Development of an algorithm to detect methotrexate wrong frequency error using computerized health care data

Abstract

Purpose We validated an algorithm to detect frequency errors in computerized healthcare data and estimated the incidence of these errors in an integrated healthcare system. Methods We applied Sentinel System analytic tools on the electronic health records of Kaiser Permanente, Northern California, January 1, 2010, through May 30, 2015,to identify rheumatoid arthritis (RA) patients with new use of methotrexate (365‐day baseline period). We identified potential methotrexate frequency errors using ICD‐9 code 995.20 (adverse drug event), Current Procedural Terminology (CPT) code 96409 for injection of leucovorin and prescription refill patterns. We performed chart review to confirm the frequency errors, assessed performance for detecting frequency errors, and estimated the incidence of chart‐confirmed errors. Results The study included 24,529 methotrexate dispensings among 3,668 RA patients. Among these, 722 (3%) had one dispensing and 23,807 (97.1%) had ≥2 dispensings during 1‐year follow‐up period. We flagged 653 (2.7%) with a potential medication error (46 with one dispensing and 607 with ≥2 dispensings). We sampled 94 for chart review, and confirmed three methotrexate errors. All three confirmed frequency errors involved a first methotrexate dispensing followed by injected rescue therapy, leucovorin, (positive predictive value, 60%; 95% confidence interval [CI], 15‐95%). No potential errors were found among patients with ≥2 dispensings. We estimated the frequency error incidence among one methotrexate dispensing to be 0.4% (95%CI, 0.1% to 1.2%). Conclusion Rescue therapy is a specific indicator of methotrexate overdose among first methotrexate dispensings. This method is generalizable to other medications with serious adverse events treated with antidotes.

Implementation status of safety measures to prevent errors with non-oncologic methotrexate: surveys in community and hospital pharmacies

“…The availability of reliable data on error rates is sparse. For instance, in the USA an error rate of 0.4% of MTX packages dispensed was detected by an algorithm [7]. Case reports and pharmacovigilance evaluations show that a significant number of patients continue to be harmed by accidental overdoses worldwide [6,[8][9][10].…”