[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"health-studies-list:{\"conditionNormalized\":\"quality-indicators-health-care\",\"overallStatus\":[\"RECRUITING\",\"AVAILABLE\",\"NOT_YET_RECRUITING\"],\"orderBy\":\"LastUpdateSubmitDate:desc\",\"size\":25,\"offset\":0}":3,"health-study-condition:quality-indicators-health-care":27},{"pageToken":4,"total":5,"offset":6,"count":5,"results":7},null,3,0,[8,45,85],{"id":9,"slug":10,"hasResults":11,"nctId":12,"briefTitle":13,"officialTitle":14,"acronym":15,"eligibilityCriteria":16,"healthyVolunteers":17,"sex":18,"minAge":19,"maxAge":4,"enrollmentInfo":20,"targetDuration":4,"studyType":23,"phases":4,"briefSummary":24,"conditions":25,"keywords":28,"overallStatus":33,"whyStopped":4,"lastUpdateSubmitDate":34,"lastUpdatePostDateStruct":35,"startDateStruct":38,"completionDateStruct":40,"leadSponsor":42,"locationsCount":4},"100605035","quality-indicators-in-obstetrics-100605035",false,"NCT07157280","Quality Indicators in Obstetrics","Quality Indicators as a Tool for Continuous Improvement Process in Clinical Obstetrics","QUIG","Inclusion Criteria:\n\n* 18 years and older\n* staff in clinical obstetrics (midwife, physician)\n\nExclusion Criteria:\n\n* nurse in clinical obstetrics\n* staff in outpatient obstetrics",true,"ALL","18 Years",{"count":21,"type":22},150,"ESTIMATED","OBSERVATIONAL","The study examines whether midwives and doctors are familiar with quality indicators in clinical obstetrics and whether these are used as a tool for continuous improvement process.",[26,27],"Quality Health Care","Quality Indicators, Health Care",[29,30,31,32],"quality management","quality indicators","obstetrics","staff","NOT_YET_RECRUITING","2025-08-28",{"date":36,"type":37},"2025-09-05","ACTUAL",{"date":39,"type":22},"2025-09-01",{"date":41,"type":22},"2026-05-01",{"name":43,"class":44},"Martin-Luther-Universität Halle-Wittenberg","OTHER",{"id":46,"slug":47,"hasResults":11,"nctId":48,"briefTitle":49,"officialTitle":50,"acronym":51,"eligibilityCriteria":52,"healthyVolunteers":11,"sex":18,"minAge":4,"maxAge":4,"enrollmentInfo":53,"targetDuration":4,"studyType":55,"phases":56,"briefSummary":58,"conditions":59,"keywords":65,"overallStatus":33,"whyStopped":4,"lastUpdateSubmitDate":75,"lastUpdatePostDateStruct":76,"startDateStruct":78,"completionDateStruct":80,"leadSponsor":82,"locationsCount":84},"100580273","automatic-feedback-indicator-to-enhance-the-hospital-discharge-communication-between-acute-care-and-primary-care-100580273","NCT06835153","Automatic Feedback Indicator to Enhance the Hospital Discharge Communication Between Acute Care and Primary Care.","Automatic Feedback Indicator to Enhance the Hospital Discharge Communication Between Acute Care and Primary Care: a Randomized Controlled Cluster Trial","FIAQLS","Inclusion Criteria:\n\n* Patients hospitalized for at least 24 hours in participating services.\n* Patients discharged alive directly from participating services.\n\nExclusion Criteria:\n\n* Patients hospitalized for less than 24 hours.\n* Patients who died during hospitalization.\n* Stays in services not meeting inclusion criteria (e.g., psychiatry, long-term care, emergency services with rare direct discharges, or critical care units).",{"count":54,"type":22},132000,"INTERVENTIONAL",[57],"NA","This study, titled \"Automated Indicator Feedback for Improving the Quality of Discharge Letters: A Cluster-Randomized Controlled Trial\" (FIAQ-LS), aims to evaluate whether continuous real-time feedback to hospital teams can improve the quality of discharge letters. Discharge letters are critical for ensuring continuity of care and reducing adverse events by providing detailed information about a patient's hospital stay to both the patient and their primary care physician.\n\nThe study will be conducted at Grenoble Alpes University Hospital and involve 40 hospital services across three campuses. The trial design includes two parallel arms: an intervention group receiving monthly performance feedback through automated dashboards and a control group with no additional intervention. Services are randomized into these groups using a stratified cluster approach.\n\nThe primary objective is to assess whether this intervention increases the proportion of discharge letters validated on the day of discharge compared to usual care. Secondary objectives include evaluating patient satisfaction, rates of unplanned 30-day readmissions, and completeness of discharge letter content.\n\nThe study will include data from approximately 132,000 patient stays over two phases: a pre-implementation observational period (12 months) and an intervention phase (12 months). All data will be collected and analyzed anonymously, with findings expected to inform the broader implementation of quality improvement strategies in French hospitals.",[60,61,62,63,27,64],"Continuity of Care","Patient Safety","Hospital Discharge Communication Processes","Communication","Electronic Health Records",[66,67,68,69,70,71,72,73,74],"Discharge Summary","Patient Handover","Quality Improvement","Cluster Randomized Trial","Healthcare Outcomes","Patient Satisfaction","Quality Indicators","Real-Time Feedback","Electronic Health Records (EHR)","2025-02-13",{"date":77,"type":37},"2025-02-19",{"date":79,"type":22},"2025-03-01",{"date":81,"type":22},"2026-02-01",{"name":83,"class":44},"University Hospital, Grenoble",1,{"id":86,"slug":87,"hasResults":11,"nctId":88,"briefTitle":89,"officialTitle":90,"acronym":4,"eligibilityCriteria":91,"healthyVolunteers":11,"sex":18,"minAge":92,"maxAge":93,"enrollmentInfo":94,"targetDuration":4,"studyType":55,"phases":96,"briefSummary":97,"conditions":98,"keywords":101,"overallStatus":106,"whyStopped":4,"lastUpdateSubmitDate":107,"lastUpdatePostDateStruct":108,"startDateStruct":110,"completionDateStruct":112,"leadSponsor":114,"locationsCount":116},"100576553","artificial-intelligence-in-colonoscopy-100576553","NCT06786793","Artificial Intelligence in Colonoscopy","Artificial Intelligence in Endoscopic Diagnosis of Colorectal Polyps: A Prospective Randomized Study.","Inclusion Criteria:\n\n* Consent to participate in the study,\n* Age between 50 and 65 years,\n* Scheduled outpatient colonoscopy.\n\nExclusion Criteria:\n\n* Previous colonoscopy,\n* History of colorectal surgery,\n* Ongoing biological therapy for any indication,\n* Primary sclerosing cholangitis,\n* Familial polyposis syndrome,\n* Chronic diarrhea,\n* Ulcerative colitis,\n* Crohn's disease.","50 Years","65 Years",{"count":95,"type":22},630,[57],"Colorectal cancer is the second most common malignancy in the countries of the European Union. Colonoscopy is the primary method for detecting and preventing the development of colorectal cancer is endoscopic examination. This study aims to evaluate the impact of artificial intelligence on the detection rate of polyps and early stages of colorectal cancer.",[27,99,100],"Artificial Intelligence (AI)","Colonoscopy Diagnostic Techniques and Procedures",[102,103,99,104,105],"Quality Indicatiors","Colonoscopy","Computer-aided Detection (CADe)","Adenoma detection rate (ADR)","RECRUITING","2025-01-15",{"date":109,"type":37},"2025-01-22",{"date":111,"type":37},"2024-11-01",{"date":113,"type":22},"2025-12-31",{"name":115,"class":44},"Jagiellonian University",2]