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

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.

Conflict of interest statement

The authors report no conflicts of interest in the research; there are no plans to commercialize the software.

Schattauer GmbH Stuttgart.

Figures

Fig. 1

Adaptation of Carayon's systems engineering to improve patient safety (SEIPS) framework.

Fig. 2

Representative screenshot and output from Automated Patient History Intake Device (APHID).

Fig. 3

Protocol for Trial.

Fig. 4

Flowchart for patient enrollment, randomization, and analysis.

Appendix Fig. A1

Medication discrepancy risk scoring tool.