BEhavioral and Adherence Model for Improving Quality, Health Outcomes and Cost-Effectiveness of healthcaRe

Summary

Lack of adherence to treatment is a widespread issue worldwide, which leads to higher healthcare utilisation rates and even premature death. While the level of adherence may differ based on the specific condition and treatment, studies estimate that approximately 50% of medications are not taken according to the prescribed instructions. In addition, adherence rates tend to decrease even further when the treatment requires a behavioural change. Literature reviews about factors that affect people's adherence show that it is challenging to predict whom can be considered to have adherent and non-adherent behaviours. In addition, the studies highlight that it is challenging to support a person to be adherent. Based on this knowledge the BEAMER project was established (Behavioural and Adherence Model for improving quality, health outcomes and cost-Effectiveness of healthcaRe). The overall goal of the project is to improve the quality of life of individuals, enhance healthcare accessibility and sustainability, thereby transforming the way healthcare stakeholders engage with patients to understand their condition and adherence levels throughout their healthcare journey. To address the overall goal, the BEAMER project has developed a disease agnostic model named "B-COMPASS: BEAMER-COmputational Model for Patient Adherence and Support Solutions". The aim of the B-COMPASS is to identify patients' needs and preferences which enables the creation of patient-specific supports, with the intention of improving their adherence to treatment within the heterogeneity of the different disease-areas and healthcare contexts. Based on the validated BEAMER questionnaire, the B-COMPASS predicts relative adherence and offers an elicitation process of patient needs and preferences to enable targeted supports to improve patient adherence. This results in an allocation of patients to different groups based on their needs and preferences. Overall, the B-COMPASS provides patient insights that will enable more effective design of patient support, most likely resulting in better patient experience, improved adherence and lower healthcare and societal costs.

So far, several activities from a technical and user perspective have already been conducted in the project to refine the B-COMPASS. This has been done by applying an iterative mixed method approach were both stakeholders (regulator, pharma, academic/research and small and medium-sized enterprises) and end users (patients, health providers and health systems) have been involved. Despite the finetuning of the B-COMPASS, the effectiveness of the B-COMPASS hinges on empirical investigations into the structural elements that impact patient behaviour and the identification of predictive factors that can assist healthcare providers' (HCP) and Research Leads in designing more effective treatment plans (the term HCPs/Research Lead include both the individuals and the institutions where care is delivered). Therefore, validation studies will be conducted to assess the B-COMPASS's performance in six therapeutic areas (cardiovascular, endocrinology, immunology, neurology, oncology and rare diseases) with patients recruited in at least Italy (FISM), Portugal (APDP and MEDIDA) Norway (AHUS), Spain (FHUNJ and FIIBAP), The Netherlands (WDO), and Germany (UDUS). The collected data will be used to evaluate the B-COMPASS's capacity to attend to a variety of needs and challenges for adherence.

Conditions

• Cardiovascular Diseases
• Endocrinology
• Inmunology
• Neurology
• Oncology
• Rare Diseases

Interventions

BEHAVIORAL

B-COMPASS implementation

The patients in the intervention arm will receive B-COMPASS enhanced engagement in addition to standard care. The enhanced engagement is implemented as educational material to the HCP who is engaging with the patient. The content of the educational material will be based on the patient's B-COMPASS patient description. The engagement will either be in person or via phone call depending on the patient visiting schedule of each recruited patient.

Sponsors & Collaborators

• University of Oslo

  collaborator OTHER

• PREDICTBY RESEARCH AND CONSULTING S.L.

  collaborator UNKNOWN

• Pfizer

  collaborator INDUSTRY

• Merck KGaA, Darmstadt, Germany

  collaborator INDUSTRY

• Empirica

  collaborator UNKNOWN

• Centre for Research and Technology Hellas (CERTH)

  collaborator UNKNOWN

• Innovation Sprint

  collaborator UNKNOWN

• Fundacio d'Investigacio en Atencio Primaria Jordi Gol i Gurina

  collaborator OTHER

• Janssen Pharmaceutica N.V., Belgium

  collaborator INDUSTRY

• Novo Nordisk A/S

  collaborator INDUSTRY

• Servier Affaires Médicales

  collaborator INDUSTRY

• Takeda Pharmaceuticals International, Inc.

  collaborator INDUSTRY

• Tilburg University

  collaborator OTHER

• Technical University of Madrid

  lead OTHER

Principal Investigators

• Giuseppe Fico, Professor · Universidad Politecnica de Madrid

Study Design

Allocation

RANDOMIZED

Purpose

SUPPORTIVE_CARE

Masking

NONE

Model

SINGLE_GROUP

Eligibility

Sex

ALL

Healthy Volunteers

No

Timeline & Regulatory

Start

2025-03-01

Primary Completion

2026-06-30

Completion

2026-09-30

Countries

• Germany
• Italy
• Netherlands
• Norway
• Portugal
• Slovenia
• Spain
• Tanzania

Study Locations