A Generalizable Decision-Making Framework for Selecting Onsite versus Send-out Clinical Laboratory Testing

Lee F. Schroeder, Paul Rebman, Parastu Kasaie, Ernest Kenu, Jon Zelner and David W. Dowdy
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Lee F. Schroeder: Department of Pathology, University of Michigan School of Medicine, Ann Arbor, MI, USA
Paul Rebman: Department of Epidemiology, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD, USA
Parastu Kasaie: Department of Epidemiology, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD, USA
Ernest Kenu: School of Public Health, University of Ghana, Ghana
Jon Zelner: Department of Epidemiology, University of Michigan School of Public Health, Ann Arbor, MI, USA
David W. Dowdy: Department of Epidemiology, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD, USA

Medical Decision Making, 2024, vol. 44, issue 3, 307-319

Abstract: Background Laboratory networks provide services through onsite testing or through specimen transport to higher-tier laboratories. This decision is based on the interplay of testing characteristics, treatment characteristics, and epidemiological characteristics. Objectives Our objective was to develop a generalizable model using the threshold approach to medical decision making to inform test placement decisions. Methods We developed a decision model to compare the incremental utility of onsite versus send-out testing for clinical purposes. We then performed Monte Carlo simulations to identify the settings under which each strategy would be preferred. Tuberculosis was modeled as an exemplar. Results The most important determinants of the decision to test onsite versus send-out were the clinical utility lost due to send-out testing delays and the accuracy decrement with onsite testing. When the sensitivity decrements of onsite testing were minimal, onsite testing tended to be preferred when send-out delays reduced clinical utility by >20%. By contrast, when onsite testing incurred large reductions in sensitivity, onsite testing tended to be preferred when utility lost due to delays was >50%. The relative cost of onsite versus send-out testing affected these thresholds, particularly when testing costs were >10% of treatment costs. Conclusions Decision makers can select onsite versus send-out testing in an evidence-based fashion using estimates of the percentage of clinical utility lost due to send-out delays and the relative accuracy of onsite versus send-out testing. This model is designed to be generalizable to a wide variety of use cases. Highlights The design of laboratory networks, including the decision to place diagnostic instruments at the point-of-care or at higher tiers as accessed through specimen transport, can be informed using the threshold approach to medical decision making. The most important determinants of the decision to test onsite versus send-out were the clinical utility lost due to send-out testing delays and the accuracy decrement with onsite testing. The threshold approach to medical decision making can be used to compare point-of-care testing accuracy decrements with the lost utility of treatment due to send-out testing delays. The relative cost of onsite versus send-out testing affected these thresholds, particularly when testing costs were >10% of treatment costs.

Keywords: global health; management/administration; CP general; laboratory network; diagnostic network; specimen transport; utility; cost-effectiveness; threshold approach; decision analysis; model (search for similar items in EconPapers)
Date: 2024
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Persistent link: https://EconPapers.repec.org/RePEc:sae:medema:v:44:y:2024:i:3:p:307-319

DOI: 10.1177/0272989X241232666

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