Secure Multi-Institutional Data Integration Models for Strengthening Clinical Research Collaboration in the U.S. Health Sector

Abstract

This study examined Secure Multi-Institutional Data Integration (SMIDI) maturity as a measurable organizational capability and evaluated its association with collaboration performance in U.S. clinical research environments using a quantitative, institution-level design. A simulated sample of 96 healthcare and research institutions was analyzed to assess how variation in integration maturity, governance quality, security and privacy control maturity, and analytical infrastructure readiness corresponded with observable collaboration outcomes. SMIDI maturity was operationalized through composite indicators capturing interoperability intensity, access governance strength, auditability, privacy enforcement, and evidence automation, while collaboration performance was measured using a multidimensional index encompassing throughput, efficiency, network engagement, and output quality. Descriptive results indicated moderate-to-high dispersion across institutions, with SMIDI maturity indicators such as interface coverage averaging 46.8 interfaces (SD = 20.9), mapping completeness averaging 82.6% (SD = 9.8), and automated evidence rates averaging 69.8% (SD = 14.6). Collaboration performance measures showed substantial variability, including an average of 19.8 multi-site studies per year (SD = 10.6), a mean dataset build time of 37.6 days (SD = 16.9), and replication consistency averaging 86.2% (SD = 8.9). Reliability testing of reflective subscales produced Cronbach’s alpha values ranging from 0.79 to 0.89, supporting acceptable internal consistency for constructs used in regression models. Multivariate regression analysis demonstrated that SMIDI maturity was positively associated with collaboration performance in the baseline model (B = 0.42, SE = 0.09, p < .001), explaining 34% of outcome variance. After adjusting for governance quality and security/privacy control maturity, the SMIDI effect remained significant (B = 0.31, SE = 0.08, p < .001), and model fit improved (Adjusted R² = 0.46). Inclusion of analytical infrastructure readiness reduced the SMIDI coefficient to 0.19 (SE = 0.07, p = .004) while analytics readiness showed a strong positive association with performance (B = 0.37, SE = 0.09, p < .001), indicating partial mediation. Robustness analyses using alternative outcome definitions and index constructions yielded consistent results. Overall, the findings supported SMIDI maturity as a statistically meaningful determinant of collaboration performance and highlighted the mediating role of analytical infrastructure readiness in multi-institution clinical research settings.