DECIDE-Lab: A Value-of-Information and POMDP Framework for Diagnostic Laboratory Test Selection

Background/Objectives: Diagnostic laboratory tests are often judged by sensitivity and specificity, together with related measures of analytic validity. These assist in deciding on which tests are expected to be more accurate or precise, but they do not determine whether a test result improves patient care. A laboratory test has clinical value when it changes a provider’s decision in a way that improves expected outcomes after accounting for uncertainty and patient burden. This work presents DECIDE-Lab (Decision Centered Evaluation of Clinical Information and Dynamic Evidence for Laboratory Testing), an integrative decision-theoretic framework that adapts value-of-information (VOI) and POMDP methods to laboratory test selection to evaluate the value of single tests and serial testing. Methods: The framework connects test performance attributes to clinical utility through posterior belief updating and action thresholds. The concept of clinical utility frontiers is presented, which identifies dominated lab tests. DECIDE-Lab allows preference-sensitive and equity-aware evaluation of lab test diagnostic value by incorporating variation in test performance across patient subgroups. Results: An illustrative acute coronary syndrome application shows that the value of serial troponin testing concentrates in intermediate-risk patients for whom an additional result can change disposition or treatment. A worked sepsis pathway demonstrates the POMDP mechanics step by step from an initial belief state to the resulting stop-or-continue decision. Additional disease-state applications demonstrate how the framework can support diagnostic stewardship and adaptive ordering. Conclusions: The central implication is that diagnostic value should be measured by action-changing utility rather than accuracy alone, while examining how conclusions change with utilities and implementation constraints.