An interventional study of B-COMPASS implementation in Cardiovascular Diseases, Endocrinology and Inmunology, sponsored by Technical University of Madrid. Completed at 10 sites in 8 countries. Per ClinicalTrials.gov, last updated 2026-10-21.
Sponsored by Technical University of Madrid · Not applicable, Interventional, and Supportive care
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.
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?
5,368 studies on the registry are indexed under Cardiovascular Diseases; 939 are open to participants now.
This study's enrollment of 6,190 is above the median of 100 across 3,084 interventional studies indexed under Cardiovascular Diseases.
Browse Cardiovascular Diseases studies →Technical University of Madrid is the lead sponsor of 14 studies on the registry; 3 are open to participants now.
Counted across the registry records on this site, refreshed daily.
Go through the criteria one by one — yes, no or not sure — and take the list to your doctor or the study team. Kept in this browser only.
Exclusion Criteria:
Underlined terms in the criteria open these too. Explained by clinicaltrials.gg, not part of the registry record. The study team decides who can take part.
Before you join, the study team explains what taking part involves — its purpose, what happens, the risks and possible benefits — and answers your questions, so you can decide freely. Consent is usually recorded on a form (the informed consent form, ICF) signed by you or, where the law allows, by someone legally authorised to decide for you.
You can keep asking questions during the study, you are told of new information that matters, and you can choose to leave at any time.
Informed consent
Before you join, the study team explains what taking part involves — its purpose, what happens, the risks and possible benefits — and answers your questions, so you can decide freely. Consent is usually recorded on a form (the informed consent form, ICF) signed by you or, where the law allows, by someone legally authorised to decide for you.
You can keep asking questions during the study, you are told of new information that matters, and you can choose to leave at any time.
Explained by clinicaltrials.gg, not part of the registry record. The study team decides who can take part.
At the first data collection, patients will complete the BEAMER questionnaire and adherence-related measures will be collected. Based on patients' answers, the B-COMPASS will assign them into groups, list their support needs, and predict their relative adherence, forming their B-COMPASS description. Patients will then be randomised into either 1) an intervention arm, or 2) a control arm using stratified randomisation via the Adherence Intelligence Visualisation Platform (AIVP), ensuring balance in B-COMPASS descriptions, gender, and age. Control patients will receive standard care and HCPs/Research Leads will not be informed of their B-COMPASS description. Where possible, at pilot sites, HCPs/Research Leads will also be randomised to ensure that HCPs/Research Leads in the control groups have as limited knowledge of the B-COMPASS/patient description as possible.
At the first data collection, patients will complete the BEAMER questionnaire and adherence-related measures will be collected. Based on patients' answers, the B-COMPASS will assign them into groups, list their support needs, and predict their relative adherence, forming their B-COMPASS description. Patients will then be randomised into either 1) an intervention arm, or 2) a control arm using stratified randomisation via the Adherence Intelligence Visualisation Platform (AIVP), ensuring balance in B-COMPASS descriptions, gender, and age. 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.
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.
Accuracy of the B-COMPASS to predict adherence
Predictive accuracy of B-COMPASS of adherence to treatment will be validated against TAP-Q in Visit 1 and other specific adherence measurements for all participants. The B-COMPASS is an adherence prediction model based on the BEAMER questionnaire, which is a questionnaire that contains 22 questions about subjective health experience and subjective awareness of health condition. Likert scale with 7 response options, 1 = Fully disagree, 7 = Fully agree (11 questions). Likert scale with 6 response options, 1 = Fully disagree, 6 = Fully agree (4 questions). Likert scale with 5 response options, 1 = Fully disagree, 5 = Fully agree (5 questions). Score on a 10-step ladder where step 1 = The day at the past 4 weeks I felt at my worst, step 10 = The day in the past 4 weeks I felt at my best (2 questions).
Time frame: At first data collection
Validity of B-COMPASS groupings
B-COMPASS groupings will be validated through the qualitative thematic analysis of interviews and focus groups with patients and HCPs in the intervention groups.
Time frame: 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.
Accuracy of identification of patients' support needs
The accuracy of the support needs identified by the B-COMPASS will also be analysed through qualitative analysis of focus groups and interviews with the intervention groups.
Time frame: 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.
Reliability of B-COMPASS prediction over time
The over-time reliability of the B-COMPASS will be measured by comparing its groupings and adherence prediction results at the first and second visits for the control group.
Time frame: 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.
Extent to which the B-COMPASS affects patient adherence to treatment
The impact of the engagement prompted by the support needs identified by the B-COMPASS model on the adherence, will be measured through pre-post intervention design using adherence measurements results from the first and second visits (changes from baseline). Adherence will be measured through TAP-Q, MARS-5, or dispensation and prescription electronic records, as specified above.
Time frame: 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.
Patients' perceptions of the received engagement with HCPs based on B-COMPASS
Patients' experience and perceptions will be measured by a perspectives of B-COMPASS Likert-scale questionnaire that have 5 questions, as well as semi-structured interviews in the intervention group. The study patient perceptions questionnaire contains 5 questions (i) understanding of how to adhere to treatment, (ii) perceptions regarding whether the received support is useful (iii) perceptions regarding whether the tools received is sufficient to adhere to treatment, (iv) perception regarding whether the given support motivates the patient to be adherent, and (v) satisfaction with the support received. Likert scale with 7 response options, 1 = Fully disagree, 7 = Fully agree.
Time frame: 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.
Perception of HCPs of the B-COMPASS
HCPs perceptions will be measured by a perspectives of B-COMPASS questionnaire of 5 questions, as well as focus groups The study HCP perceptions questionnaire contains 5 questions about (i) ease of use of B-COMPASS, perceived (ii) impact of B-COMPASS cards on interaction with patients, (iii) impact of B-COMPASS patient description in supporting patients, (iv) intention to use B-COMPASS in the future, and (v) perceived benefit of B-COMPASS cards on patient engagement. Likert scale with 7 response options, 1 = Fully disagree, 7 = Fully agree.
Time frame: 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.
Cost-effectiveness impact of B-COMPASS on healthcare utilisation
Health-related quality of life will be assessed with EQ5D-5L and transformed into utilities to parametrize a cost-utility analysis of the B-COMPASS. The EQ-5D-5L is a standardized measure of health-related quality of live that comprises 5 dimensions: mobility, self-care, usual activities, pain/discomfort, and anxiety/depression. Each dimension has five levels of severity, ranging from "no problems" to "extreme problems".
Time frame: 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.
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Ran from Mar 2025 to primary completion in Aug 2026, 17 months.
Of 1,077 non-industry interventional studies with no phase under Cardiovascular Diseases, half reached primary completion within 26 months of starting (the median), counting those still running; a quarter within 12 and three quarters within 48. This study's 17 months is below that.
Counting every sponsor, half of 1,216 studies reached it within 26 months; a quarter within 12 and three quarters within 49.
Cardiovascular Diseases covers many different conditions, not one, so the studies compared here vary widely. Read these figures as a rough guide.
Since we started tracking on Sep 25, 2026, the dates moved once, on Oct 21, 2026: primary completion Jun 2026 → Aug 2026 and completion Sep 2026 → Aug 2026.
Earlier changes are on the record history on ClinicalTrials.gov ↗
How these figures are worked out, and which studies are left out of them.
From the registry record's own update history. This site started tracking changes on Sep 25, 2026; for anything earlier, see the record history on ClinicalTrials.gov ↗
This study is completed, as verified in Oct 2026. You cannot join it, but the record below documents what was studied.
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Technical University of Madrid