[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"health-studies-list:{\"conditionNormalized\":\"falls-risk\",\"overallStatus\":[\"RECRUITING\",\"AVAILABLE\",\"NOT_YET_RECRUITING\"],\"orderBy\":\"LastUpdateSubmitDate:desc\",\"size\":25,\"offset\":0}":3,"health-study-condition:falls-risk":52},{"pageToken":4,"total":5,"offset":6,"count":5,"results":7},null,3,0,[8,37,67],{"id":9,"slug":10,"hasResults":11,"nctId":12,"briefTitle":13,"officialTitle":14,"acronym":4,"eligibilityCriteria":15,"healthyVolunteers":11,"sex":16,"minAge":17,"maxAge":4,"enrollmentInfo":18,"targetDuration":4,"studyType":21,"phases":4,"briefSummary":22,"conditions":23,"keywords":4,"overallStatus":25,"whyStopped":4,"lastUpdateSubmitDate":26,"lastUpdatePostDateStruct":27,"startDateStruct":30,"completionDateStruct":32,"leadSponsor":34,"locationsCount":5},"100501500","effectiveness-of-an-automated-falls-risk-screening-and-referral-tool-in-the-emergency-department-ed-100501500",false,"NCT05810064","Effectiveness of an Automated Falls-Risk Screening and Referral Tool in the Emergency Department (ED)","Preventing Future Falls in Older Adult ED Patients: Evaluating the Implementation and Effectiveness of a Novel Automated Screening and Referral Intervention - Assessing Outcomes From Medical Records and Medicare Claims Data","Retrospective analysis will include data from:\n\n* ED patients 65 years or older\n* discharged from the ED (not admitted)","ALL","65 Years",{"count":19,"type":20},30000,"ESTIMATED","OBSERVATIONAL","The purpose of this retrospective cohort study is to evaluate the effectiveness of an EHR-based clinical decision support system (CDS) for automatically screening older adult ED patients for risk of future falls and providing ED clinicians opportunity to place referrals orders to the UW Health Mobility and Falls Clinic for those at highest risk prior to discharge.\n\nThis CDS tool has already been implemented at the UW Hospital ED, and as a QI initiative will be implemented in a staged process at two other UW Health-affiliated emergency departments (The American Center and Swedish American Hospital).",[24],"Falls-Risk","RECRUITING","2026-02-13",{"date":28,"type":29},"2026-02-17","ACTUAL",{"date":31,"type":29},"2022-02-22",{"date":33,"type":20},"2026-08",{"name":35,"class":36},"University of Wisconsin, Madison","OTHER",{"id":38,"slug":39,"hasResults":11,"nctId":40,"briefTitle":41,"officialTitle":42,"acronym":4,"eligibilityCriteria":43,"healthyVolunteers":44,"sex":16,"minAge":4,"maxAge":4,"enrollmentInfo":45,"targetDuration":4,"studyType":47,"phases":48,"briefSummary":50,"conditions":51,"keywords":53,"overallStatus":57,"whyStopped":4,"lastUpdateSubmitDate":58,"lastUpdatePostDateStruct":59,"startDateStruct":61,"completionDateStruct":63,"leadSponsor":65,"locationsCount":4},"100598957","examining-nurses-trust-and-acceptance-of-fair-an-ai-powered-falls-risk-recommender-100598957","NCT07078240","Examining Nurses' Trust and Acceptance of FAIR, an AI-powered Falls Risk Recommender","\"You Sure or Not?\" Examining the Trust, Acceptance and Adoption of Falls Risk - Artificial Intelligence Recommender (FAIR) System by Nurses","Inclusion Criteria:\n\n* Practicing nurse involved in falls risk assessments of patients\n\nExclusion Criteria:\n\n\\-",true,{"count":46,"type":20},60,"INTERVENTIONAL",[49],"NA","An exploratory mixed-method study will be conducted to test acceptance and trust of an AI-powered falls risk predictor system by inpatient hospital nurses",[52],"Falls Risk",[54,55,56],"Artificial Intelligence trust","Artificial Intelligence acceptance","Artificial Intelligence","NOT_YET_RECRUITING","2025-07-21",{"date":60,"type":29},"2025-07-22",{"date":62,"type":20},"2027-01-01",{"date":64,"type":20},"2029-06-30",{"name":66,"class":36},"Tan Tock Seng Hospital",{"id":68,"slug":69,"hasResults":11,"nctId":70,"briefTitle":71,"officialTitle":71,"acronym":4,"eligibilityCriteria":72,"healthyVolunteers":44,"sex":16,"minAge":17,"maxAge":4,"enrollmentInfo":73,"targetDuration":4,"studyType":21,"phases":4,"briefSummary":75,"conditions":76,"keywords":4,"overallStatus":25,"whyStopped":4,"lastUpdateSubmitDate":80,"lastUpdatePostDateStruct":81,"startDateStruct":83,"completionDateStruct":85,"leadSponsor":87,"locationsCount":89},"100590006","validating-a-multifactorial-algorithm-to-predict-fall-risk-in-community-dwelling-older-persons-aged-65-years-or-older-100590006","NCT06961799","Validating a Multifactorial Algorithm to Predict Fall Risk in Community Dwelling Older Persons Aged 65 Years or Older","Inclusion Criteria:\n\n* 65years or older\n* community dwellers\n* absence of surgery or exacerbation of symptoms in the last 6 months\n* ability to stand and walk independently (alone), possibly with an walking aid.\n\nExclusion Criteria:\n\n* \\\u003C65 years of age\n* surgery within the previous 6 months affecting gait and mobility\n* exacerbation of symptoms coming from a diagnosed disease\n* older adults with insufficient (language) comprehension to complete the tests and questionnaires",{"count":74,"type":20},228,"Falls in older adults have an annual incidence between 23 and 34% for persons of 65 years and older. The lack of transfer of promising research results on falls prevention to daily practice may have several explanations. One of the first concerns for that matter may be a valid and sensitive selection of the persons at risk who are eligible for fall prevention interventions\n\nGoals of the prospective obeservational study:\n\n1. To validate a new, comprehensive, multifactorial screeningsintrument to predict the risk on falls in community dwelling, Belgian, older adults (\\>65years or older).\n2. To optimize the new, comprehensive, multifactorial screeningsintrument and to specify correct cut off scores\n\nResearchers will compare the data of the accuracy of new algorithm with the current Belgian policy.\n\nParticipants will participate in a one-time testing moment, where they will be asked some questions about general characteristics and medical history, followed by two questionnaire and seven physical tests . Based on this data, their fall risk will be assessed. In the year that follows, the older person's fall behavior will be monitored with a monthly falls calender. Participant will be asked to fill out these calenders everyday ('Did you fall today?' YES\u002FNO) and send them at the end of each month to the researchers, digitally or postal.",[77,78,52,79],"Aged 65 Years or Older","Community Dwelling Older Adults","Falls (Accidents) in Old Age","2025-05-05",{"date":82,"type":29},"2025-05-08",{"date":84,"type":29},"2025-03-20",{"date":86,"type":20},"2026-12",{"name":88,"class":36},"University Ghent",1]