Health Insurance Markets

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Health Insurance Markets
Call for Papers
Innovations in Health Insurance
Chair: Richard Lindrooth, Ph.D.
Sunday, June 6 • 9:30 a.m.-11:00 a.m.
• The Incidence of the Health Care Costs of Obesity
M. Kate Bundorf, Ph.D., M.B.A., M.P.H., Jay Bhattacharya,
M.D., Ph.D.
Presented by: M. Kate Bundorf, Ph.D., M.B.A., M.P.H.,
Assistant Professor, Health Research and Policy, Stanford
University School of Medicine, HRP Redwood Building, Room
257, Stanford, CA 94305-5405; Tel: 650.725.0067; E-mail:
bundorf@stanford.edu
Research Objective: Americans are increasingly either
overweight or obese. Because obese individuals tend to be
sicker and to spend more on health care, this trend suggests
poor future population health and rising health care
expenditures. In a health economy where third parties pay for
most health care expenditures, the insured population at large
pays for these deleterious trends, not just the obese. In the
context of employer provided health care, these increased
payments will take the form of increased health insurance
premiums, and may have unintended consequences ranging
from employers dropping health insurance coverage to
regressive distributional effects. Whether these adverse
consequences arise depends critically upon who pays for
rising health insurance premiums due to obesity—employers
or employees. Our research objective is to examine the
incidence of obesity-related health care costs among
individuals with employer-sponsored health insurance.
Study Design: Using data from the National Longitudinal
Survey of Youth from 1989-1999, we examine differences
between obese and non-obese full-time workers in the
difference in wages between those with and without health
insurance from their employer. We estimate multivariate
models of hourly wages as a function of insurance status and
indicator of obesity and their interaction. We include
individual fixed effects and estimate models with a variety of
control variables including year fixed effects as well as timevarying individual characteristics including marital status,
indicator of rural residence, age, worker industry and
occupation, and employer-size.
Population Studied: Full-time workers aged 18 and over from
1989 to 1998.
Principal Findings: We find a striking increase in obesity rates
among full-time workers in the NLSY sample from 12% to
26% from 1989 to 1998. We find that obese workers in firms
offering health insurance experience a greater wage offset for
health insurance than non-obese workers in firms offering
health insurance. While cash wages for insured workers are
greater than those for uninsured workers for both obese and
non-obese workers, the wage premium for insured workers is
smaller for obese than for non-obese workers. We also find
that the estimate of the incidence of health insurance
premiums on cash wages has increased over time. Our
findings suggest that obese workers pay between $0.09 and
$0.23 per hour more than non-obese workers for health
insurance coverage from an employer in the form of lower
cash wages.
Conclusions: Our results are consistent with the incidence of
at least some of the health care costs associated with obesity
falling on obese workers in the form of lower cash wages.
Implications for Policy, Delivery or Practice: The results of
this project are particularly notable given the difficulty other
researchers have faced in identifying the wage offset and the
lack of evidence of the extent to which wage offsets exists for
individual characteristics. Our results provide additional
support for economic models indicating that employees bear
the cost of employer-sponsored health insurance in the form
of lower wages. They also suggest that individuals obtaining
health insurance in the employer-sponsored market are
increasingly facing risk rating based on their individual health
status.
• Who Uses Individual Health Insurance and for How
Long? An Analysis of the 1996-2000 SIPP
Erika Ziller, M.S., Andrew Coburn, Ph.D., Timothy McBride,
Ph.D., Courtney Andrews, M.A.
Presented by: Andrew Coburn, Ph.D., Professor and Director,
Institute for Health Policy, Muskie School of Public Service,
University of Southern Maine, P.O. Box 9300, Portland, ME
04104-9300; Tel: 207.780.4435; Fax: 207.228.8138; E-mail:
andyc@usm.maine.edu
Research Objective: This study examines patterns of
individual insurance coverage among non-elderly adults in the
United States. Specifically we consider three questions: (1)
Who uses individual insurance? (2) What characteristics
predict how long a person has coverage? And, (3) What
insurance status do people have before and after individual
insurance spells?
Study Design: This study uses the 1996-2000 panel of the
Survey of Income and Program Participation (SIPP), a
nationally representative, longitudinal survey by the Census
Bureau. We use bivariate and multivariate analyses to
determine what characteristics predict individual health
insurance use, including state regulation of individual and
small group markets. We also conduct multivariate survival
analysis to determine what factors affect individual insurance
spell lengths.
Population Studied: Adults aged 18-64.
Principal Findings: Compared to those with employer
coverage, people with individual insurance are more likely to
be part-time workers, not working, self-employed and/or
working for small business. They are also more likely to be
unmarried and Asian or non-Hispanic White. In addition,
living in a state with a high-risk pool is associated with being
individually insured.
The median length for new spells of individual insurance is 8.2
months. Although 47% of spells last for less than six months,
nearly one-fifth last more than two years. Multivariate survival
analysis indicates that spells are at least 20% longer for the
unemployed, self-employed, non-Hispanic Whites or Asians,
or those with employer-based coverage the month before
gaining individual coverage. Being out of the labor force, a
small business employee, unmarried, and female also
increase time with individual coverage, as does living in a
state with guaranteed renewal laws for individual plans.
The number of months with individual insurance is lower for
those in fair/poor health and people who gained individual
insurance after having public coverage. Living in a state with
small group community rating laws is also associated with
shorter spells.
Around two-thirds of individual insurance spells begin when a
person loses employer-based coverage, and the same number
end with a person gaining employer-based coverage. Eightythree percent of those who lose coverage from an employer
regain employer-based insurance. About one-sixth of people
who lose individual insurance become uninsured.
Conclusions: Most new individual insurance spells appear to
bridge periods of employer-based coverage, and these spells
are longer on average than among those who gain individual
insurance after being uninsured. For many, these gaps in
employer-based coverage may arise when people become
unemployed, work part-time, work for a small business and/or
for themselves. However, a large minority of those who lose
individual insurance become uninsured. This, coupled with
the fact that those in poorest health have the shortest
coverage, points to potential failings of the individual
insurance market and warrant further research. State policies,
including high-risk pools, community rating and guaranteed
renewal relate to the likelihood or length of time a person has
individual insurance, although the causal direction remains
unclear.
Implications for Policy, Delivery or Practice: This research
provides crucial information about patterns of individual
health insurance use, and can assist federal and state
policymakers who seek strategies for improving access to
affordable individual insurance coverage.
Primary Funding Source: RWJF
• Prescription Drug Demand for Therapeutic Substitutes:
Do Copayments and Insurer Non-Price Rationing
Influence Patient Utilization?
Dominick Esposito, Ph.D.
Presented by: Dominick Esposito, Ph.D., Researcher,
Mathematica Policy Research, Inc., P.O. Box 2393, Princeton,
NJ 08543; Tel: 609.275.2358; Fax: 609.799.0005; E-mail:
desposito@mathematica-mpr.com
Research Objective: To determine if differential copayments
and type of insurance arrangements affect the demand for
therapeutically equivalent cholesterol-lowering prescription
drugs in the statins class.
Study Design: The statins were chosen due to their
widespread use among patients with cardiovascular disease,
their aggregate U.S. expenditure as a class, and the
expectation of considerably greater utilization in the future.
This study examines drug choice, with a multinomial logit, for
a sample of 44,642 patients who each use only one statin
(monotherapy). The data source is medical and pharmacy
claims from the 1997 and 1998 MarketScan Commercial
Claims and Encounters database, which allows for
simultaneous examination of patient health care utilization,
prescription drug use and patient health status. A variety of
health plans, including preferred provider organizations, point
of service plans, indemnity plans, and health maintenance
organizations, provide healthcare to the individuals
represented in this database. Average copayments vary across
and within insurer type; for example, HMO copayments range
from $11.48 for Lipitor to $8.96 for Lescol. Explanatory
variables used to model drug choice include relative
copayments, insurance type, demographic characteristics
(age, gender, and region), and clinical factors (comorbidities,
utilization of other lipid-modifying drugs, and evidence of or
cardiovascular disease).
Population Studied: Commercial health plan enrollees aged
18-94 representing 33 health plans throughout the United
States.
Principal Findings: An increase in the relative copayment of
the patient’s drug of choice by 10% decreases that drug’s
market share by as much as 2.8%. Patients’ insurance type
also influences drug choice independently from differential
copayments. HMOs shifted patient utilization away from
Lipitor and Mevacor to Zocor, Pravachol and Lescol in this
sample. Compared to utilization among indemnity plans,
Lipitor’s market share is nearly 30% lower in HMOs while use
of Zocor is 20% higher. Results relating to demographic and
health status variables also provide clinically interesting
comparisons across statins.
Conclusions: Results demonstrate that copayments imposed
by insurers do influence drug choice, shifting market share in
health plans among therapeutic alternatives. Consequently,
since copayments are set insurers company rather than
pharmaceutical firms, health plans have a device with which
they can shift demand. Findings also indicate that insurers
affect choice through non-price rationing methods.
Implications for Policy, Delivery or Practice: Results have
implications for bargaining between insurers and drug
manufacturers as well as the implementation of the Medicare
prescription drug benefit. By setting differential copayments
for therapeutically equivalent drugs, insurers can alter market
share by shifting patients towards preferred agents. If drug
firms are willing to lower prices to obtain higher volume,
insurers could use differential copayments as a negotiating
tool. This strategy could also be employed to encourage
utilization of cost-effective alternatives within therapeutic drug
classes. Prescription drug plans (PDPs) who enroll Medicare
beneficiaries could also utilize this approach. The
implementation of pharmacy benefit schemes targeted to
influence drug selection among beneficiaries would give PDPs
substantial bargaining power to command price reductions
and generate cost savings to Medicare.
• The Causal Effect of Managed Care on Quality: Evidence
from Cancer Screening Guideline Discontinuities
Srikanth Kadiyala, B.A., Grant Miller, M.P.P.
Presented by: Srikanth Kadiyala, B.A., Doctoral Student,
Health Policy, Harvard University, NBER / 1050
Massachusetts Avenue, Cambridge, MA 02138; Tel:
617.588.0346; E-mail: kadiyala@fas.harvard.edu
Research Objective: Although voluminous, empirical
research on the impact of managed care on quality has
generally not been conclusive because of difficulties in
disentangling true causal effects from well-known
associations. The principle methodological obstacle is the
sorting of enrollees into plan types according to unobserved
heterogeneity in health status and other patient
characteristics. We circumvent this difficulty and provide
estimates of the causal effect of various forms of managed
care on cancer screening rates. Although only one dimension
of quality of care, preventive screenings are critical in reducing
the incidence of major cancers.
Study Design: Specifically, we employ a difference-indifference design that exploits age discontinuities in the
amount of cancer screening recommended by widelyrecognized national guidelines. This approach eliminates
unobserved patient differences across plan types –
importantly, including ones that change over time – using
within-plan comparisons that exploit discrete increases in
screening rates at recommended age thresholds.
Furthermore, using data on offer and take-up rates, we are
able to disentangle supply-side effects (i.e., being offered a
screening) from demand-side effects (i.e., following a
clinician’s advice to have one).
Population Studied: We analyze nationally-representative
samples of individuals around national screening guideline
thresholds using MEDSTAT's MarketScan Research
Databases (1998-2001) and the 1995-2001 National Health
Interview Surveys. Specific populations studied vary with
cancer screening types. For example, individuals aged 45-54
are used for colorectal cancer screening analyses, for which
the threshold is age 50.
Principal Findings: Preliminary findings suggest that on
average, managed care plans are about 20% more likely to
provide cancer screenings (mammograms, PSA tests, and
fecal occult blood tests) than are traditional indemnity plans.
Results specific to various tools employed by managed care as
well as extensions to health outcomes are presented.
Conclusions: Financial and non-financial incentives appear to
have a direct causal effect on the amount of appropriate
medical services provided. In particular, high-power payment
contracts and more restrictive networks can result in better
quality of care along some dimensions.
Implications for Policy, Delivery or Practice: Qualityimprovement initiatives should be cognizant of evidence that
the traditional tools of managed care can exert influence on
quality.
Primary Funding Source: NIA
• Immigrants and Employer-Provided Health Insurance
Anthony LoSasso, Ph.D., Thomas Buchmueller, Ph.D., Sarah
Senesky, Ph.D.
Presented by: Anthony LoSasso, Ph.D., Research Associate
Professor, Institute for Policy Research, Northwestern
University, 2040 Sheridan Road, Evanston, IL 60208; Tel:
847.467.3167; Fax: 847.467.4040; E-mail: alosasso@northwestern.edu
Research Objective: Immigrants are nearly three times as
likely as native-born Americans to lack health insurance:
31.6% of immigrants were uninsured in 2000 versus 11.8% of
natives. However, while the difference in group health
insurance coverage is striking (66% for natives vs. 48.7% for
immigrants), the difference in Medicaid coverage is less than
one percentage point (10.4% for natives, 9.9% for
immigrants). Thus, in order to understand the lower rates of
health insurance coverage for immigrants and to evaluate
policies designed to improve this situation, it is necessary to
understand the factors that contribute to the low rates of
employer-provided insurance coverage of immigrants. The
goal of our study is to decompose the reasons behind the
striking difference in employer health insurance coverage
between natives and immigrants in the US.
Study Design: Our analyses use data from the 1996 panel of
the Survey of Income and Program Participation (SIPP). The
SIPP is a longitudinal survey in which respondents are
interviewed every four months over a four-year period. A
distinct advantage of the SIPP relative to other more
commonly used data sets such as the Current Population
Survey (CPS) is that it contains detailed measures of the
reasons why respondents are uninsured. For example, unlike
the CPS we know whether uninsured workers and their
families were offered health insurance, whether they eligible
for offered health insurance, and whether they chose not to
take-up offered health insurance. In addition, the SIPP
contains detailed measures of immigrant status, including
year of arrival and country of origin and current citizenship
status. In addition to the typical demographic variables (age,
race, gender, family size, income), information is also
available on work history, tenure with the firm, health status,
and functional limitations. Detailed information on
educational attainment, including information on degrees
received and fields of study, makes it possible to improve
upon the years of schooling variable used in many empirical
studies. We use regression analysis to decompose the
difference in employer-provided health insurance coverage
between natives, naturalized citizens, and non-naturalized
residents.
Population Studied: We use a national random sample of
immigrants and native citizens in the US from 1996 through
2000.
Principal Findings: We find that employed non-naturalized
residents have a baseline 22 percentage point lower level of
being offered health insurance by their employer relative to
natives. Interestingly, naturalized citizens do not have a
statistically significant different rate of being offered health
insurance by their employers. When we control for age,
education, and family characteristics, the baseline difference in
the employer offer rate falls to 11 percentage points, indicating
that those factors explain half of the observed difference in the
employer health insurance offer rate between natives and nonnaturalized residents. When we add additional variables to
control for firm size, tenure with the firm, industry fixed
effects, and state fixed effects, the difference is nearly halved
again to roughly 6.6 percentage points. Differences in the rate
of eligibility and take-up between immigrants and natives are
tiny and do not account for a significant portion of the
employer-provided health insurance coverage gap.
Conclusions: Our results clearly indicate that the primary
reason for lack of employer-provided health insurance
coverage for non-naturalized residents is that they
disproportionately work for firms that do not offer health
insurance. The same is not true for naturalized citizens, who
generally do not differ significantly from natives. Much of the
baseline difference between natives and non-naturalized
residents is accounted for by observable differences in
characteristics and experiences of the individual as well as
characteristics of the firms immigrants work for.
Implications for Policy, Delivery or Practice: Our results
point to the difficulties that policymakers face in crafting
solutions to the employer-provided health insurance gap
between natives and non-naturalized citizens. The employers
in question are small, low-wage firms most likely with high
turnover rates that are unlikely to be able to afford even a
basic health insurance policy, thus policy options must take
care to avoid causing job loss in an effort to increase
insurance coverage.
Primary Funding Source: RWJF
Related Posters
Poster Session B
Tuesday, June 8 • 7:30 a.m.-8:45 a.m.
• Effects of Medicare HMO Penetration on In-Hospital
Mortality and Post-Acute-Care Utilization of Ischemic
Stroke
John Bian, Ph.D., William Dow, Ph.D., Elizabeth Richardson
Vigdor, Ph.D., Morris Weinberger, Ph.D., David Matchar, M.D.
Presented by: John Bian, Ph.D., Assistant Professor,
Department of Medicine, University of Alabama at
Birmingham, MT 640, 1530 3rd Avenue S., Birmingham, AL
35294-4410; Tel: 205.934.7608; Fax: 205.934.7959; E-mail:
jbian@uab.edu
Research Objective: To understand how increased Medicare
HMO penetration affects in-hospital mortality and subsequent
use of skilled nursing facilities (SNF) and home health postacute-care (PAC) at the market level.
Study Design: Using the 1993-98 Nationwide Inpatient
Sample and county-level Medicare HMO enrollment data, we
constructed a hospital panel data set for estimation. We
focused on in-hospital mortality and, for those discharged
alive, use of SNFs and home health. The key independent
variable is Medicare risk HMO penetration. The unit of
analysis is the individual patient. Discrete-time hazard models
were used to estimate the effects of Medicare HMO
penetration on in-hospital morality, and logit models were
used to estimate the effects of Medicare HMO penetration on
utilization of SNFs and home health. Both analyses used
hospital fixed effects to control for HMO selection.
Population Studied: Patients who were hospitalized for
ischemic stroke at age = 65 years old and had no missing
state/county codes were included for the analysis.
Principal Findings: The analytical file had 327,793 patients
during the 6-year period. A total of 27,152 patients (8.3%) died
during hospitalization. The rate of in-hospital mortality
declined from 9.6% in 1993 to 7.3% in 1998. During the same
period, the use of SNF increased from 45.8% in 1993 to 55.2%
in 1998, while the use of home health care decreased slightly.
Medicare HMO penetration grew steadily from 7.5% in 1993
to 18.0% in 1997, but dipped to 12.2% in 1998; Medicare IPA
HMO penetration was 3.0%, 10.9%, and 6.8%, respectively, in
1993, 1997, and 1998. Multivariate analysis showed that
Medicare HMO penetration was not associated with inhospital mortality or SNF utilization, but was negatively
associated with home health utilization (p < .001). Further
analysis suggested that the effects of Medicare IPA and nonIPA HMO penetration on home health utilization differed.
Alternative specifications showed the robustness of the above
results.
Conclusions: After accounting for the censored nature of
mortality data and HMO selection, we found no evidence
suggesting that increased Medicare HMO penetration
affected in-hospital mortality for ischemic stroke. Although no
evidence showed any impact of Medicare HMO penetration
on utilization of SNF, the utilization rate of home health was
negatively associated with Medicare HMO penetration.
Additional evidence on post-stroke outcomes (including longterm follow-up of patients) is needed to fully assess the
impact of Medicare HMO penetration on stroke care.
Implications for Policy, Delivery or Practice: This study
suggests that increased Medicare HMO penetration might not
have adversely affected outcomes of in-hospital care.
Primary Funding Source: AHRQ/NRSA fellowship
• Bias in Estimates of Non-Group Health Insurance
Coverage: Comparison of Surveys and Administrative Data
Joel Cantor, Sc.D., Alan Monheit, Ph.D., Susan Brownlee,
Ph.D.
Presented by: Joel Cantor, Sc.D., Director and Professor,
Center for State Health Policy, Rutgers University, 317 George
Street, Suite 400, New Brunswick, NJ 08901; Tel: 732.932.3105
Ext. 228; Fax: 732.932.0069; E-mail: jcantor@cshp.rutgers.edu
Research Objective: The non-group health insurance is
subject to risk selection and exclusionary insurer practices.
Policy responses to these practices are controversial and
difficult to evaluate. The Current Population Survey (CPS), the
main dataset used to evaluate the non-group market, classifies
respondents as having non-group coverage if they answer that
they were “covered by a plan that (they) PURCHASED
DIRECTLY, that is, not related to current or past employer” in
the prior year. This study examines the adequacy of the CPS
for studies of the non-group market.
Study Design: We compare the number and characteristics of
New Jersey residents with non-group coverage in the CPS to
aggregate state regulatory reports filed by insurers and to
household data from the 2001 NJ Family Health Survey
(NJFHS) (n=6,466; response rate=59.4%). CPS and NJFHS
estimates of the composition of the NJ non-group market are
also compared to a unique survey of known non-group
enrollees sampled from the rosters of insurers representing
over 95% of the market (n=732; response rate=52.0%).
Population Studied: NJ residents with non-group health
insurance.
Principal Findings: CPS estimates of NJ non-group
enrollment are 1.7 to 2.9 times higher than regulatory reports
for 1995 to 2001. Moreover, non-group enrollment in
regulatory reports declined in each of those years by -0.7 to 0.2 percentage points while the CPS shows annual changes of
-2.6 to +1.0 percentage points with no clear trend. Estimates
of the NJ non-group population are 91,449 (Q3 2001 NJ
regulatory reports), 259,096 (2002 CPS), and 218,585 (2001
NJFHS).
The composition of NJ non-group enrollees in the 2002 CPS
and 2001 NJFHS is considerably different than the 2002
known sample. CPS and NJFHS non-group enrollees are
younger (mean age 44.4 & 44.2 years) compared to the
known sample (48.4 years) and more likely to be minority
(23.5% & 27.9% versus 12.8%, respectively), non-US born
(17.0% & 23.2% versus 12.3%), below 200% FPL (20.3% &
29.3% versus 15.3%), and less than college educated (67.5%&
66.0% versus 57.2%). The three surveys provide similar
estimates of health status and utilization (CPS does not ask
utilization).
Conclusions: Population surveys appear to over-estimate
non-group enrollment by two fold or more even after
accounting for differences in survey reference periods. The
CPS measures coverage at any time in the prior year while
regulatory reports and NJFHS estimates reflect a point in
time. Thus, we expect CPS to be higher than point-in-time
sources. However, the point-in-time 2001 NHFHS overstates
non-group enrollment by nearly as much as 2002 CPS
compared to regulatory reports (2.8 times higher and 2.4
times higher, respectively).
Self-reported non-group enrollees in the CPS and NJFHS are
of lower socioeconomic status, younger and more likely
minority and non-US born compared to known non-group
enrollees. The predominance of managed care in Medicaid
may lead some public enrollees to mistakenly report that they
are “direct purchasers”. Also, low education and immigrant
respondents may not understand survey questions or health
coverage complexities.
Implications for Policy, Delivery or Practice: Studies of the
non-group market using the CPS and other population surveys
appear to suffer significant reporting bias.
Primary Funding Source: CWF, The Robert Wood Johnson
Foundation
• TennCare: Cost Saving or Cost Shifting?
William Cecil, M.B.A., Steven Coulter, M.D.
Presented by: William Cecil, M.B.A., Director, Health Policy
Research, Health Care Services, BlueCross BlueShield of
Tennessee, 801 Pine Street, Chattanooga, TN 37402; Tel:
423.763.3372; Fax: 423.755-5100; E-mail: bill_cecil@bcbst.com
Research Objective: The TennCare program is credited with
coverage expansion to the uninsured and uninsurable and
health care cost savings. The objective of our study is to
determine whether professional health care providers, faced
with the cost cuts associated with the TennCare program
implementation and coverage expansion absorbed the cost
cuts or shifted costs to non-Medicaid non-Medicare payment
sources.
Study Design: Our analysis is based on a simple theoretical
model in which non-Medicare non-Medicaid spending on
physician and other professional health care services and total
per capita spending depends on the number of beneficiaries
in the Medicaid/TennCare program. We hypothesize that
physician and other professional health care services providers
who faced decreased revenues due to Medicaid/TennCare
payment reductions would increase revenues from other
health care payment sources, that is, shift costs to the nonMedicare non-Medicaid population. To test our hypothesis,
we conducted an analysis of state health accounts health care
spending for physician and other professional services and
total spending by source of funds. Using this data we estimate
time series regression models of non-Medicare non-Medicaid
spending on physician and other professional services and
total per capita spending by source of funds and service for
each state and the District of Columbia, in addition to
Tennessee for comparison. The independent variables are
trend, TennCare/Medicaid beneficiaries, Medicare enrollment,
and the population not covered by Medicare or
Medicaid/TennCare.
Population Studied: The population reported on in the CMS
national and state health accounts reports for Medicare
enrollment, Medicaid beneficiaries and the total population
from 1980 through 1998 for Tennessee and each state
including the District of Columbia.
Principal Findings: We find that physician and other
professional services and all services cost shifting did occur
with TennCare and with Medicaid programs in 17 other states
during the time period studied. Six states showed evidence of
cost savings associated with the Medicaid program while
twenty-six states and the District of Columbia showed no
significant effect on spending. The largest cost shift for
TennCare occurred in 1995 when 1) the number of TennCare
beneficiaries increased by 56%, 2) TennCare spending for
physician and other professional services increased by 11%, 3)
the non-Medicare non-Medicaid population decreased by
13.5%, 4) non-Medicaid non-Medicare spending for physician
and other professional services spending increased by 17%, 5)
TennCare per capita spending declined by $656, and 6)
allpayer per capita spending for Tennessee rose $229.
Conclusions: Consistent with our expectations the TennCare
program did not show savings for physician and other
professional services and total spending. Instead of cost
savings TennCare created cost shifting to those whose health
care is largely privately funded.
Implications for Policy, Delivery or Practice: The shift of
costs to private funding sources represents an additional and
unexpected cost burden borne by consumers and employers
that would otherwise be funded through tax policy.
Policymakers would play an important role by managing
employer health care cost burdens at levels that would be
nationally and globally competitive.
Primary Funding Source: , BlueCross BlueShield of
Tennessee
• Health Status and the Price Elasticity of Health Plan
Choice
Bryan Dowd, Ph.D., Adam Atherly, Ph.D., Roger Feldman,
Ph.D.
Presented by: Bryan Dowd, Ph.D., Professor, Division of
Health Services Research and Policy, University of Minnesota,
Box 729 MMC, Minneapolis, MN 55455; Tel: 612.6245468; Fax:
612.624.2196; E-mail: dowdx001@tc.umn.edu
Research Objective: The purpose of this paper is to (a)
interpret the theory of price elasticities that vary with the
consumer’s health status, (b) present empirical evidence on
that variation, and (c) explore the policy implications of healthrelated variations in plan-choice price elasticities.
Study Design: We develop a model of information and
preferences that predicts lower price-elasticities for chronically
ill individuals. Data on health plan choices are observed for
samples of employed individuals and Medicare beneficiaries.
Nested logit health plan choice models are estimated and the
out-of-pocket premium elasticity of choice is compared for
individuals who are healthy versus those who are chronically
ill.
Population Studied: Twin Cities employees and a national
sample of Medicare beneficiaries drawn from the Medicare
Current Beneficiary Survey data. Both datasets contain
individuals who are healthy and who have self-reported
chronic illnesses.
Principal Findings: We find a statistically significant, but
numerically small reduction in out-of-pocket premium price
elasiticities for chronically ill employees relative to their healthy
counterparts. The effect is limited to plans offering a broad
choice of providers, rather than prepaid group practice
HMOs. We also find that price elasticities decline with the
length of time the employee has been in the plan. We do not
find an effect among Medicare beneficiaries.
Conclusions: Although we do not find a strong effect of
chronic illness on the price elasticity of health plan choice,
other authors have found evidence of an effect, and thus the
topic should remain open for further research. Specifically, it
would be helpful to have data on charateristics of health plans
that are difficult for consumers to learn about without
enrolling in the plan.
Implications for Policy, Delivery or Practice: If a subset of
consumers with low price elasticity could be identified and
isolated, health plans might be able to enroll, acclimate, and
then charge monopoly premiums to high-risk consumers or
consumers with longer enrollment periods. If health plans
cannot identify and isolate high risk / low elasticity consumers
who prefer their plans, then certain types of benefits or types
of health plans might be subject to "death spirals."
• Realistic Consumerism: Assessing the Prospects for
Consumer Empowerment with Respect to Health Plan
Experiences
Mark Schlesinger, Ph.D., Brian Elbel, M.P.H.
Presented by: Brian Elbel, M.P.H., Doctoral Student, Health
Policy and Administration, Yale University, P.O. Box 208034,
New Haven, CT 06520; Tel: 203.809.0517; Fax: 203.785.6287;
E-mail: brian.elbel@yale.edu
Research Objective: American health policy has increasingly
relied on consumer empowerment to improve the
performance of health plans. Consumers who experience
problems are expected to respond by either switching to a new
plan (exit) or filing a grievance with the plan (formal voice). In
this study, we assess how consumers actually respond to
problems of various sorts. We estimate the potential for
enhancing empowerment by examining the behavior of
consumers who are already well-educated and well-informed
about their options in the health care system.
Study Design: We assess the prevalence of consumer
responses, focusing on problems that have the most severe
consequences for consumers and on those consumers who
attribute their problem, at least in part, to the performance of
their health plan. To simulate the potential for enhanced
consumerism, we identify various subsets of “empowered”
consumers, using various plausible definitions of
empowerment to test the reliability of our findings.
Population Studied: Nationally representative telephone
sample of 5000 individuals with health insurance.
Approximately half of all individuals had a problem with their
health care in the last year, and 67% attribute this problem at
least in part to their health plan.
Principal Findings: Exit and formal voice were utilized by only
18% and 6%, respectively, of individuals who had a problem
with their health care that they blamed, at least in part, on
their health plan. Active consumerism increased for problems
with more severe consequences, but was still reported by less
than half of all respondents. Among individuals who had to
pay at least $1000 in out of pocket expenses, aggrieved
patients filed a grievance only 35% of the time and left their
plan in only 11% of all cases. Among enrollees who reported
having experienced a serious health decline because of the
problem in question, 38% formally complained to the plan
and 17% switched health plans.
Our sub-sample of empowered consumers did not respond
appreciably more often, though there is some variation across
types of problems. We continue to explore alternative
groupings to characterize “empowerment”. Although exit and
formal voice appear to be difficult to establish as reliable
forms of consumerism, health plan enrollees do more
consistently respond to problems in other ways, including
informal contacts with plans and communicating with their
physicians.
Conclusions: Market-oriented policies that rely on
empowered consumers to police the behavior of health plans
have evident limitations. Although the subset of enrollees who
do respond through exit or voice may create an adequate
signal to encourage plans to improve their average
performance, these consumer responses are too inconsistent
to provide reliable protection for individual patients.
Implications for Policy, Delivery or Practice: At all levels of
empowerment, health plan enrollees respond to problems
primarily through informal mechanisms, which are unlikely to
be identified by existing state monitoring programs or
conveyed to the public on report cards measuring plan
performance. There appears to be only limited potential to
increase empowerment by providing enrollees with more
information or educating them about the appropriate ways in
which to respond to problems related to their health care.
• The Effects of State Managed Care Patient Protections on
Physicians' Attitudes
Frank Sloan, Ph.D., Mark Hall, J.D., John Rattliff, Ph.D., Mark
Hall, J.D.
Presented by: Mark Hall, J.D., Professor of Law and Public
Health, Department of Public Health Sciences, Wake Forest
University Medical School, 2000 W. 1st Street, WinstonSalem, NC 27157-1063; Tel: 336.716.9807; Fax: 336.716.7554; Email: mhall@wfubmc.edu
Research Objective: During the 1990s, as part of the
backlash against managed care organizations (MCOs), 47
states adopted laws protecting against some of the perceived
abuses of MCOs. These laws included: external review of
coverage denials; subjecting MCOs to tort liability; requiring
direct patient access to specialists without obtaining a
gatekeeper’s approval; requiring payment for emergency room
visits under a prudent layperson’s standard of necessity; and
restricting use of financial incentives. In most states, this
legislation was spearheaded by medical societies and other
groups representing providers. This study assesses whether
these laws improved physicians’ views about the conditions of
their medical practice.
Study Design: Data came from 3 waves of the Community
Tracking Study physician surveys, conducted between 19962001, with about 15,000 respondents nationally. Most
physicians participated in more than 1 wave. The attitude
measures included physician reports of career satisfaction,
clinical freedom, the quality of care the physician is able to
provide, ease of referrals, and the degree to which profiling
affects compensation. Each physician’s change in these
views between survey rounds was modeled as dependent on
whether the state had enacted a set of managed care patient
protection laws (or a “patients’ bill of rights”), either prior to
or during the respective time intervals between survey rounds.
We estimated separate regressions for primary care providers
(PCPs) and specialists.
Principal Findings: Between 1996-7 and 1998-9, specialists,
but not PCPs, perceived improvements in states with a set of
patient protection laws. It did not matter whether the laws had
been implemented prior to or during this time interval.
However, in the analysis of 1998-9 to 2000-1 changes, neither
PCPs nor specialists perceived improvements in states that
enacted or retained patient protection laws in those years.
Conclusions: Overall, this analysis suggests that these laws
improved specialist physicians’ views of their medical
practices when relatively few states had enacted the laws.
However, after many states had done so, this effect
disappeared, both for states with newly enacted and
continuing laws. Qualitative interviews reported elsewhere
from a different part of this study suggest that there was a
tipping point after which the MCOs changed their practices in
all states in which they operated rather than differentiate
according to the particular regulatory environments. Thus,
although there were improvements overall in physicians’
attitudes between 1998-9 and 2000-1, these improvements
were not more likely in states with patient protection laws.
Also, these laws appear more relevant to specialists than
PCPs.
Implications for Policy, Delivery or Practice: This analysis
does not identify the precise mechanism through which
physicians’ attitudes may have been affected by these laws.
Changes in attitudes may reflect concrete underlying changes
in the behavior of health plans, or physicians’ perceptions may
be improved by knowing that they achieved a desired
legislative victory. The fact that improved attitudes were shortlived in the first group of enacting states suggests the latter
possibility. However, the facts that improvements were seen
only among specialists, and that physicians’ attitudes
continued to improve without regard to these laws, suggest
these laws may have been one of the social forces that
succeeded in changing managed care practices across the
industry.
Primary Funding Source: RWJF
• The Effect of HMO Coverage on the Choice of Outpatient
or Inpatient Surgery
Hsou Mei Hu, Ph.D., Niccie McKay, Ph.D.
Presented by: Hsou Mei Hu, Ph.D., Postdoctoral Fellow,
Institute for Health, Health Care Policy and Aging Research,
Rutgers the State University of New Jersey, 30 College Avenue,
New Brunswick, NJ 08901; Tel: 732.932.6942; Fax: (732) 9326872; E-mail: hhu@ihhcpar.rutgers.edu
Research Objective: To examine the effect of health
maintenance organization (HMO) coverage on the choice of
surgery setting for a surgery that is feasible in either the
inpatient or outpatient setting.
Study Design: We constructed a dataset pooling 1997, 1998,
1999, and 2000 Medical Expenditure Panel Survey (MEPS)
data. Cases included in the final dataset are for privately
insured individuals under age 65 with an ICD-9 procedure
code that was reported in both the 1996 National Hospital
Discharge Survey and the 1996 National Survey of Ambulatory
Surgery. Surgeries that were done in only one of the settings
(inpatient or outpatient) are excluded. The final dataset
contains 1,044 cases (702 outpatient and 342 inpatient). The
dependent variable is whether the surgery was performed
outpatient or inpatient. The independent variable (type of
health plan) has four possible values: HMO, fee-for-service
(FFS), non-HMO with gatekeeper, or multiple plans. The
percentage of cases by type of health plan (HMO, non-HMO
with gatekeeper, FFS, multiple plans) is 46.7%, 7.2%, 35.2%,
and 10.9%, respectively. A logistic regression model was
specified to analyze the effect of HMO coverage on having an
outpatient surgery (vs. inpatient surgery), controlling for
severity, patient characteristics, and payer characteristics.
Population Studied: Privately insured patients under age 65
who had a surgery that is feasible in either inpatient or
outpatient setting
Principal Findings: The percentage of cases with HMO
coverage having an outpatient surgery (69.1%) was similar to
that for those with FFS coverage (70.5%), while 77.3% of cases
covered by a non-HMO with gatekeeper and 65.4% of those
with multiple plan coverage were outpatient. The regression
results showed that HMO coverage did not increase the
likelihood of having an outpatient surgery, holding other
factors constant. However, the interaction between HMO
status and facility payment had a significant negative effect on
the likelihood of having an outpatient surgery. Specifically,
when facility payment increased, the likelihood of having an
outpatient surgery dropped more for those with HMO
coverage than for those with FFS coverage. Non-HMO with
gatekeeper and multiple plan coverage did not significantly
affect the likelihood of having an outpatient surgery.
Conclusions: This study found that HMO coverage did not
increase the likelihood of having outpatient surgery relative to
those with FFS coverage. However, HMOs did pay less for
both types of surgery. These results are inconsistent with the
general belief that HMOs control costs by directly controlling
the use of services, at least for inpatient vs. outpatient surgery.
Rather, HMOs seem to have focused more on controlling
payments to providers than on controlling utilization.
Implications for Policy, Delivery or Practice: When
examining how health plans control expenditures, it is
important to distinguish between payment-control approaches
and methods that focus on controlling utilization.
• Decomposing the Changes in the Number of Uninsured
in USA Since 1994
Mahmud Khan, Ph.D.
Presented by: Mahmud Khan, Ph.D., Professor, Health
Systems Management, Tulane University, 1440 Canal Street,
#1900, New Orleans, LA 70112; Tel: 504.584.1979; Fax:
504.584.3783; E-mail: khan@tulane.edu
Research Objective: To decompose the uninsured population
into a number of components or determinants like poverty,
age, gender, race and source of insurance
Study Design: Difference equations were used to decompose
the uninsurance rates to identify the proportion of change
affected by the selected social and economic determinants.
Population Studied: Macro uninsurance data for a number of
years since 1994 have been used.
Principal Findings: The decomposition exercise indicates that
if there were no changes in the insurance coverage rates of
different races from the base year levels, uninsured population
would have increased by 2.3 million over the years 1994-98
and 0.6 million over 1998-99. Employer sponsored insurance
(ESI) was the most important factor explaining the reduction
in the number of uninsured. Even during 1994-98, employer
sponsored insurance would have reduced the size of
uninsured if other insurance programs did not add so many to
the uninsured pool. Prevalence of poverty was not a very
strong factor in explaining the uninsurance rate. The more
important factor was the improvements in the income-classspecific coverage rates.
Conclusions: Changes related to economic growth were
crucial in determining the size of the uninsured population in
the USA since 1994. In order to reduce the variability of
insurance coverage, policy makers need to identify alternative
methods of providing health insurance coverage to the
population so that access to insurance becomes less sensitive
to macroeconomic changes.
Implications for Policy, Delivery or Practice: Uninsurance
rate in a market-oriented health care system will remain at a
relatively high level even with strong performance of the
macro economy. Public sector intervention appears to be the
only feasible way of reducing uninsurance rates significantly in
the longer run.
• Impact of Three-Tier Pharmacy Benefit Design on
Demand for Prescription Medications: Results from Three
Prescription Benefit Plans
Winnie Yi, Pharm.D., BCPS, Pamela Landsman, M.P.H.,
Dr.PH, XiaoFeng Liu, Ph.D., Steven Teutsch, M.D., Marc
Berger, M.D.
Presented by: Pamela Landsman, M.P.H., Dr.PH, Sr.
Manager, Outcomes Research & Management, Merck & Co.,
Inc., PO Box 4, WP39-166, West Point, PA 19486-0004; Tel:
215.652.7492; Fax: 215.652.0860; E-mail:
pamela_landsman@merck.com
Research Objective: This study estimates the price elasticity
of demand for specific therapeutic classes among three
managed care commercial populations undergoing different
two-tier to three-tier pharmacy benefit plan changes for
specific therapeutic classes.
Study Design: Retrospective pharmacy claims database
analysis for consumers enrolled in one of three prescription
benefit plans filling prescriptions for an NSAID, SSRI, ACE-I,
CCB, ARB, HMG-CoA, or triptan.
Population Studied: During the period 1999-2001, three
prescription drug benefit plans managed by a large pharmacy
benefit management organization moved enrollees from a
two- to a three-tier formulary structure. Copayments for
enrollees of Plan 1 increased from $5 for tier 1 and $10 for tier
2 drugs ($5/$10) to $5 for tier 1, $15 for tier 2, and $25 for tier 3
drugs ($5/$15/$25). Plan 2 changed from $10/$20 to
$10/$20/$40 and Plan 3 from $5/$10 to $5/$20/$35. Plans
were geographically dispersed; Plan 1 enrollees resided in the
Northeast, Plan 2 enrollees in the South, and Plan 3 enrollees
in the Southeast. Patients were continuously enrolled for 24
months with 12 months experience pre- and post- benefit
change and have at least 2 prescriptions filled for a drug of
interest 3-months prior to the benefit change. Elasticity of
demand was calculated for each drug class within the
individual plans.
Principal Findings: Elasticity of demand varied by therapeutic
classes and by plans. In general, drugs that are used for
chronic or asymptomatic conditions (e.g. ACEIs, ARBs,
statins, SSRIs) tend to be less elastic than drugs used for
acute symptomatic conditions (e.g. triptans, Cox-2 and
NSAIDs). Elasticity of demand varied also from plan to plan
without consistent patterns For example, Plan 2 enrollees
were more price sensitive (elasticity -0.24) for ARBs compared
to the other two plans (-0.16 and -0.13). Elasticity for Cox-2s (0.50) in Plan 2 was also nearly twice that of Plans 1 and 3 (0.26 for both). Plan 1 enrollees demonstrated a greater
elasticity of demand for SSRIs in contrast to those in Plans 2
and 3 (-0.47 versus -0.20 and -0.31). Neither age nor gender,
appear to explain elasticity differences seen among the plans.
Conclusions: The demand of pharmaceuticals in these
populations was relatively inelastic for medications treating
chronic asymptomatic conditions and somewhat higher for
medications treating acute symptomatic conditions. While
demand decreased with an increase in copayment, the
magnitude of the decrease varied with both drug class and
copayment. Utilization changes across plans may be
explained by other factors not examined such as overall and
baseline drug utilization, total member copayment burden
and other member education and disease management
initiatives in place. More detailed analyses examining the tiers
for specific products may also explain the inconsistent
patterns of elasticity seen across plans.
Implications for Policy, Delivery or Practice: Patients are
sensitive to changes in copayments for prescription
medications. Their sensitivity varies with medical condition
and class of medication. Other factors along with cost may
explain the variation in sensitivity across plans.
Primary Funding Source: Merck & Co., Inc.
• The Health Care Safety Net and Crowd-Out of Private
Health Insurance
Anthony LoSasso, Ph.D., Bruce Meyer, Ph.D.
Presented by: Anthony LoSasso, Ph.D., Research Associate
Professor, Institute for Policy Research, Northwestern
University, 2040 Sheridan Road, Evanston, IL 60208; Tel:
847.467.3167; Fax: 847.467.4040; E-mail: alosasso@northwestern.edu
Research Objective: To examine the impact of the health care
safety net on the health insurance coverage of children.
Study Design: We conduct an individual-level analysis of
children's health insurance coverage using data from the
Current Population Survey for the years 1990-2000 combined
with a long panel of state level data on hospital
uncompensated care and free and reduced price care offered
by Federally Qualified Health Centers (FQHCs). Because
measures of the safety net are likely to be confounded with
insurance coverage, we use an instrumental variables
approach in estimating the impact of the safety net on health
insurance coverage. The instruments for our measures of the
safety net include measures of tax appropriations and state
and local support received by hospitals and FQHCs, state
Disproportionate Share payments, state uncompensated care
pool dollars, and the amount of state budget surplus or
deficit. We also control for Medicaid eligibility of sample
members with standard techniques. By additionally including
state fixed effects we can avoid the bias that can occur in
previous cross-sectional designs because of unobserved
differences across states that result in, for example, high levels
of both uninsurance and safety net dollars. Including state
fixed effects lets us restrict the analysis to the within-state
variation in health insurance coverage and the health care
safety net measures.
Population Studied: A national sample of children aged 14
and under for the years 1990-2000.
Principal Findings: When we omit state fixed effects, we
observe that high levels of hospital uncompensated care are
associated with statistically significantly higher levels of
uninsurance and lower levels of both public insurance and
private insurance. Our results imply that a one standard
deviation increase in hospital uncompensated care per
population (a 46% increase) would be associated with a 3
percentage point increase in the uninsurance rate among
children. However this result, which generally conforms to
prior findings, does not control for unobserved state
heterogeneity. When we include state fixed effects we find no
statistically significant impact of hospital or FQHC
uncompensated care on health insurance coverage.
Conclusions: While there are clear cross-state differences in
insurance coverage and safety net support, it does not appear
that differences in safety net support are causally related to
insurance coverage for children.
Implications for Policy, Delivery or Practice: Our results
suggest that, contrary to previous work, unintended health
insurance coverage consequences associated with the health
care safety net are likely to be minimal.
Primary Funding Source: RWJF
• The Impact of Benefit Buy-Down on Health Services
Utilization
Raymond Phillippi, Ph.D., Phil Johnson, FSA, MAAA, Allen
Naidoo, Ph.D., Natalie Ramey
Presented by: Raymond Phillippi, Ph.D., Sr. Biostatistical
Research Scientist, Health Services Research, BlueCross
BlueShield of TN, 801 Pine Street, 3E, Chattanooga, TN 37402;
Tel: 423.752.8243; Fax: 423.755.5100; E-mail:
raymond_phillippi@bcbst.com
Research Objective: With the rise in health care costs, many
employers have been changing the benefit structure that they
offer their employees in order to reduce their premiums, called
benefit buy-down in the industry. While this clearly shifts
costs to the employee, little is know about the impact of buydown on health care utilization. This research was meant to
answer two questions; 1. Does benefit buy-down affect the
utilization of services by members, and 2. If buy-down does
affect utilization, are there threshold levels of buy-down that
must be reached in order to have an effect?
Study Design: Data were collected on small groups that
renewed their health insurance with BlueCross BlueShield of
Tennessee between July 2001 and June 2002. Utilization data,
consisting of admissions, inpatient days, hospital outpatient
visits, emergency room visits, physician office visits, and
overall utilization, for these groups were collected for the
twelve months prior and twelve months after the groups
renewed. Groups who changed their benefit structure by
increasing coinsurance, deductibles, out of pocket maximums,
emergency room co-pays, outpatient surgery coinsurance, or
office visit co-pay or who changed to a more restrictive
network were classified as changed groups. All others were
classified as no change groups. In addition, a second
independent variable consisting of the sixteen patterns of
change among the first four changes was created. All
utilization measures were examined pre and post renewal to
determine if the benefit buy down had an effect with the no
change groups serving as controls.
Population Studied: Members of commercial small groups,
under 150 employees, insured by BlueCross BlueShield of
Tennessee.
Principal Findings: Among groups that changed benefits,
there was a statistically significant decrease in inpatient days,
ER visits, and office visits while the groups that did not change
benefits either had no change in utilization or showed an
increase in utilization. The pattern analysis revealed that few
patterns reduced utilization across the board and almost all
patterns reduced office visits. Further analysis revealed that
seventy-seven percent of those utilization measures that
showed significant reductions were related to a pattern that
involved an increase in office visit co-pay. The threshold
analysis showed that regardless of how much office visit copay increased, only co-pays of twenty dollars or more reduced
utilization and the greater the increase over twenty dollars, the
greater the reduction.
Conclusions: Changing benefit structure in general has little
impact on utilization, however increasing physician office visit
co-pay not only reduces office visits, but also reduces other
utilization parameters. This makes sense if the physician
drives all other health care utilization.
Implications for Policy, Delivery or Practice: From an
insurer’s perspective, reducing unnecessary utilization, which
will help to control health care costs and insurance premiums,
can be accomplished by increasing the physician office visit
co-pay.
• Health Benefits Offer Rates: Are We Reaching the Wrong
Conclusions Because of Nonresponse?
Jeremy Pickreign, M.S., Jon Gabel, M.S.
Presented by: Jeremy Pickreign, M.S., Statistician, Health
System Studies, HRET, One Empire Drive, Rensselaer, NY
12144; Tel: 518.431.7827; Fax: 518.431.7915; E-mail:
jpickreign@aha.org
Research Objective: To determine if a bias due to
nonresponse exists when estimating the offer rate for health
benefits in firms with fewer than 50 workers
Study Design: We conducted a follow-up survey to the 2003
Employer Health Benefits Survey sponsored by the Kaiser
Family Foundation and Health Research and Educational
Trust. This follow-up survey collected health benefits offering
data from firms with fewer than 50 workers that did not fully
participate in the main survey. We used McNemar’s Test to
verify that the follow-up survey provided comparable results to
the main survey, and t-tests were used to identify bias in offer
rates between responders and nonresponders. We calculated
and applied a simple weighting adjustment to the main survey
data to control for the observed bias in health benefits offer
rates and compared the results.
Population Studied: Private and public firms with at least
three workers and as many as 49 workers throughout the
United States.
Principal Findings: Firms with 50 or fewer workers not
responding to the main survey were significantly less likely to
offer health benefits. Combining the responses from the two
surveys, we find that the unweighted offer rate is being
overstated by 4.6 percentage points, a rate that exceeds a
common rule of thumb for determining nonresponse bias.
After adjusting the weights to control for this bias, we find that
the weighted offer rate for firms with fewer than 50 workers
drops from 66.7 percent to 63.4 percent.
Conclusions: A positive bias exists in the offer rates of firms
with 50 or fewer workers, most likely due to nonresponse by
firms that do not offer health benefits. An adjustment to the
sampling weights to reflect this bias resulted in a reduction of
the offer rate by over three percentage points in firms with
fewer than 50 workers.
Implications for Policy, Delivery or Practice: These findings
send a proceed with caution warning to analysts studying offer
rates. Because the offer rate appears inversely correlated with
the survey response rate, analysts need to account for
differences in survey response rates when analyzing and
reporting on health benefits offer rates.
• Quality and Utilization in Managed Care: Is More Care
Better?
Sarah Scholle, M.P.H., Dr.PH, Russell Mardon, Ph.D., Gregory
Pawlson, M.D., M.P.H., FACP
Presented by: Sarah Scholle, M.P.H., Dr.PH, Assistant Vice
President, Research & Analysis, National Committee for
Quality Assurance, 2000 L Street, N.W., Suite 500,
Washington, DC 20036; Tel: 202.955.1726; Fax: 202.955.3599;
E-mail: scholle@ncqa.org
Research Objective: Previous studies of Medicare data show
that large regional and local differences in health care
spending are unrelated to access to care, quality of care,
health outcomes and satisfaction. As health care spending
rises, it is unclear whether the purchasers and consumers of
care are getting value for their health care dollar. The purpose
of this study was to examine correlations of commercial health
plan performance on HEDIS effectiveness of care with access
to care, outpatient use, and hospital use, as a proxy for cost.
Study Design: Health care utilization and quality measures
reported by 316 commercial managed care plans in the 2003
HEDIS data were analyzed. Plans report on a standardized set
of performance measures using detailed specifications. To be
considered in the HEDIS data set, an independent audit of
data collection procedures is required. This study used data
from all reporting plans (including unaccredited plans that do
not allow public reporting of their data). Utilization measures
include Access to care (the proportion of adults with at least
one primary care or preventive visit) and the rate of outpatient
visits. As a proxy for potentially avoidable hospitalization, the
rate of hospitalization (excluding surgical and obstetric care)
examined. Quality measures include all the measures
available in the HEDIS Effectiveness of Care domain, such as
the diabetes measurement set, anti-depressant medication
management, follow-up after hospitalization for mental
illness, use appropriate medication for people with asthma,
breast cancer screening, cervical cancer screening, cholesterol
management after acute cardiovascular event, beta blocker
treatment after a heart attack, controlling high blood pressure,
Chlamydia screening, childhood immunizations and
adolescent immunizations.
Population Studied: Three hundred sixteen plans
representing 63% of MCOs in the US and representing 87% of
individuals enrolled in commercial MCOs. Average number of
enrollees per plan is 211,635. The commercial enrollee
population is 52% female and less than 2% are ages 65 years
or older. Plan product types include HMOs (36%),
HMO/POS combined (61%), and POS (3%).
Principal Findings: Rates of medical hospitalizations and
outpatient visits vary by more than six-fold between the
highest and lowest utilization plans. For example, the average
annual number of medical Hospitalizations among adults age
45-64 ranged from 11.5 to 76.5 per 1000 members, with a
mean of 48.4. Access to care (defined as at least one primary
or preventive care visit) was not as variable, with a mean of
94.2 and range of 67.7 to 98.4 for this age group.
Higher rates of access to primary and preventive visits were
associated with higher performance on HEDIS measures. For
example, access to care for adults age 45-64 was correlated
0.31 with the plan’s average performance on diabetes control,
0.31 with acute phase depression management, 0.39 with
appropriate asthma medication use, 0.45 with breast cancer
screening, and 0.30 with childhood immunizations. In
contrast, higher rates of hospital care were associated with
lower quality performance with performance on HEDIS quality
of care measures: -0.27 for Diabetes control, -0.32 for acute
phase anti-depressant medication management, -0.11 for
appropriate asthma medication use, -0.22 for breast cancer
screening, and -0.11 with childhood immunizations.
Quality was only slightly, if any amount, correlated with
outpatient visit utilization rates:0.00 for diabetes HbA1c
control, 0.09 for acute phase depression management, 0.03
for asthma medication, 0.04 for breast cancer screening, and
0.00 with childhood immunizations.
Conclusions: High quality health plans may reduce
hospitalization care, while increasing access to primary care
services. Some plans may achieve high quality more efficiently
than others, given the lack of correlation between quality and
utilization. Further research should examine whether potential
differences in patient populations, health plan characteristics
and provider supply factors account for these correlations.
Implications for Policy, Delivery or Practice: With health
care costs rising and placing greater burdens on purchasers
and consumers, there is a critical need to learn more about
ways to identify and reward efficient provision of high quality
care. Initiatives to identify health plans that achieve higher
performance while minimizing costs are needed.
• Favorable HMO Selection among Medicare Enrolled
Veterans
Min-Woong Sohn, Ph.D., Denise Hynes, Ph.D., R.N., Kristin
Koelling, M.P.H., Linda Kok, M.S., Noreen Arnold, M.S.
Presented by: Min-Woong Sohn, Ph.D., Associate Director,
VA Information Resource Center, Edward Hines Jr. VA
Hospital, 5th Avenue and Roosevelt Road, Building 1, Room
C303, Hines, IL 60141; Tel: 708.202.2413; Fax: 708. 202.2415;
E-mail: sohn@research.hines.med.va.gov
Research Objective: To investigate whether there has been
favorable HMO selection among Medicare enrolled veterans
aged 65 years old or older. Favorable HMO selection refers to
the phenomenon that healthier individuals selectively join
managed care programs more than those with poorer health.
Study Design: We used the VA-Medicare linked data to
identify veterans who newly enrolled in Medicare+Choice in
2000. For risk adjustment, we used the Hierarchical
Condition Categories (HCC) risk adjustment model, which will
be used by the Centers for Medicare and Medicaid Services
(CMS) to risk adjust Medicare reimbursements in 2004. We
combined the VA administrative databases and the Medicare
claims files for 1999 to compute the “concurrent” HCC risk
scores for patients. Hierarchies in HCC are designed to allow
for coding variations due to different financial incentives
under the VA and Medicare systems. Four risk groups were
defined based on the quartile values on the risk scores.
Multiple logistic regression was used to model the odds of a
veteran joining Medicare+Choice in 2000, controlling for
individual, access, and market characteristics.
Population Studied: Our sample consisted of veterans who
were 65 years old or older on January 1, 1999 and were
Medicare enrolled but did not participate in Medicare+Choice
in any month in 1999.
Principal Findings: There were 1.65 million Medicare enrolled
veterans who did not participate in Medicare+Choice in 1999;
about 16,000 (0.1%) newly enrolled in this program in 2000.
Bivariate analysis shows that only 0.78% in the highest risk
group joined the program, compared with 1.27% in the lowest
risk group (p<0.0001). Adjusted for individual, access, and
market characteristics, veterans in the highest risk group were
about 35% less likely to join the program than those in the
lowest risk group (Odds Ratio = 0.65, p < 0.001). Additionally,
we found that blacks (OR = 1.29, p < 0.001) and veterans with
low incomes (OR = 1.27, p < 0.001) were more likely to join,
while older veterans (OR = 0.54, p <0.001 for veterans 85 and
older, compared to veterans 65-74) were less likely to join
Medicare+Choice.
Conclusions: Like the general elderly population in the United
States, healthier veterans joined Medicare+Chioice more
frequently than veterans with poor health, indicating favorable
HMO selection among veterans. Unlike previous studies that
relied on self-reported health status, we used the HCC risk
scores as an objective measure of health status for veterans.
Implications for Policy, Delivery or Practice: The proposed
VA+Choice Medicare plan for Medicare eligible veterans needs
to carefully consider how favorable HMO selection may affect
this program.
Primary Funding Source: VA
percutaneous transluminal coronary angioplasty (PTCA) in a
managed care environment. Both competition and volume are
known to affect quality of care independently, but their
combined effect on mortality has not been studied in detail.
Study Design: In-hospital mortality of patients who received
coronary angioplasty were used as the main outcome
measure. Patient, hospital and environmental characteristics
were included as covariates in multivariate logistic regression
models. The APR-DRG severity index was used to adjust for
patient severity.
Population Studied: A cross-sectional sample of 37,206
patients who received coronary angioplasty at 116 hospitals in
California in 1995.
Principal Findings: Competition was negatively and
significantly associated with adjusted mortality in hospitals
with 350 or less procedures a year. A 10% increase in
competition was associated with a 12% decrease in mortality
at a volume of 50 (Odds Ratio [OR] = 0.881; 95% Confidence
Interval [CI], 0.850 – 0.978; P < 0.000) and with a 5.7%
decrease at a volume of 350 (OR = 0.943; 95% CD, 0.896 –
0.993; P = 0.026). Competition was associated with increased
mortality at 650 or more procedures. Hospitals with higher
volume had lower mortality when under low to moderate
competition. An increase in volume by 10 procedures was
associated with a decrease in mortality of 1.8% for hospitals
under no competition (OR = 0.982; 95% CI, 0.972 – 0.992; P
< 0.000) and of 0.7% for hospitals under moderate
competition (OR = 0.993; 95% CI, 0.988 – 0.998; P = 0.004).
For hospitals under intense competition, an increase in
volume did not affect mortality.
Conclusions: The effect of volume was not constant across
different levels of competition. For hospitals that operated
under intense competition, increasing volume did not
improve quality of care for patients who received coronary
angioplasty. This suggests that price competition among high
volume hospitals to obtain contracts may have resulted in
increased pressures to reduce cost and the resulting cost
constraint might have increased the likelihood among
hospitals under intense competition to engage in qualityskimping behavior.
Implications for Policy, Delivery or Practice: Regionalization
of specialized clinical services may not necessarily improve
outcomes if it involves concentrating volume in hospitals
under intense competition. Recent proposal to regionalize
services in metropolitan areas may need to be reconsidered,
because hospitals in metropolitan areas are likely to have
higher volume and be under stronger competition than those
in the fringes or in rural areas.
Primary Funding Source: VA
• The Association between Competition, Volume and
Mortality among Patients Receiving Coronary Angioplasty
Min-Woong Sohn, Ph.D., Paul Rathouz, Ph.D., Larry
Manheim, Ph.D., Neeraj Jolly, M.D.
• Utilization and Outcomes of Chiropractic Care for WorkRelated LBP: Impact of Workers' Compensation
Reimbursement Policies
Radoslaw Wasiak, Ph.D., Eileen McNeely, Ph.D., Sandra
Magnetti, Ph.D.
Presented by: Min-Woong Sohn, Ph.D., Associate Director,
VA Information Resource Center, Edward Hines Jr. VA
Hospital, 5th Avenue and Roosevelt Road, Building 1, Room
C303, Hines, IL 60141; Tel: 708.202.2413; Fax: 708.202.2415; Email: sohn@research.hines.med.va.gov
Research Objective: To examine the association between
competition, volume, and mortality for patients who received
Presented by: Radoslaw Wasiak, Ph.D., Researcher, Center for
Disability Research, Liberty Mutual, 71 Frankland Road,
Hopkinton, MA 01748; Tel: 508.497.0242; Fax: 508.435.8136; Email: radoslaw.wasiak@libertymutual.com
Research Objective: In workers’ compensation (WC),
utilization and pricing of chiropractic care for work-related low
back pain (LBP) is subject to several cost containment
measures (reimbursement limits, provider choice/change,
utilization/bill review, visit limits). We examined the impact of
state reimbursement policies (fee schedules and payment
policy) on the utilization and cost of chiropractic care for
occupational non-specific LBP to answer the following
questions:
1. Do WC reimbursement policies effectively control costs
associated with chiropractic care for occupational LBP?
2. Is high/low reimbursement for chiropractic care associated
with high/low utilization?
Study Design: A cross-sectional analysis of claims from a
large WC insurer (10% of US market) for service years 19992001 in seven states. For most frequently utilized CPT codes,
fee schedule and actual reimbursement levels were
benchmarked against the Medicare fee schedules for
chiropractic treatments. WC and actual reimbursement
indices were developed using weighted averages to proxy state
payment policies and classify states as high or low
reimbursers. Utilization and outcomes measures included:
chiropractic visits and services per individual, services per
chiropractic visit, cost of chiropractic care per visit and per
individual.
Population Studied: Individuals with a work-related nonspecific LBP reported to the insurer in one of seven states (FL,
ID, IL, MD, NH, NY, PA) and at least one visit to a
chiropractor during the 1999-2001 period (N-99=4732, N00=4898, N-01=5524).
Principal Findings: States vary in their relative
reimbursement levels for chiropractic services provided to
individuals with work-related LBP (low reimbursers: FL, MD,
NY; high: ID, IL, NH, PA; range 0.52-2.36 with the value of
1.00 denoting average weighted reimbursement at the
Medicare fee schedule level). Similarly, utilization and
outcomes measures show substantial variation across the
states. Median visits per individual ranged from 5 to 14,
services per individual from 11 to 25, services per visit from 1
to 3, chiropractic costs per visit from $28 to $69, and
chiropractic costs per individual from $290 to $655. None of
the utilization measures correlated with the relative level of
reimbursement for chiropractic services. Low reimbursement
states had lower costs per visit (F-value 15.72, p=0.01) but
such relationship was not observed for costs per individual.
Conclusions: Payment policies seem to effectively control
chiropractic costs per visit. Such association does not carry
through to chiropractic costs per individual, as chiropractors
adjust their utilization in low reimbursement states. The
utilization adjustment varies by state; chiropractors increase
either the number of visits per individual (NY) or the number
of services per visit (FL and MD). Given other state WC
policies, which are targeted more directly at utilization, high or
low reimbursement does not correlate with any of utilization
measures.
Implications for Policy, Delivery or Practice: Restrictive
reimbursement policy aimed at curbing chiropractic costs and
utilization is not able to reduce both costs and utilization.
Providers adjust to introduced price limitations to preserve the
overall level of revenue per individual. Other WC measures
may be better suited to target utilization levels in conjunction
with payment policies and fee schedules. More research is
required to understand the joint impact of various cost
containment measures on utilization and outcomes of
chiropractic care in WC.
• Index of Treatment Variation: A Qualitative Approach to
Measuring Practice Patterns in the Treatment of Asthma
William Westerfield, M.A., Allen Naidoo, Ph.D. CHES, Ken
Patric, M.D., Judy Slagle, R.N., M.P.A.
Presented by: William Westerfield, M.A., Senior Research
Analyst, Health Services Research, BlueCross BlueShield of
Tennessee, 801 Pine Street, 3E, Chattanooga, TN 37402; Tel:
423.755.6260; E-mail: William_Westerfield@BCBST.com
Research Objective: The primary objective of this study was
to measure the relative variation in the courses of treatment
selected by a provider or specialty to treat asthma without
comorbidity. The secondary objective of this study was to
determine the most common course of treatment used by a
provider or specialty to treat asthma without comorbidity.
Study Design: Treatment variation was measured using the
Index of Qualitative Variation. Called the Index of Treatment
Variation (ITV) for the purposes of this study, the ITV is an
appropriate measure for determining the relative number of
differences in a given set of items. ITV scores range from
0.00 to 1.00. An ITV score of 0.00 indicates no treatment
variation, while an ITV score of 1.00 indicates maximum
treatment variation. To measure the variation in distinct
courses of treatment, data based on an “episode of care”
model and extracted from a commercial Preferred Provider
Organization were used. The data covered episodes of care
from June 2002 – May 2003. Episodes from the Episode
Treatment Group 389 “Asthma without Comorbity” were
chosen to test the variation in asthma treatments. Berenson
& Eggers Type of Service Codes were used to identify medical
treatments. Therapeutic Class Codes were used to identify
drug therapies.
Population Studied: 2,923 episodes of asthma without
comorbidity were studied. The episodes were treated by a
variety of specialties including Internal Medicine, Family
Practice, Pediatric Medicine, Nurse Practitioner, Pulmonary
Disease, Emergency Medicine, and Allergy & Immunology.
Principal Findings: ITV scores for individual providers ranged
from 0.84 to 1.00. The most common ITV score was 1.00.
The provider with the lowest treatment variation was an
Allergy & Immunologist. This particular provider treated 5
episodes of asthma and used 3 different courses of treatment.
The provider’s most common course of treatment included an
office visit, a respiratory flow volume loop, an adrenergic
agent, a sympathomimetic agent, and other unclassified drug
therapies. The specialty with the lowest treatment variation
was also Allergy & Immunology. This specialty treated 144
episodes of asthma and used 106 different courses of
treatment. This specialties’ most common course of
treatment included an office visit, a respiratory volume flow
loop, an adrenergic agent, and a sympathomimetic agent.
Conclusions: The variation in treatment courses used by the
providers and specialists to treat asthma appears clinically
significant. The most common approach to the treatment of
asthma was a different course of treatment for each episode.
The Index of Treatment Variation is a useful measure for
comparing the amount of variation in courses of treatment
selected by providers and/or specialties to treat a particular
illness.
Implications for Policy, Delivery or Practice: The Index of
Treatment Variation is a valuable and flexible measure.
Combined with an episode of care model, the Index of
Treatment Variation could be used in practice pattern analysis,
disease profiling, evidence-based medicine, and quality
measures
Primary Funding Source: BlueCross and BlueShield of
Tennessee
• Strategic Lessons for the Advantageous Use of Provider
Incentives in Health Insurance Markets Learned from the
National Evaluation of Seven Rewarding Results Local
Demonstration Projects
Bert White, M.B.A., D.Min., Gary Young, Ph.D., J.D., Matthew
Guldin, M.P.H.
Presented by: Bert White, M.B.A., D.Min., Project Director,
Health Services Department, Boston University School of
Public Health, Talbot Building, 715 Albany Street, Boston, MA
02118-2526; Tel: 617.232.9500 Ext. 4380; Fax: 617.232.6140; Email: bertw@bu.edu
Research Objective: Programs involving monetary or nonmonetary rewards to clinicians who achieve certain quality
goals are becoming increasingly popular as a mechanism for
improving health care and controlling costs. This research
evaluates seven demonstration sites that are measuring the
results of offering financial incentives to providers. The
objective of this research is to make a strategic contribution to
those who need to calculate the impact and value of incentives
on providers.
Study Design: Multiple data collection approaches are being
used including telephone interviews, written surveys, and site
visits in accordance with a conceptual frame work that
includes seven domains: awareness, scope of control,
financial salience, scientific and clinical credibility, fairness,
readiness for change and unintended consequences. Practice
executives with responsibility for physician contracts in the
health insurance market have been identified in each of the
seven local demonstration projects. These practice executives
provide demographic information and access to physicians
exposed to a demonstration’s incentive plan. There will be
standard data collection across all demonstrations measuring
how incentives influence provider behavior. During the fouryear project, practice executives will be interviewed three times
and physicians will be surveyed twice.
Population Studied: A scientific sample from contracting
entities in each demonstration has been used to identify and
study practice executives and physicians.
Principal Findings: Findings to date include major
differences among the demonstration sites’ structure and
implementation of incentives including: magnitude;
distribution; fee-for-service versus capitation payment
methodologies; and the communication features of incentives.
Preliminary data collection indicates that physicians are very
sensitive to any perceived association between the practice of
medicine and the pursuit of incentives. In addition, the
gateway role of the practice executive may be central to
understanding the total value of any incentives for quality
targets offered to providers.
Conclusions: This research will identify and report the
overarching lessons learned about incentives from across the
seven local demonstration projects. Evidence based insights
will document the strategic domains and requirements for
incentives as a mechanism for improving health care and
controlling costs.
Implications for Policy, Delivery or Practice: The study will
provide comparative business-case information to CMS and
health insurance markets required for a more robust
understanding of incentives and their application. These
findings should be strategic for additional research and
demonstration projects on incentives in the health insurance
markets.
Primary Funding Source: AHRQ, The Robert Wood Johnson
Foundation
Invited Papers
Trends & Innovations in Insurance Design: Implications
for Cost, Access & Quality
Chair: Jon Christianson, Ph.D.
Monday, June 7 • 4:00 p.m.-5:30 p.m.
•
Panelists: Richard Kronick, University of California, San
Diego; Stephen Parente, University of Minnesota; Greg
Scandlen, Galen Institute; Humphrey Taylor, Harris
Interactive (no abstracts provided)
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