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- W3172447477 abstract "Multimorbidity, defined as the co-occurrence of multiple chronic conditions, has posed significant health and economic burden on public health. There was an urgent need to study multimorbidity based on existing data. This study aimed to summarize CPs for multimorbidity for three mainstream data sources (survey data, administrative claims data, and electronic health records(EHRs)) through a systematic literature review. We have conducted a systemic literature review in Medline (via PubMed), Embase, and web of science. Observational studies on multimorbidity-related issues published between January 1, 2000, and December 31, 2019 were included. 2 reviewers conducted the review separately, and disagreements were resolved by the study team as whole. Fifty-two articles were included for data extraction. Eighteen studies focused on disease-specific multimorbidity, such as HIV-related multimorbidity (4), cancer-related multimorbidity (4), diabetes-related multimorbidity (3). Among them, 10 of the studies’ population was located in the USA. 13 studies used claims data, 14 studies used electronic health records, 13 studies used survey data, and the rest used different registry administrative datasets. We have summarized CPs for survey data, claims data, and EHRs, respectively. CPs we have summarized can serve as a useful instrument to support future studies on multimorbidity-related issues." @default.
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- W3172447477 date "2021-06-01" @default.
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- W3172447477 title "PMU25 Computable Phenotypes (CPS) for Identifying Individuals with MULTI-Morbidity from Real-World DATA (RWD): A Systematic Literature Review" @default.
- W3172447477 doi "https://doi.org/10.1016/j.jval.2021.04.737" @default.
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