The Trauma Quality Improvement Program: Pilot Study and Initial Demonstration of Feasibility

Hemmila, Mark R.; Nathens, Avery B.; Shafi, Shahid; Calland, J. Forrest; Clark, David E.; Cryer, H. Gill; Goble, Sandra; Hoeft, Christopher; Meredith, J. Wayne; Neal, Melanie; Pasquale, Michael D.; Pomphrey, Michelle; Fildes, John

doi:10.1097/ta.0b013e3181cfc8e6

Cited by 137 publications

(110 citation statements)

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“…27 The inclusion criteria for entry into TQIP require at least one valid trauma International Statistical Classification of Diseases, Ninth Revision, Clinical Modification (ICD-9-CM) code in the range of 800-959, excluding the late effects of trauma (905-909). 26 Although the ACS administers the program, the authors of this study are solely responsible for the analyses and conclusions presented here. The study was approved by the research ethics board of Sunnybrook Health Sciences Center (Toronto, Ontario, Canada).…”

Section: Data Sourcementioning

confidence: 99%

“…The TQIP was created to provide an opportunity for trauma centers to compare their processes of care-and risk-adjusted outcomes with their peer centers. 26 As of late 2011, the TQIP includes 155 ACS-verified level I and II trauma centers across the United States and Canada. More than 100 patient and institutional variables are recorded by trained abstractors, including patient demographics, comorbid conditions, type and mechanism of injury, injury severity, prehospital and emergency department (ED) physiological variables, in-hospital procedures and complications, and outcome information, including in-hospital mortality and discharge disposition.…”

Section: Data Sourcementioning

confidence: 99%

“…More than 100 patient and institutional variables are recorded by trained abstractors, including patient demographics, comorbid conditions, type and mechanism of injury, injury severity, prehospital and emergency department (ED) physiological variables, in-hospital procedures and complications, and outcome information, including in-hospital mortality and discharge disposition. 26 Reliability of the data is ensured through intensive training mechanisms for the abstractors and interrater reliability audits of the participating sites. 27 The inclusion criteria for entry into TQIP require at least one valid trauma International Statistical Classification of Diseases, Ninth Revision, Clinical Modification (ICD-9-CM) code in the range of 800-959, excluding the late effects of trauma (905-909).…”

Section: Data Sourcementioning

confidence: 99%

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Intracranial Pressure Monitoring in Severe Traumatic Brain Injury: Results from the American College of Surgeons Trauma Quality Improvement Program

Alali

Fowler

Mainprize

et al. 2013

Journal of Neurotrauma

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175

145

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Although existing guidelines support the utilization of intracranial pressure (ICP) monitoring in patients with traumatic brain injury (TBI), the evidence suggesting benefit is limited. To evaluate the impact on outcome, we determined the relationship between ICP monitoring and mortality in centers participating in the American College of Surgeons Trauma Quality Improvement Program (TQIP). Data on 10,628 adults with severe TBI were derived from 155 TQIP centers over 2009-2011. Random-intercept multilevel modeling was used to evaluate the association between ICP monitoring and mortality after adjusting for important confounders. We evaluated this relationship at the patient level and at the institutional level. Overall mortality (n = 3769) was 35%. Only 1874 (17.6%) patients underwent ICP monitoring, with a mortality of 32%. The adjusted odds ratio (OR) for mortality was 0.44 [95% confidence interval (CI), 0.31-0.63], when comparing patients with ICP monitoring to those without. It is plausible that patients receiving ICP monitoring were selected because of an anticipated favorable outcome. To overcome this limitation, we stratified hospitals into quartiles based on ICP monitoring utilization. Hospitals with higher rates of ICP monitoring use were associated with lower mortality: The adjusted OR of death was 0.52 (95% CI, 0.35-0.78) in the quartile of hospitals with highest use, compared to the lowest. ICP monitoring utilization rates explained only 9.9% of variation in mortality across centers. Results were comparable irrespective of the method of case-mix adjustment. In this observational study, ICP monitoring utilization was associated with lower mortality. However, variability in ICP monitoring rates contributed only modestly to variability in institutional mortality rates. Identifying other institutional practices that impact on mortality is an important area for future research.

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Section: Data Sourcementioning

confidence: 99%

Section: Data Sourcementioning

confidence: 99%

Section: Data Sourcementioning

confidence: 99%

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Intracranial Pressure Monitoring in Severe Traumatic Brain Injury: Results from the American College of Surgeons Trauma Quality Improvement Program

Alali

Fowler

Mainprize

et al. 2013

Journal of Neurotrauma

Self Cite

175

145

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“…4 Benchmarking, by comparing the predicted and observed outcome, is an important tool for trauma health care quality evaluation. 5 Such benchmarking has been shown to reduce mortality rates after cardiac and noncardiac surgery. 6 It has been suggested that by using newly developed robust prediction models in TBI, similar improvements in quality of care and outcome could be achieved.…”

Section: Introductionmentioning

confidence: 99%

Predicting Outcome after Traumatic Brain Injury: Development of Prognostic Scores Based on the IMPACT and the APACHE II

Raj

Siironen

Kivisaari

et al. 2014

Journal of Neurotrauma

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Prediction models are important tools for heterogeneity adjustment in clinical trials and for the evaluation of quality of delivered care to patients with traumatic brain injury (TBI). We sought to improve the predictive performance of the IMPACT (International Mission for Prognosis and Analysis of Clinical Trials) prognostic model by combining it with the APACHE II (Acute Physiology and Chronic Health Evaluation II) for 6-month outcome prediction in patients with TBI treated in the intensive care unit. A total of 890 patients with TBI admitted to a large urban level 1 trauma center in 2009-2012 comprised the study population. The IMPACT and the APACHE II scores were combined using binary logistic regression. A randomized, split-sample technique with secondary bootstrapping was used for model development and internal validation. Model performance was assessed by discrimination (by area under the curve [AUC]), calibration, precision, and net reclassification improvement (NRI). Overall 6-month mortality was 22% and unfavorable neurological outcome 47%. The predictive power of the new combined IMPACT-APACHE II models was significantly superior, compared to the original IMPACT models (AUC, 0.81-0.82 vs. 0.84-0.85; p < 0.05) for 6-month mortality prediction, but not for unfavorable outcome prediction (AUC, 0.81-0.82 vs. 0.83; p > 0.05). However, NRI showed a significant improvement in risk stratification of patients with unfavorable outcome by the IMPACT-APACHE II models, compared to the original models (NRI, 5.4-23.2%; p < 0.05). Internal validation using split-sample and resample bootstrap techniques yielded equivalent results, indicating low grade of overestimation. Our findings show that by combining the APACHE II with the IMPACT, improved 6-month outcome predictive performance is achieved. This may be applicable for heterogeneity adjustment in forthcoming TBI studies.

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“…19,23 Comparing the observed outcome with the expected outcome has been shown to be a feasible method for improving quality of trauma and intensive care. 22,[136][137][138][139] For example, the Trauma Audit & Research Network (TARN) in the UK annually presents casemix adjusted survival rates (oft en referred to as SMR for Standardized Mortality Rate) from their participating hospitals publicly at https://www.tarn.ac.uk/. Public comparisons of adjusted survival rates are, however, not without problems and it is important to know the limitation of such comparisons.…”

Section: Quality Auditsmentioning

confidence: 99%

Prognostic models in traumatic brain injury

Raj

2015

Acta Anaesthesiol Scand

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Background Prognostic models are important tools for heterogeneity adjustment in traumatic brain injury (TBI). Prognoses after TBI have been particularly challenging to predict, with limited availability of robust prognostic models. TBI patients are by definition trauma patients, and often treated in the intensive care unit (ICU). Several prognostic models for ICU and trauma patients have been developed, although their applicability in patients with TBI is uncertain. Recently, however, some new prognostic models specifically designed for patients with TBI were introduced. Still, the optimal type of prognostic model in TBI remains unknown. Aim This aims to investigate the applicability of different types of prognostic models in patients with TBI and to develop novel models with enhanced performance to previous models, focusing on long‐ term outcome prediction. Methods Four patient databases of patients with TBI treated in the ICU were used to validate three TBI specific models, two computerized tomography (CT) scoring systems, one trauma scoring system, and three intensive care scoring systems. Models were validated by assessing their discrimination using area under the curve (AUC), calibration, and explanatory variation. Logistic regression was used for model customization and development. Models were internally validated using a resample bootstrap technique or a split‐sample technique. Primary outcome was 6‐month mortality and unfavorable neurological outcome by the Glasgow Outcome Scale. 30‐day in‐hospital mortality was used for the trauma scoring system. Results Study populations ranged from 342 to 9915 patients. The TBI models showed the best performance with AUCs between 0.80 and 0.85, followed by the intensive care scoring systems and the CT scores with AUCs between 0.68 to 0.80 and 0.63 to 0.70, respectively. Most models showed poor calibration, although good calibration was achieved following customization. The trauma scoring system exhibited modest to good discrimination (AUC 0.76–0.89) for short‐term mortality prediction but poor calibration. Several new prognostic models, with statistically significant superior performance to previous models were created, among them a combined TBI‐ICU model (‘IMPACT‐APACHE’) and a novel CT scoring system (‘The Helsinki CT score’). Using a TBI‐specific model, based on admission characteristics, up to 40% of the patient's final long‐term outcome could be predicted. Conclusion The TBI models showed superior predictive performance to the intensive care and trauma scoring systems, showing that TBI patients are a highly specific population in the trauma and ICU setting. Thus, the use of a TBI‐specific model is advocated in the setting of TBI. The newly proposed models were found to be significant improvements over previous models, but require external validation to show generalizability.

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The Trauma Quality Improvement Program: Pilot Study and Initial Demonstration of Feasibility

Cited by 137 publications

References 13 publications

Intracranial Pressure Monitoring in Severe Traumatic Brain Injury: Results from the American College of Surgeons Trauma Quality Improvement Program

Intracranial Pressure Monitoring in Severe Traumatic Brain Injury: Results from the American College of Surgeons Trauma Quality Improvement Program

Predicting Outcome after Traumatic Brain Injury: Development of Prognostic Scores Based on the IMPACT and the APACHE II

Prognostic models in traumatic brain injury

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