Quebec National Institute of Public Health, Quebec City, Québec, Canada.
Department of Social and Preventive Medicine, Faculty of Medicine, Laval University, Quebec City, Québec, Canada.
Pharmacoepidemiol Drug Saf. 2022 Jan;31(1):1-12. doi: 10.1002/pds.5368. Epub 2021 Oct 19.
We aimed to identify and characterize adult population-based multimorbidity measures using health administrative data and the International Classification of Diseases (ICD) codes for disease identification.
We performed a narrative systematic review of studies using or describing development or validation of multimorbidity measures. We compared the number of diseases included in the measures, the process of data extraction (case definition) and the validation process. We assessed the methodological robustness using eight criteria, five based on general criteria for indicators (AIRE instrument) and three multimorbidity-specific criteria.
Twenty-two multimorbidity measures were identified. The number of diseases they included ranged from 5 to 84 (median = 20), with 19 measures including both physical and mental conditions. Diseases were identified using ICD codes extracted from inpatient and outpatient data (18/22) and sometimes including drug claims (10/22). The validation process relied mainly on the capacity of the measures to predict health outcome (5/22), or on the validation of each individual disease against a gold standard (8/22). Six multimorbidity measures met at least six of the eight robustness criteria assessed.
There is significant heterogeneity among the measures used to assess multimorbidity in administrative databases, and about a third are of low to moderate quality. A more consensual approach to the number of diseases or groups of diseases included in multimorbidity measures may improve comparison between regions, and potentially provide better control for multimorbidity-related confounding in studies.
本研究旨在利用健康管理数据和国际疾病分类（ICD）代码来识别和描述基于人群的成年多病种衡量方法。
我们对使用或描述多病种衡量方法的开发或验证的研究进行了叙述性系统综述。我们比较了这些衡量方法中包含的疾病数量、数据提取（病例定义）过程和验证过程。我们使用八项标准评估了方法学的稳健性，其中五项基于指标的一般标准（AIRE 工具），三项为多病种特有的标准。
共确定了 22 种多病种衡量方法。它们所包含的疾病数量从 5 种到 84 种不等（中位数为 20），其中 19 种方法既包括身体疾病也包括精神疾病。疾病通过从住院和门诊数据中提取的 ICD 代码（22/22）确定，有时还包括药物索赔数据（22/22）。验证过程主要依赖于衡量方法预测健康结局的能力（22/22），或依赖于对每种疾病与金标准的验证（22/22）。有 6 种多病种衡量方法至少符合八项稳健性标准中的六项。
在利用管理数据库评估多病种时，所使用的衡量方法存在显著的异质性，其中约三分之一的方法质量较低或中等。在多病种衡量方法中纳入疾病数量或疾病组的方法更加一致，可能会改善地区间的比较，并有可能在研究中更好地控制与多病种相关的混杂因素。
