[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"health-study-detail:100607946":3},{"organization":4,"outcomesModule":7,"designInfo":18,"detailedDescription":21,"studyPopulation":22,"armGroups":17,"interventions":17,"overallOfficials":23,"centralContacts":28,"locations":34,"responsibleParty":57,"collaborators":17,"id":59,"slug":60,"hasResults":61,"nctId":62,"briefTitle":63,"officialTitle":64,"acronym":17,"eligibilityCriteria":65,"healthyVolunteers":61,"sex":66,"minAge":67,"maxAge":68,"enrollmentInfo":69,"targetDuration":17,"studyType":72,"phases":17,"briefSummary":73,"conditions":74,"keywords":76,"overallStatus":37,"whyStopped":17,"lastUpdateSubmitDate":79,"lastUpdatePostDateStruct":80,"startDateStruct":83,"completionDateStruct":85,"leadSponsor":87,"locationsCount":88},{"fullName":5,"class":6},"PG Medical Systems Ltd.","INDUSTRY",{"primaryOutcomes":8,"secondaryOutcomes":13,"otherOutcomes":17},[9],{"measure":10,"description":11,"timeFrame":12},"Agreement by percent agreement","Interrater reliability defined as the agreement between the PGS 1.0 algorithm and Pain Expert in rating pain patients' pain diagnosis as measured by percent agreement.","At the completion of patients' enrollment, agreement will be assessed between PGS 1.0 diagnosis and the expert diagnosis per patient (diagnosis of expert at the intake to the pain clinic and PGS 1.0 diagnosis as per the data the patient filled in).",[14],{"measure":15,"description":16,"timeFrame":12},"Agreement by Cohen's Kappa coefficient.","Interrater reliability defined as the agreement between the PGS 1.0 algorithm and Pain Expert in rating pain patients' diagnosis as measured by Cohen's Kappa coefficient.",null,{"allocation":17,"interventionModel":17,"interventionModelDescription":17,"primaryPurpose":17,"observationalModel":19,"timePerspective":20,"maskingInfo":17},"CASE_ONLY","PROSPECTIVE","Background and Rationale:\n\nChronic pain is a global epidemic. On average, 20% of the Western population suffers from chronic pain, and in some countries, such as the U.S., the number reaches up to 30%. When chronic pain is not properly diagnosed and treated, it leads not only to patient suffering but also to serious comorbidities, increased use of healthcare services, and, in growing numbers, addiction and misuse of prescription drugs.\n\nPain medicine, a relatively young medical field, offers evidence-based diagnosis and treatment tailored to the patient's pain mechanisms. However, there is a major gap between the large number of patients and the very limited number of pain specialists (around 4,000 in the U.S. and about 80 in Israel). This shortage leads to extremely long waiting times (5-6 months) while patients continue to suffer.\n\nTo help close this gap, PG Medical Systems, together with Dr. Simon Wolfson (Head of the Pain Institute at Rambam Health Care Campus), developed an algorithm that analyzes patient symptoms and provides recommendations for pain diagnosis and treatment pathways.\n\nStudy Objective:\n\nThe study aims to prospectively validate the algorithm's performance by collecting patient data via an online questionnaire at the Rambam Pain Institute. The results will compare the algorithm's diagnoses to those of pain specialists.\n\nStudy Procedures:\n\nPatients visiting the Rambam Pain Institute (first-time or follow-up appointments) will be invited to join the study. After signing informed consent, they will complete an online questionnaire with the help of a research assistant. This is a one-time activity, following their medical consultation. The study does not involve additional clinical follow-up. Participation will not affect the patient's diagnosis or treatment.\n\nDuration:\n\nEach participant will spend about 45-60 minutes, including the consent process and questionnaire completion.\n\nCompensation:\n\nParticipants will receive 100 NIS for their time.\n\nData Management and Privacy:\n\nThe study will collect only non-identifiable patient data. Each participant will be assigned a code number. Identifying details will remain securely stored at Rambam, linked only by the consent form. This allows for possible follow-up research but ensures that the sponsor company has access only to de-identified data.\n\nData Security:\n\nAll data is stored on Amazon's secure cloud with advanced encryption. Access requires strict authentication, servers are closed to public internet, and only approved private networks can connect. All data is encrypted in transfer and storage. Importantly, the system does not collect identifiable patient information.","Male and Female patients aged 18-80, consecutively all patients referred to a pain expert.",[24],{"name":25,"affiliation":26,"role":27},"Simon Vulfsons, MD","Rambam Health Care Campus","PRINCIPAL_INVESTIGATOR",[29],{"name":30,"role":31,"phone":32,"phoneExt":17,"email":33},"Shany Blum, MD PhD","CONTACT","+972545331773","shany@pgmeds.com",[35],{"facility":36,"status":37,"city":38,"state":17,"zip":39,"country":40,"countryCode":41,"cosmosGeoPoint":42,"geoPoint":47,"contacts":48},"Pain Medicine Institute, Rambam Health Care Campus","RECRUITING","Haifa","31906","Israel","IL",{"type":43,"coordinates":44},"Point",[45,46],34.99928,32.81303,{"lat":46,"lon":45},[49,53,54],{"name":50,"role":31,"phone":51,"phoneExt":17,"email":52},"May Haddad, PhD","+97247772166","ma_haddad@rambam.health.gov.il",{"name":25,"role":27,"phone":17,"phoneExt":17,"email":17},{"name":55,"role":56,"phone":17,"phoneExt":17,"email":17},"Amir Minerbi, MD PhD","SUB_INVESTIGATOR",{"type":58,"investigatorFullName":17,"investigatorTitle":17,"investigatorAffiliation":17,"oldNameTitle":17,"oldOrganization":17},"SPONSOR","100607946","validating-and-evaluating-the-pain-medicine-digital-workflow-algorithm-pgs-10-100607946",false,"NCT07195162","Validating and Evaluating the Pain Medicine Digital Workflow Algorithm (PGS 1.0)","Prospective Validation and Performance Evaluation of the Algorithm of the Pain Medicine Digital Workflow (PGS 1.0)","Inclusion Criteria:\n\n* Patient is willing and capable of providing Informed Consent.\n* Pain persisting for at least 1 month.\n\nExclusion Criteria:\n\nNone","ALL","18 Years","80 Years",{"count":70,"type":71},200,"ESTIMATED","OBSERVATIONAL","This is a prospective, non-randomized, double blind, single center, single arm, validation study, to evaluate the performance of PGS 1.0 algorithm in analyzing pain specific symptoms and medical history data of pain patients referred to a pain expert consultation.",[75],"Chronic Pain",[75,77,78],"Diagnosis","Algorithm","2026-09-24",{"date":81,"type":82},"2026-09-25","ACTUAL",{"date":84,"type":82},"2025-09-17",{"date":86,"type":71},"2027-02",{"name":5,"class":6},1]