The COVID-19 pandemic heralded a transformation in care delivery to virtual services and digital technologies such as telemedicine, remote patient monitoring, and asynchronous patient portal communications. This transition, coupled with the growing field of “Big Data” informatics and generative artificial intelligence (“GenAI”), has reinvigorated enthusiasm in the “digital transformation” of health care [1] and the use of novel digital technologies to provide personalized, convenient, and comprehensive care for all. It has also resulted in calls to improve the “digital health competencies” of clinicians, to help both current health care providers and trainees meet this transformative moment in care delivery [2-4].

Digital health tools—which include a wide range of “virtual” technologies such as telemedicine, remote sensors, and wearables, as well as medical “apps” and eHealth and mobile health tools, digitized health record and communications platforms (electronic health records [EHRs] and patient portals), clinical decision support systems, and personalized and predictive modeling technologies [5]—have been progressively integrated into mechanisms of care delivery over the last decade, with growing support from both patients and clinicians [3,6,7]. Patient empowerment and self-management are factors that contribute to patient use of digital health [8]. In the United States, 93% of physicians believe digital health tools are an advantage for patient care, with the majority citing a desire to provide competent remote care to patients as a significant motivator to adopt digital tools [6].

Among medical trainees, sentiments around use of digital health technologies are similar, with these technologies increasingly becoming inseparable from medical training [9,10]. This trend accelerated during the COVID-19 pandemic, as resident clinics pivoted to telemedicine and training shifted to virtual conferences, e-learning modules, and telesimulation [11,12]; nursing and other allied health professions saw similar shifts in their own education and care delivery experiences [13,14]. This dramatically shifted environment has created an appetite for both learning and teaching digital health skills among medical trainees, while also exposing gaps in current approaches to curricular development, implementation, and evaluation [3,4,15-17]. At the same time, there is growing recognition of the equity risks associated with digital health technology [18,19], particularly as the use of these tools was expanded during the pandemic and disparities in access and proficiency widened existing health care inequalities [18,20-22]. This reality underscores the need to cultivate a health care workforce that is both technically and culturally competent, as well as to better integrate health equity efforts in clinical training.

This paper explores the current state of digital health education and training competencies among medical and allied health professions through a brief narrative review and identifies key limitations in these approaches. We then offer a novel framework—the digital determinants of health (DDoH)—that can help unify and direct ongoing competency development and evaluation efforts. The DDoH framework can also ensure that key equity considerations of digital health are incorporated into trainee competencies, thereby helping reduce disparities associated with this these technologies’ use.

At its core, the challenge of teaching digital health competencies to medical trainees lies in the lack of consensus regarding what those competencies are and how they should be taught. While several major medical organizations in the United States and internationally have released statements [23-25] regarding some element of digital health competencies at undergraduate, graduate, and professional continuing medical education levels, significant heterogeneity exists in these organizations’ definitions, areas of focus, and evaluation tools and metrics (Table 1). A brief narrative review of the current medical literature on the topic of “digital health training” reveals both vagueness and variability in the definition of “digital health,” with overrepresentation of language from biomedical informatics, health information technology, and telemedicine. Often, only general recommendations for training competency domains (eg, patient safety and medical knowledge) are offered, rather than any specific competencies. Existing instruments to measure competencies often focus on specific use cases (eg, EHR proficiency) rather than the broad-scope digital health tools and services that exist today [2]. Many instruments are not validated, being either adapted from previously developed tools or newly designed to meet the changing technological landscape and educational needs [2].

This state of ambiguity has resulted in an uneven and ad hoc approach to digital health education programming in undergraduate and graduate training institutions. Since the pandemic, a growing number of medical schools have implemented digital health courses, consisting mostly of electives focused on biomedical informatics or (more recently) telemedicine [3,37]. Few of these programs are integrated into the larger medicine curriculum, however [38], in part because considerable knowledge gaps remain regarding the most effective ways to integrate them [33]. Even less work has been done at the graduate level, although several novel Objective Structured Clinical Examinations (OSCEs) have been developed to provide “hands-on” training to residents [26,38-40]. Overall, systematized approaches to understanding, defining, and building digital health curriculum for medical trainees are lacking, as are those for faculty development and practicing clinicians [41].

We argue that a comprehensive, multilevel approach to understanding, defining, and evaluating digital health skills for trainees is needed in order to properly prepare health professions students to meet the needs of patients in this new health care landscape. To accomplish this, we offer a model based on our growing understanding of “digital determinants of health”—the novel technological contexts and constructs that mediate an individual or community’s interactions with the health care system—and their intersections with care delivery, innovations, education, and equity.

DDoH refer to antecedents within the digital environment that impact a patient’s ability to access, use, and satisfactorily experience the health care system. DDoH exist at individual, community, and structural levels [18] and include a patient’s personal experiences with digital health technology (eg, use patterns, preferences, and digital skills), communal attitudes (eg, perceptions of usefulness, trust, privacy, and surveillance), cultural beliefs and social conditions (eg, the digital environments a community experiences, including “digital deserts”), and structural factors (eg, national technology policies, bias, and discrimination; Figure 1). DDoH can act as barriers or facilitators to effective health care and may disproportionately affect certain individuals or communities [18].

The DDoH framework is modeled on the well-established social determinants of health (SDoH) framework [42]. The SDoH framework consists of conditions that shape the lived experiences of individuals and environments that impact health [43]. SDoH include both place-based conditions and “political, socioeconomic, and cultural constructs” [43]. Some examples include income level, availability of transportation, and social support and community inclusivity [43]. SDoH affect populations in negative and positive ways and can both protect health and contribute to disparities [44]. Given the developments made in understanding SDoH in the last 2 decades and integrating them in health and medicine, a large body of literature now exists exploring socioeconomic factors and the ways they shape health outcomes [45,46]. As knowledge of SDoH has expanded to health care, it has been integrated into medical curricula, and SDoH training is now considered to be a core piece in medical education [47,48]. The success of SDoH competencies and curricula development can serve as a model for integrating DDoH into medical education. The DDoH model effectively transposes SDoH thinking into digital spaces and challenges us to think beyond individual characteristics (eg, digital health literacy) when considering a person, community, or population’s interactions with digital health tools (Figure 1) [19]. DDoH are valuable to effectively conduct virtual care delivery, which is becoming more prominent in health care today [49].

Overall, we argue that digital care delivery cannot be successful or equitable without more attention to the DDoH that define it. Critical to this is the inclusion of DDoH thinking into training paradigms, programs, and resources at all levels.

Specifically, the DDoH framework can help improve digital health competency development through the following:

Overall, health professions educators should use the DDoH framework as a guide in creating robust educational programming and evaluation tools aimed at developing health professionals who understand and can competently use digital health tools to deliver care for diverse patients. Practically, the integration of DDoH in educational programming should leverage a mixed-pedagogical approach that extends beyond passive learning and includes applied learning strategies such as OSCEs and “flipped” classrooms and innovative technologies such as virtual reality. To accomplish this effort, educators can first identify existing spaces in didactic curriculum to infuse DDoH, including adding it to SDoH training. However, a DDoH-based approach can also be taught through problem-based learning, experiential and workplace-based learning, performance assessment, and continuing medical education. Experiential “hands-on training” within community-based and service-learning opportunities (eg, homeless shelters and community advocacy organizations) can imbue technical facility while also educating on social and structural contexts of care using these technologies. In particular, connecting trainees with lay community members such as community health workers or digital navigators can expose them to the common technical skills needed to support patients as well as the social and cultural nuances of a digital health technology’s use in the real world. Incorporating trainees into health system IT efforts is another example that can provide unique administrative and regulatory contexts for learners. DDoH-sensitive learning can also complement quality improvement curricula, particularly as those programs increasingly involve EHRs, clinical decision support, informatics, and other digital health tools.

In keeping with a multilevel approach, digital health competency assessments should evaluate skills at technical, interpersonal, and structural levels, and educators applying the DDoH framework should consider stratifying their assessment domains based on these levels. For example, when developing a learning program on remote blood pressure monitoring in hypertension management, consider the following:

In this case, depending on the level of learner and training goals, while a teaching session dedicated purely to technical skill building (eg, training clinicians on the variety of remote blood pressure monitors and how to successfully take a home blood pressure measurement) may be the focus, using a DDoH-guided approach would allow educators to increase the value of the training by teaching clinicians to also address individual DDoH needs (eg, language preferences and physical or cognitive accessibility needs) and social layers (eg, local library Wi-Fi access) that may contribute to a blood pressure device’s ultimately successful use.

There are some challenges to creating an educational system based on the DDoH framework. Designing robust experiences is time-consuming and often labor-intensive. Consequently, it is important to identify already developed programs that can be quickly adapted and evaluated; this can include existing SDoH programs, but it can also include the myriad of ad hoc telemedicine training tools that proliferated during the COVID -19 pandemic that can now be reworked to be more robust and structured. In general, flexible learning approaches that can respond to the short technology life cycles of many of these products are critical to ensure that skills remain relevant or can be quickly updated; this is challenging to keep on top of and may favor a longitudinal approach that offers multiple teaching touch points throughout a training program. Finding competent faculty to teach these skills may also be difficult, as practicing clinicians and educators are often learning about novel technologies alongside trainees. Finally, convincing health care stakeholders that DDoH are worth studying, learning, and evaluating in their own right take efforts, particularly given the other demands and competing priorities of health training. However, we strongly believe these technologies will only continue to proliferate and become further embedded in health care delivery, and ignoring their outsized and disruptive role in clinical care in critical training periods is ultimately a disservice to the health care workforce and patients.

There is growing need to develop unified digital health education and training competencies for health professions students. Efforts to cultivate a workforce adept in digital health tools must prioritize understanding and mitigating the digital determinants of health that shape individuals’ interactions with health care technology. Using a DDoH framework in medical education—including not only didactic training but also hands-on skill building, as well as continuing education opportunities—can help guide robust educational programming and evaluation tools aimed at developing health professionals who understand and can competently use digital health tools to deliver care for diverse patients.