The effects of electronic prescribing on the quality of prescribing.

WHAT IS ALREADY KNOWN ABOUT THIS SUBJECT: Electronic prescribing has been shown to reduce prescribing errors in US hospitals. However we know little about its effect on prescribing quality, or its effectiveness in UK hospitals where systems for medication prescribing and supply are very different. Hospital pharmacists already review prescriptions to both detect errors and improve prescription quality. WHAT THIS STUDY ADDS: Electronic prescribing significantly increased prescribing quality in a UK hospital, as shown by fewer pharmacists' interventions and fewer prescribing errors. However, some new types of error were introduced. There was relatively little overlap between prescribing errors and pharmacists' interventions, signifying their different contributions to prescribing quality. Electronic prescribing and pharmacists' interventions should be viewed as an integrated system. AIMS: To investigate the effects of electronic prescribing (EP) on prescribing quality, as indicated by prescribing errors and pharmacists' clinical interventions, in a UK hospital. METHODS: Prescribing errors and pharmacists' interventions were recorded by the ward pharmacist during a 4 week period both pre- and post-EP, with a second check by the principal investigator. The percentage of new medication orders with a prescribing error and/or pharmacist's intervention was calculated for each study period. RESULTS: Following the introduction of EP, there was a significant reduction in both pharmacists' interventions and prescribing errors. Interventions reduced from 73 (3.0% of all medication orders) to 45 (1.9%) (95% confidence interval (CI) for the absolute reduction 0.2, 2.0%), and errors from 94 (3.8%) to 48 (2.0%) (95% CI 0.9, 2.7%). Ten EP-specific prescribing errors were identified. Only 52% of pharmacists' interventions related to a prescribing error pre-EP, and 60% post-EP; only 40% and 56% of prescribing errors resulted in an intervention pre- and post-EP, respectively. CONCLUSIONS: EP improved the quality of prescribing by reducing both prescribing errors and pharmacists' clinical interventions. Prescribers and pharmacists need to be aware of new types of error with EP, so that they can best target their activities to reduce clinical risk. Pharmacists may need to change the way they work to complement, rather than duplicate, the benefits of EP.

The impact of a closed-loop electronic prescribing and administration system on prescribing errors, administration errors and staff time: a before-and-after study.

OBJECTIVES: To assess the impact of a closed-loop electronic prescribing, automated dispensing, barcode patient identification and electronic medication administration record (EMAR) system on prescribing and administration errors, confirmation of patient identity before administration, and staff time. DESIGN, SETTING AND PARTICIPANTS: Before-and-after study in a surgical ward of a teaching hospital, involving patients and staff of that ward. INTERVENTION: Closed-loop electronic prescribing, automated dispensing, barcode patient identification and EMAR system. MAIN OUTCOME MEASURES: Percentage of new medication orders with a prescribing error, percentage of doses with medication administration errors (MAEs) and percentage given without checking patient identity. Time spent prescribing and providing a ward pharmacy service. Nursing time on medication tasks. RESULTS: Prescribing errors were identified in 3.8% of 2450 medication orders pre-intervention and 2.0% of 2353 orders afterwards (p<0.001; chi(2) test). MAEs occurred in 7.0% of 1473 non-intravenous doses pre-intervention and 4.3% of 1139 afterwards (p = 0.005; chi(2) test). Patient identity was not checked for 82.6% of 1344 doses pre-intervention and 18.9% of 1291 afterwards (p<0.001; chi(2) test). Medical staff required 15 s to prescribe a regular inpatient drug pre-intervention and 39 s afterwards (p = 0.03; t test). Time spent providing a ward pharmacy service increased from 68 min to 98 min each weekday (p = 0.001; t test); 22% of drug charts were unavailable pre-intervention. Time per drug administration round decreased from 50 min to 40 min (p = 0.006; t test); nursing time on medication tasks outside of drug rounds increased from 21.1% to 28.7% (p = 0.006; chi(2) test). CONCLUSIONS: A closed-loop electronic prescribing, dispensing and barcode patient identification system reduced prescribing errors and MAEs, and increased confirmation of patient identity before administration. Time spent on medication-related tasks increased.

Providing feedback to hospital doctors about prescribing errors; a pilot study.

OBJECTIVE: To assess the feasibility and acceptability of obtaining data on prescribing error rates in routine practice, and presenting feedback on such errors to medical staff. SETTING: One clinical directorate of a London teaching trust. METHODS: Ward pharmacists recorded all prescribing errors identified in newly written medication orders on one day each fortnight between February and May 2005. We examined prescribing errors reported on the trust's medication incident database for the same period. MAIN OUTCOME MEASURES: Prescribing errors identified and recorded by ward pharmacists, prescribing errors reported as incident reports; prescribing error rates per clinical specialty; lead consultants' views on receiving feedback on errors for their specialty. RESULTS: During eight data collection days, 4,995 new medication orders were examined. Of these, 462 (9.2%; 95% confidence interval 8.5 -10.1%) contained at least one prescribing error. There were 474 errors in total. Pharmacists indicated that they would have reported 19 (4%) of the prescribing errors as medication incidents. Eight prescribing errors were reported for the entire four-month study period on non-data collection days. Feedback was presented to lead clinicians of 10 clinical specialties. This included graphical summaries showing how the specialty compared with others, and a list of errors identified. This information was well-received by clinicians. CONCLUSION: Prescribing errors identified by ward pharmacists can be systematically fed back at the level of the clinical specialty; this is acceptable to the consultants involved. Incident report data is subject to gross under-reporting. Routinely providing feedback for each consultant team or for individual prescribers will require more focussed data collection.