M Hellot-Guersing1, C Jarre2, C Molina2, A-S Leromain2, C Derharoutunian2, A Gadot2, R Roubille2. 1. Service de pharmacie, centre hospitalier Lucien-Hussel, montée du Docteur-Chapuis, 38200 Vienne, France. Electronic address: m.hellot-guersing@ch-vienne.fr. 2. Service de pharmacie, centre hospitalier Lucien-Hussel, montée du Docteur-Chapuis, 38200 Vienne, France.
Abstract
OBJECTIVES: Computerized physician order entry (CPOE) can generate medication errors. It is necessary to identify them and analyse their causes in order to secure the medication use system. METHODS: Errors were recorded during the pharmaceutical analysis of prescriptions over a period of 4 years on 425 beds. A code frame was provided. Errors were classified according to type, causes and time of detection. The most often drug implicated and the error correction rate were studied. Deep causes were determined and contributing factors were listed. RESULTS: Among 99,536 prescriptions analyzed, 2636 errors were detected (2.65 errors per 100 orders analyzed). The most common error was omission (31.49%). The most represented cause was redundancy requirement (11.34%). Antibacterials were most commonly involved (224 errors). Exactly 65.9% of the prescriptions were modified by physicians. Three root causes were identified: (1) configuration issues; (2) misuse; (3) design problem. Three types of contributing factors have also been detailed: economic, human and technical factors. CONCLUSIONS: Identifying root causes has targeted three types of improvement actions: (1) software settings; (2) training of users; (3) requests for improvements. Contributing factors have to be identified to control the generated risk. Some errors related to CPOE may lead to serious side effects for the patient. That is why it is necessary to identify these errors and analyze them in order to implement improvement actions and prevention to secure the prescription.
OBJECTIVES: Computerized physician order entry (CPOE) can generate medication errors. It is necessary to identify them and analyse their causes in order to secure the medication use system. METHODS: Errors were recorded during the pharmaceutical analysis of prescriptions over a period of 4 years on 425 beds. A code frame was provided. Errors were classified according to type, causes and time of detection. The most often drug implicated and the error correction rate were studied. Deep causes were determined and contributing factors were listed. RESULTS: Among 99,536 prescriptions analyzed, 2636 errors were detected (2.65 errors per 100 orders analyzed). The most common error was omission (31.49%). The most represented cause was redundancy requirement (11.34%). Antibacterials were most commonly involved (224 errors). Exactly 65.9% of the prescriptions were modified by physicians. Three root causes were identified: (1) configuration issues; (2) misuse; (3) design problem. Three types of contributing factors have also been detailed: economic, human and technical factors. CONCLUSIONS: Identifying root causes has targeted three types of improvement actions: (1) software settings; (2) training of users; (3) requests for improvements. Contributing factors have to be identified to control the generated risk. Some errors related to CPOE may lead to serious side effects for the patient. That is why it is necessary to identify these errors and analyze them in order to implement improvement actions and prevention to secure the prescription.