[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"health-study-detail:100610151":3},{"organization":4,"outcomesModule":7,"designInfo":47,"detailedDescription":52,"studyPopulation":52,"armGroups":55,"interventions":68,"overallOfficials":52,"centralContacts":76,"locations":82,"responsibleParty":99,"collaborators":103,"id":107,"slug":108,"hasResults":109,"nctId":110,"briefTitle":111,"officialTitle":112,"acronym":113,"eligibilityCriteria":114,"healthyVolunteers":109,"sex":115,"minAge":116,"maxAge":52,"enrollmentInfo":117,"targetDuration":52,"studyType":120,"phases":121,"briefSummary":123,"conditions":124,"keywords":126,"overallStatus":85,"whyStopped":52,"lastUpdateSubmitDate":134,"lastUpdatePostDateStruct":135,"startDateStruct":138,"completionDateStruct":140,"leadSponsor":142,"locationsCount":143},{"fullName":5,"class":6},"Washington University School of Medicine","OTHER",{"primaryOutcomes":8,"secondaryOutcomes":13,"otherOutcomes":36},[9],{"measure":10,"description":11,"timeFrame":12},"Frequency of patients with a type and screen order placed during the preoperative clinic assessment visit","This is a binary outcome at the patient \u002F surgical case level, which will be aggregated across all patients in the study to produce an overall frequency. Placement of a type and screen order during the preoperative clinic assessment visit will be evaluated at the patient \u002F surgical case level. This includes orders placed and collected during the preoperative clinic assessment visit, as well as orders signed during the preoperative clinic assessment visit or subsequent follow up care and held to be drawn on the day of surgery.","Decision made during the preoperative assessment clinic visit",[14,18,22,25,28,32],{"measure":15,"description":16,"timeFrame":17},"Frequency of a valid type and screen order at the start of surgery","This is a binary outcome at the patient \u002F surgical case level, which will be aggregated across all patients in the study to produce an overall frequency. Valid type and screen order at the start of surgery (defined as resulted prior to 1h after anesthesia start). The 1 hour buffer is used to account for orders that were drawn prior to surgery but may not have resulted by the time the patient enters the operating room. This will include orders placed by the clinicians working in preoperative assessment clinic and any orders that may be placed by the day of surgery anesthesia or surgical teams. This will not include type and screen orders that have expired by the start of surgery. This is a secondary efficacy outcome that reflects type and screen ordering decisions by all members of the patient's care team.","Start of surgery (1 hour after Anesthesia Start)",{"measure":19,"description":20,"timeFrame":21},"Frequency of red cell transfusion during surgery","This is a binary outcome at the patient \u002F surgical case level, which will be aggregated across all patients in the study to produce an overall frequency. Administration of allogeneic packed red blood cells during surgery will be retrieved from the electronic health record. Documentation of transfusion is mandatory and the electronic health record scan is used to confirm the correct patient. This is a secondary efficacy outcome, as lack of a type and screen may prevent discretionary intraoperative transfusion.","During surgery",{"measure":23,"description":24,"timeFrame":21},"Frequency of emergency release blood use during surgery","This is a binary outcome at the patient \u002F surgical case level, which will be aggregated across all patients in the study to produce an overall frequency. Administration of emergency release allogeneic packed red blood cells will be retrieved from the electronic health record. These are either documented as volumes under the MTP tab or individually scanned as uncrossmatched red cells. This is the primary safety outcome of the study as emergency release blood may be administered if red cell transfusion is urgently indicated but a type and screen is not available. The frequency of this outcome will be reported overall across both groups, and stratified by whether the patient had an active type and screen at the start of surgery.",{"measure":26,"description":27,"timeFrame":21},"Frequency of red cell transfusion during surgery without an active type and screen at the start of surgery","This is a binary outcome at the patient \u002F surgical case level, which will be aggregated across all patients in the study to produce an overall frequency. This is the secondary safety outcome intended to capture false negative results, i.e., patients who required transfusion during surgery but did not have a preoperative type and screen. This outcome will be collected electronically from the EHR and will capture patients for whom the type and screen was resulted after the start of surgery (i.e., after 1h after anesthesia start), suggesting it was collected after the patient entered the operating room",{"measure":29,"description":30,"timeFrame":31},"Frequency of transfusion reaction","This is a binary outcome at the patient \u002F surgical case level, which will be aggregated across all patients in the study to produce an overall frequency. Transfusion reactions are reported by clinical teams to the blood bank, and the transfusion medicine service investigates and classifies each transfusion reaction. These investigation reports will be transmitted to the study team for adverse event reporting and outcome collection. This is also a secondary safety outcome for the study. Transfusion reactions will be reported stratified by category, as hemolytic transfusion reactions are the most relevant to the trial.","From time of surgery to hospital discharge or 30 days after surgery",{"measure":33,"description":34,"timeFrame":35},"Red cell transfusion during surgery where the preoperative clinic clinician did not order the type and screen but a subsequent clinician did","This is a secondary safety outcome intended to capture \"near-miss\" events, where a type and screen was not ordered by the preoperative clinic clinician or would not have been available based on the preoperative clinic clinician's orders, but subsequently another clinician (e.g., day of surgery anesthesia team or surgery team) ordered a type and screen so it was active at the start of surgery, defined with the same 1h after anesthesia start grace period as the main safety outcome. This secondary safety outcome was added at the request of the Data Safety Monitoring Board meeting on July 20, 2026.","Day of surgery",[37,41,44],{"measure":38,"description":39,"timeFrame":40},"Viewing S-PATH predictions (Implementation outcome)","Clinician-level measure of the frequency of viewing S-PATH predictions, retrieved from EHR audit log data","Through study completion, an average of 1 year",{"measure":42,"description":43,"timeFrame":40},"Acceptance of S-PATH recommendation (Implementation outcome)","Clinician-level measure of the frequency of the clinician's blood order during the preoperative clinic visit (1' outcome) matching S-PATH's recommendation",{"measure":45,"description":46,"timeFrame":40},"Cost assessment","Estimate of the cost savings associated with S-PATH use",{"allocation":48,"interventionModel":49,"interventionModelDescription":50,"primaryPurpose":51,"observationalModel":52,"timePerspective":52,"maskingInfo":53},"RANDOMIZED","CROSSOVER","Stepped-wedge cluster randomized trial","SCREENING",null,{"masking":54,"maskingDescription":52,"whoMasked":52},"NONE",[56,62],{"label":57,"type":58,"description":59,"interventionNames":60},"Usual care","ACTIVE_COMPARATOR","Usual care for determining presurgical blood orders, including use of the institutional Maximum Surgical Blood Ordering Schedule (MSBOS)",[61],"Other: Usual care",{"label":63,"type":64,"description":65,"interventionNames":66},"S-PATH","EXPERIMENTAL","Access to the S-PATH clinical decision support system",[67],"Other: S-PATH clinical decision support system",[69,73],{"type":6,"name":70,"description":71,"armGroupLabels":72,"otherNames":52},"S-PATH clinical decision support system","Access to the S-PATH electronic health record (EHR)-integrated clinical decision support system",[63],{"type":6,"name":57,"description":74,"armGroupLabels":75,"otherNames":52},"Including use of the conventional Maximum Surgical Blood Ordering Schedule (MSBOS)",[57],[77],{"name":78,"role":79,"phone":80,"phoneExt":52,"email":81},"Sunny S Lou, MD, PhD","CONTACT","314-362-5000","slou@wustl.edu",[83],{"facility":84,"status":85,"city":86,"state":87,"zip":88,"country":89,"countryCode":90,"cosmosGeoPoint":91,"geoPoint":96,"contacts":97},"Washington University \u002F Barnes Jewish Hospital","RECRUITING","St Louis","Missouri","63110","United States","US",{"type":92,"coordinates":93},"Point",[94,95],-90.19789,38.62727,{"lat":95,"lon":94},[98],{"name":78,"role":79,"phone":80,"phoneExt":52,"email":81},{"type":100,"investigatorFullName":101,"investigatorTitle":102,"investigatorAffiliation":5,"oldNameTitle":52,"oldOrganization":52},"PRINCIPAL_INVESTIGATOR","Sunny Lou","Assistant Professor",[104],{"name":105,"class":106},"National Heart, Lung, and Blood Institute (NHLBI)","NIH","100610151","ai-driven-clinical-decision-support-for-perioperative-blood-orders-100610151",false,"NCT07223853","AI-driven Clinical Decision Support for Perioperative Blood Orders","Intelligent Clinical Decision Support for Preoperative Blood Management: A Cluster-Randomized Clinical Trial","SPATH","Clinician Level Exclusion Criteria:\n\n* Clinician (resident physician or advanced practice provider) who works at a preoperative assessment clinic\n\nClinician Level Exclusion Criteria:\n\n* None\n\nPatient Inclusion Criteria:\n\n* Scheduled for surgery in one of the main operating room areas (non-remote) at Barnes Jewish Hospital\n* Evaluated in-person at one of the preoperative assessment clinics affiliated with BJC Healthcare\n* Have a valid S-PATH model prediction prior to their preoperative assessment clinic visit\n\nPatient Exclusion Criteria:\n\n* Pregnant\n* Presence or history of red cell alloantibodies","ALL","18 Years",{"count":118,"type":119},50,"ESTIMATED","INTERVENTIONAL",[122],"NA","20 million patients have surgery in the United States every year, with approximately 1 million of those patients requiring life-saving blood transfusion. Presurgical preparation for transfusion is important to allow for safe and timely transfusion during surgery; however, excessive preparation is unfortunately common, costly, and contributes to blood waste. This study aims to evaluate an intelligent clinical decision support system that helps clinicians prepare blood for patients who are likely to need it, while avoiding excessive preparation for patients who don't, potentially improving patient safety while reducing blood waste and healthcare costs.",[125],"Surgery",[127,128,129,130,131,132,133],"artificial intelligence","clinical decision support","machine learning","surgery","perioperative blood management","anesthesia","pretransfusion testing","2026-08-24",{"date":136,"type":137},"2026-08-27","ACTUAL",{"date":139,"type":137},"2025-10-28",{"date":141,"type":119},"2027-01-01",{"name":5,"class":6},1]