Expanding Insurance Coverage: Financial and Quality Spillovers in Local Health Care Markets

Slide Presentation from the AHRQ 2009 Annual Conference

On September 19, 2009, Jose A. Pagan made this presentation at the 2009 Annual Conference.

Select to access the PowerPoint® presentation (2 MB).


Slide 1

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

JA Pagán
9/15/2009

Slide 2

Acknowledgment

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

Slide 3

Americans are becoming more cynical as to what they will gain from health care reform.

Image: Line graph shows that number of people who consider they would be better off after health care reform has remained about the same (38% to 36%) between Feburary and August 2009. People who believe they would be worse off has risen from 11% to 31%, and people who believe it wouldn't make much difference has fallen from 43% to 27%.

Slide 4

More Worry About Negative Effects Then About Passage

Which worries you more?

51%: That Congress and the President will pass a reform bill that won't be good for you and your family

39%: That Congress and the President won't be able to pass health care reform this year

6%: Don't know/Refused

4%: Neither

Slide 5

Issues

  • Health care reform debate is confusing.
  • Everyone wants to know: "What's 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.

Slide 6

The uninsured population

  • 45 million nonelderly uninsured in 2009.
  • 54 million nonelderly uninsured by 2019.
  • 65% are from low-income families <200% 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.

Slide 7

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"

Slide 8

Percent Uninsured Under Age 65 - 2005 SAHIE Program

Image: Map of the United States shows percentage of uninsured by state and county.

Source: U.S. Census Bureau, Small Area Health Insurance Estimates (SAHIE) program, Oct. 2008

Slide 9

Local communities and uninsurance

Image: Chart shows relationship between health services, access to care, and economic effects.

Slide 10

Unmet medical needs by community ranking and insurance status

  Unisured Insured
Low 17.1% 5.5%
Mid-low 18.8% 6.1%
Mid-high 18.6% 7.2%
High 17.2% 8.l3%

A 10%-point increment in the proportion of local uninsured adults was associated with a 29.3% increase in the likelihood that an insured adult would have had unmet medical needs within the last 12 months.

Pagn JA, Pauly MV. (2006). "Community-level uninsurance and the unmet medical needs of insured and uninsured adults," Health Services Research, 41(3): 788-803.

Slide 11

Spillovers and vulnerability: the case of community uninsurance Pauly and Pagn, 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).

Slide 12

  • 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.

Slide 13

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.

Slide 14

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.

Slide 15

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.

Slide 16

Health Care Access, Utilization, And Quality Indicators Of Insured Adults, By Community Uninsurance, 2003

Image: Sample page of report.

Slide 17

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

  • Women ages 40-69 from 2000-2001 CTS HS (n=12,595).
  • Prob of mammography screening falls by 1.3% for every 10% increase in community uninsurance.

Slide 18

2009 IOM Report

  • Report covers:
    1. Health insurance coverage trends
    2. Health effects
    3. Community effects

Slide 19

Pauly & Pagn: 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).

Slide 20

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

Slide 21

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).

Slide 22

Table 1: Descriptive Statistics: Full Sample and by Community Uninsurance and Charity Care Use

  Community Uninsurance   Charity Care Use
Individual-level variables All Low High P-value Low High P-value
Have usual source of care (%) 89.06 91.32 86.54 0.00 90.16 87.98 0.07
Have a doctor's visit in the past year (%) 79.64 80.38 78.82 0.17 80.27 79.03 0.27
Have a doctor's visit for preventive care (%) 60.11 61.26 58.83 0.07 60.28 59.94 0.8
Very satisfied with choice of primary care
physician (%)
67.14 69.26 64.77 0.00 69.04 65.26 0.02
Very satisifed with health carea (%) 63.55 65.63 61.19 0.00 64.85 62.27 0.09
Trust doctors (%) 69.34 70.53 67.96 0.04 70.44 68.23 0.06
Fair or poor health (%) 9.1 8.26 10.03 0.01 8.64 9.55 0.2
Age (years) (mean) 40.87 40.85 40.89 0.90 41.15 40.6 0.13
Education (years) (mean) 13.92 14.03 13.8 0.03 13.89 13.95 0.61
Race/Ethnicity (%)  
White 76.64 83.95 68.53 0.00 83.69 69.74 0
Black 9.53 6.87 12.48 0.02 6.69 12.31 0.02
Hispanic 9.07 4.75 13.86 0.00 4.53 13.51 0
Other 4.76 4.43 5.13 0.49 5.09 4.44 0.53
Married (%) 71.48 73.61 69.11 0.01 72.68 70.3 0.2
Female (%) 50.95 50.79 51.12 0.73 51.34 50.56 0.39
Income/family poverty level (mean) 4.59 4.78 4.38 0.03 4.52 4.66 0.45
Community-level variables  
Percent uninsured in community (%) 15.15 10.20 20.64 0.00 13.98 16.28 0.13
Percent of uninsured population with no
cost-related access difficulties (%)
67.71 65.77 69.86 0.16 58.31 76.91 0
Median household income/1,000 (mean) 47.51 53.11 41.29 0.00 47.57 47.46 0.97
 
Gini coefficient (mean) 0.38 0.36 0.4 0.00 0.37 0.39 0.03

Notes: a Wald test of differences in means/proportions by low/high community uninsurance and low/high charity care use (i.e., comparison between the 30 communities with low and hight community uninsurance and charity care use, respectively.

Slide 23

Table 2: Adjusted Odds Ratios of Potential and Realized Health Care Access

  Had a place to go when sick or in need of advice about health Had a doctor's visit in the past year Had a doctor's visit for a routine preventive care
Individual-level variables OR 95% ci OR 95% ci OR 95% ci
Fair or poor health 1.05 (0.78, 1.41) 2.27*** (1.74, 2.95) 1.20 (0.99, 1.46)
Age (years) 1.02*** (1.01, 1.03) 1.02*** (1.01, 1.02) 1.03*** (1.02, 1.03)
Education (years) 1.02 (0.98, 1.06) 1.06*** (1.03, 1.08) 1.04*** (1.02, 1.06)
Black 0.85 (0.65, 1.12) 0.94 (0.74, 1.18) 1.73*** (1.39, 2.15)
Hispanic 0.53*** (0.42, 0.67) 0.71*** (0.59, 0.86) 1.07 (0.91, 1.25)
Other 0.48*** (0.35, 0.64) 0.68*** (0.51, 0.91) 1.02 (0.83, 1.25)
Married 1.44*** (1.15, 1.80) 0.98 (0.85, 1.12) 0.99 (0.89, 1.11)
Female 2.03*** (1.81, 2.29) 2.82*** (2.56, 3.12) 2.59*** (2.35, 2.86)
Income/family poverty level 1.04 (1.81, 2.29) 1.07*** (1.03, 1.10) 1.04*** (1.02, 1.07)
Community-level variables  
Percent uninsured in community /10 0.63*** (0.60, 0.68) 0.89*** (0.85, 0.92) 0.91*** (0.88, 0.94)
Percent of uninsured population with no
cost-related access difficulties /10
0.98 (0.95, 1.01) 1.00 (0.99, 1.02) 0.99* (0.98, 1.00)
Median household income/1,000 1.00 (0.99, 1.01) 1.00 (1.00, 1.00) 1.01*** (1.00. 1.01)
 
Gini coefficient 36.43*** (10.40, 127.63) 9.07*** (4.06, 20.26) 7.00*** (4.11, 11.91)

Notes: *p<0.05p<0.01***p<0.001

Slide 24

Table 3: Adjusted Odds Ratios of Assessment of Health Care System Providers

  Very satisfied with choice of primary care physician Very satisfied with health care Trust doctors
 
Individual-level variables OR 95% CI OR 95% CI OR 95% CI
Fair or poor health 0.77* (0.62. 0.94) 0.70*** (0.58, 0.85) 0.73*** (0.60, 0.88)
Age (years) 1.01*** (1.01, 1.01) 1.01*** (1.00, 1.01) 1.01*** (1.00, 1.01)
Education (years) 1.01 (0.99, 1.04) 1.00 (0.97, 1.02) 0.98* (0.95, 1.00)
Black 1.04 (0.87, 1.25) 0.93 (0.76, 1.15) 0.96 (0.79, 1.16)
Hispanic 0.78** (0.66, 0.94) 0.74* (0.58, 0.93) 0.63*** (0.52, 0.76)
Other 0.73** (0.59, 0.90) 0.84 (0.61, 1.16) 0.87 (0.67, 1.12)
Married 0.93 (0.84, 1.03) 1.07 (0.94, 1.23) 0.83** (0.74, 0.94)
Female 1.31*** (1.18, 1.45) 1.11** (1.04, 1.19) 1.16** (1.04, 1.30)
Income/family poverty level 1.02 (1.00, 1.05) 1.07*** (1.05, 1.10) 1.00 (0.98, 1.03)
Community-level variables
Percent uninsured in community /10 0.75*** (0.72, 0.78) 0.90*** (0.86, 0.94) 0.93*** (0.94, 0.96)
Percent of uninsured population with no cost-related access difficulties /10 0.93*** (0.91, 0.95) 0.95*** (0.93, 0.97) 0.99 (0.98, 1.00)
Median household income/1,000 0.99*** (0.98, 0.99) 1.00 (1.00, 1.00) 1.00* (1.00, 1.01)
 
Gini coefficient 14.32*** (5.53, 3703) 2.94* (1.22, 7.07) 2.62*** (1.57, 4.35)

Notes: *p<0.05p<0.01***p<0.001

Slide 25

Simulated Effects of Changes in Community Uninsurance and Charity Care on Potential and Realized Health Care Access

 

  Had a place to go when sick Had a doctor's visit in the past year Had a visit for routine preventive care Has seen specialist in the last 12 months
  % % % %
Community uninsurance
Percent uninsured in community (Baseline=15.15%) 92 85 64.8 98.3
Percent uninsured in community (New=25.15%) 88 83.4 62.6 97.9
Percentage point change -4.05 -1.61 -2.23 -0.31
Charity care
Percent of uninsured population with no cost-related access difficulties (Baseline=67.71%) 92.2 85.1 64.9 98.3
Percent of uninsured population with no cost-related access difficulties (New=77.71%) 92.1 85.1 64.7 98.2
Percentage point change -0.13 0.03 -0.26 -0.08

Slide 26

Simulated Effects of Changes in Community Uninsurance and Charity Care on Assessment of Health Care System Providers

 

  Very satisfied with PCP choice Very satisfied with health care Trust doctors Very satisfied with choice of specialist seen
  % % % %
Community uninsurance
Percent uninsured in community (Baseline=15.15%) 62.7 53.7 72.1 74.5
Percent uninsured in community (New=25.15%) 55.6 51 70.8 71.8
Percentage point change -7.06 -2.7 -1.38 -2.72
Charity care
Percent of uninsured population with no cost-related access difficulties (Baseline=67.71%) 63.1 53.9 72.2 74.7
Percent of uninsured population with no cost-related access difficulties (New=77.71%) 61.3 52.7 72.1 74.6
Percentage point change -1.76 -1.24 -0.17 -0.08

Slide 27

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.

Slide 28

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.

Slide 29

Agent-based model
(D Damianov, JA Pagn)

  • 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).

Slide 30

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 "What's in for me?" question should always consider the broader community/market effects.

Thanks!

Current as of December 2009
Internet Citation: Expanding Insurance Coverage: Financial and Quality Spillovers in Local Health Care Markets: Slide Presentation from the AHRQ 2009 Annual Conference. December 2009. Agency for Healthcare Research and Quality, Rockville, MD. http://www.ahrq.gov/news/events/conference/2009/pagan/index.html