Patient safety/original researchComputerized Decision Support for Medication Dosing in Renal Insufficiency: A Randomized, Controlled Trial
Introduction
Emergency physicians prescribe many medications that require dosage adjustment in the presence of renal insufficiency.1 When prescribing these medications, physicians must correctly identify which patients need dosage adjustments. Serum creatinine level is a poor marker of clinically important renal insufficiency.2, 3, 4 Its sensitivity in identifying clinically important renal impairment ranges from 32% to 60%.2, 5, 6 Instead, serum creatinine level should be used in combination with other variables to estimate creatinine clearance level, which can then be used to guide medication dosing. We recently reported the first study to test the use of computer-assisted decision support in an emergency department (ED) and found that decision support significantly reduced prescribing of potentially unsafe medications to older ED patients.7
Computerized decision support systems may also facilitate proper dosing of renally cleared medications. Decision support systems can estimate a patient's creatinine clearance level and make a specific dosing recommendation when a medication is prescribed that requires dosage adjustment. Although previous research supports the use of such dosage adjustment systems, the most rigorous research has been carried out using time-series study designs.8, 9 To our knowledge, there have been no randomized, controlled trials of computerized decision support to more safely determine medication dosage in patients with renal impairment. In addition, this type of computer-assisted decision support has not been tested in an ED setting.
The purpose of this study was to examine, in a randomized, controlled fashion, the extent to which computerized decision support in an ED enhances the safety of prescribing to patients with renal disease. The hypothesis was that decision support for emergency physicians in an established computerized physician order entry system would reduce excessive medication dosing for patients with clinically important renal impairment.
Section snippets
Study Design
This was a randomized controlled trial and was approved by the Indiana University institutional review board before implementation of the intervention.
Setting
The Wishard Memorial Hospital is a 450-bed, urban, public hospital on the Indiana University Medical Center campus. The Wishard Emergency Department is a Level I trauma center and has approximately 100,000 annual visits. During routine patient care, clinicians electronically write all discharge orders, including prescriptions, using a
Characteristics of Study Subjects
Figure 3 shows the flow of physicians and patients through the study. Pertinent characteristics of the 42 physicians and the 2,783 patient visits in which there was sufficient information to estimate creatinine clearance level are provided in Table 1. There were no important differences in the characteristics of intervention and control physicians or the 2 groups of patients who received their care. The average age of patients was 46 years; 1,768 (64%) were women, and 1,523 (55%) were black.
Main Results
Limitations
There are several potential limitations of the current study. First, this study was carried out in a single site and included a small sample of residents and academic emergency physicians who provide care within an established health information technology infrastructure.11 Our findings may not be generalizable to other providers or to other settings. However, a survey carried out more than 7 years ago found that 35% of academic EDs use computerized prescribing systems,13 and we expect the
Discussion
Computer-assisted decision support resulted in a statistically significant reduction in excessive dosing of renally cleared medications in the ED. To our knowledge, this is the first randomized, controlled trial of computer-assisted decision support to reduce excessive prescribing to patients with clinically significant renal disease. There have been 3 nonrandomized studies of computerized decision support to facilitate proper medication dosing for patients with renal insufficiency or failure.8
References (15)
- et al.
Discordance between serum creatinine and creatinine clearance for identification of ED patients with abdominal pain at risk for contrast-induced nephropathy
Am J Emerg Med
(2007) - et al.
The Regenstrief Medical Record System: a quarter century experience
Int J Med Inform
(1999) - et al.
A trial of automated decision support alerts for contraindicated medications using computerized physician order entry
J Am Med Inform Assoc
(2005) Micromedex Healthcare Series USP DI
(2004)- et al.
Magnitude of underascertainment of impaired kidney function in older adults with normal serum creatinine
J Am Geriatr Soc
(2007) Clinical practice guidelines for chronic kidney disease: evaluation, classification, and stratificationPart 5. Evaluation of laboratory measurements for clinical assessment of kidney disease. Guideline 4. Estimation of GFR
Am J Kidney Dis
(2002)- et al.
Assessing kidney function—measured and estimated glomerular filtration rate
N Engl J Med
(2006)
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Author contributions: All authors participated in conception of the study and designing the trial. KMT, AJP, SLH, and CMC obtained research funding. KMT, AJP, CMC, PRD, and DKM supervised the conduct of the trial and data collection. AJP and SLH managed the data and analyzed the data. KMT drafted the manuscript, and all authors contributed substantially to its revision. KMT takes responsibility for the paper as a whole.
Funding and support: By Annals policy, all authors are required to disclose any and all commercial, financial, and other relationships in any way related to the subject of this article that might create any potential conflict of interest. See the Manuscript Submission Agreement in this issue for examples of specific conflicts covered by this statement. This research was supported by Dr. Terrell's Dennis W. Jahnigen Career Development Award, which is funded by the American Geriatrics Society, the John A. Hartford Foundation, and Atlantic Philanthropies Inc.
Supervising editor: Steven M. Green, MD
Publication dates: Available online May 8, 2010.
Reprints not available from authors.
Please see page 624 for the Editor's Capsule Summary of this article.