Where Do Real-Time Prescription Benefit Tools Fit in the Landscape of High US Prescription Medication Costs? A Narrative Review

被引:0
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作者
Rachel Wong
Tanvi Mehta
Bradley Very
Jing Luo
Kristian Feterik
Bradley H. Crotty
Jeremy A. Epstein
Michael J. Fliotsos
Nitu Kashyap
Erika Smith
Fasika A. Woreta
Jeremy I. Schwartz
机构
[1] Renaissance School of Medicine at Stony Brook,Department of Biomedical Informatics
[2] Duke University School of Medicine,Department of Medicine
[3] University of Pittsburgh School of Medicine,Department of Medicine
[4] Froedtert & the Medical College of Wisconsin Health Network,Department of Ophthalmology and Visual Science
[5] Johns Hopkins University School of Medicine,Joint Data Analytics Team
[6] Yale School of Medicine, Internal Medicine and Information Technology
[7] Yale New Haven Hospital,Wilmer Eye Institute
[8] Yale New Haven Health and Yale School of Medicine,Section of General Internal Medicine
[9] Johns Hopkins University School of Medicine,undefined
[10] Yale University School of Medicine,undefined
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关键词
Prescription medication costs; Real-time prescription benefit tools; Medication price transparency; Cost of care; Formulary decision support;
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学科分类号
摘要
The problem of unaffordable prescription medications in the United States is complex and can result in poor patient adherence to therapy, worse clinical outcomes, and high costs to the healthcare system. While providers are aware of the financial burden of healthcare for patients, there is a lack of actionable price transparency at the point of prescribing. Real-time prescription benefit (RTPB) tools are new electronic clinical decision support tools that retrieve patient- and medication-specific out-of-pocket cost information and display it to clinicians at the point of prescribing. The rise in US healthcare costs has been a major driver for efforts to increase medication price transparency, and mandates from the Centers for Medicare & Medicaid Services for Medicare Part D sponsors to adopt RTPB tools may spur integration of such tools into electronic health records. Although multiple factors affect the implementation of RTPB tools, there is limited evidence on outcomes. Further research will be needed to understand the impact of RTPB tools on end results such as prescribing behavior, out-of-pocket medication costs for patients, and adherence to pharmacologic treatment. We review the terminology and concepts essential in understanding the landscape of RTPB tools, implementation considerations, barriers to adoption, and directions for future research that will be important to patients, prescribers, health systems, and insurers.
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页码:1038 / 1045
页数:7
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