MRT Innovations in Social Determinants of Health Initiative

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Q1 Please provide your contact information below.

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Q2 Please describe your company or organizations overall goals and mission.

CMA is a NYS – Certified, Woman Owned Business. Since 1984, we have provided information technology products and services to clients across the commercial, industrial and public sectors, and have emerged as an industry leading provider within the health and human services marketplace. We are proud of our affiliation with OHIP. As prime contractor for the New York State – Medicaid Data Warehouse (MDW), CMA developed and implemented a replacement Medicaid Data Warehouse (MDW) solution and currently maintains responsibility for the operational support of the Office of Health Insurance Programs’ (OHIP) Data Mart.

The MDW plays a central role in New York State’s Medicaid program. NYSDOH views the MDW as a strategic, system of record for state, local and federal agencies, as well as the continuum of stakeholders involved in the administration of New York’s Medicaid program.

In 2012, CMA implemented an enterprise solution (The NYS Clinical Research Database) to provide fast and flexible access to over 25 years of claims data and transform this data into actionable insights that are enabling the State’s Medicaid Redesign Team’s – DSRIP and Value Based Payment initiatives. The current and potential value of such insights are integral to Medicaid stakeholders, including community–based organizations that are essential to efforts to effect timely interventions that address the social determinants of health (SDH).

The MDW facilitates transparency of claims and encounter data, while meeting all Health Insurance Portability and Accountability (HIPAA) requirements, including 5010, and Health Information Technology for Economic and Clinical Health Act (HITECH) requirements.

CMA has collaborated with Dr. Eric Hirsh, PhD in preparing this response. Eric has published widely on housing instability, homelessness, and has done extensive evaluation research on homeless programs funded by SAMHSA, HUD, and the U.S. Census Bureau. He has an M.A. and Ph.D. in Sociology from the University of Chicago. Eric is Professor of Sociology at Providence College, and previously served as an Assistant Professor of Sociology at Columbia University.

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Q4 Innovation Executive Summary. Please describe the innovation, and how it addresses the social determinants of health. Please identify how the innovation addresses the 6 innovation criteria (i.e. ROI, scalability, feasibility, evidence–based support for innovation, relevance to the Medicaid population and speed to market).

Introduction

A growing body of evidence reflects the positive impact that targeted, housing interventions can have on Medicaid related outcomes. This includes improvements in service utilization, with a corresponding impact on client outcomes and costs.

Recognizing the important role that housing stability can play in determining the outcomes of high–cost Medicaid Members, the state´s Medicaid Redesign Team´s – Affordable Housing Work Group established a set of recommendations to ensure reasonable availability and adequacy of supportive housing programs statewide. Among the Work Group´s recommendations was the need to target high– need, high–cost Medicaid recipients, to assure that their needs are not overlooked.

The process of targeting high–need, high–cost individuals for housing placement is not new. In fact, HUD requires that providers have in place the mechanisms to prioritize individuals for placement based upon vulnerability assessments that take into account three key factors: housing status, health condition (serious mental illness, substance use, and chronic health needs), and system–level cost. Short of incorporating longitudinal utilization and cost data into the assessment process, the fidelity of most vulnerability assessments can be impacted by:

• Client´s inability to recall and report complete and accurate information, including cost and utilization data;
• Client´s deliberate under/over–statement of information, in an attempt to influence a desired outcome; and
• Inability to stratify vulnerability at a level of granularity that serves as a "tie–breaker" among clients with similar risk scores.

To address these limitations, the City of New York (HRA) has developed a Standardized Vulnerability Assessment (SVA) that considers self–reported information as well as the client´s Medicaid utilization and expenditure levels, which are derived from the state´s Medicaid Data Warehouse. Similar capabilities can be developed to support providers outside of New York City, as they look to optimize the potential value associated with supportive housing services.

Appreciating the fact that providers have already adopted assessment tools of their own, CMA recommends that the Department of Health´s – Bureau for the Social Determinants of Health establish a supplemental, "Housing Vulnerability Assessment Tool" that incorporates longitudinal utilization and cost data from the MDW. This supplemental level of analysis will enhance the fidelity of the assessment and prioritization processes and support the optimization of Value Based outcomes.

Our proposed innovation is well aligned with the Department´s evaluative criteria:

1. Potential Return on Investment: A growing body of evidence reflects the positive impact that targeted, community and housing interventions can have on Medicaid related outcomes. This includes improvements in service utilization, with a corresponding impact on client outcomes and costs. Identifying Medicaid recipients with specific service utilization patterns can improve Medicaid cost efficiency and yield a positive Return on Investment. (1, 2)
2. Scalability: New York State´s Medicaid Analytics and Performance Portal (MAPP) and MDW were developed to support designated end– users, statewide. Residing within the MAPP environment, the proposed Vulnerability Assessment Tool will be able to analyze the depth and breadth of the MDW´s historical claims and encounter data for any Medicaid beneficiary in question.
3. Feasibility: The Vulnerability Assessment Tool will be straight forward in design, and developed to seamlessly integrate with the pre– existing, MDW and MAPP architectures, thereby fostering a highly feasible innovation.
4. Evidence–based support for innovation: Our proposed innovation aligns with considerable research, which conclusively supports the potential that prioritized housing placements can have on population–based outcomes and costs.
5. Relevance to the Medicaid Population: There is a high correlation between individuals who are homeless or experiencing housing instability, and Medicaid Super–Utilizers. The proposed innovation will establish a supplemental means for assessing individuals, based upon an analysis of complete and accurate utilization and cost data that is not readily gathered by self–report assessments or individual Performing Provider Systems, MCOs, CBOs, or providers. The supplemental ability to analyze longitudinal data, will increase the fidelity of assessments, ensuring that placement in the state´s limited, supportive housing capacity is prioritized in a manner that yields the greatest possible impact.
6. Speed to Market: We estimate that the proposed, Vulnerability Assessment Tool can be developed and introduced for pilot testing within a 3–month period of time. Subsequent, state–wide rollout of this innovation could be realized within 10–monthstime.

Overview of our Proposed Innovation

The Supportive Housing Provider (SHP) will gain access to the Vulnerability Assessment Tool, via the state´s MAPP. The Tool´s user interface will prompt the SHP to enter the Medicaid enrollee´s – Client Identification Number (CIN), and subsequently indicate whether the recipient is flagged as a high priority candidate for housing placement.

The user interface will return an affirmative to the end user if the recipient meets any of the three (3), proposed criteria described below, and has been assigned an active MRT SH vulnerability/prioritization flag. Importantly, the only information that the SHP will need to input in this supplemental assessment tool is the recipient´s CIN, and no specific PHI/PII data will be revealed to the SHP.

MDW MRT SH Health & Behavioral Health Identifier Flag

An MRT SH vulnerability/prioritization flag will check the recipient´s claims history for the most recent 12–month base period (assuming a six–month claim lag) to determine whether the following criteria is met and then auto–assign on a monthly basis, a flag that will remain active for 12–months post–assignment (based upon recipient CIN):

1. Claims submitted at any time during the twelve–month base period with any of the following HARP rate codes (except 7778 or 7779):
   7778 HARP HCBS Brief Assessment
   7779 HARP HCBS Full Assessment 7780 Plan of Care Development – Initial
   7781 Plan of Care Development – Ongoing 7782 HARP Care Management – Outreach 7783 HARP Care Management – Active
   7784 HARP HCBS Psychosocial Rehab – Individual, On–Site 7785 HARP HCBS Psychosocial Rehab – Individual, Off–Site 7786 HARP HCBS Psychosocial Rehab – Group 2–3
   7787 HARP HCBS Psychosocial Rehab – Group 4–5 7788 HARP HCBS Psychosocial Rehab – Group 6–10
   7789 HARP HCBS Psychosocial Rehab – Individual, Per Diem 7790 HARP HCBS CPST (Physician)
   7791 HARP HCBS CPST (NP, Psychologist)
   7792 HARP HCBS CPST (RN, LMHC, LMFT, LCSW, LCSW)
   7793 HARP HCBS CPST (All Other Allowable Professionals) 7794 HARP HCBS Peer Supports – By Credentialing Staff 7795 HARP HCBS Residential Support Services
   7796 HARP Short–Term Crisis Respite (Dedicated Facility) 7797 HARP Short–Term Crisis Respite (Non–Dedicated Facility) 7798 HARP Intensive Crisis Respite
   7799 HARP HCBS Family Support / Training (Individual) 7800 HARP HCBS Family Support / Training (Group of 2 or 3) 7801 HARP HCBS Pre–Vocational
   7802 HARP HCBS Transitional Employment
   7803 HARP HCBS Intensive Supported Employment 7804 HARP HCBS On–Going Supported Employment 7805 HARP HCBS Education Support Services
   7806 HARP HCBS Provider Travel Supplement (Per Mile) 7807 HARP HCBS Provider Travel Supplement (Subway)
   – OR –
2. High frequency Emergency Department (ED) or Inpatient Stay service utilization during the 12–month base period:
   1. Five separate ED claims with different Dates of Service (DOS) as indicated by the following rate and/or procedure codes: 1402 (rate code), 1409 (rate code) and/or 99281–99285 (procedure codes); or
   2. Two separate inpatient claims with different admit data as indicated by the following FFS Category of Service: 0285, or Encounter Category of Service "11"; or
   3. A combination of one inpatient claim and four ED claims.
   – OR –
3. High Medicaid Spending that exceeds 80% of utilizers relative to the county of fiscal responsibility during the 12–month base period:
   1. For example:
      1. More than $74,298* in annual Medicaid spending (Medicaid total spending including pharmacy and managed care (plan reported) if the recipient´s County of fiscal responsibility is one of the following: 28, 47, 58, 59, 60, 61, 62 or 66.
         
         OR
      2. More than $45,237* in annual Medicaid spending (Medicaid total spending including pharmacy and managed care (plan reported) if the recipient´s County of fiscal responsibility is one of the following: 28, 47, 59, 60, 61, 62, 66, 97, 98 or 99.
   *Note, the 80% threshold spending amount will be updated annually based on county of fiscal responsibility

Additional Considerations:

The base solution would be extensible, enabling the potential for supplemental data and indicators to be to be added over time, to increase the fidelity of insights generated by the recommended, "Housing Vulnerability Assessment Tool".

As an example, subsequent enhancements to the base solution might:

• Enable end–users to tailor prioritization thresholds based on CBO´s target populations, including: Seriously and Persistently Mentally Ill (SPMI), Alcohol and Other Drugs (AOD), or residents transitioning from nursing homes or other institutions. This includes an ability to integrate supplemental sources of pertinent data, including HIMS, Division of Criminal Justice Services database, PSYCKES (if required and authorized);
• Include an ability to provide end users with more detailed claims data, comparable to what is provided for Health Homes and/or a tiered response that will indicate the level of need for MRT SH based on the candidate´s degree of health and behavioral health vulnerability; and
• Include an expanded suite of tools to streamline and expedite the administrative process required to place an individual in supportive housing which would shorten wait times, improve access, strengthen care coordination, and mitigate candidate attrition. Lastly, and to further enhance savings, the State could pursue a Federal Waiver to secure FFP for Medicaid billable housing support services. In conjunction with our proposed innovation, such a strategy would provide both the means and incentives by which MCOs and CBOs participating in the state´s Medicaid Value Based Payment initiative can optimize interventions that address housing instability as a social determinant. Many state Medicaid programs (i.e.: AL, CA, CT, FL, LA, MN, and WI) have obtained Waivers, allowing their Medicaid programs to receive reimbursement (and Federal share) for housing support services.

Footnotes:

1. https://www.health.ny.gov/health_care/medicaid/redesign/2017/docs/2017–05_utilization_rpt.pdf
2. https://www.shvs.org/wp–content/uploads/2015/10/Improving–Care–for–Medicaid–Beneficiaries–Experiencing–Homelessness.pdf
3. Wright, B.J., Vartanian, K.B, Li, H.F, Royal, Jl, Matson, J.K. (2016). Formerly homeless people had lower overall health care expenditures after moving into supportive housing. Health Affairs, 35(1), 20–27,

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