Rethinking Digital Health Transformation as an Adaptive System

Digital transformation in healthcare has long been framed as a straight-line march from paper to pixels, but a new systematic and bibliometric review argues that this view is too narrow. The study, published open access in Humanities and Social Sciences Communications, analyzed literature published between 2010 and 2025 and concluded that digital transformation is not a linear or purely technical process. Instead, the authors describe it as a dynamic adjustment among policy frameworks, organizational capabilities, and technological change, in which each domain continuously reshapes the others.

The review combined bibliometric mapping with a grounded qualitative synthesis of the research literature. The authors, Carolina Busco, Angélica Muñoz, and Casandra Bastías, structured their analysis around three questions: which themes and trends dominate healthcare digital transformation, which policy-level barriers and enablers shape its development, and which strategic challenges and benefits influence transformation inside healthcare institutions. This dual approach allowed the team to chart the volume and connections of published work while also extracting the conceptual patterns embedded within it.

One of the review’s central findings concerns the models that organizations most often use to benchmark their progress. Widely adopted frameworks such as the HIMSS Electronic Medical Record Adoption Model and the McKinsey 7S framework offer valuable reference points, the authors report, but they remain limited by static and technocentric assumptions. In other words, these models tend to measure how much technology an institution has deployed rather than how well its policies, people, and systems adapt together over time.

To address that gap, the study proposes an integrated framework grounded in Social Systems Theory. Within this framing, digital transformation is conceptualized as an adaptive system characterized by iterative feedback, learning, and recalibration across the policy, organizational, and technological domains. Rather than treating implementation as a project with a fixed endpoint, the framework portrays it as a continuing cycle in which outcomes at one level feed back into decisions at the others, prompting ongoing adjustment.

The authors position this contribution on two fronts. Theoretically, the framework advances an evolutionary understanding of digital transformation, moving beyond models that privilege either technological or organizational perspectives in isolation. Practically, they present it as a roadmap for policymakers and healthcare managers who aim to build health systems that are sustainable, interoperable, and human-centered. Because the analysis rests on a synthesis of published literature rather than new empirical measurements, its conclusions describe patterns in the research record and a proposed conceptual model, not measured outcomes from clinical implementation. Even so, the review offers a clear message for a field often judged by deployment checklists: progress in digital health may depend less on any single technology than on how well policy, organization, and technology learn to move together.

Subject of Research: A systematic and bibliometric review of digital transformation strategies, policies, barriers, and benefits in healthcare

Article Title: Digital transformation in healthcare: a systematic and bibliometric review of strategies, policies, barriers, and benefits

Article References: Busco, C., Muñoz, A., & Bastías, C. (2026). Digital transformation in healthcare: a systematic and bibliometric review of strategies, policies, barriers, and benefits. Humanities and Social Sciences Communications. https://doi.org/10.1057/s41599-026-09281-7

Image Credits: AI Generated

DOI: 10.1057/s41599-026-09281-7

Keywords: digital transformation, healthcare, systematic review, bibliometrics, health policy, HIMSS EMRAM, McKinsey 7S, Social Systems Theory, interoperability, organizational change, Digital, transformation