Modeling to inform long-term care policy and planning for an aging society


Book Section

© 2017, Springer International Publishing AG. Demographic changes such as increasing longevity, declining family sizes, and increasing female participation in the labor market have implications for long-term care (LTC) planning for the elderly. As the population in both developed and developing world ages, the prevalence of health conditions such as chronic diseases and disabilities increases. Consequently, the proportion of elderly adults who require assistance with their daily activities rises. Further, the potential decrease in family members available as caregivers implies an increase in the demand for alternative LTC arrangements. Planning of LTC services is fraught with dynamic complexities. Various issues, such as projecting future need, cost, capacity, and quality of care and caregivers—formal and informal—can influence the effectiveness and efficiency of LTC services. The trends outlined point to the need for a comprehensive LTC planning that accounts for all these dynamics changes. This chapter aims to demonstrate the use of simulation modeling as a communication tool that allows for the LTC complexity to be reduced to its essential elements to inform policy for an aging society. The forms of simulation techniques used in the planning of LTC policy and services and real-world applications across different institutional contexts are discussed. Of particular focus is the application of the system dynamics methodology in LTC planning. Three LTC projects using system dynamics methodology are presented. Specifically, these LTC projects comprise the methodological process in the projection of the number of disabled elderly in Singapore accounting for changing educational attainment, the impact of various LTC policies on informal eldercare hours and labor force participation of informal caregivers, and the impact of LTC capacity expansion policies on acute care.

Full Text

Duke Authors

Cited Authors

  • Ansah, JP; Koh, V; Qureshi, MA; Matchar, DB

Published Date

  • January 1, 2017

Book Title

  • Understanding Complex Systems

Start / End Page

  • 183 - 224

Digital Object Identifier (DOI)

  • 10.1007/978-3-319-55774-8_7

Citation Source

  • Scopus