Evaluation of Multimedia Medication Reconciliation Software: A Randomized Controlled, Single-Blind Trial to Measure Diagnostic Accuracy for Discrepancy Detection

Appl Clin Inform. 2018 Apr;9(2):285-301. doi: 10.1055/s-0038-1645889. Epub 2018 May 2.

Abstract

Background: The Veterans Affairs Portland Healthcare System developed a medication history collection software that displays prescription names and medication images.

Objective: This article measures the frequency of medication discrepancy reporting using the medication history collection software and compares with the frequency of reporting using a paper-based process. This article also determines the accuracy of each method by comparing both strategies to a best possible medication history.

Study design: Randomized, controlled, single-blind trial.

Setting: Three community-based primary care clinics associated with the Veterans Affairs Portland Healthcare System: a 300-bed teaching facility and ambulatory care network serving Veteran soldiers in the Pacific Northwest United States.

Participants: Of 212 patients with primary care appointments, 209 patients fulfilled the study requirements.

Intervention: Patients randomized to a software-directed medication history or a paper-based medication history. Randomization and allocation to treatment groups were performed using a computer-based random number generator. Assignments were placed in a sealed envelope and opened after participant consent. The research coordinator did not know or have access to the treatment assignment until the time of presentation.

Main outcome measures: The primary analysis compared the discrepancy detection rates between groups with respect to the health record and a best possible medication history.

Results: Of 3,500 medications reviewed, we detected 1,435 discrepancies. Forty-six percent of those discrepancies were potentially high risk for causing an adverse drug event. There was no difference in detection rates between treatment arms. Software sensitivity was 83% and specificity was 91%; paper sensitivity was 81% and specificity was 94%. No participants were lost to follow-up.

Conclusion: The medication history collection software is an efficient and scalable method for gathering a medication history and detecting high-risk discrepancies. Although it included medication images, the technology did not improve accuracy over a paper list when compared with a best possible medication history.

Trial registration: ClinicalTrials.gov Identifier: NCT02135731.

Publication types

  • Randomized Controlled Trial
  • Research Support, U.S. Gov't, Non-P.H.S.

MeSH terms

  • Aged
  • Electronic Health Records
  • Female
  • Humans
  • Male
  • Medication Reconciliation*
  • Middle Aged
  • Multimedia*
  • Primary Health Care / statistics & numerical data
  • Research Design
  • Single-Blind Method
  • Software*

Associated data

  • ClinicalTrials.gov/NCT02135731

Grants and funding

Funding This study was funded by VA National Center for Patient Safety.