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Moving Toward Evidence-Based Health Policy in California's Medicaid Program. Andrew B. Bindman, MD Professor Medicine, Health Policy, Epidemiology & Biostatistics University of California San Francisco. Research Interest. Health consequences of public policies

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Moving toward evidence based health policy in california s medicaid program l.jpg

Moving Toward Evidence-Based Health Policy in California's Medicaid Program

Andrew B. Bindman, MD

Professor Medicine, Health Policy, Epidemiology & Biostatistics

University of California San Francisco

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Research Interest Medicaid Program

  • Health consequences of public policies

  • Access to and quality of care for low-income, diverse, and patient populations vulnerable to poor health because of their social circumstances

  • Tied to clinical and teaching activities at San Francisco General Hospital

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Scientific Research/Advocacy Medicaid Program

  • Possible to advocate without research

  • Evidence-based approach may provide a more compelling means to reach group consensus on the truth and strategy

  • Scientific approach comes with responsibilities (scientific integrity, ethical obligation to publish results)

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Medi-Cal: Medicaid ProgramCalifornia’s Medicaid Program

  • 6.6 million beneficiaries

  • $40 billion this past year

  • 2nd largest use of general fund (17%)

  • Pays for 1 in every 2 births in the state

  • Covers 2 of 3 nursing home patients

  • Half of beneficiaries are Latino

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Medi-Cal’s Challenges Medicaid Program

  • Cost of program outpacing other state programs/funds to support it

  • Data systems offer limited assessment of access, quality, value

  • Constraints on state government salaries results in brain drain

  • Bureaucracy makes it challenging to contract for help

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CaMRI Medicaid Program

  • California Medicaid Research Institute

  • Collaborative partnership between University of California and California Department of Health Care Services (Medi-Cal)

  • Focus is on health policy research, evaluation, and technical assistance

  • Similar model in several other states

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Opportunity for UC Medicaid Program

  • To develop new knowledge that can contribute to evidence based decision-making for an important state health program

  • To participate in the development and use of data systems that can improve the assessment of access, cost and quality of Medi-Cal program

  • To create a training environment for future health policy decision-makers and investigators

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CaMRI Steering Committee Medicaid Program

  • UCSF (Host Campus)

    • Andrew Bindman, Director

    • Claire Brindis, Associate Director

  • UCB

    • Richard Scheffler, Associate Director

  • UCLA

    • Richard (Rick) Brown, Associate Director

  • UCSD

    • Richard (Rick) Kronick, Associate Director

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How CaMRI works Medicaid Program

  • Interagency Agreement/project template

  • Regular dialogue between Medi-Cal and UC

  • State support as well as federal matching of UC’s certified public expenditures

  • Facilitate Medi-Cal’s access to UC experts

  • Enhance UC access to Medi-Cal data

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Scope of Work Medicaid Program

  • Beneficiaries

    • health services and support needs

    • utilization patterns

    • health outcomes

    • beneficiary satisfaction

  • Program benefits

    • scope, duration and frequency of benefits

    • clinical- or cost-effectiveness of benefits

  • Program eligibility

    • Service/cost implications of eligibility expansions or reductions

    • outreach, enrollment and retention

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Scope of Work (cont) Medicaid Program

  • Health care delivery systems

    • fee-for-service and managed care

    • use and effectiveness of health IT

    • incentive payment systems

    • quality improvement programs

    • costs/benefits of delivery models

  • Program administration

    • enrollment/re-determination processes

    • provider enrollment processes

    • effectiveness of cost controls/UM

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Challenges Medicaid Program

  • Logistics of data sharing

  • Political nature of annual budget process

  • Understanding each others culture, timing, and expectations for gauging success

  • Building sustained trust in the partnership

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Land Mines to Avoid Medicaid Program

  • Conflicts of interest

  • Compromising UC’s role as a trusted independent voice

  • Compromising DHCS competitiveness in the market place

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National Advisory Committee Medicaid Program

  • To help protect us from the land mines

  • Panel of state and national experts who will serve as a sounding board and advisory body to our process

  • Connect our work to related work nationally and in other states

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Example Project: Medicaid ProgramEligibility Re-determination

  • More than half of Medicaid beneficiaries nationwide have interruptions in coverage

  • State laws vary regarding duration of eligibility re-determination period

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Study Questions Medicaid Program

How does the administrative burden of re-enrollment in Medicaid effect the continuity of coverage?

What are the health and cost consequences of interruptions in Medicaid enrollment?

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Nature of State’s Medi-Cal data Medicaid Program

  • Claims (eg hospital, outpt, pharmacy)

  • No claims for managed care (~50%)

  • Monthly eligibility

  • No record of beneficiaries after they lose coverage

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Linkage Medicaid Program

DHS: Medi-Cal Enrollment Database

  • Demographics

  • Monthly enrollment history

  • Aid Category (e.g. TANF or SSI)

  • FFS, managed care

  • Other insurance



Linked CA Hospital Discharge and Medicaid Eligibility Files

OSHPD: Hospital Discharge Data



  • Diagnosis (ICD-9 Code)

  • Month/Year of admission

  • Payer

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Creating a Valid Link Medicaid Program

  • Deterministic match on SS#

  • Probabilistic match with partial SS#, DOB, and sex

  • Validated match with separate Medi-Cal payment records

  • 98% success in matching

  • Least success with <1 year olds

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Study Design Medicaid Program

  • All individuals 1-64 years with at least 1 month of

    Medicaid coverage Jan 1998 to December 2002

  • Outcome

    Time to a hospital admission for an ambulatory care sensitive condition

  • Main predictor

    Continuous or interrupted Medicaid coverage between enrollment and time of admission

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ACS Conditions Medicaid Program

Ambulatory Care Sensitive Conditions:AHRQ Prevention Quality Indicators

  • Condition with acute course and window for intervention

  • Condition with chronic course amenable to self-management

Chronic Conditions:

  • Asthma

  • Hypertension

  • COPD

  • Diabetes Mellitus

  • Heart Failure

  • Angina

Acute Conditions:

  • Dehydration

  • Ruptured Appendicitis

  • Cellulitis

  • Bacterial Pneumonia

  • Urinary Tract Infection

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Reverse Causality Medicaid Program

  • Interruption in coverage might not predict worse health outcome so much as worse health might predict whether or not have interrupted coverage

  • Bias of higher admissions among those with continuous coverage

  • Consider option of using subjects as their own control

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Survival Analysis of Medicaid Coverage and Interruption Spells on ACS Hospitalizations



Medicaid Coverage

ACS Admission


(2003 or 65 Years)

ACS Admission

New Spell



Interruption of Coverage

New Spell

ACS Admission


(2003 or 65 Years)



Censored (2003 or 65 Years)

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ACS Hospitalization Rates: Spells on ACS HospitalizationsContinuous vs Interrupted Medicaid Beneficiaries

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Probability of ACS Hospitalization Spells on ACS HospitalizationsOver Time by Medicaid Coverage Status

Cumulative Probability

Time (Months)

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Adjusted Risk of ACS Hospitalization Spells on ACS Hospitalizations

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Limitations Spells on ACS Hospitalizations

  • Do not have measures of disease prevalence or health status differences between those with continuous versus interrupted Medicaid coverage

  • Limited information on the subsequent health insurance status of those with interrupted Medicaid coverage

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Natural Experiment of Interrupted Medicaid Coverage Spells on ACS Hospitalizations

  • California extended Medicaid eligibility re-determination period for all children in California from every 6 to every 12 months on January 1, 2001

  • Extension of eligibility re-determination period should be associated with an increase in continuity of Medicaid coverage, but should not except through its influence on continuity of coverage affect the health status of children.

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Pre/Post Study of Re-Enrollment Policy Change for Children Spells on ACS Hospitalizations

  • Children 1-17 years with a minimum of 1 month of Medicaid coverage in California

  • Outcome = time to a hospital admission for an ambulatory care sensitive condition

  • Main predictor = time period

    • Pre policy change = 1/99-12/00

    • Post policy change = 1/01 -12/02

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Children with Continuous Medicaid Enrollment by Time Period Extension of Re-Determination Period




Years of Enrollment

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Comparison Group: TimeAdults in Medicaid

  • Medicaid eligibility re-determination period did not change during study period for adults in California

  • Adults with Medicaid coverage

    • 1999-2000 = 62%

    • 2001-2002 = 60%

  • Adjusted relative hazard of a hospitalization for an ACS condition for adults in post vs pre period= 1.11

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Who Is Paying the Bill? Enrollment Extension in 2001 – 2002

  • Among hospitalized children

    • 60% re-gained Medi-Cal

    • 33% had another form of insurance

    • 7% uninsured

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Other Hidden Costs of Interrupted Coverage Enrollment Extension in 2001 – 2002

  • Administrative costs of more frequent eligibility re-determination

  • Costs of more frequent emergency room visits

  • Costs of hospitaliations of other potentially avoidable hospitalizations

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Policy Implications Enrollment Extension in 2001 – 2002

  • States need to become more aware of the hidden costs in their Medicaid eligibility policies

  • Continuity of Medicaid coverage can support better health and decrease wasteful spending on hospitalizations that could have been avoided with less costly outpatient care

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Research Partnership with State Government Enrollment Extension in 2001 – 2002

  • Opportunity to link HSR with a needy/receptive customer

  • Steep learning curve for each party

  • Building capacity takes time

  • Can experience challenges in trying to publish results of 1 state

  • Significant public service component that university needs guidance on how to measure/value