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The War on Poverty’s Experiment in Public Medicine: Community Health Centers and the Mortality of Older Americans. Martha J. Bailey 12 and Andrew Goodman-Bacon 1 1 University of Michigan 2 National Bureau of Economic Research. Community Health Centers (CHCs).
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The War on Poverty’s Experiment in Public Medicine: Community Health Centers and the Mortality of Older Americans Martha J. Bailey12 and Andrew Goodman-Bacon1 1 University of Michigan 2 National Bureau of Economic Research
Community Health Centers (CHCs) • Public provision of primary care and subsidies for drugs • Model: Affordable, convenient, comprehensive and efficient delivery • located in poor communities • outreach, health education • in-house pharmacy • home visits and transportation • employed members of the community • Lofty ideals: Transform the model of health care for the poor
Why Care about CHCs? • CHCs have survived to 2010 • “Community”/“Federally-Qualified” Health Centers • CHCs important in health reform • ARRA: funds 126 new and 1,100 existing CHCs • ACA: over $11 billion • By 2015, CHCs should serve 40 million Americans
What Is Known about CHCs? • Medical and Health Services Literature • Increase access (Hadley and Cunningham ‘04, LoSasso and Byck ‘10) • Reduce ER visits (Hochheiser, Woodward and Charney ‘71, Gold and Rosenberg ‘74) • Reduce preventable hospital admissions (Epstein ‘01, Falik et al. ‘01) • Reduce health disparities (Politzer et al. ‘01, Regan et al. ‘03, Shin, Jones and Rosenbaum ‘03, O’Malley et al. ‘05) • Improve infant health (Chabot ‘71, Goldman and Grossman ‘88) • Limitations • Dated methods: Cross-sectional, interrupted timeseries, or case-control methods • Substance: Almost all about health service use • Little data: no database on where, when, who for a longer-period
This Paper Question: How have CHCs affected health? • Empirical strategy: • Roll-out of the first CHC programs from 1965 to 1974 “It was an era that attracted some of the brightest social thinkers in the country but not those with the most well-organized minds. It was an era of great administrative confusion.” ~Robert A. Levine (1970) • Focus on older adult mortality (ages 50 and older) • Accounts for an important and rising share of U.S. health care costs • Mortality is sensitive to the availability of medical care • Comprise >80% of deaths in the U.S from 1960 to 1990, mortality well measured in every year at the county level from 1959 to 1988 • Long-term health effects of primary care/drugs • Cumulative impact up to 15 years after CHCs began • Examine CHCs’ cumulative (15-year) effects • Direct Evidence on CHCs’ Health Effects • Mortality of those 50 and older is a novel outcome and allows us to compare the effects of CHCs for those with Medicare (65+) to those without • Mortality is the only county-level health outcome available annually, 1959-1988 • Mortality is well measured and allows large sample sizes (~80-88% of deaths for 50+)
This Paper’s Conclusions • CHCs associated with a 2% reduction in age-adjusted and age-specific county-level mortality rates for those 50+ • Due to reductions in cardiovascular-related causes • No effect on accident related mortality • This is a plausible but large ITT effect for poor, 50+ patients • ATET implies a 6-8 percent reduction in mortality of the poor • ATET is 18-24 percent of the 1966 rich-poor mortality gap • Mechanisms • SHSUE: 20% increase in “regular source of care” and 40% reduction in the likelihood of having any prescription drug expenditures among poor • Low cost (hypertension) drugs may account for 40% of the effect • Medicare awareness may contribute but no evidence of increases in per capita Medicare expenditures in counties after CHCs arrive
Johnson’s War on Poverty • Johnson declared an “unconditional war on poverty” in his first State of the Union address (Jan. 1964) • Landslide victory in ‘64 + most liberal Congress since New Deal
1964 Economic Opportunity Act • Administered by the Office of Economic Opportunity (OEO) • Sargent Shriver is “poverty czar” • Almost 1 billion in outlays • Bulk of funds budgeted for VISTA, Head Start, Job Corps • 360 million for Community Action Programs (CAPs)
Poor Health as anImpediment to War on Poverty Goals … We saw hundreds of people whose only hope of obtaining medical care was to become an emergency which could not be turned away. We heard countless stories of driving 50 or 100 miles to a city general hospital after refusal of care at a local hospital …High blood pressure, diabetes, urinary tract infections, anemia, tuberculosis, gall bladder and intestinal disorders, eye and skin diseases were frequent findings among adults ~Dr. Raymond Wheeler, Citizen’s Board of Inquiry into Hunger, 1967-71
CHCs in 116 Counties, 1965-1974 OEO and DHEW funded CHCs in 40 states. Two in Washington: 1. 1969: King County (Community Health Board of Seattle) 2. 1973: Adams County (Columbia Basin Health Association). Columbia Point Mound Bayou, MS
Many are Large Operations • The 1972 Directory of CHCs reports that • CHC in Denver had two centers and 11 satellite centers, 800+ staff, targeted a population of 287k • CHC in Oakland, CA provided 24/7 ambulatory care, employed 52 physicians and served 40k • On average, 32k per county per year
Effects on “Clinic” Use? 1963 and 1970 Survey of Health Services Utilization and Expenditures (SHSUE) surveyed same PSUs Y: Use of a “clinic” as usual source of care X: binary variable for sex, age groups, race, education and area size I: income groups (<100%, 100-299, 300-449, 450 of poverty) D*: 1 if CHC before 1970; Dt: 1 if 1970 Triple difference: Change over time in treated versus untreated PSUs for poorer versus richer respondents.
“Clinic” as Usual Source of Care • Among the poorest households, clinic use increased over 170 % (0.16, s.e. 0.05) in PSUs receiving CHCs • Higher income households (300-449 of poverty) had little increase (0.2 %) in PSUs receiving CHCs
All-Cause Mortality, 1959-1988 1959-88: ~900=28% 1959-88: ~436=30% 1959-88: ~1300=28% 1959-88: ~3755=25%
Why did Mortality Fall? • Largely due to decreases in cardiovascular mortality (diseases of the heart/stroke) • In 1960, CVD accounted for >50% of deaths • By 1988, deaths by diseases of the heart fell by over 40% and strokes by over 60% • Often attributed to introductions of anti-hypertensive drugs and information campaigns • Deaths due to cancer increased
CHCs’ Effects on Mortality? • Reduced cost of primary care and prescription drugs • Increase use of care • Increase compliance with recommended treatments (Medicare/Medicaid did not typically cover drugs) • Increase awareness about Medicaid and Medicare • Diversion of care=changes in quality • Externalities • Information spillovers, contagious diseases • Reductions in ER crowding • Changes in population “frailty”
County Roll-Out of Community Health Centers, 1965-1974 Varies geographicallyand over time.
Local CHC Grants • Any organization could apply to the OEO • Applications from “various and sundry groups” • ~Theodore Berry, Assistant Director of the OEO • No funding precedent; no guidelines • It was a wild sort of operation in those early days, making the first grants. We didn’t have any guidelines and didn’t have the time really to draft them to start out… • ~Donald Baker, chief counsel for the OEO (Gillette 1996)
Event-Study Framework : county (j) f.e; : urban group-by-year f.e. : year (t) or state-by-year fixed effects X: annual, county-level covariates REIS:cash public assistance (AFDC, SSI, GA) and cash retirement and disability payments OTHER: • 1960 county characteristics interacted with linear trends (proportion of population in urban area, nonwhite, with income under $3k, and the proportion of the county’s land that is rural or on a farm, number of active physicians in a county) OR • county-specific linear time trends
Event-Study Framework Dj1(): Dummies for y years before & after CHC establishment (Tj*) • Year before establishment is omitted: 1(t-Tj* = -1) : Pre-effects • change in average difference in treated county outcomes y years before establishment relative to the untreated counties • visual/statistical evaluation of pre-treatment trends (falsification test) : Post-effects • Change in the average difference in treated county outcomes y years after establishment relative to the untreated counties • describe dynamic, likely non-linear evolution of effects, reflecting set up costs, changes in use, and changes in composition of population
Identifying Assumption • CHC establishment uncorrelated with other determinants of mortality • Threats to internal validity must be correlated with CHC counties and first-grant timing • Threats to internal validity vs. mechanisms
Sensitivity and Notes • Reweight sample of untreated counties • propensity scores balance observables between treated and untreated (DiNardo et al. 1996, Heckman et al. 1998) • trim sample of counties <0.10 and >0.90 (Crump et al. 2009) • Technical notes • Estimated in levels (not logs) • Weighted by relevant 1960 population • Standard errors clustered by county • Sample limited to locations with at least 100 residents over the age of 80 in every year
Point estimates small in magnitude and statistically insignificant Trend break: clear, robust, and negative beginning in the year the CHC was funded All-Cause Age-Adjusted Mortality, 50+
Years 0-4: ~30-40 = 0.8-1.2% Years 5-9: ~60-70 = 1.9-2.2% r r All-Cause Age-Adjusted Mortality, 50+ Phase-in consistent with setting up new facilities, hiring staff, attracting patients, effects accumulating with exposure
How Large is the Effect? • We recover ITT (intention-to-treat effects); not everyone in a county used CHCs • How large was the mortality reduction among the “treated” (ATET)? • Broad treatment definition: All elderly and poor are treated: ~25% • Spill-overs in knowledge, eradication of contagious disease, reductions of crowding in ER • Narrow treatment definition: Only patients in the last five years:~18%
Narrow “Treated” Definition • Users: ~1,358/100k in 1971 SHSUE (National) • Use in treated counties? 25 % of U.S. 50+ population 1357/. 25 = 5428 patients in treated counties • Underreporting? 39 to 50% report accurately As high as 13,928 in treated counties/100,000 • Cumulative use? 75% of individuals who saw a physician visits in previous 5 years saw one in the last year 18,500 in treated counties/100,000 -Freeman et al. (1982) report that ~15% of 40+ use CHCs • ATET: 60/0.0185-323/100k for 50+ patients
Magnitude of Estimates • ATET of CHCs on older adult mortality • Relative to mortality of poor: 6-8 % • Relative to nonpoor/poor mortality gap: 18 -24 % • Relative to ‘60-’80 decline in AMR: 35 % • Relative to Chay et al. 2001’s Medicare effect 66%
All-Cause 50-64 AMR Not just a Medicare effect! Years 5-9: ~15 = 1.5%
All-Cause 65-79 AMR Years 5-9: ~100 = 2.3%
All-Cause 80+ AMR Years 5-9: ~230 = 1.7%
Additional Results Summary • By Cause: driven by cardiovascular causes. • Anti-hypertension meds? • Falsification: No effects on accidents. • Reassuring, since CHC provide primary care • Heterogeneity: largest effects in OEO centers, urban centers, counties with high pre-treatment mortality, counties with many doctors. • These groupings are correlated.
Threats to Internal Validity? • CHC establishment uncorrelated with changes in other determinants of mortality • Threats to internal validity must be concentrated in CHC counties and correspond in timing to establishment dates
Potential Confounders? Other War on Poverty (WoP) grants packaged with CHCs grants
Other WoP Grants Funding probability equals 1 in year of first funding Continued support. P(Subsequent CHC grant) <1 in a given year because of multi-year grants (few clinics closed)
Potential Confounders? Other War on Poverty (WoP) grants packaged with CHCs grants CHC grants allocated based on mortality (cherry-picking).
Potential Confounders? Other War on Poverty (WoP) grants packaged with CHCs grants CHC grants allocated based on mortality (cherry-picking). Local initiatives to expand medical resources for the poor in treated counties that correspond in timing to CHC dates