Optimizing nursing clinical decision support systems: Insights from nurses' experiences

PurposeThis study explores nurses' experiences with a Nursing Clinical Decision Support System (Nu-CDSS) two years post-implementation and identifies user-centered areas for system optimization.MethodsA descriptive qualitative study was conducted in a tertiary acute care hospital in Shanghai. A select, stratified group of 15 Chinese-speaking clinical nurses and nurse managers across five wards participated in in-depth semi-structured interviews. Data were transcribed verbatim and analyzed thematically with findings organized using the 5R framework.ResultsSeven themes and 14 subthemes were identified. Optimization requirements encompassed: 1) Right Information: enhancing clinical relevance and patient-specific adaptability of diagnoses and interventions; 2) Right People: optimizing role-based usability; 3) Right Formats: integrating clinical records and embedding notifications directly into primary workflows; 4) Right Channels: improving platform interoperability and seamless mobile-desktop data synchronization; 5) Right Time: minimizing system latency and optimizing reminder timing and lifecycles. Furthermore, participants emphasized the need for 6) robust technical and network support, including adaptive inference engines, and 7) standardized nursing protocols.ConclusionOptimizing Nu-CDSS in acute care requires improvements in the knowledge base, interface integration, platform synchronization, reminder timing, and technical support. Future iterations should incorporate AI-enhanced, context-sensitive decision support while preserving nurses' clinical judgment.