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

Healthc (Amst). 2023 Jun;11(2):100689. doi: 10.1016/j.hjdsi.2023.100689. Epub 2023 Mar 28.

Abstract

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 characteristics 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.

MeSH terms

  • Academic Medical Centers
  • Cross-Sectional Studies
  • Drug Costs*
  • Drug Prescriptions*
  • Health Expenditures
  • Humans