Economic evaluation of the impact of medication errors reported by U.S. clinical pharmacists

Abstract

Objective: Medication errors defined as "any preventable event that may cause or lead to inappropriate medication use or patient harm" have been highlighted as a top national priority in a report issued by the Institute of Medicine. However, little information is available on precise costs of medication errors. This study estimated the cost of medication errors reported by clinical pharmacists using a modified societal perspective.

Methods: Information on 779 medication errors was collected in the Medication Error Detection, Amelioration and Prevention (MEDAP) study that documented medication errors observed by clinical pharmacists during a consecutive 14-day period. The rate of medication errors, outcomes (number of errors resulting in temporary/permanent patient harm, prolonged hospitalization, or life-sustaining therapy), and interventions (communication, medication changes, patient monitoring, and treatment referrals) were collected. A decision model was developed to estimate the economic impact of medication errors reported by clinical pharmacists. Event probabilities were derived from MEDAP data. Direct costs were obtained through reviews of the literature, hospital charge data, and Medicare and Medicaid reimbursement. One-way and Monte Carlo sensitivity analyses were used to explore uncertainty in the values.

Results: In the base case, the mean expected cost of a medication error was $88.57. In the Monte Carlo simulation, the mean cost was $89.35 (± $30.17 SD). One-way sensitivity analysis revealed that changes in the probability of medication errors causing hospitalization and the cost of hospitalization had the greatest variability on the outcome ($50.44-$155.81 [probability of hospitalization], $32.59-$136.40 [cost of hospitalization]).

Conclusions: Medication errors are costly to the health care system. A better understanding of medication error costs may be used to justify initiatives to reduce the risk and inefficiency associated with these errors.

Keywords: costs; decision analysis; medication errors; modeling.