An Operational Framework for the Adoption and Integration of New Diagnostic Tests

The gap between medical research on diagnostic testing and clinical workflow can lead to rejection of valuable medical research in a busy clinical environment due to increased workloads, or rejection of medical research in the lab that may be valuable in practice due to a misunderstanding of the system-level benefits of the new test. This has implications for research organizations, diagnostic test manufacturers, and hospital managers. To bridge this gap, we develop a Markov Decision Process (MDP) from which we create “adoption regions” that specify the combination of test characteristics medical research must achieve for the test to be feasible for adoption in practice. To address the curse of dimensionality from patient risk stratification, we develop a decomposition heuristic along with structural properties that shed light on which patients and when a new diagnostic test should be used. In a case study of a partner Emergency Department, we show that the conventional myopic medical criterion can lead to poor decision making in both research development and clinical practice. This myopic approach can lead to overvaluing or undervaluing new medical research. This mismatch is accentuated when a simple (current) policy is used to integrate research into the clinical environment compared with our MDP's policy – poor implementation of a new test can also lead to unnecessary rejection. Our framework provides easily interpretable guidelines for medical research development and clinical adoption decisions that can guide medical research as to which test characteristics to focus on to improve chances of adoption