Research on Vertical Professional Collaborative Evaluation Tools of Healthcare System Based on the Tight County Healthcare Alliance in China

Objectives: To develop the vertical professional collaborative evaluation tools to promote the establishment of integrated healthcare system in China.

Method: Based on the previous theoretical framework, the evaluation system was developed and 450 doctors and other health professionals in tight county healthcare alliance in D county of H province were selected and interviewed. Through stratified cluster equal proportion random sampling method with an effective recovery rate of 93.33%, reliability and validity were tested with exploratory factor analysis, Cronbach’s α and structural equation model method.

Results: The cumulative contribution rate of the five common factors was 72.23%, the Cronbach’s α of whole is 0.846. Except for the common factor F4, the Cronbach’s α of other common factors were greater than 0.7. The component reliability (CR) of 5 common factors were all greater than 0.7 and the average coefficients of variation extraction (AVE) were all greater than 0.6. In the revised model (M1), the P values of the standard regression coefficients of F1, F2, F3, F4 and those of the corresponding items and factors were all smaller than 0.05, and the model fitting indexes of were all better than those of the initial model (M0).

Conclusions: The vertical professional collaborative evaluation tools of healthcare system constructed in this paper contain 4 dimensions: (1) Value compatibility and trust, defined as the alignment of health-related values, cultural norms, and behavioral expectations across different provider levels (e.g., primary vs. tertiary care) and specialties (e.g., physicians vs. nurses), operationalized through shared decision-making and perceived reliability; (2) Communication and coordination mechanisms, encompassing systems for bidirectional information flow (e.g., standardized referral protocols, interoperable IT platforms) and procedural safeguards to enable cross-disciplinary collaboration; (3) Incentive and constraint mechanisms, referring to policy tools (financial/non-financial rewards, accountability metrics) designed to motivate or regulate collaborative behaviors; and (4) Structure and strength of collaborative relationships, characterized by the topology (e.g., network centrality) and resilience of inter-provider connections, measured through interaction frequency and resource-sharing patterns.,; 8 factors and 15 items whose overall reliability and validity were good and has certain applicability in China. Given regional sociocultural diversity, the findings require validation through broader case studies.