The Health Interventions Prioritization Tool (HIPtool) is a cloud-based, open-access, user-friendly, high-impact resource to assist with health intervention prioritization at the country level. It combines context-specific data on burden of disease and intervention effectiveness to help stakeholders identify funding priorities and targets.
Global momentum towards Universal Health Care (UHC) continues to accelerate since its inclusion in the UN Sustainable Development Goal on ‘Good Health and Wellbeing’. While universal access remains the ultimate goal, most countries will have to transition to universality through a gradual process of widening provision. Research has highlighted the advantages of defining explicit health service packages on the path to UHC, sometimes called Health Benefits Packages (HBP), which are free at the point of use. Defined Health Benefits Packages can:
Significant investments in health systems data collection and synthesis are maturing. We now have more information than ever before about current and future trends in burden of disease, health service costs and the expected impact of service provision. This information can be used to support the evidence-based formulation of HBPs.
In December 2017, two packages of the most cost-effective health interventions across disease areas were published in Disease Control Priorities, Third Edition (DCP3). The DCP3 Essential UHC (EUHC) package and Highest-Priority Package (HPP) provide a foundation on which to prioritize services. However, each country has its own epidemiological profile, cost base and service delivery system. So, while the EUHC and HPP provide general guidelines, they need to be adapted to a country’s own context. Countries may also want to compare DCP3 recommendations with those of the World Health Organization, or to monitor progress towards national or global targets.
Decision makers thus have an unprecedented body of evidence to inform their selection of high priority health services but navigating such complex evidence can prove challenging.
HIPtool has been developed to assist decision makers in selecting, synthesising and generating evidence to aid policy discussions around health intervention prioritization and HBP design.
HIPtool analyses bring together IHME data on burden of disease and DCP3 data on the EUHC and HPP packages, together with other secondary data sources.
These data are combined in an open-access, online interface that is intended to be user-friendly and flexible. While a set of default data are included in the tool, these can be amended by users to better reflect local contexts.
The first step in a HIPtool analysis is to identify what services are currently provided, and which of those are included in the HBP if one exists or is clearly defined. Once relevant services are identified, the following five steps constitute a HIPtool analysis:
A range of stakeholders should usually be involved throughout the process to help validate both the inputs and outputs of a HIPtool analysis, and to inform the feasibility of different scenarios by identifying ethical, financial, logistic, political and other potential constraints.
HIPtool is designed to produce clear graphic outputs that can be understood by stakeholders with a wide range of expertise. The aim of these outputs is to support discussions across different branches of government, such as ministries of finance or transport, which are essential if progress toward UHC is to be made.
When setting priorities for a health benefits package, countries may want to compare any changes against current spending and service provision. The HIPtool can compare the impact of different packages so that stakeholders can compare the gains and losses that may result from any changes.
The HIPtool includes an optimisation algorithm and offers the option to estimate allocations of spending to maximise:
The HIPtool can be used to estimate the impact of different spending scenarios to help inform decision-makers about (a) which services would benefit most from additional funding, (b) which services might be prioritised if overall funding decreases, or (c) to help advocate for additional future funding by quantifying the impact of different funding scenarios.