Wedekind Lisa, Fleischmann-Struzek Carolin, Rose Norman, Spoden Melissa, Günster Christian, Schlattmann Peter, Scherag André, Reinhart Konrad, Schwarzkopf Daniel
Institute of Medical Statistics, Computer and Data Sciences, Jena University Hospital, Jena, Germany.
Institute for Infectious Diseases and Infection Control, Jena University Hospital, Jena, Germany.
Front Med (Lausanne). 2023 Jan 9;9:1069042. doi: 10.3389/fmed.2022.1069042. eCollection 2022.
Methods for assessing long-term outcome quality of acute care for sepsis are lacking. We investigated a method for measuring long-term outcome quality based on health claims data in Germany.
Analyses were based on data of the largest German health insurer, covering 32% of the population. Cases (aged 15 years and older) with ICD-10-codes for severe sepsis or septic shock according to sepsis-1-definitions hospitalized in 2014 were included. Short-term outcome was assessed by 90-day mortality; long-term outcome was assessed by a composite endpoint defined by 1-year mortality or increased dependency on chronic care. Risk factors were identified by logistic regressions with backward selection. Hierarchical generalized linear models were used to correct for clustering of cases in hospitals. Predictive validity of the models was assessed by internal validation using bootstrap-sampling. Risk-standardized mortality rates (RSMR) were calculated with and without reliability adjustment and their univariate and bivariate distributions were described.
Among 35,552 included patients, 53.2% died within 90 days after admission; 39.8% of 90-day survivors died within the first year or had an increased dependency on chronic care. Both risk-models showed a sufficient predictive validity regarding discrimination [ = 0.748 (95% CI: 0.742; 0.752) for 90-day mortality; = 0.675 (95% CI: 0.665; 0.685) for the 1-year composite outcome, respectively], calibration (Brier Score of 0.203 and 0.220; calibration slope of 1.094 and 0.978), and explained variance ( = 0.242 and = 0.111). Because of a small case-volume per hospital, applying reliability adjustment to the RSMR led to a great decrease in variability across hospitals [from median (1st quartile, 3rd quartile) 54.2% (44.3%, 65.5%) to 53.2% (50.7%, 55.9%) for 90-day mortality; from 39.2% (27.8%, 51.1%) to 39.9% (39.5%, 40.4%) for the 1-year composite endpoint]. There was no substantial correlation between the two endpoints at hospital level (observed rates: ρ = 0, = 0.99; RSMR: ρ = 0.017, = 0.56; reliability-adjusted RSMR: ρ = 0.067; = 0.026).
Quality assurance and epidemiological surveillance of sepsis care should include indicators of long-term mortality and morbidity. Claims-based risk-adjustment models for quality indicators of acute sepsis care showed satisfactory predictive validity. To increase reliability of measurement, data sources should cover the full population and hospitals need to improve ICD-10-coding of sepsis.
目前缺乏评估脓毒症急性护理长期结局质量的方法。我们研究了一种基于德国健康保险数据来衡量长期结局质量的方法。
分析基于德国最大的健康保险公司的数据,该数据覆盖了32%的人口。纳入了2014年因符合脓毒症-1定义而使用国际疾病分类第十版(ICD-10)编码诊断为严重脓毒症或脓毒性休克的15岁及以上患者。短期结局通过90天死亡率进行评估;长期结局通过由1年死亡率或对长期护理的依赖性增加所定义的复合终点进行评估。通过逐步后退选择的逻辑回归确定危险因素。使用分层广义线性模型校正医院内病例的聚集情况。通过自助抽样的内部验证评估模型的预测效度。计算有和没有可靠性调整的风险标准化死亡率(RSMR),并描述其单变量和双变量分布。
在35552名纳入患者中,53.2%在入院后90天内死亡;90天幸存者中有39.8%在第一年内死亡或对长期护理的依赖性增加。两个风险模型在区分度方面均显示出足够的预测效度[90天死亡率的C统计量=0.748(95%CI:0.742;0.752);1年复合结局的C统计量=0.675(95%CI:0.665;0.685)]、校准度(Brier评分分别为0.203和0.220;校准斜率分别为1.094和0.978)以及解释方差(分别为0.242和0.111)。由于每家医院的病例数较少,对RSMR应用可靠性调整导致各医院间的变异性大幅降低[90天死亡率从中位数(第1四分位数,第3四分位数)54.2%(44.3%,65.5%)降至53.2%(50.7%,55.9%);1年复合终点从39.2%(27.8%,51.1%)降至39.9%(39.5%,40.4%)]。在医院层面,两个终点之间没有显著相关性(观察率:ρ=0,P=0.99;RSMR:ρ=0.017,P=0.56;可靠性调整后的RSMR:ρ=0.067;P=0.026)。
脓毒症护理的质量保证和流行病学监测应包括长期死亡率和发病率指标。基于保险理赔的急性脓毒症护理质量指标风险调整模型显示出令人满意的预测效度。为提高测量的可靠性,数据来源应覆盖全部人群,且医院需要改进脓毒症的ICD-10编码。