Elsevier

Academic Pediatrics

Volume 10, Issue 4, July–August 2010, Pages 233-237
Academic Pediatrics

Medication Safety
Using Pharmacy Data to Screen for Look-Alike, Sound-Alike Substitution Errors in Pediatric Prescriptions

https://doi.org/10.1016/j.acap.2010.04.024Get rights and content

Objective

The aim of this study was to pilot test a screening approach to detect potential look-alike, sound-alike (LASA) errors in pediatric outpatient prescriptions.

Method

Medicaid pharmacy claims from one state were reviewed. From a list of LASA drug pairs, we identified candidate pairs meeting the following criteria: 1) one drug was commonly prescribed in children; 2) the paired drug was uncommonly prescribed for children; and 3) both drugs were available as oral preparations only, resulting in 11 LASA pairs. We identified patients who usually received one drug in a pair, then presented with a first dispensing of the paired drug, representing a “screening alert” for potential LASA error. We determined a “true error” as any patient who triggered a screening alert, received only one dispensing of the paired drug in the subsequent 6 months, and had no diagnoses supporting the dispensing of the paired drug.

Results

Among the 22 test drugs, there were 1 420 091 prescriptions to 173 005 subjects. There were 395 screening alerts generated, representing a screening alert frequency of 0.28 screening alerts per 1000 prescriptions. We identified 43 true LASA errors. In the dataset, the overall LASA error rate is estimated to be approximately 0.00003%, or 0.03 LASA errors per 1000 prescriptions.

Conclusion

Prescription dispensing patterns can be used to screen for LASA errors in pediatric prescriptions. The rates of pediatric LASA errors appear to be much lower than other types of pediatric medication errors and may be best addressed by automated processes.

Section snippets

Data Source

This study used 2000–2006 South Carolina Medicaid paid claims data for patients aged less than 20 years, obtained from the South Carolina Office of Research and Statistics.12 The dataset contained unique encrypted patient identifiers used to link enrollees to pharmacy and diagnostic data. We began with outpatient dispensed prescriptions, then matched patient data (from enrollee files) to each prescription. We obtained subjects' encounter diagnoses from outpatient, inpatient, and emergency

Results

Among the 22 test drugs, there were 1 420 091 prescriptions to 173 005 subjects. We identified 395 screening alerts, for a screening alert rate of 0.28 screening alerts per 1000 prescriptions. The Table shows patients prescribed each of the 22 drugs (11 LASA pairs), number of prescriptions of each drug, number (and frequencies) of prescriptions that triggered a screening alert, the PPVs of the alerts, and the corresponding estimate of true LASA error rate. The total number of prescriptions

Discussion

We believe that this study demonstrates the feasibility of real-time pharmacy screening for LASA errors, and the frequency of those errors appears to be generally low in the 22 drugs studied. We believe these analyses to be the first to attempt to determine frequencies of LASA errors in pediatric care. Indeed, little published data of any type exist on LASA errors in children. One other group of authors has evaluated LASA errors in children, also utilizing a Medicaid database. Although their

Acknowledgments

This project was supported by grant K08HS015679 from the Agency for Healthcare Research and Quality (William T. Basco, Jr, principal investigator). The project was also supported by grant D54HP05448 from the Health Resources and Services Administration (William T. Basco, Jr, principal investigator). The content is solely the responsibility of the authors and does not necessarily represent the official views of the funding agencies. The authors thank James R. Roberts, MD, MPH, for his assistance

References (20)

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