Frameworks for Integrating Learning Analytics With the Electronic Health Record

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.

Five Domains of a Conceptual Framework of Continuing Professional Development

ABSTRACT

Continuing professional development (CPD) for health professionals involves efforts at improving health of individuals and the population through educational activities of health professionals who previously attained a recognized level of acceptable proficiency (licensure). However, those educational activities have inconsistently improved health care outcomes of patients. We suggest a conceptual change of emphasis in designing CPD to better align it with the goals of improving health care value for patients through the dynamic incorporation of five distinct domains to be included in learning activities. We identify these domains as: (1) identifying, appraising, and learning new information [New Knowledge]; (2) ongoing practicing of newly or previously acquired skills to maintain expertise [New Skills and Maintenance]; (3) sharing and transfer of new learning for the health care team which changes their practice [Teams]; (4) analyzing data to identify problems and drive change resulting in improvements in the health care system and patient outcomes [Quality Improvement]; and (5) promoting population health and prevention of disease [Prevention]. We describe how these five domains can be integrated into a comprehensive conceptual framework of CPD, supported by appropriate learning theories that align with the goals of the health care delivery system. Drawing on these distinct but interrelated areas of CPD will help organizers and directors of learning events to develop their activities to meet the goals of learners and the health care system.

Ethical use of Artificial Intelligence in Health Professions Education: AMEE Guide No. 158

Health Professions Education (HPE) has benefitted from the advances in Artificial Intelligence (AI) and is set to benefit more in the future. Just as any technological advance opens discussions about ethics, so the implications of AI for HPE ethics need to be identified, anticipated, and accommodated so that HPE can utilise AI without compromising crucial ethical principles. Rather than focussing on AI technology, this Guide focuses on the ethical issues likely to face HPE teachers and administrators as they encounter and use AI systems in their teaching environment. While many of the ethical principles may be familiar to readers in other contexts, they will be viewed in light of AI, and some unfamiliar issues will be introduced. They include data gathering, anonymity, privacy, consent, data ownership, security, bias, transparency, responsibility, autonomy, and beneficence. In the Guide, each topic explains the concept and its importance and gives some indication of how to cope with its complexities. Ideas are drawn from personal experience and the relevant literature. In most topics, further reading is suggested so that readers may further explore the concepts at their leisure. The aim is for HPE teachers and decision-makers at all levels to be alert to these issues and to take proactive action to be prepared to deal with the ethical problems and opportunities that AI usage presents to HPE.

Using eHealth Data to Inform CPD for Medical Practitioners: A Scoping Review with a Consultation Exercise with International Experts

INTRODUCTION

eHealth data analytics is widely used in health care research. However, there is limited knowledge on the role of eHealth data analysis to inform continuing professional development (CPD). The aim of this study was to collate available research evidence on the use of eHealth data for the development of CPD programs and plans for medical practitioners.

METHODS

A scoping review was conducted using the six-stage Arksey and O'Malley Framework. A consultation exercise (stage 6) was performed with 15 international experts in the fields of learning and practice analytics to deepen the insights.

RESULTS

Scoping review. The literature searches identified 9876 articles published from January 2010 to May 2022. After screening and full-text review, a total of nine articles were deemed relevant for inclusion. The results provide varied-and at times partial or diverging-answers to the scoping review research questions. Consultation exercise. Research rigor, field of investigation, and developing the field were the three themes emerged from analysis. Participants validated the scoping review methodology and confirmed its results. Moreover, they provided a meta-analysis of the literature, a description of the current CPD ecosystem, and clear indications of what is and should be next for the field.

DISCUSSION

This study shows that there is no formal or well-established correlation between eHealth data and CPD planning and programming. Overall findings fill a gap in the literature and provide a basis for further investigation. More foundational work, multidisciplinary collaborations, and stakeholders' engagement are necessary to advance the use of eHealth data analysis for CPD purposes.