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Using the stochastic health state function to forecast healthcare demand and healthcare financing: Evidence from Singapore

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  • Ngee Choon Chia
  • Shu Peng Loh

Abstract

Typically, healthcare financing for an ageing population requires projections on healthcare demand and cost. However, projecting healthcare demand based on projected elderly does not consider changes in population health state over time. This paper proposes a new approach to forecast health variables using a stochastic health state function and the well‐established Lee–Carter stochastic mortality model. With the estimated health state at each age over time, we project the hospitalization rate, healthcare demand, and financing cost for Singapore using historical life tables and hospital admission data. Our findings show that while hospital insurance claims increase owing to an aging population, improving health state could save costs from hospital insurance claims. This has policy implications: more attention should be given to preventive healthcare such as health screening to improve the overall health state of the population.

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  • Ngee Choon Chia & Shu Peng Loh, 2018. "Using the stochastic health state function to forecast healthcare demand and healthcare financing: Evidence from Singapore," Review of Development Economics, Wiley Blackwell, vol. 22(3), pages 1081-1104, August.
    • Handle: RePEc:bla:rdevec:v:22:y:2018:i:3:p:1081-1104
    DOI: 10.1111/rode.12528
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    Cited by:

    1. Zhao, Xinxing & Li, Kainan & Ang, Candice Ke En & Ho, Andrew Fu Wah & Liu, Nan & Ong, Marcus Eng Hock & Cheong, Kang Hao, 2022. "A deep learning architecture for forecasting daily emergency department visits with acuity levels," Chaos, Solitons & Fractals, Elsevier, vol. 165(P1).

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