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Measuring clinical utility in the context of genetic testing: a scoping review.

ABSTRACT: Standardized approaches to measuring clinical utility will enable more robust evaluations of genetic tests. To characterize how clinical utility has been measured, this scoping review examined outcomes used to operationalize this concept in the context of genetic testing, spanning relevant literature (2015-2017). The search strategy and analysis were guided by the Fryback and Thornbury hierarchical model of efficacy (FT Model). Through searches in Ovid MEDLINE, EMBASE and Web of Science, 194 publications were identified for inclusion. Two coders reviewed titles, abstracts, and full texts to determine eligibility. Results were analyzed using thematic and frequency analyses. This review generated a catalog of outcomes mapped to the efficacy domains of the FT Model. The degree of representation observed in each domain varied by the clinical purpose and clinical indication of genetic testing. Diagnostic accuracy (68%), technical (28.4%), and patient outcome (28.4%) efficacy studies were represented at the highest rate. Findings suggest that the FT Model is suitable for the genetics context however domain refinements may be warranted. More diverse clinical settings, robust study designs, and novel strategies for measuring clinical utility are needed.

SUBMITTER: Walcott SE

PROVIDER: S-EPMC7940410 | biostudies-literature | 2021 Mar

REPOSITORIES: biostudies-literature

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Measuring clinical utility in the context of genetic testing: a scoping review.

Walcott Shantel E SE Miller Fiona A FA Dunsmore Kourtney K Lazor Tanya T Feldman Brian M BM Hayeems Robin Z RZ

European journal of human genetics : EJHG 20201021 3

Standardized approaches to measuring clinical utility will enable more robust evaluations of genetic tests. To characterize how clinical utility has been measured, this scoping review examined outcomes used to operationalize this concept in the context of genetic testing, spanning relevant literature (2015-2017). The search strategy and analysis were guided by the Fryback and Thornbury hierarchical model of efficacy (FT Model). Through searches in Ovid MEDLINE, EMBASE and Web of Science, 194 pub ...[more]

PMID: 33087880

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Project description:Electronic health records (EHRs) allow for meaningful usage of healthcare data. Their adoption provides clinicians with a central location to access and share data, write notes, order labs and prescriptions, and bill for patient visits. However, as non-clinical requirements have increased, time spent using EHRs eclipsed time spent on direct patient care. Several solutions have been proposed to minimize the time spent using EHRs, though each have limitations. Digital scribe technology uses voice-to-text software to convert ambient listening to meaningful medical notes and may eliminate the physical task of documentation, allowing physicians to spend less time on EHR engagement and more time with patients. However, adoption of digital scribe technology poses many barriers for physicians. In this study, we perform a scoping review of the literature to identify barriers to digital scribe implementation and provide solutions to address these barriers. We performed a literature review of digital scribe technology and voice-to-text conversion and information extraction as a scope for future research. Fifteen articles met inclusion criteria. Of the articles included, four were comparative studies, three were reviews, three were original investigations, two were perspective pieces, one was a cost-effectiveness study, one was a keynote address, and one was an observational study. The published articles on digital scribe technology and voice-to-text conversion highlight digital scribe technology as a solution to the inefficient interaction with EHRs. Benefits of digital scribe technologies included enhancing clinician ability to navigate charts, write notes, use decision support tools, and improve the quality of time spent with patients. Digital scribe technologies can improve clinic efficiency and increase patient access to care while simultaneously reducing physician burnout. Implementation barriers include upfront costs, integration with existing technology, and time-intensive training. Technological barriers include adaptability to linguistic differences, compatibility across different clinical encounters, and integration of medical jargon into the note. Broader risks include automation bias and risks to data privacy. Overcoming significant barriers to implementation will facilitate more widespread adoption.Supplementary informationThe online version contains supplementary material available at 10.1007/s12553-021-00568-0.

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Measuring clinical utility in the context of genetic testing: a scoping review.

Publications

Measuring clinical utility in the context of genetic testing: a scoping review.

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