Predictive modeling for identification of older adults with high utilization of health and social services.

Journal: Scandinavian journal of primary health care
PMID:

Abstract

AIM: Machine learning techniques have demonstrated success in predictive modeling across various clinical cases. However, few studies have considered predicting the use of multisectoral health and social services among older adults. This research aims to utilize machine learning models to detect high-risk groups of excessive health and social services utilization at early stage, facilitating the implementation of preventive interventions.

Authors

  • Heba Sourkatti
    VTT Technical Research Centre of Finland Ltd, Espoo, Finland.
  • Juha Pajula
    VTT Technical Research Centre of Finland Ltd, Espoo, Finland.
  • Teemu Keski-Kuha
    Finnish Institute of Health and Welfare (THL), Helsinki, Finland.
  • Juha Koivisto
    Department of Physics, University of Helsinki, Gustaf Hällsströmin katu 2, FI-00560, Helsinki, Finland.
  • Mika Hilvo
    VTT Technical Research Centre of Finland Ltd, Espoo, Finland.
  • Jaakko Lähteenmäki
    VTT Technical Research Centre of Finland Ltd, Espoo, Finland.