See all on-demand Graph + AI Sessions: https://www.tigergraph.com/graph-ai-world-sessions/ Get TigerGraph: https://www.tigergraph.com/get-tigergraph/

1. Care Intervention Assistant
Omaha Clinical Data Information System
Team Sonar
Martin Dillon
Andrew Johnson
Niall Mc Guinness
Jamie O’Leary

2. • Andrew Johnson – Principal Data Scientist
Team
2
• Jamie O’Leary – Principal Engineer
• Martin Dillon – Senior Software Engineer
• Niall McGuinness – Senior Software Engineer
• Thomas Harlan – Associate Director Clinical Informatics

3. Clinical Care Program
An Overview

4. 4
#perks
#splurge
#convenienc
e
They Love They Hate
Being Independent Carelessness
Talking on the phone Technology
Simplicity Being alone
Routine Financial burden
“Family is everything. My health is my Wealth”
Member Persona - Glenda
71 years old
Race: Caucasian
Physical Activity: Low
Income: Under 30K
Former School teacher
Clinical Social
Congestive Heart Failure
Supports Children +
Grandchildren
Diabetes Works For Extra Income
7 Different Medications Husband Has Passed Away
Sees 6 Different Specialists
Granddaughter has learning
disability

5. 5
They Love They Hate
Quality Carelessness
Simplicity Compromising standards
Recognition Treated insignificantly
High touch service Unpredictability
41 years old
Married, no children
Husband also works long hours
Geriatric nurse
Part of a team
Huge caseload that
continuously increases
Planning a career break in a
few years to go travelling
“Wish I didn’t get so tired by the end of the day but do value my time helping
patients”
Nurse Persona - Paula The Priority Juggler
Strengths Challenges
Patient Interactions - Listens
Intently
Struggles with Chaotic Time
Schedules
Frequently Checks for
Updates
Difficulty with Deep Patient
Relationships
Is More Relaxed with Children
Skims Information and Relies
on Instincts
Career Focused

6. 6
Triggered a HF
algorithm for
non-adherence to
medication
Member Engagement Journey - Glenda
Placed in a
dialer
campaign
Connected
with a nurse to
discuss care
Based upon medical and
pharmacy claims data for
events that occurred 3
weeks prior
Reached on 3rd
attempt –
caller ID is very generic
No member information is
presented outside of
demographics and rule that
triggered

7. Current Statistic on Nurse Practitioners
7
86
%
52
%
Do not feel they have enough time to understand and
discuss lifestyle behaviors' that affect a patient’s health
Spend no more than 11-15 minutes with each patient

8. Why can't I hold all these limes...?
8
X X 11-15 MinXX
Unique Individuals
Communication
Multiple Conditions
Support
Time Constraints

9. Care Intervention Assistant

10. Overview
10
Nurses are time poor with ever growing
case-loads and find it difficult to spend
sufficient time with a member to
understand their holistic picture.
THE SOLUTION
To use data and machine learning
to establish patterns of care plans
that have successfully been used
to treat patients with similar traits
using holistic attributes
Care Intervention Assistant
THE PROBLEM

11. Solving the Clinical Data-Information
Puzzle
11
0
1
0
2
0
3
Solution
Business
Solution
Create a ranked list (by priority) of
problems, symptoms and their
recommended “Care Interventions”
for patients who have
multidimensional, (often
confounding) medical, mental, and
socio-economic considerations
Nurse Value Proposition
Quickly rank the importance of the problems
to be addressed for patients given a
overwhelming number of considerations,
priorities, and severities.
Business Value Proposition
Increase ability to manage more members.
Increase engagement rates through personalized
experience. Ability to tailor engagement programs
based upon specific member attributes. Increased
member satisfaction and NPS for care
management program
Nurse

12. Ontology As an Example
12
1 I NCOME
2 SANITATION
3 RESIDENCE
4 NEIGHBORHOOD / WORKPLACE SAFETY
5 COMMUNICATION WITH COMMUNITY RESOURCES
6 SOCIAL CONTACT
7 ROLE CHANGE
8 INTERPERSONAL RELATIONSHIP
9 SPIRITUALITY
10 GRIEF
11 MENTAL HEALTH
12 SEXUALITY
13 CARETAKING/PARENTING
14 NEGLECT
15 ABUSE
16 GROWTH AND DEVELOPMENT
17 HEARING
18 VISION
19 SPEECH AND LANGUAGE
20 ORAL HEALTH
21 COGNITION
22 PAIN
23 CONSCIOUSNESS
24 SKIN
25 NEURO-MUSCULO-SKELETAL FUNCTION
26 RESPIRATION
27 CIRCULATION
28 DIGESTION-HYDRATION
29 BOWEL FUNCTION
30 URINARY FUNCTION
31 REPRODUCTIVE FUNCTION
32 PREGNANCY
33 POSTPARTUM
34 COMMUNICABLE / INFECTIOUS CONDITION
35 NUTRITION
36 SLEEP AND REST PATTERNS
37 PHYSICAL ACTIVITY
38 PERSONAL CARE
39 SUBSTANCE USE
40 FAMILY PLANNING
41 HEALTH CARE SUPERVISION
42 MEDICATION REGIMEN
Omaha System Problems Set (42)
Omaha Clinical Data Information System.
Rating: 1 2 3 4 5
Knowledge Ignorant Minimal Basic Adequate Superior
Behavior Inappropriate Rarely
Appropriate
Inconsistent Usually
Appropriate
Consistent
Status Extremely
Symptoms
Severely
Symptoms
Moderately
Symptoms
Minimal
Symptoms
No
Symptoms
Omaha System KBS Problem Rating Scale (Knowledge, Behavior, Status)
Recommended Interventions:
1. Intervention Category: Treatments & Procedures
2. Intervention Action: Wound care
3. Intervention Rationale: Chosen due to highest severity rank and Omaha score combination.

13. Methodology

14. 14

15. Explainable AI Models Leverage Graphs
15
Training
Data
Training
Data
Machine
Learning
Process
New
Machine
Learning
Process
Learned
Function
Today
Explainable AI
• Why did you do that?
• Why not something else?
• When do you succeed?
• When do you fail?
• When can I trust you?
• How to I correct an error?
• I understand why
• I understand why not
• I know when you succeed
• I know when you fail
• I know when to trust you
• I know why you erred
Decision or
Recommendation
Explanation
Interface
Explainable Model
Task
Task

16. 16

17. Graph and Network Visualization
17
Each color is a different network with many
Interconnections between individuals.
The placement algorithm is called a “Force
Directed Graph” because the positioning
simulates physical spring forces.
Individual

18. Interactions + AI + Graph in Unison
18
Member
Interactions
Nurse
Interactions Cognitive
Agent
Graph
NLP + ML
Agent

19. EXISTING
HEALTHCARE
GRAPH
Patients
GEO-Location
Conditions
Optum Graph Database
OMAHA TAXONOMY
4 Domains
42 Problems
Intervention Scheme
TAXONOMY
EXTENSIONS
Covid-19
Other…
Other…. Problem Rating
Healthcare Graph with Omaha
Taxonomy
Individual Family Community
Algorithms (Cosine Similarity, Timeline Trend Analysis)

20. Machine Learning Approaches
20
Text Interaction Data
Member Data
Pretrained NLP
models using e.g.
BERT
Outputs Provide
Risk Scoring for
Various Health
Problem Spaces
Demographics, Clinical
Data, SDoH, etc

21. O
DEMO

22. 22
Summary
BENEFITS
Influence Members
Discover Trends
Save Time
Company Motto
Influence the Member to take proactive
steps to address patterns to improve their
health
Help the patient or provider discover hidden
trends or patterns that may lead to
adjustments in medication or treatment
Minimize the time spent gathering and
reviewing data during visits with the care
team
Help People Live Healthier Lives
To use data and machine learning to establish patterns of care plans that
have successfully been used to treat patients with similar traits and use
holistic attributes

23. Really Nice Feature with HUGE Possibilities:
Microsoft announced new meetings extensibility points that will enable developers to expand the Teams meeting experience.
With this new capability, developers will be able to build apps or integrate their existing ones within the meeting surface
and provide a richer collaboration experiences for users across the entire meeting lifecycle – covering events and actions from
before, during, and after a meeting. These new extensibility points will be available soon for developer preview over coming
weeks.
Extensions and Future Possibilities
23
Embed Real-Time
Optum Cognitive
App Interface

24. • Dan McCreary – Optum Distinguished Engineer
Additional Acknowledgements
24
• Samuel Brisson – Optum Director of Business Systems Analytics

25. Thank you!
25