Sepsis Clinical Decision Support [CDS] Master Enrollment Study Protocol
Purpose
This protocol will collect real-world data retrospectively from the electronic health record (EHR) as data obtained from the delivery of routine medical care to develop a machine learning (ML)-based Clinical Decision Support (CDS) system for severe sepsis prediction and detection.
Conditions
- Severe Sepsis
- Severe Sepsis Without Septic Shock
Eligibility
- Eligible Ages
- Between 18 Years and 89 Years
- Eligible Genders
- All
- Accepts Healthy Volunteers
- No
Inclusion Criteria
- All races, ages and ethnicities - All patients admitted to the hospital or presenting to the Emergency Department
Exclusion Criteria
- Patients not presenting to a hospital setting (e.g. urgent care, outpatient clinic excluded).
Study Design
- Phase
- Study Type
- Observational
- Observational Model
- Cohort
- Time Perspective
- Retrospective
Arm Groups
| Arm | Description | Assigned Intervention |
|---|---|---|
| Primary Objective: Severe Sepsis | The primary endpoint for this study is defined as the presence of sufficient data for SOWS training and algorithm development to proceed with subsequent validation. To provide sufficient data subsets (severe sepsis EHR encounters) for training and validation of the Sepsis Onset Warning System algorithm. There will not be any interventions administered. |
Recruiting Locations
Cleveland, Ohio 44109
More Details
- Status
- Recruiting
- Sponsor
- Beckman Coulter, Inc.
Detailed Description
The purpose of this study is to gather data for the clinical development of the Sepsis Onset Warning System (SOWS) Software as Medical Device (SaMD) product to support a De Novo FDA submission and commercialization in the United States. Product development of SOWS is funded in part with federal funds from the Department of Health and Human Services; Office of the Assistant Secretary for Preparedness and Response; Biomedical Advanced Research and Development Authority. Data will be obtained from passive prospective collection of patient encounter data throughout the duration of the planned study to support the product development life cycle activities associated with developing the Sepsis Onset Warning System (SOWS) for severe sepsis risk detection. Inputs from patient health records in combination with proprietary hematology parameters developed by Beckman Coulter, such as Monocyte Distribution Width (MDW), will be used. The SOWS tool will look to use clinical measurements which are commonly and reliably available in the EHR as structured data elements, such as heart rate, temperature, blood pressure, and laboratory results and account for changes in these values over time.