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Am J Emerg Med. 2014 Sep;32(9):958-61. doi: 10.1016/j.ajem.2014.05.002. Epub 2014 May 12.

Computerized physician order entry and decision support improves ED analgesic ordering for renal colic.

Author information

1
Department of Emergency Medicine, University of Calgary, Calgary, Alberta.
2
Department of Emergency Medicine, University of Calgary, Calgary, Alberta. Electronic address: eddy.lang@albertahealthservices.ca.

Abstract

OBJECTIVES:

Computerized physician order entry (CPOE) offers the potential for safer, faster patient care, as well as greater use of evidence-based therapy via built-in decision support. However, the effectiveness of CPOE in yielding these benefits has shown mixed results in the emergency department (ED) setting. Our objective was to evaluate the impact of CPOE implementation on analgesic prescribing and dosing practices for renal colic presentations.

METHODS:

This retrospective pre/post comparative study was conducted in 3 tertiary hospitals that implemented CPOE in 2010. Two patient groups were compared: prior to (pre-CPOE) and after (post-CPOE) CPOE implementation. Each group consisted of 230 randomly selected, high-acuity patients presenting to the ED with renal colic. The primary outcome was the proportion of patients receiving ketorolac in the ED. Secondary outcomes included choice of analgesic and average morphine dose.

RESULTS:

The proportion of patients receiving ketorolac significantly increased after CPOE implementation (65.6% pre-CPOE vs 76.5% post-CPOE, P = .015), as did the proportion of patients receiving fentanyl (pre, 9.7%; post, 16.7%; P = .047). Differences in morphine use (pre, 66.0%; post, 69.1%) and average morphine dose (pre, 10.09 mg; post, 12.28 mg) did not reach statistical significance.

CONCLUSIONS:

The introduction of CPOE is associated with an increase in ketorolac use for ED renal colic visits. This may reflect the inclusion of ketorolac in the renal colic order set. Computerized physician order entry implementation with condition-specific electronic order sets and decision support may improve evidence-based practice.

PMID:
24997107
DOI:
10.1016/j.ajem.2014.05.002
[Indexed for MEDLINE]
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