Quantifying Discharge Medication Reconciliation Errors at 2 Pediatric Hospitals

Abstract

Introduction: Medication reconciliation errors (MREs) are common and can lead to significant patient harm. Quality improvement efforts to identify and reduce these errors typically rely on resource-intensive chart reviews or adverse event reporting. Quantifying these errors hospital-wide is complicated and rarely done. The purpose of this study is to define a set of 6 MREs that can be easily identified across an entire healthcare organization and report their prevalence at 2 pediatric hospitals.

Methods: An algorithmic analysis of discharge medication lists and confirmation by clinician reviewers was used to find the prevalence of the 6 discharge MREs at 2 pediatric hospitals. These errors represent deviations from the standards for medication instruction completeness, clarity, and safety. The 6 error types are Duplication, Missing Route, Missing Dose, Missing Frequency, Unlisted Medication, and See Instructions errors.

Results: This study analyzed 67,339 discharge medications and detected MREs commonly at both hospitals. For Institution A, a total of 4,234 errors were identified, with 29.9% of discharges containing at least one error and an average of 0.7 errors per discharge. For Institution B, a total of 5,942 errors were identified, with 42.2% of discharges containing at least 1 error and an average of 1.6 errors per discharge. The most common error types were Duplication and See Instructions errors.

Conclusion: The presented method shows these MREs to be a common finding in pediatric care. This work offers a tool to strengthen hospital-wide quality improvement efforts to reduce pediatric medication errors.

Fig. 1.

Total number of each error type identified at each institution (N = 10,176). Error types ordered by descending count of Institution A.

Fig. 2.

Numerator is the number of each error type identified at each institution; the denominator is the number of total discharge medications at each institution. Note that multiple errors could be present for a single discharge medication. Error types ordered by descending percent value of Institution A.

Fig. 3.

At each institution, all discharge medications were analyzed by an algorithm to identify six error types. A clinician reviewed each error identified by the algorithm. Reported errors were only those confirmed by a clinician.