Michelle Condren1, Brooke L Honey2, Sandra M Carter3, Nelson Ngo3, Jeremy Landsaw3, Cheryl Bryant4, Stephen Gillaspy4. 1. Department of Pharmacy, Clinical and Administrative Sciences-Tulsa, University of Oklahoma College of Pharmacy and Department of Pediatrics, University of Oklahoma School of Community Medicine, Tulsa, Okla. Electronic address: michelle-condren@ouhsc.edu. 2. Department of Pharmacy, Clinical and Administrative Sciences-Tulsa, University of Oklahoma College of Pharmacy and Department of Pediatrics, University of Oklahoma School of Community Medicine, Tulsa, Okla. 3. University of Oklahoma College of Pharmacy, Oklahoma City, Okla. 4. Department of Pediatrics, Section of General and Community Pediatrics, University of Oklahoma College of Medicine, Oklahoma City, Okla.
Abstract
OBJECTIVE: To measure the difference in prescribing error rates between 2 clinics, 1 with a system in place to reduce errors and 1 with no such system; to determine variables that affect the likelihood of prescription errors. METHODS: This was a retrospective study at 2 university-based general pediatric clinics utilizing the same electronic medical record (EMR) system. Clinic 1 employed pharmacists who provided daily prescription review, provider feedback and education, and EMR customization to decrease errors. Clinic 2 had no systems in place for reducing prescribing errors. Prescriptions written by resident physicians over 2 months were identified and reviewed. RESULTS: A total of 1361 prescriptions were reviewed, 40.7% from clinic 1 and 59.3% from clinic 2. Errors were found in 201 prescriptions (14.8%). Clinics 1 and 2 had error rates of 11% and 17.5%, respectively (P = .0012). The odds of a prescription error at clinic 2 were 1.7 times the odds of a prescription error at clinic 1. Logistic regression identified clinic, nonpediatric resident, liquid dose forms, and younger patient age as significant predictors of prescription errors. Half of the errors could have been prevented with consistent use of a custom medication list within the EMR. CONCLUSIONS: We found 37% fewer prescribing errors in a clinic with systems in place for prescribing error detection and prevention. Pediatric clinics should explore systematic procedures for identifying, resolving, and providing education about prescribing errors to reduce patient risk.
OBJECTIVE: To measure the difference in prescribing error rates between 2 clinics, 1 with a system in place to reduce errors and 1 with no such system; to determine variables that affect the likelihood of prescription errors. METHODS: This was a retrospective study at 2 university-based general pediatric clinics utilizing the same electronic medical record (EMR) system. Clinic 1 employed pharmacists who provided daily prescription review, provider feedback and education, and EMR customization to decrease errors. Clinic 2 had no systems in place for reducing prescribing errors. Prescriptions written by resident physicians over 2 months were identified and reviewed. RESULTS: A total of 1361 prescriptions were reviewed, 40.7% from clinic 1 and 59.3% from clinic 2. Errors were found in 201 prescriptions (14.8%). Clinics 1 and 2 had error rates of 11% and 17.5%, respectively (P = .0012). The odds of a prescription error at clinic 2 were 1.7 times the odds of a prescription error at clinic 1. Logistic regression identified clinic, nonpediatric resident, liquid dose forms, and younger patient age as significant predictors of prescription errors. Half of the errors could have been prevented with consistent use of a custom medication list within the EMR. CONCLUSIONS: We found 37% fewer prescribing errors in a clinic with systems in place for prescribing error detection and prevention. Pediatric clinics should explore systematic procedures for identifying, resolving, and providing education about prescribing errors to reduce patient risk.
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