Aim: To evaluate the efficacy of multidimensional geriatric assessment (MGA/CGA) in patients over 65 years old in predicting the release of the accompaniment allowance (AA) indemnity by a Local Medico-Legal Committee (MLC-NHS) and by the National Institute of Social Security Committee (MLC-INPS). Methods: In a longitudinal observational study, 200 Italian elder citizens requesting AA were first evaluated by MLC-NHS and later by MLC-INPS. Only MLC-INPS performed a MGA/CGA (including SPMSQ, Barthel Index, GDS-SF, and CIRS). This report was written according to the STROBE guidelines. Results: The data analysis was performed on January 2016. The evaluation by the MLC-NHS and by the MLC-INPS was in agreement in 66% of cases. In the 28%, the AA benefit was recognized by the MLC-NHS, but not by the MLC-INPS. By the multivariate analysis, the best predictors of the AA release, by the MLC-NHS, were represented by gender and the Barthel Index score. The presence of carcinoma, the Barthel Index score, and the SPMQ score were the best predictors for the AA release by MLC-INPS. Conclusions: MGA/CGA could be useful in saving financial resources reducing the risk of incorrect indemnity release. It can improve the accuracy of the impairment assessment in social security system

The potential impact of multidimesional geriatric assessment in the social security system

Corbi, Graziamaria
;
Ferrara, Nicola;Campobasso, Carlo Pietro
2018-01-01

Abstract

Aim: To evaluate the efficacy of multidimensional geriatric assessment (MGA/CGA) in patients over 65 years old in predicting the release of the accompaniment allowance (AA) indemnity by a Local Medico-Legal Committee (MLC-NHS) and by the National Institute of Social Security Committee (MLC-INPS). Methods: In a longitudinal observational study, 200 Italian elder citizens requesting AA were first evaluated by MLC-NHS and later by MLC-INPS. Only MLC-INPS performed a MGA/CGA (including SPMSQ, Barthel Index, GDS-SF, and CIRS). This report was written according to the STROBE guidelines. Results: The data analysis was performed on January 2016. The evaluation by the MLC-NHS and by the MLC-INPS was in agreement in 66% of cases. In the 28%, the AA benefit was recognized by the MLC-NHS, but not by the MLC-INPS. By the multivariate analysis, the best predictors of the AA release, by the MLC-NHS, were represented by gender and the Barthel Index score. The presence of carcinoma, the Barthel Index score, and the SPMQ score were the best predictors for the AA release by MLC-INPS. Conclusions: MGA/CGA could be useful in saving financial resources reducing the risk of incorrect indemnity release. It can improve the accuracy of the impairment assessment in social security system
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11695/73789
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