Thygesen Lau C, Baixauli-Pérez Cristobal, Librero-López Julián, Martínez-Lizaga Natalia, Ridao-López Manuel, Bernal-Delgado Enrique
1 National Institute of Public Health, University of Southern Denmark, Copenhagen, Denmark.
2 Fundación para el Fomento de la Investigación Sanitaria y Biomédica de la Comunidad Valenciana (FISABIO), Valencia, Spain 3 Red de Investigación en Servicios de Salud en Enfermedades Crónicas (REDISSEC), Spain.
Eur J Public Health. 2015 Feb;25 Suppl 1:8-14. doi: 10.1093/eurpub/cku229.
In geographical studies, population distribution is a key issue. An unequal distribution across units of analysis might entail extra-variation and produce misleading conclusions on healthcare performance variations. This article aims at assessing the impact of building more homogeneous units of analysis in the estimation of systematic variation in three countries.
Hospital discharges for six conditions (congestive heart failure, short-term complications of diabetes, hip fracture, knee replacement, prostatectomy in prostate cancer and percutaneous coronary intervention) produced in Denmark, England and Portugal in 2008 and 2009 were allocated to both original geographical units and new ad hoc areas. New areas were built using Ward's minimum variance methods. The impact of the new areas on variability was assessed using Kernel distribution curves and different statistic of variation such as Extremal Quotient, Interquartile Interval ratio, Systematic Component of Variation and Empirical Bayes statistic.
Ward's method reduced the number of areas, allowing a more homogeneous population distribution, yet 20% of the areas in Portugal exhibited less than 100 000 inhabitants vs. 7% in Denmark and 5% in England. Point estimates for Extremal Quotient and Interquartile Interval Ratio were lower in the three countries, particularly in less prevalent conditions. In turn, the Systematic Component of Variation and Empirical Bayes statistic were slightly lower in more prevalent conditions.
Building new geographical areas produced a reduction of the variation in hospitalization rates in several prevalent conditions mitigating random noise, particularly in the smallest areas and allowing a sounder interpretation of the variation across countries.
在地理学研究中，人口分布是一个关键问题。分析单位间的不平等分布可能会带来额外的变异，并在医疗保健绩效差异方面得出误导性结论。本文旨在评估构建更同质化的分析单位对三个国家系统变异估计的影响。
将丹麦、英格兰和葡萄牙在2008年和2009年因六种病症（充血性心力衰竭、糖尿病短期并发症、髋部骨折、膝关节置换、前列腺癌前列腺切除术和经皮冠状动脉介入治疗）产生的医院出院病例分配到原始地理单位和新的特设区域。使用沃德最小方差法构建新区域。使用核分布曲线和不同的变异统计量（如极值商、四分位间距比、变异的系统成分和经验贝叶斯统计量）评估新区域对变异性的影响。
沃德方法减少了区域数量，使人口分布更趋同质化，但葡萄牙20%的区域居民少于10万，而丹麦为7%，英格兰为5%。三个国家的极值商和四分位间距比的点估计值较低，在发病率较低的病症中尤其如此。反过来，在发病率较高的病症中，变异的系统成分和经验贝叶斯统计量略低。
构建新的地理区域降低了几种常见病症住院率的变异，减轻了随机噪声，特别是在最小的区域，并能更合理地解释各国之间的变异。
