Data sharing and big data in health professions education: Ottawa consensus statement and recommendations for scholarship.

Changes in digital technology, increasing volume of data collection, and advances in methods have the potential to unleash the value of big data generated through the education of health professionals. Coupled with this potential are legitimate concerns about how data can be used or misused in ways that limit autonomy, equity, or harm stakeholders. This consensus statement is intended to address these issues by foregrounding the ethical imperatives for engaging with big data as well as the potential risks and challenges. Recognizing the wide and ever evolving scope of big data scholarship, we focus on foundational issues for framing and engaging in research. We ground our recommendations in the context of big data created through data sharing across and within the stages of the continuum of the education and training of health professionals. Ultimately, the goal of this statement is to support a culture of trust and quality for big data research to deliver on its promises for health professions education (HPE) and the health of society. Based on expert consensus and review of the literature, we report 19 recommendations in (1) framing scholarship and research through research, (2) considering unique ethical practices, (3) governance of data sharing collaborations that engage stakeholders, (4) data sharing processes best practices, (5) the importance of knowledge translation, and (6) advancing the quality of scholarship through multidisciplinary collaboration. The recommendations were modified and refined based on feedback from the 2022 Ottawa Conference attendees and subsequent public engagement. Adoption of these recommendations can help HPE scholars share data ethically and engage in high impact big data scholarship, which in turn can help the field meet the ultimate goal: high-quality education that leads to high-quality healthcare.

Validity evidence and psychometric evaluation of a socially accountable health index for health professions schools.

There is an expectation that health professions schools respond to priority societal health needs. This expectation is largely based on the underlying assumption that schools are aware of the priority needs in their communities. This paper demonstrates how open-access, pan-national health data can be used to create a reliable health index to assist schools in identifying societal needs and advance social accountability in health professions education. Using open-access data, a psychometric evaluation was conducted to examine the reliability and validity of the Canadian Health Indicators Framework (CHIF) conceptual model. A non-linear confirmatory factor analysis (CFA) on 67 health indicators, at the health-region level (n = 97) was used to assess the model fit of the hypothesized 10-factor model. Reliability analysis using McDonald's Omega were conducted, followed by Pearson's correlation coefficients. Findings from the non-linear CFA rejected the original conceptual model structure of the CHIF. Exploratory post hoc analyses were conducted using modification indices and parameter constraints to improve model fit. A final 5-factor multidimensional model demonstrated superior fit, reducing the number of indicators from 67 to 32. The 5-factors included: Health Conditions (8-indicators); Health Functions (6-indicators); Deaths (5-indicators); Non-Medical Health Determinants (7-indicators); and Community & Health System Characteristics (6-indicators). All factor loadings were statistically significant (p < 0.001) and demonstrated excellent internal consistency ( ω >0.95). Many schools struggle to identify and measure socially accountable outcomes. The process highlighted in this paper and the indices developed serve as starting points to allow schools to leverage open-access data as an initial step in identifying societal needs.

The Certificate of Added Competence credentialling program in family medicine: a descriptive survey of the family physician perspective of enhanced skill practices in Canada.

Introduction: The College of Family Physicians of Canada (CFPC) offers the Certificate of Added Competence (CAC) program to designate a family physician with enhanced skills. In 2015, the College expanded its program to introduce enhanced certification in four new domains: Palliative Care, Care of the Elderly, Sports and Exercise Medicine, and Family Practice Anesthesia. In this study, we elicited perceptions from Canadian family physicians with and without the CAC on practice impacts associated with the program. Methods: Active family physicians in Canada with and without CACs were surveyed between November 2019 to January 2020. Descriptive statistics were generated to describe the perceptions of family physicians regarding the CAC program and its impacts on practice. Results: Respondents agreed with several benefits of the program including enhancing the capacity to deliver comprehensive care, alleviating the burden of patient travel by increasing the availability of care in rural and remote communities, and providing opportunities to engage in various collaborative care models and new leadership roles. All respondents perceived CAC holders to pursue the certificate to meet both professional interests and community needs. Conclusions: There is a need for strong and continued investment in systemic practice improvements that incentivize the delivery of comprehensive family medicine practice.

Introduction: Le certificat de compétence additionnelle (CCA) accordé par le Collège des médecins de famille du Canada (CMFC) vise à reconnaître un haut niveau de compétences chez un médecin de famille. En 2015, le Collège a élargi le titre de compétences additionnelles à quatre nouveaux domaines : soins palliatifs, soins aux personnes âgées, médecine du sport et de l'exercice, et anesthésie en médecine familiale. Dans cette étude, nous avons recueilli les perceptions de médecins de famille titulaires et non titulaires d'un CCA sur l'influence de pratiques associées au programme de certification. Méthodes: Des médecins de famille actifs au Canada, titulaires et non titulaires du CCA, ont été interrogés entre novembre 2019 et janvier 2020. Des statistiques descriptives ont été générées pour décrire leurs perceptions concernant le Certificat et ses impacts sur la pratique. Résultats: Les répondants s'entendaient pour reconnaître au CCA plusieurs avantages, notamment le fait d'améliorer la capacité des médecins à fournir des soins complets, de leur offrir la possibilité de s'engager dans divers modèles de soins collaboratifs et de nouveaux rôles de leadership, et d'alléger le fardeau des déplacements des patients en augmentant la disponibilité des soins dans les populations rurales et éloignées. Tous les répondants estiment que les médecins recherchent l'obtention de ce titre de compétence pour répondre à la fois à leurs intérêts professionnels et aux besoins de la collectivité. Conclusions: Il faut investir de manière importante et continue dans des améliorations systémiques qui favoriseront une pratique holistique de la médecine familiale.

Global Perceptions on Social Accountability and Outcomes: A Survey of Medical Schools.

Phenomenon: Social accountability has become a universal component in medical education. However, medical schools have little guidance for operationalizing and applying this concept in practice. This study explored institutional practices and administrative perceptions of social accountability in medical education. Approach: An online survey was distributed to a purposeful sample of English-speaking undergraduate medical school deans and program directors/leads from 245 institutions in 14 countries. The survey comprised of 38-items related to program mission statements, admission processes, curricular content, and educational outcomes. Survey items were developed using previous literature and categorized using a context-input-process-products (CIPP) evaluation model. Exploratory Factor Analysis (EFA) was used to assess the inter-relationship among survey items. Reliability and internal consistency of items were evaluated using McDonald's Omega. Findings: Results from 81 medical schools in 14 countries collected between February and June 2020 are presented. Institutional commonalities of social accountability were observed. However, our findings suggest programs focus predominately on educational inputs and processes, and not necessarily on outcomes. Findings from our EFA demonstrated excellent internal consistency and reliability. Four-factors were extracted: (1) selection and recruitment; (2) institutional mandates; (3) institutional activities; and (4) community awareness, accounting for 71% of the variance. McDonald's Omega reliability estimates for subscales ranged from 0.80-0.87. Insights: This study identified common practices of social accountability. While many medical schools expressed an institutional commitment to social accountability, their effects on the community remain unknown and not evaluated. Overall, this paper offers programs and educators a psychometrically supported tool to aid in the operationalization and reliability of evaluating social accountability.

Associations between admissions factors and the need for remediation.

This study examines the way in which student characteristics and pre-admissions measures are statistically associated with the likelihood a student will require remediation for academic and professionalism offenses. We anchor our inquiry within Irby and Hamstra's (2016) conceptual framework of constructs of professionalism. Data from five graduating cohorts (2014-2018) from McMaster University (Hamilton, Canada) (N = 1,021) were retroactively collected and analyzed using traditional and multinominal logistic regression analyses. The relationship among student characteristics, pre-admissions variables, and referral for potential remediation both by occurrence (yes/no) as well as type (academic/professional/no referral) were examined separately. Findings indicate that gender (OR = 0.519, 95% CI 0.326-0.827, p < 0.01) and undergraduate grade point average (GPA) (OR = 0.245, 95% CI 0.070-0.855, p < 0.05) were significantly associated with instances of referral for potential professionalism and academic remediation, respectively. Women were less likely than men to require remediation for professionalism (OR = 0.332, 95% CI 0.174-0.602, p < 0.001). Undergraduate GPAs (OR = 0.826, 95% CI 0.021-0.539, p < 0.01) were significantly associated with remediation for academic reasons. Lower undergraduate GPAs were associated with a higher likelihood of remediation. These findings point to the admissions variables that are associated with instances that prompt referral for potential remediation. Where associations are not significant, we consider the application of different conceptualizations of professionalism across periods of admissions and training. We encourage those involved in applicant selection and student remediation to emphasize the importance of the interactions that occur between personal and contextual factors to influence learner behaviour and professional identity formation.

Social Accountability Frameworks and Their Implications for Medical Education and Program Evaluation: A Narrative Review.

PURPOSE: Medical schools face growing pressures to produce stronger evidence of their social accountability, but measuring social accountability remains a global challenge. This narrative review aimed to identify and document common themes and indicators across large-scale social accountability frameworks to facilitate development of initial operational constructs to evaluate social accountability in medical education. METHOD: The authors searched 5 electronic databases and platforms and the World Wide Web to identify social accountability frameworks applicable to medical education, with a focus on medical schools. English-language, peer-reviewed documents published between 1990 and March 2019 were eligible for inclusion. Primary source social accountability frameworks that represented foundational values, principles, and parameters and were cited in subsequent papers to conceptualize social accountability were included in the analysis. Thematic synthesis was used to describe common elements across included frameworks. Descriptive themes were characterized using the context-input-process-product (CIPP) evaluation model as an organizational framework. RESULTS: From the initial sample of 33 documents, 4 key social accountability frameworks were selected and analyzed. Six themes (with subthemes) emerged across frameworks, including shared values (core social values of relevance, quality, effectiveness, and equity; professionalism; academic freedom and clinical autonomy) and 5 indicators related to the CIPP model: context (mission statements, community partnerships, active contributions to health care policy); inputs (diversity/equity in recruitment/selection, community population health profiles); processes (curricular activities, community-based clinical training opportunities/learning exposures); products (physician resource planning, quality assurance, program evaluation and accreditation); and impacts (overall improvement in community health outcomes, reduction/prevention of health risks, morbidity/mortality of community diseases). CONCLUSIONS: As more emphasis is placed on social accountability of medical schools, it is imperative to shift focus from educational inputs and processes to educational products and impacts. A way to begin to establish links between inputs, products, and impacts is by using the CIPP evaluation model.

A Call to Investigate the Relationship Between Education and Health Outcomes Using Big Data.

There exists an assumption that improving medical education will improve patient care. While seemingly logical, this premise has rarely been investigated. In this Invited Commentary, the authors propose the use of big data to test this assumption. The authors present a few example research studies linking education and patient care outcomes and argue that using big data may more easily facilitate the process needed to investigate this assumption. The authors also propose that collaboration is needed to link educational and health care data. They then introduce a grassroots initiative, inclusive of universities in one Canadian province and national licensing organizations that are working together to collect, organize, link, and analyze big data to study the relationship between pedagogical approaches to medical training and patient care outcomes. While the authors acknowledge the possible challenges and issues associated with harnessing big data, they believe that the benefits supersede these. There is a need for medical education research to go beyond the outcomes of training to study practice and clinical outcomes as well. Without a coordinated effort to harness big data, policy makers, regulators, medical educators, and researchers are left with sometimes costly guesses and assumptions about what works and what does not. As the social, time, and financial investments in medical education continue to increase, it is imperative to understand the relationship between education and health outcomes.

In Search of Black Swans: Identifying Students at Risk of Failing Licensing Examinations.

PURPOSE: To determine which admissions variables and curricular outcomes are predictive of being at risk of failing the Medical Council of Canada Qualifying Examination Part 1 (MCCQE1), how quickly student risk of failure can be predicted, and to what extent predictive modeling is possible and accurate in estimating future student risk. METHOD: Data from five graduating cohorts (2011-2015), Schulich School of Medicine & Dentistry, Western University, were collected and analyzed using hierarchical generalized linear models (HGLMs). Area under the receiver operating characteristic curve (AUC) was used to evaluate the accuracy of predictive models and determine whether they could be used to predict future risk, using the 2016 graduating cohort. Four predictive models were developed to predict student risk of failure at admissions, year 1, year 2, and pre-MCCQE1. RESULTS: The HGLM analyses identified gender, MCAT verbal reasoning score, two preclerkship course mean grades, and the year 4 summative objective structured clinical examination score as significant predictors of student risk. The predictive accuracy of the models varied. The pre-MCCQE1 model was the most accurate at predicting a student's risk of failing (AUC 0.66-0.93), while the admissions model was not predictive (AUC 0.25-0.47). CONCLUSIONS: Key variables predictive of students at risk were found. The predictive models developed suggest, while it is not possible to identify student risk at admission, we can begin to identify and monitor students within the first year. Using such models, programs may be able to identify and monitor students at risk quantitatively and develop tailored intervention strategies.