Integrating "best of care" protocols into clinicians' workflow via care provider order entry: impact on quality-of-care indicators for acute myocardial infarction.
other · Level IV
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- Record sourced from PubMed, PMID 16357360.
- Also identified by PMC identifier 1447538.
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Abstract
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. 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. 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. 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. The decision support tool increased optional use of the ACS order set, but room for additional improvement exists.
Medical subject headings
- Guideline Adherence
- Medical Order Entry Systems
- Myocardial Infarction
- Quality Indicators, Health Care
- Therapy, Computer-Assisted