Department of Pathology, University of Michigan School of Medicine, Ann Arbor, MI, USA.
Department of Epidemiology, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD, USA.
Med Decis Making. 2024 Apr;44(3):307-319. doi: 10.1177/0272989X241232666. Epub 2024 Mar 6.
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.
Our objective was to develop a generalizable model using the threshold approach to medical decision making to inform test placement decisions.
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.
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.
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.
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.
实验室网络通过现场检测或标本运输到更高层次的实验室提供服务。这一决策基于检测特征、治疗特征和流行病学特征的相互作用。
我们的目标是使用医疗决策的阈值方法开发一个可推广的模型,为检测位置决策提供信息。
我们开发了一个决策模型,用于比较现场检测与送检检测在临床目的上的增量效用。然后,我们进行了蒙特卡罗模拟,以确定每种策略在哪些情况下会更受欢迎。结核病被建模为一个范例。
决定现场检测与送检检测的最重要因素是送检检测延迟导致的临床效用损失,以及现场检测的准确性降低。当现场检测的敏感性降低很小时,当送检检测延迟减少临床效用超过 20%时,现场检测往往更受欢迎。相比之下,当现场检测的敏感性降低很大时,当由于延迟而导致的效用损失超过 50%时,现场检测往往更受欢迎。现场检测与送检检测的相对成本会影响这些阈值,尤其是当检测成本超过治疗成本的 10%时。
决策者可以使用因送检检测延迟而导致的临床效用损失百分比和现场检测与送检检测的相对准确性的估计值,以基于证据的方式选择现场检测与送检检测。该模型旨在推广到各种用例。
可以使用医疗决策的阈值方法来设计实验室网络,包括在护理点或通过标本运输访问的更高层次上放置诊断仪器的决策。决定现场检测与送检检测的最重要因素是因送检检测延迟而导致的临床效用损失和现场检测的准确性降低。医疗决策的阈值方法可用于比较现场检测的准确性降低与因送检检测延迟而导致的治疗效用损失。现场检测与送检检测的相对成本会影响这些阈值,尤其是当检测成本超过治疗成本的 10%时。