Comparison of a Cancer Family History Collection and Risk Assessment Tool – ItRunsInMyFamily – with Risk Assessment by Health-Care Professionals

Autor: Jordon B. Ritchie, Brandon M. Welch, Caitlin G. Allen, Lewis J. Frey, Heath Morrison, Joshua D. Schiffman, Alexander V. Alekseyenko, Brian Dean, Chanita Hughes Halbert, Cecelia Bellcross
Rok vydání: 2021
Předmět:
Zdroj: Public Health Genomics
ISSN: 1662-8063
1662-4246
Popis: Introduction: Primary care providers (PCPs) and oncologists lack time and training to appropriately identify patients at increased risk for hereditary cancer using family health history (FHx) and clinical practice guideline (CPG) criteria. We built a tool, “ItRunsInMyFamily” (ItRuns) that automates FHx collection and risk assessment using CPGs. The purpose of this study was to evaluate ItRuns by measuring the level of concordance in referral patterns for genetic counseling/testing (GC/GT) between the CPGs as applied by the tool and genetic counselors (GCs), in comparison to oncologists and PCPs. The extent to which non-GCs are discordant with CPGs is a gap that health information technology, such as ItRuns, can help close to facilitate the identification of individuals at risk for hereditary cancer. Methods: We curated 18 FHx cases and surveyed GCs and non-GCs (oncologists and PCPs) to assess concordance with ItRuns CPG criteria for referring patients for GC/GT. Percent agreement was used to describe concordance, and logistic regression to compare providers and the tool’s concordance with CPG criteria. Results: GCs had the best overall concordance with the CPGs used in ItRuns at 82.2%, followed by oncologists with 66.0% and PCPs with 60.6%. GCs were significantly more likely to concur with CPGs (OR = 4.04, 95% CI = 3.35–4.89) than non-GCs. All providers had higher concordance with CPGs for FHx cases that met the criteria for genetic counseling/testing than for cases that did not. Discussion/Conclusion: The risk assessment provided by ItRuns was highly concordant with that of GC’s, particularly for at-risk individuals. The use of such technology-based tools improves efficiency and can lead to greater numbers of at-risk individuals accessing genetic counseling, testing, and mutation-based interventions to improve health.
Databáze: OpenAIRE
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