JMIR Publications

ABSTRACT

Background:

Health dataspaces (HDSs) such as the European Health Data Space (EHDS) require acceptance models that go beyond classic technology acceptance research. Established models, including the Technology Acceptance Model (TAM) and the Unified Theory of Acceptance and Use of Technology (UTAUT), capture core determinants such as perceived usefulness and ease of use, but do not adequately reflect the governance, transparency, trust, and multi-stakeholder characteristics of HDSs.

Objective:

This study aimed to develop a Health Dataspace Technology Acceptance Model (HDS-TAM) as a reusable framework for evaluating acceptance of technologies in HDSs and to apply it in a case evaluation of Germany’s electronic patient record (Elektronische Patientenakte, ePA) from the patient perspective.

Methods:

The study followed a 2-step approach. First, a literature review was conducted to identify acceptance-related constructs, variables, and relationships relevant to HDSs. Of 1,788 records identified, 68 studies were included in the final analysis and used to develop HDS-TAM. The resulting model organized determinants into 5 perspectives: identity, aspects of technology, application environment, extrinsic motivators, and social influences. Second, HDS-TAM was adapted to the ePA context and operationalized in a scenario-based online survey. A total of 149 valid responses were analyzed. The survey assessed central constructs and 20 derived hypotheses using factor analysis, reliability analysis, linear regression, and independent-samples t tests.

Results:

HDS-TAM provided a structured basis for evaluating patient acceptance of the ePA. Of the 20 hypotheses, 8 were confirmed. Perceived usefulness had the strongest positive effect on behavioral intention to use the ePA (B=.672, P<.001), whereas perceived risk had a significant negative effect (B=−.295, P<.001). Social influence also positively affected behavioral intention (B=.075, P=.029). Perceived ease of use positively affected perceived usefulness (B=.177, P=.012) and reduced perceived risk (B=−.393, P<.001), indicating an indirect role in acceptance. Perceived need increased perceived usefulness but did not directly affect behavioral intention. Transparency did not significantly influence perceived usefulness or perceived risk, although sufficient information about data processing improved perceived ease of use (B=.350, P<.001). Behavioral intention did not significantly predict actual system use. Open-ended responses reinforced the quantitative findings by highlighting centralized data storage as a key benefit and privacy, misuse, and security concerns as major barriers.

Conclusions:

HDS-TAM extends established acceptance models with HDS-specific perspectives and showed applicability in the evaluation of patient acceptance of the ePA. Acceptance was primarily shaped by perceived usefulness, perceived risk, and social influence. The findings suggest that HDS acceptance depends not only on usability and expected benefit but also on trust- and governance-related concerns. Clinical Trial: not applicable