Data integration and knowledge discovery in biomedical databases. Reliable information from unreliable sources | Zendy

Arnold Mitnitski | Zendy; Alexander Mogilner | Zendy; Chris MacKnight | Zendy; Kenneth Rockwood | Zendy

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Data integration and knowledge discovery in biomedical databases. Reliable information from unreliable sources

Author(s) -

Arnold Mitnitski,

Alexander Mogilner,

Chris MacKnight,

Kenneth Rockwood

Publication year - 2003

Publication title -

data science journal

Language(s) - English

Resource type - Journals

SCImago Journal Rank - 0.358

H-Index - 21

ISSN - 1683-1470

DOI - 10.2481/dsj.2.25

Subject(s) - scope (computer science) , computer science , data science , usability , metadata , transparency (behavior) , open data , reuse , implementation , world wide web , data discovery , data publishing , publishing , software engineering , political science , engineering , computer security , human–computer interaction , programming language , waste management , law

To better understand information about human health from databases we analyzed three datasets collected for different purposes in Canada: a biomedical database of older adults, a large population survey across all adult ages, and vital statistics. Redundancy in the variables was established, and this led us to derive a generalized (macroscopic state) variable, being a fitness/frailty index that reflects both individual and group health status. Evaluation of the relationship between fitness/frailty and the mortality rate revealed that the latter could be expressed in terms of variables generally available from any cross-sectional database. In practical terms, this means that the risk of mortality might readily be assessed from standard biomedical appraisals collected for other purposes

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