Just what the doctor ordered. Review of the evidence of the impact of computerized physician order entry system on medication errors

Tatyana A. Shamliyan, Sue Duval, Jing Du, Robert L Kane

Research output: Contribution to journalArticlepeer-review

143 Scopus citations


Objective. To examine the association between computerization of physician orders and prescribing medication errors. Data Sources. Studies published in English language were identified through MEDLINE (1990 through December 2005), Cochrane Central Register of Controlled Trials, and bibliographies of retrieved articles. Of 252 identified in the search, 12 (4.8 percent) original investigations that compared rates of prescribing medication errors with handwritten and computerized physician orders were included. Data Collection. Information on study design, participant characteristics, clinical settings, and outcomes rates were abstracted independently by two investigators using a standardized protocol. Principal Findings. Compared with handwritten orders, 80 percent of studies (8/10 studies) reported a significant reduction in total prescribing errors, 43 percent in dosing errors (3/7 studies), and 37.5 percent in adverse drug events (3/8 studies). The use of computerized orders was associated with a 66 percent reduction in total prescribing errors in adults (odds ratio [OR]=0.34; 95 percent confidence interval [CI] 0.22-0.52) and a positive tendency in children (p for interaction=.028). The benefit of computerized orders was larger when the rate of errors was more than 12 percent with handwritten orders (p for interaction=.022). Significant heterogeneity in the results compromised pooled relative risks. One randomized controlled intervention demonstrated the greatest benefits of computerized orders on total prescribing errors (OR=0.02, 95 percent CI 0.01-0.02) and dosing errors (OR=0.28; 95 percent CI 0.15-0.52) with 775 avoided prescribing errors (95 percent CI 752-811) per 1,000 orders in a pediatric hospital. Conclusions. Computerization of physicians' orders shows great promise. It will be more effective when linked to other computerized systems to detect and prevent prescribing errors.

Original languageEnglish (US)
Pages (from-to)32-53
Number of pages22
JournalHealth services research
Issue number1 P1
StatePublished - Feb 2008


  • Epidemiologic studies
  • Medical order entry systems
  • Medication errors


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