Clinical Utility of Diagnostic Tests: Impact on Patient Care and Value

This report analyzes the concept of clinical utility in the context of diagnostic tests, with a specific focus on genetic testing. It addresses the challenges faced by diagnostic firms in demonstrating the value of their products to payers and other stakeholders. The report discusses how manufacturers can build a case for a diagnostic's positive impact on patient care, detailing the data and information needed to demonstrate clinical utility, such as evidence of improved diagnostic accuracy, therapeutic options, and patient outcomes. The report also explores the feasibility of collecting this data, and presents the author's view on whether clinical utility is a good metric for assessing the value of a diagnostic test, concluding that it is not and should be a more encompassing concept. References are provided to support the analysis.

Running head: CLINICAL UTILITY 1
Clinical utility
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Clinical utility
Clinical utility is one of the most critical challenges facing new diagnostic firms and their
stakeholders. Without scientific proof, payers may not cover or reimburse the discovered
technology regardless of how promising they are. Diagnostic tests should be evaluated critically
before their incorporation into daily practice (Peabody, Shimkhada, Tong & Zubiller, 2014).
Payers and other diagnostic test users request for more than simple measures of diagnostic
accuracy and technical performance. They also require to see the testing contribute to health
benefits.
The acceptance of healing or preventative interventions that lead to health results which
is the clinical utility of an assessment is based on sufficient access to suitable interventions.
Therefore, a diagnostic test alone cannot have inherent efficiency (Peabody et al., 2014). Clinical
utility broadly can denote to any conclusions that are taken as crucial to an individual and used in
making different health decisions for the individual.
Genetic testing has been questioned on its contribution to clinical utility; however, its
utility has numerous dimensions ranging from clinical, public health, personal, and social
benefits. The capacity to appraise clinical practice and influence the results not directly linked to
the health status is an essential use of genetic testing (Berger & Olson, 2013). For instance, a
genetic test is crucial in the determination of vulnerability to common chronic conditions.
Different levels of impact are considered beyond the viability and validity of the assessment. The
stages include diagnostic thinking which is the value of evidence in determining a diagnosis,
cause, and prognosis, a therapeutic option referring to the trial outcomes in clinical organization
and patient outcomes which apply to endpoints for instance mortality. This identifies the clinical
utility of genetic testing whereby the manufacturer can collect data regarding an individual

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genotypic variation linked to risk of diseases (Peabody, Paculdo, Valdenor, Burgon & Jeter,
2019). Collection of this data to show the clinical utility of genetic testing is feasible in the
laboratory.
To conclude, in my view, clinical utility is not a good metric for defining the value of a
diagnostic test. This is because genetic testing has significantly contributed to the incremental
population health benefit. Clinical utility should be a more encompassing concept of the overall
benefits.

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References
Berger, A. C., & Olson, S. (2013). Genome-based Diagnostics: demonstrating clinical utility in
oncology. In Institute of Medicine of the National Academies: Workshop Summary.
Peabody, J. W., Shimkhada, R., Tong, K. B., & Zubiller, M. B. (2014). New thinking on clinical
utility: hard lessons for molecular diagnostics. Am J Manag Care, 20(9), 750-6.
Peabody, J., Tran, M., Paculdo, D., Valdenor, C., Burgon, T., & Jeter, E. (2019). Establishing
Clinical Utility for Diagnostic Tests Using a Randomized Controlled, Virtual Patient
Trial Design. Diagnostics, 9(3), 67.