OP70 Gaps In The Evaluation Of Clinical Decision Support Software (CDSS): Interviews With Australian Policymakers

Introduction Clinical Decision Support Software (CDSS) can improve the quality and safety of care by providing patient-specific diagnostic treatment recommendations. However, robust evaluation is required to ensure that recommendations provided are clinically valid, up-to-date, relevant a specific clinical context. Most studies assess CDSS performance from perspective end-user requirements. But only occasionally subject stringent pre- post-market evaluation, making it difficult determine in practice. This study aimed Australia identify gaps approaches. Methods We conducted 11 semi-structured interviews with different policymakers committees involved digital health activities Australia. Data were thematically analyzed using both theory-based (deductive) data-driven (inductive) Results Our findings indicated evaluating as purely technical intervention has overly narrowed assessment benefits risks inadequately capturing sociotechnical environment. Existing methods, adopting static view implemented system, cannot discern impact dynamic environment rapidly evolving technology on performance. The timeframe also incongruent fast software upgrade cycles, practices potentially changing time complete. regulation medical device depends intended use. exempt because they ‘produce advice’; however, this ignores fact transition specifying diagnosis after update. There no framework for continuous monitoring, especially important when algorithm change patient management. Conclusions significant factor influencing practice, therefore approaches must acknowledge nature organizational contexts. Pragmatic methodologies landscape practice its relationship technology.