American Journal of Emergency Medicine 33 (2015) 320–325

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American Journal of Emergency Medicine journal homepage: www.elsevier.com/locate/ajem

Original Contribution

Impact of clinical decision support on head computed tomography use in patients with mild traumatic brain injury in the ED Ivan K. Ip, MD, MPH a,b,c,e,⁎, Ali S. Raja, MD, MPH, MBA a,b,d,e, Anurag Gupta, MD, MBA, MMSc a,b,d,e, James Andruchow, MD a,b,d,e, Aaron Sodickson, MD, PhD a,b,e, Ramin Khorasani, MD, MPH a,b,e a

Center for Evidence-Based Imaging, Harvard Medical School, Boston, MA Department of Radiology, Harvard Medical School, Boston, MA Department of Medicine, Harvard Medical School, Boston, MA d Department of Emergency Medicine, Harvard Medical School, Boston, MA e Brigham and Women's Hospital, Harvard Medical School, Boston, MA b c

a r t i c l e

i n f o

Article history: Received 18 August 2014 Received in revised form 31 October 2014 Accepted 3 November 2014

a b s t r a c t Background: Reduction of unnecessary head computed tomographies (CTs) in patients with mild traumatic brain injury (MTBI) was recently endorsed by American College of Emergency Physicians (ACEP) in the “Choosing Wisely” campaign. We examined the impact of computerized clinical decision support (CDS) on head CT utilization in MTBI emergency department (ED) visits. Methods: We conducted a 2-year cohort study at a level 1 trauma center and compared our results with the National Hospital Ambulatory Medical Care Survey from 2009 to 2010. All adult patients discharged from the ED with MTBI-associated diagnoses were included. After a baseline observation period at our institution, real-time CDS was implemented. Based upon the clinical history entered, low utility orders triggered an alert to clinicians, suggesting imaging studies might not adhere to evidence-based guidelines. Clinicians could cancel the order or ignore the alert. Primary outcome was intensity of head CT use in MTBI ED visits. Secondary outcomes included rates of delayed imaging and delays in diagnosing radiologically significant findings. χ2, logistic regression, and process control chart assessed preintervention and postintervention differences. Results: In study patients, 58.1% of MTBI-related visits resulted in head CT preintervention vs 50.3% postintervention (13.4% relative decrease, P = .005), a change not detected in controls (73.3% vs 76.9%, P = .272). Study cohort patients not receiving a head CT during their index visit were neither more nor less likely to receive one in the subsequent 7 days (6.7% preintervention vs 9.4% postintervention, P = .231). Rates of delayed diagnosis of radiologically significant findings were unchanged (0% vs 0%). Conclusions: Evidence-based CDS can reduce low utility imaging for MTBI. © 2014 Elsevier Inc. All rights reserved.

1. Introduction Mild traumatic brain injuries (MTBIs) are commonly seen in US emergency departments (EDs), accounting for an estimated 1.2 million outpatient visits annually [1]. Although most patients have no clinical sequelae from their injuries, many undergo head computed tomography (CT) as part of their routine evaluation. In fact, nearly 1 million blunt trauma patients undergo head CT imaging annually in the United States, whereas fewer than 6% prove to have significant intracranial injuries that require neurosurgical intervention [2]. A number of clinical decision rules have been developed to help guide clinicians in selecting patients for whom a head CT is likely to be beneficial. These rules allow for risk stratification of patients with suspected intracranial injuries, based on clinical findings [3-5]. When used appropriately, they ⁎ Corresponding author. Center for Evidence-Based Imaging, Department of Radiology and Medicine, Brigham and Women's Hospital, 20 Kent St, Second Floor, Boston, MA 02445. Tel.: +1 617 525 9713; fax: +1 617 525 9797. E-mail address: [email protected] (I.K. Ip). http://dx.doi.org/10.1016/j.ajem.2014.11.005 0735-6757/© 2014 Elsevier Inc. All rights reserved.

can help avoid unnecessary head CTs, without jeopardizing patient safety [6]. Despite their potential utility [7-10] and acceptance by professional societies [11], their clinical adoption remains scarce. It is estimated that 10% to 35% of CTs obtained in the ED for MTBI are not recommended according to the guidelines [12], and head CT utilization varies significantly both nationwide and within institutions [13,14]. Even when MTBI decision rules are used, significant interphysician variation persists [15]. In response, the reduction of unnecessary head CTs in patients with MTBI was recently endorsed by the American College of Emergency Physicians as a priority in their “Choosing Wisely” campaign that is pioneered by the American Board of Internal Medicine [16]. Cost-effectiveness analyses have demonstrated that if CTs for MTBI were performed according to decision rules, the United States could reduce health care expenditures by as much as $120 million annually [17]. Furthermore, associated reductions in both unnecessary exposure to radiation [18] and potential overdiagnosis [19] would be beneficial. However, interventions such as education and policy changes designed to reduce unnecessary imaging have yet to show significant cost saving [20].

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2. Methods

cancel the order as recommended by the CDS. Because of our focus on MTBI, orders of scans for multiple body parts (eg, head CTs ordered together with maxillofacial or cervical spine CT or head through pelvis “pan scans” in multisystem trauma patients) were not included to minimize unnecessary physician interactions with CDS for MTBI and help reduce alert fatigue [23].

2.1. Study design and setting

2.4. Methods and measurements

The study site is an academic quaternary care, 793-bed, level 1 trauma center, with approximately 60 000 ED visits annually. The requirement to obtain informed consent was waived by our institutional review board for this Health Insurance Portability and Accountability Act (HIPAA) compliant, observational cohort study.

Patient demographics in the study cohort were collected from electronic health records. Imaging data were identified using the radiology information system and CPOE system. The use of any head CT in the study cohort, performed on either the day of the ED visit or within the subsequent 7 days at our institution, was recorded, along with the results of that head CT to search for delayed diagnoses of radiologically significant findings. For the control cohort, similar patient demographic and head CT utilization data were collected from the NHAMCS database. Because of the design of NHAMCS, data regarding imaging studies ordered subsequent to the ED visit and delayed diagnosis of radiologically significant findings were not available for the control cohort.

The purpose of this study was to examine the impact of real-time computerized clinical decision support (CDS), based on published high-quality evidence, on the use of head CT in adult ED patients diagnosed with MTBI.

2.2. Selection of participants The study cohort included all adult ED patient visits with a discharge diagnosis of MTBI between January 1, 2009, and December 31, 2010. We selected this period to allow direct comparison with a nationwide control cohort, for which data from this timeframe have been recently published and were readily available. To identify eligible visits, we queried our institutional billing database for all visits of patients aged 18 years or older with an associated primary (or top 2 secondary) discharge diagnosis of MTBI, using International Classification of Diseases, Ninth Revision (ICD-9) codes for concussion (850.0, 850.1, 850.11, 850.12, 850.2, 850.3, 850.4, 850.5, and 850.9) and head injury not otherwise specified (959.01) as codes previously determined to represent minor traumatic brain injury [1]. To account for secular differences, we selected a control cohort consisting of ED patients diagnosed with MTBI captured from the most recent publicly available National Hospital Ambulatory Medical Care Survey (NHAMCS) during our study period. The NHAMCS was designed to be representative of emergency medical care delivered in the United States and includes data on patient demographics, medications listed, laboratory and imaging studies ordered, and up to 3 discharge diagnoses derived from ICD-9 codes. We included only visits of adult patients aged 18 years or older and used ICD-9 diagnosis (primary or secondary) to identify MTBI-related visits using the same codes as for our study cohort. 2.3. Intervention After gathering baseline data for 1 year, we implemented real-time computerized CDS into our institutional imaging computerized physician order entry (CPOE) system during the last quarter of 2009. Details of the implementation have been described previously [21,22]. The CDS enables iterative interaction with the ordering clinician to provide automated, actionable, and real-time feedback to optimize the ordering decision (Fig. 1). The CDS launched, when a head CT was ordered for the indication of “trauma.” Based on clinical data entered by the requesting clinician, the CDS indicated when head CT might be of low utility. The CDS logic was derived from 3 large, multiinstitutional, well-validated trials of high-quality evidence (the New Orleans Criteria [5], the Canadian CT Head Rule [3], and the CT in Head Injury Patients Prediction Rule [4]) for the use of head CT in patients with MTBI. The combination of these 3 high-quality prediction models allows us to capture most MTBI patients at our institution (eg, Canadian CT Head Rule excludes patients who had no loss of consciousness, whereas it is not an exclusion criterion in the CT in Head Injury Patients Prediction Rule). The CDS logic was created, reviewed, and approved collaboratively by clinical leadership in radiology and emergency medicine, including final approval from respective department chairs. Details of the logic have been described previously [22]. If a head CT order is classified as “low utility” based on the above rules, the provider is shown a CDS screen informing him/her of such, with direct links to the corresponding supporting evidence [22]. Ordering clinicians could either ignore the advice and proceed with imaging or

2.5. Outcomes Our primary outcome measure was the head CT utilization rate, defined as the number of head CTs ordered per the number of ED visits for MTBI. Head CT use in the preintervention period was compared with that postintervention. Change in head CT use between the preintervention and postintervention periods in the study cohort was compared with the control cohort to account for secular confounders. Secondary outcome measures in the study cohort included the rate of delayed imaging and the rate of delayed diagnosis of a radiologically significant finding on imaging. Delayed imaging was defined as cases in which a head CT was not performed during the initial ED visit but subsequently performed during a follow-up ED, inpatient, or outpatient visit at our institution within 7 days. Radiologically significant findings on imaging included the presence of an acute traumatic intracranial lesion (subdural, epidural, or parenchymal hematoma; subarachnoid hemorrhage; cerebral contusion; or depressed skull fracture) [5] as defined in previous studies [5,3]. 2.6. Analysis Analyses were performed using Microsoft Excel 2003 (Microsoft, Redmond, WA) and JMP 10 (SAS Institute, Cary, NC). χ2 and logistic regression were used to assess preintervention and postintervention differences. A 2-tailed P value of b .05 was defined as statistically significant. As a secondary analysis, for the study cohort, we also evaluated trend using statistical process control chart from 2008 to 2011, based on 3 δ and p subtype. Statistical process control analysis allows one to distinguish “noise” from “signal [24].” The extended period for the secondary analysis was chosen to allow for 8 data points (grouped quarterly) before and after the intervention [24]. 3. Results 3.1. Characteristic of cohorts Between January 2009 and December 2010, there were 116 009 unique ED visits at the study site and 53 477 visits in the control cohort, which were representative of nearly 20 million ED visits captured nationally through the NHAMCS. Overall, MTBI represented 1.2% of all ED visits (1.12% at the study site and 1.28% from NHAMCS). Of the 1988 combined MTBI visits identified, 50.8% were for female patients, and the average age of all patients was 46.2 years. The study cohort (n = 1302) was more diverse ethnically and contained a greater proportion of women than

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Fig. 1. A to D, Screenshots of CDS presented for orders for head CT in patients with MTBI. A to C, Data to determine whether the patient's clinical scenario is consistent with MTBI. D, Based on a combination of 3 validated decision rules, it displays for studies that have low utility.

the control cohort (52.7%). Details of the patient demographic characteristics of the study and control cohorts are shown in Table 1. 3.2. Main results Head CT utilization: Overall, 1221 (61.4%) MTBI-related ED visits were associated with a head CT being performed on the day of visit. In the study cohort, we observed a decrease in the utilization rate of head CTs among patients with MTBI after implementing CDS. In the preintervention, 58.1% of MTBI ED visits (n = 372/640) were associated with a head CT being performed, whereas in the post-CDS intervention, Table 1 Patient demographic characteristics of study and control cohorts Characteristic Sex Female (n [%]) Age (y: average ± SD) Race/ethnicity (n [%]) White Black/African American Hispanic Asian/other ⁎ Denotes statistical significance.

Study cohort (n = 1302)

Control cohort (n = 686)

P

696 (53.5%) 45.8 ± 21.6

313 (45.6%) 47.0 ± 21.9

.0009⁎ .244 b.0001⁎

732 (56.2%) 258 (19.8%) 176 (13.5%) 136 (10.5%)

446 (65.0%) 86 (12.55%) 68 (9.9%) 86 (12.55%)

utilization decreased to a rate of 50.3% (n = 333/662), an absolute difference of 7.8% and a relative decrease of 13.4% (P = .005). In contrast, in the control cohort, the use of head CT did not change significantly (73.3% preintervention vs 76.9% postintervention, P = .272) (Fig. 2). The decrease in head CT utilization in the study cohort postintervention persisted even after accounting for baseline demographic differences in age, sex, and race between the study and control cohorts (adjusted odds ratio, 0.73; P b .0001) (Table 2). 3.3. Secondary analysis To visualize temporal changes in the rate of head CT utilization and to determine if observed changes were attributable to common or special causes, we conducted statistical process control analysis of the study cohort from 2008 to 2011. Control chart (Fig. 3) demonstrated a sustained reduction in the proportion of head CT among patients with MTBI, which did not begin until after the intervention. Statistical significance was demonstrated by a run of 8 consecutive points below the center line [24]. 3.4. Secondary outcomes In the study cohort, among the 597 index ED MTBI visits that were not associated with a CT being performed, 49 (8.2%) had a head CT

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Fig. 2. Comparison of head CT utilization between study and control cohorts.

performed during the subsequent 7 days. There was no significant change in the rate of delayed imaging between the preintervention and postintervention periods in the study cohort (6.7% vs 9.4%, P = .231) or the rate of delayed diagnosis of radiologically significant findings (0% vs 0%). 4. Discussion Even with high-profile national educational campaigns like “Choosing Wisely” that advocate for reducing unnecessary head CT in patients with MTBI [16], the translation of evidence-based guidelines into clinical practice can be a slow and difficult process, often taking 10 to 20 years [12,25-27]. Health information technology–enabled CDS may serve as a vehicle to accelerate the adoption of evidence [28]. In our 2year cohort study, implementation of CDS based on high-quality evidence derived from 3 validated clinical decision rules was associated with a 13.4% relative (and 7.8% absolute) decrease in head CT utilization in adult ED patients diagnosed with MTBI, a difference not found in a national control cohort. Moreover, we found no evidence of delayed diagnosis of intracranial injury within 7 days of the index ED visit or increased intensity of follow-up imaging in patients not imaged in the initial ED visit. Coupled with the recent finding by Gupta et al [22] that CDS was associated with a 56% relative increase in documented adherence to evidence-based guidelines for imaging in patients with MTBI, our findings of reduced head CT utilization most likely represent more guideline-concordant, appropriate ordering practices in this patient population, a result not observed in our control cohort. Compared with previous reports of head CT use in patients with MTBI, our study cohort had a lower utilization rate, even in the preintervention period (58.1%). In a matched-pair cluster-randomized trial at a hospital ED in Canada, Stiell et al [20] found that approximately 62.8% to 76.2% of patients with minor head injury obtained CT imaging. Similarly, Melnick et al [29] estimated that approximately 75% of MTBI patients received CTs in the United States. These figures are comparable Table 2 Results of multivariate regression on the use of head CT controlling for patient characteristics in study cohort Variable

Odds ratio

95% CI

P

Patient age (by year)

1.03 per year 1.66

1.02-1.03

b.001⁎

1.31-2.09

b.001⁎ .651

1.07 0.91 0.91 0.73

0.73-1.57 0.59-1.41 0.57-1.45 0.58-0.92

Patient sex (reference = female) Race/ethnicity (reference = Asian/other) White Black/African American Hispanic Intervention Abbreviation: CI, confidence interval. ⁎ Denotes statistical significance.

.007⁎

with the utilization rate in our control cohort preintervention and postintervention. It is notable that, during the study period, some reports have shown an overall decline in imaging [30]. This decrease may be caused by multiple factors, including policy reform and increased emphasis on reducing radiation exposure [30]. However, we did not observe this decline in imaging for MTBI in our national comparison cohort. Although a detailed user experience analysis was beyond the scope of this study, from our informal discussions with ordering providers, the combination of high-quality evidence and the highsensitivity of the associated prediction rule were likely key contributors in adoption of the rule by ordering providers. In a potentially lifethreatening diagnosis, such as intracranial hemorrhage, many providers voiced that they would be uncomfortable with a rule that has sensitivity of less than 90%. As with any new technology, CPOE and CDS systems have had their share of unintended consequences [31,32], which include changes in workflow, changes in communication, physician concerns for loss of autonomy, increased variation [14], and duplicate orders [33,34]. We are not aware of any prior study reporting imaging CPOE/CDS being associated with an increase in the proportion of delayed diagnoses, which could pose risks to patient safety. In our study, CDS was associated with a nonsignificant trend toward increased delayed imaging in patients with MTBI. Although these delayed studies were not associated with any radiologically significant findings, this phenomenon could be associated with increased costs for an additional ED, clinic, or physician visit as well as potential patient anxiety. These follow-up visits may have neutralized some of the initial benefits associated with the decreased CT utilization in the index ED visit and may indicate a need for improved patient-provider communication regarding reasons for follow-up during the initial ED visit [35]. Further studies to examine this potential unintended consequence as well as patient-centered or shared clinical decision making are warranted. Our study has several limitations. First, it was performed at a single academic medical center with a well-established culture of quality and use of CPOE/CDS, so the generalizability of our findings in other settings is unclear, particularly for a study on physician behavior, which is more susceptible to such bias. However, our clinicians were not informed that the CDS was part of a research study. Second, it is possible that our observed decline in imaging use may not be solely due to our intervention but also confounders, such as increased public awareness of harm associated with inappropriate imaging and the publication of a related American College of Emergency Physicians' clinical policy during the study period [11]. However, no change in imaging use was observed in the control cohort, supporting previous findings that guideline publication alone may be a weak intervention for changing clinical practice [36]. Because of design of the NHAMCS survey, data to assess delayed imaging or diagnoses in the control cohort were not available. The difference in data collection methodology between the

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CT = Computed Tomography MTBI = Minor Traumatic Brain Injury UCL = Upper control limit LCL = Lower control limit µ0 = mean proportion obtained from before intervention time period Fig. 3. Statistical control chart, p subtype, depicting temporal trend of head CT utilization rate before and after intervention, based on 3 δ.

study and control cohorts (health records vs survey, respectively) represents another limitation. However, other studies over the same period have found similar head CT utilization rates as the NHAMCS cohort [29]. Another potential limitation is that we used billing data in cohort identification, which may not have captured all MTBI patients; patients who were found to have acute traumatic intracranial lesion (subdural, epidural, or parenchymal hematoma; subarachnoid hemorrhage; cerebral contusion; or depressed skull fracture) were excluded, and patients with minor head trauma who were not diagnosed with concussion or head injury would have been missed. However, our methodology is similar to that used by prior studies [1]. We likely missed a low percentage of MTBI patients [5] but this methodology would have resulted in similar proportions of missed patients in both our study and control cohorts. Furthermore, only delayed imaging performed at our institution (as measured by the ED CPOE system) was included, potentially underestimating both rates of delayed imaging or delayed diagnoses of clinically significant findings of patients who were initially seen in our ED but subsequently sought care at other institutions. However, based on our existing local practice and referral patterns, we believe this to be a very infrequent occurrence. The likelihood of delayed imaging may be associated with how well a provider counsels a patient on surveillance for postconcussive syndrome symptoms. Given this study's pragmatic nature, we allowed providers to follow their usual counseling practices of preintervention and postintervention, so this would not impact our results. However, it is possible that counseling practices changed over time. Finally, we did not assess the appropriateness of CTs performed or the work-up of patients who were not imaged.

5. Conclusion In summary, implementation of a CDS based on high-quality evidence was associated with a modest but significant decrease in head CT use in patients with MTBI with no evidence of significant increase in follow-up imaging or delayed diagnosis of intracranial injury within 7 days of their index ED visit. Our findings suggest that evidencebased imaging CDS can help safely reduce unnecessary imaging in the

ED without increase in delayed diagnosis or increase intensity of follow-up imaging. References [1] Mannix R, O'Brien MJ, Meehan III WP. The epidemiology of outpatient visits for minor head injury: 2005 to 2009. Neurosurgery 2013;73(1):129–34. http://dx.doi. org/10.1227/01.neu.0000429846.14579.41 [discussion 134]. [2] Mower WR, Hoffman JR, Herbert M, Wolfson AB, Pollack Jr CV, Zucker MI. Developing a decision instrument to guide computed tomographic imaging of blunt head injury patients. J Trauma 2005;59(4):954–9. [3] Stiell I, Wells G, Vandemheen K, Clement C, Lesiuk H, Laupacis A, et al. The Canadian CT Head Rule for patients with minor head injury. Lancet 2001;357(9266):1391–6. http://dx.doi.org/10.1016/S0140-6736(00)04561-X. [4] Smits M, Dippel DWJ, Steyerberg EW, de Haan GG, Dekker HM, Vos PE, et al. Predicting intracranial traumatic findings on computed tomography in patients with minor head injury: the CHIP prediction rule. Ann Intern Med 2007;146(6):397–405. [5] Haydel MJ, Preston CA, Mills TJ, Luber S, Blaudeau E, DeBlieux PM. Indications for computed tomography in patients with minor head injury. N Engl J Med 2000; 343(2):100–5. http://dx.doi.org/10.1056/NEJM200007133430204. [6] Stiell IG, Bennett C. Implementation of clinical decision rules in the emergency department. Acad Emerg Med 2007;14(11):955–9. http://dx.doi.org/10.1197/j.aem. 2007.06.039. [7] Harnan SE, Pickering A, Pandor A, Goodacre SW. Clinical decision rules for adults with minor head injury: a systematic review. J Trauma 2011;71(1):245–51. http:// dx.doi.org/10.1097/TA.0b013e31820d090f. [8] Papa L, Stiell IG, Clement CM, Pawlowicz A, Wolfram A, Braga C, et al. Performance of the Canadian CT Head Rule and the New Orleans Criteria for predicting any traumatic intracranial injury on computed tomography in a United States level I trauma center. Acad Emerg Med 2012;19(1):2–10. http://dx.doi.org/10.1111/j.1553-2712.2011.01247.x. [9] Smits M, Dippel DWJ, de Haan GG, Dekker HM, Vos PE, Kool DR, et al. External validation of the Canadian CT Head Rule and the New Orleans Criteria for CT scanning in patients with minor head injury. JAMA 2005;294(12):1519–25. http:// dx.doi.org/10.1001/jama.294.12.1519. [10] Stiell IG, Clement CM, Rowe BH, Schull MJ, Brison R, Cass D, et al. Comparison of the Canadian CT Head Rule and the New Orleans Criteria in patients with minor head injury. JAMA 2005;294(12):1511–8. http://dx.doi.org/10.1001/jama.294.12.1511. [11] Jagoda AS, Bazarian JJ, Bruns Jr JJ, Cantrill SV, Gean AD, Howard PK, et al. Clinical policy: neuroimaging and decision making in adult mild traumatic brain injury in the acute setting. Ann Emerg Med 2008;52(6):714–48. http://dx.doi.org/10.1016/j. annemergmed.2008.08.021. [12] Melnick ER, Szlezak CM, Bentley SK, Dziura JD, Kotlyar S, Post LA. CT overuse for mild traumatic brain injury. Jt Comm J Qual Patient Saf 2012;38(11):483–9. [13] Andruchow JE, Raja AS, Prevedello LM, Zane RD, Khorasani R. Variation in head computed tomography use for emergency department trauma patients and physician risk tolerance. Arch Intern Med 2012;172(8):660–1. http://dx.doi.org/10.1001/ archinternmed.2011.2243.

I.K. Ip et al. / American Journal of Emergency Medicine 33 (2015) 320–325 [14] Prevedello LM, Raja AS, Zane RD, Sodickson A, Lipsitz S, Schneider L, et al. Variation in use of head computed tomography by emergency physicians. Am J Med 2012; 125(4):356–64. http://dx.doi.org/10.1016/j.amjmed.2011.06.023. [15] Stiell IG, Wells GA, Vandemheen K, Laupacis A, Brison R, Eisenhauer MA, et al. Variation in ED use of computed tomography for patients with minor head injury. Ann Emerg Med 1997;30(1):14–22. [16] Glatter R. ACEP's campaign to reduce unnecessary testing in the emergency department. Forbes 2013 [http://www.forbes.com/sites/robertglatter/2013/10/16/reducinginappropriate-testing-and-procedures-in-the-emergency-department-acepscontribution-to-the-choosing-wisely-campaign/. Accessed November 25, 2013]. [17] Smits M, Dippel DWJ, Nederkoorn PJ, Dekker HM, Vos PE, Kool DR, et al. Minor head injury: CT-based strategies for management—a cost-effectiveness analysis. Radiology 2010;254(2):532–40. http://dx.doi.org/10.1148/radiol.2541081672. [18] Sodickson A, Baeyens PF, Andriole KP, Prevedello LM, Nawfel RD, Hanson R, et al. Recurrent CT, cumulative radiation exposure, and associated radiation-induced cancer risks from CT of adults. Radiology 2009;251(1):175–84. http://dx.doi.org/ 10.1148/radiol.2511081296. [19] Welch HG. Overdiagnosed: making people sick in the pursuit of health. Boston, Mass: Beacon Press; 2011. [20] Stiell IG, Clement CM, Grimshaw JM, Brison RJ, Rowe BH, Lee JS, et al. A prospective cluster-randomized trial to implement the Canadian CT Head Rule in emergency departments. CMAJ 2010;182(14):1527–32. http://dx.doi.org/10.1503/cmaj.091974. [21] Ip IK, Schneider LI, Hanson R, Marchello D, Hultman P, Viera M, et al. Adoption and meaningful use of computerized physician order entry with an integrated clinical decision support system for radiology: ten-year analysis in an urban teaching hospital. J Am Coll Radiol 2012;9(2):129–36. http://dx.doi.org/10. 1016/j.jacr.2011.10.010. [22] Gupta A, Ip IK, Raja AS, Andruchow JE, Sodickson A, Khorasani R. Effect of clinical decision support on documented guideline adherence for head CT in emergency department patients with mild traumatic brain injury. J Am Med Inform Assoc 2014. http://dx.doi.org/10.1136/amiajnl-2013-002536. [23] Carspecken CW, Sharek PJ, Longhurst C, Pageler NM. A clinical case of electronic health record drug alert fatigue: consequences for patient outcome. Pediatrics 2013;131(6):e1970–3. http://dx.doi.org/10.1542/peds. 2012-3252. [24] Cheung YY, Jung B, Sohn JH, Ogrinc G. Quality initiatives: statistical control charts: simplifying the analysis of data for quality improvement. Radiographics 2012; 32(7):2113–26. http://dx.doi.org/10.1148/rg.327125713. [25] America C on Q of HC in, Medicine I of. Crossing the quality chasm: a new health system for the 21st century. 1st ed. National Academies Press; 2001.

325

[26] Heskestad B, Baardsen R, Helseth E, Ingebrigtsen T. Guideline compliance in management of minimal, mild, and moderate head injury: high frequency of noncompliance among individual physicians despite strong guideline support from clinical leaders. J Trauma 2008;65(6):1309–13. http://dx.doi.org/10.1097/TA.0b013e31815e40cd. [27] Heskestad B, Waterloo K, Ingebrigtsen T, Romner B, Harr ME, Helseth E. An observational study of compliance with the Scandinavian guidelines for management of minimal, mild and moderate head injury. Scand J Trauma Resusc Emerg Med 2012;20:32. http://dx.doi.org/10.1186/1757-7241-20-32. [28] Raja AS, Ip IK, Prevedello LM, Sodickson AD, Farkas C, Zane RD, et al. Effect of computerized clinical decision support on the use and yield of CT pulmonary angiography in the emergency department. Radiology 2011;262(2):468–74. http://dx.doi. org/10.1148/radiol.11110951. [29] Melnick ER, Nielson JA, Finnell JT, Bullard MJ, Cantrill SV, Cochrane DG, et al. Delphi consensus on the feasibility of translating the ACEP clinical policies into computerized clinical decision support. Ann Emerg Med 2010;56(4):317–20. http://dx.doi.org/10. 1016/j.annemergmed.2010.03.006. [30] Sharpe Jr RE, Levin DC, Parker L, Rao VM. The recent reversal of the growth trend in MRI: a harbinger of the future? J Am Coll Radiol 2013;10(8):599–602. http://dx.doi. org/10.1016/j.jacr.2013.01.023. [31] Ash JS, Sittig DF, Poon EG, Guappone K, Campbell E, Dykstra RH. The extent and importance of unintended consequences related to computerized provider order entry. J Am Med Inform Assoc 2007;14(4):415–23. http://dx.doi.org/10.1197/jamia.M2373. [32] Han YY, Carcillo JA, Venkataraman ST, Clark RS, Watson RS, Nguyen TC, et al. Unexpected increased mortality after implementation of a commercially sold computerized physician order entry system. Pediatrics 2005;116(6):1506–12. http://dx.doi.org/10.1542/peds. 2005-1287. [33] Campbell EM, Sittig DF, Ash JS, Guappone KP, Dykstra RH. Types of unintended consequences related to computerized provider order entry. J Am Med Inform Assoc 2006;13(5):547–56. http://dx.doi.org/10.1197/jamia.M2042. [34] Magid S, Forrer C, Shaha S. Duplicate orders: an unintended consequence of computerized provider/physician order entry (CPOE) implementation: analysis and mitigation strategies. Appl Clin Inform 2012;3(4):377–91. http://dx.doi.org/10.4338/ACI2012-01-RA-0002. [35] Wilson IB, Dukes K, Greenfield S, Kaplan S, Hillman B. Patients' role in the use of radiology testing for common office practice complaints. Arch Intern Med 2001; 161(2):256–63. http://dx.doi.org/10.1001/archinte.161.2.256. [36] Solomon DH. Techniques to improve physicians' use of diagnostic tests: a new conceptual framework. JAMA 1998;280(23):2020–7. http://dx.doi.org/10.1001/jama. 280.23.2020.

Impact of clinical decision support on head computed tomography use in patients with mild traumatic brain injury in the ED.

Reduction of unnecessary head computed tomographies (CTs) in patients with mild traumatic brain injury (MTBI) was recently endorsed by American Colleg...
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