The Impact of Computerized Physician Order Entry on Medication Error Prevention
- David W Bates,
- Jonathan M Teich,
- Joshua Lee,
- Diane Seger,
- Gilad J Kuperman,
- Nell Ma'Luf,
- Deborah Boyle,
- Lucian Leape
- Brigham and Women's Hospital and Harvard Medical School. Partners Information Systems. Harvard School of Public Health, Boston, Massachusetts
- Corresdpondence and reprints: David W. Bates, MD, MSc, Division of General Medicine, Department of Medicine, Brigham and Women's Hospital, 75 Francis Street, Boston, MA 02115. e-mail: 〈 〉
- Received 7 December 1998
- Accepted 26 February 1999
Background Medication errors are common, and while most such errors have little potential for harm they cause substantial extra work in hospitals. A small proportion do have the potential to cause injury, and some cause preventable adverse drug events.
Objective To evaluate the impact of computerized physician order entry (POE) with decision support in reducing the number of medication errors.
Design Prospective time series analysis, with four periods.
Setting and participants All patients admitted to three medical units were studied for seven to ten-week periods in four different years. The baseline period was before implementation of POE, and the remaining three were after. Sophistication of POE increased with each successive period.
Intervention Physician order entry with decision support features such as drug allergy and drug-drug interaction warnings.
Main outcome measure Medication errors, excluding missed dose errors.
Results During the study, the non-missed-dose medication error rate fell 81 percent, from 142 per 1,000 patient-days in the baseline period to 26.6 per 1,000 patient-days in the final period (P < 0.0001). Non-intercepted serious medication errors (those with the potential to cause injury) fell 86 percent from baseline to period 3, the final period (P = 0.0003). Large differences were seen for all main types of medication errors: dose errors, frequency errors, route errors, substitution errors, and allergies. For example, in the baseline period there were ten allergy errors, but only two in the following three periods combined (P < 0.0001).
Conclusions Computerized POE substantially decreased the rate of non-missed-dose medication errors. A major reduction in errors was achieved with the initial version of the system, and further reductions were found with addition of decision support features.
This work was supported in part by the Risk Management Foundation, Boston, Massachusetts.