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Identifying drug orders stopped within 45 minutes of prescribing can help detect medication errors

Drug prescribing errors are one of the most frequent types of medical errors. Methods for identifying medication errors are subject to inaccuracy and systematic bias. However, a new study shows that identifying drug prescriptions that are stopped within 45 minutes of the initial prescribing is an inexpensive and quick way to detect prescribing errors.

Researchers at the University of Pennsylvania Center for Education and Research on Therapeutics analyzed medication orders that were entered into a computerized physician order entry (CPOE) system at an urban hospital and discontinued within 2 hours. They then investigated these stop orders in real time via interviews with the corresponding ordering physicians. Each order was also independently reviewed by a clinical pharmacist or physician.

Of 114 rapidly discontinued orders by 75 physicians during a 24-day period, two-thirds of medication orders discontinued within 45 minutes were deemed inappropriate (for example, wrong dose or drug). In addition, 55 percent of medication orders discontinued within 2 hours were deemed inappropriate. Physicians said they typically stopped orders due to drug-disease reconsiderations, drug-drug interactions, and patient preferences.

Although doctors often caught their own mistakes, the impetus for the stop order often came from other house staff, nurses, pharmacists (who often call prescribing physicians with questions), and attending physicians. The classes of drugs most likely to be quickly discontinued were low therapeutic index drugs, insulin, antiretrovirals, antineoplastics, and immunosuppressive drugs. The study was supported by the Agency for Healthcare Research and Quality (HS11530).

See "Identifying and quantifying medication errors: Evaluation of rapidly discontinued medication orders submitted to a computerized physician order entry system," by Ross Koppel, Ph.D., Charles E. Leonard, Pharm.D., A. Russell Localio, J.D., Ph.D., and others, in the July/August 2008 Journal of the American Medical Informatics Association 15, pp. 461-465.

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