Implementation of a Clinical Decision Support System for Children With Minor Blunt Head Trauma Who Are at Nonnegligible Risk for Traumatic Brain Injuries

Ballard, Dustin; Kuppermann, Nathan; Vinson, David R.; Tham, Eric; Hoffman, Jeff; Swietlik, Marguerite; Davies, Sara J Deakyne; Alessandrini, Evaline A.; Tzimenatos, Leah; Bajaj, Lalit; Mark, Dustin G.; Offerman, Steven R.; Chettipally, Uli K.; Paterno, Marilyn D.; Schaeffer, Molly; Richards, Rachel; Casper, T. Charles; Goldberg, Howard; Grundmeier, Robert W.; Dayan, Peter

doi:10.1016/j.annemergmed.2018.11.011

Cited by 23 publications

(28 citation statements)

References 40 publications

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“…EMR decision support has been shown to safely decrease CT utilization in children with head trauma presenting to the pediatric ED 8,15,19 . Providing specific risk estimates of ciTBI via integrated decision support has been shown to reduce CT use from 24.2% to 21.6% in children with one isolated PECARN risk factor 11 . Our study reaffirms the impact of clinical decision aids as part of a QI initiative for minor head trauma in children.…”

Section: Discussionsupporting

confidence: 72%

“…Finally, we think that our institution’s policy of discussing the patient with the radiologist before obtaining a CT scan contributed to our low baseline CT rates for MHI patients. Our baseline was already lower than previously reported preintervention (21.6% to 62.5%) and postintervention rates (21.6% to 35.9%) for intermediate‐risk MHI patients across both pediatric and community ED settings 11,12,17 . We believe that preapproval by a radiologist ensures due diligence on the part of ED providers, weighing the necessity of ordering CT scans, thus limiting the number of inappropriate studies.…”

Section: Discussioncontrasting

confidence: 50%

“…In another multicenter study, implementation of decision support was associated with a modest decrease in head CT rate from 24.2% to 21.6%. This study only examined children with one isolated intermediate PECARN risk factor for ciTBI 11 . In a different initiative, based in a community setting, a PECARN‐based pediatric closed head injury assessment tool was successful in decreasing CT use in both all‐risk (37.7% to 16.9%) and intermediate‐risk (62.5% to 35.9%) MHI patients 12 .…”

Section: Discussionmentioning

confidence: 99%

“…There are no published benchmark goals for CT use in intermediate‐risk MHI patients. Previous improvement initiatives have reported postintervention rates varying from 21.6% to 35.9%, but our baseline was already lower than these rates 11,12,17 . We compared our baseline performance with top‐performing sites within the MEDIC collaborative to frame our site‐specific goal.…”

Section: Methodsmentioning

confidence: 99%

“…Intermediate‐risk MHI patients pose a challenge, because the rules recommend either CT or ED observation (based on clinical presentation and provider/parental preference). Implementation of PECARN rules in combination with clinical decision support systems and provider feedback has successfully reduced CT rates for all‐risk MHI patients in both pediatric and community EDs 7–9,11,12 . Moving forward, the intermediate‐risk MHI patients provide a challenging opportunity for improvement because CT scan utilization in this group remains high.…”

mentioning

confidence: 99%

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Reducing Computed Tomography Scan Utilization for Pediatric Minor Head Injury in the Emergency Department: A Quality Improvement Initiative

Arora

White

Niedbala

et al. 2020

Academic Emergency Medicine

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Background The validated Pediatric Emergency Care Applied Research Network (PECARN) prediction rules are meant to aid clinicians in safely reducing unwarranted imaging in children with minor head injuries (MHI). Even so, computed tomography (CT) scan utilization remains high, especially in intermediate‐risk (per PECARN) MHI patients. The primary objective of this quality improvement initiative was to reduce CT utilization rates in the intermediate‐risk MHI patients. Methods This project was conducted in a Level I trauma pediatric emergency department (ED). Children < 18 years evaluated for intermediate‐risk MHI from June 2016 through July 2019 were included. Our key drivers were provider education, decision support, and performance feedback. Our primary outcome was change in head CT utilization rate (%). Balancing measures included return visit within 72 hours of the index visit, ED length of stay (LOS), and clinically important traumatic brain injury (ciTBI) on the revisit. We used statistical process control methodology to assess head CT rates over time. Results A total of 1,535 eligible intermediate‐risk MHI patients were analyzed. Our intervention bundle was associated with a decrease in CT use from 18.5% (95% confidence interval [CI] = 14.5% to 22.5%) in the preintervention period to 13.9% (95% CI = 13.8% to 14.1%) in the postintervention period, an absolute reduction of 4.6% (p = 0.015). Over time, no difference was noted in either ED LOS or return visit rate. There was only one revisit with a ciTBI to our institution during the study period. Conclusions Our multifaceted quality improvement initiative was both safe and effective in reducing our CT utilization rates in children with intermediate‐risk MHI.

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Section: Discussionsupporting

confidence: 72%

Section: Discussioncontrasting

confidence: 50%

Section: Discussionmentioning

confidence: 99%

Section: Methodsmentioning

confidence: 99%

mentioning

confidence: 99%

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Reducing Computed Tomography Scan Utilization for Pediatric Minor Head Injury in the Emergency Department: A Quality Improvement Initiative

Arora

White

Niedbala

et al. 2020

Academic Emergency Medicine

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Machine Learning at the Clinical Bedside—The Ghost in the Machine

2019

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settings, in which lack of resources means that patients are given an appointment up to 3 months after the initial script. Too often, both clinicians and patients may settle for better without an understanding of what best looks like. Dose optimization requires several visits, clinician time, and patient education. This initial investment might lead to more patients achieving remission over just improvement and might mitigate our current rates of adherence and persistence, which are poor. 7 Ching et al 1 have done the pediatric field a great service by asking the right questions and by neatly outlining the relevant studies on formulation, maximum dose range used, and mean dose. Clinical trials can do a better job of describing their titration process and outlining the rationale for dosing limits in their manuscripts. As we move toward personalized or precision approaches to ADHD treatment, identifying the factors associated with the variability in dose response effects is a crucial next step.

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Algorithmic Medicine

Grant

2024

The Virtual Hospital

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Implementation of a Clinical Decision Support System for Children With Minor Blunt Head Trauma Who Are at Nonnegligible Risk for Traumatic Brain Injuries

Cited by 23 publications

References 40 publications

Reducing Computed Tomography Scan Utilization for Pediatric Minor Head Injury in the Emergency Department: A Quality Improvement Initiative

Reducing Computed Tomography Scan Utilization for Pediatric Minor Head Injury in the Emergency Department: A Quality Improvement Initiative

Machine Learning at the Clinical Bedside—The Ghost in the Machine

Algorithmic Medicine

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