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

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.

Serving over 5.7 million members United Intro

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

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.

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

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

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

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

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.

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.

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

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

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

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

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

Thank you! Kim Nettleton, kim_a_nettleton@uhc.com Crossing data to connect systems Nettleton, Opot, Thibaudeau, Tucker Thank you! Kim Nettleton, kim_a_nettleton@uhc.com Kelly Opot kelly.opot@csh.org Eva Thibaudeau ethibaudeau@homelesshouston.org Susan Tucker Susan.Tucker@MolinaHealthCare.Com Open up for questions