Disease Characteristics Influence the Privacy Calculus to adopt Electronic Health Records: A randomized controlled trial in Germany

BackgroundThe electronic health record (EHR) is integral to improving healthcare efficiency and quality. Its successful implementation hinges on patient willingness to use it, particularly in Germany where concerns about data security and privacy significantly influence usage intention. Little is known, however, about how specific characteristics of medical data influence patients intention to use the EHR. ObjectiveThis study aims to validate the Privacy Calculus Model (PCM) in the EHR context and to assess how personal and disease characteristics, namely disease-related stigma and disease time course, affect PCM predictions. MethodsAn online survey was conducted to empirically validate the PCM for EHR, incorporating a case vignette varying in disease-related stigma (high/low) and time course (acute/chronic), with 241 German participants. The data were analyzed using SEM-PLS. ResultsThe model explains R{superscript 2}=71.8% of the variance in intention to use. The intention to use is influenced by perceived benefits, data privacy concerns, trust in the provider, and social norms. However, only the diseases time course, not stigma, affects this intention. For acute diseases, perceived benefits and social norms are influential, whereas for chronic diseases, perceived benefits, privacy concerns, and trust in the provider influence intention. ConclusionsThe PCM validation for EHRs reveals that personal and disease characteristics shape usage intention in Germany. This suggests the need for tailored EHR adoption strategies that address specific needs and concerns of patients with different disease types. Such strategies could lead to a more successful and widespread implementation of EHRs, especially in privacy-conscious contexts.