Demand for transcatheter aortic valve implantation (TAVI) has increased in the last decade and has outpaced system capacity, impacting wait times and bringing undesirable health outcomes such as waitlist mortality and number of urgent procedures. Risk-based prioritization can improve equitable access to patients. In this study, we assess the impacts of different classifications and wait times for each risk group on health outcomes.

We developed decision-analytic models that simulate the patient trajectory from referral to completion of TAVI. Using prediction models that can classify patients based on their risk of adverse events on the waitlist, we assessed the impacts of (i) the number of risk groups, (ii) size of the risk groups, and (iii) recommended wait times for each risk group, on waitlist mortality, hospitalization, and the proportion of urgent TAVIs. All scenarios were modeled under the same resource constraints, allowing us to explore the trade-offs between faster access to prioritized patients and deferred access to nonprioritized groups.

Increasing the number of risk groups from two to three, increasing the sizes of the higher-risk groups from five percent to 30 percent of the cohort each, and providing faster access to the higher-risk groups (five to three weeks for high-risk and 11 to five weeks for medium-risk) achieved the greatest reductions in mortality, hospitalizations, and urgent TAVIs (relative reductions of up to 29%, 23%, and 38%, respectively). However, this occurs at the expense of excessive wait times in the nonprioritized group (up to 25 weeks). The reduction in adverse events was lower when the nonprioritized group had more reasonable wait times.

When developing and implementing waitlist prioritization strategies, it is important to consider the resource constraints of the system and the patient profile, as the benefits of providing faster access to prioritized patients can lead to unreasonable wait times for nonprioritized ones. In settings with long wait times, prioritization initiatives must be followed by expansion of supply to achieve optimal improvements in health outcomes.

Artificial intelligence (AI)-based health technologies (AIHTs) have already been applied in clinical practice. However, there is currently no standardized framework for evaluating them based on the principles of health technology assessment (HTA).

A two-round Delphi survey was distributed to a panel of experts to determine the significance of incorporating topics outlined in the EUnetHTA Core Model and twenty additional ones identified through literature reviews. Each panelist assigned scores to each topic. Topics were categorized as critical to include (scores 7–9), important but not critical (scores 4–6), and not important (scores 1–3). A 70 percent cutoff was used to determine high agreement.

Our panel of 46 experts indicated that 48 out of the 65 proposed topics are critical and should be included in an HTA framework for AIHTs. Among the ten most crucial topics, the following emerged: accuracy of the AI model (97.78 percent), patient safety (95.65 percent), benefit–harm balance evaluated from an ethical standpoint (95.56 percent), and bias in data (91.30 percent). Importantly, our findings highlight that the Core Model is insufficient in capturing all relevant topics for AI-based technologies, as 14 out of the additional 20 topics were identified as crucial.

It is imperative to determine the level of agreement on AI-relevant HTA topics to establish a robust assessment framework. This framework will play a foundational role in evaluating AI tools for the early diagnosis of dementia, which is the focus of the European project AI-Mind currently being developed.

The European Union Joint Clinical Assessment (JCA) process aligns with the regulatory process to promote faster patient access. The PICO (population, intervention, comparator, and outcome) scoping for the JCA must occur before the regulatory process concludes. The risk of indication change during this period is one of the concerns for the success of the JCA process. We investigated the frequency and type of changes that are made to proposed indications and examined how such changes could impact the PICO scoping for JCA.

Twenty-seven recently approved oncology and 15 Advanced Therapy Medicinal Products (ATMP) products were included. Observed indication changes were categorized into editorial or population changes population changes were graded based on the anticipated impact on JCA scope depending on their nature.

The majority of products had only editorial changes between proposed and approved indications (67 percent). Once amended, it was common for the indicated population to be narrowed, and rare for it to be broadened. The most common change observed was the shift to a later treatment line. The greatest risk for PICO rescoping would be when new populations would have been added, or new subpopulations or subgroups would have been omitted from the initial scope.

The impact on JCA scope depends on the proposed indication wording and how the PICO scoping would have been conducted. Rescoping warrants a considered decision, and to mitigate the risk of delays, dialogue between the assessors and the developer is recommended for informed decision-making.

To meet the needs of an evolving health and care system, the National Institute of Health and Care Excellence (NICE) is changing its approach to topic prioritization so it can focus on what matters most. To support this, NICE ran a public dialogue to gather informed opinion on how it should select topics for guidance, including for some technology evaluation programs.

Fifty-five general public participants from across England took part in two face-to-face and three online deliberative workshops (each lasting two or three hours, held over four weeks in 2023). Participants were asked to consider the following criteria in the context of prioritization: health and care need, evidence availability, system impact, budget impact, health inequalities, and environmental sustainability. The workshops were designed to understand whether any aspects were more important than others and explore the reasons why. They used deliberative engagement methods and included trade-off exercises, role-play, group discussion, ranking tasks, and interactions with specialists.

Emerging findings show that the participants think NICE should consider several aspects when prioritizing topics for guidance. Health and care need was of primary importance for people, followed by evidence availability, budget impact, and system impact. Health inequalities and environmental sustainability were generally considered to be less important, though participants still felt these were areas that should inform NICE’s prioritization decisions. Participants identified relevant interactions between the criteria, suggesting that each criterion cannot be considered in isolation. Full results will be available to present at HTAi 2024.

Deliberative public engagement is a meaningful way to involve the public in complex policy decisions with a social value element. Broad public agreement was found with the criteria NICE has proposed to consider when prioritizing topics for guidance, and some criteria are more important to people than others. The findings will feed into NICE’s new approach to topic prioritization.

One of the pillars of health technology assessment (HTA) is transparency, which guarantees reproducibility and accountability. Due to the “black-boxness” of artificial intelligence (AI) models, the use of AI-based tools adds new layers of complexity for transparency issues. The aim of this scoping review is to map AI-based tools applied in HTA processes, regarding human supervision and “open-sourceness” aspects.

A search strategy using the terms “AI,” “HTA,” and correlated terms was performed in nine specialized databases (health and informatics) in February 2022. Inclusion criteria were publications testing AI models applied in HTA. Selection of studies was performed by two independent researchers. No filter was applied. Variables of interest included a subset of AI models (e.g., machine learning [ML], neural network), learning methods (e.g., supervised, unsupervised, or semi-supervised learning), and code availability (e.g., open source, closed source). Data were analyzed exploratorily as frequency statistics.

ML with one layer of hidden nodes was applied in 48 (78.6 %) studies, while deep learning (DL) (two-plus layers) were applied in eight (13.1 %). ML models that used supervised learning accounted only for half of the reported models, while half used unsupervised learning. Considering supervision methods in DL models, seven used unsupervised learning, and one used supervision. Four studies did not report the AI model, and 14 studies did not report the supervision paradigm. It was not possible to assess “open-sourceness” in 31 studies. Among the identified software, seven models were not open source, and 13 were open source.

Transparency and accountability are of utmost importance to HTA. Complexity of AI models may introduce trustworthiness issues in HTA. Transparency provided by open-source code becomes essential in building trust in the automation of HTA processes, as does quality of report. Although progress has been observed in transparency and quality, the lack of a methodological framework still poses challenges in the field.

This study investigates the impact of coronavirus disease 2019 (COVID-19) pandemic on HTAsiaLink members at the organizational level and provides recommendations for mitigating similar challenges in the future.

A survey was disseminated among HTAsiaLink members to assess the COVID-19 impact in three areas: (i) inputs, (ii) process, and (iii) outputs of the Health Technology Assessment organizations’ (HTAOs) research operations and HTA process in general.

Survey results showed that most HTAOs hired more staff and secured similar or higher funding levels during COVID-19. Nevertheless, some organizations reported high staff turnover. COVID-19-relevant research was prioritized, and most of the organizations had to adapt their research design to meet the needs of policymakers. Time constraints in conducting research and inability to collect primary data were reported as impacts on the research process. Overall, the number of research projects and accessibility of respondents’ publications increased during COVID-19.

Research demand for HTAOs increased during COVID-19 and impacted their research process; however, they demonstrated resilience and adaptability to provide timely evidence for policymakers. With the growing reliance on HTA, HTAOs require adequate financial support, continuous capacity building, collaboration, and partnership, innovative HTA methods, and a pragmatic yet robust, evidence-to-policy process in preparation for future pandemics.

Health technologies play a relevant role in environmental sustainability (ES). However, limited evidence exists on approaches and methods to integrate ES into the Health Technology Assessment (HTA).

The purpose of this study is: (i) to provide an overview of global HTA organizations’ progression toward the integration of ES into HTA; (ii) to investigate various paths for this integration, highlighting obstacles, priorities, potential approaches, and methods.

Data were collected via questionnaires from organizations belonging to HTA networks, International Network of Agencies for Health Technology Assessment, and European Network for HTA. To complement the results of the survey, the authors carried out a desk analysis with strategic documents available on institutional websites.

The survey included twenty-six respondents from twenty different countries (thirty-three percent response rate). Among the study’s participants, there is a notable acknowledgment of the importance of integrating ES into HTA. However, only nine organizations are actively engaged in these integration efforts, each employing unique methodologies and perspectives. There is a substantial consensus on the application of life cycle assessment, with a particular emphasis on the use of environmentally extended input–output analysis, and a stronger preference for cost-utility analysis. Nevertheless, evidence on integrating ES into HTA remains scarce. Major challenges identified include data collection difficulties and the necessity for interdisciplinary teams.

Our study represents a preliminary effort to systematize initiatives aimed at integrating ES into HTA. Further research is required to customize methods and tools for appropriately evaluating the environmental impacts of technologies. The findings suggest that achieving ES-HTA integration demands a multi-tiered, interdisciplinary approach.

The advent of artificial intelligence (AI) in digital health technologies (DHT) requires a comprehensive health technology assessment (HTA) to ensure safety and effectiveness and to demonstrate the value of these technologies in healthcare systems. Recognizing the unique requirements posed by AI-based DHT, our agency has undertaken several initiatives to tailor and adapt our processes for effective HTA.

We started by identifying the processes that were not working optimally and planned a list of actions needed to improve them. These actions were: (i) to develop a new evaluation framework for the assessment of DHT, including those based on AI; (ii) to increase our activity on early HTA; (iii) to seek collaboration with an organization for technical assessment of AI, with a particular emphasis on trustworthy AI requirements; (iv) to adapt our HTA report templates; (v) to create new forms to request information from the technology developers; and (vi) to set up a working group on HTA of AI-based DHT.

We have now an evaluation framework that informs on the relevant aspects for HTA of AI-based DHT and the evidence that developers need to generate in order to proof the value of their technology. We designed a circuit to identify promising technologies and increased our early HTA work for timely advice. The evaluation team now involves an additional partner for the technical assessment domain. In addition, we have new templates for early HTA reports, which explain those AI-specific elements to be addressed, as well as industry information request forms that enable collecting specific information like algorithm type and population used for clinical validation.

Tailoring HTA processes to AI-based DHT is crucial in today’s fast-paced health technology landscape. Our new evaluation framework, the involvement of new partners in the assessment team, the creation of new templates, and enhanced early HTA work helps to evaluate these technologies optimally. We are also setting up a working group to ensure homogeneous evaluation within Spain.

Healthcare stakeholders in Latin America, including payers, manufacturers, and patients, seek to expedite access to technologies. However, uncertainty sometimes surrounds their true benefits and budgetary implications. Managed entry agreements (MEAs) are proposed to address this uncertainty by redistributing risks among key actors.

The objective of Health Technology Assessment International’s 2023 Latin American Policy Forum was to examine the potential utility of MEA in technology reimbursement and decision-making processes in the region.

This article is based on a background document, a survey, and the deliberative work of the country representatives and others who participated in the Policy Forum.

Interest in MEA in Latin America is increasing, with financial agreements being more prevalent than those based on clinical outcomes. During the Policy Forum, potential barriers to MEA implementation were identified, such as the lack of legal frameworks, insufficient reliable data, and, in some cases, distrust among stakeholders. Some potential solutions were also identified, including early stakeholder involvement to enhance dialogue and understanding, and piloting shorter-duration MEA to facilitate the revision of agreement terms, especially in situations of epidemiological uncertainty.

The Policy Forum served as a valuable platform for discussing the importance of flexible MEA implementation that acknowledges data uncertainty, promotes transparent dialogue to incorporate opinions and values from all stakeholders, and develops legal frameworks to support effective technology access schemes in Latin America.

Literature reviews (LR) play a crucial role in all health technology assessment (HTA) dossiers, presenting evidence-based value of interventions. There is global exploration of artificial intelligence (AI) to expedite and enhance the efficiency of literature reviews. Our research aimed to identify any existing guidance from HTA bodies regarding the use of AI for conducting literature reviews.

We conducted a comprehensive search and review of any published guidance from prominent HTA bodies, including the National Institute for Health and Care Excellence (NICE, England), Scottish Medicines Consortium (SMC, Scotland), National Centre for Pharmacoeconomics (NCPE, Ireland), National Authority for Health (HAS, France), Federal Joint Committee (G-BA, Germany), Institute for Quality and Efficiency in Health Care (IQWiG, Germany), Canadian Agency for Drugs and Technologies in Health (CADTH, Canada), and Pharmaceutical Benefits Advisory Committee (PBAC, Australia). This was done to gain insights into their views regarding the utilization of AI in literature reviews. Additionally, we engaged with HTA representatives, such as NICE, to gain a deeper understanding of their perspectives.

We found a lack of clear guidance on the use of AI for conducting LRs. NICE has recommended a priority screening technique using machine learning (ML) for identification of a higher proportion of relevant papers at an earlier stage. NICE is currently in the process of developing guidance and is updating its manual in this area. SMC refers readers to NICE methodologies. In its HRB-CICER report, NCPE only acknowledges the potential of ML algorithms for LRs, with no additional information. IQWiG, in its general methods, recommends the use of ML-validated classifiers for identifying randomized controlled trials (RCTs) within bibliographic searches.

Our research indicates that there is scarce guidance available for the use of AI in LRs for HTA submissions. However, considering the rapidly evolving nature of this field, it is anticipated that guidance documents and manuals will be updated in the near future.

In 2021, the Australian Government Department of Health and Aged Care’s Consumer Evidence and Engagement Unit (CEEU) launched an online consultation hub to provide a centralized pathway for consumer engagement in health technology assessment (HTA) processes. The hub enables consumers (patients, carers, health professionals, and citizens) to provide commentary on items being considered by HTA committees for subsidization.

A survey was developed by the CEEU, committee members, and consumer representatives to facilitate consultation on applications assessed by the Pharmaceutical Benefits Advisory Committee (PBAC)—a principal Australian HTA committee. Questions were designed as simple and engaging, including guidance on the type of information required. Responses are summarized thematically by efficacy, safety, accessibility, and quality-of-life impacts of the proposed health technology. New surveys are launched to coincide with each PBAC meeting agenda publication and allow a ten-week consultation period. Awareness of consultations is supported by the CEEU’s HTA Engage e-newsletter, which alerts the public and targeted stakeholders.

The hub surveys have enabled streamlined consumer commentary to be provided for PBAC considerations. It has also allowed increased time for quality consultation with stakeholders. The success of the hub is further demonstrated in the current development of a similar survey for another principal committee, the Medical Services Advisory Committee (MSAC), to transition its consultation processes to the hub. Of note, while consumers’ feedback on the hub is positive, there remains a desire for educational resources and face-to-face interactions to support consumer engagement in HTA processes. The CEEU are developing materials to address and further support this need.

In a time when technological communication can be optimized to complement face-to-face conversations, it is vital consumer engagement in HTA processes follows suit. To facilitate continued engagement that is sustainable for both present and future Australians, the CEEU continues to evolve a strategy regarding virtual consultations to increase consumer awareness and education and promote effective participation in Australian HTA.

In the field of Laboratory Medicine, the evolution of knowledge and the innovation of technologies are the basis of analytical and diagnostic progress, leading to the development of new solutions based on innovative technologies. However, these advances must be accompanied by evidence of appropriateness, diagnostic effectiveness, and organizational efficiency, considering the test’s first impact on patient outcomes.

The Health Technology Assessment (HTA) is a valid management tool to support Laboratory Medicine professionals in assessing technologies and which is the most appropriate to adopt. This study is an illustrative case of the application of HTA, exploiting the EUnetHTA Core Model, on two analyzers able to determine the glycated hemoglobin (Hemoglobin A1c, HbA1c), the Capillarys 2 Flex piercing analyzer and the HLC-723G11 analyzer in the Laboratory Medicine Service of the IRCCS San Raffaele Hospital (Milan, IT). The main focus is related to potential differences in methods, organizational aspects, and clinical effectiveness of these approaches for measuring HbA1c.

The EUnetHTA Core Model has proven to be the optimal method for HTA in the field of Laboratory Medicine, as it allows to highlight both the peculiarities of the methods on which the analyzers are based and the clinical efficacy of the laboratory test on specific patient populations, considering individual variations in treatment responses, assessing the potential benefits for individual patients or small groups.

This granular analysis helps provide insights into the effectiveness and value of healthcare interventions at the patient level, contributing to evidence-based decision-making in clinical practice and healthcare policy.

Understanding patient experience and needs is crucial to develop high-value therapies. Patient experience data (PED) inform trial design and evidence generation plans. The U.S. Food and Drug Administration’s roadmap to patient-focused outcome measurement advocates integrating PED into product development. We adapted this theoretical framework to include the health technology assessment (HTA) perspective and operationalized it as a patient disease strategy (PDS) framework.

The PDS framework is a methodology that systematically integrates patient-informed activities to reflect the patient health value of a new treatment. A PDS is developed per indication, initiated in the preclinical phase, applied in clinical development, and continuously adapted throughout the product development lifecycle. The three PDS phases include: (i) development of patient profile, including epidemiology, demographics, patient journey, disease, and treatment burden for patients and caregivers; (ii) PED gap analysis, focusing on identification of patient priorities, unmet needs, preferences, and expectations for new therapies; and (iii) translation into actions, such as diversity and inclusion (D&I) plans and outcomes strategy.

Out of 58 indications, 31 percent have endorsed PDS and 67 percent are in progress. Patient-relevant label opportunities increased by over 50 percent. Each indication was informed on average by patients from three different countries. The PDS framework helped to identify factors that impacted health outcomes for integration into trial designs and D&I plans. Early understanding of heterogeneous patient populations, unmet needs, benefit/risk trade-offs, and patient experiences ensured development programs measured the most meaningful outcomes while also addressing evidence gaps. Early understanding of patient priorities and barriers to participation optimized the studies by reducing burden and identifying proactive support needed to complete the trial.

The PDS framework systematically identified health value opportunities for a target population and integrated the patient needs into the overall development plan. PED informs clinical trial design and endpoint strategy optimization, including factors that influence diversity and data integrity. We anticipate that the PDS will enable HTA decisions to reflect patients’ health value and ultimately improve access to innovative therapies.

The number of orphan drug (OD) approvals has increased sharply in Europe. In Germany, all ODs are initially subject to a limited assessment after market access. Their added benefit over the standard of care is accepted as established upon EU approval; a regular health technology assessment (HTA) is performed only in certain cases.

We assessed whether the increase in OD approvals has led to improvements in patient-relevant outcomes as supported by the evidence submitted by market authorization holders (MAHs) for HTA in Germany. We also examined the extent to which these ODs address unmet medical needs.

The results of limited assessments and regular HTAs of ODs in Germany (January 2011–September 2021, plus January–December 2023) were analyzed to determine their added benefit based on MAH-submitted dossiers. Added benefit was reported separately for each research question generated from the EU-approved therapeutic indications and any sub-indications (e.g., different subpopulations or control interventions) specified for HTA in Germany.

Eighty-nine ODs (limited assessments: sixty-nine; regular HTAs: twenty) were evaluated in 175 research questions (limited assessments: ninety-seven; regular HTAs: seventy-eight). The added benefit granted in limited assessments was non-quantifiable in nearly eighty percent of the ninety-seven questions. In regular HTAs, no proof of added benefit was shown in fifty-four percent of the seventy-eight questions, mainly due to insufficient comparative data with the standard of care. Established treatments were available for fifty-eight percent of the seventy-eight questions; more than half of which addressed oncology indications (although these account for only eight percent of rare diseases).

Due to evidence gaps in post-approval HTA, many ODs approved in the EU lack proof of added benefit in terms of improving patient-relevant outcomes. Moreover, most approved ODs are indicated for diseases with established treatments and oncology indications, while many unmet medical needs remain. Incentives are required to encourage research in areas of unmet medical need and to generate comparative data with the standard of care.

The National Centre for Pharmacoeconomics (NCPE) has a Patient Organisation Submission Process (POSP) enabling patients to communicate their experiences to the drug-reimbursement decision-maker. The NCPE proactively invites and supports patient organizations to make submissions to the decision-maker for ongoing health technology assessments (HTAs). We evaluate uptake of the POSP and determine whether submission trends differ by drug type.

We reviewed all HTAs completed by the NCPE since 2016 (when the POSP was first introduced) to present (data cut-off date 22 November 2023). Time trends in the proportions of HTAs for which a patient organization submission had been made to the NCPE were analyzed descriptively. We also compared the proportions of HTAs for which a patient organization submission had been made for (i) orphan versus non-orphan drugs and (ii) oncology versus non-oncology drugs.

The number of patient organization submissions made to the NCPE has increased over time. In 2016, 24 percent (6/25) of completed HTAs were associated with a patient organization submission compared with 50 percent (11/22) in 2023. The proportions of completed HTAs associated with a patient organization submission are comparable between orphan (38%; 24/64) and non-orphan drugs (29%; 34/117) (Chi²; p=0.245). The proportion of completed HTAs for which a patient organization submission had been made was lower for oncology drugs (14%; 14/97) versus non-oncology drugs (52%; 44/84) (Chi²; p<0.001).

Patient organization submissions to the NCPE have increased over time. The proportions of HTAs for which patient organization submissions have been made are comparable between orphan and non-orphan drugs. However, the proportion of patient organization submissions for oncology drugs is lower than the proportion for non-oncology drugs. The NCPE will continue to liaise with patient organizations to increase engagement with the POSP.

Advanced therapy medicinal product (ATMP) is a classification used by the European Medicines Agency (EMA) for cell-, gene-, and tissue-engineered therapies. Since the first ATMP received market authorization in 2009, a substantial proportion of these highly innovative therapies have been withdrawn from the European market. This research investigates the key reasons underlying these withdrawals.

ATMPs with withdrawn EMA marketing authorizations were identified from the EMA website. A targeted review of relevant company press releases was undertaken and key information extracted. Health technology assessment (HTA) outcomes in France, Germany, and England were extracted from their respective websites (1 Sep 2023).

Thirty-two ATMPs have received EMA marketing authorizations, with 22 percent (7/32) withdrawn. One of these seven withdrawals was driven by unfavorable clinical results versus six out of seven due to commercial reasons. Of the six withdrawals driven by commercial reasons, four were associated with negative HTA and/or reimbursement issues (Chondro-Celect, Glybera, and Zalmoxis’s Service Médical Rendu (SMR, actual medical benefit) insufficient, driven by data-related issues in France; Glybera’s challenge to obtain reimbursement by insurance funds with only one sale reported, and Zynteglo’s price agreement not reached in Germany). One of the six withdrawals (Chondro-Celect) was also associated with hospital exemption (continued production without marketing authorization). One of six (Provenge) was also associated with chemistry-, manufacturing-, and controls (CMC)-related issues.

The ATMP landscape has rapidly evolved in the past decade. While ATMPs offer the promise of long-term benefits, the unique manufacturing, clinical, and especially the reimbursement challenges they face can lead to commercial failure. To ensure ATMP patient access and commercial success, manufacturers should engage early with payers, understand potential reimbursement challenges, and proactively plan to mitigate these.

Ministry of Health (MOH) Malaysia stakeholders seek primary care access to sodium-glucose cotransporter 2 inhibitor (SGLT2i). Addressing this required a complex decision, selecting among three SGLT2i for two different indications and two practice settings. The options include expanding the existing SGLT2i (empagliflozin) in the MOH Medicines Formulary to primary care and/or having dapagliflozin and/or luseogliflozin as alternatives. This study aimed to conduct a multiple health technology assessment (HTA) to determine the SGLT2i of choice for the MOH setting.

The clinical benefits of SGLT2i were assessed through a systematic literature review and affordability was assessed through the development of three budget impact analysis models simulating seventy scenarios. Each model varied by prescribing indications, restrictions, and SGLT2i involved (M1: glycemic control, HbA1c between 6.5 percent and 10 percent, empagliflozin–dapagliflozin–luseogliflozin; M2: cardiovascular benefits, HbA1c less than 10 percent, empagliflozin-dapagliflozin; M3: a composite of M1 and M2). The outcome of the HTA was presented to the MOH decision-makers.

Although there was no significant difference in glycemic control between the SGLT2i, differences exist in cardiovascular benefits conferred. Despite having scenarios with lower net budget impact (NBI) in the M1, M2, and M3 models, decision-makers decided to expand empagliflozin use to primary care setting and add dapagliflozin for hospital-only setting for both indications [NBI of $4.38 mil] due to empagliflozin’s advantage in reducing risk for cardiovascular death and prior experience of its use in MOH.

The multiple HTA approach guided the complex decision-making process by providing a holistic understanding of the decision’s impact.

Personalized precision medicine (PPM) is an innovative approach to disease diagnosis, prognosis, and treatment of individual or group characteristics using diverse data sources. While omics technologies are integral to PPM, they pose challenges. Therefore, developing an appropriate methodology to assess these technologies is crucial for patient safety, resource efficiency, and clinical decision-making within the Spanish National Health System.

This health technology assessment (HTA) methodology procedure was developed by combining three different approaches: a systematic review (SR); a survey targeting experts in omics technology, ranging from basic science researchers to clinicians, and patient associations; and, finally, a consensus method (RAND Appropriateness Method [RAM]).

Through data extraction and evidence synthesis of the 38 studies included in SR, 30 existing frameworks for evaluating omics technologies were identified, as well as the elements needed to assess these technologies, leading to the first version of the framework. Two surveys were performed to integrate the perspectives of omics technology experts and patients. Subsequently, this framework version was further developed by a RAM consensus panel of experts from HTA agencies to ensure a rigorous evaluation of gathered data. The final framework was categorized into 94 elements divided into sections, categories, domains, and subdomains.

A methodological guide, including the assessment framework, was developed for the Spanish HTA network. The framework is divided into several sections addressing evidence-gathering, provision models, organizational elements, economic evaluation, and ethical and social implications. Compared to other available frameworks, our proposal included aspects such as bioinformatics, technological maturity level, and the patient perspective with the personal utility domain.

The aim of this study is to understand the path for establishing digital health technologies-health technology assessment (DHT-HTA) in India.

A rapid review of HTA and DHT frameworks on PubMed (MEDLINE) and Google Scholar was conducted to identify DHT-HTA guidelines, and HTA processes in India. MS-Excel template was created with key domains for assessing DHT in resource-constrained settings based on studies and reports identified. Responses received from seventeen experts with varying expertise in DHT, HTA, clinical, and research were contacted using an online form. Following the principles of qualitative research rooted on grounded theory approach, themes and domains were derived for a framework which was again circulated through participants. Weightage for each theme was assigned based on the frequency of responses and qualifiers were used to interpret results. Inductively derived themes from these responses were clubbed together to identify macro-level systems requirements, and finally pre-requisites for setting up DHT-HTA framework was synthesized.

HT are commonly perceived by experts (64.7 percent participants) as a technology strictly connected to health information. Real-world data (i.e., electronic health data) are recognized as a relevant tool in support of decision-making for clinical and managerial levels. Experts identified some pre-requisites for the establishment of DHT-HTA in the country in terms of infrastructure, contextual factors, training, finance, data security, and scale-up.

Our research not only identified the pre-requisites for the adoption of a DHT-HTA framework for India, but confirmed the need to address DHT-HTA’s acceptability among. Hospitals and health insurance providers.