PDF(Pubmed)
Abstract：
UNASSIGNED: 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.
UNASSIGNED: 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.
UNASSIGNED: 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 [AUC = 0.748 (95% CI: 0.742; 0.752) for 90-day mortality; AUC = 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 (R 2 = 0.242 and R 2 = 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, p = 0.99; RSMR: ρ = 0.017, p = 0.56; reliability-adjusted RSMR: ρ = 0.067; p = 0.026).
UNASSIGNED: 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.
UNASSIGNED: 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.
UNASSIGNED: 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 [AUC = 0.748 (95% CI: 0.742; 0.752) for 90-day mortality; AUC = 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 (R 2 = 0.242 and R 2 = 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, p = 0.99; RSMR: ρ = 0.017, p = 0.56; reliability-adjusted RSMR: ρ = 0.067; p = 0.026).
UNASSIGNED: 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.
摘要：
未经证实：目前尚缺乏评估脓毒症急性治疗长期结局质量的方法。我们研究了一种基于德国健康声明数据的长期结果质量测量方法。
UASSIGNED：分析基于德国最大的健康保险公司的数据，覆盖了32%的人口。包括2014年住院的根据脓毒症-1定义的严重脓毒症或脓毒性休克的ICD-10编码的病例（15岁及以上）。通过90天死亡率评估短期结局；通过复合终点评估长期结局，复合终点定义为1年死亡率或对慢性护理的依赖性增加。通过逆向选择的逻辑回归确定风险因素。分层广义线性模型用于校正医院中的病例聚类。通过使用自举抽样的内部验证来评估模型的预测有效性。在有和没有可靠性调整的情况下计算风险标准化死亡率（RSMR），并描述了它们的单变量和双变量分布。
未经证实：在35,552名患者中，53.2%在入院后90天内死亡；39.8%的90天幸存者在第一年内死亡或对慢性护理的依赖性增加。两种风险模型都显示出足够的关于歧视的预测有效性[AUC=0.748（95％CI：0.742;0.752）对于90天死亡率；AUC=0.675（95％CI：0.665;0.685）对于1年综合结局，分别]，校准（Brier评分为0.203和0.220；校准斜率为1.094和0.978），并解释了方差(R2=0.242和R2=0.111)。因为每家医院的病例量很小，对RSMR应用可靠性调整导致各医院的变异性大大降低[从中位数(第一四分位数，第三四分位数）54.2%（44.3%，65.5%）至53.2%（50.7%，90天死亡率为55.9％；从39.2％（27.8％，51.1%）至39.9%（39.5%，40.4%）为1年综合终点]。医院水平的两个终点之间没有实质性相关性（观察率：ρ=0，p=0.99；RSMR：ρ=0.017，p=0.56；可靠性调整RSMR：ρ=0.067；p=0.026）。
UNASSIGNED：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的指标。基于索赔的急性脓毒症护理质量指标的风险调整模型显示出令人满意的预测有效性。为了提高测量的可靠性，数据源应覆盖全部人群,医院需要改进脓毒症的ICD-10编码.
UASSIGNED：分析基于德国最大的健康保险公司的数据，覆盖了32%的人口。包括2014年住院的根据脓毒症-1定义的严重脓毒症或脓毒性休克的ICD-10编码的病例（15岁及以上）。通过90天死亡率评估短期结局；通过复合终点评估长期结局，复合终点定义为1年死亡率或对慢性护理的依赖性增加。通过逆向选择的逻辑回归确定风险因素。分层广义线性模型用于校正医院中的病例聚类。通过使用自举抽样的内部验证来评估模型的预测有效性。在有和没有可靠性调整的情况下计算风险标准化死亡率（RSMR），并描述了它们的单变量和双变量分布。
未经证实：在35,552名患者中，53.2%在入院后90天内死亡；39.8%的90天幸存者在第一年内死亡或对慢性护理的依赖性增加。两种风险模型都显示出足够的关于歧视的预测有效性[AUC=0.748（95％CI：0.742;0.752）对于90天死亡率；AUC=0.675（95％CI：0.665;0.685）对于1年综合结局，分别]，校准（Brier评分为0.203和0.220；校准斜率为1.094和0.978），并解释了方差(R2=0.242和R2=0.111)。因为每家医院的病例量很小，对RSMR应用可靠性调整导致各医院的变异性大大降低[从中位数(第一四分位数，第三四分位数）54.2%（44.3%，65.5%）至53.2%（50.7%，90天死亡率为55.9％；从39.2％（27.8％，51.1%）至39.9%（39.5%，40.4%）为1年综合终点]。医院水平的两个终点之间没有实质性相关性（观察率：ρ=0，p=0.99；RSMR：ρ=0.017，p=0.56；可靠性调整RSMR：ρ=0.067；p=0.026）。
UNASSIGNED：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的指标。基于索赔的急性脓毒症护理质量指标的风险调整模型显示出令人满意的预测有效性。为了提高测量的可靠性，数据源应覆盖全部人群,医院需要改进脓毒症的ICD-10编码.
