Disease characteristics influence the privacy calculus to adopt electronic health records: A survey study in Germany

Abstract

Background The 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 about how specific characteristics of medical data influence patients’ intention to use the EHR. Objective This study aims to validate the privacy calculus model (PCM) regarding EHRs and to assess how personal and disease characteristics, namely disease-related stigma and disease time course, affect PCM predictions. Methods An 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 N = 241 participants, aged 18 years and older residing in Germany with no previous experience with the diseases mentioned in the respective medical reports. Participants were randomized (single-blinded) into four groups in parallel: high stigma and acute time course ( n = 74), high stigma and chronic time course ( n = 56), low stigma and acute time course ( n = 62) and low stigma and chronic time course ( n = 49). The data were analyzed using structural equation modeling with partial least squares. Results The model explains R 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 disease's 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. Conclusions The PCM validation for EHRs reveals that personal and disease characteristics shape usage intention in Germany. 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.