Feasibility study to address key condition/risk factor cost evidence gaps and comparable costs
Feasibility study to address key condition/risk factor cost evidence gaps and comparable costs
Theme 4: Applied Evaluation
There are evidence gaps regarding the societal costs of key health conditions and risk factors that reduce the ability of policy makers to efficiently allocate constrained resources. These include a lack of comparable public and private costs (in particular, health care resources, social care resources, productivity and informal care costs) and associated fiscal impacts (including the tax and welfare transfers) across key health conditions and risk factors.
Published societal costs for a given health condition/risk factor can sometimes vary significantly due to, for instance, different methods and missing and/or different cost categories (e.g. social care costs) and sub-cost categories (e.g. absenteeism). Similarly, cost categories and methods often vary across health conditions and risk factors, which means that cost estimates are generally not comparable across health conditions/risk factors.
Costs feed into models that determine the economic efficiency of interventions. The lack of comparable costs means that the evidence used to prioritise resources across public health/health interventions may not give a fair/accurate picture, so we may not be prioritising effectively. Policy makers may end up implicitly comparing costs when modelling the economic returns on an intervention to decide whether it is worth investing in, or using existing internal tools that collate health condition/risk factor costs, even if appropriate caveats are in place, which could lead to incorrect conclusions.This makes it hard to understand where to prioritise resources across preventing different conditions/risk factors.
It is recognised that there does not exist a single data source that would allow simultaneous causal estimation of the attributable economic impacts with ability to decompose to consistently defined and measured disease, risk factor, geography and sociodemographic characteristics. Hence the purpose of this feasibility study is to understand the extent to which the desired information could be produced by combining data or estimates from multiple sources. It is also of interest to understand the practicality and costs of different methods for producing and updating this information. This research will aim to aid the prioritisation of resources across public health and health interventions that seek to prevent key risk factors and health conditions in England.
This project aims to address evidence gaps in relation to the generation of consistent cost estimates across diseases and risk factors by:
i) Summarising the current approaches to estimating comparable cost estimation for societal (in particular, health care, social care and productivity) costs of key health conditions and risk factors.
ii) Considering how comparable costs could be estimated in a way such that the costs could be updated in an automated fashion, as far as possible.
iii) Summarising how comparability can be defined and assessed and determining methods that could be used to assess the risk and consequences of misprioritisation.
iv) Summarising potential methodological work to evaluate the quality and any potential trade-offs across different approaches to cost estimation (e.g. lower quality but more frequent update based on routine data vs higher quality bespoke estimation with less frequent update)
Susan Griffin - susan.griffin@york.ac.uk
Background
The Government decides how to divide funding across different areas of healthcare. Ideally, these decisions are based on knowledge about how much different diseases and risk factors cost in terms of healthcare, social care and sick leave from work. Researchers have estimated these links on the basis of limited data that do not track every individual through their lifetime, using separate data sources depending on the disease or cost being estimated. This means that the cost information available is calculated differently, depending on which disease you are looking at. This means it is not always possible to decide if one disease generates greater costs than another. Ideally, we would rule out the differences caused by different estimation methods and different data sources, giving a clear, consistent, comparable picture of the costs associated with each disease. This research study will look at the feasibility of calculating comparable costs for some key disease areas (such as cancer and heart disease) and risk factors (such as smoking and obesity). This will feed into the design of further research to help policy makers in England make better decisions about where to spend healthcare funding.
Aim and Objectives
This study aims to show how comparable costs could be calculated across different disease areas and risk factors. The research will:
Look at the current approaches for estimating comparable costs across different health conditions and risk factors.
Define what "comparable" means for these costs and develop ways to work out the risks of making wrong spending decisions due to incorrect cost estimates.
Look at the pros and cons of the different methods that could be used to estimate comparable costs.
Consider the feasibility of setting up an automated process to produce and update comparable costs.
Methods
This study will follow four steps:
We will meet with the people using this research (for example, data analysts) to identify key areas of focus. These will include the types of costs, health conditions and risks, location, timing, and patient characteristics.
We will carry out a rapid review of existing research to see how costs for major diseases in England have been estimated in the past. We will focus on studies that examine more than one disease and gather information on where they got their data (the data sources), their methods, and which specific costs they included.
We will check what data sources are available today in addition to those used in existing studies. We will describe what information each source contains, when it was collected, and how frequently it has been updated, for the areas described in our study plan.
We will look at our findings and form a view on different ways in which the costs we are interested in can be estimated. We will summarise the evidence gaps, suggest the most promising approaches, and discuss with our stakeholders to determine future research priorities.
Policy relevance and dissemination
This research could help policy makers spend money more effectively across funding programmes that aim to reduce major health conditions and risk factors. We will publish the results of our study as a journal article, which will include the methods and data sources that could be used to generate comparable costs.