhani R (2020) Presenting a productive and sustainable model of integrated management system for achieving an added value in organisational processes. IJPQM 30:429–461. https://doi.org/10.1504/IJPQM.2020.108569

Ge J, Fu Y, Xie R, Liu Y, Mo W (2018) The effect of GVC embeddedness on productivity improvement: from the perspective of R&D and government subsidy. Technol Forecast Soc Chang 135:22–31. https://doi.org/10.1016/j.techfore.2018.07.057

Ghatorha KS, Sharma R, Singh G (2020) Application of root cause analysis to increase material removal rate for productivity improvement: a case study of the press manufacturing industry. Mater Today 26:1780–1783. https://doi.org/10.1016/j.matpr.2020.02.374

Gleeson F, Coughlan P, Goodman L, Newell A, Hargaden V (2019) Improving manufacturing productivity by combining cognitive engineering and lean-six sigma methods. Proced CIRP 81:641–646. https://doi.org/10.1016/j.procir.2019.03.169

Globerson S, Vitner G (2019) Measuring productivity in multi-stage, multi-product environment. IJPQM 26:290–304. https://doi.org/10.1504/IJPQM.2019.098365

Gupta P, Vardhan S (2016) Optimizing OEE, productivity and production cost for improving sales volume in an automobile industry through TPM: a case study. Int J Prod Res 54:2976–2988. https://doi.org/10.1080/00207543.2016.1145817

Gurley K, Edlow J, Burstein JL, Grossman SA (2020) Errors in decisionmaking in emergency medicine: the case of the landscaper’s back and root cause analysis. Ann Emerg Med. https://doi.org/10.1016/j.annemergmed.2020.05.031

Harikrishnan R, Rajeswaran M, Sathish Kumar S, Dinesh K (2020) Productivity improvement in poly-cover packing line through line balancing and automation. Mater Today 33:102–111. https://doi.org/10.1016/j.matpr.2020.03.253

Harris AM, Ziemba J, Bylund J (2020) Implementing a root cause analysis program to enhance patient safety education in urology residency. Urology 138:24–29. https://doi.org/10.1016/j.urology.2019.11.059

Hynes JP, Murray AS, Murray OM, Eustace SK, Gilchrist S, Dolan A, Lawler LP (2019) Use of Lean Six Sigma methodology shows reduction of inpatient waiting time for peripherally inserted central catheter placement. Clin Radiol 74:733.e5-733.e9. https://doi.org/10.1016/j.crad.2019.04.022

Inui T, Kawakami A, Miyagawa T (2012) Market competition, differences in technology, and productivity improvement: an empirical analysis based on Japanese manufacturing firm data. Jpn World Econ 24:197–206. https://doi.org/10.1016/j.japwor.2012.04.002

Islamoglu NE, Ryu K, Moon I (2014) Labour productivity in modular assembly: a study of automotive module suppliers. Int J Prod Res 52:6954–6970. https://doi.org/10.1080/00207543.2014.917773

Ismail R (2018) The impact of human capital and innovation on labour productivity of Malaysian small and medium enterprises. IJPQM 25:245–261. https://doi.org/10.1504/IJPQM.2018.094769

Jadhav JR, Mantha SS, Rane SB (2014a) Exploring barriers in lean implementation. Int J Lean Six Sigma 5(2):122–148. https://doi.org/10.1108/IJLSS-12-2012-0014

Jadhav JR, Mantha SS, Rane SB (2014b) Development of framework for sustainable Lean implementation: an ISM approach. J Ind Eng Int 10:72. https://doi.org/10.1007/s40092-014-0072-8

Jiang G, Zhang R, Ma W, Zhou D, Wang X, He X (2017) Cultivated land productivity potential improvement in land consolidation schemes in Shenyang, China: assessment and policy implications. Land Use Policy 68:80–88. https://doi.org/10.1016/j.landusepol.2017.07.001

Jones EC, Parast MM, Adams SG (2010) A framework for effective six sigma implementation. Total Qual Manag Bus Excell 21:415–424. https://doi.org/10.1080/14783361003606720

Kamble R, Wankhade L (2017) Perspectives on productivity: identifying attributes influencing productivity in various industrial sectors. IJPQM 22:536–566. https://doi.org/10.1504/IJPQM.2017.087868

Kaswan MS, Rathi R (2020) Green Lean Six Sigma for sustainable development: integration and framework. Environ Impact Assess Rev 83:106396. https://doi.org/10.1016/j.eiar.2020.106396

Khan SA, Badar MA, Alzaabi M (2020) Productivity improvement using DMAIC in a Caravan Manufacturing company. IJPQM 30:234–251. https://doi.org/10.1504/IJPQM.2020.107825

Kirkire MS, Rane SB (2017) Evaluation of success factors for medical device development using grey DEMATEL approach. J Model Manag 12:204–223. https://doi.org/10.1108/JM2-09-2015-0062

Kirkire MS, Rane SB, Jadhav JR (2015) Risk management in medical product development process using traditional FMEA and fuzzy linguistic approach: a case study. J Ind Eng Int 11:595–611. https://doi.org/10.1007/s40092-015-0113-y

Kirkire MS, Rane SB, Abhyankar GJ (2020) Structural equation modelling—FTOPSIS approach for modelling barriers to product development in medical device manufacturing industries. J Model Manag 15:967–993. https://doi.org/10.1108/JM2-09-2018-0139

Klefsjö B, Wiklund H, Edgeman RL (2001) Six sigma seen as a methodology for total quality management. Meas Bus Excell 5:31–35. https://doi.org/10.1108/13683040110385809

Kulkarni RG, Kulkarni VN, Gaitonde VN (2018) Productivity improvement in assembly workstation of motor winding unit. Mater Today Proc 5:23518–23525. https://doi.org/10.1016/j.matpr.2018.10.139

Kumar R, Kalra P, Kant S (2020) Productivity enhancement of assembly line by using Maynard operation sequence technique after identification of lean wastages. IJPQM 29:463–482. https://doi.org/10.1504/IJPQM.2020.106400

Kumar Banga H, Kumar R, Kumar P, Purohit A, Kumar H, Singh K (2020) Productivity improvement in manufacturing industry by lean tool. Mater Today Proc 28:1788–1794. https://doi.org/10.1016/j.matpr.2020.05.195

Kusneniwar A, Potdar P, Rane S (2019) Evaluation of performance characteristics and bite condition of single ferrule bite fitting by finite element analysis (FEA). In: Vasudevan H, Kottur VKN, Raina AA (Eds.) Proceedings of international conference on intelligent manufacturing and automation. Springer, Singapore, pp. 239–252. https://doi.org/10.1007/978-981-13-2490-1_22

Liang C, Zhou S, Yao B, Hood D, Gong Y (2020) Toward systems-centered analysis of patient safety events: improving root cause analysis by optimized incident classification and information presentation. Int J Med Inform 135:104054. https://doi.org/10.1016/j.ijmedinf.2019.104054

Liu W-Y, Chen C-H, Chen W-T, Shu C-M (2017) A study of caprolactam storage tank accident through root cause analysis with a computational approach. J Loss Prev Process Ind 50:80–90. https://doi.org/10.1016/j.jlp.2017.09.004

Liu C, Lore KG, Jiang Z, Sarkar S (2021) Root-cause analysis for time-series anomalies via spatiotemporal graphical modeling in distributed complex systems. Knowl-Based Syst 211:106527. https://doi.org/10.1016/j.knosys.2020.106527

Machado CG, Winroth MP, Ribeiro da Silva EHD (2020) Sustainable manufacturing in industry 4.0: an emerging research agenda. Int J Prod Res 58:1462–1484. https://doi.org/10.1080/00207543.2019.1652777

Mahalakshmi S, Arokiasamy A (2020) Productivity and quality enrichment through multi criteria trajectory optimisation of an industrial robot. IJPQM 30:279–303. https://doi.org/10.1504/IJPQM.2020.108380

Mahalakshmi S, Arokiasamy A, Ahamed JFA (2019) Productivity improvement of an eco friendly warehouse using multi objective optimal robot trajectory planning. IJPQM 27:305–328. https://doi.org/10.1504/IJPQM.2019.101517

Meena ML, Jain R, Kumar P, Gupta S, Dangayach GS (2018) Process improvement in an Indian automotive part manufacturing company: a case study. IJPQM 23:524–551. https://doi.org/10.1504/IJPQM.2018.090263

Mexia JT (1990) Best linear unbiased estimates, duality of F tests and the Scheffé multiple comparison method in the presence of controlled heteroscedasticity. Comput Stat Data Anal 10:271–281. https://doi.org/10.1016/0167-9473(90)90007-5

Article   MathSciNet   MATH   Google Scholar  

Mishra N, Rane SB (2019a) Business excellence initiative success prediction model based on logistic regression and artificial neural network. Int J Qual Innov 4:132–166. https://doi.org/10.1504/IJQI.2019.105749

Mishra N, Rane SB (2019b) Prediction and improvement of iron casting quality through analytics and Six Sigma approach. Int J Lean Six Sigma 10(1):189–210. https://doi.org/10.1108/IJLSS-11-2017-0122

Mishra DP, Sugla M, Singha P (2013) Productivity improvement in underground coal mines—a case study. J Sustain Min 12:48–53. https://doi.org/10.7424/jsm130306

Molan G, Molan M (2020) Theoretical model for accident prevention based on root cause analysis with graph theory. Saf Health Work. https://doi.org/10.1016/j.shaw.2020.09.004

Article   MATH   Google Scholar  

Motlagh MA, Valmohammadi C, Modiri M (2020) Developing a qualitative model of productivity for service companies using fuzzy analytic hierarchy process: a case study. IJPQM 29:126–147. https://doi.org/10.1504/IJPQM.2020.104519

Mulugeta L (2020) Productivity improvement through lean manufacturing tools in Ethiopian garment manufacturing company. Mater Today Proc. https://doi.org/10.1016/j.matpr.2020.06.599

Murali CS, Prabukarthi A (2020) Productivity improvement in furniture industry using lean tools and process simulation. IJPQM 30:214–233. https://doi.org/10.1504/IJPQM.2020.107812

Murray A, Papa A, Cuozzo B, Russo G (2016) Evaluating the innovation of the Internet of Things: empirical evidence from the intellectual capital assessment. Bus Process Manag J 22:341–356. https://doi.org/10.1108/BPMJ-05-2015-0077

Nakamura K, Kaihatsu S, Yagi T (2019) Productivity improvement and economic growth: lessons from Japan. Econ Anal Policy 62:57–79. https://doi.org/10.1016/j.eap.2018.11.002

Nandakumar N, Saleeshya PG, Harikumar P (2020) Bottleneck identification and process improvement by Lean Six Sigma DMAIC methodology. Mater Today Proc 24:1217–1224. https://doi.org/10.1016/j.matpr.2020.04.436

Padhy R (2017) Six sigma project selections: a critical review. Lean Six Sigma J 8:244–258. https://doi.org/10.1108/IJLSS-06-2016-0025

Pandey H, Garg D, Luthra S (2018) Identification and ranking of enablers of green Lean Six Sigma implementation using AHP. IJPQM 23:187–217. https://doi.org/10.1504/IJPQM.2018.089156

Parmar PS, Desai TN (2020) Evaluating Sustainable Lean Six Sigma enablers using fuzzy DEMATEL: a case of an Indian manufacturing organization. J Clean Prod 265:121802. https://doi.org/10.1016/j.jclepro.2020.121802

Patil RB, Kothavale BS (2020) Failure modes and effects analysis of CNC turning center. In: Gupta VK, Varde PV, Kankar PK, Joshi N (eds.) Reliability and risk assessment in engineering, Lecture notes in mechanical engineering. Springer, Singapore, pp. 49–59. https://doi.org/10.1007/978-981-15-3746-2_5

Patil RB, Kothavale BS (2018) Failure modes and effects analysis (FMEA) of computerized numerical control (CNC) turning center. Int Rev Mech Eng (IREME) 12:78–87. https://doi.org/10.15866/ireme.v12i1.14156

Potdar P, Rane S (2018) Selection of the best manufacturer using TOPSIS and PROMETHEE for asset propelled industry (API). Ind Eng J 11:1–21. https://doi.org/10.26488/IEJ.11.10.1147

Potdar P, Rane S, Mishra N (2020) Design of experiments and Monte Carlo simulation based prediction model for productivity improvement in printing industry. Int J Prod Qual Manag. https://doi.org/10.1504/ijpqm.2020.10033290

Potdar P, Rane S (2017) Exploring success factors for effective implementation of business analytics. National conference on Changing Technology and Rural Development -2017. ISSN [ONLINE]: 2395-1052. 156–163. https://ijsart.com/Home/IssueDetail/20732

Prashar A (2014) Process improvement in farm equipment sector (FES): a case on six sigma adoption. Lean Six Sigma J 5:62–88. https://doi.org/10.1108/IJLSS-08-2013-0049

Rane SB, Kirkire MS (2016) Analysis of barriers to medical device development in India: an interpretive structural modelling approach. Int J Syst Assur Eng Manag 7:356–369. https://doi.org/10.1007/s13198-016-0497-0

Rane SB, Kirkire MS (2017) Interpretive structural modelling of risk sources in medical device development process. Int J Syst Assur Eng Manag 8:451–464. https://doi.org/10.1007/s13198-015-0399-6

Rane SB, Mishra N (2018) Roadmap for business analytics implementation using DIPPS model for sustainable business excellence: case studies from the multiple fields. Int J Bus Excell 15:308–334. https://doi.org/10.1504/IJBEX.2018.092574

Rane SB, Narvel YAM (2016) Reliability assessment and improvement of air circuit breaker (ACB) mechanism by identifying and eliminating the root causes. Int J Syst Assur Eng Manag 7:305–321. https://doi.org/10.1007/s13198-015-0405-z

Rane SB, Narvel YAM (2021) Data-driven decision making with Blockchain-IoT integrated architecture: a project resource management agility perspective of industry 40. Int J Syst Assur Eng Manag. https://doi.org/10.1007/s13198-021-01377-4

Rane S, Potdar P (2020) Blockchain-IoT based risk management approach for Project Procurement process of Asset Propelled Industries (API). Int J Procure Manag 1:1. https://doi.org/10.1504/ijpm.2020.10032403

Rane SB, Thakker SV (2020) Green procurement process model based on blockchain–IoT integrated architecture for a sustainable business. Manag Environ Qual Int J 31:741–763. https://doi.org/10.1108/MEQ-06-2019-0136

Rane SB, Narvel YAM, Khatua N (2017) Development of mechanism for mounting secondary isolating contacts (SICs) in air circuit breakers (ACBs) with high operational reliability. Int J Syst Assur Eng Manag 8:1816–1831. https://doi.org/10.1007/s13198-017-0678-5

Rane SB, Potdar PR, Rane S (2019a) Accelerated life testing for reliability improvement: a case study on Moulded Case Circuit Breaker (MCCB) mechanism. Int J Syst Assur Eng Manag 10:1668–1690. https://doi.org/10.1007/s13198-019-00914-6

Rane SB, Potdar PR, Rane S (2019) Development of Project Risk Management framework based on Industry 40 technologies. Benchmarking Int J 28:1451–1481. https://doi.org/10.1108/BIJ-03-2019-0123

Rane SB, Potdar PR, Mewada M (2021) Implementation of a Six Sigma strategy for process improvement in the wiper motor manufacturing industry. Int J Six Sigma Compet Adv 13:241–270. https://doi.org/10.1504/IJSSCA.2021.120219

Rehman A, Ramzan MB, Shafiq M, Rasheed A, Naeem MS, Savino MM (2019) Productivity improvement through time study approach: a case study from an apparel manufacturing industry of Pakistan. Proced Manuf 39:1447–1454. https://doi.org/10.1016/j.promfg.2020.01.306

Reosekar RS, Pohekar SD (2014) Six Sigma methodology: a structured review. Lean Six Sigma J 5:392–422. https://doi.org/10.1108/IJLSS-12-2013-0059

Schiermoch PD, Beisheim B, Rahimi-Adli K, Engell S (2020) A methodology for data based root-cause analysis for process performance deviations in continuous processes. In: Pierucci S, Manenti F, Bozzano GL, Manca D (eds.) Computer aided chemical engineering, 30 European Symposium on Computer Aided Process Engineering. Elsevier, pp. 1873–1878. https://doi.org/10.1016/B978-0-12-823377-1.50313-X

Schuh G, Potente T, Wesch-Potente C, Weber AR, Prote J-P (2014) Collaboration mechanisms to increase productivity in the context of industrie 4.0. Proced CIRP 19:51–56. https://doi.org/10.1016/j.procir.2014.05.016

Selvam G, Prince SAD, Prakash VS, Rohit T (2018) Quality and productivity improvement through spot welding process optimisation in automobile body shop. IJPQM 23:110–127. https://doi.org/10.1504/IJPQM.2018.088611

Siddiqui SQ, Ullah F, Thaheem MJ, Gabriel HF (2016) Six sigma in construction: a review of critical success factors. Lean Six Sigma J 7:171–186. https://doi.org/10.1108/IJLSS-11-2015-0045

Singh M, Rathi R, Garza-Reyes JA (2021) Analysis and prioritization of Lean Six Sigma enablers with environmental facets using best worst method: a case of indian MSMEs. J Clean Prod 279:123592. https://doi.org/10.1016/j.jclepro.2020.123592

Sommer AC, Blumenthal EZ (2019) Implementation of lean and six sigma principles in ophthalmology for improving quality of care and patient flow. Surv Ophthalmol 64:720–728. https://doi.org/10.1016/j.survophthal.2019.03.007

Steenwinckel B, De Paepe D, Vanden Hautte S, Heyvaert P, Bentefrit M, Moens P, Dimou A, Van Den Bossche B, De Turck F, Van Hoecke S, Ongenae F (2021) FLAGS: a methodology for adaptive anomaly detection and root cause analysis on sensor data streams by fusing expert knowledge with machine learning. Futur Gener Comput Syst 116:30–48. https://doi.org/10.1016/j.future.2020.10.015

Steere L, Rousseau M, Durland L (2018) Lean Six Sigma for intravenous therapy optimization: a hospital use of lean thinking to improve occlusion management. J Assoc Vasc Access 23:42–50. https://doi.org/10.1016/j.java.2018.01.002

Sunder MV (2016) Lean Six Sigma project management—a stakeholder management perspective. TQM J 28:132–150. https://doi.org/10.1108/TQM-09-2014-0070

Swarnakar V, Singh AR, Tiwari AK (2020) Effect of Lean Six Sigma on firm performance: a case of Indian automotive component manufacturing organization. Mater Today Proc. https://doi.org/10.1016/j.matpr.2020.07.115

Tenera A, Pinto LC (2014) A Lean Six Sigma (LSS) project management improvement model. Proced Soc Behav Sci 119:912–920. https://doi.org/10.1016/j.sbspro.2014.03.102

Thangaiah ISS, Sharma V, Sundharam VN (2018) Analysing of customer feedback on critical quality parameters to improve productivity in manufacturing—a case study. IJPQM 23:349–368. https://doi.org/10.1504/IJPQM.2018.089805

Timans W, Ahaus K, Antony J (2014) Six Sigma methods applied in an injection moulding company. Lean Six Sigma J 5:149–167. https://doi.org/10.1108/IJLSS-07-2013-0037

Titmarsh R, Assad F, Harrison R (2020) Contributions of Lean Six Sigma to sustainable manufacturing requirements: an industry 4.0 perspective. Proced CIRP 90:589–593. https://doi.org/10.1016/j.procir.2020.02.044

Uddin MA, Stranieri A, Gondal I, Balasubramanian V (2021) A survey on the adoption of blockchain in IoT: challenges and solutions. Blockchain Res Appl. https://doi.org/10.1016/j.bcra.2021.100006

Waibel MW, Steenkamp LP, Moloko N, Oosthuizen GA (2017) Investigating the effects of smart production systems on sustainability elements. Proced Manuf 8:731–737. https://doi.org/10.1016/j.promfg.2017.02.094

Wang S, Wan J, Li D, Zhang C (2016) Implementing smart factory of industrie 4.0: an outlook. Int J Distrib Sens Netw 12(1):3159805. https://doi.org/10.1155/2016/3159805

Wang J, Yang Z, Su J, Zhao Y, Gao S, Pang X, Zhou D (2018) Root-cause analysis of occurring alarms in thermal power plants based on Bayesian networks. Int J Electr Power Energy Syst 103:67–74. https://doi.org/10.1016/j.ijepes.2018.05.029

Wu C, Yi D, Weng W, Li S, Zhou J, Zheng F (2015) Arc erosion behavior of Ag/Ni electrical contact materials. Mater Des 85:511–519. https://doi.org/10.1016/j.matdes.2015.06.142

Yadav S, Luthra S, Garg D (2022) Internet of things (IoT) based coordination system in Agri-food supply chain: development of an efficient framework using DEMATEL-ISM. Oper Manag Res 15:1–27. https://doi.org/10.1007/s12063-020-00164-x

Yang J, Zhan Z, Chou CC, Yang R-J, Zheng L, Guo G (2018) Root cause analysis strategy for robust design domain recognition. Eng Optim 50:1325–1346. https://doi.org/10.1080/0305215X.2017.1391241

Yue W, Chen X, Huang K, Zeng Z, Xie Y (2018) Knowledge modeling for root cause analysis of complex systems based on dynamic fuzzy cognitive maps. IFAC-PapersOnLine 51:13–18. https://doi.org/10.1016/j.ifacol.2018.09.385

Zahraee SM, Rohani JM, Wong KY (2018) Application of computer simulation experiment and response surface methodology for productivity improvement in a continuous production line: case study. J King Saud Univ 30:207–217. https://doi.org/10.1016/j.jksues.2018.04.003

Zhong X, Xu Y, Liu Y, Wu X, Zhao D, Zheng Y, Jiang J, Deng Z, Fu X, Li X (2020) Root cause analysis and diagnosis of solid oxide fuel cell system oscillations based on data and topology-based model. Appl Energy 267:114968. https://doi.org/10.1016/j.apenergy.2020.114968

Zu X, Fredendall LD (2009) Enhancing six sigma implementation through human resource management. Qual Manag J 16:41–54. https://doi.org/10.1080/10686967.2009.11918249

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Rane, S.B., Wavhal, S. & Potdar, P.R. Integration of Lean Six Sigma with Internet of Things (IoT) for productivity improvement: a case study of contactor manufacturing industry. Int J Syst Assur Eng Manag 14 , 1990–2018 (2023). https://doi.org/10.1007/s13198-023-01980-7

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DOI : https://doi.org/10.1007/s13198-023-01980-7

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A case-based methodology for lean implementation in hospital operations

Affiliation.

• 1 Universidade Federal da Paraíba , João Pessoa, Brazil.
• PMID: 31625821
• DOI: 10.1108/JHOM-09-2018-0267

Purpose: Although there are general methodologies for lean implementation in manufacturing companies, a specific methodology for the implementation of lean healthcare in hospitals has not been addressed by the literature. Addressing this gap, the purpose of this paper is to develop a practice-driven methodology for implementing lean in hospital operations.

Design/methodology/approach: Three case studies were conducted to collect evidence on the lean implementation process in Brazilian hospitals. From empirical evidence and literature, the implementation methodology was proposed and submitted to critical assessment by experts from the field.

Findings: The process of lean implementation was very similar in all cases, triggered by strategic planning and operationalized by continuous improvement projects. On the other hand, in all cases, the lean implementation teams had to deal with employees' resistance. These findings were valuable inputs to the development of the implementation methodology. After refinement, it was proposed a feasible, useful and user-friendly methodology.

Research limitations/implications: The proposed methodology was raised from the practice through case study research. However, the proposed methodology was not fully applied, and the associated performance measures were not elaborated in this paper. Therefore, more case studies and applications will be necessary to generalize the findings.

Practical implications: The methodology provides practical guidelines that support lean implementation in hospital operations. Although it demands adaptations for each specific hospital setting, this initial step may encourage hospital managers to start the lean journey.

Originality/value: This study addressed the gap in the literature regarding the lack of methodologies for implementing lean healthcare in hospital operations. The methodology synthesizes the knowledge, principles and tools of lean thinking that can be applied in hospital operations.

Keywords: Healthcare; Hospital operations; Lean implementation.

• Efficiency, Organizational / standards*
• Hospitals / standards*
• Organizational Case Studies
• Quality Improvement*
• Total Quality Management / methods*