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Principal Investigator: Marcela V Horvitz-Lennon
Organization: RAND CORPORATION
Fiscal Year: 2024
Award: $796,338
Funding agency: National Institute of Mental Health
PROJECT SUMMARY
Medicaid is a key player in the care of individuals living with serious mental illness (SMI). Despite its high
costs, Medicaid-funded SMI care is characterized by low quality and inequities. Although state Medicaid
programs have implemented policies to improve quality or value of care for high-need beneficiaries including
those with SMI, policymakers lack the necessary information to develop, target, implement, and evaluate these
policies. For example, the associations between person- and area-level characteristics and quality of SMI care
are not well understood, precluding the targeting of corrective interventions. Moreover, concerns have been
raised about SMI quality measurement, with some arguing that available process-based indicators do not
cover key areas of SMI care and may not be associated with key patient outcomes, both health outcomes
(e.g., suicidality) and social outcomes (e.g., homelessness). Crucially, the quality and cost effects of the broad
adoption of telehealth to deliver mental health care following the COVID-19 pandemic are not well understood,
nor are its effects on disparities. Last, because little is known about the relationships between quality, health
and social outcomes, and Medicaid and other costs or their interplay with race/ethnicity, policymakers lack a
full understanding of the state budgetary and societal impacts of interventions to improve the quality and equity
of SMI care. Our proposed research seeks to fill these evidence gaps hindering policymakers’ efforts to
improve quality, equity, and value of SMI care. We will leverage an ongoing partnership with the New York
State Medicaid program’s mental health authority, availability of several patient-level datasets, and subject
matter and methods expertise. Aim 1 will identify person- and area-level predictors of quality of care and
determine if the associations vary by race/ethnicity. Aim 2 will estimate the effects of receipt of high-quality
care on health and social outcomes and determine if the effects vary by race/ethnicity. Aim 3 will estimate the
effects of telehealth on quality of mental health care and costs to Medicaid and determine if the effects vary by
race/ethnicity. Aim 4 will develop alternative quality-improving interventions and compare their effects on
health and social outcomes, Medicaid and broader state spending, and racial/ethnic equity. Our proposed
research is responsive to PAR-23-095 and aligned with the NIMH Strategic Plan’s Goal 4 because, among
other tasks, we will (a) identify mutable factors that are likely to influence disparities in quality and outcomes for
underserved groups, (b) use large representative data sets and novel computational approaches to improve
mental health care and its outcomes, and (c) evaluate the impacts of an innovation (telehealth). Successful
completion of our aims will provide policymakers with race/ethnicity-infused evidence regarding (a) groups to
be targeted for interventions to improve quality of care, (b) the effects of high-quality care on key patient
outcomes, (c) the effects of telemental health policies, and (d) the comparative effects of alternative quality-
improving interventions on outcomes of high significance to patients, state policymakers, and society.
Terms: <21+ years old><Access to Care><Address><Adoption><Adult><Adult Human><Affect><Algorithms><Alternative Therapies><Alternative intervention><Area><Bipolar Affective Psychosis><Bipolar Disorder><COVID crisis><COVID epidemic><COVID pandemic><COVID-19 crisis><COVID-19 epidemic><COVID-19 era><COVID-19 global health crisis><COVID-19 global pandemic><COVID-19 health crisis><COVID-19 pandemic><COVID-19 period><COVID-19 public health crisis><COVID-19 years><Caring><Characteristics><Data><Data Set><Diagnosis><Disparities><Disparity><Equity><Ethnic Origin><Ethnic equity><Ethnicity><Funding><Goals><Health><Health Care Costs><Health Costs><Health Policy><Health Services Accessibility><Healthcare><Healthcare Costs><Homelessness><Individual><Inequity><Intervention><Intervention Strategies><Life Expectancy><Link><Literature><Machine Learning><Major Depressive Disorder><Manic-Depressive Psychosis><Measurement><Measures><Medicaid><Medical><Mental Health><Mental Health Services><Mental Hygiene><Mental Hygiene Services><Mentally Ill><Mentally Ill Persons><Methods><NIMH><National Institute of Mental Health><New York><New York City><Outcome><Patient outcome><Patient-Centered Outcomes><Patient-Focused Outcomes><Patients><Persons><Policies><Policy Analyses><Policy Analysis><Policy Maker><Population><Process><Provider><Psychological Health><Public Domains><Public Health><QOC><Quality of Care><Quasi-experiment><Quasi-experimental analysis><Quasi-experimental approach><Quasi-experimental design><Quasi-experimental methods><Quasi-experimental research><Quasi-experimental study><Quasi-experimental technique><Race><Races><Reporting><Research><Risk><SARS-CoV-2 epidemic><SARS-CoV-2 global health crisis><SARS-CoV-2 global pandemic><SARS-CoV-2 pandemic><SARS-coronavirus-2 epidemic><SARS-coronavirus-2 pandemic><Schizophrenia><Schizophrenic Disorders><Severe Acute Respiratory Syndrome CoV 2 epidemic><Severe Acute Respiratory Syndrome CoV 2 pandemic><Severe acute respiratory syndrome coronavirus 2 epidemic><Severe acute respiratory syndrome coronavirus 2 pandemic><Social outcome><Societies><Strategic Planning><Telemental><Telemental health><Underserved Population><Visit><access to health services><access to services><access to treatment><accessibility to health services><adulthood><authority><availability of services><beneficiary><bipolar affective disorder><bipolar disease><bipolar illness><bipolar mood disorder><burden of disease><burden of illness><care access><chronic mental illness><clinical depression><co-morbid><co-morbidity><cohort><comorbidity><comparative><coronavirus disease 2019 crisis><coronavirus disease 2019 epidemic><coronavirus disease 2019 global health crisis><coronavirus disease 2019 global pandemic><coronavirus disease 2019 health crisis><coronavirus disease 2019 pandemic><coronavirus disease 2019 public health crisis><coronavirus disease crisis><coronavirus disease epidemic><coronavirus disease pandemic><coronavirus disease-19 global pandemic><coronavirus disease-19 pandemic><cost><cost outcomes><dementia praecox><disability><disease burden><disparities in race><disparity due to race><disparity in ethnic><ethnic based disparity><ethnic disadvantage><ethnic disparity><ethnic inequality><ethnic inequity><ethnic minority><ethnicity disparity><health care><health care policy><health service access><health services availability><healthcare policy><high risk><homeless><improved><inequality due to race><inequity due to race><innovate><innovation><innovative><interventional strategy><machine based learning><machine learned algorithm><machine learning algorithm><machine learning based algorithm><major depression><major depression disorder><manic depressive disorder><manic depressive illness><mental health care><mental healthcare><novel><patient oriented outcomes><patient subclass><patient subcluster><patient subgroups><patient subpopulations><patient subsets><patient subtypes><payment><persistent mental illness><physical conditioning><physical health><policy evaluation><programs><public health relevance><race based disparity><race based inequality><race based inequity><race disparity><race related disparity><race related inequality><race related inequity><racial><racial background><racial disparity><racial inequality><racial inequity><racial minority><racial origin><racially unequal><schizophrenic><serious mental disorder><serious mental illness><service availability><severe acute respiratory syndrome coronavirus 2 global health crisis><severe acute respiratory syndrome coronavirus 2 global pandemic><severe mental disorder><severe mental illness><social><social health determinants><stem><suicidal><suicidality><telehealth><treatment access><under served group><under served individual><under served people><under served population><underserved group><underserved individual><underserved people><unhoused>