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Published on: September 16, 2022
Risk-adjustment models for clean and colorectal surgery surgical site infection for the Spanish health system
Daniel Angel García1, Ismael Martínez Nicolás1, José Andrés García Marín2
1Departamento de Fisioterapia, Facultad de Ciencias de la Salud, Universidad Católica San Antonio de Murcia, Murcia 30009, Spain.
Objective:
To develop risk-adjusted models for two quality indicators addressing surgical site infection (SSI) in clean and colorectal surgery, to be used for benchmarking and quality improvement in the Spanish National Health System.
Study Design:
A literature review was undertaken to identify candidate adjustment variables. The candidate variables were revised by clinical experts to confirm their clinical relevance to SSI; experts also offered additional candidate variables that were not identified in the literature review. Two risk-adjustment models were developed using multiple logistic regression thus allowing calculation of the adjusted indicator rates.
Data Source:
The two SSI indicators, with their corresponding risk-adjustment models, were calculated from administrative databases obtained from nine public hospitals. A dataset was obtained from a 10-year period (2006-2015), and it included data from 21 571 clean surgery patients and 6325 colorectal surgery patients.
Analysis Methods:
Risk-adjustment regression models were constructed using Spanish National Health System data. Models were analysed so as to prevent overfitting, then tested for calibration and discrimination and finally bootstrapped.
Results:
Ten adjustment variables were identified for clean surgery SSI, and 23 for colorectal surgery SSI. The final adjustment models showed fair calibration (Hosmer-Lemeshow: clean surgery χ2 = 6.56, P = 0.58; colorectal surgery χ2 = 6.69, P = 0.57) and discrimination (area under receiver operating characteristic [ROC] curve: clean surgery 0.72, 95% confidence interval [CI] 0.67-0.77; colorectal surgery 0.62, 95% CI 0.60-0.65).
Conclusions:
The proposed risk-adjustment models can be used to explain patient-based differences among healthcare providers. They can be used to adjust the two proposed SSI indicators.
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