Clinical audit indicators of outcome following admission to hospital with acute exacerbation of chronic obstructive pulmonary disease
Clinical audit indicators of outcome following admission to hospital with acute exacerbation of chronic obstructive pulmonary disease
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DOI：
10.1136/thorax.57.2.137
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发表时间：
2002-02-01
期刊：
影响因子：
10
通讯作者：
Pearson, MG
中科院分区：
文献类型：
--
作者：
Roberts, CM;Lowe, D;Pearson, MG
背景资料：1997年BTS/RCP对急性慢性阻塞性肺疾病（COPD）的护理过程进行了国家审计。本文描述了从相同的情况下，死亡的结果，再入院率在3个月内首次入院，和住院时间。结果的主要入院前预测因素的识别可用于控制混杂因素的人口特征时，比较性能之间的units.Methods：74个变量的数据进行了回顾性收集使用审计形式从英国医院收治的急性COPD患者。三个结果的措施，确定了重要的预后变量的相对风险和Logistic回归被用来放置这些在为了预测value.Results：1400从38急性医院入院整理。14%的病例在入院后3个月内死亡，医院之间的差异为0- 50%。体力状态差、酸中毒和腿部水肿是死亡的最佳独立预测因素。年龄在65岁以上、体力状态差、第一秒最低用力呼气量（FEV（1））三分位数是住院时间（中位数8天）的最佳预测因素。34%的患者再入院（范围5-65%）;最低FEV（1）三分位数，以前的入院，再入院与五个或更多的药物是最好的predictors for recommissation.Conclusions：重要的预测结果已被确定和正式记录这些可能有助于占混杂患者的特点时，医院之间的比较。医院之间的结果仍然存在很大差异，这些因素仍然无法解释。虽然这种差异可能是由于数据记录不完整或尚未确定的患者因素造成的，但以前确定的护理过程中的缺陷似乎可能是某些单位结果不佳的原因。
Background: The 1997 BTS/RCP national audit of acute chronic obstructive pulmonary disease (COPD) in terms of process of care has previously been reported. This paper describes from the same cases the outcomes of death, readmission rates within 3 months of initial admission, and length of stay. Identification of the main pre-admission predictors of outcome may be used to control for confounding factors in population characteristics when comparing performance between units.Methods: Data on 74 variables were collected retrospectively using an audit proforma from patients admitted to UK hospitals with acute COPD. Important prognostic variables for the three outcome measures were identified by relative risk and logistic regression was used to place these in order of predictive value.Results: 1400 admissions from 38 acute hospitals were collated. 14% of cases died within 3 months of admission with variation between hospitals of 0-50%. Poor performance status, acidosis, and the presence of leg oedema were the best significant independent predictors of death. Age above 65, poor performance status, and lowest forced expiratory volume in I second (FEV(1)) tertile were the best predictors of length of stay (median 8 days). 34% of patients were readmitted (range 5-65%); lowest FEV(1) tertile, previous admission, and readmission with five or more medications were the best predictors for readmission.Conclusions: Important predictors of outcome have been identified and formal recording of these may assist in accounting for confounding patient characteristics when making comparisons between hospitals. There is still wide variation in outcome between hospitals that remains unexplained by these factors. While some of this variance may be explained by incomplete recording of data or patient factors as yet unidentified, it seems likely that deficiencies in the process of care previously identified are responsible for poor outcomes in some units.