Implementing real-time prescription benefit tools: Early experiences from 5 academic medical centers

被引:4
|
作者
Luo, Jing [1 ]
Wong, Rachel [2 ]
Mehta, Tanvi [3 ]
Schwartz, Jeremy I. [4 ]
Epstein, Jeremy A. [5 ]
Smith, Erika [6 ]
Kashyap, Nitu [7 ,8 ]
Woreta, Fasika A. [9 ]
Feterik, Kristian [1 ]
Fliotsos, Michael J. [9 ,10 ]
Crotty, Bradley H. [6 ]
机构
[1] Univ Pittsburgh, Div Gen Internal Med, Sch Med, Pittsburgh, PA USA
[2] Renaissance Sch Med Stony Brook, Dept Biomed Informat, Stony Brook, NY USA
[3] Duke Univ, Sch Med, Durham, NC USA
[4] Yale Univ, Sect Gen Internal Med, Sch Med, New Haven, CT USA
[5] Johns Hopkins Univ, Div Gen Internal Med, Sch Med, Baltimore, MD USA
[6] Froedtert & Med Coll Wisconsin, Milwaukee, WI USA
[7] Yale New Haven Hlth, New Haven, CT USA
[8] Yale Sch Med, New Haven, CT USA
[9] Johns Hopkins Univ Hosp, Wilmer Eye Inst, Baltimore, MD USA
[10] Yale New Haven Hosp, Dept Ophthalmol & Visual Sci, New Haven, CT USA
基金
美国国家卫生研究院;
关键词
REDUCE ALERT FATIGUE; UNITED-STATES; CANCER CARE; COST; DRUGS;
D O I
10.1016/j.hjdsi.2023.100689
中图分类号
R19 [保健组织与事业(卫生事业管理)];
学科分类号
摘要
Background: Medication price transparency tools are increasingly available, but data on their use, and their potential effects on prescribing behavior, patient out of pocket (OOP) costs, and clinician workflow integration, is limited.Objective: To describe the implementation experiences with real-time prescription benefit (RTPB) tools at 5 large academic medical centers and their early impact on prescription ordering.Design: and Participants: In this cross-sectional study, we systematically collected information on the characteristics of RTPB tools through discussions with key stakeholders at each of the five organizations. Quantitative encounter data, prescriptions written, and RTPB alerts/estimates and prescription adjustment rates were obtained at each organization in the first three months after "go-live" of the RTPB system(s) between 2019 and 2020.Main measures: Implementation characteristics, prescription orders, cost estimate retrieval rates, and prescription adjustment rates.Key results: Differences were noted with respect to implementation characteristics related to RTPB tools. All of the organizations with the exception of one chose to display OOP cost estimates and suggested alternative prescriptions automatically. Differences were also noted with respect to a patient cost threshold for automatic display. In the first three months after "go-live," RTPB estimate retrieval rates varied greatly across the five organizations, ranging from 8% to 60% of outpatient prescriptions. The prescription adjustment rate was lower, ranging from 0.1% to 4.9% of all prescriptions ordered.Conclusions: In this study reporting on the early experiences with RTPB tools across five academic medical centers, we found variability in implementation char-acteristics and population coverage. In addition RTPB estimate retrieval rates were highly variable across the five organizations, while rates of prescription adjustment ranged from low to modest.
引用
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页数:6
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