A Review of Medical Data Sharing Initiatives With a Focus on the Use of Blockchain Technologies: Qualitative Comparative Analysis.

Background: Medical data sharing initiatives are crucial for advancing research, improving patient outcomes, and fostering innovation in health care. With the advent of blockchain technology, there has been significant interest in exploring its potential to enhance the security, transparency, and efficiency of medical data sharing. Objective: This study aimed to examine a selected set of blockchain-based medical data sharing initiatives, focusing on their governance, incentive structures, ownership models, business approaches, transaction mechanisms, and sustainability strategies. The analysis explored patterns in operational status and longevity, providing insight into the factors shaping these initiatives. The objective was to identify common characteristics and contextual factors that may influence their development and persistence. Methods: The study used snowball sampling to identify a selection of primarily blockchain-based medical data sharing initiatives, drawing from academic literature, web searches, and expert consultations. To examine structural and operational patterns, initiatives were selected based on the availability of sufficient public documentation for systematic classification. Each initiative was categorized by governance, incentives, ownership, business models, transaction mechanisms, and sustainability strategies. A follow-up assessment examined operational status over time. The analysis applied qualitative comparative analysis to identify common structural features and relationships between governance, incentives, and sustainability. Results: The survey identified 42 initiatives, categorizing them based on ownership, governance, business, incentive, transaction, and sustainability models. These categories were systematically identified and assigned numerical values to facilitate fuzzy-set qualitative comparative analysis. The base model, run at an inclusion threshold of 0.65, identified multiple configurations associated with sustained initiative activity, highlighting the role of governance mechanisms and transaction structures in supporting long-term viability. The sensitivity analysis, conducted across multiple thresholds, demonstrated that while several configurations remained stable, higher thresholds led to more restrictive solutions. At 0.80, only two configurations remained, representing the most consistent pathways to sustained activity, reinforcing the importance of governance and transaction models in initiative sustainability. Conclusions: The analysis revealed a range of governance, ownership, business, and sustainability models, with no single structural configuration guaranteeing long-term viability. The findings suggest that governance and transaction mechanisms are particularly influential in sustaining initiatives, often compensating for the absence of strong business or sustainability models. The scope was limited to initiatives identified through available documentation and snowball sampling, and the results underscore the need for further research into the interplay between governance structures, financial models, and long-term sustainability in medical data sharing.