Priority setting in health: Development and application of a multi-criteria algorithm for the population of New Zealand's Waikato region

Abstract

Background: Priority setting in a climate of diverse needs and limited resources is one of the most significant challenges faced by health care policymakers. This paper develops and applies a comprehensive multi-criteria algorithm to help determine the relative importance of health conditions that affect a defined population. Methods: Our algorithm is implemented in the context of the Waikato District Health Board (WDHB) in New Zealand, which serves approximately 10% of the New Zealand population. Strategic priorities of the WDHB are operationalized into five criteria along which the algorithm is structured - scale of disease, household financial impact of disease, health equity, cost-effectiveness, and multimorbidity burden. Using national-level data and published literature from New Zealand, the World Health Organization, and other high-income Commonwealth countries, 25 health conditions in Waikato are identified and mapped to these five criteria. These disease-criteria mappings are weighted with data from an ordered choice survey administered to the general public of the Waikato region. The resulting output of health conditions ranked in order of relative importance is validated against an explicit list of health concerns, provided by the survey respondents. Results: Heart disease and cancerous disorders are assigned highest priority rankings according to both the algorithm and the survey data, suggesting that our model is aligned with the primary health concerns of the general public. All five criteria are weighted near-equal across survey respondents, though the average health equity preference score is 9.2% higher for Maori compared to non-Maori respondents. Older respondents (50 years and above) ranked issues of multimorbidity 4.2% higher than younger respondents. Conclusions: Health preferences of the general population can be elicited using ordered-choice surveys and can be used to weight data for health conditions across multiple criteria, providing policymakers with a practical tool to inform which health conditions deserve the most attention. Our model connects public health strategic priorities, the health impacts and financial costs of particular health conditions, and the underlying preferences of the general public. We illustrate a practical approach to quantifying the foundational criteria that drive public preferences, for the purpose of relevant, legitimate, and evidence-based priority setting in health.