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. 2017 Aug;45(6):595-604.
doi: 10.1177/1403494817715399. Epub 2017 Jul 1.

Description of OPRA: A Danish database designed for the analyses of risk factors associated with 30-day hospital readmission of people aged 65+ years

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Description of OPRA: A Danish database designed for the analyses of risk factors associated with 30-day hospital readmission of people aged 65+ years

Mona K Pedersen et al. Scand J Public Health. 2017 Aug.

Abstract

Aims: To describe the construction of the Older Person at Risk Assessment (OPRA) database, the ability to link this database with existing data sources obtained from Danish nationwide population-based registries and to discuss its research potential for the analyses of risk factors associated with 30-day hospital readmission.

Methods: We reviewed Danish nationwide registries to obtain information on demographic and social determinants as well as information on health and health care use in a population of hospitalised older people. The sample included all people aged 65+ years discharged from Danish public hospitals in the period from 1 January 2007 to 30 September 2010. We used personal identifiers to link and integrate the data from all events of interest with the outcome measures in the OPRA database. The database contained records of the patients, admissions and variables of interest.

Results: The cohort included 1,267,752 admissions for 479,854 unique people. The rate of 30-day all-cause acute readmission was 18.9% ( n=239,077) and the overall 30-day mortality was 5.0% ( n=63,116).

Conclusions: The OPRA database provides the possibility of linking data on health and life events in a population of people moving into retirement and ageing. Construction of the database makes it possible to outline individual life and health trajectories over time, transcending organisational boundaries within health care systems. The OPRA database is multi-component and multi-disciplinary in orientation and has been prepared to be used in a wide range of subgroup analyses, including different outcome measures and statistical methods.

Keywords: Aged; database; epidemiology; patient readmission; risk factor.

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