[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"health-study-detail:100657443":3},{"organization":4,"outcomesModule":7,"designInfo":13,"detailedDescription":20,"studyPopulation":11,"armGroups":21,"interventions":28,"overallOfficials":11,"centralContacts":11,"locations":11,"responsibleParty":36,"collaborators":11,"id":38,"slug":39,"hasResults":40,"nctId":41,"briefTitle":42,"officialTitle":43,"acronym":44,"eligibilityCriteria":45,"healthyVolunteers":40,"sex":46,"minAge":47,"maxAge":48,"enrollmentInfo":49,"targetDuration":11,"studyType":52,"phases":53,"briefSummary":54,"conditions":55,"keywords":57,"overallStatus":58,"whyStopped":11,"lastUpdateSubmitDate":59,"lastUpdatePostDateStruct":60,"startDateStruct":63,"completionDateStruct":65,"leadSponsor":67,"locationsCount":11},{"fullName":5,"class":6},"Oman Ministry of Health","OTHER_GOV",{"primaryOutcomes":8,"secondaryOutcomes":11,"otherOutcomes":11},[9],{"measure":10,"description":11,"timeFrame":12},"• Reduction in the prevalence of potentially inappropriate medication prescribing following OPIP Score integration, reassessed using the 2023 AGS Beers Criteria",null,"2 years",{"allocation":14,"interventionModel":15,"interventionModelDescription":16,"primaryPurpose":17,"observationalModel":11,"timePerspective":11,"maskingInfo":18},"NA","SINGLE_GROUP","A three-phase mixed-methods translational research design, integrating epidemiological evidence generation, digital health innovation, and real-world implementation evaluation","HEALTH_SERVICES_RESEARCH",{"masking":19,"maskingDescription":11,"whoMasked":11},"NONE","Study Rationale and Design Framework Geriatric prescribing safety represents a critical health services focus. This protocol evaluates an investigator-assigned digital health intervention designed to systematically intercept prescribing risks at the point of care. While the protocol includes a baseline run-in period to parameterize the software, the study functions globally as a prospective interventional trial. It measures the clinical efficacy of an AI-assisted clinical decision support system (CDSS) within an active primary care workflow.\n\nPhase 1: Baseline Assessment \\& Parameterization The study initiates with a prospective baseline assessment of a primary care patient cohort aged 65 or older. Investigators systematically extract data regarding active medication regimens, clinical diagnoses, and health expenditures. This phase applies the 2023 AGS Beers Criteria and STOPP\u002FSTART v3 criteria to establish a strict pre-intervention standard-of-care baseline for polypharmacy prevalence, PIP rates, and associated medication costs.\n\nPhase 2: Intervention Engineering \\& System Validation Data derived from Phase 1 are immediately used to program, calibrate, and validate the proprietary OPIP Score engine. This engine drives the bilingual (Arabic\u002FEnglish) POLYMED web calculator. The software applies machine learning algorithms to generate an explainable-AI narrative. This narrative visually highlights specific pharmacological risk vectors to actively prompt clinicians during patient evaluations.\n\nPhase 3: Prospective Interventional Workflow The core interventional component of the protocol utilizes a prospective before-and-after design to evaluate the tool's clinical impact.\n\n1. Protocol-Mandated Assignment: The investigator actively assigns participating primary care clinicians to integrate the POLYMED calculator into their clinical consultations. For all prospectively enrolled participants in this phase, clinicians are required by the study protocol to execute the web calculator at the point of care during the patient visit.\n2. Clinical Action and Decision Support: The software functions as an active advisory system. Upon receiving the real-time, explainable-AI risk alerts, clinicians are required by the study workflow to conduct a structured medication review. While clinicians maintain complete medical autonomy over final prescribing modifications, the review process itself is forced by the trial protocol.\n3. Justification for Interventional Framework: This study is classified as interventional because the systematic application of this specific AI-driven risk calculator is explicitly mandated by the investigator's protocol to alter clinical behavior and evaluate its direct effect on patient health outcomes. This intensive workflow and real-time risk feedback loop are not part of routine medical care in Oman and would not occur outside the context of this clinical trial. The study evaluates the resulting differences in prescribing patterns, safety metrics, and medication costs between the baseline standard of care and the active intervention phase.",[22],{"label":23,"type":24,"description":25,"interventionNames":26},"OPIP Score-Guided Medication Review","EXPERIMENTAL","A prospective, single-arm cohort of primary care clinicians and their elderly patients (65 years or older) attending chronic disease clinics. The investigator assigns participating clinicians to systematically integrate the OPIP Score calculator into their active workflow. For all prospectively enrolled patients in this phase, pharmacists are required by protocol to utilize the full dashboard and family physicians are prompted via a lightweight prescribing alert to guide structured medication reviews. Clinical and prescribing outcomes from this active intervention phase are evaluated against each patient's own pre-intervention Phase 1 baseline data",[27],"Device: OPIP Score Calculator (Oman Potentially Inappropriate Prescribing Risk Score)",[29],{"type":30,"name":31,"description":32,"armGroupLabels":33,"otherNames":34},"DEVICE","OPIP Score Calculator (Oman Potentially Inappropriate Prescribing Risk Score)","A bilingual (Arabic\u002FEnglish) web-based clinical decision support tool designed to systematically intercept prescribing risks. The software features a three-layer architecture: a rule-based engine executing the 2023 AGS Beers Criteria (incorporating drug-drug interactions and renal dosing alerts), a risk-scoring model calibrated to local Omani clinical data, and an explainable-AI narrative providing explicit, prioritized recommendations. Per the interventional study protocol, clinicians are mandated to deploy this tool at the point of care during consultations to trigger real-time medication reviews. While clinicians maintain final medical autonomy over prescribing modifications, the systematic application of the tool and the mandatory documentation of clinical overrides are driven prospectively by the investigator's study design to alter and optimize the standard care pathway.",[23],[35],"POLYMED AI Risk Calculator (OPIP Score)",{"type":37,"investigatorFullName":11,"investigatorTitle":11,"investigatorAffiliation":11,"oldNameTitle":11,"oldOrganization":11},"SPONSOR","100657443","a-digital-tool-to-help-doctors-and-pharmacists-prescribe-medicines-more-safely-for-older-adults-in-oman-100657443",false,"NCT07840222","A Digital Tool to Help Doctors and Pharmacists Prescribe Medicines More Safely for Older Adults in Oman","POLYMED: A Triphasic Explainable AI-Assisted Potentially Inappropriate Prescribing Risk Calculator to Optimize Medication Safety and Pharmaceutical Efficiency Among Elderly Patients in Oman","POLYMED","Inclusion Criteria:\n\n* • Aged 65 years or older at the time of recruitment\n\n  * Registered in a chronic disease clinic in a participating primary healthcare centre\n  * Receiving at least one long-term prescribed medication for chronic disease management\n  * Able to provide informed consent independently\n\nExclusion Criteria:\n\n* • Cognitive impairment or severe communication limitations precluding informed consent\n\n  * Currently receiving palliative care\n  * Currently admitted as an inpatient during the recruitment period\n  * Major medication regimen change within the preceding four weeks","ALL","65 Years","85 Years",{"count":50,"type":51},400,"ESTIMATED","INTERVENTIONAL",[14],"This is a prospective, multi-phase interventional study evaluating the clinical utility and efficacy of POLYMED-a bilingual (Arabic\u002FEnglish) web-based, explainable-AI medication risk calculator-on optimizing geriatric medication safety in Muscat primary care. The primary objective is to evaluate whether deploying this clinical decision support software at the point of care systematically reduces potentially inappropriate prescribing (PIP) and polypharmacy among elderly patients.\n\nThe study protocol integrates baseline parameterization with an active clinical intervention:\n\n* Phase 1 \\& 2 (Baseline \\& Tool Validation): A baseline cross-sectional assessment of elderly patients is conducted to quantify local prescribing burdens via international criteria (2023 AGS Beers \u002F STOPP\u002FSTART v3). These prospective baseline data are used to calibrate and validate the OPIP Score engine powering the POLYMED calculator.\n* Phase 3 (Active Intervention Phase): A prospective before-and-after trial evaluates the direct clinical effect of the tool. Clinicians are assigned by the study protocol to actively deploy the POLYMED calculator at the point of care during consultations. The trial measures the resulting changes in polypharmacy burden and medication spending compared to standard, routine care.",[56],"Polypharmacy",[44],"NOT_YET_RECRUITING","2026-09-21",{"date":61,"type":62},"2026-09-24","ACTUAL",{"date":64,"type":51},"2026-11",{"date":66,"type":51},"2028-12-31",{"name":5,"class":6}]