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Theoretical models and frameworks clarify stakeholder perspectives during the commercial digital health innovation life cycleNew framework helps teams navigate complex digital health technology

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Key Takeaway
Note that existing frameworks categorize digital health innovation into user behavior, organizational adoption, and design.

This systematic review explores the theoretical landscape of health digitalization by identifying and categorizing 12 distinct theories, models, and frameworks (TMFs) from a pool of 4628 potentially relevant articles. The scope focuses on clarifying fragmented knowledge across scholarly disciplines to support digitalization teams in navigating the innovation life cycle.

The synthesis identifies three primary categories for these frameworks: 4 TMFs focus on the behavior change of end users, 2 TMFs explore organizational adoption, and 6 TMFs address factors shaping innovation design and development. These categorizations aim to provide a holistic view of how different stakeholders approach digital health innovations.

The review does not evaluate clinical outcomes, patient safety, or specific medical interventions. It serves as a conceptual mapping of implementation science in the digital health space. The findings are intended to help practitioners understand the theoretical landscape rather than providing evidence for specific clinical protocols.

Moving a new piece of technology into a hospital or clinic is complicated. It involves everything from changing patient habits to redesigning how staff work together. Because the field is so broad, many teams struggle with fragmented information when trying to launch these tools.

A review of 12 specific models and frameworks helps clear up this confusion. These frameworks were grouped into three main areas: four focused on how patients change their behavior, two looked at how organizations adopt new tech, and six focused on the design and development of the innovation itself.

This overview provides a roadmap for teams working in digital health. By using these established models, developers can better understand the different needs of stakeholders. While this study does not measure patient safety or clinical results, it offers a clearer way to organize the knowledge needed to build successful digital tools.

What this means for you:
Organized frameworks help healthcare teams navigate the complex process of launching new digital health technologies.

Common questions

What do these frameworks help with?

These models help teams navigate the life cycle of a digital health innovation. They provide clarity for different stakeholders by organizing information into three areas: user behavior change, organizational adoption, and the design and development of the technology.

Study Details

Study typeMeta analysis
EvidenceLevel 1
PublishedJul 2026
View Original Abstract ↓
Health digitalization entails a complex array of actors and roles, including healthcare stakeholders and commercial digital-health innovators. The implementation of digital health innovations (DHIs) is notoriously prone to failure. Consequently, many theories, models, and frameworks (TMFs) have been developed to explain or guide the process of health digitalization. Depending on their scholarly origins, these TMFs differ in their perspective, origin, and terminology, leading to knowledge fragmentation and confusion. The aim of this review was to create an overview of the available TMFs, bringing together and clarifying different perspectives of healthcare stakeholders and innovators during the DHI life cycle. This study focused on TMFs describing, explaining, predicting, or prescribing parts of the innovation pathway considering influential factors and actors. Three databases (PubMed, EMBASE, and Web of Science) were searched using the aid of an information specialist in February 2025. We identified relevant keywords for the search by extensively reviewing eHealth and health digitalization literature. Studies were eligible for inclusion if they were published after 2000, written in English, and presented a new or significantly adapted TMF empirically tested in healthcare settings involving a commercial DHI. Studies applying only a known TMF without contextual adaptation or a DHI in the prototype phase were excluded. From the 4628 potentially relevant articles, 12 fulfilled the inclusion criteria. The included TMFs came from diverse scholarly disciplines, pointing to the multidisciplinary knowledge needed for health digitalization. Four TMFs focused on behavior change of end users, two TMFs explored organizational adoption of the DHI, and six TMFs dealt with factors that shape innovation design and development. Several constructs were found in two or all of the TMF groups. The actors involved came from diverse backgrounds and differed according to the type of DHI and scope of implementation. The included TMFs synthesized foundational theories and constructs from specific problem areas in health digitalization. Analyzing the reasons for adding certain constructs indicated how actors and researchers in the different groups perceive the landscape of health digitalization and the realities that shape the digitalization process, helping to create a holistic view aiding continuity and outward growth of the digitalization team. https://www.crd.york.ac.uk/PROSPERO/view/CRD420251027510, PROSPERO CRD420251027510.
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