医保等行政管理数据确定慢性病洗脱期最佳策略的系统综述
A systematic review of optimal strategies for identifying chronic disease washout period with administrative data like insurance data
当使用医疗保险等行政管理数据时，为正确确定反复就医的慢性病新发病时点，研究者尝试使用洗脱期为基础确定新发病例。本文系统地检索了在PubMed、Web of science、Embase、中国知网、维普、万方数据库中从建库至2022年10月1日发表的所有利用行政管理数据探究慢性疾病发病、患病的相关文献，筛选并提取相关信息，总结洗脱期时长的确定方法。 截止2022年10月1日，共纳入26篇有效文献，结果显示，文献来源主要集中在加拿大、美国、澳大利亚等行政管理数据完整丰富的国家，研究疾病包括糖尿病、肿瘤、精神分裂等多种慢性疾病。研究认为，设定合适的洗脱期是准确识别发病病例的基础。目前文献中确定洗脱期的方法主要分为三大类，包括经验确定法、一致性检验法和逆向生存函数法。三种方法均有相应的优势和局限性，方法的选择、判断标准和稳定性有待进一步的探究。
医学研究方法医药卫生理论
慢性疾病行政管理数据医疗保险数据洗脱期发病患病
王敬鑫,艾丽梅,杨文怡,万霞.医保等行政管理数据确定慢性病洗脱期最佳策略的系统综述[EB/OL].(2023-01-30)[2025-10-05].https://chinaxiv.org/abs/202301.00212.点此复制
When using administrative data such as medical insurance, the researchers attempted to identify new cases based on the washout period in order to correctly identify the new onset point of chronic diseases with repeated visits. In this paper, all literatures on exploring the incidence and illness of chronic diseases using administrative data from PubMed, Web of science, Embase, CNKI, VIP and Wanfang databases published from the establishment of the database to October 1, 2022 were systematically searched. Relevant information was screened and extracted, and the determination method of washout duration was summarized. As of October 1, 2022, a total of 26 valid literatures were included. The results showed that the literatures were mainly from Canada, the United States, Australia and other countries with complete and abundant administrative data, and the research diseases included diabetes, cancer, schizophrenia and other chronic diseases. It is believed that setting an appropriate washout period is the basis for accurate identification of cases. At present, the methods for determining washout period in literature mainly fall into three categories, including empirical determination method, consistency test method and reverse survival function method. The three methods have corresponding advantages and limitations, and the selection, judgment criteria and stability of the methods need to be further explored.
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