Development and validation of hospital "end-of-life" treatment intensity measures.
Development and validation of hospital "end-of-life" treatment intensity measures.
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DOI：
10.1097/mlr.0b013e3181993191
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发表时间：
2009-10
期刊：
影响因子：
3
通讯作者：
Angus DC
中科院分区：
文献类型：
--
作者：
Barnato AE;Farrell MH;Chang CC;Lave JR;Roberts MS;Angus DC
卫生保健利用率之间的死者越来越多地被用来作为衡量卫生保健效率，但基于死者的措施可能是有偏见的估计“垂死”的病人接受的护理。制定和验证医院“临终”治疗强度的新措施。回顾性队列研究，使用宾夕法尼亚州卫生保健成本控制理事会（PHC4）出院数据（2001年4月至2005年3月）和医疗保险和医疗补助服务中心（CMS）数据（1999年1月至2003年12月）。65岁及以上的患者入住宾夕法尼亚州174家急诊医院。临终入院（死亡者）和死亡概率高的入院患者中重症监护室（ICU）和生命维持治疗（LST）使用的医院特定标准化比率，以及患者在生命最后6个月内医院、ICU和医生的支出和使用。在死亡和高死亡概率入院的患者中，ICU和LST的使用存在显著的院间差异。所有住院死亡人数与高死亡概率指标高度相关（p <0.0001）。在主成分因子分析中，所有4个基于最近6个月队列的指标、基于死亡和高风险入院的ICU指标以及12个死亡和高死亡概率LST指标中的8个加载到单个因子中，解释了42%的数据变异。医院的临终关怀强度在使用特定的生命维持治疗方面有所不同，这些治疗在某种程度上象征着积极的临终关怀。寿命终了强度是一个相对稳定的医院属性，对多种测量方法具有鲁棒性。
Health care utilization among decedents is increasingly used as a measure of health care efficiency, but decedent-based measures may be biased estimates of care received by “dying” patients. To develop and validate new measures of hospital “end-of-life” treatment intensity. Retrospective cohort study using Pennsylvania Health Care Cost Containment Council (PHC4) discharge data (April 2001–March 2005) and Centers for Medicare and Medicaid Services (CMS) data (January 1999–December 2003). Patients 65 and older admitted to 174 Pennsylvania acute care hospitals. Hospital-specific standardized ratios of intensive care unit (ICU) and life-sustaining treatment (LST) use among terminal admissions (decedents) and admissions with a high probability of dying, and spending and use of hospitals, ICUs, and physicians among patients in their last 6 months of life. There was marked between-hospital variation in the use of the ICU and LSTs among decedents and admissions with high probability of dying. All hospital decedent and high probability of dying measures were highly correlated (p < 00001). In principal components factor analysis, all 4 of the last-6-months cohort-based measures, the decedent and high-risk admission-based ICU measures, and 8 of the 12 decedent and high probability of dying LST measures loaded onto a single factor, explaining 42% of the variation in the data. Hospitals’ end-of-life intensity varies in the use of specific life-sustaining treatments that are somewhat emblematic of aggressive end-of-life care. End-of-life intensity is a relatively stable hospital attribute that is robust to multiple measurement approaches.