Healthcare's digital skills gap: why existing competency tools aren't built for the full workforce

Of the 20 workforce-facing digital health competency assessment tools examined in a rapid review published in the International Journal of Medical Informatics this July, nearly half were designed exclusively for nurses. Only two met the bar for validity across an interprofessional workforce. For health system leaders planning enterprise-wide digital rollouts, that gap in measurement capability is not a research footnote; it is an operational problem.

The rapid review, led by Robertson and colleagues, screened publications across PubMed, CINAHL, and Google Scholar through April 2025. It found 28 publications and grey literature sources meeting inclusion criteria, with 61% of those published in the last five years, a sign of accelerating research attention. Yet quantity has not translated to quality coverage. While 71% of instruments reported some psychometric properties, the evidence quality varied considerably, and the interprofessional gap remained stark.

A measurement problem with a real cost

Health systems deploying electronic health records, AI-assisted diagnostics, or remote patient monitoring need to know, before and after go-live, whether clinicians across every discipline can use those tools safely and effectively. Without validated, role-agnostic assessment instruments, that baseline is essentially guesswork. According to the International Journal of Medical Informatics review, only two tools currently meet both the validity and interprofessional scope criteria that a serious enterprise evaluation would require.

This matters at the procurement stage too. Training vendors and digital health platform vendors frequently reference workforce readiness and competency programs in their pitches. If the tools underpinning those programs are validated only for nurses, a hospital system deploying across radiologists, pharmacists, care coordinators, and hospitalists is working from incomplete data. The review frames this plainly: understanding which tools are fit for purpose is essential for health services seeking to improve digital health competence at scale.

The public health side: 222 competencies, now narrowed to 19

A separate but complementary scoping review published in npj Digital Public Health tackled the workforce competency problem from a population-health angle. Searching Medline, Embase, Web of Science, and ERIC, researchers identified 994 records after deduplication, ultimately including 13 studies that together contributed 222 discrete competencies. Through a structured synthesis process, those were refined into a final framework of 19 competencies organized across three domains.

• Health data: governance, quality, interoperability, and standards
• Digital public health services and functions: service delivery, digital intervention design, and policy application
• Analytics and artificial intelligence: data analysis, AI application, and population-level insight generation

The npj Digital Public Health framework is explicitly aimed at shaping curriculum integration and workforce strategy, particularly across European national contexts. But the domain structure translates directly to enterprise workforce planning anywhere. An organization building out a health analytics team or standing up an AI-assisted surveillance function now has a peer-reviewed competency map to work against, rather than assembling one from scratch.

Where the two studies converge

Both reviews, independent in scope and methodology, arrive at the same operational conclusion: the research interest in digital health workforce capability is growing fast, but the evidence base for measuring and building it remains thin, particularly outside nursing and outside the United States and United Kingdom. The npj study specifically notes limited evidence from Europe, while the International Journal of Medical Informatics review highlights the near-absence of tools validated for the full interprofessional team.

For digital health transformation to deliver on its operational promise, health systems need to know where their workforce stands before they deploy, not after. Neither study argues that the current tools are unusable; they argue that users need to understand the boundaries of what those tools actually measure. A nursing-validated survey applied to a multidisciplinary team produces noise, not signal.

What this means for your team

• Audit any competency assessment tools currently in use or proposed by training vendors: confirm the target population the tool was validated for and whether it covers all clinical roles in your deployment scope.
• Use the 19-competency digital public health framework from npj Digital Public Health as an internal benchmark when scoping workforce readiness for analytics, AI, or population-health programs.
• When evaluating digital health platforms, ask vendors to specify which validated assessment instruments they use in their workforce readiness programs and request the psychometric evidence behind them.
• Flag the interprofessional gap to workforce development partners: if they cannot provide tools validated across disciplines, build a phased assessment strategy that layers role-specific tools while the field catches up.