• No results found

Reducing Head CT Use for Children With Head Injuries in a Community Emergency Department

N/A
N/A
Protected

Academic year: 2020

Share "Reducing Head CT Use for Children With Head Injuries in a Community Emergency Department"

Copied!
11
0
0

Loading.... (view fulltext now)

Full text

(1)

Reducing Head CT Use for Children

With Head Injuries in a Community

Emergency Department

Rebecca M. Jennings, MD, a, b Jennifer J. Burtner, MD, c Joseph F. Pellicer, MD, c Deepthi K. Nair, MS, b Miranda C. Bradford, MS, b Michele Shaffer, PhD, b Neil G. Uspal, MD, d Joel S. Tieder, MD, MPHa, b

Divisions of aGeneral Pediatrics and Hospital Medicine and dEmergency Medicine, Seattle Children’s Hospital, Seattle, Washington; bCenter for Clinical & Translational Research, Seattle Children’s Research Institute, Seattle, Washington; and cProvidence St Peter Hospital Emergency Department, Olympia, Washington

Dr Jennings conceptualized and designed the study, performed and supervised the primary data abstraction, and drafted the initial manuscript; Drs Burtner, Pellicer, and Uspal helped design and implement the quality improvement initiative and reviewed and revised the manuscript; Ms Nair designed the data collection instruments, coordinated and supervised data collection, and reviewed and revised the manuscript; Ms Bradford performed data analysis and reviewed and revised the manuscript; Dr Shaffer helped to plan the data analysis and reviewed and revised the manuscript; Dr Tieder provided leadership for the design and implementation of the quality improvement initiative and critically reviewed the manuscript; and all authors approved the fi nal manuscript as submitted.

DOI: 10.1542/peds.2016-1349 Accepted for publication Oct 24, 2016

Address correspondence to Rebecca M. Jennings, MD, M/S FA.2.115, PO Box 5371, Seattle, WA 98145-5005. E-mail: rebecca.jennings@seattlechildrens.org PEDIATRICS (ISSN Numbers: Print, 0031-4005; Online, 1098-4275).

Copyright © 2017 by the American Academy of Pediatrics

FINANCIAL DISCLOSURE: The authors have indicated they have no fi nancial relationships relevant to this article to disclose.

Pediatric head trauma is a common reason to seek emergency department (ED) care in the United States,

accounting for 650 000 visits per year. 1 Patients with head trauma

present a diagnostic challenge. Clinicians need to quickly identify serious traumatic brain injuries (TBIs) while limiting the radiation exposure, sedation risk, and cost from unnecessary head computed tomography (CT). Children are

particularly susceptible to the carcinogenic properties of radiation; it is estimated that 1 case of leukemia results from every 5250 head CT scans performed on children <5 years old. 2

The Pediatric Emergency Care Applied Research Network (PECARN) created a validated prediction rule to identify pediatric patients with blunt head trauma at very low risk of clinically important TBI (ci-TBI), who can safely

abstract

BACKGROUND AND OBJECTIVE: Clinical decision rules have reduced use of computed

tomography (CT) to evaluate minor pediatric head injury in pediatric emergency departments (EDs). CT use remains high in community EDs, where the majority of children seek medical care. We sought to reduce the rate of CT scans used to evaluate pediatric head injury from 29% to 20% in a community ED.

METHODS: We evaluated a quality improvement (QI) project in a community ED

aimed at decreasing the use of head CT scans in children by implementing a validated head trauma prediction rule for traumatic brain injury. A multidisciplinary team identified key drivers of CT use and implemented decision aids to improve the use of prediction rules. The team identified and mitigated barriers. An affiliated children’s hospital offered Maintenance of Certification credit and QI coaching to participants. We used statistical process control charts to evaluate the effect of the intervention on monthly CT scan rates and performed a Wald test of equivalence to compare

preintervention and postintervention CT scan proportions.

RESULTS: The baseline period (February 2013–July 2014) included 695

patients with a CT scan rate of 29.2% (95% confidence interval, 25.8%– 32.6%). The postintervention period (August 2014–October 2015) included 651 patients with a CT scan rate of 17.4% (95% confidence interval,

14.5%–20.2%, P < .01). Barriers included targeting providers with variable pediatric experience and parental imaging expectations.

CONCLUSIONS: We demonstrate that a Maintenance of Certification QI project

sponsored by a children’s hospital can facilitate evidence-based pediatric care and decrease the rate of unnecessary CT use in a community setting.

(2)

be evaluated without a CT scan. 3

The PECARN guidelines identify multiple risk factors for ci-TBI for patients with minor head trauma (eg, severe mechanism of injury, loss of consciousness, palpable skull fracture). Among patients with no risk factors, the prediction rule has a high negative predictive value for ci-TBI of 100.0% for children <2 years old and 99.95% for children ≥2 years old. Since the publication of the PECARN guidelines, multiple quality improvement (QI) projects have achieved significant reduction in head CT scan rates for pediatric head injury in academic pediatric EDs, 4, 5

but there have not been similarly reported efforts in community settings. It is important to address head CT use in general EDs because 89% of emergency visits in the United States for patients <14 years old are in general EDs 6 and head CT

scan rates are significantly higher among patients who present to general EDs (22%) compared with pediatric EDs (13%).7, 8

Leaders in the study hospital’s pediatric department and ED identified pediatric head CT use as an area for improvement because the baseline head CT scan rate was significantly higher than the rate observed at other general EDs. 8 The goal of reducing head CT

scans aligned with the Washington State Hospital Association 100K Children Campaign, whose aim is to reduce pediatric radiation exposure in Washington hospitals. 9

We established a multidisciplinary team, including nurses, general pediatricians, and ED physicians, to identify key drivers of CT use and implement decision aids to improve the use of head trauma prediction rules for pediatric TBI. We used the Maintenance of Certification (MOC) Multispecialty Portfolio Program from an affiliated academic children’s hospital to provide support and coaching for the QI project. The aim was to reduce the rate of head CT

scans for the evaluation of pediatric head injury in a general ED from the current median rate of 29% to a goal median rate of 20% within 12 months.

METHODS

Specifi c Aim

The specific aim of the project was to reduce the head CT scan rate among pediatric patients with head trauma from 29% to 20% within 12 months. We chose 20% because it is near the published national average for general EDs. 8 Primary

drivers identified for implementation of evidence-based care were ED provider knowledge of head trauma prediction rules, standard decision process for CT imaging, and effective caregiver education about head trauma and imaging ( Fig 1).

Setting

Providence St Peter Hospital is a community hospital in Olympia, Washington, 60 miles from Seattle, with 12 000 pediatric visits per year. It is staffed by 24 emergency medicine and family medicine trained physicians and 7 physician assistants (PAs). The PAs see less acute patients. They see patients independently and consult with the ED physicians if they need guidance. Pediatric hospitalists contracted with Seattle Children’s Hospital provide 24-hour in-hospital consultation. The closest pediatric neurosurgical consultant is 28 miles away.

Seattle Children’s American Board of Medical Specialties Multispecialty MOC Portfolio Program was accredited in 2012 and maintains a portfolio of approved MOC projects aimed at improving health outcomes for children in the Pacific Northwest. The program provides MOC credit to >200 physicians per year from multiple specialties.

The Providence Institutional Review Board approved this study and waived participant consent.

Planning the Intervention

We convened a multidisciplinary team that included leaders (nurses and physicians) from the ED, trauma team, pediatric department, and a regional pediatric hospital MOC portfolio program. The project was led by a pediatric hospitalist and a general ED physician. Seattle Children’s MOC Portfolio program provided QI consultation, and participants were eligible for MOC credit. The team evaluated the impact of the interventions on patients <18 years old who presented to the ED with head injury from February 2013 to October 2015. Improvement performance, overall and by

individual clinician, was evaluated monthly via annotated statistical process control (SPC) charts.

Improvement Activities

Provider Education

The team met and developed interventions, or secondary drivers, to address the primary drivers. The team created an evidence-based decision support tool, or clinical protocol, that was adapted from the PECARN prediction rule. This protocol was finalized through feedback with key stakeholders at multiple planning meetings in July 2014. The QI initiative was then launched for the ED physicians during an initial educational meeting in August 2014, where the PECARN prediction rule was reviewed and the new clinical protocol was introduced. The clinical protocol was posted on a laminated sheet at each physician workstation in the ED. Laminated pocket-sized cards were distributed to all physicians and PAs. To address caregiver education, we discussed possible scripts to use when

(3)

Performance Data

Baseline CT scan rates were reviewed and compared with national averages at the stakeholder and ED provider meetings. The project’s progress was reviewed every 3 to 4 months at ED provider meetings, and barriers to implementation were addressed. An annotated run chart was updated monthly, publicly posted in a

common area of the ED, and e-mailed to providers. Semiannually, clinicians were privately provided with their personal CT use rates, benchmarked

to other providers in the group on a deidentified chart. Only providers who had treated ≥5 patients with head injuries in both the preintervention and postintervention periods were included.

Subject Identifi cation

We performed a retrospective medical record review on eligible subjects during the preintervention period (February 1, 2013 to July 31, 2014) and postintervention period (August 1, 2014 to October 31, 2015). We included patients <18

years old at the time of presentation to the ED with an International Classification of Diseases, Ninth Revision, Clinical Modification (ICD-9-CM) discharge diagnosis code indicating head trauma (head injury [959.01], concussion [850.xx], skull fracture [800.xx–804.xx], intracranial hemorrhage [851.xx– 853.xx], or other brain injury [854.xx]). 7 For patients discharged

in October 2015, the International Classification of Diseases, 10th Revision discharge codes of S06.0X0A, S06.0X1A, S06.9X1A,

FIGURE 1

(4)

S09.8XXA, and S09.90XA were used. Patients with an ICD-9-CM discharge code indicating comorbid conditions that might increase risk for bleeding or brain injury were excluded. Excluded ICD-9-CM discharge codes were hemophilia (286.xx), thrombocytopenia (287.xx), and ventriculoperitoneal shunt (V45.2). For October 2015, the International Classification of Diseases, 10th Revision discharge codes of D65–D69.XXX, P54, P61.0, and Z98.2 were used.

Outcome Assessment

The primary outcome of interest was the rate of cranial CT imaging among eligible patients. Covariates included race, age, sex, and insurance status (public versus private). Balancing measures were readmissions within 72 hours to the index ED to assess missed cases of ci-TBI, and length of stay (LOS) to assess changes in resource utilization. Patients with an LOS >12 hours were excluded from the LOS analysis if they were evaluated by the crisis counselor for psychiatric comorbidity after their initial evaluation for head trauma. The provider was considered the assigned attending provider listed in the electronic medical record (EMR) encounter. If a patient was evaluated by both a PA and a physician, the physician was assigned the role of attending provider.

Data Analysis

We summarized sample characteristics by using

appropriate descriptive statistics for quantitative (mean and SD or median and interquartile range [IQR]) and categorical (counts and percentages) variables. We calculated preintervention and postintervention proportions for CT head imaging. We estimated 95% confidence intervals (CIs) for CT scan proportions by

using a logit transform and Huber–White sandwich variance estimates to account for within-subject correlation due to repeat admissions (<5% of patients) and performed a Wald test of equivalence for preintervention and postintervention proportion estimates. 10, 11 In addition, we

carried out an interrupted time series analysis based on autoregressive integrated moving average models as a sensitivity analysis to account for potential secular trends. 12

SPC charts with 1-month time intervals were constructed to assess the effect of the intervention on CT scan rates. We set control limits at 3 SD from the mean and used standard criteria to identify special causes. 13, 14

Centerline shifts were made when 8 consecutive points fell above or below the centerline. SPC charts were constructed with QI Macros (KnowWare International, Inc, Denver, CO).

We compared preintervention and postintervention LOS by using the Wilcoxon rank-sum test. For our other balancing measure, 72-hour readmissions, we calculated preintervention and postintervention monthly readmission proportions.

RESULTS

The baseline period included 695 patients, and the postintervention period included 651 patients. Four patients were excluded because of comorbid conditions (2 in the preintervention period and 2 in the postintervention period). The characteristics of our patient population were similar in the preintervention and postintervention groups ( Table 1).

The proportion of head CT scans declined from 29.2% (95% CI, 25.8%–32.6%) at baseline to

17.4% during the postintervention period (95% CI, 14.5%–20.2%,

P < .01) ( Fig 2). These results were consistent with results from the interrupted time series sensitivity analysis, which estimated that monthly CT scan rates dropped by 12.0% (95% CI, 7.4%–16.5%,

P < .01). Multiple barriers were identified and addressed by the team with new or modified interventions ( Table 2).

The median LOS increased from 1.5 hours in the preintervention period (IQR 0.9–2.5) to 1.9 hours in the postintervention period (IQR 1.0–2.8,

P < .01).

There were 13 readmissions within 72 hours during the study period, 5 in the preintervention period and 8 in the postintervention period. None of these readmissions were diagnosed with a ci-TBI; 1 patient in the preintervention period was diagnosed with a linear, nondisplaced skull fracture.

During the baseline period,

individual provider rates of head CT scan usage varied from 4% to 92%. The majority of providers (22 out of 28) demonstrated a reduction in head CT scan rate during the postintervention period ( Fig 3). Among physicians, the average CT scan rate declined from 47.0% (95% CI, 41.9%–52.1%) at baseline to 31.4% (95% CI, 26.3%–36.9%) after intervention, whereas among PAs the average CT scan rate fell from 6.6% (95% CI, 4.1%–10.1%) to 2.5% (95% CI, 1.1%–4.9%).

DISCUSSION

(5)

patients in a community ED from 29.2% to 17.4% and sustain this change over 15 months.

Our project was aided by a multidisciplinary QI team, with coaching from an academic center with more QI expertise. Formal mentoring has been shown to help successfully implement evidence-based recommendations and reduce variation in care in the community setting. 15 The educational outreach

by a pediatric ED physician from a site that had successfully implemented the PECARN rules probably helped in the adoption of the intervention. 16

The majority of providers improved their rate of CT use, although variation persisted across

providers. Among providers who had a higher CT scan rate in the postintervention period, there were not identifiable reasons for the increase. We found that providing feedback to individual providers about how their performance compared with others within our organization was beneficial. This feedback was particularly useful in a community

setting. The pediatric-specific resources available in community EDs are often not as robust as in academic pediatric EDs, and patient populations may differ. Our providers preferred feedback within their peer group, instead of being benchmarked to external providers.

We had marked improvement in ordering rates by PAs. Our PAs see

FIGURE 2

SPC chart of the proportion of eligible patients in the ED with head trauma receiving a head CT scan from February 2013 through October 2015. LCL, lower control limit; UCL, upper control limit.

TABLE 2 Characteristics of Patients in the Preintervention and Postintervention Time Periods Characteristic Preintervention, N = 695 Postintervention, N = 651

Age, median (IQR); range 8 (2–13); 0–17 9 (3–14); 0–17

Race, n (%)

White 550 (79.1) 487 (74.8)

Nonwhite 129 (18.6) 124 (19)

Unknown or refused 16 (2.3) 40 (6.1)

Private insurance, n (%) 314 (45.2) 295 (45.3)

(6)

less acute patients independently, and we encouraged them to consult the ED physicians for more acute patients who may need a CT scan. PAs can play a critical component in quality care endeavors and in fact are now required to incorporate QI in their MOC process. 17 Our

study demonstrates the importance of involving nonphysician care providers in QI processes.

There is a significant lag between when research is first described and when it is finally adopted into clinical practice. 18 Numerous QI

projects in tertiary care pediatric EDs have sought to increase the use of evidence-based guidelines. 19–21

Yet the majority of pediatric patients are seen at community hospital EDs.6 Hospitals that see a smaller

volume of pediatric patients are less likely to have adopted guidelines to help guide imaging decision-making processes for pediatric head trauma patients. 22 Indeed, head CT scan rates

among pediatric head injury patients are significantly higher in community hospitals. 7

There are many barriers to the adoption of evidence-based pediatric care in community EDs. Because the

majority of patients seen by general ED physicians are adults, continuing medical education programs may not focus on pediatric care and there may be no impetus to create pediatric-specific protocols. The Joint Commission has implemented multiple national hospital inpatient quality core measures, but nearly all these measures are specific to adult care. 23 This discrepancy may

lead some community hospitals to focus all or nearly all of their QI endeavors on adult care. When pediatric-specific quality measures are created, community hospitals may more readily focus on pediatric care. We found this to be the case at our own institution when the Washington State

Hospital Association included imaging for pediatric head trauma among their improvement efforts. 9 Our community hospital

was able to overcome these barriers with the help of hospital leadership support for our pediatric-specific QI initiative. In addition, because of the presence of pediatric hospitalists, we have hospital-based providers invested in improving pediatric quality measures.

Another barrier to the dissemination of pediatric-specific evidence encountered at community hospitals is that providers may use adult-specific decision tools for pediatric patients. We found that before our intervention, many of our providers used the Canadian CT Head Rule to decide whether to image pediatric patients, even though this decision tool included only patients ≥16 years old. 24 Pediatric QI efforts

at community hospitals should emphasize the unique clinical considerations of pediatric patients for providers who manage the full age spectrum. We demonstrate that the use of pediatric-specific evidence-based clinical protocols can improve the use of evidence-based medicine in community EDs.

The adoption of the PECARN guidelines is important because it decreases radiation exposure, which can lead to cancer, 25

and is cost-effective. Given the lifetime risk of cancer, imaging is beneficial only with higher pretest probability of ci-TBI, such as the higher-risk patients in the PECARN guidelines. 26 Unnecessary testing

can lead to incidental findings; of the patients included in the PECARN study, 4% who underwent CT scans were found to have incidental findings on head CT scans. 27

Incidental findings can result in additional parental anxiety, testing, cost, and procedures and often have unclear clinical significance. 28

Because of the risks associated with unnecessary testing, many professional groups have focused on appropriate use criteria. During our postintervention period, our hospital performed 76 fewer CT scans than we would have if our preintervention CT scan rate had continued.

The regional pediatric hospital facilitated an effective QI project in a local community hospital by using MOC credit to encourage TABLE 1 Barriers to Implementation Identifi ed and Mitigated During Initiative

Barrier Intervention

Discomfort with pediatric assessment among ED physicians

1. ED physicians encouraged to consult on-call pediatric hospitalist for patients with equivocal examination or presentation.

2. PECARN criteria and clinical pathway reviewed at monthly pediatric hospitalist meeting.

Management of parental expectations

1. Scripts to use with parents were reviewed at follow-up ED provider meetings. Providers encouraged to show parents pathway to help explain risk.

2. Clinical pathway presented at grand rounds with outpatient providers. Outpatient providers encouraged to explain referral to ED as referral for additional evaluation, not referral for CT.

Address late adopters 1. Individual provider feedback: ED physicians provided with deidentifi ed chart to benchmark personal CT scan rate as compared with rest of group.

Familiarity with PECARN rules 1. Presentation to ED physicians, PAs: Clinical protocol adapted from PECARN rule and presented at ED physician and PA meetings and grand rounds.

2. Clinical protocol posted on a laminated sheet at each physician workstation.

(7)

participation. Other studies have shown that offering MOC credit can increase participation for QI projects in community settings. 29 MOC was established

by the American Board of Medical Specialties to encourage ongoing improvement in physicians’ knowledge, and improvement in medical practice to evidence-based care. 30 In part IV of the

MOC requirements, physicians participate in approved QI projects. 29 However, MOC

requirements have been criticized because they do not always fulfill practice-specific needs, and they provide minimal benefit if not tailored to the practice of the physician, 30 and so valuable

MOC projects are needed.31

We demonstrate that regional children’s hospitals can use MOC requirements to help community hospitals adopt evidence-based best practices and improve important outcomes.

One challenge we encountered was that we were unable to standardize the CT ordering process through a “best practice alert” in the EMR. Because the community hospital is part of a larger health system, EMR changes were difficult to institute. These changes may have further decreased our rate of head CT scans. 32, 33

It is important to note that we did have a statistically significant

increase in our LOS, 1 of our balancing measures. This increase in LOS is probably secondary to more patients who were observed after head injury instead of immediately imaged. The median LOS increased by only 24 minutes (from 90 minutes to 114 minutes), and so the clinical significance of this increased LOS is unclear. We think that the benefits of decreased CT use outweigh the disadvantage of a longer LOS.

This study has several important limitations. First, the partnership with pediatric hospitalists from the regional pediatric hospital helped engage and coach multiple stakeholders in change, and

FIGURE 3

(8)

this assistance is not available at many community hospitals. Therefore, our results may not be generalizable to community hospitals that do not have pediatric hospitalist presence. Second, although we tracked readmissions within 72 hours to our hospital, patients may have been readmitted to other hospitals. There may be patients with ci-TBIs that were missed when we evaluated readmissions. However, with proper implementation of PECARN, the rate of missed ci-TBIs is low. 3, 25

In addition, we evaluated only absolute CT scan rates and did not evaluate whether PECARN was appropriately used with each encounter, because this analysis was beyond the scope of this study. Glasgow Coma Scale scores were not available in the EMR for the majority of

the included patients, and so we were unable to limit our study population to patients with only minor head injuries, and we were unable to compare the head injury severity in the preintervention and postintervention patient populations. We have not yet demonstrated prolonged sustainability, but we plan to continue tracking CT scan rates, monitoring readmissions, and engaging the ED providers to maintain change.

CONCLUSIONS

We demonstrate that a

multidisciplinary MOC QI project sponsored by a regional children’s hospital can decrease the rate of CT use in the evaluation of pediatric head injury in a community setting.

ABBREVIATIONS

CI:  confidence interval ci-TBI:  clinically important

traumatic brain injury CT:  computed tomography ED:  emergency department EMR:  electronic medical record ICD-9-CM:  International

Classification of Diseases, Ninth Revision, Clinical Modification IQR:  interquartile range LOS:  length of stay MOC:  Maintenance of

Certification PA:  physician assistant PECARN:  Pediatric Emergency

Care Applied Research Network

QI:  quality improvement SPC:  statistical process control TBI:  traumatic brain injury

FUNDING: All phases of this study were supported by Seattle Children’s Hospital Academic Enrichment Fund. POTENTIAL CONFLICT OF INTEREST: The authors have indicated they have no potential confl icts of interest to disclose.

REFERENCES

1. Kuppermann N. Pediatric head trauma: the evidence regarding indications for emergent neuroimaging. Pediatr

Radiol. 2008;38(suppl 4):S670–S674

2. Miglioretti DL, Johnson E, Williams A, et al. The use of computed tomography in pediatrics and the associated radiation exposure and estimated cancer risk.

JAMA Pediatr. 2013;167(8):700–707

3. Kuppermann N, Holmes JF, Dayan PS, et al; Pediatric Emergency Care Applied Research Network (PECARN). Identifi cation of children at very low risk of clinically-important brain injuries after head trauma: a prospective cohort study. Lancet. 2009;374(9696):1160–1170

4. Bressan S, Romanato S, Mion T, Zanconato S, Da Dalt L. Implementation of adapted PECARN decision rule for children with minor head injury in the pediatric emergency department. Acad

Emerg Med. 2012;19(7):801–807

5. Nigrovic LE, Stack AM, Mannix RC, et al. Quality improvement effort to reduce cranial CTs for children with minor blunt head trauma. Pediatrics. 2015;136(1). Available at: www. pediatrics. org/ cgi/ content/ full/ 136/ 1/ e227

6. Gausche-Hill M, Schmitz C, Lewis RJ. Pediatric preparedness of US emergency departments: a 2003 survey. Pediatrics. 2007;120(6):1229–1237

7. Mannix R, Bourgeois FT, Schutzman SA, Bernstein A, Lee LK. Neuroimaging for pediatric head trauma: do patient and hospital characteristics infl uence who gets imaged? Acad Emerg Med. 2010;17(7):694–700

8. Blackwell CD, Gorelick M, Holmes JF, Bandyopadhyay S, Kuppermann N. Pediatric head trauma: changes in use of computed tomography in emergency departments in the United States over time. Ann Emerg Med. 2007;49(3):320–324

9. WA State Hospital Association. 100K Children Campaign. Available at: www. wsha. org/ quality- safety/ projects/ 100k- children- campaign/ . Accessed January 11, 2016

10. Huber PJ. The behavior of maximum likelihood estimates under nonstandard conditions. In:

Proceedings of the Fifth Berkeley Symposium on Mathematical Statistics and Probability. Vol 1. Berkeley, CA: University of California Press; 1967:221–233

11. White H. A heteroskedasticity-consistent covariance matrix estimator and a direct test for heteroskedasticity. Econometrica. 1980;48(4):817–838

12. Box GEP, Jenkins GM, Reinsel GC. Time Series Analysis: Forecasting and Control. 4th ed. Hoboken, NJ: Wiley; 2008

(9)

tool for research and healthcare improvement. Qual Saf Health Care. 2003;12(6):458–464

14. Benneyan JC. Use and interpretation of statistical quality control charts. Int

J Qual Health Care. 1998;10(1):69–73

15. Li J, Hinami K, Hansen LO, Maynard G, Budnitz T, Williams MV. The physician mentored implementation model: a promising quality improvement framework for health care change.

Acad Med. 2015;90(3):303–310

16. Grol R, Grimshaw J. From best evidence to best practice: effective implementation of change in patients’ care. Lancet. 2003;362(9391):1225–1230

17. Boucher NA, Mcmillen MA, Gould JS. Agents for change: nonphysician medical providers and health care quality. Perm J. 2015;19(1):90–93

18. Trochim W, Kane C, Graham MJ, Pincus HA. Evaluating translational research: a process marker model. Clin Transl Sci. 2011;4(3):153–162

19. Jerardi KE, Elkeeb D, Weiser J, Brinkman WB. Rapid implementation of evidence-based guidelines for imaging after fi rst urinary tract infection.

Pediatrics. 2013;132(3). Available at: www. pediatrics. org/ cgi/ content/ full/ 132/ 3/ e749

20. Murtagh Kurowski E, Shah SS, Thomson J, et al. Improvement methodology increases guideline recommended blood cultures in children with pneumonia. Pediatrics. 2015;135(4). Available at: www. pediatrics. org/ cgi/ content/ full/ 135/ 4/ e1052

21. Ambroggio L, Thomson J, Murtagh Kurowski E, et al. Quality improvement methods increase appropriate antibiotic prescribing for childhood pneumonia. Pediatrics. 2013;131(5). Available at: www. pediatrics. org/ cgi/ content/ full/ 131/ 5/ e1623

22. Wylie MC, Merritt C, Clark M, Garro AC, Rutman MS. Imaging of pediatric head injury in the emergency department. Pediatr Emerg Care. 2014;30(10):680–685

23. The Joint Commission. Specifi cations manual for national hospital inpatient quality measures. Available at: www. jointcommission. org/ specifi cations_ manual_ for_ national_ hospital_ inpatient_ quality_ measures. aspx. Accessed August 11, 2016

24. Stiell IG, Wells GA, Vandemheen K, et al. The Canadian CT Head Rule for patients with minor head injury. Lancet. 2001;357(9266):1391–1396

25. Nishijima DK, Yang Z, Urbich M, et al. Cost-effectiveness of the PECARN rules in children with minor head trauma.

Ann Emerg Med. 2015;65(1):72–80.e6

26. Hennelly KE, Mannix R, Nigrovic LE, et al. Pediatric traumatic brain injury and radiation risks: a clinical decision analysis. J Pediatr. 2013;162(2):392–397

27. Rogers AJ, Maher CO, Schunk JE, et al; Pediatric Emergency Care Applied Research Network. Incidental fi ndings in children with blunt head trauma evaluated with cranial CT scans.

Pediatrics. 2013;132(2). Available at: www. pediatrics. org/ cgi/ content/ full/ 132/ 2/ e356

28. Jensen MC, Brant-Zawadzki MN, Obuchowski N, Modic MT, Malkasian D, Ross JS. Magnetic resonance imaging of the lumbar spine in people without back pain. N Engl J Med. 1994;331(2):69–73

29. Gorzkowski JA, Klein JD, Harris DL, et al. Maintenance of Certifi cation Part 4 Credit and recruitment for practice-based research. Pediatrics. 2014;134(4):747–753

30. Cook DA, Holmboe ES, Sorensen KJ, Berger RA, Wilkinson JM. Getting maintenance of certifi cation to work: a grounded theory study of physicians’ perceptions. JAMA Intern Med. 2015;175(1):35–42

31. Levinson W, King TEJ Jr, Goldman L, Goroll AH, Kessler B. Clinical decisions. American Board of Internal Medicine maintenance of certifi cation program.

N Engl J Med. 2010;362(10):948–952

32. Ballard DW, Rauchwerger AS, Reed ME, et al; Kaiser Permanente CREST Network. Emergency physicians’ knowledge and attitudes of clinical decision support in the electronic health record: a survey-based study.

Acad Emerg Med. 2013;20(4):352–360

33. Sheehan B, Nigrovic LE, Dayan PS, et al; Pediatric Emergency Care Applied Research Network (PECARN). Informing the design of clinical decision support services for evaluation of children with minor blunt head trauma in the emergency department: a sociotechnical analysis. J Biomed

(10)

DOI: 10.1542/peds.2016-1349 originally published online March 2, 2017;

2017;139;

Pediatrics

Miranda C. Bradford, Michele Shaffer, Neil G. Uspal and Joel S. Tieder

Rebecca M. Jennings, Jennifer J. Burtner, Joseph F. Pellicer, Deepthi K. Nair,

Emergency Department

Reducing Head CT Use for Children With Head Injuries in a Community

Services

Updated Information &

http://pediatrics.aappublications.org/content/139/4/e20161349 including high resolution figures, can be found at:

References

http://pediatrics.aappublications.org/content/139/4/e20161349#BIBL This article cites 30 articles, 8 of which you can access for free at:

Subspecialty Collections

sub

http://www.aappublications.org/cgi/collection/quality_improvement_ Quality Improvement

_management_sub

http://www.aappublications.org/cgi/collection/administration:practice Administration/Practice Management

sub

http://www.aappublications.org/cgi/collection/emergency_medicine_ Emergency Medicine

following collection(s):

This article, along with others on similar topics, appears in the

Permissions & Licensing

http://www.aappublications.org/site/misc/Permissions.xhtml in its entirety can be found online at:

Information about reproducing this article in parts (figures, tables) or

Reprints

(11)

DOI: 10.1542/peds.2016-1349 originally published online March 2, 2017;

2017;139;

Pediatrics

Miranda C. Bradford, Michele Shaffer, Neil G. Uspal and Joel S. Tieder

Rebecca M. Jennings, Jennifer J. Burtner, Joseph F. Pellicer, Deepthi K. Nair,

Emergency Department

Reducing Head CT Use for Children With Head Injuries in a Community

http://pediatrics.aappublications.org/content/139/4/e20161349

located on the World Wide Web at:

The online version of this article, along with updated information and services, is

by the American Academy of Pediatrics. All rights reserved. Print ISSN: 1073-0397.

Figure

TABLE 2  Characteristics of Patients in the Preintervention and Postintervention Time Periods
TABLE 1  Barriers to Implementation Identifi ed and Mitigated During Initiative

References

Related documents

Do not soft reset a Pocket PC running Windows Mobile 2003, 2003SE or Windows Mobile 5.0 when a Socket card is inserted, or errors may occur in application(s) that use the card.

– Increased intraabdominal adipose tissue (metabolically active) leads to increased glucose and hyperinsulinemia – Increased insulin resistance.. – Downregulation of insulin

Real-world ethics in palliative care: Protocol for a systematic review of the ethical challenges reported by specialist palliative care practitioners in their clinical practice..

2,15,17 Are there any other treatment options for patients who fail both conservative and interventional procedures before undergoing surgical procedures (discectomy,

For example, Salvaterra et al assert that “Broad consent is not truly informed consent, but rather is a generic authorisation that sacrifices the right of the donor to

As suggested by the high level of evidence used to support its recommendation as a first-line therapy, sodium oxybate has demonstrated efficacy for the treatment of cataplexy

Type 2 diabetes mellitus might be a risk factor for mild cognitive impairment progressing to alzheimer’s disease.. Wei