Behrendt Susann, Schwinger Antje, Tsiasioti Chrysanthi, Stieglitz Kai, Klauber Jürgen
Wissenschaftliches Institut der AOK (WIdO), Fachbereich Pflege, Berlin.
Wissenschaftliches Institut der AOK (WIdO), Geschäftsführung, Berlin.
Gesundheitswesen. 2020 Mar;82(S 01):S52-S61. doi: 10.1055/a-1057-8799. Epub 2020 Feb 4.
Although administrative data on health care in Germany are part of legal quality assurance in hospital care, they are not part of quality assessment in long-term care. However, claims data of German statutory health and long-term care insurance provide valuable information on outcome quality in nursing homes. Claims data-based quality measurement in nursing homes has hardly been researched and basic work in secondary data analysis is required. This involves the claims data linkage of both statutory health and long-term care insurance as well as new ways of operationalization for quality indicators and their risk adjustment for fair facility comparisons. Using the example of pressure ulcer (PU) occurrence in nursing homes, this study develops a claims data-based quality indicator and discusses potentials and methodological challenges.
The analysis is based on administrative data from eleven statutory health and long-term care insurance funds (AOK, 2015). The dataset covers 31% of German nursing homes. The operationalisation of PU acquired within the facility included ICD-10 diagnoses, and prescriptions on dressings. Relevance and validity of claims data on PU-specific aids were also checked in this context. Our risk adjustment strategy followed the one already established by the claims data-based QSR (Quality assurance of inpatient health-care). The Standardized Morbidity Ratio was based on logistic regression with robust standard errors.
In 2015, 7.2% of the nursing home residents had at least one PU incident within the facility. The outcome quality considerably varied between facilities. Overall, claims data-based measurement of PU occurrence as outcome quality indicator is feasible for inpatient long-term care and can contribute to transparency and evaluation of care in nursing homes. Information derived from an assessment of care dependency as well as within the amended legal quality assurance system for long-term care may offer new opportunities for routine data-based quality indicators in nursing homes.
尽管德国医疗保健的行政数据是医院护理法定质量保证的一部分，但它们并非长期护理质量评估的一部分。然而，德国法定健康保险和长期护理保险的理赔数据提供了有关养老院护理结果质量的宝贵信息。基于理赔数据的养老院质量测量研究较少，需要开展二次数据分析的基础工作。这涉及法定健康保险和长期护理保险的理赔数据链接，以及质量指标的新操作化方法及其风险调整，以便进行公平的机构比较。本研究以养老院压疮（PU）发生情况为例，开发了一个基于理赔数据的质量指标，并讨论了其潜力和方法学挑战。
分析基于来自11个法定健康保险和长期护理保险基金（AOK，2015年）的行政数据。该数据集覆盖了德国31%的养老院。设施内获得的PU的操作化包括国际疾病分类第10版（ICD-10）诊断和敷料处方。在此背景下，还检查了PU专用辅助器具理赔数据的相关性和有效性。我们的风险调整策略遵循基于理赔数据的住院医疗质量保证（QSR）已经确立的策略。标准化发病率基于具有稳健标准误的逻辑回归。
2015年，7.2%的养老院居民在设施内至少发生过一次压疮事件。各机构的护理结果质量差异很大。总体而言，基于理赔数据测量压疮发生率作为护理结果质量指标对于住院长期护理是可行的，并且有助于提高养老院护理的透明度和评估。从护理依赖评估以及修订后的长期护理法定质量保证系统中获得的信息，可能为基于常规数据的养老院质量指标提供新的机会。
