1. Clinical Decision Support Systems in the Perioperative Setting
Bala G. Nair, PhD
Associate Professor & Director, PPiQSO
Anesthesiology and Pain Medicine
University of Washington, Seattle, WA

2. Coulter Foundation Grant
Dexcom, Inc

3. Clinical Decision Support (CDS)
Computer System
Assimilates & processes EMR information
Assists clinician in decision making towards:
Safer and optimal clinical care
Accurate documentation  improved billing & compliance
Better efficiency – cost & waste reduction
(EMR – Electronic Medical Record)

4. Perioperative setting
> 5000 hospitals
30 million surgeries
40-50% hospital revenue
Expensive care (~$50/min)
High risk
Major complication rate
= 3-17% (Half preventable)
Litigations
Major lawsuits: 150/y
Payment: ~$350,000
20-33 % of all hospital wastes
Waste
Complex, critical & dynamic environment
Multi-sourced information flow
Rapid shifts in patient conditions and information

5. Types of CDS Active Passive User initiated Automatic Non real-time
“Hard stops”
Guideline documents
Real-time
Post-hoc reports
Preoperative summary
Real-time alerts
Real-time guidance

6. CDS Architecture PIMS / EMR Database Voice Report Phone Pager
Rules Builder
Decision Rules
Data Acquisition
Module
Data processing
Module
Rules Processing
Module
PIMS / EMR
Database
Notification
Module
Message &
Response Logs
PIMS Workstation
Visual
display of alerts
Voice
Report
Phone
Pager
PIMS - Perioperative Information Management System
EMR – Electronic Medical Record

7. Integrated and add on Advantages Disadvantages Integrated Stand-alone
Advantages
Disadvantages
Integrated
Self-contained
Immediate access to data
Seamless
Lack of specialization and focus
Simplistic, inflexible solutions
Slower pace of enhancements
Stand-alone
Generally superior features
More customized to meet perioperative needs
Generally faster pace of enhancements
Indirect access to PIMS data & data latency
Updates to the EMR could cause data interface failures
Requires more maintenance

8. Integrated CDS – Advanced Clinical Guidance – Talis Clinical LLC
Examples
Integrated CDS – Advanced Clinical Guidance – Talis Clinical LLC

9. Add On CDS – Smart Anesthesia Manager with Cerner EMR
Examples
Add On CDS – Smart Anesthesia Manager with Cerner EMR

10. Examples
Add On CDS – AlertWatch

11. Benefits Target item CDS description Passive Active: Post-hoc
Target item
CDS description
Passive
Billing/compliance
Required fields or hard stops
Clinical protocols
Links to clinical protocols
Active:
Post-hoc
Quality measure
report on failed antibiotic administration
Individualized s on noncompliant documentation
Cost savings
Individualized feedback on gas flows

12. Benefits Active: Near real-time Target item CDS description
Target item
CDS description
Active:
Near
real-time
Quality measures
Timely antibiotic initial dose and redoses
Perioperative β-blocker administration
Billing/
Compliance
Documentation of invasive lines
Data elements required for billing
Cost savings
Feedback on reducing fresh gas flow
Patient Monitoring / Anesthesia management
Gaps in non-invasive blood pressure monitoring
Hypotension or hypertension
Activate patient monitor alarms after CPB
Tidal volume for patients at risk of acute lung injury
Clinical protocols
Glycemic management guidelines
PONV risk and antiemetic drug therapy
Traumatic Brain Injury
CPB - Cardio Pulmonary Bypass
PONV – Post-Operative Nausea & Vomiting

13. Hurdles Access to data Data latency Interoperability
Custom queries, FHIR, HL7
Data latency
Delayed alerts, False alerts
Interoperability
Domain restrictions
Operational impact
Production operation, User interaction

14. Considerations Provider buy in, education Workflow compatibility
Educate and obtain provider buy in
Solicit feedback, refine rules
Workflow compatibility
Impact on workflow
Ability to perform CDS recommendations
Timing & Content
When & how to alert?
Feedback message content
Alert fatigue
Repeat alerts?
How frequently?

15. Future directions Intraoperative Perioperative Prescriptive Automatic
(Precision medicine)
Automatic
(Closed-loop systems)
Future
Predictive
(Machine learning, predictive analytics)
Optimal
(Optimization techniques)
Next
Reactive
Suboptimal
Manual
Current

16. Questions ?