Details descriptions of the session:
Prioritizing services within health benefits packages (HBP) is a data-demanding process. Often, HBPs are prioritized based on various criteria such as cost-effectiveness, cost/budget impact, feasibility, and equity. Analysts are faced with adapting methods to demanding time constraints and varying levels of available local data. This is particularly acute when revising full benefits packages , where data demands are so intensive that they often draw on data from other jurisdictions, global estimates, default values, and/or expert opinion.
While there have been efforts in recent years to pool global evidence to inform HBP prioritization, combining data from various sources or adapting it from other contexts is inherently uncertain. In turn, using uncertain information in HBP design can incur a high risk, or opportunity cost, particularly in settings with low resource levels.
In health economics, uncertainty analysis typically focuses on the range and uncertainty of possible values used to parameterize cost-effectiveness analysis (CEA). Likewise, value of information analysis (VOI) is used to quantify risk by drawing on sensitivity analyses from these CEAs to estimate the value of reducing uncertainty.
However, evaluating risk in HBPs is challenging. First, uncertainty in HBPs goes beyond parameter uncertainty. For example, structural uncertainty, differences in health systems, and uncertainty of transferring estimates from other jurisdictions should be considered. Second, HBPs typically draw on secondary CEAs, and obtaining the necessary values to calculate VOI is not always possible. Finally, frameworks for evaluating uncertainty and risk have mostly been developed in high-income countries but have rarely been considered in the context of HBP design which is typically concentrated in low- and middle-income countries (LMICs).
There is limited guidance on how best to represent the uncertainty associated with HBP design, and the resulting risk of making the wrong decision.
Learning objectives and target audience:
This session will explore how existing methodological frameworks for addressing risk have been considered in Kyrgyzstan, Rwanda, Malawi, and Thailand.
The target audience for this session is HBP and health technology assessment practitioners in LMICs who may use these methods when designing an HBP.
Structure of presentation:
The session will be chaired by Regis Hitimana, Rwanda Social Security Board, Rwanda, and start with 4 presentations:
- Exploring the “Appraisal of Risk Chart (ARCH)” for the appraisal of cancer services in Rwanda
- Assessing the value of default versus refined cost estimates for Kyrgyzstan’s health benefits package
- Concomitant health benefits package design and research prioritization – developing a value of information (VOI) approach and application in Malawi
- Managing the uncertainty and risk in dialysis policy development: from defining the research question to uncertainty in policy implementation
Presentations will be followed by audience Q&A for general understanding of methods. This will be followed by discussants’ reflections including Anna Vassall, LSHTM, UK, and Mark Jit, LSHTM, UK.
