The Fast and Furious Journey of Adaptive Health Technology Assessment in Low- and Middle-Income Countries

In a world of limited resources and rising health care demand, decision-makers are permanently urged to make explicit, evidence-based decisions about which services or health technologies to fund, for whom, and how much to pay for them. Health technology assessment (HTA) plays a critical role in this process by evaluating the benefits and costs of health interventions to inform coverage decisions, negotiate price or reimbursement rates, and establish clinical practice guidelines.

While HTA’s importance is increasingly recognized in low- and middle-income countries (LMICs), urgent decision-making needs, limited data availability, and insufficient technical and institutional capacity to conduct traditional HTA has prompted countries to explore alternative methods. These approaches aim to simplify, speed up, or leverage existing assessments to inform decision-making. Notably, this trend did not start in LMICs—high-income countries such as Canada and Scotland have been using rapid assessments for many years—and it has evolved organically in response to need, rather than through a strategic initiative led by normative bodies, such as the World Health Organization. Recent efforts to define and categorize these approaches have helped. The term 'adaptive HTA' (aHTA) is now widely used, a taxonomy with different aHTA types have recently been published, and aHTA guidelines are now available.

Recognizing that perspective matters (policymakers have different needs and risk tolerances compared to academics) and that there is no free lunch (adaptive approaches might lead to inaccuracies, particularly on costs), this blog dives into what matters most to policymakers interested in making evidence-informed choices. It explores five key drives that determine the degree of abridgement and associated uncertainty policymakers are willing to accept. Ultimately, the selection of a particular HTA approach involves balancing result precision with the limitations imposed by data availability and expertise.

Urgency

The more urgent the decision, the less policymakers are likely to worry about the lack of rigor and the more willing they are likely to accept a trade-off between velocity (how fast was the decision made and executed?) and quality (how good was the evidence base of the decision?)

A comprehensive review can typically take between 12 and 24 months to complete, and more often than not, decision-makers need to make decisions quickly. Therefore, it is no surprise that urgency is frequently cited in the literature as a key trigger for aHTA, even when local data and skills are available (see, for example, how high-income settings such as England, Canada, and the European Union often resort to rapid reviews or rapid HTAs when time is tight). Also, in the context of a public health emergency, if a policymaker must decide whether to pay for a new medication to address the crisis, a 'de facto HTA' (adapting decisions made in countries with established HTA processes and applying them in other contexts) or a rapid review might be acceptable, if decisions are revisited quickly once more information becomes available.

Type of decision

The bigger the consequence of the decision, the less willing policymakers are likely to embrace uncertainty, especially if the decision does not need to be made immediately or by them.

Policymakers will also make their willingness to accept sub-optimal evidence dependent on the type of decision and the setting in which the findings will be applied. There are certain decision-making settings where precision is more important. For example, precision in HTA studies may be critical when determining vaccination schedules. Any errors or approximations could lead to suboptimal efficiency at scale since vaccinations will be rolled out to huge cohorts nationwide. On the other hand, precision may not be so important when HTA is informing topic prioritization processes to identify which new technologies should be further scrutinized to determine their inclusion in a benefits package. In fact, some experts recommend aHTA to primarily be used for ‘topic prioritization’ whereby those interventions which are highly cost-ineffective, can directly be ruled out, thus saving time and resources for conducting full HTAs.

Budget implications

The bigger the potential budget impact of a decision, the more risk adverse policymakers will be to accept uncertainty in the results of HTA studies.

Policymakers are likely to feel that decisions regarding the reimbursement or coverage of expensive technologies such as new cancer therapies, which may have a significant budget impact, may require more robust assessments using local data, especially if there is a reasonable degree of uncertainty about whether it might be cost effective in their context. Less analytically and data-demanding HTA approaches are more likely to be acceptable by policymakers for technologies with a low expected budget impact. Conversely, if the additional budget required for a new technology is substantial (or would absorb a significant proportion of the available budget), decision-makers are more likely to consider transferring economic evaluations or accepting manufacturer submissions, thereby allowing more time for the analysis to be conducted.

Political liability

The greater the likelihood of a decision generating political backlash and discontent, the less willing policymakers may be to accept a lack of rigor in the studies informing their decisions.

Policymakers are also concerned with maintaining political support, especially when they are elected by public vote and are likely to run again. Consequently, they are likely to shy away from making unpopular decisions, especially those that will restrict access to health technologies,  regardless of their cost-effectiveness. For instance, a decision not to cover an expensive medicine is likely to generate public outcry and opposition from powerful stakeholders, necessitating the generation of more rigorous evidence to support the decision and render it robust and legitimate. Conversely, a decision to implement a basic intervention for the treatment of diabetes is likely to elicit a comparatively muted political response from key stakeholders.  

Probability of being right

Policymakers are more likely to accept less rigor when the decision is a no-brainer or the likelihood of making the right decision is very high.

HTA practitioners and policymakers will be attentive to the confidence about the expected value (or lack thereof) of health technologies when considering the use of different pragmatic approaches to HTA. The more confident they are, the more likely they will opt for less analytically demanding aHTA approaches. Argentina, for example, used a triage approach to developing a benefit package using rapid revies to identify  technologies  with very low likelihood of being cost-effective. Similar recommendations have been made when using cost-effectiveness analyses or HTA reports from other countries. Essentially, policymakers are eager to understand the likelihood that a technology found to be cost-ineffective elsewhere will be cost-effective locally. If this probability is low, it is less important to conduct a full HTA. Conversely, if the results of the cost-effectiveness analysis conducted elsewhere are likely to differ significantly in the local context, policymakers are likely to demand a more thorough HTA.

Moving forward

There are many reasons why policymakers do not have the luxury (or the need) to rely on full HTAs for their decision-making processes. This should not deter them from moving towards more evidence-based resource allocation decisions. In fact, many countries are exploring a broad spectrum of abbreviated evaluation methods to inform their decisions.

To further promote the use of aHTA, it is now necessary to link the specific concerns and perspectives of policymakers outlined above to the menu of aHTA options available. Providing clear guidelines on which methods are best suited to different situations and contexts, along with minimum technical and methodological standards, is key. Finally, regardless of the aHTA methods chosen, they must be embedded in processes that adhere to the same good governance principles recommended for HTA overall: transparency, participation, and consistency.