Integrated Research and Treatment Center-Center for Sepsis Control and Care, Jena University Hospital, Jena, Germany.
Department of Anesthesiology and Intensive Care Medicine, Jena University Hospital, Jena, Germany.
PLoS One. 2018 Mar 20;13(3):e0194371. doi: 10.1371/journal.pone.0194371. eCollection 2018.
Sepsis is a major cause of preventable deaths in hospitals. Feasible and valid methods for comparing quality of sepsis care between hospitals are needed. The aim of this study was to develop a risk-adjustment model suitable for comparing sepsis-related mortality between German hospitals.
We developed a risk-model using national German claims data. Since these data are available with a time-lag of 1.5 years only, the stability of the model across time was investigated. The model was derived from inpatient cases with severe sepsis or septic shock treated in 2013 using logistic regression with backward selection and generalized estimating equations to correct for clustering. It was validated among cases treated in 2015. Finally, the model development was repeated in 2015. To investigate secular changes, the risk-adjusted trajectory of mortality across the years 2010-2015 was analyzed.
The 2013 deviation sample consisted of 113,750 cases; the 2015 validation sample consisted of 134,851 cases. The model developed in 2013 showed good validity regarding discrimination (AUC = 0.74), calibration (observed mortality in 1st and 10th risk-decile: 11%-78%), and fit (R2 = 0.16). Validity remained stable when the model was applied to 2015 (AUC = 0.74, 1st and 10th risk-decile: 10%-77%, R2 = 0.17). There was no indication of overfitting of the model. The final model developed in year 2015 contained 40 risk-factors. Between 2010 and 2015 hospital mortality in sepsis decreased from 48% to 42%. Adjusted for risk-factors the trajectory of decrease was still significant.
The risk-model shows good predictive validity and stability across time. The model is suitable to be used as an external algorithm for comparing risk-adjusted sepsis mortality among German hospitals or regions based on administrative claims data, but secular changes need to be taken into account when interpreting risk-adjusted mortality.
败血症是医院中可预防死亡的主要原因。需要找到可行且有效的方法来比较医院之间败血症治疗的质量。本研究旨在开发一种适合于比较德国医院之间败血症相关死亡率的风险调整模型。
我们使用全国性德国索赔数据开发了一种风险模型。由于这些数据只能延迟 1.5 年获得，因此我们研究了模型在时间上的稳定性。该模型是使用逻辑回归和广义估计方程从 2013 年接受严重败血症或败血症性休克治疗的住院病例中得出的，使用向后选择进行回归，并进行聚类校正。然后在 2015 年接受治疗的病例中进行验证。最后，在 2015 年重复进行模型开发。为了研究长期趋势，我们分析了 2010-2015 年期间死亡率的风险调整轨迹。
2013 年的偏差样本包括 113750 例病例；2015 年的验证样本包括 134851 例病例。2013 年开发的模型在区分度（AUC = 0.74）、校准（第 1 和第 10 个风险分类的观察死亡率：11%-78%）和拟合度（R2 = 0.16）方面均表现良好。当将该模型应用于 2015 年时，其有效性仍然稳定（AUC = 0.74，第 1 和第 10 个风险分类：10%-77%，R2 = 0.17）。该模型不存在过拟合的迹象。2015 年最终开发的模型包含 40 个风险因素。2010 年至 2015 年间，败血症患者的医院死亡率从 48%下降至 42%。调整风险因素后，死亡率下降的趋势仍然显著。
该风险模型具有良好的预测有效性和时间稳定性。该模型适用于使用行政索赔数据比较德国医院或地区之间风险调整后的败血症死亡率，但在解释风险调整后的死亡率时需要考虑长期趋势。
