Skip to main content

Next Generation Health Technology Assessment to support patient-centred, societally oriented, real-time decision-making on access and reimbursement for health technologies throughout Europe

Periodic Reporting for period 1 - 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: 2019-01-01 to 2020-06-30

The treatment of patients has become much more complicated in recent years 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 is capable of identifying for whom health technologies work and for whom they are not essential, hereby guaranteeing that the right treatment is provided, to the right patient, at the right time and leading to an increase in societal healthcare benefits. However, the data to inform these types of decisions still do not exist. Moreover, limited datasets for innovative medicines and medical devices will make decision-making even harder. To add to this, companion diagnostics, target therapies and digital health interventions are being introduced into healthcare systems for which no HTA frameworks exist.
So, the main issue is that we need to change HTA paradigms to obtain future proof HTA that can address changes in health care such as:
- Personalized treatments/medicine
- Smaller populations
- Combinations of treatments, different sequences
- Companion diagnostics (genetic testing)
- The use of real-world evidence (RWE)
- Internationalization of HTA evaluations
HTx provides a general framework that can help groups to develop HTA methods for specific disease areas. This approach allows a society to maximise its health outcomes at population level for a given healthcare system in a way that is consistent with the principles of HTA. These methods have a clear link to national reimbursement and pricing processes and can be practically used in healthcare practice:
- By HTA organisations to facilitate HTA for personalised treatments (including support appropriate use).
- By healthcare providers as part of new guidelines.
- For individual patients and their clinicians.
HTx objectives:
• HTx will facilitate the development of methodologies to deliver more customized information on the effectiveness and cost-effectiveness of complex and personalised combinations of health technologies.
• HTx will also provide methods to support personalised treatment advice that will be shared with patients and their physicians.
• Finally, HTx will in close collaboration with the European Network for HTA (EUnetHTA) and its stakeholders pilot the implementation of these methods in Europe.
A review was conducted to assess the challenges of performing HTAs of complex health technologies by national HTA agencies. The main findings of this review suggest that most of the challenges root in the availability of data at time of HTA, resulting in challenges with outcomes in the relative-effectiveness assessment and uncertainty around input parameters for the cost-effectiveness assessment.
Additionally, we developed the general framework for the innovation of HTA methods. This framework, called IHTAM, uses a three-phase process (i.e. identifying needs for the innovation, developing the method, implementing the method) on how to innovate HTA methods.
Simultaneously for the case studies proton therapy of head/neck cancer, diabetes, pharmacological treatment of multiple sclerosis (MS) and treatment of myelodysplastic syndrome (MDS) systematic reviews on the current state of treatment were produced. These reviews provided a starting point for identifying the prominent issues that are relevant in the HTAs of those treatments in the different indications and a necessity for developing new HTA methods.
As part of methods work on using RWD for evidence synthesis to support decision-making we started to create an overview on the available methods to combine data from randomised clinical trials (RCTs) and non-randomised studies (NRS). Additionally, a two-stage evidence synthesis prediction model was developed to synthesize evidence and predict the most likely outcome under several possible treatment options while accounting for patients’ characteristics.
First developments on the use of artificial intelligence (AI)/machine learning (ML) to forecast individual treatments based on RWD focused on the pre-processing and imputation of raw data from clinical practice. A Shiny app was designed to apply pre-processing and visualization methods on longitudinal hospital visit data. Additionally, due to the limitations of sharing individual patient data (data-ownership and privacy issues) an alternative method for sharing data was studied.
The HTA agencies within the project heavily invested in building consensus between the involved HTA-agencies; NICE, TLV and ZIN. Recent appraisals for the treatments in the case studies have been compared and communal gaps and questions have been distilled. In addition, information has been gathered from 23 agencies throughout Europe to find out why they are (not) using RWD. For consensus between HTA and regulatory bodies a systematic review was conducted. A literature review exploring the use of the sandbox concept in healthcare, to date, has been completed. Already three meetings with our advisory boards from stakeholders have been achieved.
Transferability has been discussed with all case study leaders and work package leaders in the HTx project, to ensure that this will be included at the earliest stage of each process. HTx results have been presented on 17 conferences, trainings and webinars reaching an estimated 900 scientists, 730 policy makers, 270 patient representatives and many other delegates of extra stakeholder groups.
Involvement of patient organisations in HTx received further attention for instance by regular attendance to work package e-meetings and visits of patient representatives to the work package leaders and case study holders (2 in 2019 and 1 in 2020). HTx has been systemically included in the annual Eurordis training programme for patients (Eurordis Summer School) starting from the first year. The dissemination and engagement of the Multiple Sclerosis patient community have been ensured by subcontracting this part of the activity to EMSP (European Multiple Sclerosis Platform).
Finally, a governance structure was implemented for HTx that helped steering the efforts towards the achievement of the scientific objectives in an efficient and agile manner.
The aim of HTx is to enrich the methodological arsenal with improved methods for data synthesis of experimental and RWD, including network meta-analysis that can provide accurate estimations of the effectiveness of combinations of personalised treatment modalities. That includes improved methods of health econometric analysis beyond the level of an average treatment effect. Simultaneously, we aim to develop a decision analytic framework that can be used to evaluate long term effectiveness and cost-effectiveness for the different complex treatment strategies. Also, we expect to deliver artificial intelligence and machine learning tools that yield more accurate estimations of effectiveness to support personalised treatment advice for patients and doctors. Finally, in order to ensure the sustainability, HTx will providing a toolbox of different reimbursement and pricing options for HTA organisations and payers that may facilitate access to more complex treatment modalities.
Project logo