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Zusammenhang zwischen Letalität und Patientenmindestmenge an deutschen Traumazentren. eine Analyse des TraumaRegisters DGU®
Zusammenhang zwischen Letalität und Patientenmindestmenge an deutschen Traumazentren. eine Analyse des TraumaRegisters DGU®
Background: The American College of Surgeons Committee on Trauma (ACS COT) requires at least 240 patients per year with an injury severity score (ISS) ≥16 for level-I trauma centres. In Germany, the issue of patient volume is discussed controversially. The aim was to find out, whether there is an effect of patient volume on mortality? Methods: Retrospective study. Analysis of the TraumaRegister DGU® Inclusion criteria were: trauma patients within Germany, ISS≥16. Patients transferred early were excluded. Descriptive data and outcome analysis (observed vs. expected mortality obtained by revised injury severity classification score, RISC-II) and logistic regression was performed (2009-13). Results: 39,289 patients met the inclusion criteria. Mean age was 49.9±21.8 years, 71.3% were male, mean ISS was 27.2±11.6 and 29.2% had a Glasgow come scale (GCS)<8. Of 587 hospitals, 98 were level-I, 235 level-II and 254 level-III trauma centres. Within the subgroups with 40-59, 60-79 or 80-99 patients per year, the observed vs. expected mortality did not differ significantly (p>0.05). Within the subgroups with 1-19 and 20-39 patients per year, the observed mortality was significantly above the predicted mortality (p<0.05). There was a trend in the difference of observed and predicted outcome of about 1% between very low and very high volume hospitals in favour of high patient volume. Adjusted logistic regression analysis showed that patient volume is an independent and significant positive predictor of survival (odds ratio=OR 1.001 per case per year, p=0.005). Even when adjusted for hospital levels, patient volume remained a stable and robust positive predictor of survival. Conclusion: Overall, high patient volume is an independent, significant and positive predictor of survival. Based on these findings, a clear cut-off value could not be detected. However, it seems that ≥40 patients per year per hospital might be beneficial for an increased survival. High volume hospitals have an absolute difference of observed vs. predicted mortality of about +1% survival benefit compared to low volume hospitals.
Trauma, major trauma, patient volume, case load, severely injured, polytrauma, RISC-II, mortality, outcome
Zacher, Martina
2016
Deutsch
Universitätsbibliothek der Ludwig-Maximilians-Universität München
Zacher, Martina (2016): Zusammenhang zwischen Letalität und Patientenmindestmenge an deutschen Traumazentren: eine Analyse des TraumaRegisters DGU®. Dissertation, LMU München: Medizinische Fakultät
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Abstract

Background: The American College of Surgeons Committee on Trauma (ACS COT) requires at least 240 patients per year with an injury severity score (ISS) ≥16 for level-I trauma centres. In Germany, the issue of patient volume is discussed controversially. The aim was to find out, whether there is an effect of patient volume on mortality? Methods: Retrospective study. Analysis of the TraumaRegister DGU® Inclusion criteria were: trauma patients within Germany, ISS≥16. Patients transferred early were excluded. Descriptive data and outcome analysis (observed vs. expected mortality obtained by revised injury severity classification score, RISC-II) and logistic regression was performed (2009-13). Results: 39,289 patients met the inclusion criteria. Mean age was 49.9±21.8 years, 71.3% were male, mean ISS was 27.2±11.6 and 29.2% had a Glasgow come scale (GCS)<8. Of 587 hospitals, 98 were level-I, 235 level-II and 254 level-III trauma centres. Within the subgroups with 40-59, 60-79 or 80-99 patients per year, the observed vs. expected mortality did not differ significantly (p>0.05). Within the subgroups with 1-19 and 20-39 patients per year, the observed mortality was significantly above the predicted mortality (p<0.05). There was a trend in the difference of observed and predicted outcome of about 1% between very low and very high volume hospitals in favour of high patient volume. Adjusted logistic regression analysis showed that patient volume is an independent and significant positive predictor of survival (odds ratio=OR 1.001 per case per year, p=0.005). Even when adjusted for hospital levels, patient volume remained a stable and robust positive predictor of survival. Conclusion: Overall, high patient volume is an independent, significant and positive predictor of survival. Based on these findings, a clear cut-off value could not be detected. However, it seems that ≥40 patients per year per hospital might be beneficial for an increased survival. High volume hospitals have an absolute difference of observed vs. predicted mortality of about +1% survival benefit compared to low volume hospitals.