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Behavioural Model of Factors Affecting Patient Adherence
Deadline: Mar 17, 2021  
CALL EXPIRED

 Entrepreneurship and SMEs
 Innovation
 Health Care
 E-Health
 IT
 Horizon Europe
 Open Source
 Research
 Clinical trials

Specific Challenge:

Patient non-adherence to prescribed treatment is an issue that affects patient health outcomes and healthcare system costs worldwide. It is estimated that it contributes to 200 000 premature deaths in the EU each year, and the annual costs of avoidable hospitalisations, emergency care and adult outpatient visits are assessed at EUR 125 billion. Addressing the issues of adherence would significantly improve both individual patient outcomes and reduce societal costs.

Many researchers have approached the topic of adherence but insights have necessarily been limited to specific sub-topics due to the breadth of the field. Unless the underlying problem is well-defined and understood, the probability of developing effective solutions with broad and consistent impact is low.

Consequently, there is a need to generate a more comprehensive theoretical and empirical understanding of the underlying causes of these patient behaviours and any interactions. This topic proposes the creation of a generalised model, grounded in behavioural theory, which integrates significant factors affecting non-adherent behaviour. This would provide a robust definition of the problem – a foundation for understanding and predicting patient behaviour – and guidance to develop and implement cost-effective tools and solutions for patients, healthcare professionals (HCPs) and other healthcare stakeholders, which directly target the causes of non-adherence and, ultimately, improve patient outcomes and reduce health system costs.

Creating the necessary understanding for an effective model will require broad engagement and skills, particularly since we are targeting a disease agnostic model. The perspectives of patients, healthcare providers, academic experts, behavioural scientists, digital and data analytics experts, and regulatory bodies will be essential to maximise the benefits and ensure all sectors of society are well served.

 

Scope:

The aims of the Call topic are to:

  • develop a comprehensive understanding of the factors which affect patient needs and adherence, independently from the therapeutic area (i.e. generic or disease-agnostic), in a real-world context (as opposed to clinical setting);
  • identify the most significant factors;
  • evaluate existing models and then either create an open access behavioural model or further develop an existing model;
  • collect additional real-world data to refine the model;
  • provide tools that will enable healthcare stakeholders to cost-effectively develop and implement solutions to address patient needs and improve adherence rates.

A behavioural model will be created or selected and refined. In parallel, adherence modules will be added to existing patient studies to fill identified gaps in the data.

While disease-agnostic, the model should be able to increase the prediction power and accuracy when applying additional, disease-specific inputs.

Once developed or refined, the model will be validated for multiple ages (including paediatric), ethnicities and conditions. It is anticipated that this shall be achieved using the following therapeutic areas, dependent on access to patients provided by members of the consortium:

  • Cardiovascular;
  • Oncology;
  • Immunology;
  • Neurology;
  • Endocrinology and
  • Rare Disease.

This list is not exhaustive. Where opportunities arise to validate in other additional therapeutic areas, these should be explored.

 

Expected Impact:

In their proposals, applicants should describe how the outputs of the project will contribute to the following impacts and include wherever possible baselines, targets and metrics to measure impact:

  • Positive impact on healthcare at a societal level through enhanced adherence, targeted use of resources, and improved overall patient outcomes;
  • Validated foundation to compile and understand factors affecting patient non-adherence to treatment regimens and the relative weighting of these factors;
  • Identification of sub-groups of the population with similar causes of non-adherent behaviour such that solutions can be tailored to population needs and applied in a cost-effective manner to multiple treatment conditions;
  • Model for the basis of a consistent approach to non-adherence across the industry; a framework for future development of patient-centric solutions, with the capacity for the model to evolve with the future needs of patient populations;
  • Guidance, based on the validated model, for identifying patient needs and tailoring support tools for patients and HCPs which most closely address patient adherence needs and improve patient outcomes and quality of life;
  • The data collected during the project will provide a broad and deep resource for future understanding of adherence.

In their proposals, applicants should outline how the project plans to leverage the public-private partnership model to maximise impact on innovation, research & development, as well as regulatory, clinical and healthcare practices, where relevant. This could include a strategy for engagement with patients, healthcare professional associations, healthcare providers, regulators, Health Technology Assessment (HTA) agencies, payers etc., where relevant.

In addition, applicants should describe how the project will impact the competitiveness and growth of companies including SMEs.

In their proposals, applicants should outline how the project will:

  • Manage research data including use of data standards;
  • Disseminate, exploit, and sustain the project results. This may involve engaging with suitable biological and medical sciences Research Infrastructures;
  • Communicate the project activities to relevant target audiences.

It is expected that the model, guidance and any development tools will be made available through an open source process to achieve the aims of maximising the number of patients receiving support.

 



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