The modern health sector is highly digitized [1]. As a result, health care professionals, consumers, and other stakeholders interact with a plethora of commonly used digital health technologies [2-4]. One widely used technology in the health sector is electronic health records (EHRs) and electronic medical records (EMRs), which are types of clinical information systems that serve as sources of patient health information. They are designed for use by health care professionals to capture data reflecting specific clinical experiences [5]. The data that clinical information systems including EHRs and EMRs collect have great potential for a range of secondary applications, including research, informing policy, and quality improvement [6,7]. However, these systems are currently underused for secondary applications such as Continuing Professional Development (CPD), practice reflection, personalized workplace learning, and insights about their performance [8,9].

CPD, reflective practice, and lifelong learning are essential activities for health care professionals to stay up to date on the latest evidence and maintain their registration to practice [1]. Health care professionals engage in a variety of learning activities, including attending local or international conferences, participating in mentorship and peer review, joining seminars, journal clubs, and other activities [10]. A large portion of these activities also takes the form of workplace learning [11]. The workplace provides a unique environment and a unique instructional context that is often focused on informal and experiential learning [12] to help overcome workplace problems or improve performance [12]. It can also offer a range of formal and informal pathways for receiving performance feedback. Although much of the learning that health care professionals engage in takes place in the workplace, there is a dearth of research on how to align learning activities with the clinical environment and on the pedagogical value of doing so. One mechanism to support data-driven professional development and enable better-aligned workplace learning is the utilization of data from EHRs and EMRs for the personalization of digital workplace education, data-driven CPD, or supporting reflective practice [8].

EHRs are sources of electronic health data that are increasingly being implemented in health care [13]. Existing enterprise-level systems focus on the use of their data for immediate patient care and billing, with a particular focus on recording patient information, including patient demographics, progress notes, medication, and laboratory results, which is generated by one or more encounters in any health care delivery setting [5]. The primary intent of EHRs is to provide data on patient care and health care operations; however, there is an increasing desire to explore the secondary use of data from clinical information systems in nondirect care operations, such as research, analytics, and measurements of quality and safety. In this context, they have been used for projects, such as research using population-wide data on cancer patient experiences and therapy outcomes [6], and quality improvement activities, such as toxicity monitoring and symptom management of chemotherapy treatments [7].

One underexplored secondary use of EHRs and EMRs is to support health care professional learning, performance review, and reflective practice. Reflective practice is the process by which professionals review and reflect on past experiences to gain understanding and identify opportunities for potential improvement [14]. While modern EHRs increasingly incorporate feedback through clinical decision support systems and dashboards, less work has focused on how EHRs can more effectively use onboard data to support reflective practice and health care professional learning. However, interest in better using clinical information systems is increasing, with a small but growing body of research in an area termed “Practice Analytics” [15-17]. Practice analytics seeks to equip health care professionals, their workplaces, and their associated peak bodies with the data and tools needed to review their own clinical practice [16]. Literature related to the use of electronic health data to date indicates that, when used correctly, it can help health care professionals understand their performance [7]. Further, it indicates that health care professionals themselves would like to access these data for learning purposes [9]. However, it has also been noted that health care professionals currently have varied access to these data for understanding their performance, and there is considerable variation in the ways it is visualized and shared with them [18].

The aim of this project is to determine how EHRs and EMRs can be leveraged to enable formative performance feedback for health care professionals. Over the course of the project, the researchers aim to understand how health care professionals are currently using EMRs and EHRs to support their practice, what the role of these technologies is in performance feedback and reflective practice of medical practitioners, and how the design of these technologies can be rethought to support a “next-generation” EHR that could support reflective practice. This project has been designed to build upon existing literature in the field of practice analytics and beyond, indicating that clinical information systems could better facilitate health care professional learning [19]; however, current solutions are not well-designed to do so [20]. This work is particularly timely, as global work is being undertaken to develop next-generation EHRs and EMRs [21]. This provides a unique opportunity to design new systems that incorporate interface design and scaffolds, ensuring that EHRs not only use data for direct patient care but also provide data back to health care professionals and teams for performance review and to support evidence-based practice. There is not only technological innovation driving change in this space but also an evolution of the policy landscape regarding how health care professionals engage in learning activities. Policies are increasingly encouraging health care professionals to better use electronic data collected from repositories, such as EHRs, as a component of mandated CPD and for revalidation [22].

A mixed methodology is being used to undertake the project, as this methodology is the most appropriate for answering the individual aims of the study. Mixed methodologies are particularly beneficial for balancing out the limitations of qualitative and quantitative methodologies and are particularly important for getting a holistic picture of participant behaviors [23]. The methodology is particularly aligned with the project described in this proposal, as it will not only enable the collection of data on what people do but also provide a rich understanding of why these behaviors occur [23].

The project will be undertaken in 3 phases: needs finding (phase 1), prioritization (phase 2), and key informant consultation (phase 3). For an overview of the research flow, refer to Figure 1. The protocol follows recommendations listed in the TIDieR (Template for Intervention Description and Replication) checklist [24] (Multimedia Appendix 1).

The study received ethics approval from the University of Sydney Human Research Ethics Committee (protocol number 2024/HE000253). All participants will provide written informed consent before participating in the study. All data will be deidentified prior to analysis. Participants do not receive compensation for participation in the study.

This protocol describes a methodology for undertaking a mixed methods study designed to generate insights on how next-generation EMRs and EHRs could better support health care professional learning. The study is undertaking a triphasic approach consisting of phase 1 (needs finding), phase 2 (prioritization), and phase 3 (key informant consultation). This approach is being used to obtain a rich understanding of the complex challenges of designing clinical information systems that support reflective practice, understanding of health care professional performance, and workplace learning. It has been recognized that there is a notable knowledge gap on the secondary use of clinical information systems like EMRs and EHRs for enabling health care professionals to gain insights into their performance [9,20]. Furthermore, policy changes are increasingly encouraging health care professionals to use data from these types of systems to chart data and set goals; however, there are few evidence-based methods for providing feedback to support professional learning and reflective practice [17].

The findings from this study will expand the understanding of the methodologies that can be used effectively in the relatively new field of practice analytics. There is currently only one protocol published presenting a practice analytics methodology [15], which emphasizes the need to use multidisciplinary approaches for delivery on a large-scale program. The study described in this protocol builds on the existing methodological approaches used in practice analytics, incorporating multidisciplinary methods, such as needs finding interviews and key informant workshops, to gain a deeper understanding of how technology design and human interaction with it could be used to enable workplace-based learning in the area of practice analytics. A triphasic approach is being used to identify health care professionals’ needs for EHRs that enable reflective practice and workplace learning, prioritize features that are most conducive to this process, and then aggregate key stakeholder perspectives on how these priorities could be harnessed in a next-generation EHR or EMR design.

Finally, this study aims to generate new insights on how next-generation EHRs and EMRs could be designed to better support performance feedback, workplace learning, and data-driven CPD. The literature to date has identified that health care professionals have an interest in accessing more data about their practice from clinical information systems [9], and there is advocacy for enhancing existing clinical information systems to better facilitate health care professional learning [19]. Despite this interest, there is notable variation in current approaches for visualizing and sharing these data with health care professionals [8], and there are few examples of best-practice approaches for designing clinical information systems that support reflective practice [20]. The study described in this protocol aims to address this gap by generating new knowledge on how one type of clinical information system, EHRs and EMRs, could be better used to support workplace learning, reflective practice, and performance feedback.

A limitation of this study is that we are using a convenience sample, largely recruited from Australia, for the first 2 phases of the study, which may limit the generalizability of our findings across health professions and geographic regions. This limitation is being mitigated by undertaking extensive recruitment via a breadth of channels in an attempt to reach participants with a breadth of insights. An additional potential limitation is not focusing on a single EMR or EHR as part of recruitment for this study, as this may also influence the generalizability of findings. The researchers decided not to take this approach because these records have limited use in supporting reflective practice. We aimed to obtain a broad range of insights into how health care professionals are using these systems, and focusing on only the most commonly used enterprise solutions could exclude valuable insights from bespoke EMRs, EHRs, or smaller systems. Future researchers should consider undertaking a study looking specifically at larger enterprise systems for supporting reflective practice.

EHRs are increasingly prevalent in the health sector, and their implementation and ongoing support often represent a significant financial investment. They are a unique repository of electronic health data that has a plethora of potential uses in health professions. One underexplored use of EHRs and the data they collect is to enable health care professionals to understand their performance and engage in data-driven learning activities. Increased understanding of the extent to which these workplace technologies provide health care professionals formative performance feedback is important in order to understand opportunities to design and use these technologies more effectively to support reflective practice in the future.