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Effect of Electronic Prescribing Strategies on Medication Error and Harm in Hospital: a Systematic Review and Meta-analysis

Abstract

Background

Computerized physician order entry and clinical decision support systems are electronic prescribing strategies that are increasingly used to improve patient safety. Previous reviews show limited effect on patient outcomes. Our objective was to assess the impact of electronic prescribing strategies on medication errors and patient harm in hospitalized patients.

Methods

MEDLINE, EMBASE, CENTRAL, and CINAHL were searched from January 2007 to January 2018. We included prospective studies that compared hospital-based electronic prescribing strategies with control, and reported on medication error or patient harm. Data were abstracted by two reviewers and pooled using random effects model. Study quality was assessed using the Effective Practice and Organisation of Care and evidence quality was assessed using Grading of Recommendations Assessment, Development, and Evaluation.

Results

Thirty-eight studies were included; comprised of 11 randomized control trials and 27 non-randomized interventional studies. Electronic prescribing strategies reduced medication errors (RR 0.24 (95% CI 0.13, 0.46), I2 98%, n = 11) and dosing errors (RR 0.17 (95% CI 0.08, 0.38), I2 96%, n = 9), with both risk ratios significantly affected by advancing year of publication. There was a significant effect of electronic prescribing strategies on adverse drug events (ADEs) (RR 0.52 (95% CI 0.40, 0.68), I2 0%, n = 2), but not on preventable ADEs (RR 0.55 (95% CI 0.30, 1.01), I2 78%, n = 3), hypoglycemia (RR 1.03 (95% CI 0.62-1.70), I2 28%, n = 7), length of stay (MD - 0.18 (95% - 1.42, 1.05), I2 94%, n = 7), or mortality (RR 0.97 (95% CI 0.79, 1.19), I2 74%, n = 9). The quality of evidence was rated very low.

Discussion

Electronic prescribing strategies decrease medication errors and adverse drug events, but had no effect on other patient outcomes. Conservative interpretations of these findings are supported by significant heterogeneity and the preponderance of low-quality studies.

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