Survival After Implementation of a Decision Support Tool to Facilitate Evidence-Based Cancer Treatment.

Autor:	Ojha RP; Center for Epidemiology & Healthcare Delivery Research, JPS Health Network, Fort Worth, TX., Lu Y; Center for Epidemiology & Healthcare Delivery Research, JPS Health Network, Fort Worth, TX., Narra K; Oncology and Infusion Center, JPS Health Network, Fort Worth, TX., Meadows RJ; Center for Epidemiology & Healthcare Delivery Research, JPS Health Network, Fort Worth, TX., Gehr AW; Center for Epidemiology & Healthcare Delivery Research, JPS Health Network, Fort Worth, TX., Mantilla E; Acclaim Neurology, JPS Health Network, Fort Worth, TX., Ghabach B; Oncology and Infusion Center, JPS Health Network, Fort Worth, TX.
Jazyk:	angličtina
Zdroj:	JCO clinical cancer informatics [JCO Clin Cancer Inform] 2023 Jun; Vol. 7, pp. e2300001.
DOI:	10.1200/CCI.23.00001
Abstrakt:	Purpose: Decision support tools (DSTs) to facilitate evidence-based cancer treatment are increasingly common in care delivery organizations. Implementation of these tools may improve process outcomes, but little is known about effects on patient outcomes such as survival. We aimed to evaluate the effect of implementing a DST for cancer treatment on overall survival (OS) among patients with breast, colorectal, and lung cancer. Methods: We used institutional cancer registry data to identify adults treated for first primary breast, colorectal, or lung cancer between December 2013 and December 2017. Our intervention of interest was implementation of a commercial DST for cancer treatment, and outcome of interest was OS. We emulated a single-arm trial with historical comparison and used a flexible parametric model to estimate standardized 3-year restricted mean survival time (RMST) difference and mortality risk ratio (RR) with 95% confidence limits (CLs). Results: Our study population comprised 1,059 patients with cancer (323 breast, 318 colorectal, and 418 lung). Depending on cancer type, median age was 55-60 years, 45%-67% were racial/ethnic minorities, and 49%-69% were uninsured. DST implementation had little effect on survival at 3 years. The largest effect was observed among patients with lung cancer (RMST difference, 1.7 months; 95% CL, -0.26 to 3.7; mortality RR, 0.95; 95% CL, 0.88 to 1.0). Adherence with tool-based treatment recommendations was >70% before and >90% across cancers. Conclusion: Our results suggest that implementation of a DST for cancer treatment has nominal effect on OS, which may be partially attributable to high adherence with evidence-based treatment recommendations before tool implementation in our setting. Our results raise awareness that improved process outcomes may not translate to improved patient outcomes in some care delivery settings.
Databáze:	MEDLINE
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