INSIGHT by DASCENA

AI-powered sepsis prediction can help you save lives. InSight is a clinical decision support software tool that leverages readily-available data in the EHR to help clinicians identify sepsis earlier. Built with advanced machine learning capabilities, InSight can identify patterns to predict the risk of sepsis onset more accurately than rules-based tools. Our technology and alerts seamlessly integrate into existing clinical workflows, improving outcomes with little additional effort from the care team.

InSight®– Early Sepsis Prediction

“We are seeing a positive impact

for our patients through improved rates of survival.”

Hoyt J. Burdick, MD Chief Medical Officer

Cabell Huntington Hospital

HARD-TO-CATCH CASES

Of all septic shock patients,

40%leading to:1

• 2x greater mortality• 2x less likely to receive

a compliant bundle

TIME-CRITICAL CONDITION

Each hour delay in treatment yields

8%leading to:2

• poor quality metrics• high emotional burden

on clinical staff

Existing tools like SIRS and SOFA can’t address these issues.

Problem: Rules-based tools are not enough

present with vague symptoms,

increase in patient mortality,

Solution: ML algorithms can help you improve outcomes

Data is autonomously fed into Dascena's HIPAA compliant cloud

Data IngestionAlgorithm-enabled care leads to improved patient outcomes, including reduced rate of mortality and length of stay

Improved careCare team performs independent assessment and delivers intervention

InterventionAlgorithm analyzes each patient over time for signs of sepsis

Data AnalysisInSight alerts care team with potential sepsis cases

Notification

Seamless Workflow Integration

Our tool continuously analyzes patient vitals over time to quickly identify those at risk of sepsis

INSIGHT by DASCENA

Dascena, Inc. | 12333 Sowden Road, Suite B, PMB 65148, Houston, Texas 77080 | dascena.com

Partial customer list:

1. Filbin MR, Lynch J, Gillingham TD, Thorsen JE, Pasakarnis CL, Nepal S, Matsushima M, Rhee C, Heldt T, Reisner AT. Presenting Symptoms Independently Predict Mortality in Septic Shock: Importance of a Previously Unmeasured Confounder. Crit Care Med. 2018 Oct;46(10):1592-1599. doi: 10.1097/CCM.0000000000003260. PMID: 29965833.

2. Kumar A et al. Duration of hypotension prior to initiation of effective antimicrobial therapy is the critical determinant of survival in human septic shock. Critical Care Medicine. 2006;(34):1589-1596.3. Shimabukuro DW et al. Effect of a machine learning-based severe sepsis prediction algorithm on patient survival and hospital length of stay: a randomised clinical trial. BMJ Open Respir Res. 2017 Nov 9;4(1):e000234.4. Rodriguez RM, Greenwood JC, Nuckton TJ, et al. Emerg Med J 2018;35:350–356.5. Rhee C, Dantes R, Epstein L, et al. Incidence and Trends of Sepsis in US Hospitals Using Clinical vs Claims Data, 2009-2014. JAMA. 2017;318(13):1241–1249. doi:10.1001/jama.2017.138366. Burdick H, Pino E, Gabel-Comeau D, et al. Effect of a sepsis prediction algorithm on patient mortality, length of stay and readmission: a prospective multicentre clinical outcomes evaluation of real-world patient data from US

hospitals. BMJ Health Care Inform 2020;27:e100109. doi:10.1136/bmjhci-2019-100109

The statements contained in this document are supported by clinical trials and corresponding datasets. InSight undergoes periodic updates and performance improvements, and results may vary based on these algorithm improvements, as well as an institution’s unique data collection practices and standards for sepsis care. InSight is a clinical decision support tool intended to help identify patients that may be in need of further investigation. InSight is not intended to prevent, diagnose, or treat any medical condition. InSight should not be used as a substitute for the independent clinical judgment of a healthcare professional.

More Cases Caught, Fewer False Alarms

InSight has demonstrated higher sensitivity and specificity than traditional rules-based tools. In fact, an InSight alert is 2-4x more likely to be a real sepsis case, as measured by positive predictive value.*

*Figures calculated using an in-hospital incidence of 5.9%.5

Clinical Validation

InSight is one of the only prospectively validated ML-based clinical decision support tools, backed by a randomized clinical trial and a post-marketing study.

Additional validation can be found at www.dascena.com/publications

ICU patients at UCSF

Randomized clinical trial3(2016-17)

-58%p < .018

9.0%

21.3%

-25%p < .042

6.31

8.40

w/ InSight(n = 67)

w/o InSight(n = 75)

All-cause Mortality Days in ICU

Post-marketing study6

(2017-18)-39%

p < .001

2.3%

3.9%

-32%p < .001

3.27

4.83

-23%p < .001

28.1%

36.4%

Post-InSight(n = 14,166)

Pre-InSight(n = 3,592)

All-cause Mortality Days in Hospital 30-d Readmission Rate

Inpatient & ED wards across 9 institutions

InSight® Features

Target Population General adult inpatient and ED population

Algorithm Input Continuous vital sign data from point of admission, requiring at least one measurement of each feature

Core Features • Temperature • Systolic blood pressure • Heart rate • Diastolic blood pressure • Respiratory rate • Oxygen saturation (SpO2)

Algorithm Output Patient risk of sepsis – single alert per patient is generated when patient risk exceeds a prevalidated threshold

(measured over time)

Algorithm performance

demonstrated in the clinical

setting3