Health technology assessment and innovation: here to help or hinder? | International Journal of Technology Assessment in Health Care

Funding mechanisms

It should be noted that many countries commonly use funding mechanisms in pricing and reimbursement decision making for pharmaceuticals, whereas HTA is used to determine the value of a technology at both the individual and population levels. Price points ensure affordable and equitable access to new drugs at the same time as providing industry with an incentive to develop new therapies. Pharmaceutical innovation is commonly rewarded by funders agreeing to a premium price for a new drug, widely seen as stimulating innovation while at the same time delivering value for money to the payee. Funders who primarily focus on price minimization may, however, reduce the incentive for future innovation. Again, determining innovation and “real benefit” of a drug is difficult and may consider factors beyond just being a new or novel entity. For example, a new drug that has the same therapeutic effect but can be taken orally at home rather than intravenously in hospital offers real benefit to patients, carers, and healthcare providers. There is a risk; however, for health systems that operate within a limited budget, that by valuing anything beyond therapeutic benefit and inappropriately rewarding “innovation” will displace other, more cost-effective therapies, leading to a decrease in patient outcomes at the population level (Reference de Solà-Morales, Cunningham and Flume5;Reference Hofmann, Branner, Misra and Lintener13). The move toward personalized medicine highlights this issue. Funding high-cost oncology or orphan disease drugs that deliver improved patient outcomes for a relatively few at the individual level may incentivize companies to stop developing incremental improvements in drugs that target common diseases, compromising population-level healthcare (Reference de Solà-Morales, Cunningham and Flume5). This highlights the fine line for decision makers to distinguish between subsidizing versus incentivizing innovation (Reference Goodman14).

ICER thresholds represent the maximum value, or threshold, that funders are willing to pay for a health outcome in order to decide whether investing in a new intervention is an efficient use of resources (15). In determining whether new health technologies should be funded, funders prefer explicit to implicit methods of analysis to ensure transparency and consistency of decision making. Most funders have implicit ICER values, that is, an “unspoken” ICER value that represents the acceptable price for a unit of additional health gain for which decision makers, on behalf of society, are willing to pay. If the ICER exceeds this threshold value, then technologies will not be funded unless they satisfy other value-based criteria, such as equity or unmet clinical need in rare diseases. Although using an explicit ICER threshold is not supported by all funders, applying the same threshold to all technologies and all patient groups does lend a degree of transparency, accountability, and certainty to the funding process (Reference Charlton and Rid3;Reference Charlton, Lomas and Mitchell6).

Traditional cost-effectiveness analyses are unlikely to capture the full range of benefits of innovative technologies, such as digital health technologies, which may be hugely beneficial but these benefits are hard to capture with a traditional ICER (Reference Syeed, Poudel, Ngorsuraches, Diaz and Chaiyakunapruk11). To address this shortcoming, some agencies may justify funding technologies that exceed the ICER threshold by considering ethical and social values such as unmet clinical need or end-of-life treatments, in addition to the innovative nature of the technology (Reference Syeed, Poudel, Ngorsuraches, Veettil and Chaiyakunapruk10). The difficulty in defining and capturing innovation in evaluations is reflected in recent changes to NICE’s evaluation guidelines. Previously, NICE explicitly stated that innovation could be used to justify funding technologies that were not cost-effective; however, what constituted innovation was not clearly defined and may have resulted in arbitrary funding decisions (Reference Charlton and Rid3). NICE’s evaluation guidelines now refer to funding decisions for technologies with an ICER above £20,000 per QALY gained, or £100,000 per QALY gained for highly specialized technologies that consider “aspects that relate to uncaptured benefits and non-health factors” (16).

Managed entry agreements (MEAs, also referred to as risk-sharing agreements or patient access schemes), where the risk of investing in high-cost technologies is mitigated by, or shared with, manufacturers. Investment in new healthcare technologies can be challenging for payers in resource-constrained health systems as funding decisions for high-cost, innovative technologies are often associated with a high level of risk and a degree of uncertainty in the (often immature) clinical evidence base, cost-effectiveness, budget impact, price or eligible patient population. With conventional reimbursement decisions, the risk associated with the uncertainty around the true value of a technology is transferred from the manufacturer to the healthcare payer. MEAs share the risk between manufacturers and the payer while at the same time delivering patient access to new technologies (Reference Efthymiadou17;Reference Vreman, Broekhoff, Leufkens, Mantel-Teeuwisse and Goettsch18)

MEAs can be classified into two broad categories – health outcomes and financial-based agreements, or sometimes a combination of both; however, the majority of MEAs are financial-based agreements where there is often uncertainties in utilization and budget impact (Reference Federici, Reckers-Droog and Ciani19). Basic financial agreements include simple discounts agreed between the payer and manufacturer, or price–volume agreements, often applied to drugs with the price of the drug decreasing as more patients receive the treatment (Reference Efthymiadou17;Reference Efthymiadou and Kanavos20). More complex MEAs are needed to reduce risk and encourage innovation, including value-based pricing, performance-linked reimbursement, and CED, where time-limited funding of technologies is conditional on additional data collection to reduce uncertainties in the (immature) evidence base (Reference Vreman, Broekhoff, Leufkens, Mantel-Teeuwisse and Goettsch18). MEAs allow early patient access to innovative technologies and provide an incentive to manufacturers to produce technologies that are likely to be of value. Outcome-based MEAs, especially for innovative technologies with a limited evidence base such as cell and gene therapies, offer an opportunity to accumulate a robust body of real-world evidence (RWE) to inform future reimbursement decisions as well as recommendations about a technology’s use (Reference Goodman14).

Outcome-based MEAs such as CED are not used widely due to the complexity and cost of their implementation including the high cost of administration, data collection and analysis, and an unrealistic definition of value, which is often determined at an early stage of development. Although the use of MEAs has increased over time, they have yet to gain widespread acceptance, mainly due to a lack of evaluation of their effectiveness in meeting their stated goals, that is, increasing patient access and reducing payer risk (Reference Efthymiadou17;Reference Federici, Reckers-Droog and Ciani19;Reference Efthymiadou and Kanavos20).

Accelerated access is a form of CED where new health technologies receive accelerated regulatory approval by demonstrating early beneficial effects with accumulation of RWE (e.g., progression-free survival) that may translate to real clinical benefits (e.g., overall survival) when post-approval confirmatory studies are completed and evaluated (Reference Gyawali, Hey and Kesselheim21). Accelerated access is granted based on limited evidence, and that at the end of the approval period, technologies should undergo HTA evaluation, especially addressing safety, budget impact, and cost-effectiveness (Reference Fens, van Puijenbroek and Postma22)

Accelerated access has primarily been used to fast-track the regulatory process predominantly for oncology drugs, expediting access to patients who have little or no treatment options. It does; however, take considerable time for the comprehensive post-marketing evaluation of drugs granted accelerated approval, and as such, the risks and benefits of these drugs remain unclear for some time. A good example of this occurred during the COVID-19 pandemic, where transparent HTA processes were sidelined in favor of emergency use authorizations from regulators operating under the “rule of rescue” for approvals of therapeutics, diagnostics, and vaccines (Reference O’Rourke, Orsini and Guerino23). Provisional approvals granted to COVID-19 vaccines were largely successful. However, accelerated approval of many COVID-19 therapeutics, such as emergency authorization given to remdesivir and hydroxychloroquine, were not as successful, with both shown to be either ineffective or harmful after the assessment of real-world data (RWD) (Reference Chalkidou, Walker and Sullivan24;Reference Singh, Ryan, Kredo, Chaplin and Fletcher25).

Appropriate use of this pathway requires confirmatory trials to be conducted in a timely fashion, using clinically meaningful and validated endpoints, such as overall survival; however, currently, many of these trials are not completed and often it is difficult to remove a drug once it has become available (Reference Beaver, Howie and Pelosof26;Reference Omae, Onishi, Sahker and Furukawa27). Accelerated access could also be used to incentivize innovation and improve healthcare efficiency by providing early patient access to nondrug technologies including new devices, diagnostics, and digital technologies.

Multicriteria decision analysis

The full range of benefits of innovative technologies may not be captured with the reliance on the use of traditional HTA criteria such as objective comparative measures to determine the approval of new technologies (Reference Gongora-Salazar, Rocks, Fahr, Rivero-Arias and Tsiachristas28;Reference Wahlster, Goetghebeur, Kriza, Niederländer and Kolominsky-Rabas29). The weighting of HTA criteria in the assessment process is often unclear, and innovative technologies may not be funded if evidence of clinical benefit and cost-effectiveness is lacking or insufficient for an investment decision. Decision making can also vary between stakeholders with different perspectives on the benefits of certain medical innovations. These limitations may be overcome with the use of MCDA, a tool that identifies and weighs the attributes of alternative options from multiple stakeholder perspectives. MCDA supports healthcare decision making through the construction of explicit criteria with associated scores or weightings, then ranking, rating, or making pairwise comparisons, ultimately combining multiple factors into a single value (Reference Howard, Scott, Ju, McQueen and Scuffham30). As such, criteria can be selected, structured, and then weighted to describe aspects of innovation. For example, Howard et al. defined innovation as a “novel technology not previously used in health care or a totally new indication (or use) of an existing technology, and gave decision makers three discrete choices for the technology in question:

1. (i) not innovative: equivalent technology is available or no significant iteration of existing technology;

2. (ii) incremental innovation: substantial iteration of existing technology or new indication of existing technology; and

3. (iii) substantial innovation: new technology” (Reference Howard, Scott, Ju, McQueen and Scuffham30).

A recent systematic review of MCDAs identified twenty-two different, context-specific criteria that varied according to whether they were used for priority setting or informing clinical or regulatory decision making. Common criteria used were safety, cost and budget impact, quality of care, health outcomes, feasibility, and acceptability. Innovation was seldom used as a criterion (~10 percent), but when it was used, it was in the context of priority setting (Reference Gongora-Salazar, Rocks, Fahr, Rivero-Arias and Tsiachristas28). The use of MCDA has increased in recent years; however, transparency and quality may currently be lacking in its application in the decision-making process. Standardization of MCDA methodology, reporting and selection of criteria according to the intended context (i.e., clinical or regulatory decision making) would improve transparency and enable comparisons across health systems, although defining the type and number of criteria used will depend on the context that the MCDA is intended to be used for (Reference Gongora-Salazar, Rocks, Fahr, Rivero-Arias and Tsiachristas28). MCDA informs stakeholder preferences for early innovation and may expedite early access to beneficial innovations, with a full HTA to follow with the development of evidence. By explicitly contextualizing the MCDA criteria to address localized needs and priorities, MCDAs may add a level of nuance to funding decision making (Reference Wahlster, Goetghebeur, Kriza, Niederländer and Kolominsky-Rabas29). However, more needs to be done to standardize MCDA frameworks, whether they are designed for specific disease areas or general use (Reference Fens, van Puijenbroek and Postma22). See background paper for further details (Reference Syeed, Poudel, Ngorsuraches, Diaz and Chaiyakunapruk11).

Horizon scanning

The role of HS was discussed at length at the 2019 APF as a means of reducing uncertainty, enabling planning to facilitate appropriate adoption of health technologies, and providing a degree of future-proofing for health systems (Reference Mundy, Trowman and Kearney31). Four members of the APF are active members of the HS network International HealthTechScan (formerly EuroScan International Network): Malaysia, Singapore, Taiwan, and South Korea, using HS to inform on new and emerging, innovative health technologies as well as identifying new uses for existing technologies. HS allows policy makers to anticipate and plan, optimizing investment decision making to ensure the successful adoption and implementation of potentially disruptive technologies (Reference Packer, Gutierrez-Ibarluzea and Simpson32) such as gene and cellular therapies, and oncological pharmaceuticals (Reference Daruwalla, Kambhammettu, Chainani, McKeering and Bhattacharjee33).

An early assessment capability can also respond to demand signaling by actively identifying the needs and key priorities/challenges of a health service, especially scanning and mapping groups of technologies in a clinical care pathway rather than just single technologies. By providing an early assessment of the evidence for new technologies, HS can also feed into MEAs or accelerated access where technologies appear to be beneficial to patients, but robust evidence is lacking to support its full introduction into the health system.

By accelerating policy development and access to health technologies, HS has the potential to provide the link between research and development, speeding up the time to public reimbursement of health innovations (Reference Wang, Rattanavipapong and Teerawattananon34).

Many of these approaches emphasize the importance of building links between all steps of health technology development: linking industry research and development to academia and HTA, and finally regulators, policy makers and the health system.