ArticleBMC health services research2026
Stakeholder preferences on digital health in Germany: a health preference study protocol.
Article in BMC health services research, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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Abstract
backgroundDigital health interventions (DHIs) are increasingly shaping healthcare systems. However, their adoption is often hindered by fragmented evaluation frameworks that fail to reflect clinical, technical, economic, and societal value dimensions. This study protocol outlines the design of a stakeholder-informed preference study aimed at developing a multidimensional evaluation framework for DHIs in Germany.
methodsThe study applies a prospective health preference research design combining discrete choice experiments (DCEs) and best-worst scaling (BWS) Type 1. Based on a systematic review, qualitative interviews (N = 10), and expert consultations, four decision models were developed reflecting the value dimensions of DHIs at the subject, interaction, system, and societal levels. A total of 31 descriptive and two continuous attributes (out-of-pocket costs and daily time investment) were identified and structured into a partial profile design. These models form the basis for four DCE modules. A total of 4,250 to 4,300 participants from the general population and healthcare provider network will be recruited and randomly assigned to one DCE module. Each participant will complete nine choice tasks, each followed by a question to approximate real-world acceptance. Following the DCE module, a BWS Type 1 task will be administered to rank all 31 attributes. A joint likelihood model will be used to combine DCE and BWS data using shared attributes as anchors. The final survey instrument was pretested with six individuals to assess usability, clarity, and response behavior under realistic conditions. Planned analyses include conditional logit, mixed logit, and latent class models. Background variables including self-reported health status, experience with digital health, and key sociodemographic characteristics will be used for subgroup analyses. Quality assurance measures include pre-launch testing of the survey infrastructure and automated detection of inattentive or non-human responses using indicators such as completion time anomalies, repetitive patterns, and semantic plausibility of open-ended input. DISCUSSION: This study will generate robust evidence on stakeholder preferences for DHIs. It will quantify attribute importance, willingness to pay, willingness to invest time, and subgroup-specific heterogeneity. The resulting multidimensional framework aims to support the design, implementation, and reimbursement of DHIs in alignment with stakeholder values.
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