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A Multidisciplinary Housestaff-Led Initiative to Safely Reduce Daily Laboratory Testing

Iams, Wade, MD; Heck, Josh, MD; Kapp, Meghan, MD; Leverenz, David, MD; Vella, Michael, MD, MBA; Szentirmai, Eszter; Valerio-Navarrete, Irene, MS; Theobald, Cecelia, MD, MPH; Goggins, Kathryn, MPH; Flemmons, Kevin, MD; Sponsler, Kelly, MD; Penrod, Cody, MD; Kleinholz, Patricia, MD; Brady, Donald, MD; Kripalani, Sunil, MD, MSc

doi: 10.1097/ACM.0000000000001149
Research Reports

Purpose Provision of high-value care is a milestone in physician training. The authors evaluated the effect of a housestaff-led initiative on laboratory testing rates.

Method Vanderbilt University Medical Center’s Choosing Wisely steering committee, led by housestaff with faculty advisors, sought to reduce unnecessary daily basic metabolic panel (BMP) and complete blood count (CBC) testing on inpatient general medicine and surgical services. Intervention services received a didactic session followed by regular data feedback with goal rates and peer comparison. Testing rates during January 1, 2013–February 9, 2015, were compared on intervention services and control services using a difference-in-differences analysis and an interrupted time-series analysis with segmented linear regression.

Results Compared with concurrent controls, the mean number of BMP tests per patient day decreased by an additional 0.23 (95% CI 0.17–0.29) on medical housestaff and 0.15 (95% CI 0.09–0.21) on hospitalist intervention services. Daily CBC tests decreased by an additional 0.28 (95% CI 0.23–0.33) on medical housestaff, 0.08 (95% CI 0.03–0.13) on hospitalist, and 0.12 (95% CI 0.05–0.20) on surgical housestaff intervention services. Patients with lab-free days (0 labs ordered in 24 hours) increased by an additional 4.1 percentage points (95% CI 2.1–6.1) on medical housestaff and 9.7 percentage points (95% CI 6.6–12.8) on hospitalist intervention services. There were no adverse changes in length of stay or intensive care unit transfer, in-hospital mortality, or 30-day readmission rates.

Conclusions A housestaff-led intervention utilizing education and data feedback with goal setting and peer comparison resulted in safe, significant reductions in daily laboratory testing rates.

W. Iams is chief resident in internal medicine, Department of Internal Medicine, Vanderbilt University Medical Center, Nashville, Tennessee.

J. Heck was chief resident in radiology and musculoskeletal radiology fellow, Department of Radiology, Vanderbilt University Medical Center, Nashville, Tennessee, at the time of implementation and writing.

M. Kapp is chief resident in pathology, Department of Pathology, Vanderbilt University Medical Center, Nashville, Tennessee.

D. Leverenz is a third-year internal medicine resident, Department of Internal Medicine, Vanderbilt University Medical Center, Nashville, Tennessee.

M. Vella is a fourth-year general surgery resident, Department of Surgery, Vanderbilt University Medical Center, Nashville, Tennessee.

E. Szentirmai is a fourth-year medical student, School of Medicine, Vanderbilt University Medical Center, Nashville, Tennessee.

I. Valerio-Navarrete is data analyst, Department of Informatics, Vanderbilt University Medical Center, Nashville, Tennessee.

C. Theobald is assistant professor of medicine, Department of Internal Medicine, Vanderbilt University Medical Center, Nashville, Tennessee.

K. Goggins is research coordinator, Department of Internal Medicine and Center for Clinical Quality and Implementation Research, Vanderbilt University Medical Center, Nashville, Tennessee.

K. Flemmons is assistant professor of medicine, Department of Internal Medicine, Vanderbilt University Medical Center, Nashville, Tennessee.

K. Sponsler is assistant professor of medicine, Department of Internal Medicine, Vanderbilt University Medical Center, Nashville, Tennessee.

C. Penrod is a pediatric emergency medicine fellow, Department of Pediatrics, Vanderbilt University Medical Center, Nashville, Tennessee.

P. Kleinholz is chief resident in neurology, Department of Neurology, Vanderbilt University Medical Center, Nashville, Tennessee.

D. Brady is professor of medicine and designated institutional official, Office of Graduate Medical Education, Vanderbilt University Medical Center, Nashville, Tennessee.

S. Kripalani is associate professor of medicine, Department of Internal Medicine, and director, Center for Clinical Quality and Implementation Research, Vanderbilt University Medical Center, Nashville, Tennessee.

Funding/Support: The evaluation was supported by the Vanderbilt Center for Clinical Quality and Implementation Research.

Other disclosures: None reported.

Ethical approval: This study was approved by the Vanderbilt University institutional review board as a quality improvement study.

Disclaimers: The authors received approval from the ABIM Foundation and the national Choosing Wisely initiative to use their logo with the intervention materials.

Previous presentations: This work has been orally presented at the Association of American Medical Colleges 2014 Integrating Quality Meeting, June 11–13, 2014, Rosemont, Illinois; the Accreditation Council for Graduate Medical Education Annual Meeting, February 26–March 1, 2015, San Diego, California; the Society of Hospital Medicine Annual Meeting, March 29–April 1, 2015, National Harbor, Maryland; and the Association for Program Directors in Internal Medicine Annual Meeting, April 26–29, 2015, Houston, Texas.

Supplemental digital content for this article is available at and

Correspondence should be addressed to Sunil Kripalani, Vanderbilt Center for Clinical Quality and Implementation Research, 2525 West End Ave., Suite 1200, Nashville, TN 37203; telephone: (615) 936-4875; e-mail:

Low-value care is a pervasive problem in the U.S. medical system, with an estimated $750 billion per year spent on care that does not change health outcomes.1 The problem of low-value care provision is most acute among physicians immediately after they complete training, as studies have shown that more experienced physicians practice at lower cost than recent residency graduates.2

Several national organizations therefore have targeted residency training as an opportunity to educate physicians about cost-effective, high-value care to combat rising health care costs. The American Board of Internal Medicine (ABIM) Foundation and the American College of Physicians have acknowledged that the stewardship of finite health care resources is an ethical responsibility of physicians,1 , 3 , 4 and they have launched the Choosing Wisely campaign5 and a high-value care curriculum,6 respectively, to encourage cost-effective care implementation. The Accreditation Council for Graduate Medical Education (ACGME) and the ABIM have specified in their milestones for residency education that an internal medicine physician “identifies forces that impact the cost of health care, and advocates for, and practices cost-effective care.”7

As part of the Choosing Wisely campaign, the Society of Hospital Medicine and the Critical Care Societies Collaborative have cited daily basic metabolic panel (BMP) and complete blood count (CBC) testing in the absence of clinical changes in their lists of the top five common, unnecessary practices that should be questioned.8 , 9 Concerns over unnecessary daily laboratory testing arise from observations that such testing can lead to erroneous results and further unnecessary testing, that early-morning awakening for blood draws is a major disturbance for patients’ sleep quality, and that patients can develop hospital-acquired anemia due to an activity often perceived by providers as benign.10–12 Many educational and infrastructure-based strategies have been proposed and used to reduce unnecessary BMP and CBC testing, and in general these interventions have safely reduced laboratory testing by 5% to 40%.13–25 However, their effects have often been transient.26

In this report, we describe a housestaff-led, multifaceted intervention using education and data feedback with goal setting and peer comparison to reduce unnecessary daily BMP and CBC testing on inpatient general medicine and surgical services at Vanderbilt University Medical Center (VUMC). We anticipated that housestaff leadership of these efforts would provide a unique mechanism to encourage change among ordering clinicians.

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In December 2013, at the prompting of our designated institutional official (D.B.) and with the support of our residency program directors, a Choosing Wisely steering committee was formed at VUMC. The committee was formed with the objective of integrating housestaff into the institutional leadership’s pursuit of high-value care principles across the academic medical center. The committee is led by housestaff and is composed of 15 individuals (two-thirds housestaff and one-third faculty) from the departments of internal medicine, radiology, surgery, pathology, pediatrics, neurology, graduate medical education, and the medical school. The group reviewed Choosing Wisely recommendations from national societies and chose reduction in daily laboratory testing among stable medical and surgical inpatients as the initial initiative, given its broad applicability.

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The medical services targeted by the intervention were all general medicine housestaff services and hospitalist services. The intervention surgical housestaff services included trauma surgery, gastrointestinal and laparoscopic surgery, surgical oncology, and endocrine surgery.

Our intervention to reduce unnecessary daily laboratory testing began with a 20-minute oral presentation at each target department’s best-attended didactic session. This one-time, housestaff-led session was provided to all housestaff and hospitalists in the target service lines, including individuals who subsequently rotated on control services. The presentation highlighted high-value care principles and the Choosing Wisely campaign generally as well as the historical background and baseline test ordering habits for our initiative specifically. Knowledge acquisition following this didactic session was not directly assessed; changes in test ordering were used as a surrogate for this educational goal. The didactic session occurred in April 2014 for the general medicine housestaff services, July 2014 for the hospitalist services, and August 2014 for the selected surgical housestaff services.

Immediately following this didactic session, laminated pocket-sized cards containing the charges for a BMP and CBC and an educational flyer highlighting the Choosing Wisely recommendations supporting the initiative were disseminated throughout all intervention service work areas. We confirmed the ABIM Foundation’s agreement with our flyer material prior to dissemination. (The flyer is available as Supplemental Digital Appendix 1 at

After the project launch, housestaff and faculty on intervention services received weekly data feedback e-mails comparing their daily BMP and CBC ordering rates with the ordering rates of peer services and the goal ordering rates. We set as the goal an absolute reduction in daily BMP and CBC ordering rates of 20% on the general medicine and surgical housestaff services and 10% on the hospitalist services, based on their baseline testing rates and prior literature showing that this degree of reduction in lab ordering at VUMC had been safe.19 A smaller change was targeted for the hospitalist services because their baseline test ordering rates were lower.

On the general medicine housestaff services, new housestaff and faculty members rotating on service were sent an onboarding e-mail with baseline laboratory ordering rates, information about the Choosing Wisely campaign, and the ACGME/ABIM milestones regarding high-value care and responding to practice-based data feedback. On these services, a summary monthly e-mail containing photos of the residents and faculty member with the lowest daily laboratory ordering rate over the preceding month was also sent. There were no additional incentives for reducing laboratory testing rates. We did not assess the rates of e-mail opening or pursue systematic assessments of change in resident attitudes. Faculty were encouraged but not mandated to discuss laboratory ordering rates with their housestaff teams, and laboratory test orders were placed by housestaff. The hospitalist and surgical services did not receive monthly onboarding or summary e-mails.

The e-mails with weekly data feedback (all intervention services) and monthly onboarding information and summaries (general medicine housestaff services only) continued throughout the evaluation period.

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Control groups

For each intervention service, we identified a comparable control service with a similar patient population and provider training level. The gastroenterology and cardiology housestaff services served as controls for the general medicine housestaff services. The emergency general surgery and vascular surgery housestaff services served as controls for the intervention surgical housestaff services. The geriatrics service (with geriatrics physicians and nurse practitioners) served as a control for the hospitalist services because it was the most similar faculty service without housestaff and had similar baseline testing rates.

Housestaff crossed between intervention and control services throughout the intervention period according to their rotation schedules. In general, faculty did not cross over, with the exception of one hospitalist who staffed the geriatrics service every other week for the majority of the intervention period. The control services did not receive weekly data feedback, and they had separate work areas.

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Outcomes and data collection

The Vanderbilt University institutional review board reviewed and approved evaluation of this intervention as a quality improvement study without the requirement of informed consent from participants.

For this analysis, laboratory testing data were collected retrospectively for the period January 1, 2013, through February 9, 2015, for all medical and surgical services that received the intervention and their control services. All comparisons between intervention and control services were for concurrent time periods. The primary outcomes were the daily rates of BMP and CBC ordering, defined as the number of each test ordered per patient per 24-hour period. We also determined the percentage of patients who had a lab-free day, defined as 24 hours without blood tests of any type. Secondary outcomes included hospital length of stay, escalations of care (i.e., transfer to the intensive care unit [ICU]), in-hospital mortality, and 30-day readmissions to the same facility. Data were extracted on February 23, 2015, from the VUMC’s Enterprise Data Warehouse, which includes computerized order entry, clinical documentation, and administrative data.

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Statistical analysis

The transition between the baseline and intervention periods was defined as the date of the didactic session provided to each target service line. We used the Student t test to compare the change in daily laboratory testing rates between the baseline and intervention periods within each medical or surgical service. We also used a difference-in-differences approach to compare changes in testing rates and secondary outcomes on intervention services versus control services using a t test.

To account for temporal trends in laboratory ordering, we further examined rates of BMP and CBC testing and lab-free days using an interrupted time-series analysis with segmented linear regression.27 The study period was divided into two-week intervals. Least-squares linear regression models were fit to the baseline period and projected into the intervention period assuming no change. Separate models were then fit to the intervention period and compared with the baseline models using covariance analysis. All statistical testing was two sided at an alpha level of .05. All analyses were conducted using Stata 12.1 (StataCorp, College Station, Texas).

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Baseline period data were available for 30,799 patient days on the medical housestaff services, 31,849 patient days on the hospitalist and geriatrics services, and 53,694 patient days on the surgical housestaff services. Intervention period data were available for 19,401, 13,241, and 15,516 patient days, respectively.

Unadjusted rates of BMP testing, CBC testing, and lab-free days during the baseline and intervention periods for intervention and control services are shown in Table 1. During the baseline period, the housestaff services averaged 0.98 to 1.09 BMPs and 0.77 to 0.97 CBCs per patient day. The hospitalist and geriatrics services averaged 0.65 to 0.69 BMPs and 0.51 to 0.58 CBCs per patient day.

Table 1

Table 1

Comparing the baseline and intervention periods, BMP and CBC testing rates declined significantly within each medical and surgical service studied (Table 1). The amount of improvement was greater on intervention services compared with their respective controls. For example, among the medical housestaff, intervention services experienced an absolute reduction of 0.30 BMPs and 0.38 CBCs per patient day, compared with reductions of 0.04 and 0.17, respectively, on control services. The difference-in-differences analysis showed a statistically significant additional reduction of 0.23 (95% CI 0.17–0.29) in BMPs and 0.28 (95% CI 0.23–0.33) in CBCs on the intervention medical housestaff services compared with control services. On the hospitalist services, the mean number of BMPs per patient day was reduced by an additional 0.15 (95% CI 0.09–0.21), and the mean number of CBCs was reduced by an additional 0.08 (95% CI 0.03–0.13) compared with the geriatrics (control) service. The percentage of patients with lab-free days increased by an additional 4.1 percentage points (95% CI 2.1–6.1) on the intervention medical housestaff services and 9.7 percentage points (95% CI 6.6–12.8) on the hospitalist services compared with their controls. Effects on the surgical housestaff services were less consistent: A significant intervention effect was evident only on the rate of CBC testing (mean difference = 0.12; 95% CI 0.05–0.20).

We further examined the effects of the intervention through interrupted time-series analysis and segmented linear regression. For the intervention and control medical services, during the baseline period, BMP and CBC testing rates were generally flat, except for slight trends upward in BMP ordering on the geriatrics (control) service and in CBC ordering on the hospitalist (intervention) services (Figures 1 and 2, panels A–D). On the intervention medical services, the trajectory of BMP and CBC testing improved markedly during the intervention period (Figures 1 and 2, panels A and C). Regression analysis confirmed that these changes in slope were statistically significant (Table 2). On the control medical services, testing rates also improved (Figures 1 and 2, panels B and D), but the improvement was less pronounced than on the intervention medical services.

Table 2

Table 2

Figure 1

Figure 1

Figure 2

Figure 2

On the surgical services, during the baseline period, daily testing rates were already declining (Figures 1 and 2, panels E and F). After initiation of the intervention, trends for ordering BMP and CBC tests did not change significantly and consistently (Table 2).

The initiative had comparable effects on trends in lab-free days. Among the medical services, the percentage of patients with lab-free days increased markedly and significantly on intervention services (Figure 3, panels A and C); on control services, there was no statistically significant increase (Table 2). All surgical services were experiencing a baseline trend toward more lab-free days; this continued to a similar degree in the intervention period, without significant differences between intervention and control services (Figure 3, panels E and F).

Figure 3

Figure 3

Comparison of several balancing measures during the baseline and intervention periods revealed no adverse changes in hospital length of stay, ICU transfer rate, in-hospital mortality rate, or 30-day readmission rate (see Supplemental Digital Appendix 2 at

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We have demonstrated that an intervention utilizing a multifaceted approach of education and data feedback with goal setting and peer comparison can create safe, significant reductions in rates of daily laboratory testing and increases in the percentage of patients with lab-free days at an academic medical center. Our novel housestaff-driven model, with faculty oversight through formation of a multidisciplinary Choosing Wisely steering committee, sets our initiative apart from prior efforts to reduce unnecessary laboratory testing and serves as an example that can be adapted at other institutions to implement site-specific high-value care initiatives.

Our feedback methods and competition among peers lowered laboratory testing rates significantly, as evidenced by the larger gains on intervention services compared with concurrent controls. On a larger scale, this initiative has resulted in an increase in institutional awareness of high-value care principles in general and the Choosing Wisely campaign specifically.

Furthermore, the substantial increase in the percentage of patients with lab-free days seen with this initiative has resulted in significant labor savings at VUMC. An internal systems engineering analysis revealed that when nursing staff perform phlebotomy, the median duration from undertaking the task until completion is 20 minutes. Therefore, across just the intervention medical housestaff services, for example, the increase in lab-free days saves more than five hours of nursing staff time per week.

Improving the cost-conscious behavior of faculty, resident physicians, nurse practitioners, and physician assistants has been attempted in many ways over the past 30 years. Since the early 1980s these efforts have included displaying charges at the time of test ordering,15 , 28 offering financial incentives within training departments,23 , 29 eliminating the potential to order recurring labs,19 , 21 and giving individualized feedback between housestaff and faculty regarding the utility of specific tests.23 , 26 The majority of these initiatives have been effective initially, but with time most lose their effect.30 We are currently working to ingrain our data feedback mechanism within our institutional quality improvement infrastructure and thereby expand our work without cessation of data feedback to the intervention services.

In addition to decreasing unnecessary laboratory testing, our initiative also aimed to raise awareness and provide a mechanism to learn about high-value care. Despite the multitude of advocates, a 2012 survey of internal medicine program directors showed that only 15% of responding programs had a formal curriculum in cost-conscious care.24 Institutions that do not yet have a high-value care curriculum can explore our example as well as other examples from the Teaching Value and Choosing Wisely Challenge,25 such as using case vignettes or increasing cost transparency, to select a program that fits their organization, faculty, and trainees best.

It is noteworthy that our initiative, which began with the general medicine housestaff services, has expanded across surgery and neurology departments at VUMC and from housestaff to faculty hospitalist services. We believe the factors promoting the success of this initiative include the establishment of a multidisciplinary steering committee that integrates housestaff with faculty and institutional leaders; real-time data feedback to encourage high users to change their behavior; goal setting with peer comparison data; and motivated housestaff champions from multiple departments, including surgery, pathology, and radiology. The mechanisms through which we are currently pursuing sustainability include the aforementioned integration with VUMC’s quality improvement infrastructure and quarterly reporting to our Diagnostic Laboratory Advisory Committee. Our expansion targets include reducing excessive telemetry, emergency department brain computed tomography, and ICU chest radiograph utilization. We feel that our methodology of combined didactics, educational materials, and data feedback is amenable to any trackable utilization metric and to most high-value care initiatives.

One of the potential limitations of performing this type of study is the need to account for existing temporal trends, particularly as they relate to physician behavior and practices. The use of an interrupted time-series analysis strengthens our quasi-experimental design by facilitating calculation of the effect of the intervention above and beyond any preexisting longitudinal trends. Another limitation of this study is its single-institution setting, which limits generalizability because the results may be dependent on local culture and physician ordering practices specific to the institution. Although a reduction in testing rates has been sustained into 2015, long-term sustainability remains to be determined, and no washout period has been implemented, nor is one planned. As noted previously, all-too-often high-value care interventions are effective only in the short term. Furthermore, the reductions in test ordering rates on the control services are unlikely to be solely attributable to our initiative because improving the cost-effectiveness of clinician test ordering has been broadly targeted by VUMC leadership and featured in national discussions of high-value care principles. It is possible that general reductions in test ordering would have occurred at our institution independent of our initiative, and we did not assess control participants for the main drivers of their ordering change. This possibility is most likely on the surgical services, as it appears that departmental leadership’s emphasis on improving daily laboratory ordering rates preceded our initiative and may have acted as the predominant force contributing to decreases in laboratory ordering rates on those services. Finally, we did not perform any adjustment for severity of illness or other patient-level factors, although it is assumed that these are relatively stable among the hospital population over this time period.

In sum, we have shown that a multifaceted intervention led by housestaff can generate significant, safe reductions in unnecessary daily laboratory testing and increases in lab-free days. Our overall model demonstrates not only a means to effect immediate practice improvement but also a way to train future leaders in health care system change implementation.

Acknowledgments: The authors appreciate the support of Sandi Holtzclaw, without whom this work would not be possible.

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1. Moriates C, Mourad M, Novelero M, Wachter RM. Development of a hospital-based program focused on improving healthcare value. J Hosp Med. 2014;9:671–677.
2. Mehrotra A, Reid RO, Adams JL, Friedberg MW, McGlynn EA, Hussey PS. Physicians with the least experience have higher cost profiles than do physicians with the most experience. Health Aff (Millwood). 2012;31:2453–2463.
3. Snyder L; American College of Physicians Ethics, Professionalism, and Human Rights Committee. American College of Physicians Ethics Manual: Sixth edition. Ann Intern Med. 2012;156(1 pt 2):73–104.
4. ABIM Foundation, ACP-ASIM Foundation, European Federation of Internal Medicine. Medical professionalism in the new millennium: A physician charter. Ann Intern Med. 2002;136:243–246.
5. Cassel CK, Guest JA. Choosing wisely: Helping physicians and patients make smart decisions about their care. JAMA. 2012;307:1801–1802.
6. Owens DK, Qaseem A, Chou R, Shekelle P; Clinical Guidelines Committee of the American College of Physicians. High-value, cost-conscious health care: Concepts for clinicians to evaluate the benefits, harms, and costs of medical interventions. Ann Intern Med. 2011;154:174–180.
7. Iobst W, Aagaard E, Bazari H, et al. The Internal Medicine Milestone Project: A joint initiative of the Accreditation Council for Graduate Medical Education and the American Board of Internal Medicine. 2015. Accessed January 18, 2016.
8. Bulger J, Nickel W, Messler J, et al. Choosing wisely in adult hospital medicine: Five opportunities for improved healthcare value. J Hosp Med. 2013;8:486–492.
9. Halpern SD, Becker D, Curtis JR, et al; Choosing Wisely Taskforce; American Thoracic Society; American Association of Critical-Care Nurses; Society of Critical Care Medicine. An official American Thoracic Society/American Association of Critical-Care Nurses/American College of Chest Physicians/Society of Critical Care Medicine policy statement: The Choosing Wisely® top 5 list in critical care medicine. Am J Respir Crit Care Med. 2014;190:818–826.
10. Salisbury AC, Reid KJ, Alexander KP, et al. Diagnostic blood loss from phlebotomy and hospital-acquired anemia during acute myocardial infarction. Arch Intern Med. 2011;171:1646–1653.
11. Lyon AW, Chin AC, Slotsve GA, Lyon ME. Simulation of repetitive diagnostic blood loss and onset of iatrogenic anemia in critical care patients with a mathematical model. Comput Biol Med. 2013;43:84–90.
12. Thavendiranathan P, Bagai A, Ebidia A, Detsky AS, Choudhry NK. Do blood tests cause anemia in hospitalized patients? The effect of diagnostic phlebotomy on hemoglobin and hematocrit levels. J Gen Intern Med. 2005;20:520–524.
13. Bates DW, Kuperman GJ, Jha A, et al. Does the computerized display of charges affect inpatient ancillary test utilization? Arch Intern Med. 1997;157:2501–2508.
14. Seguin P, Bleichner JP, Grolier J, Guillou YM, Mallédant Y. Effects of price information on test ordering in an intensive care unit. Intensive Care Med. 2002;28:332–335.
15. Feldman LS, Shihab HM, Thiemann D, et al. Impact of providing fee data on laboratory test ordering: A controlled clinical trial. JAMA Intern Med. 2013;173:903–908.
16. Stuebing EA, Miner TJ. Surgical vampires and rising health care expenditure: Reducing the cost of daily phlebotomy. Arch Surg. 2011;146:524–527.
17. Wang TJ, Mort EA, Nordberg P, et al. A utilization management intervention to reduce unnecessary testing in the coronary care unit. Arch Intern Med. 2002;162:1885–1890.
18. May TA, Clancy M, Critchfield J, et al. Reducing unnecessary inpatient laboratory testing in a teaching hospital. Am J Clin Pathol. 2006;126:200–206.
19. Neilson EG, Johnson KB, Rosenbloom ST, et al; Resource Utilization Committee. The impact of peer management on test-ordering behavior. Ann Intern Med. 2004;141:196–204.
20. Calderon-Margalit R, Mor-Yosef S, Mayer M, Adler B, Shapira SC. An administrative intervention to improve the utilization of laboratory tests within a university hospital. Int J Qual Health Care. 2005;17:243–248.
21. Sussman E, Goodwin P, Rosen H. Administrative change and diagnostic test use. The effect of eliminating standing orders. Med Care. 1984;22:569–572.
22. Roberts DE, Bell DD, Ostryzniuk T, et al. Eliminating needless testing in intensive care—an information-based team management approach. Crit Care Med. 1993;21:1452–1458.
23. Martin AR, Wolf MA, Thibodeau LA, Dzau V, Braunwald E. A trial of two strategies to modify the test-ordering behavior of medical residents. N Engl J Med. 1980;303:1330–1336.
24. Patel MS, Reed DA, Loertscher L, McDonald FS, Arora VM. Teaching residents to provide cost-conscious care: A national survey of residency program directors. JAMA Intern Med. 2014;174:470–472.
25. Shah N, Levy AE, Moriates C, Arora VM. Wisdom of the crowd: Bright ideas and innovations from the teaching value and choosing wisely challenge. Acad Med. 2015;90:624–628.
26. Axt-Adam P, van der Wouden JC, van der Does E. Influencing behavior of physicians ordering laboratory tests: A literature study. Med Care. 1993;31:784–794.
27. Wagner AK, Soumerai SB, Zhang F, Ross-Degnan D. Segmented regression analysis of interrupted time series studies in medication use research. J Clin Pharm Ther. 2002;27:299–309.
28. Tierney WM, Miller ME, McDonald CJ. The effect on test ordering of informing physicians of the charges for outpatient diagnostic tests. N Engl J Med. 1990;322:1499–1504.
29. Han SJ, Saigal R, Rolston JD, et al. Targeted reduction in neurosurgical laboratory utilization: Resident-led effort at a single academic institution. J Neurosurg. 2014;120:173–177.
30. Solomon DH, Hashimoto H, Daltroy L, Liang MH. Techniques to improve physicians’ use of diagnostic tests: A new conceptual framework. JAMA. 1998;280:2020–2027.

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