Expanding insurance coverage: Financial and quality spillovers in local health care markets

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Expanding insurance coverage Financial and
quality spillovers in local health care markets

• JA Pagán
• 9/15/2009

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Acknowledgment

• AHRQs Minority Research Infrastructure Support
  Program.
• AHRQs M-RISP Program funded the Health Services
  Research Initiative at The University of
  Texas-Pan American.
• Grant Number R24HS017003.

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Issues

• Health care reform debate is confusing.
• Everyone wants to know Whats in for me?
• Understanding potential spillovers of insurance/
  uninsurance on local health care markets is key.
• Empirical analyses based on data from the
  Community Tracking Study ? Potential/realized
  access and assessment of health care providers.
• Policy modeling and implications.

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The uninsured population

• 45 million nonelderly uninsured in 2009.
• 54 million nonelderly uninsured by 2019.
• 65 are from low-income families (lt200 FPL).
• 35 of Latinos, 29 of Native Americans and 20
  of African Americans are uninsured compared to
  12 of whites.
• Sources Congressional Budget Office, 2009
  Kaiser Family Foundation (2006) The Uninsured, A
  Primer.

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Rationale for providing access

• Good but not fully convincing argument
• It is the right thing to do
• Enlightened self-interest argument
• It makes you and me better off

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Local communities and uninsurance
Increased public/ Private spending
Public health services
Lower revenue for healthcare providers
Economic effects
Population health
Financial instability of Providers/institutions
Reduce charity/ uncompensated care
Access to care
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Unmet medical needs by community ranking and
insurance status
Pagán JA, Pauly MV. (2006). Community-level
uninsurance and the unmet medical needs of
insured and uninsured adults, Health Services
Research, 41(3) 788-803.
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Spillovers and vulnerability the case of
community uninsurance (Pauly and Pagán, Health
Affairs 2007)

• IOM framework High uninsurance results in higher
  uncompensated care (bad debt and charity care).
• End result Insured people pay for this (10
  higher premiums higher prices cost-shifting).
• This is a pecuniary community spillover (that is,
  a financial spillover that works its way through
  prices).
• Local pecuniary spillovers on the insured are
  likely to be small when money flows from the
  outside (e.g., Medicare DSP, state funds).

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Non-pecuniary or real spillovers

• Occur when the uninsured demand a lower quality
  and quantity of health care than the insured.
• Preference externalities distinct groups of
  consumers who have substantially different
  preferences from others bring forth products
  with more appeal to themselves but less appeal to
  others (Waldfogel, 2003).
• Caveat Local health care markets must not be
  perfectly segmented.

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Non-pecuniary, real spillovers in partially
insured markets

• Uninsured demand lower quality care.
• Even if the insured have differential access to
  health care (e.g., better facilities to go to),
  there are high fixed costs for quality
  differentiation.

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Example Two communities of same size and number
of uninsured

• Community 1 Uninsured never use charity care and
  can only pay for low quality care.
• ? Only quality spillover.
• Community 2 Uninsured get charity care and do
  not skimp on quality.
• ? Only pecuniary spillover.

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How can the insured reduce these negative
effects?

• By patronizing health care suppliers that do not
  provide care to the uninsured or who do not
  engage in cost shifting.
• This can only happen in large enough markets that
  can be segmented (e.g., in certain regions and
  for low-fixed-cost services).
• Quality spillovers are more likely in specialty
  care, care requiring expensive equipment (e.g.,
  scanning), etc.

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Community uninsurance and mammography (J of
Clinical Oncology April 2008)

• Women ages 40-69 from 2000-2001 CTS HS
  (n12,595).
• Prob of mammography screening falls by 1.3 for
  every 10 increase in community uninsurance.

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2009 IOM Report

• Report covers
• Health insurance coverage trends
• Health effects
• Community effects

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Pauly Pagán Spillovers of uninsurance in
communities

• 2003 CTS Household Survey ? Participants
  clustered in 60 communities (48 large metro
  areas, 3 small metro areas and 9 non-metro
  areas).
• Working age population (N 31,935).
• Health care measure f(Community uninsurance,
  Charity care, X, C).

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Dependent variables

• Potential and realized health care access
• (1) Respondent has a place to go when sick
• (2) Visited doctor
• (3) Visited doctor for routine preventive care
• Assessment of health care providers
• (1) Satisfaction with choice of PCP
• (2) Satisfaction with health care received
• (3) Trust doctor

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Independent variables (distinguishing pecuniary
and real spillovers)

• Community uninsurance rate ? Proportion
  uninsured.
• Charity care ? Proportion of uninsured
  respondents in a community with no cost-related
  problems obtaining medical care.
• Charity care proxy is correlated with different
  sources of free care (hospitals, doctors and
  FQCHCs Herring, 2005).

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Simulated Effects of Changes in Community
Uninsurance and Charity Care on Potential and
Realized Health Care Access
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Simulated Effects of Changes in Community
Uninsurance and Charity Care on Assessment of
Health Care System Providers
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Conclusion/caveats

• Model predictions depend on
• the degree of market segmentation,
• the amount of charity care (or below cost care),
  and
• the source of resources to cover the cost of
  charity or below cost care.
• Empirical evidence points to both real and
  pecuniary spillovers.
• The theory is value neutral ? Insurance-related
  quality spillovers could be good or bad.

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Punchline

• Different approaches to cover the uninsured will
  lead to different effects on the insured.
• Ex 1 Increase support for safety net providers
  that cater to the uninsured (e.g., community
  health centers) ? little positive real spillover
  on the insured.
• Ex 2 Tax credits for health insurance would have
  a positive real spillover on the insured.

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Agent-based model (D Damianov, JA Pagán)

• Objective Understand consequences of various
  health care reform proposals.
• Approach Modeling incentives to purchase
  insurance and use services based on the quality
  of the service provided, price, and
  risk/preferences.
• Model useful to understand complex social
  dynamics and learning between micro/macro-level
  processes.
• Agents respond to their social context,
  especially to the actions of other members in
  their community (local health care market).

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Future

• Health care reform plans are constantly changing
  How do we muddle through and get our message
  across?
• In making the individual, business or social case
  for reform, the answer to the Whats in for me?
  question should always consider the broader
  community/market effects.

Thanks!