March Stefanie, Zimmermann Linda, Kubat Denise, Neumann Anne, Schmitt Jochen, Baum Fabian, Schoffer Olaf, Arnold Katrin, Seifert Martin, Kliemt Roman, Häckl Dennis, Pfennig Andrea, Swart Enno
Medizinische Fakultät, Institut für Sozialmedizin und Gesundheitssystemforschung, Otto-von-Guericke-Universität Magdeburg, Magdeburg.
Zentrum für Evidenzbasierte Gesundheitsversorgung, Universitätsklinikum Carl Gustav Carus an der Technischen Universität Dresden, Dresden.
Gesundheitswesen. 2020 Mar;82(S 01):S4-S12. doi: 10.1055/a-1036-6364. Epub 2020 Jan 21.
The adequate and need-based medical care of mentally ill patients places special demands on psychiatric care. The §64b Social Code Book (SGB) V enables mentoring mentally ill people through multiprofessional, cross-sectoral model projects across the treatment phase and implementing new forms of financing. These model projects have been evaluated in a prospective and retrospective claims data-based controlled cohort study (EVA64) since 2015.
In September 2016 and since then annually, the data transfer of all statutory health insurance funds (SHI) involved in this evaluation took place for the first time on the basis of a consented data set description. For later analysis, the clear identification of the index hospital admission and the assignment to the model or control group are important. The methodological challenges of data provision by the data owner, the formal and content-related data preparation as well as the subsequent establishing of an evaluation data set are discussed in detail.
So far, data from 71 SHI has been taken into account. In each case 20 tables with claims data from outpatient and inpatient care (including psychiatric institute outpatient departments [PIA]), drug and medical supplies as well as data from incapacity to work and personal data of the insurees. Not all tables could be filled completely by the SHIs. In addition, updates of the study designs require the adaptation of the data selection process. Even though data sets have been delievered regularly the data preparation process is still not routine.
The scientific use of claims data of numerous SHIs in the context of an evaluation study represents a great challenge. In the absence of reference values for abnormalities and implausibilities, an a priori determination of test algorithms was limited; instead they had to be updated every year. The individual examination of the data of all health insurance companies remains very complex. The detailed documentation of these algorithms provides support for future comparable studies.
为精神疾病患者提供充分且基于需求的医疗护理对精神科护理提出了特殊要求。《社会法典》第五编第64b条使通过跨治疗阶段的多专业、跨部门示范项目指导精神疾病患者并实施新的融资形式成为可能。自2015年以来，这些示范项目已在一项基于前瞻性和回顾性理赔数据的对照队列研究（EVA64）中得到评估。
2016年9月及此后每年，参与该评估的所有法定健康保险基金（SHI）首次根据商定的数据集描述进行数据传输。为便于后续分析，明确识别索引医院入院情况并将其分配至示范组或对照组很重要。详细讨论了数据所有者提供数据的方法挑战、形式和内容相关的数据准备以及随后建立评估数据集的问题。
到目前为止，已考虑来自71个SHI的数据。每种情况下都有20张表，包含门诊和住院护理（包括精神病院门诊部[PIA]）的理赔数据、药品和医疗用品以及投保人的工作能力丧失数据和个人数据。并非所有表格都能由SHI完全填写。此外研究设计的更新需要调整数据选择过程。尽管数据集已定期交付，但数据准备过程仍未常规化。
在评估研究中科学使用众多SHI的理赔数据是一项巨大挑战。由于缺乏异常和不合理情况的参考值，测试算法的先验确定受到限制；相反，它们必须每年更新。对所有健康保险公司的数据进行单独检查仍然非常复杂。这些算法的详细记录为未来的可比研究提供了支持。
