[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"health-study-detail:100581945":3},{"organization":4,"armGroups":7,"interventions":19,"overallOfficials":25,"centralContacts":30,"locations":38,"responsibleParty":177,"collaborators":180,"id":209,"slug":210,"hasResults":211,"nctId":212,"briefTitle":213,"officialTitle":213,"acronym":214,"eligibilityCriteria":215,"healthyVolunteers":211,"sex":216,"minAge":12,"maxAge":12,"enrollmentInfo":217,"targetDuration":12,"studyType":220,"phases":221,"briefSummary":223,"conditions":224,"keywords":231,"overallStatus":41,"whyStopped":12,"lastUpdateSubmitDate":235,"lastUpdatePostDateStruct":236,"startDateStruct":239,"completionDateStruct":241,"leadSponsor":243,"locationsCount":244},{"fullName":5,"class":6},"Technical University of Madrid","OTHER",[8,13],{"label":9,"type":10,"description":11,"interventionNames":12},"Control arm","NO_INTERVENTION","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\u002FResearch Leads will not be informed of their B-COMPASS description. Where possible, at pilot sites, HCPs\u002FResearch Leads will also be randomised to ensure that HCPs\u002FResearch Leads in the control groups have as limited knowledge of the B-COMPASS\u002Fpatient description as possible.",null,{"label":14,"type":15,"description":16,"interventionNames":17},"Intervention arm","ACTIVE_COMPARATOR","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.",[18],"Behavioral: B-COMPASS implementation",[20],{"type":21,"name":22,"description":23,"armGroupLabels":24,"otherNames":12},"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.",[14],[26],{"name":27,"affiliation":28,"role":29},"Giuseppe Fico, Professor","Universidad Politecnica de Madrid","PRINCIPAL_INVESTIGATOR",[31,35],{"name":27,"role":32,"phone":33,"phoneExt":12,"email":34},"CONTACT","(+34) 91 067 2636","giuseppe.fico@upm.es",{"name":36,"role":32,"phone":12,"phoneExt":12,"email":37},"Beatriz Merino, PhD","beatriz.merino@upm.es",[39,59,73,87,98,113,126,140,154,163],{"facility":40,"status":41,"city":42,"state":12,"zip":12,"country":43,"countryCode":44,"cosmosGeoPoint":45,"geoPoint":50,"contacts":51},"UDUS - Heinrich-Heine-University Duesseldorf","RECRUITING","Düsseldorf","Germany","DE",{"type":46,"coordinates":47},"Point",[48,49],6.77927,51.22319,{"lat":49,"lon":48},[52,56],{"name":53,"role":32,"phone":54,"phoneExt":12,"email":55},"Kathrin Scheckenbach","0000000000","Kathrin.Scheckenbach@med.uni-duesseldorf.de",{"name":57,"role":32,"phone":12,"phoneExt":12,"email":58},"Nicole Sander","Nicole.Sander@med.uni-duesseldorf.de",{"facility":60,"status":41,"city":61,"state":12,"zip":12,"country":62,"countryCode":63,"cosmosGeoPoint":64,"geoPoint":68,"contacts":69},"FISM - Italian Multiple Sclerosis Foundation","Genova","Italy","IT",{"type":46,"coordinates":65},[66,67],11.87211,45.21604,{"lat":67,"lon":66},[70],{"name":71,"role":32,"phone":54,"phoneExt":12,"email":72},"Chiara Briasco","chiara.briasco@fismets.it",{"facility":74,"status":41,"city":75,"state":12,"zip":12,"country":76,"countryCode":77,"cosmosGeoPoint":78,"geoPoint":82,"contacts":83},"WDO - World Duchenne Organization","Veenendaal","Netherlands","NL",{"type":46,"coordinates":79},[80,81],5.55891,52.02863,{"lat":81,"lon":80},[84],{"name":85,"role":32,"phone":54,"phoneExt":12,"email":86},"Karolina Podolska","karolina.podolska@worldduchenne.org",{"facility":88,"status":41,"city":89,"state":90,"zip":91,"country":92,"countryCode":93,"cosmosGeoPoint":12,"geoPoint":12,"contacts":94},"AHUS - Akershus University Hospital","Lørenskog","Akershus","1478","Norway","NO",[95],{"name":96,"role":32,"phone":54,"phoneExt":12,"email":97},"Harald Hrubos-Strøm","janhar@uio.no",{"facility":99,"status":41,"city":100,"state":12,"zip":101,"country":102,"countryCode":103,"cosmosGeoPoint":104,"geoPoint":108,"contacts":109},"APDP Diabetes Portugal","Lisbon","1250-203","Portugal","PT",{"type":46,"coordinates":105},[106,107],-9.1498,38.72509,{"lat":107,"lon":106},[110],{"name":111,"role":32,"phone":54,"phoneExt":12,"email":112},"Rogério Ribeiro","rogerio.ribeiro@apdp.pt",{"facility":114,"status":41,"city":115,"state":12,"zip":12,"country":102,"countryCode":103,"cosmosGeoPoint":116,"geoPoint":120,"contacts":121},"MEDCIDS - Departamento de Medicina da Comunidade Informação e Decisão em Saúde","Porto",{"type":46,"coordinates":117},[118,119],-8.61097,41.1485,{"lat":119,"lon":118},[122],{"name":123,"role":32,"phone":124,"phoneExt":12,"email":125},"Rita Amaral","000000000","rita.s.amaral@gmail.com",{"facility":127,"status":41,"city":128,"state":12,"zip":12,"country":129,"countryCode":130,"cosmosGeoPoint":131,"geoPoint":135,"contacts":136},"UMCM - University Medical Center Maribor","Maribor","Slovenia","SI",{"type":46,"coordinates":132},[133,134],15.64593,46.55583,{"lat":134,"lon":133},[137],{"name":138,"role":32,"phone":54,"phoneExt":12,"email":139},"Šefik Salkunić","Sefik.SALKUNIC@ukc-mb.si",{"facility":141,"status":41,"city":142,"state":12,"zip":12,"country":143,"countryCode":144,"cosmosGeoPoint":145,"geoPoint":149,"contacts":150},"FHUNJ - Fundación para la Investigación Biomédica del Hospital Infantil Universitario Niño Jesús","Madrid","Spain","ES",{"type":46,"coordinates":146},[147,148],-3.70256,40.4165,{"lat":148,"lon":147},[151],{"name":152,"role":32,"phone":54,"phoneExt":12,"email":153},"Andrés Castillo","andres.castillo@salud.madrid.org",{"facility":155,"status":41,"city":142,"state":12,"zip":12,"country":143,"countryCode":144,"cosmosGeoPoint":156,"geoPoint":158,"contacts":159},"FIIBAP - Fundación para la Investigación e Innovación Biosanitaria de Atención Primaria",{"type":46,"coordinates":157},[147,148],{"lat":148,"lon":147},[160],{"name":161,"role":32,"phone":54,"phoneExt":12,"email":162},"Jaime Barrio Cortes","jaime.barrio@salud.madrid.org",{"facility":164,"status":165,"city":166,"state":12,"zip":12,"country":167,"countryCode":12,"cosmosGeoPoint":168,"geoPoint":172,"contacts":173},"KCRI - Kilimanjaro Clinical Research Institute","NOT_YET_RECRUITING","Moshi","Tanzania",{"type":46,"coordinates":169},[170,171],37.33333,-3.35,{"lat":171,"lon":170},[174],{"name":175,"role":32,"phone":54,"phoneExt":12,"email":176},"Victor Mosha","v.mosha@kcri.ac.tz",{"type":29,"investigatorFullName":178,"investigatorTitle":179,"investigatorAffiliation":5,"oldNameTitle":12,"oldOrganization":12},"Beatriz Merino","Postdoctoral researcher",[181,183,186,188,190,193,195,197,199,201,203,205,207],{"name":182,"class":6},"University of Oslo",{"name":184,"class":185},"PredictBy Research and Consulting, S.L","INDUSTRY",{"name":187,"class":185},"Pfizer",{"name":189,"class":185},"Merck KGaA, Darmstadt, Germany",{"name":191,"class":192},"Empirica","UNKNOWN",{"name":194,"class":6},"Centre for Research and Technology Hellas",{"name":196,"class":192},"Innovation Sprint",{"name":198,"class":6},"Fundacio d'Investigacio en Atencio Primaria Jordi Gol i Gurina",{"name":200,"class":185},"Janssen Pharmaceutica N.V., Belgium",{"name":202,"class":185},"Novo Nordisk A\u002FS",{"name":204,"class":185},"Servier Affaires Médicales",{"name":206,"class":185},"Takeda Pharmaceuticals International, Inc.",{"name":208,"class":6},"Tilburg University","100581945","behavioral-and-adherence-model-for-improving-quality-health-outcomes-and-cost-effectiveness-of-healthcare-100581945",false,"NCT06856902","BEhavioral and Adherence Model for Improving Quality, Health Outcomes and Cost-Effectiveness of healthcaRe","BEAMER","Inclusion Criteria:\n\n* Having the diagnosis of the pilot sites target groups described above as per clinical assessment or validated diagnosis criteria\n* Having the age of the pilot sites target groups described above\n* Having accepted to participate in the study and provided written informed consent\n* Having the availability to participate on all study activities\n\nExclusion Criteria:\n\n* Individuals that do not fulfil ALL the inclusion criteria will be excluded to participate.","ALL",{"count":218,"type":219},3100,"ESTIMATED","INTERVENTIONAL",[222],"NA","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.\n\nSo 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\u002Fresearch 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\u002FResearch 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.",[225,226,227,228,229,230],"Cardiovascular Diseases","Endocrinology","Inmunology","Neurology","Oncology","Rare Diseases",[232,233,234],"Digital health","adherence to treatment","healthcare","2026-03-26",{"date":237,"type":238},"2026-04-01","ACTUAL",{"date":240,"type":238},"2025-03-01",{"date":242,"type":219},"2026-09-30",{"name":5,"class":6},10]