Discussions at the Health Technology Assessment International (HTAi) Asia Policy Forum (HAPF) aimed to understand the meaning of “high-cost technologies,” and to explore mechanisms to increase access to these technologies in publicly funded health systems in the Asia region.

Discussions and presentations at the 2018 HAPF, informed by a literature review and a premeeting survey of HTA agencies and industry, form the basis of this paper.

Challenges payers in the public health system face when investing in high-cost technologies include a lack of data, especially real-world data, affordability, and the budgetary impact of high-cost technologies. Managed entry schemes (MES) are one means to enable earlier access to high-cost technologies, or at reduced cost to the system. Most countries surveyed had used an MES to introduce a new health technology and most industry representatives had experience with financial-based MES, such as discounts or rebates, with most put in place to increase access to pharmaceuticals. Little experience of outcome-based or evidence-generation MES was reported.

Although it is early days in the implementation of MES in Asia, they have the potential to play an important role enabling access to new, mainly pharmaceutical, health technologies. The development of a “road map” of MES in the region should outline the intent and need for a MES, articulating the “rules of engagement” for all stakeholders—patients, providers, payers, and industry—which will assist countries to clearly identify the problem trying to be solved, and how an MES can be part of the solution.

Canada has a long history of the use of clinical evidence to support healthcare decision making. Given improvements in data holdings and analytic capacity in Canada and stakeholder interest, the purpose of this study is to reflect on perceptions of the value of real-world evidence in pricing and reimbursement decisions, barriers to its optimal use in pricing and reimbursement, current initiatives that may lead to its increased use, and what role the pharmaceutical industry may play in this.

To capture stakeholder perceptions, ninety-one participants identified as key stakeholders were identified according to background roles and geography and invited to participate in four round table discussions conducted under Chatham House rule. Important themes emerging from these discussions included: (i) the need to understand what “real world” evidence means; (ii) barriers to using real world evidence from differences in access, governance, inter-operability, system structures, expertise, and quality across Canadian health systems; (iii) differing views on industry's role.

The use of real-world data in Canada to inform pricing and reimbursement decisions is far from routine but nascent and slowly increasing. Barriers, including interoperability concerns, may also apply to other federated health systems that need to focus on the networking of healthcare administrative data across provincial jurisdictional boundaries. There also appears to be a desire to see better use of pragmatic trials linked to these administrative data sets. Emerging initiatives are under way to use real world evidence more broadly, and include identification of common data elements and approaches to networking data.

As healthcare decision makers continue to face challenges in health services delivery to their patients, disinvestment programs are being established for a sustainable healthcare system. This study aimed to collect data and information by means of a survey of disinvestment candidates and ongoing disinvestment projects in the health technology assessment (HTA) community.

An online survey was conducted to collect information on disinvestment candidates and activities from members of the Health Technology Assessment International Disinvestment & Early Awareness Interest Group, the EuroScan International Network and International Network of Agencies for Health Technology Assessment.

Among the 362 invitees, twenty-four unique responses were received, and almost 70 percent were involved in disinvestment initiatives. The disinvestment candidates identified represented a range of health technologies. Evidence or signaling of clinical ineffectiveness or inappropriate use typically led to the nomination of disinvestment candidates. Health technology assessments and reassessments were usually conducted to evaluate the technology in question, and decisions usually led to the limited use of the technology. Barriers to disinvestment decisions included the strength of interest and advocacy groups, insufficient data for assessments, a systematic decision process and political challenges, while obstacles to their implementation were clinicians’ reluctance and insufficient funding and incentives.

The survey results suggested that disinvestment activities are occurring in the HTA community, especially in the public sector. Future research can further investigate the processes and methods used to reach and implement disinvestment decisions from our survey respondents and explore to form closer ties between the HTA and clinical communities.

Healthcare organizations have invested efforts on hospital-based health technology assessment (HB-HTA) and enterprise risk management (ERM) processes for novel systems to obtain more accurate data on which to base strategic decisions. This study proposes to analyze how HB-HTA and ERM processes can share personal resources and skills to achieve principles with value-oriented results.

Literature on ERM and HB-HTA and data from interviews with healthcare managers compose the research data sources, which were submitted to a qualitative data analysis. It was oriented to identify the association between ERM and HB-HTA application in hospitals and the common principles between both processes, in addition to proposing the capability to share personal resources between both teams in a matrix.

The common principles and personal background suggested for HB-HTA and ERM teams allowed the build of a matrix identifying how both teams can work in an integrated manner being more effective and value-oriented. The shared resource matrix reports how each professional (with a specific background) may interact with each activity associated to HB-HTA or ERM implementation guidelines.

The identification of common principles and capabilities between ERM and HB-HTA suggested advances with the literature from both research areas. The opportunity to share personal resources also contributes to the implementation of those processes in hospitals with less financial resources, approaching its own management to be more efficient with the care chain.

Very few practical frameworks exist to guide the formulation of recommendations at hospital-based health technology assessment (HTA) units. The objectives of our study were: (i) to identify decision criteria specific to the context of hospital-based health technologies and interventions, (ii) to estimate the extent to which the expert community agrees on the importance of the identified criteria, (iii) to incorporate the identified criteria into a decision-aid tool, and (iv) to illustrate the application of a prototype decision-aid tool.

Relevant decision criteria were identified using existing frameworks for HTA recommendations, our past experience, a literature search, and feedback from a survey of diverse stakeholders.

Based on the survey results, twenty-three decision criteria were incorporated into the final framework. We defined an approach that eschewed a scoring system, but instead relied on a visual means for arriving at a final recommendation, by juxtaposing the importance rating for each criterion against the results of the health technology assessment. For a technology to be approved, a majority of criteria considered important should also have received favorable findings.

We created a simple and practical decision-aid tool that incorporates all decision criteria relevant to a hospital-based HTA unit. With its ease of use and accessibility, our tool renders the subjective decision-making process more structured and transparent.

It is important to capture all health effects of interventions in cost-utility analyses conducted under a societal or healthcare perspective. However, this is rarely done. Household spillovers (health effects on patients’ other household members) may be particularly likely in the context of technologies and interventions to change behaviors that are interdependent in the household. Our objective was to prospectively collect outcome data from household members and illustrate how these can be included in a cost-utility analysis of a behavior change intervention in chronic obstructive pulmonary disease (COPD).

Data were collected from patients’ household members (n = 153) alongside a randomized controlled trial of a COPD self-management intervention. The impact of the intervention on household members’ EQ-5D-5L scores (primary outcome), was evaluated. Analyses were then carried out to estimate household members’ quality-adjusted life-years (QALYs) and assess the impact of including these QALYs on cost-effectiveness.

The intervention had a negligible spillover on household members’ EQ-5D-5L scores (−0.007; p = .75). There were also no statistically significant spillovers at the 5 percent level in household member secondary outcomes. In the base-case model, the inclusion of household member QALYs in the incremental cost-effectiveness ratio (ICER) denominator marginally increased the ICER from GBP 10,271 (EUR 13,146) to GBP 10,991 (EUR 14,068) per QALY gained.

This study demonstrates it is feasible to prospectively collect and include household members’ outcome data in cost utility analysis, although the study highlighted several methodological issues. In this case, the intervention did not impact significantly on household members’ health or health behaviors, but inclusion of household spillovers may make a difference in other contexts.

Indirect comparisons via a common comparator (anchored comparisons) are commonly used in health technology assessment. However, common comparators may not be available, or the comparison may be biased due to differences in effect modifiers between the included studies. Recently proposed population adjustment methods aim to adjust for differences between study populations in the situation where individual patient data are available from at least one study, but not all studies. They can also be used when there is no common comparator or for single-arm studies (unanchored comparisons). We aim to characterise the use of population adjustment methods in technology appraisals (TAs) submitted to the United Kingdom National Institute for Health and Care Excellence (NICE).

We reviewed NICE TAs published between 01/01/2010 and 20/04/2018.

Population adjustment methods were used in 7 percent (18/268) of TAs. Most applications used unanchored comparisons (89 percent, 16/18), and were in oncology (83 percent, 15/18). Methods used included matching-adjusted indirect comparisons (89 percent, 16/18) and simulated treatment comparisons (17 percent, 3/18). Covariates were included based on: availability, expert opinion, effective sample size, statistical significance, or cross-validation. Larger treatment networks were commonplace (56 percent, 10/18), but current methods cannot account for this. Appraisal committees received results of population-adjusted analyses with caution and typically looked for greater cost effectiveness to minimise decision risk.

Population adjustment methods are becoming increasingly common in NICE TAs, although their impact on decisions has been limited to date. Further research is needed to improve upon current methods, and to investigate their properties in simulation studies.

Timely access to innovative medical technologies driven by accelerated patient access pathways can substantially improve the health outcomes of patients who often have few therapeutic alternatives. We analyzed lead-times for the medical procedure reimbursement coverage process undertaken in South Korea from 2014 to 2017, which is considered one of the most important factors contributing to delays in patient access to new medical technologies.

This analysis was performed using the open datasets source of “Medical Procedure Expert Evaluation Committee (MPEEC)” meeting results and medical procedure coverage application information published on the Health Insurance Review and Assessment Service Web site.

From 2014 to 2017, 90 percent of all new coverage determinations took on average >250 days with almost 20 percent taking more than 2 years (>750 days), The average lead-time from the medical procedure coverage application to MPEEC meeting in 2015 was 435.0 ± 214.7 days (n = 26), which was significantly shorter than the average lead-time in 2014 (624.9 ± 290.3 days, n = 16) (p < .05). The average lead-time from application to official enforcement in 2015 was significantly shorter than that of 2014 (540.8 ± 217.4; n = 16 versus 734.1 ± 299.7 days; n = 26, respectively) (p < .05).

While this analysis showed a general trend of a reduction in the time taken to receive a positive coverage determination for a new medical technology, the average lead-time remains well over the government mandated 100 days. To continue this trend and further enhance the patient access pathway for medical procedure coverage determinations, some measures can be applied. In particular, the extended “One-Stop Service” program encompassing coverage determinations is one such recommendation that could be considered.

There is little evidence in China regarding the cost-effectiveness of non-invasive prenatal testing (NIPT) for Down syndrome (DS). This study aims to evaluate the cost-effectiveness of NIPT and provide evidence to inform decision-making.

To determine the cost-effectiveness of NIPT for DS, a decision-analytic model was developed using the TreeAge Pro software from a societal perspective in a simulated cohort of 10 000 pregnant women. Main indicators were based on field surveys from sampled hospitals in four locations in China and a literature review.

The conventional maternal serum screening (CMSS) strategy, contingent screening strategy (NIPT delivered to high risk pregnant women after CMSS), and universal screening strategy could prevent 3.02, 7.53, and 9.97 DS births, respectively. NIPT would decrease unnecessary invasive procedures, resulting in fewer procedure-related miscarriages. The cost-effectiveness ratio of the contingent screening strategy was the lowest. When compared with the CMSS strategy, the incremental cost per DS birth averted by the contingent screening strategy and universal screening strategy were USD 20,160 and 352,388, respectively. One-way sensitivity analysis showed that, if the cost of NIPT could be decreased to USD 76.92, the cost-effectiveness ratio of the universal screening strategy would be lower than the CMSS strategy.

Although NIPT has the merits of greater effectiveness and safety, CMSS is unlikely to be replaced by NIPT at this time because of NIPT's higher cost. Contingent screening may be an appropriate strategy to balance the effectiveness and cost factors of the new genetic testing technology.

Neuroendocrine tumors (NETs) are rare, slow-growing malignant tumors. So far, there are no data on patient preferences regarding its therapy. This empirical study aimed to elicit patient preferences in the drug treatment of NET.

Based on qualitative patient interviews and an analytic hierarchy process, six patient-relevant attributes were analyzed and weighted using a discrete-choice experiment. Patients were recruited with the help of a NET support group. An experimental 3*3 + 6*3 –MNL design was created using NGene. The design consisted of eighty-four choices, divided into seven blocks. Participants were randomly assigned to these blocks. The analysis included random parameter logit and latent class models.

A total of 275 participants (51.6 percent female; mean age, 58.4 years) were included. The preference analysis within the random parameter logit model, taking into account the 95 percent confidence interval, showed predominance for the attribute “overall survival.” The attributes “response to treatment” and “stabilization of tumor growth” followed. The side effects “nausea/vomiting” and “diarrhea” were considered of relatively equal importance. Latent class analysis of possible subgroup differences revealed three preference patterns.

Preferences can influence therapeutic decisions. Preference analyses indicated that “overall survival” had the strongest influence, with participants clearly weighing outcome attributes higher than side effect attributes. In conclusion, mono-criterial decisions would not fully reflect patient perspectives.