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Multidimensional prognostic index (MPI) predicts successful application for disability social benefits in older people

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Abstract

Aim

The economic recognition of disability is of importance in daily practice, but the tools used in older people are still limited. Therefore, we aimed to investigate the effectiveness of the multidimensional prognostic index (MPI) to identify frail older subjects to be submitted to civil invalidity application for disability benefits including Attendance Allowance (AA) indemnity, Carer’s Leave (Law 104) and/or Parking Card for people with disabilities.

Methods

From March 2018 to January 2019, 80 older people were included. The MPI was calculated from comprehensive geriatric assessment information including eight different domains. Civil benefits included attendance allowance (AA) indemnity by the Local Medico-Legal Committee (MLC-NHS) and by the National Institute of Social Security Committee (INPS), Carer’s Leave (Law 104), and Parking Card for people with disabilities.

Results

MPI values were associated with an increased probability to obtain a 100% civil disability, AA indemnity, Carer’s Leave and a parking card for people with disabilities. MPI score showed a very good accuracy in predicting the civil invalidity benefits with a area-under-curve (AUC) of 87.3 (95% CI 80.6–97.4) to predict the release of AA indemnity, 81.3 (95% CI 68.5–91.1) to predict Care’s leave and 70.7 (95% CI 59.4–84.7) to predict the Parking Card release. Moreover, data showed that a cut-off score of MPI ≥ 0.75 could identify the 100% of older subjects who successfully obtained the indemnity release.

Conclusion

MPI is an excellent predictor of social benefits’ release by local and national agencies.

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Funding

This research did not receive any specific grant from funding agencies in the public, commercial, or not-for-profit sectors.

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Authors and Affiliations

  1. Geriatrics Unit, Center for Cognitive Disorders and Dementia (CDCD), Department of Geriatric Care, Orthogeriatrics and Rehabilitation, Galliera Hospital, Via Mura delle Cappuccine 14, 16128, Genova, Italy

    Barbara Senesi, Camilla Prete, Alessandra Pinna, Angela Giorgeschi, Nicola Veronese & Alberto Pilotto

  2. Scientific Coordination Office, Biostatistics, Galliera Hospital, Genova, Italy

    Giacomo Siri

  3. Primary Care Department, Azienda ULSS3 Serenissima, District 3, Venice, Italy

    Nicola Veronese

  4. Department of Interdisciplinary Medicine, University of Bari, Bari, Italy

    Roberto Sulpasso, Carlo Sabbà & Alberto Pilotto

Authors
  1. Barbara Senesi
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  2. Camilla Prete
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  3. Giacomo Siri
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  4. Alessandra Pinna
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  5. Angela Giorgeschi
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  7. Roberto Sulpasso
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  8. Carlo Sabbà
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  9. Alberto Pilotto
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Corresponding author

Correspondence to Barbara Senesi.

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The paper does not report on primary research. All data analysed were collected as part of routine diagnosis and treatment. Therefore, the formal approval from the local Ethical Committee was not asked, in agreement with the current legislation.

Informed consent

At the time of the visit, the patients (or their legal representatives) were fully informed regarding the possible aims of the data used for clinical scenarios.

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Senesi, B., Prete, C., Siri, G. et al. Multidimensional prognostic index (MPI) predicts successful application for disability social benefits in older people. Aging Clin Exp Res 33, 1963–1969 (2021). https://doi.org/10.1007/s40520-020-01694-x

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