Faculty of Social Welfare and Health Sciences, University of Haifa, Mount Carmel 31905, Israel.
BMC Public Health. 2011 Aug 1;11:609. doi: 10.1186/1471-2458-11-609.
The ability to accurately detect differential resource use between persons of different socioeconomic status relies on the accuracy of health-needs adjustment measures. This study tests different approaches to morbidity adjustment in explanation of health care utilization inequity.
A representative sample was selected of 10 percent (~270,000) adult enrolees of Clalit Health Services, Israel's largest health care organization. The Johns-Hopkins University Adjusted Clinical Groups® were used to assess each person's overall morbidity burden based on one year's (2009) diagnostic information. The odds of above average health care resource use (primary care visits, specialty visits, diagnostic tests, or hospitalizations) were tested using multivariate logistic regression models, separately adjusting for levels of health-need using data on age and gender, comorbidity (using the Charlson Comorbidity Index), or morbidity burden (using the Adjusted Clinical Groups). Model fit was assessed using tests of the Area Under the Receiver Operating Characteristics Curve and the Akaike Information Criteria.
Low socioeconomic status was associated with higher morbidity burden (1.5-fold difference). Adjusting for health needs using age and gender or the Charlson index, persons of low socioeconomic status had greater odds of above average resource use for all types of services examined (primary care and specialist visits, diagnostic tests, or hospitalizations). In contrast, after adjustment for overall morbidity burden (using Adjusted Clinical Groups), low socioeconomic status was no longer associated with greater odds of specialty care or diagnostic tests (OR: 0.95, CI: 0.94-0.99; and OR: 0.91, CI: 0.86-0.96, for specialty visits and diagnostic respectively). Tests of model fit showed that adjustment using the comprehensive morbidity burden measure provided a better fit than age and gender or the Charlson Index.
Identification of socioeconomic differences in health care utilization is an important step in disparity reduction efforts. Adjustment for health-needs using a comprehensive morbidity burden diagnoses-based measure, this study showed relative underutilization in use of specialist and diagnostic services, and thus allowed for identification of inequity in health resources use, which could not be detected with less comprehensive forms of health-needs adjustments.
准确检测不同社会经济地位人群之间的差异资源利用能力取决于健康需求调整措施的准确性。本研究测试了不同的发病率调整方法，以解释医疗保健利用不公平现象。
从以色列最大的医疗保健组织克拉利特健康服务的 10%（约 270,000 名）成年参保人中选择了一个代表性样本。根据 2009 年一年的诊断信息，使用约翰霍普金斯大学调整临床分组®评估每个人的整体发病负担。使用多变量逻辑回归模型分别调整年龄和性别、合并症（使用 Charlson 合并症指数）或发病负担（使用调整临床分组）的健康需求水平，检验高于平均医疗资源利用（初级保健就诊、专科就诊、诊断性检查或住院）的几率。使用接收者操作特征曲线下面积和 Akaike 信息准则的检验来评估模型拟合度。
低社会经济地位与更高的发病负担（差异为 1.5 倍）相关。使用年龄和性别或 Charlson 指数调整健康需求后，所有类型服务（初级保健和专科就诊、诊断性检查或住院）的低社会经济地位者资源利用高于平均水平的几率更高。相比之下，在调整总发病负担（使用调整临床分组）后，低社会经济地位与专科护理或诊断性检查的几率增加无关（OR：0.95，CI：0.94-0.99；和 OR：0.91，CI：0.86-0.96，分别用于专科就诊和诊断性检查）。模型拟合度检验表明，使用综合发病负担衡量标准进行调整比使用年龄和性别或 Charlson 指数提供了更好的拟合度。
识别医疗保健利用方面的社会经济差异是减少差异努力的重要一步。本研究使用综合发病负担基于诊断的措施调整健康需求，发现专科和诊断服务的相对利用不足，从而确定了卫生资源利用的不公平现象，这是使用不太全面的健康需求调整形式无法检测到的。
