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Retrospective Detection of Potential Medication Errors Involving Drugs with Similar Names

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ABSTRACT

Objective

To estimate frequencies of potential errors involving similarly named drugs using a retrospective claims database and measure the association between frequencies of potential errors and two measures of drug name similarity, edit distance (minimum number of insertions, substitutions, or deletions of characters required to change a given word into another target word) and normalized edit distance (proportion of letters that must be changed to commute one word to another, and ranges from 0 to 1, with 0 indicating identical words, and 1 indicating a pair of words with no common letters).

Design

Retrospective database analysis.

Setting

Idaho Medicaid claims data from 1993 to 2000.

Patients

Not applicable.

Intervention

Potential errors were detected using adjacent claims generated by dispensing of one drug followed by dispensing of the other drug with a similar name. In all, four potential error criteria were developed: two for detecting potential refill errors and two for detecting potential initial errors. A total of 10 drug pairs were randomly selected from the Idaho Medicaid claims database for each value of edit distance, which ranged from 1 to 30 (n = 300).

Main Outcome Measures

Frequencies of potential medication errors in claims sequences for initial and refill claims, edit distance, and normalized edit distance.

Results

Of 300 drug pairs studied, 106 (35.33%) were involved in at least one potential error. A total of 1,138 dispensing episodes satisfied the criteria for potential errors. Frequencies of potential errors per drug pair were negatively associated with edit distance (r = –0.133, P < .05) and normalized edit distance (r = –0.226, P < .01). Frequencies of potential initial errors also were negatively associated with edit distance (r = –0.126, P < .05) and normalized edit distance (r = –0.222, P < .01). Potential refill errors also had negative association with edit distance (r = –0.134, P < .05) and normalized edit distance (r = –0.226, P < .01).

Conclusion

Error criteria were successfully applied to a retrospective claims database to detect potential initial and refill errors that involved similarly named drugs.

Section snippets

Objectives

The objectives of this study were to estimate the frequencies of potential errors involving drugs with similar names using a retrospective claims database and to validate frequencies of potential errors as a measure of drug name similarity by examining the association between the frequencies of potential errors and edit distance and normalized edit distance. The following hypotheses were formulated for the latter objective:

H1: A negative association exists between edit distance and frequencies

Methods

Idaho Medicaid claims data from 1993 to 2000 were analyzed for the purpose of this study. A computer program for measuring edit distance was developed by the programmer working with the Drug Utilization Review Board at the Idaho State University College of Pharmacy. Accuracy of the computer program was verified by comparing edit distance values for selected drug pairs with values obtained for those pairs from an external source.15 Normalized edit distance was computed by dividing the edit

Results

Based on screening of the Idaho Medicaid claims database using our potential error criteria, 106 of 300 drug pairs (35.33%) were involved in at least one episode of adjacent claims for both drugs. A total of 1,138 potential errors were observed; 17.54% were potential initial errors while the remaining 82.46% were potential refill errors (Table 2). The mean number (± SD) of total potential errors observed for any drug pair was 3.79 ±  per drug pair. The mean number (± SD) of potential errors for a

Discussion

Using the method developed in this study, a claims database can be used to capture potential initial or refill errors that occur as a result of similarity in drug names. Algorithms used to detect potential errors were designed to identify claims sequences with high likelihood of potential errors. Besides focusing on adjacent claims sequences during an index period, the possibility of capturing look-alike/sound-alike medication errors was increased by using a confirmation period subsequent to

Limitations

Our method for identifying look-alike/sound-alike medication errors is based on important assumptions, including isolated incidence of look-alike/sound-alike errors, and rectification of such errors during the next refill. It did not capture situations in which drug errors lasted for the duration greater than the maximum index period of 60 days. Identification of this type of error was beyond the scope of error patterns defined in this study. The results of this study cannot be generalized for

Conclusion

Error criteria developed in this study were successfully applied to a retrospective claims database to detect potential initial and refill errors that involved drugs with similar names. Negative correlations observed between measures of orthographic drug name similarity and potential error frequencies confirmed the validity of our measure for use in look-alike/sound-alike medication error research.

Using study error criteria, pharmacovigilance researchers, health systems, or managed care

CE Credit

To obtain 1.5 contact hours of continuing education credit (0.15 CEUs) for completing “Retrospective Detection of Potential Medication Errors Involving Drugs with Similar Names,” complete the assessment exercise and CE registration form and return them to APhA. A statement of credit will be awarded to respondents achieving a grade of 70% or better. APhA continuing education policy provides you with two opportunities to successfully complete this continuing education examination. Please note

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Continuing education credits: See learning objectives and test questions at the end of this article, which is number 202-000-05-197-H01 in APhA’s educational programs. CE answer sheets are located at the end of this article. To take the CE test for this article online, go to www.pharmacist.com/education.cfm, and follow the links to the APhA CE center.

Disclosure: The authors declare no conflicts of interest or financial interests in any product or services mentioned in this article, including grants, employment, gifts, stock holdings, or honoraria.

Acknowledgments: To Craig Kelley, BS, for computer programming and technical support; and Joseph Thomas III, PhD, for input during preparation of this manuscript.

Previously presented at the American Pharmaceutical Association Annual Meeting, March 15–19, 2002, Philadelphia, Pa.

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