Sepsis Clinical Decision Support [CDS] Master Enrollment Study Protocol

Study Overview
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Brief Summary
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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.

Detailed Description
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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.

Official Title
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Sepsis Onset Warning System [SOWS] Master Enrollment Study Protocol

Conditions
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Severe Sepsis, Severe Sepsis Without Septic Shock

Participation Criteria
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Eligibility Criteria
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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).

Ages Eligible for Study
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Minimum Age: 18 Years
Maximum Age: 89 Years

Sexes Eligible for Study
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All

Study Plan
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How is the study designed?
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Arms and Interventions

| Participant Group/Arm | Intervention/Treatment |
| --- | --- |
| Primary Objective: Severe Sepsis<br>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. | |

What is the study measuring?
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Primary Outcome Measures

| Outcome Measure | Measure Description | Time Frame |
| --- | --- | --- |
| Severe Sepsis | Identify patients having Severe Sepsis with the use of electronic health data | Within 6 hours from presentation to the emergency department | 

Secondary Outcome Measures

| Outcome Measure | Measure Description | Time Frame |
| --- | --- | --- |
| Mortality | Hospital mortality at hospital for Severe Sepsis patients identified by algorithm using electronic health data as potential benefits for increased early detection of risk of severe sepsis | Within 6hours from presentation to the emergency department | 
| Length of Stay | Determine length of stay at hospital for Severe Sepsis patients identified by algorithm using electronic health data as potential benefits for increased early detection of risk of severe sepsis | Within 6hours from presentation to the emergency department | 
| Re-admission Rates | Determine potential reduction of hospital readmission rates for Severe Sepsis patients identified by algorithm using electronic health data as potential benefits for increased early detection of risk of severe sepsis | Within 6hours from presentation to the emergency department |