Electronic prescribing improves medication safety in community-based office practices.
BACKGROUND
Although electronic prescribing (e-prescribing) holds promise for preventing prescription errors in the ambulatory setting, research on its effectiveness is inconclusive.


OBJECTIVE
To assess the impact of a stand-alone e-prescribing system on the rates and types of ambulatory prescribing errors.


METHODS
Prospective, non-randomized study using pre-post design of 15 providers who adopted e-prescribing with concurrent controls of 15 paper-based providers from September 2005 through June 2007.


METHODS
Use of a commercial, stand-alone e-prescribing system with clinical decision support including dosing recommendations and checks for drug-allergy interactions, drug-drug interactions, and duplicate therapies.


METHODS
Prescribing errors were identified by a standardized prescription and chart review.


RESULTS
We analyzed 3684 paper-based prescriptions at baseline and 3848 paper-based and electronic prescriptions at one year of follow-up. For e-prescribing adopters, error rates decreased nearly sevenfold, from 42.5 per 100 prescriptions (95% confidence interval (CI), 36.7-49.3) at baseline to 6.6 per 100 prescriptions (95% CI, 5.1-8.3) one year after adoption (p < 0.001). For non-adopters, error rates remained high at 37.3 per 100 prescriptions (95% CI, 27.6-50.2) at baseline and 38.4 per 100 prescriptions (95% CI, 27.4-53.9) at one year (p = 0.54). At one year, the error rate for e-prescribing adopters was significantly lower than for non-adopters (p < 0.001). Illegibility errors were very high at baseline and were completely eliminated by e-prescribing (87.6 per 100 prescriptions at baseline for e-prescribing adopters, 0 at one year).


CONCLUSIONS
Prescribing errors may occur much more frequently in community-based practices than previously reported. Our preliminary findings suggest that stand-alone e-prescribing with clinical decision support may significantly improve ambulatory medication safety.


BACKGROUND
ClinicalTrials.gov, Taconic Health Information Network and Community (THINC), NCT00225563, http://clinicaltrials.gov/ct2/show/NCT00225563?term=Kaushal&rank=6 .
Kaushal
Rainu
R
Department of Pediatrics, Weill Medical College of Cornell University, 402 East 67th Street, Room-LA-259, New York, NY 10065, USA. rak2007@med.cornell.edu
Kern
Lisa M
LM
Barrón
Yolanda
Y
Quaresimo
Jill
J
Abramson
Erika L
EL
D000328:Adult; D000368:Aged; D003153:Community Health Services; D011307:Drug Prescriptions; D055695:Electronic Prescribing / Q000706:statistics & numerical data*; D005260:Female; D006801:Humans; D008297:Male; D008508:Medication Errors / Q000517:prevention & control* / Q000706:statistics & numerical data; D008875:Middle Aged; D009518:New York; D010824:Physicians' Offices; D010818:Practice Patterns, Physicians'; D011446:Prospective Studies; D012424:Rural Population; D012449:Safety; D017751:Safety Management; D013383:Suburban Population