Frank Janina
National Association of Statutory Health Insurance Physicians, Department of Health-Based Risk Adjusted Payment, Herbert-Lewin-Platz 2, 10623 Berlin, Germany.
Health Policy. 2016 Sep;120(9):1061-9. doi: 10.1016/j.healthpol.2016.07.008. Epub 2016 Jul 18.
Coded diagnoses in claims data offer a comprehensive basis for health sciences and health policy decisions. For example, morbidity-based risk adjustment schemes use coded diagnoses to allocate resources. Therefore a routinely performed validation is important. Data reconciliation with medical records would be first best, but is not possible here. This paper validates population-based prevalences of hypertension and depression based on claims data by comparing them with prevalences stem from two different epidemiological survey data.
Data sources accessible are a nationwide sample based on outpatient claims data (GSPR), a nationwide health interview and examination survey (DEGS1) and a nationwide telephone interview survey (GEDA). The analysis includes SHI-insured aged 18-79 who live in 2010 in Germany.
There was high agreement for hypertension prevalences between GSPR (28.98% [28.95-29.02]) and DEGS1 (28.0% [26.5-29.5]) but not with GEDA (22.9% [22.1-23.7]). The agreement for depression prevalences was high between the two surveys (DEGS1: 7.6% [6.7-8.5] and GEDA: 6.7% [6.3-7.2]) and moderate compared to GSPR (12.23% [12.21-12.26]).
For an objectifiable disease, such as hypertension, diagnostic coding with claims data seems to be valid to be used for risk adjustment in German outpatient health care. Even though depression prevalences differ between claims data and survey data, more effort is required to understand the magnitude of a reference systems impact on prevalence estimates.
理赔数据中的编码诊断为健康科学和健康政策决策提供了全面依据。例如,基于发病率的风险调整方案利用编码诊断来分配资源。因此,常规进行的验证很重要。与病历进行数据核对是最佳方法,但此处无法做到。本文通过将基于理赔数据得出的高血压和抑郁症人群患病率与来自两项不同流行病学调查数据的患病率进行比较,对其进行验证。
可获取的数据源包括基于门诊理赔数据的全国性样本(GSPR)、全国性健康访谈与检查调查(DEGS1)以及全国性电话访谈调查(GEDA)。分析对象为2010年居住在德国的18 - 79岁法定医疗保险参保人。
GSPR(28.98% [28.95 - 29.02])与DEGS1(28.0% [26.5 - 29.5])之间的高血压患病率一致性较高,但与GEDA(22.9% [22.1 - 23.7])不一致。两项调查(DEGS1:7.6% [6.7 - 8.5]和GEDA:6.7% [6.3 - 7.2])之间的抑郁症患病率一致性较高,与GSPR(12.23% [12.21 - 12.26])相比为中等程度。
对于像高血压这样可客观化的疾病,在德国门诊医疗中,利用理赔数据进行诊断编码似乎可有效用于风险调整。尽管理赔数据和调查数据中的抑郁症患病率有所不同,但仍需要更多努力来了解参考系统对患病率估计的影响程度。