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Title and credits said:NBER WORKING PAPER SERIES
THE IMPACT OF AN INDIVIDUAL HEALTH INSURANCE MANDATE ON HOSPITAL AND PREVENTIVE CARE:
EVIDENCE FROM MASSACHUSETTS
Jonathan T. Kolstad
Amanda E. Kowalski
(© 2010 by Jonathan T. Kolstad and Amanda E. Kowalski. All rights reserved.)
Working Paper 16012
http://www.nber.org/papers/w16012
NATIONAL BUREAU OF ECONOMIC RESEARCH
1050 Massachusetts Avenue
Cambridge, MA 02138
May 2010
Key findings, in my opinion:Abstract said:In April 2006, the state of Massachusetts passed legislation aimed at achieving near universal health
insurance coverage. A key provision of this legislation, and of the national legislation passed in March
2010, is an individual mandate to obtain health insurance. In this paper, we use hospital data to examine
the impact of this legislation on insurance coverage, utilization patterns, and patient outcomes in Massachusetts.
We use a difference-in-difference strategy that compares outcomes in Massachusetts after the reform
to outcomes in Massachusetts before the reform and to outcomes in other states. We embed this strategy
in an instrumental variable framework to examine the effect of insurance coverage on outcomes. Among
the population discharged from the hospital in Massachusetts, the reform decreased uninsurance by
28% relative to its initial level. Increased coverage affected utilization patterns by decreasing length
of stay and the number of inpatient admissions originating from the emergency room. We also find
evidence that outpatient care reduced hospitalizations for preventable conditions. At the same time
we find no evidence that the cost of hospital care increased. The reform affected nearly all age, gender,
income, and race categories. We identify some populations for which insurance had the greatest direct
impact on outcomes and others for which the impact on outcomes appears to have occurred through
spillovers.
page 5 said:Among the population of hospital discharges in Massachusetts, the reform decreased
uninsurance by 28% relative to its initial level. We see some evidence of crowd of out private
coverage by subsidized coverage for the hospitalized population but we do not find evidence for
crowd out in the general population, suggesting the incidence of crowd out is not uniform. We also
find that the reform affected utilization patterns through decreased length of stay and a decrease
in the number of inpatient admissions originating from the emergency room. Furthermore, we
find evidence of increases in preventive care outside of the hospital setting. Our results indicate
that hospital costs did not increase following the expansion in coverage. We also find evidence for
declines in the intensity of treatment and weaker evidence for declines in prices paid by private
payers. We make several attempts to investigate and address potential selection of healthier or
sicker patients into or out of hospitals after the reform. We do not find evidence of a change in the
composition of the patient pool large enough to affect the robustness of our findings.
page 29 said:From the bottom rows of Table 6, we see that decreases in uninsurance were largest among
individuals aged 19-26. These individuals predominantly obtained coverage through Medicaid and
CommCare. Individuals of all ages obtained CommCare, and CommCares share of coverage is
largest among the near elderly population, aged 55-64. All nonelderly age groups experienced a
statistically significant decline in private coverage, suggesting that other types of coverage crowed
out private coverage within the hospitalized population.25
Seems like pretty good results to me in terms of outcomes--this analysis is not about the pricetag but instead about what it achieved in terms of uninsurance, length of stay, etc.page 30 said:In the second panel of Table 8, we report difference-in-difference results for insurance coverage
by the income quartile of the patients zip code.27 People from the lowest income zip codes are
over-represented in hospital discharges, making up 29% of the sample. People from these poorest
zip codes experienced the largest gains in coverage, mostly driven by increases in Medicaid and
CommCare. People from the richest zip codes were the only group to experience gains in private
coverage, perhaps because means-tested coverage from other sources was not available. The largest
increases in CommCare coverage occurred for patients in the second lowest income quartile, which
seems plausible because Medicaid was aimed at the poor, and CommCare was particularly targeted
at the near poor.