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Open Access Highly Accessed Research article

How are population-based funding formulae for healthcare composed? A comparative analysis of seven models

Erin Penno1*, Robin Gauld1 and Rick Audas2

Author Affiliations

1 Centre for Health Systems, Department of Preventive and Social Medicine, University of Otago, P.O. Box 913, Dunedin 9054, New Zealand

2 Division of Community Health and Humanities, Faculty of Medicine, Memorial University of Newfoundland, St. John’s, NL A1B 3X9, Canada

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BMC Health Services Research 2013, 13:470  doi:10.1186/1472-6963-13-470

Published: 8 November 2013

Abstract

Background

Population-based funding formulae act as an important means of promoting equitable health funding structures. To evaluate how policy makers in different jurisdictions construct health funding formulae and build an understanding of contextual influences underpinning formula construction we carried out a comparative analysis of key components of funding formulae across seven high-income and predominantly publically financed health systems: New Zealand, England, Scotland, the Netherlands, the state of New South Wales in Australia, the Canadian province of Ontario, and the city of Stockholm, Sweden.

Methods

Core components from each formula were summarised and key similarities and differences evaluated from a compositional perspective. We categorised approaches to constructing funding formulae under three main themes: identifying factors which predict differential need amongst populations; adjusting for cost factors outside of needs factors; and engaging in normative correction of allocations for ‘unmet’ need.

Results

We found significant congruence in the factors used to guide need and cost adjustments. However, there is considerable variation in interpretation and implementation of these factors.

Conclusion

Despite broadly similar frameworks, there are distinct differences in the composition of the formulae across the seven health systems. Ultimately, the development of funding formulae is a dynamic process, subject to availability of data reflecting health needs, the influence of wider socio-political objectives and health system determinants.

Keywords:
Health funding; Population based funding models; Comparative analysis; Resource allocation