Eric G. Neilson, MD; Kevin B. Johnson, MD; S. Trent Rosenbloom, MD, MPH; William D. Dupont, PhD; Doug Talbert, PhD; Dario A. Giuse, Dr Ing; Allen Kaiser, MD; Randolph A. Miller, MD; the Resource Utilization Committee*
Acknowledgments: The authors thank Dale Plummer Jr. for his extensive help with the statistical analyses.
Grant Support: By the Vanderbilt-Ingram Cancer Center biostatistics core through the National Cancer Institute Cancer Center (grants P30 CA-68485 and CA-50468) (Dr. Dupont) and by the National Library of Medicine (LM-06226) (Dr. Miller).
Potential Financial Conflicts of Interest:Consultancies: S.T. Rosenbloom (McKesson); Honoraria: R.A. Miller (Vanderbilt University); Royalties: D. Talbert (Vanderbilt University), D.A. Giuse (Vanderbilt University), R.A. Miller (Vanderbilt University).
Requests for Single Reprints: Eric G. Neilson, MD, Department of Medicine, Vanderbilt University School of Medicine, D-3100 Medical Center North, 21st Avenue South and Garland Avenue, Nashville, TN 37232; e-mail, email@example.com.
Current Author Addresses: Drs. Neilson and Kaiser: Department of Medicine, Vanderbilt University School of Medicine, D-3100 Medical Center North, 21st Avenue South and Garland Avenue, Nashville, TN 37232-2358.
Drs. Miller and Giuse: Department of Biomedical Informatics, Vanderbilt University School of Medicine, 2209 Garland Avenue, Lower Level Eskind Biomedical Library, Nashville, TN 37232-8340.
Dr. Dupont: Department of Biostatistics, Vanderbilt University School of Medicine, 21st Avenue South and Garland Avenue, S-2323 Medical Center North, Nashville, TN 37232-2158.
Drs. Johnson and Rosenbloom: Departments of Biomedical Informatics and Pediatrics, Vanderbilt University School of Medicine, 2209 Garland Avenue, 402 Eskind Biomedical Library, Nashville, TN 37232-8340.
Dr. Talbert: Department of Computer Science, Software Automation and Intelligence Lab, Tennessee Technological University, PO Box 5101, Cookeville, TN 38505.
Author Contributions: Conception and design: E.G. Neilson, S.T. Rosenbloom, R.A. Miller.
Analysis and interpretation of the data: E.G. Neilson, K.B. Johnson, S.T. Rosenbloom, W.D. Dupont, A. Kaiser, R.A. Miller.
Drafting of the article: E.G. Neilson, K.B. Johnson, S.T. Rosenbloom, W.D. Dupont, R.A. Miller.
Critical revision of the article for important intellectual content: E.G. Neilson, K.B. Johnson, W.D. Dupont, D.A. Giuse, A. Kaiser, R.A. Miller.
Final approval of the article: E.G. Neilson, K.B. Johnson, S.T. Rosenbloom, W.D. Dupont, D. Talbert, D.A. Giuse, A. Kaiser, R.A. Miller.
Provision of study materials or patients: D.A. Giuse.
Statistical expertise: K.B. Johnson, S.T. Rosenbloom, W.D. Dupont.
Administrative, technical, or logistic support: D. Talbert.
Collection and assembly of data: E.G. Neilson, S.T. Rosenbloom, D. Talbert, D.A. Giuse, A. Kaiser, R.A. Miller.
Neilson EG, Johnson KB, Rosenbloom ST, Dupont WD, Talbert D, Giuse DA, et al. The Impact of Peer Management on Test-Ordering Behavior. Ann Intern Med. 2004;141:196-204. doi: 10.7326/0003-4819-141-3-200408030-00008
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Published: Ann Intern Med. 2004;141(3):196-204.
Can simple electronic aids help physicians reduce unnecessary, costly test ordering?
In this interrupted time-series study from a large academic hospital, a committee of peer leaders selected ways to use their care provider order entry (CPOE) system to reduce unnecessary test ordering. Computer prompts questioning repetitive orders for routine tests and unbundling of tests within metabolic panel tests both reduced test orders. Patient readmission rates, length of stay, transfer to intensive care units, and mortality rates remained stable.
Peer-designed interventions using CPOE systems can improve provider test-ordering behavior.
Providers of clinical care order excessive tests for hospitalized patients for defensive reasons (1) or ease of access (2) or because they cannot manage the fear of uncertainty (3, 4). Excessive ordering increases the use of technology and adds unnecessary costs to the delivery of health care. Motivated by studies demonstrating substantial variation in testing behaviors among providers (2, 5-14), inappropriate or unnecessary testing (15-23), and test addiction (24-26), investigators over the past decade have tried to impose sustainable limits on diagnostic evaluations. However, many recommended approaches are too time-consuming (27), difficult to scale across an institution (28), counterproductive to training (29), detrimental to clinical decision making (26), or inappropriately intrusive (26). One study suggested that short-term reductions in the amount of testing were not sustainable (30). In a review of various approaches to limit testing, Solomon and colleagues (24) noted that multifaceted interventions are most likely to succeed.
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Print ISSN: 0003-4819 | Online ISSN: 1539-3704
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