Periodic Reporting for period 4 - HTx (Next Generation Health Technology Assessment to support patient-centred, societally oriented, real-time decision-making on access and reimbursement for health technologies throughout Europe)
Reporting period: 2023-07-01 to 2024-06-30
Context and overall objectives
Over recent years, healthcare decision-making has become much more complicated due to the development of tailored health technologies, including combinations of technologies, co-dependent technologies, and personalised medicine. As a result, the need has arisen for personalised HTA that can identify for whom health technologies work and for whom they are not essential, hereby guaranteeing that the right treatment is provided to the right person at the right time and leading to increased societal healthcare benefits. The overall objective of HTx is to create a framework for next-generation HTA that supports patient-centred, societally oriented, real-time decision-making for integrated healthcare throughout Europe. HTx will facilitate the development of methodologies to deliver more customised information on the effectiveness and cost-effectiveness of complex and personalised combinations of health technologies. The HTx key objectives are to:
1. Identify specific situations where patient-centred, real-time decision-making systems for HTA and reimbursement are most needed.
2. Enhance methods for integrating evidence from randomised clinical trials (RCTs) and real-world data (RWD) to generate effectiveness and cost-effectiveness results for these specific treatment situations.
3. Develop a methodology that enables real-world decision-making for individualised treatment pathways and helps decide in real time which treatment is most suitable for each patient.
4. Provide policy solutions for tackling pressing HTA issues related to adapting these new HTA methods.
5. Study the implementation of these results in all EU Member Countries with a particular focus on Central and Eastern European (CEE) Countries with lower incomes.
6. Disseminate the project's results to European stakeholders, focusing on the patient community.
Most of the work revolved around four case studies used to exemplify the issues at the heart of the project and test beds for the methodological solutions developed in the relevant WPs. The case studies were:
a) Proton therapy for head and neck cancer (CS1)
b) The use of lifestyle interventions, medical devices and e-health technologies in type 1 and type 2 diabetes mellitus (CS2)
c) Pharmacological treatment of relapsing-remitting multiple sclerosis (RRMS) using randomised and real-world data (CS3).
d) Evaluating myelodysplastic syndrome (MDS) treatments using clinical register data (CS4).
Over recent years, healthcare decision-making has become much more complicated due to the development of tailored health technologies, including combinations of technologies, co-dependent technologies, and personalised medicine. As a result, the need has arisen for personalised HTA that can identify for whom health technologies work and for whom they are not essential, hereby guaranteeing that the right treatment is provided to the right person at the right time and leading to increased societal healthcare benefits. The overall objective of HTx is to create a framework for next-generation HTA that supports patient-centred, societally oriented, real-time decision-making for integrated healthcare throughout Europe. HTx will facilitate the development of methodologies to deliver more customised information on the effectiveness and cost-effectiveness of complex and personalised combinations of health technologies. The HTx key objectives are to:
1. Identify specific situations where patient-centred, real-time decision-making systems for HTA and reimbursement are most needed.
2. Enhance methods for integrating evidence from randomised clinical trials (RCTs) and real-world data (RWD) to generate effectiveness and cost-effectiveness results for these specific treatment situations.
3. Develop a methodology that enables real-world decision-making for individualised treatment pathways and helps decide in real time which treatment is most suitable for each patient.
4. Provide policy solutions for tackling pressing HTA issues related to adapting these new HTA methods.
5. Study the implementation of these results in all EU Member Countries with a particular focus on Central and Eastern European (CEE) Countries with lower incomes.
6. Disseminate the project's results to European stakeholders, focusing on the patient community.
Most of the work revolved around four case studies used to exemplify the issues at the heart of the project and test beds for the methodological solutions developed in the relevant WPs. The case studies were:
a) Proton therapy for head and neck cancer (CS1)
b) The use of lifestyle interventions, medical devices and e-health technologies in type 1 and type 2 diabetes mellitus (CS2)
c) Pharmacological treatment of relapsing-remitting multiple sclerosis (RRMS) using randomised and real-world data (CS3).
d) Evaluating myelodysplastic syndrome (MDS) treatments using clinical register data (CS4).
The results of HTx can be outlined based on the key objectives:
1. One of the key HTx studies, based on the input of more than 20 European HTA bodies, demonstrated that advanced therapeutic medicinal products (ATMPs) and histology-independent therapies were considered to be the most challenging to evaluate based on the predened complex health technologies and case studies. It also concluded that most challenges in HTA of complex health technologies are rooted in data insufciencies rather than the complexity of health technologies. As the number of complex technologies grows, the urgency for new methods and policies to guide HTA decision-making was clearly highlighted in this study.
2. As a starting point, the current landscape of the average and individualised real-world effectiveness and cost-effectiveness of health technologies was reviewed. These reviews assessed:
- Quality assessment tools for non-randomised studies of interventions (NRSI).
- Studies assessing the value of diabetes monitoring systems compared studies that used RCT data and RWD.
In a next phase, a suite of Bayesian NMA and network meta-regression (NMR) models was developed, allowing for cross-design (RCT and NRS) and cross-format (IPD and AD) synthesis, and implemented these models in a new R package crossnma. Additionally, a framework for a personalised prediction modelling based on cross-design NMA was developed, and its importance to use in health economic evaluation was exemplified.
Finally, the Target Trial Emulation (TTE), a framework that uses causal inference from observational data and that can be viewed as an attempt to emulate a hypothetical randomised trial (i.e. the target trial), was further developed in HTx to allow for analysis of RWD to (try and) answer the clinical and HTA question of interest, for application in decision modelling for cost-effectiveness analysis.
3. Prediction models were developed to support an individualised treatment approach for all case studies.
4. Several policy instruments were developed under HTx. Key outputs were:
5. The activities for transferability of the models developped were organised
During the entirety of the project, we have published:
14 newsletters
27 YouTube videos (of which 17 are part of the HTx Patient Toolbox)
40 blog entries on the HTx website
120 posts on the project’s LinkedIn profile
181 tweets and retweets on the project’s Twitter / X profile
Published 45 articles in peer-reviewed scientific journals
Organised 30 HTx events
Reported presenting over 115 times at scientific meetings and conferences, including ISPOR (in 2019, 2022 & 2023), ISPOR Europe (in 2019, 2020, 2021, 2022 & 2023) and HTAi (in 2019, 2021, 2022 & 2024) annual meetings.
1. One of the key HTx studies, based on the input of more than 20 European HTA bodies, demonstrated that advanced therapeutic medicinal products (ATMPs) and histology-independent therapies were considered to be the most challenging to evaluate based on the predened complex health technologies and case studies. It also concluded that most challenges in HTA of complex health technologies are rooted in data insufciencies rather than the complexity of health technologies. As the number of complex technologies grows, the urgency for new methods and policies to guide HTA decision-making was clearly highlighted in this study.
2. As a starting point, the current landscape of the average and individualised real-world effectiveness and cost-effectiveness of health technologies was reviewed. These reviews assessed:
- Quality assessment tools for non-randomised studies of interventions (NRSI).
- Studies assessing the value of diabetes monitoring systems compared studies that used RCT data and RWD.
In a next phase, a suite of Bayesian NMA and network meta-regression (NMR) models was developed, allowing for cross-design (RCT and NRS) and cross-format (IPD and AD) synthesis, and implemented these models in a new R package crossnma. Additionally, a framework for a personalised prediction modelling based on cross-design NMA was developed, and its importance to use in health economic evaluation was exemplified.
Finally, the Target Trial Emulation (TTE), a framework that uses causal inference from observational data and that can be viewed as an attempt to emulate a hypothetical randomised trial (i.e. the target trial), was further developed in HTx to allow for analysis of RWD to (try and) answer the clinical and HTA question of interest, for application in decision modelling for cost-effectiveness analysis.
3. Prediction models were developed to support an individualised treatment approach for all case studies.
4. Several policy instruments were developed under HTx. Key outputs were:
5. The activities for transferability of the models developped were organised
During the entirety of the project, we have published:
14 newsletters
27 YouTube videos (of which 17 are part of the HTx Patient Toolbox)
40 blog entries on the HTx website
120 posts on the project’s LinkedIn profile
181 tweets and retweets on the project’s Twitter / X profile
Published 45 articles in peer-reviewed scientific journals
Organised 30 HTx events
Reported presenting over 115 times at scientific meetings and conferences, including ISPOR (in 2019, 2022 & 2023), ISPOR Europe (in 2019, 2020, 2021, 2022 & 2023) and HTAi (in 2019, 2021, 2022 & 2024) annual meetings.
HTx has further developed a roadmap for implementation of the IHTAM framework. The paper entitled “Roadmap to Innovation of HTA Methods (IHTAM): Insights from Three Case Studies of Quantitative Methods” was accepted for publication in the International Journal of Technology Assessment in Health Care in 2024.
HTx has analysed the effect of personalized healthcare, and showed that, in the case of T2D, personalized approach is not only more effective but also it saves money from the society. Another main result of WP3 is the development of the reporting checklist CHEERS-AI, which gives guidance about how economic evaluations of AI-enabled healthcare should be reported in order to help decision makers understand and trust the study. CHEERS-AI is expected to be widely used by health economists as the number of AI-enabled health technologies continues to grow, and better reporting will benefit decision makers and the HTA community.
The work done in during HTx has contributed to a deeper understanding of the barriers involved in the use of RWD for HTA. The results of HTx offer solutions for methodological challenges; for some of the data-related challenges (e.g. the combined use of RCT data and RWD), and explore solutions for policy-related problems (e.g. in sandboxes).
Transferability workshops run during the Projec ensure that the results of the HTx project are feasible to use even in Central and Eastern European countries.
HTx has analysed the effect of personalized healthcare, and showed that, in the case of T2D, personalized approach is not only more effective but also it saves money from the society. Another main result of WP3 is the development of the reporting checklist CHEERS-AI, which gives guidance about how economic evaluations of AI-enabled healthcare should be reported in order to help decision makers understand and trust the study. CHEERS-AI is expected to be widely used by health economists as the number of AI-enabled health technologies continues to grow, and better reporting will benefit decision makers and the HTA community.
The work done in during HTx has contributed to a deeper understanding of the barriers involved in the use of RWD for HTA. The results of HTx offer solutions for methodological challenges; for some of the data-related challenges (e.g. the combined use of RCT data and RWD), and explore solutions for policy-related problems (e.g. in sandboxes).
Transferability workshops run during the Projec ensure that the results of the HTx project are feasible to use even in Central and Eastern European countries.