Making it real: Auto-enrollment into new state coverage

Stan DornSenior Research AssociateUrban Institute202.261.5561sdorn@ui.urban.org

SCIWinter MeetingJanuary 25, 2007

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Overview

1. Enrollment models

2. Applying auto-enrollment to state coverage reforms

3. Challenges

Preliminary topic: Why enrollment matters

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If you build it, will they come?

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Why enrollment matters

SubstanceNecessary to improve access to health care

PoliticsEnrollment costs money – do you really want

it? The standard enrollment growth curve creates

political vulnerability – for example, see next slide

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PRESS RELEASE

The Maine Heritage Policy Center FOR IMMEDIATE RELEASE CONTACT: August 16, 2005

Muskie Survey Shows Dirigo’s Failure and High Cost to Taxpayers

Taxpayers are spending $15 million a year to reach 1,800 uninsured Mainers.

Portland, ME - The Maine Heritage Policy Center today cited the DirigoChoice Member Survey: A Snapshot of the Program’s Early Adopters, a report prepared by the Muskie School of Public Service, as definitive proof of the failure of the DirigoChoice health insurance product. The survey reveals that only 1,800 or 22.4% of DirigoChoice enrollees were uninsured and that the state is spending nearly $8.00 for every $1.00 of savings to the health care system attributed to providing coverage to those previously uninsured individuals.

“DirigoChoice is a costly failure,” said Tarren Bragdon, director of health reform initiatives for the Maine Heritage Policy Center. “It is not significantly covering the uninsured and it is costing the Maine taxpayers millions of dollars a year. Maine taxpayers are paying $15 million a year to cover 1,800 previously uninsured people.”

Part I: Basic enrollment models

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Traditional public benefits model

Government’s roleProvide program information – “outreach”Process applications

Individual mustApplyProvide individual information showing

eligibilityComplete the application process

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Implications of the traditional model Many people can be covered, with hard work

Simple and streamlined application procedures Effective outreach

BUT – the model must deny coverage to: Eligible people who do not apply Eligible people who do not complete the process

It can take years for a new program to reach most of its targeted beneficiaries

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Auto-enrollment models Default enrollment Data-driven enrollment Proactively assisted enrollment

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Basic principle: Newton’s First Law of Motion

“An object at rest tends to stay at rest…”

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Examples of auto-enrollment

1. SCHIP vs. Medicare Part D2. Retirement savings3. Medicare Part B4. Community-based, proactive facilitation

of child health enrollment5. Retention of health coverage in

Louisiana

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Example #1: SCHIP vs. Low-Income Subsidies (LIS) for Medicare Part D

SCHIP enrollment by eligible children: first five years

44%54% 60%

0%

25%

50%

75%

100%

1997 1998 2000 2002

Source: Selden, et al., 2004 (MEPS data).

Effective 10/1/97

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Example # 1, continued LIS Enrollment by Eligible Seniors as of 6/11/06, Less Than Six Months After 1/1/06 Effective Date

60%

14%

0%

25%

50%

75%

100%

Applied

Auto-enrolled

Total enrollment: 74%

Source: CMS enrollment data. Calculations by Urban Institute.

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Data-driven enrollment – Medicare Part D, LIS Can apply to SSA Without application, automatically enrolled in

drug plan, with LIS, if received Medicaid or SSI the prior year

General correspondence, not precise match, in eligibility rules Prior year income MSP – 5 states have no asset tests, unlike LIS Different income methodologies

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Example #2: retirement savings

Percentage of eligible workers who participate in tax-advantaged retirement accounts

10%

33%

90%

Independent enrollment inIRA

Firms where new hiresenroll in 401(k) only after

completing a form

Firms where new hires gointo 401(k) UNLESS they

complete an opt-out form

Sources: Etheredge, 2003; EBRI, 2005; Laibson (NBER), 2005.

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Example #3: Medicare Part BPercentage of eligible individuals who receive

various Medicare benefits

13%

33%

96%

Voluntary enrollment inMSP - SLMB

Voluntary enrollment inMSP - QMB

Medicare Part B, in whichseniors are enrolledUNLESS they opt out

Sources: NASI, 2006; Remler and Glied, 2003.

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Example #4: Community-based facilitators of child health enrollment

Medicaid/SCHIP take-up rate among low-income, Latino children in Boston: standard outreach vs.

community-based case managers

57%

96%

Standard outreach Community-based case managers

Source: Flores, et al., Pediatrics, 12/05.

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Example #5: Retention in Louisiana

Renewal outcomes for Medicaid children in Louisiana, before and after implementation of data-driven renewal and related procedures

28%

72%

8%

92%

0%

25%

50%

75%

100%

Percent losing coverage Percent retainingcoverage

June 2001

April 2005

Source: Summer and Mann, Georgetown University Health Policy Institute (prepared for Commonwealth Fund), June 2006. Note: other policy changesincluded telephone contact, rather than forms, to supplement data.

Part II: Applying Auto-Enrollment to State Coverage Reforms

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Potential applications

1. Subsidizing employer-based coverage

2. Individual responsibility

3. Subsidies from public programs

4. “Cover all kids”

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Application #1 – subsidizing low-income employees of small firms Low income is the key variable to

effectively targeting subsidies to uninsured workersLow wages and low income are not identical

Can’t ask employers to means-testPrivacyHassle

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Among micro-firms’ employees, most uninsured workers have low incomes

3.0 2.0 2.2

7.3

0

5

10

Millions of workers

Under 200% FPL Over 200% FPL

Income

Workers at establishments with fewer than 10 employees, by insurance status

and family income: 2005

UninsuredInsured

Source: Clemans-Cope and Garrett (Urban Institute) 2006. Unpublished estimates based on the February 2001 and 2005 Contingent Work Supplement of the Current Population Survey (CPS) and the March 2001 and 2005 Annual Social and Economic (ASEC) Supplement of the CPS..

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Among small firms’ employees, most uninsured workers have low incomes

1.8 1.4 1.4

6.3

0

5

10

Millions of workers

Under 200% FPL Over 200% FPL

Income

Workers at establishments with 10 to 24 employees, by insurance status and

family income: 2005

UninsuredInsured

Source: Clemans-Cope and Garrett..

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Among medium-size firms’ workers, most uninsured have low incomes

1.72.2

1.2

10.6

0

4

8

12

Millions of workers

Under 200% FPL Over 200% FPL

Income

Workers at establishments with 25 to 99 employees, by insurance status and

family income: 2005

UninsuredInsured

Source: Clemans-Cope and Garrett..

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Among large firms’ workers, most uninsured have low incomes

4.48.4

3.1

56.7

0

20

40

60

Millions of workers

Under 200% FPL Over 200% FPL

Income

Workers at establishments with 100 or more employees, by insurance status and

family income: 2005

UninsuredInsured

Source: Clemans-Cope and Garrett..

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Auto-enrollment strategy Obtain automatic access to income databases

Other means-tested programs State workforce agency earnings data State income tax data

The application depends on the reform In a premium assistance program, use data to identify

low-income employees who qualify for refunds of worker premium payments

In a program that gives small firms access to health insurance exchanges or purchasing pools, use data to identify low-income employees who qualify for premium subsidies

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Income vs. hourly wages – percentage of workers without health coverage

39%

16%

4%

54%

0%

20%

40%

60%

Under100%FPL

100-199%FPL

200-399%FPL

400%+FPL

50%

39%

21%

6%

0%

20%

40%

60%

Lessthan $7

$7 to$9.99

$10 to$14.99

$15+

Source: Clemans-Cope and Garrett..

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Income vs. hourly wages – distribution of uninsured workers

100-199% FPL, 36%

200-399% FPL, 31%

400%+ FPL, 11%

Under 100% FPL, 22%

Under $7, 24%

$7 to $9.99, 27%

$10 to $14.99,

27%

$15+, 22%

Source: Clemans-Cope and Garrett..

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Application #2 - individual responsibility laws Key enrollment junctures – e.g.:

Income reports to state workforce agencies; Health care visits; Filing state tax forms; etc.

Automatically enrolled into coverage at these junctures

Premium based on income, determined by data Note: default enrollment can be alternative or

predecessor to mandate

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Application #3 – public programs Cover people based on the income determinations of other

means-tested programs May need 1115 waiver to disregard methodological differences, use

valid SSN as evidence of satisfactory immigration/citizenship LIS auto-enrollment precedent

IT investment crucial Eligibility factors other than income

Citizenship – some databases DHS – immigration status documentation

The next four slides focus on nutrition programs, but state EITC may also provide a huge opportunity – more research needed

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Most low-income, uninsured children live in families that receive means-tested nutrition assistance

Percentage of Low-Income, Uninsured Children Whose Families Participated in Means-Tested Nutrition Programs:

2002

59%

22%8%

71%

NSLP WIC Food Stamps Any of thosethree programs

Source: Dorn and Kenney, Urban Institute (prepared for Commonwealth Fund), June 2006. Notes: (1) Analysis based on 2002 NSAF. (2) NSLP is the National School Lunch Program. (3) Low-Income is at or below 200% of the FPL.

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Health Coverage Among Low-Income Children Whose Families Participated in Means-Tested Nutrition Programs, 2002

25% 20%8%

24%

56% 66% 84% 57%

2%2%

2%2%

6%17% 12% 16%

NSLP WIC Food Stamps Any of theseprograms

ESI Medicaid/SCHIP Other coverage Uninsured

Source: Dorn and Kenney.

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Most poor, uninsured parents live in families that receive means-tested nutrition assistance or child health coverage

Percentage of Uninsured, Poor Parents Whose Families Participated in Means-Tested Nutrition Programs or

Whose Children Received Medicaid, 2002

55%39%

22%

53%

83%

NSLP WIC Food stamps One or morechildrenreceive

Medicaid

Any of thesenutrition orchild healthprograms

Source: Dorn and Kenney. Note: Poor parents have the following characteristics: their income is at or below the FPL; they are ages 18 to 64; and they live with a stepchild, biological child, or adopted child under age 18.

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Health Coverage Among Poor Parents Whose Families Participated in Means-Tested Nutrition Programs or Whose Children Received Medicaid, 2002

16% 13% 8% 7% 14%

34% 37%57%

49% 36%

4% 2%

4%3%

3%

46%32%46% 48% 41%

NSLP WIC Food Stamps Child inMedicaid

Any of theseprograms

ESI Medicaid/SCHIP Other coverage Uninsured

Source: Dorn and Kenney.High-impact, efficient intervention via SPA

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Application #4 – cover all kids Identify uninsured children at key life junctures –

Starting school year – child health form Hospital-based birth

Use data to: Provide ongoing Medicaid/SCHIP coverage to children known to

eligible Provide presumptive eligibility to children potentially eligible,

following up with community-based, proactive application assistance for ongoing coverage

For children ineligible for Medicaid/SCHIP: Allow buy-in Default enrollment into buy-in, unless parents object

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“Applications? We don’t need no stinkin’ applications!”

The Auto-Enrollment motto:

Part III: Challenges

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With default enrollment, do people get services? Real risk, but not necessarily a huge problem

Medicare Part D default enrollees average more prescriptions per month than other enrollees

Potential remedies Consumer education Health plan incentives

Limited withhold of partial capitated payments based on number of default enrollees receiving zero services

Award future default enrollment shares based on prior performance with default enrollees

Monitor with encounter data, compare default to other enrollment

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Isn’t data protected by statute?

State statutory changes may be needed to access data

Federal statutes limiting access to national data In some cases, federal law change may be needed –

e.g., national New Hires Data Base In some cases, consumers can consent to disclosure IRS and SSA data is open to Medicaid programs

Federal procedural safeguards Computer Matching and Privacy Protection Act of 1988

(Pub. L. No. 100-503)

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Regardless of the law, aren’t safeguards of privacy and data security needed? Use limitations Interagency agreements Prevention of unauthorized access, use,

modification, or disclosure of data Data transparency, including notice of databases

and data controller Individual access to and correction of data Accountability

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Data: current, accurate and complete? State workface agency data – quarterly

Gaps: work in other states, federal employees, sometimes several months out of date

Income tax data – prior year Immigration status – DHS data not strong

Real ID may force improvements Strategies

Combine recent wage data with prior-year tax data re other income Estimate, inform consumer, give consumer the ability to call and

correct Post-eligibility audits, corrections Define eligibility based on prior year income

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Won’t this cost the state money? MMIS enhanced match (90/75) generally unavailable for

eligibility purposes 50/50 FMAP for general administration

Possible access to 90/75 FMAP under MITA: incorporating eligibility information into EHRs

For proactive facilitation, target likely eligibles Possible foundation interest Multiple benefits of IT investment – coverage, integrity,

efficiency Enrolling eligible individuals Preventing erroneous grants of eligibility Lowering administrative operating costs

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Will low-income people be charged unaffordable amounts? In default enrollment system, failure to pay

first month’s premium = opt-out With personal responsibility requirements:

Very intensive income screening and enrollment into subsidies based on data, hands-on application assistance

Exceptions for unaffordable coverage

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How can premium collection be assured? Automate payment of premiums

Paycheck withholding, building on current systems – W-4, payroll companies, inexpensive software for small firms

Credit card payments Requirements or incentives – e.g., premium discounts

for automated or multiple payments Back-end collection, if individuals do not pay

Income tax liability Other, nastier mechanisms?

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Summary

For new state initiatives to succeed, enrollment and retention methods must be effective

The more you ask consumers to do, the fewer consumers will do it

If you want new initiatives to cover as many eligible individuals as possible, use default enrollment, data-driven enrollment, and proactive assistance to eliminate the need for consumers to complete forms