Related Experiment Video
Updated: Jul 29, 2025
A Novel Method for Involving Women of Color at High Risk for Preterm Birth in Research Priority Setting
Published on: January 12, 2018
From population numbers to population needs: Incorporating epidemiological change into health service planning in
Sabrina Lenzen1, Stephen Birch2
1Centre for the Business and Economics of Health, Sir Llew Edwards Building (Building 14), Level 5, Room 513a, The University of Queensland, Faculty of Business, Economics and Law, QLD, St Lucia, 4072, Australia.
Background:
In the face of rapidly ageing populations and increasing costs of health care provision, questions continue to be raised about the long-term sustainability of publicly funded health care programmes around the world. But despite increasing evidence of dynamic changes in epidemiology, most official health service planning models continue to rely on the implicit assumption that age-specific requirements for services (and by implication age-specific needs for care) will remain constant across future years ('constant-use models').
Objectives:
In this paper, we discuss the advantage of dynamic 'changing needs' planning models, compared to 'constant-use' planning models, and consider a framework that integrates population needs directly into health service planning. Using Australian survey data, we empirically illustrate the difference between static health service planning approaches to dynamic needs-driven planning models.
Methods:
We use data from the Household, Income and Labour Dynamics Survey in Australia (HILDA) to explore trends in health needs from 2001 to 2020. We subsequently simulate a 'changing-needs' planning model where changes in health needs by birth-cohorts are incorporated into official government estimates from the Australian Intergenerational Reports (IGR) to understand the potential impact on future health care requirements.
Results:
Our results show that healthy ageing trends are being observed for successive birth-cohorts with these trends greatest in older age groups, the age groups for which health care expenditures are largest. Adjusting for these changes in needs using Australian data leads to reductions in the expenditures required for future years ranging from 1.5 (2.50%) to 3 billion (5.25%) 2019 AUD.
Conclusion:
We conclude that 'constant-use' planning models based on the expected future numbers of people in different age groups applied to current levels of service use by age groups without any consideration given to changing age-specific needs for health care lead to inefficient resource planning.
