Dataset Information

The development of the Clinician-reported Genetic testing Utility InDEx (C-GUIDE): a novel strategy for measuring the clinical utility of genetic testing.

ABSTRACT: PURPOSE:Clinical utility describes a genetic test's value to patients, families, health-care providers, systems, or society. This study aims to define clinical utility from the perspective of clinicians and develop a novel outcome measure that operationalizes this concept. METHODS:Item selection for the Clinician-reported Genetic testing Utility InDEx (C-GUIDE) was informed by a scoping review of the literature. Item reduction was guided by qualitative and quantitative feedback from semistructured interviews and a cross-sectional survey of genetics and nongenetics specialists. Final item selection, index scoring, and structure were guided by feedback from an expert panel of genetics professionals. RESULTS:A review of 194 publications informed the selection of a preliminary set of 25 items. Feedback from 35 semistructured interviews, 113 surveys, and 11 expert panelists informed the content and wording of C-GUIDE's final set of 18 items that reflect on the utility of testing related to diagnosis, management, and familial/psychosocial impact. C-GUIDE achieves content and face validity for use in a range of diagnostic genetic testing settings. CONCLUSION:Work to establish reliability and construct validity is underway. C-GUIDE will be useful in comparative studies to generate policy-relevant evidence pertaining to the clinical utility of genetic testing across a range of settings.

SUBMITTER: Hayeems RZ

PROVIDER: S-EPMC6944639 | biostudies-literature | 2020 Jan

REPOSITORIES: biostudies-literature

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The development of the Clinician-reported Genetic testing Utility InDEx (C-GUIDE): a novel strategy for measuring the clinical utility of genetic testing.

Hayeems R Z RZ Luca S S Ungar W J WJ Bhatt A A Chad L L Pullenayegum E E Meyn M S MS

Genetics in medicine : official journal of the American College of Medical Genetics 20190731 1

<h4>Purpose</h4>Clinical utility describes a genetic test's value to patients, families, health-care providers, systems, or society. This study aims to define clinical utility from the perspective of clinicians and develop a novel outcome measure that operationalizes this concept.<h4>Methods</h4>Item selection for the Clinician-reported Genetic testing Utility InDEx (C-GUIDE) was informed by a scoping review of the literature. Item reduction was guided by qualitative and quantitative feedback fr ...[more]

PMID: 31363181

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Project description:BACKGROUND:Various self-reported or clinician-reported (as a proxy) measures exist to quantify the burden of schizophrenia on patients. Evidence of the psychometric relationship between these measures to inform their practical use is limited. OBJECTIVES:Our objective was to conduct an exploratory analysis of the construct validity of patient-reported (EQ-5D, SF-6D, WEMWBS, SQLS subscales of Psychosocial, Motivation, Symptoms) versus clinician-reported measures (PANSS, CGI-SCH, NSA-4, HoNOS-PbR) to inform future use of patient-reported measures for burden-of-illness assessment and/or economic evaluation. METHODS:In an adult patient population with schizophrenia, construct validity was assessed in relation to convergent and known-group validity. Convergent validity was assessed using Spearman's rank absolute correlation strength (ACS: weak ≤ 0.3, moderate = 0.3 < 0.5, strong ≥ 0.5) and graphically using locally weighted scatterplot smoothing (LOWESS) techniques. Known-group validity was assessed using Cohen's d absolute effect size (AES: small ≤ 0.5, moderate = 0.5 < 0.8, large ≥ 0.8). Floor and ceiling effects were assessed as a proxy of sensitivity in this cross-sectional study. Statistical significance was assessed at the 5% threshold level (p < 0.05). Across head-to-head assessments, the frequency of producing the strongest ACS, largest AES, and statistically significant results determined the best overall construct validity. RESULTS:Overall, 304 patients consented to the study. In relation to statistically significant results, the SF-6D most frequently exhibited the strongest ACS and largest AES against the clinician-reported measure scores (ACS range 0.084-0.436; AES range 0.043-0.746), and the SQLS Motivation subscale most frequently exhibited the weakest/smallest values (ACS range 0.009-0.157; AES range 0.002-0.397), although these results were mixed according to the clinician-reported measure used for comparative analysis (ACS range 0.009-0.529; AES range 0.002-0.934). CONCLUSION:The SF-6D indicated the best (mostly moderate) construct validity but still missed the negative symptoms of the condition. Although further evidence is required to confirm or refute these exploratory results, compared with the EQ-5D, the SF-6D can be self-reported to better capture generic health-related quality-of-life aspects of schizophrenia for the purpose of economic evaluation. The lack of construct validity for SQLS Motivation and Symptoms subscales were hypothesized post-hoc to be representative of the complementary information elicited by the subscales not captured by the clinician-reported measures. Therefore, the SQLS can be self-reported to capture complementary (i.e., additional) information relative to clinician-reported measures.

Project description:BackgroundClinicians often report that their own anxiety and low self-efficacy inhibit their use of evidence-based suicide prevention practices, including gold-standard screening and brief interventions. Exposure therapy to reduce clinician maladaptive anxiety and bolster self-efficacy use is a compelling but untested approach to improving the implementation of suicide prevention evidence-based practices (EBPs). This project brings together an interdisciplinary team to leverage decades of research on behavior change from exposure theory to design and pilot test an exposure-based implementation strategy (EBIS) to target clinician anxiety to improve suicide prevention EBP implementation.MethodsWe will develop, iteratively refine, and pilot test an EBIS paired with implementation as usual (IAU; didactic training and consultation) in preparation for a larger study of the effect of this strategy on reducing clinician anxiety, improving self-efficacy, and increasing use of the Columbia Suicide Severity Rating Scale and the Safety Planning Intervention in outpatient mental health settings. Aim 1 of this study is to use participatory design methods to develop and refine the EBIS in collaboration with a stakeholder advisory board. Aim 2 is to iteratively refine the EBIS with up to 15 clinicians in a pilot field test using rapid cycle prototyping. Aim 3 is to test the refined EBIS in a pilot implementation trial. Forty community mental health clinicians will be randomized 1:1 to receive either IAU or IAU + EBIS for 12 weeks. Our primary outcomes are EBIS acceptability and feasibility, measured through questionnaires, interviews, and recruitment and retention statistics. Secondary outcomes are the engagement of target implementation mechanisms (clinician anxiety and self-efficacy related to implementation) and preliminary effectiveness of EBIS on implementation outcomes (adoption and fidelity) assessed via mixed methods (questionnaires, chart-stimulated recall, observer-coded role plays, and interviews).DiscussionOutcomes from this study will yield insight into the feasibility and utility of directly targeting clinician anxiety and self-efficacy as mechanistic processes informing the implementation of suicide prevention EBPs. Results will inform a fully powered hybrid effectiveness-implementation trial to test EBIS' effect on implementation and patient outcomes.Trial registrationClinical Trials Registration Number: NCT05172609 . Registered on 12/29/2021.

Dataset Information

The development of the Clinician-reported Genetic testing Utility InDEx (C-GUIDE): a novel strategy for measuring the clinical utility of genetic testing.

Publications

The development of the Clinician-reported Genetic testing Utility InDEx (C-GUIDE): a novel strategy for measuring the clinical utility of genetic testing.

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