Clinical trial NCT06856902: BEhavioral and Adherence Model for Improving Quality, Health Outcomes and Cost-Effectiveness of healthcaRe
Official title: BEhavioral and Adherence Model for Improving Quality, Health Outcomes and Cost-Effectiveness of healthcaRe
Study type: INTERVENTIONAL
Overall status: RECRUITING
Phase: NA
Conditions: Cardiovascular Diseases
Endocrinology
Inmunology
Neurology
Oncology
Rare Diseases
Keywords: Digital health
adherence to treatment
healthcare
Lead sponsor: Technical University of Madrid
Sponsor class: OTHER
Collaborators: name: University of Oslo
name: PREDICTBY RESEARCH AND CONSULTING S.L.
name: Pfizer
name: Merck KGaA, Darmstadt, Germany
First posted: 2025-03-04
Enrollment: 7410
Sex: ALL
Standard ages: CHILD
ADULT
OLDER_ADULT
Accepts healthy volunteers: yes
Allocation: RANDOMIZED
Intervention model: SINGLE_GROUP
Intervention model description: Overall, this study has a Mixed Methods approach as both quantitative and qualitative data will be collected and merged to answer the SQs. A Randomised Controlled Trial (RCT) is chosen as study design for the quantitative data collection as the design is well suited for drawing conclusions from data about the effects of interventions (SQ 5). In addition, the remaining quantitative data needed to answer the SQs can be collected through this design. The qualitative data collection will be done by conducting individual and focus group interviews with HCPs and patients. The purpose of the qualitative data collection is to validate that the B-COMPASS groupings and identified needs of support are correct and to complement the quantitative data collected from the pilot studies. The qualitative data will provide insights into the perceptions, experiences, and preferences of the stakeholders involved in the intervention, as well as the contextual factors that may influence the B-COMPASS.
Primary purpose: SUPPORTIVE_CARE

Brief 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.

Detailed description: The aim of the study is to validate the B-COMPASS in real-life settings. Overall, the purpose is to provide evidence 1) to validate the B-COMPASS (primary purpose), and 2) to demonstrate the effectiveness and implementability of the B-COMPASS (secondary purpose). The project will carry out the final iterative steps of refining the model, guided by the validation studies that have been conducted. This process will be based on evaluating the performance of the generic model across six selected therapeutic areas (cardiovascular, endocrinology, immunology, neurology, oncology and rare diseases). Study participants (patients and HCPs) will be recruited (at least) from Italy, Portugal, Norway, Spain, The Netherlands, and Germany, and the validation will evaluate the capacity to attend to a variety of needs and challenges for adherence to treatment.

Overall, the study has 8 Scientific Questions (SQs), where SQ 1-4 address the validity of the B-COMPASS (primary purpose) and SQ 5-8 address the effectiveness and implementability of the B-COMPASS (secondary purpose). The SQs are:

SQ 1 How accurately does the B-COMPASS predict the relative adherence to treatment for patients? SQ 2 How valid are the B-COMPASS groupings? SQ 3 How accurately are the patient support needs identified by the B-COMPASS? SQ 4 How reliable is the B-COMPASS over time? SQ 5 To what extent does the use of the B-COMPASS affect patient adherence to treatment? SQ 6 How do the patients perceive the received engagement with HCPs/Research Leads based on the B-COMPASS? SQ 7 How do HCPs/Research Leads perceive the B-COMPASS? SQ 8 How does the B-COMPASS impact the cost-effectiveness of healthcare utilisation?

Eligibility criteria: Inclusion Criteria:

* Having the diagnosis of the pilot sites target groups described above as per clinical assessment or validated diagnosis criteria
* Having the age of the pilot sites target groups described above
* Having accepted to participate in the study and provided written informed consent
* Having the availability to participate on all study activities

Exclusion Criteria:

* Individuals that do not fulfil ALL the inclusion criteria will be excluded to participate.

Primary outcomes:
measure: Treatment Adherence Perception Questionnaire
timeFrame: At first data collection and then aging at second data collection which is 2 weeks - 6 months after first data collection (first and second data collection). It varies between pilot sites and disease area.
measure: Quality of Life (EQ-5D)
timeFrame: At second data collection which is 2 weeks - 6 months after first data collection (first and second data collection). It varies between pilot sites and disease area.
measure: Patients experience
timeFrame: At second data collection which is 2 weeks - 6 months after first data collection (first and second data collection). It varies between pilot sites and disease area.
measure: Usefulness
timeFrame: From first data collection to second data collection which is 2 weeks - 6 months after first data collection. The exact time vary between pilot sites and disease area.
Secondary outcomes:
measure: BEAMER questionnaire
timeFrame: At first data collection and then aging at second data collection which is 2 weeks - 6 months after first data collection (first and second data collection). It varies between pilot sites and disease area.
measure: Demographics
timeFrame: At first data collection and then aging at second data collection which is 2 weeks - 6 months after first data collection (first and second data collection). It varies between pilot sites and disease area.
measure: Subjective feedback
timeFrame: From first data collection to second data collection which is 2 weeks - 6 months after first data collection. The exact time vary between pilot sites and disease area. The interviews will be conducted immediately after the second data collection
Other outcomes:
Locations:
city: Porto
country: Portugal
facility: MEDCIDS - Departamento de Medicina da Comunidade Informação e Decisão em Saúde
Study officials:
affiliation: Universidad Politecnica de Madrid
name: Giuseppe Fico, Professor
role: PRINCIPAL_INVESTIGATOR
References: