Long-term sickness absence in a working population: development and validation of a risk prediction model in a large Dutch prospective cohort ...
Abstract Background Societal expenditures on work-disability benefits is high in most Western countries. As a precursor of long-term work restrictions, long-term sickness absence (LTSA) is under continuous attention of policy makers. Different healthcare professionals can play a role in identification of persons at risk of LTSA but are not well trained. A risk prediction model can support risk stratification to initiate preventative interventions. Unfortunately, current models lack generalizability or do not include a comprehensive set of potential predictors for LTSA. This study is set out to... Mehr ...
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Dokumenttyp: | Datenquelle |
Erscheinungsdatum: | 2020 |
Verlag/Hrsg.: |
figshare
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Schlagwörter: | Medicine / Biotechnology / 69999 Biological Sciences not elsewhere classified / FOS: Biological sciences |
Sprache: | unknown |
Permalink: | https://search.fid-benelux.de/Record/base-28983804 |
Datenquelle: | BASE; Originalkatalog |
Powered By: | BASE |
Link(s) : | https://dx.doi.org/10.6084/m9.figshare.c.4981388.v1 |
Abstract Background Societal expenditures on work-disability benefits is high in most Western countries. As a precursor of long-term work restrictions, long-term sickness absence (LTSA) is under continuous attention of policy makers. Different healthcare professionals can play a role in identification of persons at risk of LTSA but are not well trained. A risk prediction model can support risk stratification to initiate preventative interventions. Unfortunately, current models lack generalizability or do not include a comprehensive set of potential predictors for LTSA. This study is set out to develop and validate a multivariable risk prediction model for LTSA in the coming year in a working population aged 45–64 years. Methods Data from 11,221 working persons included in the prospective Study on Transitions in Employment, Ability and Motivation (STREAM) conducted in the Netherlands were used to develop a multivariable risk prediction model for LTSA lasting ≥28 accumulated working days in the coming year. ...