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Health budgets are limited and decision makers in all countries face very challenging decisions about which health interventions will be provided, and which will not. COVID has only added to this pressing priority setting problem. Traditional health technology assessment (HTA)—a process for systematically assessing the comparative cost and effectiveness of health interventions—is a well-established approach to informing priority setting in many high-income countries. In the UK, for example, the National Institute for Health and Care Excellence (NICE) carries out this function. But HTA is often time-consuming and data-hungry, and it demands expertise in conducting analysis and reviewing evidence. Some low- and middle-income countries (LMICs), like Thailand, already use HTA to allocate resources for universal health coverage, but many others are in early stages of their HTA journeys and are often discouraged by the prospect of taking a year or longer to answer a single research question. They may also have limited capacity or data available to carry out HTA in the same manner as high-income countries. In these contexts, new methods are needed that enable LMICs to rapidly and adaptively conduct HTA for health technologies and services including drugs, medical devices, surgical and public health interventions.

In this blog, we highlight key takeaways from our recent commentary in the BMJ Global Health, where we make the case for “adaptive health technology assessment,” or “aHTA.” We define this as a broad term for being pragmatic in conducting HTA to support evidence-based priority setting. We discuss why aHTA is needed; why HTA approaches used in high-income countries are not directly transferable to LMICs; and what could be done to develop, test, validate, and support the uptake of aHTA approaches in LMICs.

Getting on the same page: What is aHTA?

HTA is a process which includes selecting topics for analysis, conducting analysis, reviewing or “appraising” the evidence, making decisions, and implementing the recommendation(s). aHTA adapts one or multiple parts of this process in a pragmatic way that is suited to each research question and to the time and capacity of the decision maker, and thus there is no one-size-fits-all approach. For example, instead of conducting a full cost-effectiveness analysis, the analysis may leverage or adapt available data, models, or decisions from the published literature, established data sets, or other country’s HTA bodies. Likewise, the processes supporting the analysis may be abridged to expedite a decision, but it should still be informed by key HTA principles (e.g., transparency, inclusiveness, independence, etc.).

The findings of adaptive HTAs, just like more traditional HTAs, can be used to inform various policy decisions, including benefit package design, coverage decisions, strategic purchasing, clinical guidelines, and quality standards.  

For the right topics, aHTA can be a quick and practical method for evidence generation

The full HTA process—from topic selection to implementation—can take one to two years to complete. As an alternative tool in the HTA toolbox, aHTA can be a practical and useful option for topics which have been well-studied in other contexts. Policy makers who might be short on time or resources to generate evidence may be able to leverage aHTA with minimal domestic analytical burden to inform routine government processes such as strategic planning and benefit package design including coverage decisions.. Using aHTA also means that decision makers can dedicate the resources they have to conducting more detailed analysis on topics which are not well-studied in other countries but are a priority in their country. Furthermore, aHTA can be a quick learn-by-doing approach which convenes various stakeholders and introduces them to the uses and needs for HTA, fostering future demand for evidence-based policy making. 

aHTA is a tool for the HTA toolbox, but shouldn’t be the only one

Being pragmatic and leveraging HTA decisions from other contexts also has limitations, the most important of which is transferability of international data to the local setting. Other countries’ health systems have different characteristics such as structure, costs, and burden of disease. If the uncertainty linked to transferability is not well accounted for, it could lead to suboptimal decision making. Additionally, aHTA is limited to topics for which international data are available. Often this means high-cost innovative medicines such as new cancer treatments appraised by high-income countries, which may not be relevant to LMICs. Finally, the sole conduct of aHTA may not build the wide-ranging capacity or generate the locally relevant evidence needed to support the long-term goal of integrating HTA into routing decision making . Therefore, aHTA can and should be one tool in the toolbox alongside more comprehensive HTA approaches.

More work needs to be done to design, test, and validate aHTA approaches for LMICs

Different approaches to aHTA are already being undertaken in LMICs and adapted in various ways – including through our work at iDSI in countries such as Rwanda, India, and China –  but we are unaware of any empirical evidence comparing aHTA to more traditional approaches. More needs to be done to develop, standardize, and understand the merits and pitfalls of aHTA methods.

The different stakeholders could take the following actions to advance aHTA:

  • HTA practitioners could publish examples of aHTA approaches, highlighting strengths and limitations.
  • Researchers could develop and test a standardized set of aHTA approaches, comparing them with more traditional approaches.
  • Policy makers could identify priority aHTA topics and build HTA processes which support aHTA on these topics.
  • Clinicians could use aHTA evidence to inform clinical practice guidelines, supplementing with evidence from more detailed analysis as needed.
  • Donors could support aHTA uptake through investing in capacity building and global public goods such as databases of models and incremental cost-effectiveness ratios. 

Policy makers face consequential decisions daily about which health interventions will be covered, how to develop the health benefits packages, and what to include in clinical guidelines. aHTA can offer an opportunity to use economic evidence to inform such decisions in a pragmatic and rapid way.

The authors would like to acknowledge additional authors of the BMJ Global Health commentary summarized here, including Francis Ruiz, Kalipso Chalkidou, Lorna Guinness, and Francoise Cluzeau.

Disclaimer

CGD blog posts reflect the views of the authors, drawing on prior research and experience in their areas of expertise. CGD is a nonpartisan, independent organization and does not take institutional positions.