In recent years, there has been a growing recognition that health equity and health inequalities should be a consideration in all aspects of research. Since the Commission on Social Determinants of Health by the World Health Organization was established in 2005, there has been a growing interest in tackling systemic differences in health outcomes, including expanding the scope to health research including evidence synthesis and health technology assessments (HTA). This analysis aims to identify health inequality and health inequity frameworks that exist to help structure and plan research methods in evidence synthesis.

A critical analysis of the existing frameworks used in evidence synthesis to address health inequality and/or inequity was undertaken. Comprehensive, systematic searching of seven social science electronic databases and grey literature was undertaken based on the Behavior/phenomenon of interest, Health context and Model/Theory (BeHEMoTh) model, from 1990 to May 2022 to identify all relevant studies. A narrative synthesis approach was used to critically appraise the existing frameworks.

Sixty-two reviews published between 2008 and 2022 reporting on using a framework to stratify health opportunities and outcomes met the inclusion criteria. Frameworks identified included the PROGRESS (place of residence, race or ethnicity, occupation, gender, religion, educational level, socioeconomic status, and social capital), PROGRESS-Plus (plus age, disability and sexual orientation) and Preferred Reporting Items for Systematic Reviews and Mata Analysis (PRISMA) – Equity checklist.

Currently, there does not seem to be consensus in how evidence of inequality or inequity in evidence synthesis or HTA are reported. As research interests in health inequality and inequity continue to grow, there is a need to develop a framework that provides an in-depth understanding of how inequalities in health and inequities in health should be considered within evidence synthesis and HTA. This will allow researchers to analyze not just the effects of interventions, but also how healthcare outcomes are impacted by inequalities or inequities.

In model-based economic evaluations, the effectiveness parameter is often informed by studies with a limited duration of follow-up, requiring extrapolation of the treatment effect over a longer time horizon. Extrapolation from short-term data alone may not adequately capture uncertainty in that extrapolation. This study aimed to use structured expert elicitation to quantify uncertainty associated with extrapolation of the treatment effect observed in a clinical trial.

A structured expert elicitation exercise was conducted for an applied study of a podiatry intervention designed to reduce the rate of falls and fractures in the elderly. A bespoke web application was used to elicit experts’ beliefs about two outcomes (rate of falls and odds of fracture) as probability distributions (priors), for two treatment options (intervention and treatment as usual) at multiple time points. These priors were used to derive the temporal change in the treatment effect of the intervention, to extrapolate outcomes observed in a trial. The results were compared with extrapolation without experts’ priors.

The study recruited thirty-eight experts (geriatricians, general practitioners, physiotherapists, nurses, and academics) from England and Wales. The majority of experts (32/38) believed that the treatment effect would depreciate over time and expressed greater uncertainty than that extrapolated from a trial-based outcome alone. The between-expert variation in predicted outcomes was relatively small.

This study suggests that uncertainty in extrapolation can be informed using structured expert elicitation methods. Using structured elicitation to attach values to complex parameters requires key assumptions and simplifications to be considered.

Threshold analysis is a novel statistical approach which can be used to investigate which direct comparisons in a network meta-analysis (NMA) have estimated relative effects that may not be robust to changes in the evidence, either due to possible bias, sampling variation, or relevance.

In a health technology assessment of the clinical effectiveness of ablative and non-invasive therapies for patients with early hepatocellular carcinoma (HCC), we conducted a threshold analysis to identify treatment comparisons that would be sensitive to changes in the randomized controlled trial (RCT) evidence used in the NMAs, potentially leading to a change in the recommended treatment. The results of the threshold analysis were used to guide a targeted systematic review of high-quality, non-randomized, prospective comparative studies that could strengthen the evidence for those comparisons identified as sensitive to change.

We conducted NMAs of RCT evidence for four outcomes: overall survival (16 RCTs), progression-free survival (6 RCTs), overall recurrence (7 RCTs), and local recurrence (10 RCTs). The results of the NMAs displayed a high level of uncertainty, attributable to the sparse nature of the network, characterised by interventions being mainly compared in small trials. A targeted systematic review was conducted on relevant interventions that were identified as being sensitive to changes in evidence by the threshold analysis. The studies identified in this review were incorporated into a second NMA to support the RCT evidence.

Threshold analysis has been typically used as a tool to assess how robust comparisons in an NMA are to additional sources of evidence, but it can also be used to guide the search for additional non-randomized evidence when the available RCT evidence is sparse.

In spring 2020, The European network for Health Technology Assessment (EUnetHTA) decided to join forces to produce best evidence to inform health policy in the COVID-19 pandemic. The objective of this paper is to describe the process and output of the coordinated and collaborative activities of EUnetHTA.

Relevant published and internal documents were retrieved for a descriptive analysis of EUnetHTA processes, methods, and outputs related to EUnetHTA’s response to the pandemic.

Process: In April 2020, a COVID-19 task force was set up and a survey collected pressing health policy questions across Europe. Two coordinating agencies for diagnostic tests and therapeutics were assigned. A process for prioritization and selection was set up for therapeutics, as well as explicit starting and stopping rules. Methodology: To increase a timely response, it was agreed that the rapid collaborative reviews (rapid CRs) would not require the consultation of manufacturers and the involvement of external experts, but would not differ in the methods and conduct of the systematic search, review, and synthesis of all available evidence, nor in the requirement for reviewing by EUnetHTA partners. Final reports: The joint effort resulted in the production of two rapid CRs on diagnostic tests, nineteen collaborative rolling reviews on therapeutics, three of which later moved to rapid CRs.

During COVID-19 pandemic, the EUnetHTA partners proved capable of prompt collaboration, which allowed speeding up the production and release of high-quality EUnetHTA outputs, while the relationships with the other European institutions facilitated their quick dissemination.

An increasing number of innovative therapies (e.g., gene- and cell-based treatments) have been developed in the past 20 years. Despite the significant clinical potential of these therapies, access delays may arise because of differing perspectives of manufacturers and payers regarding issues such as the value of the product, clinical and financial uncertainties, and sustainability.

Managed entry agreements (MEAs) can enable access to treatments that would not be reimbursed by conventional methods because of such concerns. However, although MEA typologies exist, there is currently no structured process to come to agreements on MEAs, which can be difficult to decide upon and implement.

To facilitate more structured MEA negotiations, we propose a conceptual “value-based negotiation framework” with corresponding application tools.

The framework was developed based on an iterative process of scientific literature review and expert input.

The framework aims to (i) systematically identify and prioritize manufacturer and payer concerns about a new treatment, and (ii) select a mutually acceptable combination of MEA terms that can best address priority concerns, with the lowest possible implementation burden.

The proposed framework will be tested in practice, and is a step toward supporting payers and manufacturers to engage in more structured, transparent negotiations to balance the needs of both sides, and enabling quicker, more transparent MEA negotiations and patient access to innovative products.

Patient involvement in health technology assessment (HTA) has documented advantages, such as improved understanding of disease context, and increased legitimacy and transparency of the HTA process. In the absence of clear metrics, thresholds, or criteria, it is not clear how input regarding patient preferences influences HTA based recommendations of the pan Canadian Oncology Drug Review (pCODR).

This is a concurrent complementary mixed methods study. A quantitative model (logit) is used to estimate the impact of patient input and other HTA criteria on pCODR recommendations. A qualitative analysis of semi-structured interviews with Canadian HTA committee members is used to describe the mechanisms of action through which patient input influences recommendations.

Patient input was considered important in providing context to the HTA discussion, but committee members were not able to explicate how any specific elements of patient submissions weighted into the committee’s recommendation. There was an element of mistrust in the patient input data. The estimated impact of patient input on funding recommendations is not statistically significant, recommendations remain driven by evidence of clinical benefit.

The commitment to inclusion of patient perspectives in HTA in Canada is strong, and procedurally Canada is among the leaders in this regard. The tangible impact of patient input could be increased with an improved system for collection of most relevant data, and clear guidelines about how patient input should weigh into HTA recommendations.

Argentina has a fragmented healthcare system with social security covering almost two thirds of the population. Its benefit package—called compulsory medical program (PMO; by its Spanish acronym Programa Médico Obligatorio)—has not been formally and widely updated since 2005. However, laws, clinical practice guidelines (CPGs), and a high-cost technology reimbursement fund complement it. Our objective was to comprehensively review such a PMO and propose an update considering the corresponding complementary sources.

We followed four steps: (i) identification of health technologies from the current PMO and complementary sources, (ii) prioritization, (iii) assessment through rapid health technology assessment (HTA), and (iv) appraisal and recommendations. We evaluated three value domains: quality of evidence, net benefit, and economics, which were summarized in a five-category recommendation traffic-light scale ranging from a strong recommendation in favor of inclusion to a strong recommendation for exclusion.

Eight hundred fifty technologies were identified; 164 of those, considered as high priority, were assessed through rapid HTAs. Those technologies mentioned in laws and CPGs were mostly outpatient essential medicines, whereas those from the reimbursement system were mostly high-cost drugs; of these 101 technologies, 50 percent were recommended to be kept in the PMO. The other 63 (identified by the Superintendence of Health Services, technology producers, and patients) were mostly medical procedures and high-cost drugs; only 25 percent of those resulted in a favorable recommendation.

A methodology based on four clearly identified steps was used to carry out a comprehensive review of an outdated and fragmented benefit package. The use of rapid HTAs and a traffic-light recommendation framework facilitated the deliberative evidence-based update.

Health technology assessment (HTA) is defined as a multidisciplinary field of policy research that provides evidence on the consequences of adopting and using health technologies. A ministry of health with jurisdiction over HTA should determine the influence of public law on all HTA-related activities and the rules that apply. Therefore, health decision-makers interested in HTA must learn to navigate the legal system, starting by situating it in the legal apparatus of the country. As a result, establishing a national HTA system requires designing a legal pathway towards HTA. However, a historic overview of HTA, in the context of policy documents of Ethiopia is not clearly reported. Therefore, this review is warranted to understand the historic overview of HTA in the context of health policy documents of Ethiopia.

A review of online policy documents was conducted in advanced Google Scholars and websites of the Ministry of Health (MoH) of Ethiopia. Some of the policy documents were also obtained through contacting experts at MoH. The review findings were organized into six categories.

Regulatory documents have emphasized the approval of new health technologies before selecting health technologies. Health Policy of Ethiopia and the Directive on Medical Equipment also clearly stated the importance of institutionalizing HTA and establishing HTA organizations. Additionally, the National Medical Device Policy clearly indicated the importance of establishing an HTA advisory team at MoH. Similarly, the Health Sector Transformation Plan II (HSTP II) stressed the need to build a national capacity to conduct HTA. Even though policy statements on HTA appear scattered across different policy documents, they were not put into a national HTA system.

It is important to refer to policy statements outlined in different policy documents when establishing a national HTA system in Ethiopia. Also, attention should be given to the development of policy documents related to HTA guidelines, strategic documents in HTA, and policy documents that can link HTA results to policy-making.

The healthcare sector in the Asia Pacific (APAC) region is in a period of rapid growth and exciting innovation. This has led to an increase in the number of APAC countries adopting and implementing health technology assessment (HTA) to assess the clinical, ethical, economic, and societal aspect of healthcare technology. The aim of this study is to provide an updated snapshot of the status of HTA and key differences in selected countries of APAC region.

HTA robustness and gap requirements, including its structure, process, use in decision-making and resource allocation processes were assessed through a review of published and gray literature for each of the selected country. A qualitative analysis was carried out by using a set of 15 principles of an International Working Group for HTA Advancement to identify the robustness and key differences in HTA based decision-making process in scoping countries.

The finding of this study reveals that maturity of HTA determined by country-specific factors, such as presence of independent HTA agency, healthcare funding and expenditure, etcetera, and varies across the high-, middle-, and low-income countries of APAC region. Based on the study’s results, HTA ecosystem of selected countries categorized into rising HTA followed by advancing and mature HTA categories. In addition to the differences in HTA structure, the influence of stakeholder engagement differs among HTA bodies. The variation in the time frame of HTA decisions was significant among countries, with a general lack of awareness and transparency among health policy decision-makers and resulted in longer time for assessment for rising HTA category compared to the advance and mature HTA categories.

The vision of a comprehensive and robust HTA system can be achieved by implementing a transparent, independent, decision-making, and strongly integrated HTA process in the region. We recommend that efforts should be directed to promote a transparent and sustainable HTA, throughout the low- and middle-income countries of APAC region which eventually, lead to more effective HTA ecosystem.

The National Institute for Health and Care Excellence’s (NICE) method guide for technology appraisals (TAs) encourages medicine manufacturers to use the EuroQol 5 Dimensions (EQ-5D) in relevant clinical trials to obtain utility values; however, the EQ-5D may have low sensitivity when compared to disease-specific measures. This study investigated whether the NICE TA committee’s acceptance of manufacturer-proposed utility values is dependent on the manufacturers’ sources of the utility values.

Using publicly available data for 2011–2020, we identified 136 single TAs of cancer medicines, the health-related quality-of-life-measures used in relevant clinical trials, manufacturers’ sources of utility values, and the NICE TA committee’s acceptance of these values. Fisher’s exact tests were performed to compare the acceptability of different value sources and reasons for non-acceptance.

The number of appraisals for which the EQ-5D in the relevant clinical trials was the source of the manufacturer-proposed utility values increased continuously over time. The TA committee’s acceptance of values was not dependent on the information source. In cases where a submission for which the information source was the EQ-5D was rejected, the reason was generally related to inappropriate values for the UK population or inappropriate data adjustment, not data reliability.

Our results demonstrated that according with the NICE’s method guide regarding utility values does not guarantee acceptance by the TA committee. Manufacturers must consider in advance possible differences between their clinical trials and clinical practice in the UK and refine plans for EQ-5D measurement in order to obtain convincing evidence.

While ethics has been identified as a core component of health technology assessment (HTA), there are few examples of practical, systematic inclusion of ethics analysis in HTA. Some attribute the scarcity of ethics analysis in HTA to debates about appropriate methodology and the need for ethics frameworks that are relevant to local social values. The “South African Values and Ethics for Universal Health Coverage” (SAVE-UHC) project models an approach that countries can use to develop HTA ethics frameworks that are specific to their national contexts.

The SAVE-UHC approach consisted of two phases. In Phase I, the research team convened and facilitated a national multistakeholder working group to develop a provisional ethics framework through a collaborative, engagement-driven process. In Phase II, the research team refined the model framework by piloting it through three simulated HTA appraisal committee meetings. Each simulated committee reviewed two case studies of sample health interventions: opioid substitution therapy and either a novel contraceptive implant or seasonal influenza immunization for children under five.

The methodology was fit-for-purpose, resulting in a context-specified ethics framework and producing relevant findings to inform application of the framework for the given HTA context.

The SAVE-UHC approach provides a model for developing, piloting, and refining an ethics framework for health priority-setting that is responsive to national social values. This approach also helps identify key facilitators and challenges for integrating ethics analysis into HTA processes.

With ever increasing burden of disease and limited resources, health technology assessment (HTA) is required for efficient resources allocation and priority setting in healthcare. The objective of this study was to establish the baseline HTA evidence generation and use in Zimbabwe.

In 2019, we convened a stakeholder workshop on HTA at the University of Zimbabwe. Presentations on HTA processes, current healthcare reimbursement model, priority setting in the Ministry of Health and selection of medicines into the treatment guidelines, were done by the experts. We adapted the Health Intervention and Technology Assessment Program questionnaire for situational analysis of HTA introduction at national level and administered it among the workshop participants. We report the baseline information on HTA situation, the need, demand and supply of HTA in Zimbabwe obtained from the presentations and responses from workshop participants.

A total of 33 participants attended the workshop. Participants indicated that there is no formal HTA agency or process in Zimbabwe. The selection of medicines into treatment guideline is determined by disease burden, safety, efficacy and cost data, and it is done by a group of experts. The Association of Healthcare Funders of Zimbabwe (AFHOZ) reported that private healthcare funders use resource-based relative value scale system to determine tariffs and reimbursement levels. The regulator requires safety, efficacy and product quality data for the registration of medicines. Transparency in decision-making, registration of heath technology and formulation of essential medicines and treatment guidelines were reported as the major needs of HTA. The major users of HTA outputs were reported as medicines regulator, AFHOZ and Ministry of Health. Key suppliers of HTA evidence are academic and clinical research institutions and healthcare workers. Lack of training in health economics was cited as the major challenge to supply of HTA evidence.

There is a need to institute a formal, systematic and transparent processes of determining value of health technologies.

An iterative, life-cycle approach to the evaluation of healthcare technologies requires that clinical and economic evidence is collected since the initial stages of diffusion. Nevertheless, early cost-effectiveness models are challenging mainly due to the difficulties in estimating model parameters and faithfully characterizing parameter uncertainty. This is especially true with AI-based diagnostics, where attribution of effects on costs and patient-relevant outcomes is more challenging. Empirical applications of early-models are useful to identify the main challenges of iterative modelling and provide recommendations on best-practices. Here, we reported on a case study on a machine learning-derived hypotension predictive index (HPI), that predicts the onset of intraoperative hypotension and trigger corrective measures.

A hybrid decision-tree/Markov model was developed comparing an HPI-based intervention protocol to standard-of-care intervention protocol during gynecological procedures. A short-term component of the model was populated using data from individual patients collected at one hospital in Italy. An historical control group was also defined using propensity score matching. Long-term costs and consequences of HPI were modelled using secondary data. A probabilistic version of the headroom approach was used to determine the maximum achievable price of HPI based on available evidence. Value of Information analysis was also conducted to identify the parameters that contribute the most to the overall uncertainty, and to identify optimal future study designs. Extensive deterministic and probabilistic sensitivity analyses were conducted to characterize the uncertainty over the cost-effectiveness of HPI.

The preliminary results of the analysis suggest that HPI has potential to improve patients’ outcomes and generate efficiency gains by reducing hypotension events and permanent complications, such as acute kidney injury. The link between reduction in hypotension and the rate of complications, or the long-term effects on healthcare costs and patients’ quality of life are the parameters that contribute the most to model uncertainty.

Early cost-effectiveness models are a valuable tool to inform further product development and evidence requirements, but characterization of uncertainty and transparency in modelling assumptions are key.

Scientific literature debates on the economic affordability of transcatheter aortic valve implantation (TAVI) in order to give a useful support to decision makers aiming at establishing a reimbursement scheme for TAVI. For this reason, it is important to assess the quality and the generalizability of the existing economic evidences.

The first step was to run a literature search according to a predefined population, intervention, comparator, and outcome on the cost and effectiveness of the TAVI procedure in comparison to medical therapy and traditional surgery. Second, a manual search was carried out on the Web sites of the main HTA agencies. Third, the checklist developed by Augustovski et al. was applied in order to assess the quality and the generalizability of the articles resulting from the selection process.

Overall, 106 articles were obtained. Of these, sixty-five articles were excluded since the title was not consistent with the objective. Further selection took place after abstract and full-text reading. In the end, thirty-one documents were included for the review. According to the checklist, none of the articles was considered generalizable and only one was considered transferable which compares the TAVI procedure with Medical Management in inoperable patients.

Despite the overall quality of the selected studies was considered good, there is still a lack of evidence on whether evidences generated in different contexts can be considered generalizable. Further research on resource consumption and preferences is needed in order to provide decision makers with more robust evidences.

Extrapolation is often required to inform cost-effectiveness (CE) evaluations of immune-checkpoint inhibitors (ICIs) since survival data from pivotal clinical trials are seldom complete. The objectives of this study were to evaluate the accuracy of estimates of long-term overall survival (OS) predicted in French CE assessment reports of ICIs, and to identify models presenting the best fit to the observed long-term survival data.

A systematic review of French assessment reports of ICIs in the metastatic setting since inception until May 2020 was performed. A targeted literature review was conducted to collect associated extended follow-up of randomized controlled trials (RCTs) used in the CE assessment reports. Difference between projected and observed OS was calculated. A range of standard parametric and spline-based models were applied to the extended follow-up data from the RCT to determine the best-fitting survival models.

Of the 121 CE assessment reports published, 11 reports met the inclusion criteria. OS was underestimated in 73 percent of the CE assessment reports. The mean relative difference between each source was −13 percent (median: −15 percent; IQR: −0.4 to 26 percent). Models providing the best fit were those that could reflect nonmonotonic hazards.

Based on the available data at the time of submission, longer-term survival of ICIs was not fully captured by the extrapolation models used in CE assessments. Standard and flexible parametric models which can capture nonmonotonic hazard functions provided the best fit to the extended follow-up data. However, these models may still have performed poorly if fitted to survival data available at the time of submission to the French National Authority for Health.

Artificial intelligence (AI) is seen as one of the major disrupting forces in the future healthcare system. However, assessment of the value of these new technologies is still unclear and no agreed international HTA-based guideline exists. Therefore, a Model for ASsessing the value of AI (MAS-AI) in medical imaging was developed by a multidisciplinary group of experts and patient representatives.

The MAS-AI guideline is based on four steps. First a literature review of existing guides, evaluations, and assessments of the value of AI in the field of medical imaging (5,890 studies were assessed with 86 studies included in the scoping review). Next, interviews with leading researchers in AI in Denmark. The third step was two workshops where decision-makers, patient organizations and researchers discussed crucial topics when evaluating AI. Between workshops, the multidisciplinary team revised the model according to comments from workshop-participants. Last step is a validation workshop in Canada.

The MAS-AI guideline has three parts. There are two steps covering nine domains and then advises for the evaluation process. Step 1 contains a description of patients, how the AI-model was developed, and initial ethical and legal considerations. Finishing the four domains in Step 1 is a prerequisite for moving to step 2. In step 2, a multidisciplinary assessment of outcomes of the AI-application is done for the five remaining domains: safety, clinical aspects, economics, organizational aspects and patient aspects. The last part, is five advices to facilitate a good evaluation process.

We have developed an HTA based framework to support the prospective phase while introducing novel AI technologies into healthcare in medical imaging. MAS-AI can assist HTA organizations (and companies) in selecting the relevant domains and outcome measures in the assessment of AI applications. It is important to ensure uniform and valid decisions regarding the adoption of AI technology with a structured process and tool. MAS-AI can help support these decisions and provide greater transparency for all parties involved.

Artificial intelligence (AI)-supported technologies are rapidly developing and have the potential to improve healthcare quality at reduced cost. However, few examples exist of successfully deployed AI-technologies in a real-world context that have been adequately assessed. Therefore, the objective of this research is to: (i) identify existing health technology assessment (HTA) methods developed or adapted to assess AI-supported health technologies, (ii) identify new assessment topics or domains relevant for AI-technology uptake, and (iii) take the first step in developing a framework applicable for new challenges that emerge with the introduction of AI.

A systematic literature review of studies describing methods or frameworks to assess AI-supported health technologies was performed on PubMed from January 2010 until February 2021. Furthermore, a web page search of international HTA agencies and international organizations such as the World Health Organization, Organziation for Economic and Co-ordination and Development, and the European Commission was performed to identify important aspects to consider when implementing and assessing AI technologies.

No assessment frameworks for AI technologies were identified from the systematic literature review or web page searches of international HTA agencies. Reports from international organizations highlight limitations or inability of most AI technologies to ‘explain’ their decision-making process (black box issue), leading to lack of trust in the technology that affects its adoption. It is recommended to put more emphasis on assessing transparency and ‘explainability’ of the AI solution as well as aspects of safety, ethical, legal, and social issues related to implementation and the development/training phase of the AI technology.

The results from this study uncover key gaps in frameworks posed for performing a systematic and holistic assessment of AI in a real-world context of health care. However, valuable information on relevant assessment aspects for AI-supported technologies have been identified.

The results will form the basis for the development of a framework to assist decision-makers in assessing AI-supported technologies in a holistic manner for a responsible deployment – the HTA AI Framework.

To undertake a technical review of the search interface of the ISPOR Presentations Database. By technical review, we mean an evaluation of the technical aspects of the search interface and functionality, which a user must navigate to complete a search.

A validated checklist (Bethel and Rogers, 2014, Health Info Libr J, 31, 43-53) was used to identify where the interface performed well, where the interface was adequate, where the interface performed poorly, where functionality available in core biomedical bibliographic databases does not exist in the ISPOR database, and to establish a list of any issues arising during the review. Two researchers independently undertook the technical review in October 2021.

The ISPOR database scored 35 of a possible 165 (27/111 essential criteria and 8/54 desirable criteria). Two issues arising were identified, both of which will cause searchers to miss potentially eligible abstracts: (i) that search terms, which include * or ? as truncation or wildcard symbols should not be capitalized (e.g., cost* not Cost*; organi?ation not Organi?ation) and (ii) that quotation marks should be straight sided in phrase searching (e.g., “cost analyses” not “cost analyses”).

The ISPOR database is a promising and free database to identify abstracts/posters presented at ISPOR. We summarize two key issues arising, and we set out proposed changes to the search interface, including: adding the ability to export abstracts to a bibliographic tool, exporting search strategies, adding a researcher account, and updating the help guide. All suggestions will further improve this helpful database.

Fecal incontinence (FI) is the involuntary loss of feces and can affect up to 17 percent of community dwelling individuals, rising to 40 percent of older people in residential care homes. There is limited up-to-date evidence which formally set research priorities addressing FI. This project aimed to identify research topics of highest importance to key FI stakeholders.

An evidence gap map was produced incorporating three streams of evidence coded against predefined topic domains. The evidence streams included: emerging evidence identified through horizon scanning; existing evidence identified through systematic searches of bibliographic databases; and key FI stakeholder insights collected through an international survey. Findings were presented as a visual map to facilitate knowledge exchange during an online workshop with a purposeful sample of multidisciplinary stakeholders. The identified gaps in research were explored to see whether they were deemed representative of unmet needs, and as such, areas of priority to key FI stakeholders. Ideation techniques and group discussions were used to refine and rank priority areas.

Overall, there was a mismatch between the existing and emerging evidence, and the priorities of key FI stakeholders. New pharmaceutical and medical technology innovations were limited. Eight percent of early-stage trials identified were concerned with the use of repurposed drugs. Within the existing evidence base, individual bowel management strategies and treatments were examined, however, key FI stakeholders desired interventions to improve patient education and the psychological aspects of living with FI. The five priority topics identified in order of importance are as follows: psychological support; lifestyle interventions; long-term effects; education; and constipation.

The robust methodology used to identify priority topics were successful in identifying broad and wide-ranging areas of importance to key stakeholders. The evidence gap map was a useful visual tool to facilitate knowledge exchange and highlight where research efforts have been focused historically, identifying a mismatch between the existing evidence base and what stakeholders consider important.

The aim of this article is to describe the process, results, and experiences of European Network for Health Technology Assessment (EUnetHTA) Joint Action 3’s (JA3) Early Dialogue (ED) activities and to highlight opportunities for improving the processes.

A descriptive analysis of the steps of the EUnetHTA ED process and evaluation of the data from the EDs conducted by EU health technology assessment (HTA) bodies, published guidelines, and documents, as well as internal statistics.

In JA3, an Early Dialogues Working Party (EDWP) was established, responsible for developing and improving processes and providing advice to pharmaceutical companies, supported by the ED Secretariat. From June 2017 to May 2021, 113 requests for pharmaceutical EDs were received and 38 conducted. The process was continuously optimized, and different approaches for involving patients were tested. Finally, a centralized procedure was chosen with the key documents produced by two responsible agencies and reviewed by the EDWP. Patient involvement was primarily done by interviewing a national patient representative to obtain general feedback on the disease and the planned study design.

During JA3, EDs were established as an efficient, successful product. Pharmaceutical companies benefited not only from the positions of the individual agencies for the national HTA, but also from the recommendations that were common to all HTA authorities. In addition, regarding the European HTA Regulation, it will be important to conduct Joint Scientific Consultations with a view toward future Joint Clinical Assessments and to further develop processes aligned with the high demand for consultation.