Bending the Outcome Curve in the Fight Against Sepsis · Generates actionable intelligence Performs...
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Bending the Outcome Curve in the Fight Against Sepsis Adam Klass, Chief Technology Officer, VigiLanz Corporation Bart Abban, Ph.D, Chief Data Scientist, VigiLanz Corporation with Real-Time & Predictive Clinical Intelligence
Transcript of Bending the Outcome Curve in the Fight Against Sepsis · Generates actionable intelligence Performs...
Bending the Outcome Curve in the Fight Against Sepsis
Adam Klass, Chief Technology Officer, VigiLanz Corporation
Bart Abban, Ph.D, Chief Data Scientist, VigiLanz Corporation
with Real-Time & Predictive Clinical Intelligence
About VigiLanz
Software as a Service
(SaaS)
Gartner
Cool Vendor 2015
Offices in Minneapolis
& Chicago
Real-Time
Surveillance
Nearly 400
hospitals
Founded
2001
Our PassionDelivering real-time information and insights that healthcare executives and clinicians need to improve patient care and operational performance.
Generates actionable intelligence
Performs asynchronous surveillance
Informs clinicians real-time
Manages all data across the continuum of care
Enables collaboration and interoperability
Continuously learns by the integration of clinical and business intelligence data
Integrates innovative predictive models and analysis
Enterprise Intelligence Resource (EIR)
Intelligence Impacts Key Issues
Care
Management
Regulatory
Management
Operations
Management
Financial
ManagementResearch
Population
Health
Public
Health
Intelligence
Platform
Intelligence Impacts Key Issues
Care
Management
Regulatory
Management
Operations
Management
Financial
ManagementResearch
Population
Health
Public
Health
Intelligence
Platform
Pharmacy
Antimicrobial Stewardship
Sepsis Surveillance
DVT Prevention
Glycemic Control
Fall Prevention
Zynx Guidance
Medication Reconciliation
Infection Control
Care Management
Intelligence Impacts Key Issues
Care
Management
Regulatory
Management
Operations
Management
Financial
ManagementResearch
Population
Health
Public
Health
Intelligence
Platform
Direct NHSN
Quality Reporting
Antimicrobial Utilization
Reporting
Safety/Risk Management
Regulatory Management
Intelligence Impacts Key Issues
Care
Management
Regulatory
Management
Operations
Management
Financial
ManagementResearch
Population
Health
Public
Health
Intelligence
Platform
Safety/Risk Management
Readmissions Prevention
Medication Cost
Management
Core Measure Surveillance
Quality Indicator
Surveillance
Operations Management
Intelligence Impacts Key Issues
Care
Management
Regulatory
Management
Operations
Management
Financial
ManagementResearch
Population
Health
Public
Health
Intelligence
Platform
Data Aggregation
Research Initiative Rule Set
Research
Intelligence Impacts Key Issues
Care
Management
Regulatory
Management
Operations
Management
Financial
ManagementResearch
Population
Health
Public
Health
Intelligence
Platform
Risk Stratification
Chronic Disease
Management
Episodic Care Optimization
Preventative Health
Population Health
Intelligence Impacts Key Issues
Care
Management
Regulatory
Management
Operations
Management
Financial
ManagementResearch
Population
Health
Public
Health
Intelligence
Platform
Infectious Disease DB
Syndromic Surveillance
Public Health
Managing the data deluge
• Large quantities of data are only as meaningful as the
insights they yield
• Efficient data analytics are linked to significantly reduced
costs, increased business intelligence and improved clinical
outcomes
Key Data Issues Facing Leaders
51%A Stoltenberg Consulting poll found healthcare IT
leaders believe the most significant barrier to
hospital data analytics is not knowing what data
to collect or how much of it.
CDW 2016
Becker’s CIO Review, 2016
Embracing the care continuum• As reimbursement is linked to value,
clinical outcomes data are more
entwined with the revenue cycle
• Anywhere intelligence to make
informed decisions
Becker’s CIO Review, 2016
Sepsis Prediction
Temporalytics® Methodology
• Powerful proprietary metadata drives
cause and effect approach
• Universal methodology can be used on any
clinical, financial or operational issue
• Customized to patient population
(not one size fits all)
• Machine learning platform enables
consistent tuning and optimization
Complete Integration into Workflow
Standard Clinical Predictive Models
BMPGood Medical
Practice
Patient DataRetrospective
Stratification & Predictive Alerts
Analytics
Patient DataRetrospective &
Real-Time
Machine Learning Platform
Time-Based
Meta Data
Customization
Smart Rules
BMPGood Medical
Practice
Prescriptive Insights, Analytics & Risk Scoring
Temporalytics Predictive Models
Temporalytics® Predictive Models: Sepsis
Admission Severe Sepsis Dx(Infx + Organ Dysf)
ICU admit ICU discharge
T0 = 0 Tsepsis= Max(Tinfx, Torgan dysfn)
Discharged/
Expired
Age, BMI, History,
Comorbidities
Vitals & Labs
Goal: Predict before
onset of Severe
Sepsis
General Models
SIRS Criteria vs. VI Prediction
SIR2 (-) SIRS2 (+) Total
Severe Sepsis (-) 1,954 730 2,684
Severe Sepsis (+) 20 139 159
Model (-) Model (+) Total
Severe Sepsis (-) 2,410 274 2,684
Severe Sepsis (+) 18 141 159
•
•
•
•
B
B
A
A
B
C
C
C
C
Patient
Hour 1
Hour 4
Hour 8
15%
PPV
34%
PPV
VigiLanz Temporalytics®SIRS Models
Cost Savings and Volume Focus
Total cases requiring follow-up
VigiLanz model 415
SIRS2 criteria 869
Caseload
reduction
over 50%
Sepsis Predictive Intelligence Integration
Clinical Intelligence Portal
VigiLanz Intelligence Platform
Pharmacy
Infection Control
AntimicrobialStewardship
Temporalytics®Predictive Analytics
AdvisoryServices
Core BI Portal
Sepsis Risk Scores are Displayed and/or sent through alerts for Clinicians
Discovery
Collaborate
Customize
Train/Test
Care Management
Sepsis Risk Score
Learning
Sepsis Model Results Transparency – See it in Real-Time
Sepsis Risk Display in Workflow Integration
Vital Sign Lag Time
Patient Safety
Response Time
Clinical Issue Hot Spots
Clinical Process Performance
Lag Time Analysis
Predictive Analytics Possibilities
Clinical quality and financial value, driving actionable intelligence
with both retrospective and real-time clinical meta data.
Medication Safety
Predictive Model Performance
Endless Possibilities
Sepsis
Readmissions
Deep Vein Thrombosis (DVT)
Adverse Drug Effects (ADE)
Stroke
Morbidity Risk
Surgery Site Infections (SSI)
PneumoniaGlycemic Control
MRSA
Pressure Ulcers
COPD Diabetes CHF
Chronic Disease Management
Health Risk Scoring
Cdiff
CLABSI
CAUTIEpidemic Outbreaks
Hospital Acquired Infections (HAI)
Preventative Care
