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Review
. 2025 Jan 3;10(1):92-112.
doi: 10.1093/jalm/jfae118.

Cost-Effective Drug Testing: Analytical Methodology, Best Practices, and Clinical Utility

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Review

Cost-Effective Drug Testing: Analytical Methodology, Best Practices, and Clinical Utility

James A Chenoweth et al. J Appl Lab Med. .

Abstract

Background: Drug overdose-related deaths continue to increase globally. Testing demands have likewise increased, prompting healthcare facilities to adopt a range of methods, from simple point-of-care immunoassays to comprehensive chromatographic and mass spectrometry-based techniques. Each of these testing methods has trade-offs related to cost, performance, speed, and convenience, requiring healthcare facilities to carefully determine the best options to meet their clinical needs. Unfortunately, current testing practices may result in unnecessary costs and certain methods, such as immunoassays, have significant limitations that affect their clinical utility. As such, the goal of this review is to frame the current state of drug testing and related cost-effectiveness and patient centered approaches to address this evolving public health challenge.

Content: This review discusses the current state of substance use mortality/morbidity, the economic impact of substance use disorders, provides an overview of testing methods and their relative cost-benefit, solutions to improve test utilization and cost-effectiveness, and finally, future threats and new opportunities that can improve the clinical utility of these tests.

Summary: The cost-effectiveness of drugs of abuse testing revolves around proper test utilization, including understanding what test is being ordered, its limitations, understanding results, and ordering testing when it can provide actionable information. Fundamental principles of test utilization such as education, clinical informatics, and optimizing test panels remain essential. Future threats in this space include new compounds and regulatory changes. However, novel solutions such as new noninvasive sample types, automation, and artificial intelligence can play a significant role in improving overall test utilization practices.

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