Journal Article

Integrating “Best of Care” Protocols into Clinicians' Workflow via Care Provider Order Entry: Impact on Quality-of-Care Indicators for Acute Myocardial Infarction

Asli Ozdas, Theodore Speroff, L. Russell Waitman, Judy Ozbolt, Javed Butler and Randolph A. Miller

in Journal of the American Medical Informatics Association

Published on behalf of American Medical Informatics Association

Volume 13, issue 2, pages 188-196
Published in print March 2006 | ISSN: 1067-5027
Published online March 2006 | e-ISSN: 1527-974X | DOI: https://dx.doi.org/10.1197/jamia.M1656
Integrating “Best of Care” Protocols into Clinicians' Workflow via Care Provider Order Entry: Impact on Quality-of-Care Indicators for Acute Myocardial Infarction

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  • Medical Statistics and Methodology
  • Bioinformatics and Computational Biology
  • Biomathematics and Statistics

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Abstract

Objective: In the context of an inpatient care provider order entry (CPOE) system, to evaluate the impact of a decision support tool on integration of cardiology “best of care” order sets into clinicians' admission workflow, and on quality measures for the management of acute myocardial infarction (AMI) patients.

Design: A before-and-after study of physician orders evaluated (1) per-patient use rates of standardized acute coronary syndrome (ACS) order set and (2) patient-level compliance with two individual recommendations: early aspirin ordering and beta-blocker ordering.

Measurements: The effectiveness of the intervention was evaluated for (1) all patients with ACS (suspected for AMI at the time of admission) (N = 540) and (2) the subset of the ACS patients with confirmed discharge diagnosis of AMI (n = 180) who comprise the recommended target population who should receive aspirin and/or beta-blockers. Compliance rates for use of the ACS order set, aspirin ordering, and beta-blocker ordering were calculated as the percentages of patients who had each action performed within 24 hours of admission.

Results: For all ACS admissions, the decision support tool significantly increased use of the ACS order set (p = 0.009). Use of the ACS order set led, within the first 24 hours of hospitalization, to a significant increase in the number of patients who received aspirin (p = 0.001) and a nonsignificant increase in the number of patients who received beta-blockers (p = 0.07). Results for confirmed AMI cases demonstrated similar increases, but did not reach statistical significance.

Conclusion: The decision support tool increased optional use of the ACS order set, but room for additional improvement exists.

Journal Article.  6575 words.  Illustrated.

Subjects: Medical Statistics and Methodology ; Bioinformatics and Computational Biology ; Biomathematics and Statistics

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