Medizinische Universität Graz Austria/Österreich - Forschungsportal - Medical University of Graz
Gewählte Publikation:
Koch, T.
EVALUATION OF PROSPECTIVE COMPLICATION RECORDING IN RURAL SURGERY USING A STANDARDIZED CLASSIFICATION SYSTEM AS TOOL IN INTRAHOSPITAL QUALITY MANAGEMENT
Humanmedizin; [ Diplomarbeit ] Graz Medical University; 2015. pp.
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- Autor*innen der Med Uni Graz:
- Betreuer*innen:
- Bernhardt Gerwin
- Mischinger Hans-Jörg
- Altmetrics:
- Abstract:
- Introduction: Reporting complications is a part of every medical scientific investigation. The event considered being a complication varies thru out the studies. A complication classification such as the Clavien classification system allows transparent and objective comparing and interpreting of own complication rates with different surgeons, hospitals or with data from the literature. The hypothesis of this study was that the prospectively recording of complications with the system of Clavien leads to an improvement in patient’s care. Methods: We prospectively collected data about complications and classified them according to system of Clavien. We included all patients 6 years or older, who had a surgical intervention between 09/2005-12/2010 and stayed two or more hospital days. Data were statistically analysed with two-sided tests. A p-value of <0.05 was considered significant. Results: Two hundred and twenty five postoperative complications occurred in 3870 operations (5,8%). The average number of performed operations per year was 645±175. The mean age was 53±19 years. Patients over 80 years and male patients had a significant higher complication rate. The complication rate decreased from 8.5% in 2005 to 5.2% in 2010.The complication rate between the two residents did not differ significantly (5.3% vs. 5.4%). There was a great variance between the other surgeons ranging from 2.1% to 16.2%. Discussion: The prospectively recording of complications led to an improvement of postoperative complications over the years. The prospective recording of complication rate helped us to benchmarking our data, to reflect our results and to detect errors and so to improve patient’s care.