Success Factors for Scaling Up the Adoption of Digital Therapeutics Towards the Realization of P5 Medicine.

Introduction: Digital therapeutics (DTx) can be a valuable contribution to the successful scale up of P5 Medicine (personalized, participatory, predictive, preventive, precision medicine) as they offer powerful means of delivering personalization and active patient participation in disease self-management. We investigated how the approval and adoption of DTx within health systems have been approached in five selected European countries and regions, with a view to proposing success factors scaling up their adoption. Methodology: Preliminary research established best countries or region candidates as being Germany, UK, France, Belgium, and the Spanish Region of Catalonia. The research was informed by a literature review, interviews with public bodies and industry, and a multi-stakeholder workshop to validate the findings and fill in existing gaps. Results: To authorize the use of digital technologies, the countries and regions passed legislation and developed policy instruments, appointed bodies to assess and certify the products and formalized mechanisms for permitting reimbursement. While DTx is not a commonly used nomenclature, there are digital health technology types defined that have similar requirements as DTx. Assessment and certification frameworks are usually built around the Medical Device Regulation with additional criteria. Reimbursement considerations often observe reimbursement of therapeutic devices and/or medicines. To be integrated into reimbursement systems, countries require manufacturers to demonstrate clinical value and cost-effectiveness. As there are currently very few DTx approved in practice, there is resistance toward clinical acceptance and organizational change, and change management is highly needed to integrate DTx into healthcare systems. The integration and secondary use of DTx data is not encountered in daily practice. Although some enablers exist, there remain technical and legal barriers. Discussion: DTx strategies should be considered as an integral part of digital health strategies and legislation, and specific DTx pathways with clear and transparent assessment and guidelines that balance regulation and innovation should be defined. To help manufacturers, countries should recommend and list methods that are widely accepted and ensure scientific robustness, aligned to the MDR requirements to support transfer of relevant and comparable data across countries. To facilitate rapid uptake of innovation, countries should add flexibility to the framework by allowing temporary market authorization to enable data collection that can support the clinical and socio-economic evaluation and data gathering phase. Certification should trigger rapid price setting and reimbursement mechanisms, and dynamic ways to adjust price and reimbursement levels in time should be established. Relevant stakeholders should be approached on the potential impacts of DTx through transparent communication and change management strategies should be considered. These findings should be validated with a wider range of stakeholders.

Assessing biocomputational modelling in transforming clinical guidelines for osteoporosis management.

Biocomputational modelling as developed by the European Virtual Physiological Human (VPH) Initiative is the area of ICT most likely to revolutionise in the longer term the practice of medicine. Using the example of osteoporosis management, a socio-economic assessment framework is presented that captures how the transformation of clinical guidelines through VPH models can be evaluated. Applied to the Osteoporotic Virtual Physiological Human Project, a consequent benefit-cost analysis delivers promising results, both methodologically and substantially.

Identifying causative mechanisms linking early-life stress to psycho-cardio-metabolic multi-morbidity: The EarlyCause project.

INTRODUCTION: Depression, cardiovascular diseases and diabetes are among the major non-communicable diseases, leading to significant disability and mortality worldwide. These diseases may share environmental and genetic determinants associated with multimorbid patterns. Stressful early-life events are among the primary factors associated with the development of mental and physical diseases. However, possible causative mechanisms linking early life stress (ELS) with psycho-cardio-metabolic (PCM) multi-morbidity are not well understood. This prevents a full understanding of causal pathways towards the shared risk of these diseases and the development of coordinated preventive and therapeutic interventions. METHODS AND ANALYSIS: This paper describes the study protocol for EarlyCause, a large-scale and inter-disciplinary research project funded by the European Union's Horizon 2020 research and innovation programme. The project takes advantage of human longitudinal birth cohort data, animal studies and cellular models to test the hypothesis of shared mechanisms and molecular pathways by which ELS shapes an individual's physical and mental health in adulthood. The study will research in detail how ELS converts into biological signals embedded simultaneously or sequentially in the brain, the cardiovascular and metabolic systems. The research will mainly focus on four biological processes including possible alterations of the epigenome, neuroendocrine system, inflammatome, and the gut microbiome. Life-course models will integrate the role of modifying factors as sex, socioeconomics, and lifestyle with the goal to better identify groups at risk as well as inform promising strategies to reverse the possible mechanisms and/or reduce the impact of ELS on multi-morbidity development in high-risk individuals. These strategies will help better manage the impact of multi-morbidity on human health and the associated risk.

Designing a socio-economic assessment method for integrative biomedical research: the Osteoporotic Virtual Physiological Human project.

In integrative biomedical research, methods assessing the clinical or even socio-economic impact of more complex technologies such as Information and Communication Technology (ICT)-based tools for modelling and simulation of human physiology have rarely been applied. The EU funded Osteoporotic Virtual Physiological Human (VPHOP) research project, part of the Virtual Physiological Human (VPH) European initiative, will create a patient-specific hypermodel to predict the absolute risk of bone fracture much more accurately than predictions based on current clinical practice. The project has developed an innovative, multilevel generic methodological framework to assess the clinical and socio-economic impact of biocomputational models. The assessment framework consists of three components: a socio-economic cost benefit analysis, health economic analysis of care pathways, and disease cost simulation models. Through its holistic perspective, the method provides a tool to appraise the overall value of biocomputational models for society.

Model-Driven Paediatric Cardiomyopathy Pathways - A Clinical Impact Assessment.

Intermediate results from an ongoing health technology assessment exercise of a simulation model of paediatric cardiomyopathy are reported. Comprehensive data on paediatric cardiomyopathy/heart failure, treatment options, incidence and prevalence, prognoses for different outcomes to be expected were collected. Based on this knowledge, a detailed clinical pathway model was developed and validated against the clinical workflow in a tertiary paediatric care hospital. It combines three disease stages and various treatment options with estimates of the probabilities of a child moving from one stage to another. To reflect the complexity of initial decision taking by clinicians, a three-stage Markov model was combined with a decision tree approach - a Markov decision process. A Markov Chain simulation tool was applied to compare estimates of transition probabilities and cost data of present standard of care treatment options for a cohort of children over ten years with expected improvements from using a clinical decision support tool based on the disease model under development. Early results indicate a slight increase of overall costs resulting from the extra cost of using such a tool in spite of some savings to be expected from improved care. However, the intangible benefits in life years saved of severely ill children and the improvement in QoL to be expected for moderately ill ones should more than compensate for this.

The Costs and Benefits of SNOMED CT Implementation: An Economic Assessment Model.

As part of its investigations, the EU-funded ASSESS CT project developed an Economic Assessment Model for assessing SNOMED CT's and other terminologies' socio-economic impact in a systematic approach. Methodology and key elements of the model are presented: cost and benefit indicators for assessing deployment, and a cost-benefit analysis tool to collect, estimate, and evaluate data.