Aragon Health Sciences Institute (I + CS), Zaragoza, Spain.
BMC Public Health. 2010 May 11;10:244. doi: 10.1186/1471-2458-10-244.
The computerisation of primary health care (PHC) records offers the opportunity to focus on pharmacy expenditure from the perspective of the morbidity of individuals. The objective of the present study was to analyse the behaviour of pharmacy expenditure within different morbidity groups. We paid special attention to the identification of individuals who had higher values of pharmacy expenditure than their morbidity would otherwise suggest (i.e. outliers).
Observational study consisting of 75,574 patients seen at PHC centres in Zaragoza, Spain, at least once in 2005. Demographic and disease variables were analysed (ACG 8.1), together with a response variable that we termed 'total pharmacy expenditure per patient'. Outlier patients were identified based on boxplot methods, adjusted boxplot for asymmetric distributions, and by analysing standardised residuals of tobit regression models.
The pharmacy expenditure of up to 7% of attendees in the studied PHC centres during one year exceeded expectations given their morbidity burden. This group of patients was responsible for up to 24% of the total annual pharmacy expenditure. There was a significantly higher number of outlier patients within the low-morbidity band which matched up with the higher variation coefficient observed in this group (3.2 vs. 2.0 and 1.3 in the moderate- and high-morbidity bands, respectively).
With appropriate validation, the methodologies of the present study could be incorporated in the routine monitoring of the prescribing profile of general practitioners. This could not only enable evaluation of their performance, but also target groups of outlier patients and foster analyses of the causes of unusually high pharmacy expenditures among them. This interpretation of pharmacy expenditure gives new clues for the efficiency in utilisation of healthcare resources, and could be complementary to management interventions focused on individuals with a high morbidity burden.
基层医疗保健（PHC）记录的计算机化提供了从个体发病角度关注药房支出的机会。本研究的目的是分析不同发病群体中药房支出的行为。我们特别关注识别那些药房支出值高于其发病所暗示的值（即异常值）的个体。
这是一项观察性研究，包括 2005 年在西班牙萨拉戈萨的 PHC 中心至少就诊过一次的 75574 名患者。分析了人口统计学和疾病变量（ACG 8.1），以及我们称之为“每位患者的总药房支出”的因变量。异常值患者的识别基于箱线图方法、非对称分布的调整箱线图以及分析 tobit 回归模型的标准化残差。
在一年中，研究的 PHC 中心中多达 7%的就诊者的药房支出超出了其发病负担所预期的水平。这组患者占总年度药房支出的 24%。在低发病组中，异常值患者的数量明显更多，与该组观察到的更高变异系数相匹配（分别为 3.2、2.0 和 1.3）。
在适当验证的情况下，本研究的方法可以纳入全科医生处方概况的常规监测。这不仅可以评估他们的表现，还可以针对异常高的药房支出患者群体进行分析，并找出其中异常高药房支出的原因。这种对药房支出的解释为利用医疗资源的效率提供了新的线索，并可以补充以高发病负担个体为重点的管理干预措施。
