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EFFECTIVE LEADERSHIP IN HEALTHCARE ORGANIZATIONS - PowerPoint PPT Presentation

EFFECTIVE LEADERSHIP IN HEALTHCARE ORGANIZATIONS

Discuss the most important leadership traits and skills as well as functions of ... indira ghandi. 28. exercise (2) . 29. styles of leadership: ... – powerpoint ppt presentation.

• Dr. Naila H. Amer
• Professor of Health Administration and Planning
• Define leadership.
• Describe leadership approaches.
• Discuss the most important leadership traits and skills as well as functions of effective leadership.
• Determine sources of leaders power importance of influence.
• Explain leadership development.
• Differentiate between transactional transformational leadership.
• Discuss the role of emotional intelligence in relation to successful leadership.
• Describe the different leadership styles.
• Effective leadership is essential if a health services organization (HSO) is to provide high-quality care and succeed financially. All managers at all levels of the organization, who depend on other people for efficient and effective work performance, require leadership ability.
• The quality of leadership is crucial to how work gets done.
• Leadership is a very complex multidimensional concept and has been defined in a number of different ways.
• A common definition is
• Leaders are agents of change, persons whose acts affect other people more than other peoples acts affect them.
• Leaders following the proactive approach take responsible initiatives to change situations and attitudes through people. This approach is the essence of modern leadership,it contrasts with the
• Reactive approach where a leader responds only to events and instructions from outside.
• From your experience, try to describe a leader you worked with or had contact with whom you consider a role model of a successful leader why.
• What in your opinion are the main traits ,skills behaviours of a successful leader?
• Although none of the hundreds of studies conducted in search of universal leader traits were successful yet, certain traits are known to be associated with leader effectiveness. Table 1 is a list of traits and skills that most frequently characterise successful leaders.
• Adaptable to situations
• Alert to social environment
• Ambitious and achievement-oriented.
• Cooperative
• Dominant(desire to influence others)
• Energetic (high activity level)
• Self-confident
• Tolerant of stress
• Willing to assume responsibility
• Clever(intelligent)
• Conceptually skilled
• Diplomatic and tactful
• Fluent in speaking
• Knowledgeable about group task
• Organized (administrative ability)
• Socially skilled
• Influence is important to the leadership process because it is the means by which leaders successfully persuade others to follow their advice, suggestion or order. The essence of leadership is the ability to influence others. To have influence, however, one also must have power.
• Sources of Power
• 1.Legitimate Power This is the power a leader has as a result of his / her position in the organization.
• 2. Coercive Power Is the power to punish or control.
• 3. Reward Power Is the power of giving positive benefits or rewards whether financial or otherwise.
• 4. Expert Power Influence thats based on expertise, special skills or knowledge.
• 5. Referent Power Arises because of a persons personal traits or desirable resources, e.g. admiration of another a desire to be like that person, in this case that person has referent power over you.
• Most effective leaders rely on several different forms of power e.g. giving orders (legitimate), praising (reward), disciplining (coercive).
• Also power must be used wisely to influence people e.g. abuse of coercive power may lead to weakening or loss of referent power.
• Effective leaders understand the costs, risks, and benefits of using each kind of power and are able to recognize which to draw on in different situations and with different people.
• Leadership Behaviour
• In the 1950s, the study of leadership and leaders shifted from traits to behaviour. This raised the exciting possibility that if leader behaviour explained leadership effectiveness, then leadership could be taught since behaviour can be learned and programs can be designed to develop effective leaders.
• The trait theories maintained that leaders are born Either you have it or you dont. The behaviour theories believed that leaders are made!
• Leadership development means the improvement and strengthening of abilities and effectiveness of both current and prospective leaders.
• Some of the functions to be developed for effective leadership are demonstrated in table 2
• Table 2 Functions of Effective Leadership
• The provision of a vision that influences all who work in the organization.
• Confidence in ones vision and oneself.
• Projecting / communicating the vision.
• Initiating / guiding change.
• Mobilizing commitment and support for change.
• Resolving conflict.
• Building of trust.
• Building sustainability
• Developing others.
• Among the contemporary approaches to leadership is that leadership in organizations is of two types transformational and transactional. Transactional leaders are those who guide motivate their followers towards established goals clarify role task requirements.
• Transformational leaders on the other hand, are mainly concerned with change, the needs of followers, and helping followers look at old problems in new ways. They are able to excite ,arouse and inspire followers to put an extra effort and transcend their own self interest to achieve group goals.
• Transformational and transactional leadership should not be viewed as opposing approaches. Transformational leadership is built on top of transactional leadership producing performance that goes beyond what would occur with transactional approach alone.
• There is evidence that transformational leadership is more strongly correlated with lower turnover rates, higher productivity, higher employee satisfaction.
• Some authors state that transformational leadership is more likely to be practiced by senior managers who focus on creating system - wide change in relation to organizations missions, values, culture, strategiesetc. This group maintains that transactional leaders are those who usually have a direct supervisor-subordinate relationship with their followers.
• As a result of many researches, Goleman (1998) concluded that although successful leaders vary in many ways, yet the most effective ones are alike in one crucial way
• They all have a high degree of what has come to be known as emotional intelligence. Its not that IQ and technical skills are irrelevant. They do matter, but mainly as threshold capabilities or entry-level requirements for executive positions.
• Recent studies clearly show that without emotional intelligence a person can have the best training and a brilliant analytical mind but still wont make a great leader.
• The ability to recognize and understand your moods, emotions, and drives, as well as their effect on others.
• The ability to control or redirect disruptive impulses and moods.
• The propensity to suspend judgment.
• self-confidence
• Realistic self-assessment
• Self-deprecating sense of humor
• Trustworthiness and integrity
• Comfort with ambiguity.
• Openness to change.
• A passion to work for reasons that go beyond money or status.
• A propensity to pursue goals with energy and persistence.
• The ability to understand the emotional makeup of other people.
• Skill in treating people according to their emotional reactions.
• Proficiency in managing relationships and building networks.
• An ability to find common ground and build rapport.
• Strong drive to achieve.
• Optimism, even in the face of failure.
• Organizational commitment.
• Expertise in building and retaining talent.
• Cross-cultural sensitivity.
• Service to clients and customers..
• Effectiveness in leading change.
• Persuasiveness.
• Expertise in building and leading teams.
• I suppose that leadership at one time meant muscle but today it means getting along with people.
• Indira Ghandi
• ??????? ?????? ???????
• Leadership style is how you behave when you are trying to influence the performance of others.
• (A) Tannenbaum and Schmids Continuum of Leader Behaviour
• This relates to the decision making authority dimension of leader behaviour, and can be displayed on a continuum from autocratic to laissez-faire as shown in figure 1.
• NO ONE STYLE IS APPROPRIATE AT ALL TIMES
• CONTINGENCY THEORY
• 1- Urgency and time factor
• 2- The type of work
• 3- Subordinates characteristics
• 4- Personal characteristics of the leader
• In this model leadership style is a combination of task and relationship behaviours.
• Involves Extent to which leaders organize and define roles of followers through clearly telling them what to do, how to do it, where to do it, and when to do it, and then closely supervising their performance.
• There are four leadership styles
• Telling, Selling, Participating and Delegating
• THERE IS NO ONE BEST LEADERSHIP STYLE.
• According to Hersey and Blanchard (1996), effective leadership is an interplay among
• 1)The leaders task behaviour
• 2)The leaders relationship behaviour
• 3)The followers readiness level to take responsibility to perform a task or function.
• SITUATIONAL LEADERSHIP IS NOT
• SOMETHING YOU DO TO PEOPLE
• SOMETHING YOU DO WITH PEOPLE

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2021Congress on Healthcare Leadership Multimedia Presentations

Thank you for being a leader who cares, 2021 opening session immediate past chairman's remarks, 2021 chair remarks—carrie owen plietz, fache, gold medal award winner 2021—charles d. stokes, fache, ache's honorary fellow - sister carol keehan, dc, hfache, young healthcare executive of the year - mark schulte, fache.

Introduction to Health Care Leadership

Oct 28, 2019

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Introduction to Health Care Leadership. IHI Open School L101. Agenda. Review IHI Lessons (5 mins) Leadership Exercise (15 mins) Healthcare Leadership video and discussion (15 mins) Wrap Up (5 mins). Lesson 1: What Makes a Leader?.

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Introduction to Health Care Leadership IHI Open School L101

Agenda • Review IHI Lessons (5 mins) • Leadership Exercise (15 mins) • Healthcare Leadership video and discussion (15 mins) • Wrap Up (5 mins)

Lesson 1: What Makes a Leader? • You can lead without a position of power — leadership is about taking responsibility and taking action. • When leaders see a problem, they tackle the issue through the following steps: • Take initiative. • Investigate. • Make connections. • Identify solutions. • Take action. • Leaders collect data to solve shared problems — not to advance their own agenda. • Leaders promote an agenda that makes sense for the people around them. IHI Open School Course Summary Sheet | L 101: Introduction to Health Care Leadership

Lesson 2: Practical Skills for Leading Teams • To make a change in a system, you need to function as part of a diverse team. • As a team leader, you need to navigate people’s differences and make the most of what each person can offer. • Many assessment tools can help leaders better understand individual team members and team dynamics. Here are some tools that may be useful in different situations: • The HRET Working Styles Questionnaire • StrengthsFinder 2.0 • Myers-Briggs Type Indicator • Strength Deployment Inventory • DiSCProfile • Riso-Hudson Enneagram Type Indicator (RHETI) • Three ways to persuade people to take action with you, which will appeal to different types of people, include: • Use logic. • Get endorsed by people with power and authority. • Appeal to emotions. IHI Open School Course Summary Sheet | L 101: Introduction to Health Care Leadership

Lesson 2: Practical Skills for Leading Teams • Good leaders know their followers include a spectrum of personalities and viewpoints, and they find a way to achieve a “workable level of unity.” • Some helpful leadership tactics include: • Assign clear roles. • Set ground rules. • Treat teammates with respect. • Listen to others with an open mind. • If you are the type of person who regularly assumes a leadership stance, it is likely you will one day find yourself in a management role if you are not already. • Like leadership, management is a skill that takes learning and practice. IHI Open School Course Summary Sheet | L 101: Introduction to Health Care Leadership

Lesson 3: Strategies to Sustain Your Health Care Leadership Journey • Some general advice for launching a career in health care leadership is: • Seek out new knowledge and experience. • Get to know the people around you at all levels, and become familiar with their processes and challenges. • Learn and practice quality improvement skills — and demonstrate success. • Sociologist Michael Farrell described how some of the most creative work of artists, scientists, and professionals occurred within a circle of like-minded friends. • Several resources to help expand your professional network include: • Journals and publications in your field • Online social networks (e.g., Twitter and Facebook) • Improvement organizations (e.g., the World Health Organization and IHI) • Professional conferences IHI Open School Course Summary Sheet | L 101: Introduction to Health Care Leadership

Leadership Exercise: Think of a great leader you have known in your life and list 3 of the most important traits he/she had. We will aggregate these characteristics on the board.

Characteristics of Admired Leaders Kouzes, J.M. & Posner, B.Z. (2012). The Leadership Challenge: How To Make Extraordinary Things Happen in Organizations. San Francisco, CA: Jossey-Bass.

What Traits Do Health Care Leaders Need Today? • Learning Objectives • Identify several traits that can help a leader succeed. • Explain the benefits of connecting with staff on the front line of an organization. • Discuss how transparency can help to lead to health care improvements. • https://youtu.be/ZfBBaUEnHqs • Divide into groups, discuss questions, and then share examples.

Discussion Questions Which of the traits Dr. Kaplan mentioned do you feel is the most important to us as TCPI coaches? Why? What are some examples of this that you have experienced with your practices? • Person-Centeredness: Be consistently person-centered in word and deed. • Front Line Engagement: Be a regular authentic presence at the front line and a visible champion of improvement. • Relentless Focus: Remain focused on the vision and strategy. • Transparency: Require transparency about results, progress, aims, and defects. • Boundarilessness: Encourage and practice systems thinking and collaboration across boundaries.

Examples From The Group

Conclusion • Leadership is not who you are, it is what you do • Anyone can be a leader • Leadership is a relationship • Leadership is a muscle • “Personal-Best Leadership Experience” case* Thoughts/questions/comments? Dancing Guy video: https://www.youtube.com/watch?v=fW8amMCVAJQ *Kouzes, J.M. & Posner, B.Z. (2012). The Leadership Challenge: How To Make Extraordinary Things Happen in Organizations. San Francisco, CA: Jossey-Bass.

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Slide 1 : This slide introduces Leadership. State company name here and get started. Slide 2 : This is an Agenda slide. State your Starting agendas here. Slide 3 : This is also an Agenda slide. State your Ending Agendas here. Slide 4 : This slide defines What is Leadership with imagery. Slide 5 : This slide presents the Definition of Leadership Slide 6 : This slide states what Leadership Is. Slide 7 : This slide states Who is a Leader? with introduction, definition etc. Slide 8 : This slide presents Leadership Quotes for inspiration, motivation etc. You may change the slide content as per need. Slide 9 : This too is a Leadership Quotes slide with background imagery. Slide 10 : This slide shows another variation of Leadership Quotes. Slide 11 : This slide states the Difference Between Managers & Leaders. Showcase it here in points. Slide 12 : This is a Leadership vs Management slide with respect to the following factors- Role, Focus, Approach, Methodology, Style/tone, Outcome. Slide 13 : This slide states the Qualities of a Good Leader such as- Shared Vision, Lead Change, Set Example, Inspire People, Empower People, Honest, Competent, Forward Looking. Slide 14 : This slide states Formal and Informal Leadership in points. Slide 15 : This slide is titled Styles of Leadership. Slide 16 : This slide presents Leadership Styles based on Authority in a flow chart form. Slide 17 : This is another slide showing Leadership Styles Based On Authority divided into three categories- Autocratic, Laissez-faire, Democratic. Slide 18 : This slide presents the definition of Autocratic Leadership with imagery. You can alter it as per need. Slide 19 : This slide showcases Autocratic Leadership Advantages & Disadvantages. You can add your own as per your need and use it. Slide 20 : This slide showcases Democratic Leadership with imagery divided into- Consultative, Persuasive. Slide 21 : This slide presents a list of Democratic Leadership Advantages & Disadvantages. Slide 22 : This slide shows Laissez Faire Leadership. Slide 23 : This slide states Laissez-faire Leadership Advantages & Disadvantages in points. You can refine them on the basis of your requirements. Slide 24 : This is a Based on Task vs People Emphasis matrix slide ranging from High to Low and vice versa. Slide 25 : This is Based On Assumptions About People slide showing Mc Gregor’s Theory with human head imagery. Slide 26 : This slide showcases Likert's Styles of Leadership which include the following 4 points- Benevolent Authoritative, Consultative Leadership, Participate Leadership, Exploitative Authoritative. Slide 27 : This slide states Entrepreneurial Leadership facts and information to be displayed. Slide 28 : This slide showcases Transactional Leadership. Slide 29 : This is a Transformational Leadership slide showcasing its 4 important components- Inspirational Motivation, Individual Consideration, Idealized Influence, Intellectual Stimulation. Slide 30 : This is Transactional vs Transformational Leadership slide to state. Slide 31 : This slide is titled Theories of Leadership. Slide 32 : This slide showcases four Leadership Theories. These are- Trait Theory, The Managerial Grid, Contingency Theory, Leader Behavior Theory. Slide 33 : This is Trait Theory of Leadership slide showing Personality Traits further divided into three components- Abilities Personal Traits Motivators Slide 34 : This slide states What Makes a Leader with the following points- A Born Leader, Honesty and Integrity, Maturity and Charisma, Analytical Ability, Self Confidence, A Desire to Lead, Development, Contextualize Decisions, A Drive to Achieve. Slide 35 : This slide showcases various Traits and Skills (Leaders vs Non-Leaders). Monitor them and change as per requirement. Slide 36 : This is Behavioral Theory of Leadership differentiating between Behavioral Theory and Trait Theory. 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Research ethics and artificial intelligence for global health: perspectives from the global forum on bioethics in research

• James Shaw 1 , 13 ,
• Joseph Ali 2 , 3 ,
• Caesar A. Atuire 4 , 5 ,
• Phaik Yeong Cheah 6 ,
• Armando Guio Español 7 ,
• Judy Wawira Gichoya 8 ,
• Adrienne Hunt 9 ,
• Daudi Jjingo 10 ,
• Katherine Littler 9 ,
• Daniela Paolotti 11 &
• Effy Vayena 12  

BMC Medical Ethics volume  25 , Article number:  46 ( 2024 ) Cite this article

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The ethical governance of Artificial Intelligence (AI) in health care and public health continues to be an urgent issue for attention in policy, research, and practice. In this paper we report on central themes related to challenges and strategies for promoting ethics in research involving AI in global health, arising from the Global Forum on Bioethics in Research (GFBR), held in Cape Town, South Africa in November 2022.

The GFBR is an annual meeting organized by the World Health Organization and supported by the Wellcome Trust, the US National Institutes of Health, the UK Medical Research Council (MRC) and the South African MRC. The forum aims to bring together ethicists, researchers, policymakers, research ethics committee members and other actors to engage with challenges and opportunities specifically related to research ethics. In 2022 the focus of the GFBR was “Ethics of AI in Global Health Research”. The forum consisted of 6 case study presentations, 16 governance presentations, and a series of small group and large group discussions. A total of 87 participants attended the forum from 31 countries around the world, representing disciplines of bioethics, AI, health policy, health professional practice, research funding, and bioinformatics. In this paper, we highlight central insights arising from GFBR 2022.

We describe the significance of four thematic insights arising from the forum: (1) Appropriateness of building AI, (2) Transferability of AI systems, (3) Accountability for AI decision-making and outcomes, and (4) Individual consent. We then describe eight recommendations for governance leaders to enhance the ethical governance of AI in global health research, addressing issues such as AI impact assessments, environmental values, and fair partnerships.

Conclusions

The 2022 Global Forum on Bioethics in Research illustrated several innovations in ethical governance of AI for global health research, as well as several areas in need of urgent attention internationally. This summary is intended to inform international and domestic efforts to strengthen research ethics and support the evolution of governance leadership to meet the demands of AI in global health research.

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Introduction

The ethical governance of Artificial Intelligence (AI) in health care and public health continues to be an urgent issue for attention in policy, research, and practice [ 1 , 2 , 3 ]. Beyond the growing number of AI applications being implemented in health care, capabilities of AI models such as Large Language Models (LLMs) expand the potential reach and significance of AI technologies across health-related fields [ 4 , 5 ]. Discussion about effective, ethical governance of AI technologies has spanned a range of governance approaches, including government regulation, organizational decision-making, professional self-regulation, and research ethics review [ 6 , 7 , 8 ]. In this paper, we report on central themes related to challenges and strategies for promoting ethics in research involving AI in global health research, arising from the Global Forum on Bioethics in Research (GFBR), held in Cape Town, South Africa in November 2022. Although applications of AI for research, health care, and public health are diverse and advancing rapidly, the insights generated at the forum remain highly relevant from a global health perspective. After summarizing important context for work in this domain, we highlight categories of ethical issues emphasized at the forum for attention from a research ethics perspective internationally. We then outline strategies proposed for research, innovation, and governance to support more ethical AI for global health.

In this paper, we adopt the definition of AI systems provided by the Organization for Economic Cooperation and Development (OECD) as our starting point. Their definition states that an AI system is “a machine-based system that can, for a given set of human-defined objectives, make predictions, recommendations, or decisions influencing real or virtual environments. AI systems are designed to operate with varying levels of autonomy” [ 9 ]. The conceptualization of an algorithm as helping to constitute an AI system, along with hardware, other elements of software, and a particular context of use, illustrates the wide variety of ways in which AI can be applied. We have found it useful to differentiate applications of AI in research as those classified as “AI systems for discovery” and “AI systems for intervention”. An AI system for discovery is one that is intended to generate new knowledge, for example in drug discovery or public health research in which researchers are seeking potential targets for intervention, innovation, or further research. An AI system for intervention is one that directly contributes to enacting an intervention in a particular context, for example informing decision-making at the point of care or assisting with accuracy in a surgical procedure.

The mandate of the GFBR is to take a broad view of what constitutes research and its regulation in global health, with special attention to bioethics in Low- and Middle- Income Countries. AI as a group of technologies demands such a broad view. AI development for health occurs in a variety of environments, including universities and academic health sciences centers where research ethics review remains an important element of the governance of science and innovation internationally [ 10 , 11 ]. In these settings, research ethics committees (RECs; also known by different names such as Institutional Review Boards or IRBs) make decisions about the ethical appropriateness of projects proposed by researchers and other institutional members, ultimately determining whether a given project is allowed to proceed on ethical grounds [ 12 ].

However, research involving AI for health also takes place in large corporations and smaller scale start-ups, which in some jurisdictions fall outside the scope of research ethics regulation. In the domain of AI, the question of what constitutes research also becomes blurred. For example, is the development of an algorithm itself considered a part of the research process? Or only when that algorithm is tested under the formal constraints of a systematic research methodology? In this paper we take an inclusive view, in which AI development is included in the definition of research activity and within scope for our inquiry, regardless of the setting in which it takes place. This broad perspective characterizes the approach to “research ethics” we take in this paper, extending beyond the work of RECs to include the ethical analysis of the wide range of activities that constitute research as the generation of new knowledge and intervention in the world.

Ethical governance of AI in global health

The ethical governance of AI for global health has been widely discussed in recent years. The World Health Organization (WHO) released its guidelines on ethics and governance of AI for health in 2021, endorsing a set of six ethical principles and exploring the relevance of those principles through a variety of use cases. The WHO guidelines also provided an overview of AI governance, defining governance as covering “a range of steering and rule-making functions of governments and other decision-makers, including international health agencies, for the achievement of national health policy objectives conducive to universal health coverage.” (p. 81) The report usefully provided a series of recommendations related to governance of seven domains pertaining to AI for health: data, benefit sharing, the private sector, the public sector, regulation, policy observatories/model legislation, and global governance. The report acknowledges that much work is yet to be done to advance international cooperation on AI governance, especially related to prioritizing voices from Low- and Middle-Income Countries (LMICs) in global dialogue.

One important point emphasized in the WHO report that reinforces the broader literature on global governance of AI is the distribution of responsibility across a wide range of actors in the AI ecosystem. This is especially important to highlight when focused on research for global health, which is specifically about work that transcends national borders. Alami et al. (2020) discussed the unique risks raised by AI research in global health, ranging from the unavailability of data in many LMICs required to train locally relevant AI models to the capacity of health systems to absorb new AI technologies that demand the use of resources from elsewhere in the system. These observations illustrate the need to identify the unique issues posed by AI research for global health specifically, and the strategies that can be employed by all those implicated in AI governance to promote ethically responsible use of AI in global health research.

RECs and the regulation of research involving AI

RECs represent an important element of the governance of AI for global health research, and thus warrant further commentary as background to our paper. Despite the importance of RECs, foundational questions have been raised about their capabilities to accurately understand and address ethical issues raised by studies involving AI. Rahimzadeh et al. (2023) outlined how RECs in the United States are under-prepared to align with recent federal policy requiring that RECs review data sharing and management plans with attention to the unique ethical issues raised in AI research for health [ 13 ]. Similar research in South Africa identified variability in understanding of existing regulations and ethical issues associated with health-related big data sharing and management among research ethics committee members [ 14 , 15 ]. The effort to address harms accruing to groups or communities as opposed to individuals whose data are included in AI research has also been identified as a unique challenge for RECs [ 16 , 17 ]. Doerr and Meeder (2022) suggested that current regulatory frameworks for research ethics might actually prevent RECs from adequately addressing such issues, as they are deemed out of scope of REC review [ 16 ]. Furthermore, research in the United Kingdom and Canada has suggested that researchers using AI methods for health tend to distinguish between ethical issues and social impact of their research, adopting an overly narrow view of what constitutes ethical issues in their work [ 18 ].

The challenges for RECs in adequately addressing ethical issues in AI research for health care and public health exceed a straightforward survey of ethical considerations. As Ferretti et al. (2021) contend, some capabilities of RECs adequately cover certain issues in AI-based health research, such as the common occurrence of conflicts of interest where researchers who accept funds from commercial technology providers are implicitly incentivized to produce results that align with commercial interests [ 12 ]. However, some features of REC review require reform to adequately meet ethical needs. Ferretti et al. outlined weaknesses of RECs that are longstanding and those that are novel to AI-related projects, proposing a series of directions for development that are regulatory, procedural, and complementary to REC functionality. The work required on a global scale to update the REC function in response to the demands of research involving AI is substantial.

These issues take greater urgency in the context of global health [ 19 ]. Teixeira da Silva (2022) described the global practice of “ethics dumping”, where researchers from high income countries bring ethically contentious practices to RECs in low-income countries as a strategy to gain approval and move projects forward [ 20 ]. Although not yet systematically documented in AI research for health, risk of ethics dumping in AI research is high. Evidence is already emerging of practices of “health data colonialism”, in which AI researchers and developers from large organizations in high-income countries acquire data to build algorithms in LMICs to avoid stricter regulations [ 21 ]. This specific practice is part of a larger collection of practices that characterize health data colonialism, involving the broader exploitation of data and the populations they represent primarily for commercial gain [ 21 , 22 ]. As an additional complication, AI algorithms trained on data from high-income contexts are unlikely to apply in straightforward ways to LMIC settings [ 21 , 23 ]. In the context of global health, there is widespread acknowledgement about the need to not only enhance the knowledge base of REC members about AI-based methods internationally, but to acknowledge the broader shifts required to encourage their capabilities to more fully address these and other ethical issues associated with AI research for health [ 8 ].

Although RECs are an important part of the story of the ethical governance of AI for global health research, they are not the only part. The responsibilities of supra-national entities such as the World Health Organization, national governments, organizational leaders, commercial AI technology providers, health care professionals, and other groups continue to be worked out internationally. In this context of ongoing work, examining issues that demand attention and strategies to address them remains an urgent and valuable task.

The GFBR is an annual meeting organized by the World Health Organization and supported by the Wellcome Trust, the US National Institutes of Health, the UK Medical Research Council (MRC) and the South African MRC. The forum aims to bring together ethicists, researchers, policymakers, REC members and other actors to engage with challenges and opportunities specifically related to research ethics. Each year the GFBR meeting includes a series of case studies and keynotes presented in plenary format to an audience of approximately 100 people who have applied and been competitively selected to attend, along with small-group breakout discussions to advance thinking on related issues. The specific topic of the forum changes each year, with past topics including ethical issues in research with people living with mental health conditions (2021), genome editing (2019), and biobanking/data sharing (2018). The forum is intended to remain grounded in the practical challenges of engaging in research ethics, with special interest in low resource settings from a global health perspective. A post-meeting fellowship scheme is open to all LMIC participants, providing a unique opportunity to apply for funding to further explore and address the ethical challenges that are identified during the meeting.

In 2022, the focus of the GFBR was “Ethics of AI in Global Health Research”. The forum consisted of 6 case study presentations (both short and long form) reporting on specific initiatives related to research ethics and AI for health, and 16 governance presentations (both short and long form) reporting on actual approaches to governing AI in different country settings. A keynote presentation from Professor Effy Vayena addressed the topic of the broader context for AI ethics in a rapidly evolving field. A total of 87 participants attended the forum from 31 countries around the world, representing disciplines of bioethics, AI, health policy, health professional practice, research funding, and bioinformatics. The 2-day forum addressed a wide range of themes. The conference report provides a detailed overview of each of the specific topics addressed while a policy paper outlines the cross-cutting themes (both documents are available at the GFBR website: https://www.gfbr.global/past-meetings/16th-forum-cape-town-south-africa-29-30-november-2022/ ). As opposed to providing a detailed summary in this paper, we aim to briefly highlight central issues raised, solutions proposed, and the challenges facing the research ethics community in the years to come.

In this way, our primary aim in this paper is to present a synthesis of the challenges and opportunities raised at the GFBR meeting and in the planning process, followed by our reflections as a group of authors on their significance for governance leaders in the coming years. We acknowledge that the views represented at the meeting and in our results are a partial representation of the universe of views on this topic; however, the GFBR leadership invested a great deal of resources in convening a deeply diverse and thoughtful group of researchers and practitioners working on themes of bioethics related to AI for global health including those based in LMICs. We contend that it remains rare to convene such a strong group for an extended time and believe that many of the challenges and opportunities raised demand attention for more ethical futures of AI for health. Nonetheless, our results are primarily descriptive and are thus not explicitly grounded in a normative argument. We make effort in the Discussion section to contextualize our results by describing their significance and connecting them to broader efforts to reform global health research and practice.

Uniquely important ethical issues for AI in global health research

Presentations and group dialogue over the course of the forum raised several issues for consideration, and here we describe four overarching themes for the ethical governance of AI in global health research. Brief descriptions of each issue can be found in Table  1 . Reports referred to throughout the paper are available at the GFBR website provided above.

The first overarching thematic issue relates to the appropriateness of building AI technologies in response to health-related challenges in the first place. Case study presentations referred to initiatives where AI technologies were highly appropriate, such as in ear shape biometric identification to more accurately link electronic health care records to individual patients in Zambia (Alinani Simukanga). Although important ethical issues were raised with respect to privacy, trust, and community engagement in this initiative, the AI-based solution was appropriately matched to the challenge of accurately linking electronic records to specific patient identities. In contrast, forum participants raised questions about the appropriateness of an initiative using AI to improve the quality of handwashing practices in an acute care hospital in India (Niyoshi Shah), which led to gaming the algorithm. Overall, participants acknowledged the dangers of techno-solutionism, in which AI researchers and developers treat AI technologies as the most obvious solutions to problems that in actuality demand much more complex strategies to address [ 24 ]. However, forum participants agreed that RECs in different contexts have differing degrees of power to raise issues of the appropriateness of an AI-based intervention.

The second overarching thematic issue related to whether and how AI-based systems transfer from one national health context to another. One central issue raised by a number of case study presentations related to the challenges of validating an algorithm with data collected in a local environment. For example, one case study presentation described a project that would involve the collection of personally identifiable data for sensitive group identities, such as tribe, clan, or religion, in the jurisdictions involved (South Africa, Nigeria, Tanzania, Uganda and the US; Gakii Masunga). Doing so would enable the team to ensure that those groups were adequately represented in the dataset to ensure the resulting algorithm was not biased against specific community groups when deployed in that context. However, some members of these communities might desire to be represented in the dataset, whereas others might not, illustrating the need to balance autonomy and inclusivity. It was also widely recognized that collecting these data is an immense challenge, particularly when historically oppressive practices have led to a low-trust environment for international organizations and the technologies they produce. It is important to note that in some countries such as South Africa and Rwanda, it is illegal to collect information such as race and tribal identities, re-emphasizing the importance for cultural awareness and avoiding “one size fits all” solutions.

The third overarching thematic issue is related to understanding accountabilities for both the impacts of AI technologies and governance decision-making regarding their use. Where global health research involving AI leads to longer-term harms that might fall outside the usual scope of issues considered by a REC, who is to be held accountable, and how? This question was raised as one that requires much further attention, with law being mixed internationally regarding the mechanisms available to hold researchers, innovators, and their institutions accountable over the longer term. However, it was recognized in breakout group discussion that many jurisdictions are developing strong data protection regimes related specifically to international collaboration for research involving health data. For example, Kenya’s Data Protection Act requires that any internationally funded projects have a local principal investigator who will hold accountability for how data are shared and used [ 25 ]. The issue of research partnerships with commercial entities was raised by many participants in the context of accountability, pointing toward the urgent need for clear principles related to strategies for engagement with commercial technology companies in global health research.

The fourth and final overarching thematic issue raised here is that of consent. The issue of consent was framed by the widely shared recognition that models of individual, explicit consent might not produce a supportive environment for AI innovation that relies on the secondary uses of health-related datasets to build AI algorithms. Given this recognition, approaches such as community oversight of health data uses were suggested as a potential solution. However, the details of implementing such community oversight mechanisms require much further attention, particularly given the unique perspectives on health data in different country settings in global health research. Furthermore, some uses of health data do continue to require consent. One case study of South Africa, Nigeria, Kenya, Ethiopia and Uganda suggested that when health data are shared across borders, individual consent remains necessary when data is transferred from certain countries (Nezerith Cengiz). Broader clarity is necessary to support the ethical governance of health data uses for AI in global health research.

Recommendations for ethical governance of AI in global health research

Dialogue at the forum led to a range of suggestions for promoting ethical conduct of AI research for global health, related to the various roles of actors involved in the governance of AI research broadly defined. The strategies are written for actors we refer to as “governance leaders”, those people distributed throughout the AI for global health research ecosystem who are responsible for ensuring the ethical and socially responsible conduct of global health research involving AI (including researchers themselves). These include RECs, government regulators, health care leaders, health professionals, corporate social accountability officers, and others. Enacting these strategies would bolster the ethical governance of AI for global health more generally, enabling multiple actors to fulfill their roles related to governing research and development activities carried out across multiple organizations, including universities, academic health sciences centers, start-ups, and technology corporations. Specific suggestions are summarized in Table  2 .

First, forum participants suggested that governance leaders including RECs, should remain up to date on recent advances in the regulation of AI for health. Regulation of AI for health advances rapidly and takes on different forms in jurisdictions around the world. RECs play an important role in governance, but only a partial role; it was deemed important for RECs to acknowledge how they fit within a broader governance ecosystem in order to more effectively address the issues within their scope. Not only RECs but organizational leaders responsible for procurement, researchers, and commercial actors should all commit to efforts to remain up to date about the relevant approaches to regulating AI for health care and public health in jurisdictions internationally. In this way, governance can more adequately remain up to date with advances in regulation.

Second, forum participants suggested that governance leaders should focus on ethical governance of health data as a basis for ethical global health AI research. Health data are considered the foundation of AI development, being used to train AI algorithms for various uses [ 26 ]. By focusing on ethical governance of health data generation, sharing, and use, multiple actors will help to build an ethical foundation for AI development among global health researchers.

Third, forum participants believed that governance processes should incorporate AI impact assessments where appropriate. An AI impact assessment is the process of evaluating the potential effects, both positive and negative, of implementing an AI algorithm on individuals, society, and various stakeholders, generally over time frames specified in advance of implementation [ 27 ]. Although not all types of AI research in global health would warrant an AI impact assessment, this is especially relevant for those studies aiming to implement an AI system for intervention into health care or public health. Organizations such as RECs can use AI impact assessments to boost understanding of potential harms at the outset of a research project, encouraging researchers to more deeply consider potential harms in the development of their study.

Fourth, forum participants suggested that governance decisions should incorporate the use of environmental impact assessments, or at least the incorporation of environment values when assessing the potential impact of an AI system. An environmental impact assessment involves evaluating and anticipating the potential environmental effects of a proposed project to inform ethical decision-making that supports sustainability [ 28 ]. Although a relatively new consideration in research ethics conversations [ 29 ], the environmental impact of building technologies is a crucial consideration for the public health commitment to environmental sustainability. Governance leaders can use environmental impact assessments to boost understanding of potential environmental harms linked to AI research projects in global health over both the shorter and longer terms.

Fifth, forum participants suggested that governance leaders should require stronger transparency in the development of AI algorithms in global health research. Transparency was considered essential in the design and development of AI algorithms for global health to ensure ethical and accountable decision-making throughout the process. Furthermore, whether and how researchers have considered the unique contexts into which such algorithms may be deployed can be surfaced through stronger transparency, for example in describing what primary considerations were made at the outset of the project and which stakeholders were consulted along the way. Sharing information about data provenance and methods used in AI development will also enhance the trustworthiness of the AI-based research process.

Sixth, forum participants suggested that governance leaders can encourage or require community engagement at various points throughout an AI project. It was considered that engaging patients and communities is crucial in AI algorithm development to ensure that the technology aligns with community needs and values. However, participants acknowledged that this is not a straightforward process. Effective community engagement requires lengthy commitments to meeting with and hearing from diverse communities in a given setting, and demands a particular set of skills in communication and dialogue that are not possessed by all researchers. Encouraging AI researchers to begin this process early and build long-term partnerships with community members is a promising strategy to deepen community engagement in AI research for global health. One notable recommendation was that research funders have an opportunity to incentivize and enable community engagement with funds dedicated to these activities in AI research in global health.

Seventh, forum participants suggested that governance leaders can encourage researchers to build strong, fair partnerships between institutions and individuals across country settings. In a context of longstanding imbalances in geopolitical and economic power, fair partnerships in global health demand a priori commitments to share benefits related to advances in medical technologies, knowledge, and financial gains. Although enforcement of this point might be beyond the remit of RECs, commentary will encourage researchers to consider stronger, fairer partnerships in global health in the longer term.

Eighth, it became evident that it is necessary to explore new forms of regulatory experimentation given the complexity of regulating a technology of this nature. In addition, the health sector has a series of particularities that make it especially complicated to generate rules that have not been previously tested. Several participants highlighted the desire to promote spaces for experimentation such as regulatory sandboxes or innovation hubs in health. These spaces can have several benefits for addressing issues surrounding the regulation of AI in the health sector, such as: (i) increasing the capacities and knowledge of health authorities about this technology; (ii) identifying the major problems surrounding AI regulation in the health sector; (iii) establishing possibilities for exchange and learning with other authorities; (iv) promoting innovation and entrepreneurship in AI in health; and (vi) identifying the need to regulate AI in this sector and update other existing regulations.

Ninth and finally, forum participants believed that the capabilities of governance leaders need to evolve to better incorporate expertise related to AI in ways that make sense within a given jurisdiction. With respect to RECs, for example, it might not make sense for every REC to recruit a member with expertise in AI methods. Rather, it will make more sense in some jurisdictions to consult with members of the scientific community with expertise in AI when research protocols are submitted that demand such expertise. Furthermore, RECs and other approaches to research governance in jurisdictions around the world will need to evolve in order to adopt the suggestions outlined above, developing processes that apply specifically to the ethical governance of research using AI methods in global health.

Research involving the development and implementation of AI technologies continues to grow in global health, posing important challenges for ethical governance of AI in global health research around the world. In this paper we have summarized insights from the 2022 GFBR, focused specifically on issues in research ethics related to AI for global health research. We summarized four thematic challenges for governance related to AI in global health research and nine suggestions arising from presentations and dialogue at the forum. In this brief discussion section, we present an overarching observation about power imbalances that frames efforts to evolve the role of governance in global health research, and then outline two important opportunity areas as the field develops to meet the challenges of AI in global health research.

Dialogue about power is not unfamiliar in global health, especially given recent contributions exploring what it would mean to de-colonize global health research, funding, and practice [ 30 , 31 ]. Discussions of research ethics applied to AI research in global health contexts are deeply infused with power imbalances. The existing context of global health is one in which high-income countries primarily located in the “Global North” charitably invest in projects taking place primarily in the “Global South” while recouping knowledge, financial, and reputational benefits [ 32 ]. With respect to AI development in particular, recent examples of digital colonialism frame dialogue about global partnerships, raising attention to the role of large commercial entities and global financial capitalism in global health research [ 21 , 22 ]. Furthermore, the power of governance organizations such as RECs to intervene in the process of AI research in global health varies widely around the world, depending on the authorities assigned to them by domestic research governance policies. These observations frame the challenges outlined in our paper, highlighting the difficulties associated with making meaningful change in this field.

Despite these overarching challenges of the global health research context, there are clear strategies for progress in this domain. Firstly, AI innovation is rapidly evolving, which means approaches to the governance of AI for health are rapidly evolving too. Such rapid evolution presents an important opportunity for governance leaders to clarify their vision and influence over AI innovation in global health research, boosting the expertise, structure, and functionality required to meet the demands of research involving AI. Secondly, the research ethics community has strong international ties, linked to a global scholarly community that is committed to sharing insights and best practices around the world. This global community can be leveraged to coordinate efforts to produce advances in the capabilities and authorities of governance leaders to meaningfully govern AI research for global health given the challenges summarized in our paper.

Limitations

Our paper includes two specific limitations that we address explicitly here. First, it is still early in the lifetime of the development of applications of AI for use in global health, and as such, the global community has had limited opportunity to learn from experience. For example, there were many fewer case studies, which detail experiences with the actual implementation of an AI technology, submitted to GFBR 2022 for consideration than was expected. In contrast, there were many more governance reports submitted, which detail the processes and outputs of governance processes that anticipate the development and dissemination of AI technologies. This observation represents both a success and a challenge. It is a success that so many groups are engaging in anticipatory governance of AI technologies, exploring evidence of their likely impacts and governing technologies in novel and well-designed ways. It is a challenge that there is little experience to build upon of the successful implementation of AI technologies in ways that have limited harms while promoting innovation. Further experience with AI technologies in global health will contribute to revising and enhancing the challenges and recommendations we have outlined in our paper.

Second, global trends in the politics and economics of AI technologies are evolving rapidly. Although some nations are advancing detailed policy approaches to regulating AI more generally, including for uses in health care and public health, the impacts of corporate investments in AI and political responses related to governance remain to be seen. The excitement around large language models (LLMs) and large multimodal models (LMMs) has drawn deeper attention to the challenges of regulating AI in any general sense, opening dialogue about health sector-specific regulations. The direction of this global dialogue, strongly linked to high-profile corporate actors and multi-national governance institutions, will strongly influence the development of boundaries around what is possible for the ethical governance of AI for global health. We have written this paper at a point when these developments are proceeding rapidly, and as such, we acknowledge that our recommendations will need updating as the broader field evolves.

Ultimately, coordination and collaboration between many stakeholders in the research ethics ecosystem will be necessary to strengthen the ethical governance of AI in global health research. The 2022 GFBR illustrated several innovations in ethical governance of AI for global health research, as well as several areas in need of urgent attention internationally. This summary is intended to inform international and domestic efforts to strengthen research ethics and support the evolution of governance leadership to meet the demands of AI in global health research.

Data availability

All data and materials analyzed to produce this paper are available on the GFBR website: https://www.gfbr.global/past-meetings/16th-forum-cape-town-south-africa-29-30-november-2022/ .

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Acknowledgements

We would like to acknowledge the outstanding contributions of the attendees of GFBR 2022 in Cape Town, South Africa. This paper is authored by members of the GFBR 2022 Planning Committee. We would like to acknowledge additional members Tamra Lysaght, National University of Singapore, and Niresh Bhagwandin, South African Medical Research Council, for their input during the planning stages and as reviewers of the applications to attend the Forum.

This work was supported by Wellcome [222525/Z/21/Z], the US National Institutes of Health, the UK Medical Research Council (part of UK Research and Innovation), and the South African Medical Research Council through funding to the Global Forum on Bioethics in Research.

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JS led the writing, contributed to conceptualization and analysis, critically reviewed and provided feedback on drafts of this paper, and provided final approval of the paper. JA contributed to conceptualization and analysis, critically reviewed and provided feedback on drafts of this paper, and provided final approval of the paper. CA contributed to conceptualization and analysis, critically reviewed and provided feedback on drafts of this paper, and provided final approval of the paper. PYC contributed to conceptualization and analysis, critically reviewed and provided feedback on drafts of this paper, and provided final approval of the paper. AE contributed to conceptualization and analysis, critically reviewed and provided feedback on drafts of this paper, and provided final approval of the paper. JWG contributed to conceptualization and analysis, critically reviewed and provided feedback on drafts of this paper, and provided final approval of the paper. AH contributed to conceptualization and analysis, critically reviewed and provided feedback on drafts of this paper, and provided final approval of the paper. DJ contributed to conceptualization and analysis, critically reviewed and provided feedback on drafts of this paper, and provided final approval of the paper. KL contributed to conceptualization and analysis, critically reviewed and provided feedback on drafts of this paper, and provided final approval of the paper. DP contributed to conceptualization and analysis, critically reviewed and provided feedback on drafts of this paper, and provided final approval of the paper. EV contributed to conceptualization and analysis, critically reviewed and provided feedback on drafts of this paper, and provided final approval of the paper.

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Shaw, J., Ali, J., Atuire, C.A. et al. Research ethics and artificial intelligence for global health: perspectives from the global forum on bioethics in research. BMC Med Ethics 25 , 46 (2024). https://doi.org/10.1186/s12910-024-01044-w

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New IREACH Leadership Aim to Deepen Community Partnerships, Foster WSU Collaborations

Amanda Boyd, PhD, and Denise Dillard, PhD, have assumed leadership of the Institute for Research and Education to Advance Community Health (IREACH) following the retirement of Founding Director Dedra Buchwald, MD, in March of this year. With this transition, they look forward to continuing the research institute’s work advancing community health through partnerships and collaboration.

“As a newcomer to Washington, I am particularly excited about building relationships with Indigenous communities in Washington state and to see IREACH overall expand and deepen work with local tribes,” Dr. Dillard said.

Part of the Washington State University Elson S. Floyd College of Medicine, IREACH promotes health and health care equity among Indigenous, rural, and other underserved populations using interdisciplinary research and education initiatives focused on community-identified needs. IREACH works with American Indian, Alaska Native, Native Hawaiian, Pacific Islander, and other Indigenous peoples, in particular studying how living in rural places shapes their health disparities.

Drs. Boyd and Dillard bring extensive experience conducting research with Indigenous communities to their roles.

Dr. Boyd is an associate professor in Department of Medical Education and Clinical Sciences and a member of the Métis Nation in Alberta, Canada. She has conducted health communication research with Indigenous communities since 2006, first in Canada and later the U.S. After joining WSU in 2013, she began working with IREACH in 2015 and became co-director in 2022.

A professor in the same department and member of the Inupiaq people, Dr. Dillard joined IREACH in January of 2023 as co-director after a 21-year career as a psychologist and later director of research for the nonprofit Tribal health organization Southcentral Foundation in Anchorage, Alaska.

Seeing firsthand the health disparities Indigenous populations experience spurred both into research careers. They view their role as serving these communities to reduce health disparities and improve the health and well-being of Indigenous people of all ages. They also to aim expand the number of Indigenous peoples involved in research.

The Indigenous cultural value of focusing on the collective over the individual shapes their approach to research and leadership. IREACH prioritizes building relationships with Indigenous communities and engaging them in the research process early on to earn their trust and ensure that the research is designed to address community needs and not just add to researchers’ CVs.

“Community members don’t care if you have a PhD or an MD. They really want to know, do you have a good heart and are you doing this work for the right reason?” Dr. Dillard said.  

Heading into a new chapter, the co-directors plan to spend more time on strategic planning for the organization with input from IREACH’s more than 85 faculty, staff, and postdoctoral students—part of a larger goal to reduce hierarchy within the organization.  

“At our core we’ve got such an amazing group of faculty and staff,” Dr. Boyd said. “It’s really exciting thinking about what we can do as a group and how we can also better integrate with WSU to partner more with the College of Medicine as well as the other colleges and centers around WSU.”

IREACH administratively joined the College of Medicine in August of 2023. With this change, the co-directors aim to foster more collaborations with other College of Medicine researchers. Being a part of the college also presents a unique opportunity to work with practicing clinicians and MD students to explore their perspective on the health needs of Indigenous communities in Washington. 

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Class of 2024: Medical student prepares to bring public health to primary care in Southwest Virginia

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Name: Lauren “LB” Canary

College: Virginia Tech Carilion School of Medicine

Major: Medicine

Hometown: Central Maryland

Plans after graduation: Enter medical residency program in family and community medicine at Carilion Clinic-Virginia Tech Carilion School of Medicine in Roanoke

Favorite Hokie Memory: Match Day when members of the Class of 2024 learned where they will be going for residency, the next phase of their journey to becoming a medical doctor

Canary received a Master of Public Health in epidemiology from Emory University and worked as an infectious disease epidemiologist for the Centers for Disease Control and Prevention. This was followed by a role in public health advocacy as director of the National Viral Hepatitis Roundtable. When applying to medical schools, she was attracted to the Virginia Tech Carilion School of Medicine for its commitment to health systems science, the beautiful surroundings of Roanoke, and the supportive culture among faculty.

Breaking down barriers, building up community health

Entering medical school during the COVID-19 pandemic, Canary supported local public health initiatives by volunteering with the Medical Reserve Corps to do contact tracing and implementing training for medical students to become certified to administer the vaccine in the community. She partnered with patients, physicians, and community providers to launch the Virginia Hepatitis Coalition, which successfully advocated for the removal of Medicaid prior authorization requirements for hepatitis C treatment.

Canary has been active in the Virginia Harm Reduction Coalition, a syringe exchange program located in Roanoke, even bringing a car full of supplies with her when she came to Roanoke for her medical school interview. During her preclinical years, she accompanied various harm reduction participants to emergency room visits and doctor’s appointments.

Canary fostered opportunities for medical students to interact with community members they may not see in the clinic, by inviting them to join her in street outreach and hosting overdose reversal and hepatitis C testing trainings.

“I wanted to be able to help medical students understand what people are facing, how hard it is to get to a doctor’s appointment, and overall start to break down the stigma that has negatively impacted the health care of some of these clients,” she said.

Recently, Canary partnered with Virginia Department of Health District Director and health systems science Professor Cynthia Morrow, Carilion Family Medicine Residency Program Director Mary Beth Sweet, and Danny Clawson, director of the Virginia Harm Reduction Coalition and Canary’s wife, to launch an on-site wound care pilot program. The program provides participants with earlier intervention and helps family medicine residents learn more about patients experiencing homelessness and substance use.

Inspiration for a heart of service

Inspired to support those experiencing poverty, in part through her own life experiences , Canary serves on the board of directors of RAM House, a day shelter serving unstably housed residents in Roanoke. As a National Health Service Corps scholar she will continue working with medically underserved patients after her residency program.

Following graduation, Canary will embark on a residency in family and community medicine at Carilion Clinic-Virginia Tech Carilion School of Medicine. She will take the support and guidance of a number of mentors along the way, one in particular is Brian Unwin, professor of internal and family and community medicine and geriatric medicine specialist at Carilion Clinic.

As a physician dedicated to patient care, Unwin often makes house calls to patients who have difficulty getting to him. As part of her family medicine rotation, Canary was able to accompany him on occasion.

“Dr. Unwin is committed to meeting his patients where they are,” Canary said. “He recognizes the benefits of seeing patients in their environment. That’s the kind of doctor I want to be.”

Unwin said, “LB is the kind of human I want to be. She cares about the dignity of every human being and is particularly passionate about the care of the disenfranchised. We are blessed to have her stay in southwest Virginia.”

Leadership and accolades

During medical school, Canary has served on the board of directors for the Virginia Academy of Family Physicians and medical school's curricular committee as it reimagines preclinical training.

“I’m excited for the opportunity to stay engaged and support growth of pipelines for students interested in primary care to stay in Southwest Virginia for residency,” she said.

She also is excited about engaging LGBTQ students in medicine, having created a chapter of the Medical Student Pride Alliance during her time in medical school. As a fourth-year student, she has supported leadership opportunities for first-year students with whom she has launched free LGBTQ youth tutoring, syringe access for trans patients in hormone replacement therapy, and med student community engagement with the Roanoke Diversity Center and Blue Ridge Pride Sports league. During residency, she plans to stay engaged in advising the club and in growing LGBTQ inclusive care in Roanoke.

For her commitment to public health during her medical training Canary was awarded the 2024 United States Public Health Service Physician Professional Advisory Committee Excellence in Public Health Award.

Canary has garnered accolades during medical school, including the Medical Society of Virginia Salute to Service award, the Leonard Tow Humanism in Medicine award, and acceptance into the Alpha Omega Alpha and Gold Humanism honor societies.

Of all her experiences though, Canary notes she is most proud of her role as a caregiver for her mother during her four-year battle with lung cancer. Unfortunately, her mother passed away during Canary’s first months of medical school.

“Having instilled in me a desire to serve those less fortunate, my mother’s spirit will be with me in every step of my career.”

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Annual skilled trades competition builds technical and professional skills for Iowa students

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Southeast Polk senior Simon Frohock (R) competed in the cabinet making contest for a second year.

High-quality career and professional skill development took center stage last week as over 600 high school and college students took part in the annual SkillsUSA State Leadership and Skills Conference . Held in Ankeny at the Des Moines Area Community College campus, this two-day competition featured over 50 different leadership and technical competitions for students to test their technical skills and knowledge, explore career pathways and make valuable connections with local industry leaders.

Southeast Polk High School seniors Delvis Kouete and Simon Frohock, both 17, were well-prepared for the competition, which featured timed activities related to industrial technology, carpentry, robotics, automotive repair and job interview techniques, among many others. For this year’s skills competition, Delvis competed in architectural drafting and was a member of the school’s quiz bowl team. Simon, the 2023 state champion in cabinet making, returned for a second year in the cabinet making contest. Both students competed well in their individual competitions, with Delvis placing fifth and Simon serving as this year’s runner-up.

“The skills competition can help you strive for excellence in your work and learning,” Simon said. “Even though it’s a competition and there is pressure to do well, it’s a good, low-risk way to see what an employee in this work has to do every day.”

Both Simon and Delvis noted that the competition not only helps to strengthen a student’s technical skills, but it also engages students in career pathway discovery and professional skill development.

“Being a part of SkillsUSA and competing in the skills competition has helped me learn new skills with my hands and work on teamwork, communication and leadership skills,” Delvis said. “You learn how to work with other people that aren’t like you and get your mind thinking about your future career.”

Along with the individual contests, all competitors at the SkillsUSA State Leadership and Skills Conference were required to submit a resume and take a professional development test that focused on workplace, professional and technical skills as well as overall knowledge of SkillsUSA.

“SkillsUSA helps provide real-world context to the content being taught by classroom educators,” said Kent Storm, state director for SkillsUSA Iowa. “Taking the learning beyond the classroom allows students to grow and learn next to industry partners and gain valuable experience."

As one of Iowa’s career and technical student organizations (CTSO) , SkillsUSA champions the skilled trades industry and provides opportunities for students to apply the skills they have developed in classrooms through conferences, competitions, community service events, worksite visits and other activities.

“Participation in a CTSO like SkillsUSA helps students gain hands-on experience and connect classroom curricula to careers,” said Cale Hutchings, education consultant at the Iowa Department of Education. “Through CTSOs, students can become leaders and strengthen their employability skills, which is valuable as they explore potential next steps in their college and career pathways.”

SkillsUSA boasts a roster of over 400,000 members nationwide. In Iowa, over 1,300 students and advisers in career and technical education programs participate in local SkillsUSA chapters.

At Southeast Polk, 21 student members are a part of their SkillsUSA chapter. Led by industrial technology teachers and chapter advisers Ryan Andersen and Brett Rickabaugh, the students have been involved with several community service projects, employer presentations and opportunities to work closely with instructors.

“Any time a student participates in SkillsUSA, it gives us more time with that student to elaborate on what we’ve learned in class,” Andersen said. “They can connect the idea to the planning, design and completion of a project and how that activity fits into a real career. That’s something we can’t replicate without a CTSO.”

Anderson also stated that students who participate in SkillsUSA and activities like the State Leadership and Skills Conference build confidence through their experiences.

“It really helps students to have the confidence to rely on their skills and what they know,” he said. “The skills competition requires them to use problem-solving skills and build off their knowledge to continue to learn and persevere.”

This year’s first-place winners at the SkillsUSA State Leadership and Skills Conference will move onward to compete with 6,000 other students at the national conference in Atlanta this June.

For Simon and Delvis, the skills competition was another step in building necessary skills and acumen for their futures. Simon, with his penchant for cabinet making, already has a full-time job lined up after graduation with a local cabinet shop. Additionally, Delvis would like to pursue something within the computer science field, perhaps in the coding or software engineering areas, and although he is changing fields, he believes SkillsUSA has helped him feel more prepared for the future.

“It has definitely helped me with skill-building and problem-solving,” he said. “What I’ve learned will be beneficial no matter what I decide to do next.”