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PMHA Logic Model for Data Needs to Advance Medicaid Coverage for Psychedelic-Assisted Therapy Care Models

Context

Inputs

Activities (Proposed)

Outcomes

Activities Needed for Success

Short-term

Long-term

Success of Psychedelic-assisted therapies (PAT) requires high-quality implementation studies to create needed proof-of-concept for coverage of full PAT care model

PHEI is best positioned to support the field. Leveraging community-engagement, health equity and data, PHEI can create pathways to access and PAT care model coverage for marginalized populations with mental health needs

Priority issue areas:

Identifying data and analyses most critical for decision-makers and influencers
Creating evidence with pilot studies that look at PAT care model outcomes for marginalized pops

Uniform Data Variables for PAT pilots

Identify draft variables
Collect expert input through structured collection
Identify additional variables for payers/Medicaid through policy/Medicaid experts
Engage pilot sites such as NM
Collect lessons/revise
Identify additional data collection needs

UC Berkeley CEP (Elliot)
Academic Experts/Researchers (Kyle,)
Policy/Medicaid experts (CHCS, Heidi, etc.)
Mental Health (BF)
Clinical (Beckley, Larry)
Health Equity stakeholders

Consensus among key experts and stakeholders on PAT data needs (included key decision makers and necessary analysis)
Data variables aligned by expert input to position pilot PAT care models for POC
Initial data infrastructure and strategy for informing real-world outcomes and equity related to PAT established (decide on provider to create)
Data collection across pilot sites and marginalized populations initiated
Agreements/partnerships with other’s collecting data to collaborate on needed analysis
Process/experiments for care model development in collaboration with health equity providers

PAT pilots participate in uniform data variable collection
PAT care model refined based on early pilot insights and expert analyses
Key analyses provide positive proof points for PAT
Successful PAT POC attracts interest from traditional health equity funders
Additional, larger studies on PAT in target populations and settings are initiated
Analysis of Ketamine usage and impact with sub-populations that are the focus of PHEI
Medicaid and other insurance decision-makers are engaged in discussions about PAT in key states.

Successful PAT proof-of concept yields Medicaid and other payor pilots in key states
Reimbursement pathways are identified and tested in key states
Increase in number of people with access to PAT
Increase in number of people from marginalized population in treatment with PAT

Partners/ Experts/Stakeholders

Intermediate

Staff dedicated to health equity and field building
Convene leading experts in health, equity, research and insurance
Funding coordination
Monitoring PAT interest at state and national level
Development of data strategy and infrastructure for PAT analytics
Identifying alignment and strategic partnerships
Advocacy for PAT related research with marginalized populations

Align on analyses required for provider and payer (Medicaid, Medicare and Commercial)

Engage policy experts such as CHCS to map out key analyses/POC needed
Identify value-proposition analysis on key outcome, cost, quality and health equity metrics for different stakeholder groups
Collaborate with potential pilot sites and states to identify studies needed for POC
Collect pilot data
Hire research/expert team to finalize analyses for key provider and payers stakeholders (e.g. Berkeley CEP cost model

Develop Practice-Based Research Network Infrastructure

Explore functional and data strategy needs to determine optimal vendor and structure
Hire vendors to support build out and maintenance of PCRN for PAT
Identify research team to test, coordinate and run analyses for PCRN
Create communication plan for dissemination and sharing of key findings

PHEI & Partners

Academic/Researchers (UC Berkeley CEP (Elliot), Kyle Greenway, Dr. Leeman UNM)
Policy/Medicaid experts (CHCS, Heidi, BF, etc.)
Clinical Providers (Beckley, Sunstone, 1440, Oregon ?)
Actuarial/Medicaid reimbursement experts
Health Equity Stakeholders (Camden, Bernalillo Health Equity Council)

Building the database

Private sector (Quire Data)?

OCHIN?

Housing the database
UC Berkeley CEP (Elliot)?
OCHIN?
Joint analyses
Beckley
Academic centers for psychedelic research
Other clinical stakeholders

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Key Decision-Makers: Health Equity/Medicaid

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Medicaid is a complicated system that is different in each state. Federal and State directors make determinations as to what a system is allowed to pay for. State directors and health plan administrators decide what they choose to fund based on medical necessity which determines what is potentially available for coverage and how it will be reimbursed. Medicaid managed care plan administrators and health systems will implement how coverage is accessed and what costs. And finally, community-based organizations and clients determine what is of interest. Consequently, there are many decision makers involved in determining a community's access to Medicaid coverage and payments for effective PAT care.

The table below highlights the key decision makers that PHEI needs to influence. Immediate focus for pilots and proof-of-concept with be state Medicaid directors and Medicaid managed care plan leaders. States will be interested in the data generated and individual patient and provider stories that help bring the data to life to show the value proposition for a state Medicaid agency to allocate dollars toward PAT.

What is	FDA	CMS/ Federal	State Medicaid Directors	Medicaid Plan Admin.	Health Systems & CHCs	Community Based Org	Client Interest
Legal	X
Allowable		X	X
Available			X	X	X
Affordable				X	X
Accessible				X	X	X	X
Wanted						X	X

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Priority Analyses: State Medicaid Stakeholders

State Medicaid Medical Directors

State Legislative Leaders

Medicaid Managed Care Plan Admin.

Positive Outcomes for Subpopulations

Subgroups based on race, income, social need and chronic conditions

Effectiveness in subpopulations in real world settings

Medical Necessity

Failure on other treatments (history)

Symptom severity

Inclusion/Exclusion criteria for treatment

Cost Avoidance

Reduced utilizations (ED, inpatient psych, medications)

Care model associated costs

Adverse Events/ Safety

Safety results similar for subpopulations

Tradeoffs versus current treatments

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Analysis To Inform Medicaid Decision Makers (medium term)

Decision-Maker	Results Demonstrated	Data/Analysis needed
CMS/MACPAC	Similar & positive outcomes with Medicaid population in real world settings	Subgroup outcomes for Medicaid, Medicare and the general population with medication, care model, settings and safety clearly defined
State Medicaid Medical & Program Directors	Similar & positive outcomes for sub population for conditions of interest Improvements on equitable access Ability to deliver care safety in real world settings Cost avoidance or reduced utilizations	Subgroup outcomes for Medicaid, Medicare and the general population with medication, care model, settings and safety clearly defined Sub-population for whom this would be medically necessary (e.g., failure with other treatments Symptom severity (e.g., depression scale. suicidal ideation) Inclusion & exclusion criteria (e.g., family history of psychosis). Care model and associated costs Cost avoidance e.g., reduction in ED visits, inpatient psychiatric, medication etc. Tradeoffs from current standard of care for specific condition studied
Medicaid Managed Care Plan Administrators	Positive clinical outcomes for subgroups Cost effectiveness compared to other treatments (actuarial based) Improvements in well being and other chronic conditions Safety results	Care model components (preparation, dosing and integration) Adverse events Cost of care model Mental health-related longitudinal utilization/cost data (medical and Rx claims) Total cost of care longitudinal utilization data (medical and Rx claims)
Health Systems/ CHCs	Clinical care model outcomes Cost of care Quality of care Reduced provider burden	Care model components (preparation, dosing and integration) PROMS Facilitator qualifications Quality metrics for wellbeing and key conditions
Community based organizations	Effectiveness and outcomes for subgroups Clarity on what social supports are necessary to support clinical care model	Care model components (preparation, dosing and integration) Social supports utilized during treatment PROMS Patient and provider testimonials
Client Interest	Effective and relevant care Culturally tailored care	Patient and provider testimonials Safety profile and adverse events PROMs

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PMHA Alliance Roadmap