An Operational Framework for the Adoption and Integration of New Diagnostic Tests. Issue 2 (12th January 2021)

• Record Type: Journal Article
• Authors: Shi, Pengyi; Helm, Jonathan E.; Heese, H. Sebastian; Mitchell, Alice M.
• Is Part Of: Production and operations management. Volume 30:Issue 2(2021)
• Page Start: 330
• Page End: 354
• Publication Date: 2021-01-12
• Subjects: diagnostic test adoption -- emergency department -- system congestion -- Markov decision process -- decomposition algorithm; Production management -- Periodicals; 658.505
• DOI: 10.1111/poms.13263
• Languages: English
• ISSNs: 1059-1478

Abstract

Abstract : 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 laboratory 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 among others. 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 algorithm 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. In particular, we find that specificity—long a secondary consideration and often overlooked in the research process—is, in fact, the key to effective implementation of new tests into clinical environments. 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 the chances of adoption.