1. Crossing data to connect systems: using data improve services for vulnerable people
Kim Nettleton, Kelly Opot, Eva Thibaudeau, Susan Tucker

2. Kim Nettleton, United Healthcare Kelly Opot, CSH
Crossing data to connect systems
Nettleton, Opot, Thibaudeau, Tucker
Introductions:
Kim Nettleton, United Healthcare
Kelly Opot, CSH
Eva Thibaudeau, Coalition for the Homeless Houston/Harris County
Susan Tucker, Molina Healthcare
YOU!
Kelly will go through the room, based on how many people we will either call out by sector or ask individuals to give a brief intro. We will ask if they’re doing data match, want to do a data match, have tried and can’t get it right, etc.

3. Serving over 5.7 million members
United Intro

4. More than 4.2 million managed care members
Serve more than 8 million Medicaid and Medicare beneficiaries
Molina intro
More than 4.2 million managed care members

5. Setting the stage: Why Texas? And why Houston?
Crossing data to connect systems
Nettleton, Opot, Thibaudeau, Tucker
Setting the stage: Why Texas? And why Houston?
Kelly – intro about challenges in TX – non expansion, limited service dollars/state support appear outwardly as barriers. Houston is entrepreneurial, innovative and embarking on huge changes to the way it responds to homelessness. Ask each a question
Eva, can you give us an idea of what has happened in Houston since 2013 to help frame?
Eva to discuss coordinated access, system redesign, connecting to mainstream resources. Houston moved from a fragmented to a coordinated system where housing placement was streamlined and we increased our total units of SH by 1,200 in a year. Houston redesigned service delivery to include integrated health care for an incredibly vulnerable group of people (long term homeless, multiple barriers to housing, multiple chronic physical and mental health conditions) and were using data to track where people were, how they were doing, how connected they were and how quickly they were being housed.
Kim, will you discuss your interest in supportive housing and connection to the Houston market for United?
Kim will discuss interest in connecting with supportive housing providers to help identify vulnerable/hard to locate people and better coordinate care in a large market.
Susan, can you discuss Molina’s national interest in housing and why you are connecting with Houston specifically?
Susan will discuss priority communities for Molina, markets in Texas and building relationships with PSH providers and MCO role in TX.

6. Shared data and shared consumers: Making the case
Crossing data to connect systems
Nettleton, Opot, Thibaudeau, Tucker
Shared data and shared consumers:
Making the case
Not all data are created equal. What were we looking for and who were we trying to serve
System Frequent Utilizers
High cost members
Vulnerable
Long-time homeless
Recently housed
Discussion of what kind of data is collected in each system and our assumptions about overlap

7. Crossing data to connect systems
Nettleton, Opot, Thibaudeau, Tucker
But what about privacy?
With HIPPA, HMIS privacy requirements many organizations see too many barriers to overcome to make it worthwhile. What did you do?
HMIS User Agreements
MCO approach to sharing data
We will ask if they’re doing data match, want to do a data match, have tried and can’t get it right, etc.
Also may discuss using FTP, HMIS numbers

8. What did you do? – United Process
Crossing data to connect systems
Nettleton, Opot, Thibaudeau, Tucker
What did you do? – United Process
Focus on barriers and getting people housed

9. What did you do? – Molina Process
Crossing data to connect systems
Nettleton, Opot, Thibaudeau, Tucker
What did you do? – Molina Process
Early intervention with healthcare

10. What did you find out? Coalition/HMIS (as of 6/2016) United:
Crossing data to connect systems
Nettleton, Opot, Thibaudeau, Tucker
What did you find out?
Coalition/HMIS (as of 6/2016)
All client records in HMIS: 191,420
Homeless clients (not housed): 24,460
Clients in PSH : 2,146
United:
Total members (Harris): 137,599
Member overlap: 3,045
Target: 30
Total claims amount: $2.27MM
Molina
Total members (Texas): 367,000
Target: <10
Discuss broadly how many people were identified initially, but what that told us from the HMIS/homeless side and what it mean on the MCO side (not all HMIS users are homeless, not all frequent users now were frequent users before or will be frequent users in the future.

11. Typical United Member Profile
STAR+PLUS Product Line of Business
Medical Claims Cost = $47,000
RX Claims Cost = $12,000
Behavioral Health Claims Cost = $18,000
# of Hospital Admits = 4
Potentially Preventable Admissions = 6
Potentially Preventable Re-Admissions = 1
Potentially Preventable ER Visits = 10
Total Preventable Costs = $9,000
Condition/diagnosis, co-morbidities
(Critical Catastrophic Diagnosis 11, Diabetes 9, Mental Health 6)
Crossing data to connect systems
Nettleton, Opot, Thibaudeau, Tucker
Discuss broadly how many people were identified initially, but what that told us from the HMIS/homeless side and what it mean on the MCO side (not all HMIS users are homeless, not all frequent users now were frequent users before or will be frequent users in the future.

12. Typical Molina Member Profile
Crossing data to connect systems
Nettleton, Opot, Thibaudeau, Tucker
Typical Molina Member Profile
At least 20 contacts within last 6 months in HMIS
Star+PLUS, STAR, or MMP (all products considered)
Unable to contact – not in care management
High utilizer

13. But…what did you really find out?
Crossing data to connect systems
Nettleton, Opot, Thibaudeau, Tucker
But…what did you really find out?
Collaboration and building new partnerships is important. But it isn’t always easy. Simple ideas within complex systems serving complex people are complex.
We’re using different words to describe similar things
There are challenges of working with MCO…timelines, multiple layers of bureaucracy, legal and corporate limitations, need to focus on targeted members
Challenges to working with small nonprofits…limited staff time and resources, understanding legal requirements and BAAs, identifying staff and providers to implement for specific Medicaid members, maintaining neutrality but

14. Long term goals Crossing data to connect systems
Nettleton, Opot, Thibaudeau, Tucker
Long term goals
Connecting systems and care providers
Making healthcare connection intuitive for SH providers
Helping each do their job better – relying on the experts
Creating long term sustainability through shared funding
We are all interested in person centered care, and improving our connections improves outcomes for the people we are trying to serve

15. What would you do differently?
Crossing data to connect systems
Nettleton, Opot, Thibaudeau, Tucker
What would you do differently?
Lessons learned, how to approach going into this work

16. What has your experience been?
Crossing data to connect systems
Nettleton, Opot, Thibaudeau, Tucker
What has your experience been?
Open up for questions

17. Thank you! Kim Nettleton, kim_a_nettleton@uhc.com
Crossing data to connect systems
Nettleton, Opot, Thibaudeau, Tucker
Thank you!
Kim Nettleton,
Kelly Opot
Eva Thibaudeau
Susan Tucker
Open up for questions