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The Impact of Peer Management on Test-Ordering Behavior

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*
[+] Article and Author Information

From Vanderbilt University School of Medicine, Nashville, Tennessee.


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, eric.neilson@vanderbilt.edu.

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.


Ann Intern Med. 2004;141(3):196-204. doi:10.7326/0003-4819-141-3-200408030-00008
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Figure 2 and Table 1 report the effects of the 2 RUC interventions on test-ordering behavior. The preintervention period had a mean of 3766 component electrolyte, glucose, BUN, or creatinine tests ordered per day. Late in this baseline period, ordering decreased slightly by 1.2 tests per day (P = 0.006). After the first intervention, the expected average number of components of the metabolic panel test ordered per day decreased from 3701 tests to 2781 tests per day, with daily orders decreasing by 7.8 tests per day during this interval. This rate of decrease was significantly greater than that observed in the baseline period (P = 0.02). The second intervention caused a further decrease in the number of ordered electrolyte, glucose, BUN, and creatinine tests almost overnight, with the daily rate dropping by 51% from an expected rate of 2781 tests per day to a mean postintervention rate of 1348 tests per day (P < 0.001). We did not observe any further changes in test-ordering trends. A separate analysis confirmed a similar decrease in the order rates when counting the intended performance date of each occurrence or discontinuation (data not shown).

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Figures

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Figure 1.
Model for test-ordering behavior.

This graph describes the major components of the model used for analyzing test-ordering behavior after 2 Resource Utilization Committee interventions. The dotted lines indicate the times when the 2 interventions were initiated. The slope of lines A, C, and F give the change in number of tests ordered per day in the baseline period, between the interventions, and after the second intervention, respectively. The magnitude of lines B and D corresponds to the expected number of weekday daily orders at the first intervention and just before the second intervention, respectively. Line E is the overnight decrease in expected orders after the second intervention. This model has a hinge point at the first intervention and a discontinuity at the second intervention. The daily hospital census and terms to handle the decrease in orders on weekends before and after the second intervention, respectively, are also included in the model. Random variation in order rates was modeled by a time-series analysis. This model was selected by using standard data-fitting techniques.

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Figure 2.
Effect of the resource utilization committee (RUC) interventions on ordering components of the metabolic panel test.

Scatter plots of numbers of serum metabolic panel tests (sodium, potassium, chloride, bicarbonate, glucose, blood urea nitrogen, and creatinine tests) ordered or discontinued daily before and after each of the 2 RUC interventions. The lines give the expected number of tests on each day. Tests dramatically decreased on weekends, particularly in the preintervention period. The vertical lines connect orders on Fridays to the following Saturdays and on Sundays to the following Mondays. The break in baseline date indicates the days during the pre-2000 conversion of the pathology laboratory system, a period during which data were not readily available.

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Summary for Patients

Altering Test-Ordering Behavior of Hospital Staff

The summary below is from the full report titled “The Impact of Peer Management on Test-Ordering Behavior.” It is in the 3 August 2004 issue of Annals of Internal Medicine (volume 141, pages 196-204). The authors are E.G. Neilson, K.B. Johnson, S.T. Rosenbloom, W.D. Dupont, D. Talbert, D.A. Giuse, A. Kaiser, and R.A. Miller, for the Resource Utilization Committee.

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