[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"health-study-detail:100575403":3},{"organization":4,"armGroups":7,"interventions":14,"overallOfficials":21,"centralContacts":26,"locations":31,"responsibleParty":46,"collaborators":48,"id":52,"slug":53,"hasResults":54,"nctId":55,"briefTitle":56,"officialTitle":57,"acronym":11,"eligibilityCriteria":58,"healthyVolunteers":54,"sex":59,"minAge":11,"maxAge":60,"enrollmentInfo":61,"targetDuration":11,"studyType":64,"phases":65,"briefSummary":67,"conditions":68,"keywords":71,"overallStatus":34,"whyStopped":11,"lastUpdateSubmitDate":77,"lastUpdatePostDateStruct":78,"startDateStruct":81,"completionDateStruct":83,"leadSponsor":85,"locationsCount":86},{"fullName":5,"class":6},"University of Wisconsin, Madison","OTHER",[8],{"label":9,"type":10,"description":11,"interventionNames":12},"Pediatric eCART","EXPERIMENTAL",null,[13],"Device: Pediatric eCART",[15],{"type":16,"name":9,"description":17,"armGroupLabels":18,"otherNames":19},"DEVICE","Integration of the pediatric version of electronic Cardiac Arrest Risk Triage as a clinical decision support tool within Epic for use by clinicians",[9],[20],"electronic Cardiac Arrest Risk Triage",[22],{"name":23,"affiliation":24,"role":25},"Anoop Mayampurath, PhD","UW School of Medicine and Public Health","PRINCIPAL_INVESTIGATOR",[27],{"name":23,"role":28,"phone":29,"phoneExt":11,"email":30},"CONTACT","608-261-1028","mayampurath@wisc.edu",[32],{"facility":33,"status":34,"city":35,"state":36,"zip":37,"country":38,"countryCode":39,"cosmosGeoPoint":40,"geoPoint":45,"contacts":11},"American Family Children's Hospital","RECRUITING","Madison","Wisconsin","53792","United States","US",{"type":41,"coordinates":42},"Point",[43,44],-89.40123,43.07305,{"lat":44,"lon":43},{"type":47,"investigatorFullName":11,"investigatorTitle":11,"investigatorAffiliation":11,"oldNameTitle":11,"oldOrganization":11},"SPONSOR",[49],{"name":50,"class":51},"AgileMD, Inc.","INDUSTRY","100575403","evaluation-of-pediatric-ecart-implementation-100575403",false,"NCT06771830","Evaluation of Pediatric eCART Implementation","A Rapid Diagnostic of Risk in Hospitalized Pediatric Patients to Improve Outcomes Using Machine Learning","Inclusion Criteria (pediatric patients):\n\n* All pediatric patients scored on pediatric eCART (or eligible for scoring on either algorithm in the pre-implementation period) will be screened for study eligibility.\n* Patients eligible for pediatric eCART scoring include pediatric (\\\u003C18 years of age) patients\n* Inpatient locations\n\nExclusion Criteria (pediatric patients):\n\n* Patients who are ineligible for pediatric eCART scoring\n* Neonates and birth encounters will be excluded from the pediatric eCART study\n\nInclusion Criteria (nurse clinicians):\n\n* UW Health nurses who interact with eCART during patient care\n\nExclusion Criteria (nurse clinician):\n\n* UW Health nurses no longer employed at UW Health","ALL","17 Years",{"count":62,"type":63},30000,"ESTIMATED","INTERVENTIONAL",[66],"NA","This is a study comparing 3 years of retrospective data (pre-implementation) to 2 years of prospective data after the implementation of a pediatric version of Electronic Cardiac Arrest Risk Triage (pediatric eCART), a clinical decision support (CDS) tool that uses electronic health records (EHR) to identify patients with high risk for life threatening outcomes. Up to 30,000 encounters with pediatric patients will be assessed. Acceptability of the pediatric eCART intervention will also be measured from pediatric nurse clinicians.",[69,70],"Pediatric ALL","Sepsis",[72,73,74,75,76],"machine learning","artificial intelligence","clinical decision support","triage","electronic medical records","2025-12-15",{"date":79,"type":80},"2025-12-17","ACTUAL",{"date":82,"type":80},"2025-12-01",{"date":84,"type":63},"2027-12",{"name":5,"class":6},1]