School of Public Health, Imperial College London, Norfolk Place, London, W2 1PG, UK.
BMC Health Serv Res. 2012 Apr 26;12:104. doi: 10.1186/1472-6963-12-104.
Reducing inequalities is one of the priorities of the National Health Service. However, there is no standard system for monitoring inequalities in the care provided by acute trusts. We explore the feasibility of monitoring inequalities within an acute trust using routine data.
A retrospective study of hospital episode statistics from one acute trust in London over three years (2007 to 2010). Waiting times, length of stay and readmission rates were described for seven common surgical procedures. Inequalities by age, sex, ethnicity and social deprivation were examined using multiple logistic regression, adjusting for the other socio-demographic variables and comorbidities. Sample size calculations were computed to estimate how many years of data would be ideal for this analysis.
This study found that even in a large acute trust, there was not enough power to detect differences between subgroups. There was little evidence of inequalities for the outcome and process measures examined, statistically significant differences by age, sex, ethnicity or deprivation were only found in 11 out of 80 analyses. Bariatric surgery patients who were black African or Caribbean were more likely than white patients to experience a prolonged wait (longer than 64 days, aOR = 2.47, 95% CI: 1.36-4.49). Following a coronary angioplasty, patients from more deprived areas were more likely to have had a prolonged length of stay (aOR = 1.66, 95% CI: 1.25-2.20).
This study found difficulties in using routine data to identify inequalities on a trust level. Little evidence of inequalities in waiting time, length of stay or readmission rates by sex, ethnicity or social deprivation were identified although some differences were identified which warrant further investigation. Even with three years of data from a large trust there was little power to detect inequalities by procedure. Data will therefore need to be pooled from multiple trusts to detect inequalities.
减少不平等是国家卫生服务体系的重点之一。然而，目前还没有用于监测急症信托机构所提供的护理服务中存在的不平等现象的标准系统。我们探索了使用常规数据在急症信托机构内监测不平等现象的可行性。
对伦敦一家急症信托机构三年（2007 年至 2010 年）的医院入院统计数据进行回顾性研究。描述了七种常见手术的等待时间、住院时间和再入院率。使用多因素逻辑回归分析了年龄、性别、种族和社会贫困程度的不平等情况，并对其他社会人口学变量和合并症进行了调整。计算了样本量计算，以估计进行这种分析需要多少年的数据。
本研究发现，即使在大型急症信托机构中，也没有足够的能力来检测亚组之间的差异。在所检查的结果和过程措施方面，几乎没有不平等的证据，只有 11 项分析中发现年龄、性别、种族或贫困程度存在统计学显著差异。与白人患者相比，接受肥胖症手术的黑人或加勒比裔患者等待时间更长（超过 64 天，优势比=2.47，95%置信区间：1.36-4.49）。接受经皮冠状动脉介入治疗后，来自贫困地区的患者住院时间更长（优势比=1.66，95%置信区间：1.25-2.20）。
本研究发现，使用常规数据在信托级别上识别不平等现象存在困难。尽管发现了一些差异，但没有发现性别、种族或社会贫困程度在等待时间、住院时间或再入院率方面存在不平等的证据，这些差异需要进一步调查。即使使用了来自大型信托机构的三年数据，检测程序之间的差异的能力也很有限。因此，需要从多个信托机构汇集数据以检测不平等现象。
