Erickson LC, Torchiana DF, Schneider EC, Newburger JW, Hannan EL. The Relationship Between Managed Care Insurance and Use of Lower-Mortality Hospitals for CABG Surgery. JAMA. 2000;283(15):1976-1982. doi:10.1001/jama.283.15.1976
Author Affiliations: Department of Cardiology, Children's Hospital (Drs Erickson and Newburger), Departments of Pediatrics (Drs Erickson and Newburger) and Surgery (Dr Torchiana), Harvard Medical School, Division of Cardiovascular Surgery, Massachusetts General Hospital (Dr Torchiana), Department of Health Policy and Management, Harvard School of Public Health (Dr Schneider), and Division of General Medicine, Brigham and Women's Hospital (Dr Schneider), Boston, Mass; and the Department of Health Policy, Management and Behavior, State University of New York at Albany (Dr Hannan).
Context Explicit information about the quality of coronary artery bypass graft
(CABG) surgery has been available for nearly a decade in New York State; however,
the extent to which managed care insurance plans direct enrollees to the lowest-mortality
CABG surgery hospitals remains unknown.
Objective To compare the proportion of patients with managed care insurance and
fee-for-service (FFS) insurance who undergo CABG surgery at lower-mortality
Design A retrospective cohort study of CABG surgery discharges from 1993 to
1996, using New York Department of Health databases and multivariate analysis
to estimate the use of lower-mortality hospitals by patients with different
types of health insurance.
Setting Cardiac surgical centers in New York, of which 14 were classified as
lower-mortality hospitals (mean rate, 2.1%) and 17 were classified as higher-mortality
hospitals (mean rate, 3.2%).
Patients A total of 58,902 adults older than 17 years who were hospitalized for
CABG surgery. Patients were excluded if their CABG surgery was combined with
any valve procedure or left ventricular aneurysm resection or if they were
younger than 65 years and enrolled in Medicare FFS or Medicare managed care.
Main Outcome Measure Probability of a patient receiving CABG surgery at a lower-mortality
Results Compared with patients with private FFS insurance (n=18,905), patients
with private managed care insurance (n=7169) and Medicare managed care insurance
(n=880) were less likely to receive CABG surgery at a lower-mortality hospital
(relative risk [RR] of surgery at a lower-mortality hospital compared with
patients with private FFS insurance, 0.77; 95% confidence interval [CI], 0.74-0.81; P<.001; and RR, 0.61; 95% CI, 0.54-0.70; P<.001, respectively, after controlling for multiple potential confounding
factors). Patients with Medicare FFS insurance used lower-mortality hospitals
at rates more similar to those with private FFS insurance (n=31,948; RR, 0.95;
95% CI, 0.91-0.98; P=.004).
Conclusions Patients in New York State with private managed care and Medicare managed
care insurance were significantly less likely to use lower-mortality hospitals
for CABG surgery compared with patients with private FFS insurance.
Managed care health plans offer a package of health care benefits to
their enrollees on a prepaid basis, assuming financial risk for the covered
services. Plans manage this risk in many ways. For instance, they may selectively
contract with a restricted set of clinicians and hospitals. For acute care,
prices and other contract terms are negotiated in advance, and health plans
may require patients to use hospitals under contract with the plan or to pay
more if they choose a hospital outside the health plan network.
Financial risk provides a strong incentive for health plans to select
low-priced hospitals. However, health plans should also consider quality of
care when contracting with hospitals, especially if explicit data on quality
are available. Health plans that ignore publicly available quality data are
at risk of adverse publicity about their contracting decisions. A recent study
by Escarce et al1 found that managed care patients
in California were more likely than insured non–managed care patients
to use hospitals with lower-than-expected mortality rates for coronary artery
bypass graft (CABG) surgery, but they found no difference between these 2
types of patient groups in Florida. Data on CABG surgery mortality were not
publicly available in either setting, making it unlikely that health plans
explicitly considered mortality rates in their CABG surgery contracting decisions.
In contrast, New York was the first and one of the few states to provide
information on CABG surgery, including risk-adjusted mortality rates, to the
public,2 allowing health plans, at least in
theory, to explicitly consider quality of care when contracting with hospitals
to provide CABG surgery. To explore the relationship between insurance type
and patterns of hospital use, we compared the probabilities that patients
with managed care insurance and patients with fee-for-service (FFS) insurance
would undergo CABG surgery at lower-mortality hospitals in New York State,
where quality-of-care information is available.
We examined CABG surgery discharges in New York State for the years
1993 through 1996, using records from New York State annual hospital discharge
These legislatively mandated databases included patient age, race, ethnicity,
insurance type, ZIP code, hospital of admission, and International
Classification of Diseases, Ninth Revision, Clinical Modification (ICD-9-CM) diagnosis and procedure codes for all patients
aged 18 years or older who underwent CABG surgery in these years. We selected
New York State residents who underwent CABG surgery (ICD-9-CM codes 36.1, 36.10-36.17) at 1 of 31 CABG surgery hospitals in New
York State and had 1 of the following primary health insurance types: private
FFS, private managed care, Medicare FFS, or Medicare managed care. Single
codes represented each insurance type except private FFS, which included codes
06 (Blue Cross), 08 (commercial insurance company), and 15 (self-insured company).
Private managed care was defined as code 11 (health maintenance organization);
no codes existed for preferred provider organizations or other variations
of private managed insurance. We excluded patients who underwent CABG surgery
combined with any valve procedure or left ventricular aneurysm resection.
Because they represent such a heterogeneous group, patients younger than 65
years who were enrolled in either Medicare FFS or Medicare managed care programs
were also excluded.
Rather than ranking hospitals separately for each year, we ranked hospitals
into lower- and higher-mortality groups based on volume-weighted average adjusted
mortality rates to simplify the analysis and improve interpretability of results.
These rates, published by the New York Department of Health,7- 10
are adjusted for multiple demographic and medical risk factors, including
age, sex (for years 1995-1996 only), body surface area, hemodynamic status,
medical comorbidities, severity of atherosclerotic process, measures of ventricular
function, and history of open-heart surgery.
Based on these averages, we divided hospitals into lower- and higher-mortality
groups using a mortality rate cut point that allocated about half of the patients
to each group. The lower-mortality hospital group included 14 hospitals, constituting
49.8% of the total number of patients, with a mean adjusted mortality rate
of 2.1% (range, 1.2%-2.5%) and a mean annual case volume of 561 (range, 189-1528).
The higher-mortality hospital group included 17 hospitals, with a mean adjusted
mortality rate of 3.2% (range, 2.5%-5.1%) and a mean annual case volume of
466 (range, 63-1019).
This method of ranking hospitals appeared to be fairly stable from year
to year. The published hospital adjusted mortality rates averaged for the
first 2 years of the study correlated highly with those for the last 2 years
(Pearson r=0.53; P=.002).
Rankings derived from these rates correlated significantly as well (Spearman r=0.37; P=.04). Thus, at least
in theory, insurers could use this type of rating to predict hospital mortality
rates in future years.
The outcome of interest was the probability that a patient underwent
a CABG operation at 1 of the lower-mortality hospitals. The independent variable
of interest was insurance type. In addition, models controlled for age, sex,
urgent/emergent admission, and the presence of medical comorbidities, including
diabetes, chronic renal failure, congestive heart failure, systemic hypertension,
and chronic obstructive pulmonary disease. Age was represented as a categorical
variable with 4 values: younger than 55 years, 55 to 64 years, 65 to 75 years,
and older than 75 years. Other independent variables, determined using the
1990 US census,11 were median family income
for the patient's ZIP code of residence and designation of the patient's residential
area as urban. Median family income for ZIP code was represented as a categorical
variable in quartiles.
Because the location of a patient's residence may be correlated with
both insurance status and the choice of hospital,12- 15
our analysis also used 2 factors to account for the impact of distance on
the use of lower-mortality centers. These factors were the distance to the
nearest lower-mortality center and the distance to the nearest higher-mortality
center. Both were based on the distances from the geographic centroids16 of the hospital and patient residential ZIP codes
because street addresses were not included in the available data. Such "straight-line"
methods of estimating geographic accessibility through geographic longitude
and latitude data have been shown to correlate closely with estimated travel
times17 using actual driving routes.14 These distance factors were log-transformed prior
to analysis based on the observation in our data set and in other similar
studies18 that such transformation resulted
in a closer fit to the relationship between distance and use of a lower-mortality
hospital than did actual distance and several other transformations investigated.
We identified univariate predictors of use of lower-mortality centers
using 2 × 2 χ2 tests for categorical variables. In the
case of categorical variables with more than 2 possible values, each value
was compared with a reference value (eg, the youngest age group). The Wilcoxon
rank sum test was used to determine differences among insurance types for
all continuous variables, none of which were normally distributed.
We then used a stepwise logistic regression model to estimate the multivariate-adjusted
odds of use of lower-mortality centers, considering each of the independent
variables listed herein, including the 2 distance factors. Because the rate
of the outcome (proportion of patients in lower-mortality hospitals) exceeded
10%, we transformed odds ratios (ORs) to approximate relative risks (RRs)
according to the method described by Zhang and Yu.19
Two hospitals did not report patient race or ethnicity for the study
period, so these variables were not entered into the models. However, we did
investigate the relationships among insurance type, hospital used, and race/ethnicity
by repeating the analysis separately for patients coded as non-Hispanic white
and those coded as nonwhite or Hispanic. We also performed supplementary analyses
by stratifying patients according to age, urgency of admission, and residence
in New York City and by varying the threshold for inclusion in the lower-mortality
hospital group. In addition, we examined the distribution of patients among
individual hospitals in 4 delimited regions of the state, including Buffalo,
Rochester, Long Island, and New York City.
Among 58,902 adults admitted for CABG surgery between 1993 and 1996,
most patients were male (71%), non-Hispanic white (87%), and Medicare FFS
beneficiaries (54%). Total inpatient mortality was 2.8%. Hypertension (52%)
and diabetes (27%) were the most commonly coded comorbidities. Urgent/emergent
admissions constituted 51% of all cases. Table 1 summarizes the demographic characteristics according to
Unadjusted analyses (Table 2)
revealed that patients with private managed care, Medicare FFS, and Medicare
managed care insurance were less likely than patients with private FFS insurance
to undergo CABG surgery at lower-mortality centers. Other factors associated
with less frequent use of lower-mortality centers included female sex, nonwhite
race/ethnicity, lower median family income for ZIP code, urgent/emergent admission,
diabetes, and chronic renal failure. In contrast, patients with congestive
heart failure, hypertension, and chronic obstructive pulmonary disease were
more likely to use lower-mortality hospitals. On average, patients undergoing
surgery at a lower-mortality hospital lived closer to a lower-mortality center
(15.4 vs 24.6 miles; P<.001) and patients undergoing
surgery at a higher-mortality hospital lived closer to a higher-mortality
center (38.9 vs 13.9 miles; P<.001).
Table 2 also shows coefficients
and 95% confidence intervals (CIs) for categorical covariates in the final
multivariate model. Also included in the final model were the 2 distance variables,
discussed herein. Compared with patients with private FFS insurance, patients
with private managed care insurance were less likely to undergo CABG surgery
at a lower-mortality hospital (RR, 0.77; 95% CI, 0.74-0.81; P<.001), as were patients with Medicare managed care insurance (RR,
0.61; 95% CI, 0.54-0.70; P<.001). After controlling
for other factors, patients with Medicare FFS insurance used lower-mortality
hospitals at a rate similar to those with private FFS insurance (RR, 0.95;
95% CI, 0.91-0.98; P=.004). As in the univariate
analysis, patients who were female, lived in lower ZIP code median family
income groups, were admitted urgently or emergently, or had a code recorded
for either diabetes or chronic renal failure were less likely to be admitted
to a lower-mortality center, although the magnitude of the difference was
small in some cases. In contrast, those older than 75 years and those who
had a code recorded for heart failure, hypertension, or chronic obstructive
pulmonary disease had a greater probability of admission to a lower-mortality
center. Increasing distance from the nearest lower-mortality center reduced
the odds of admission to a lower-mortality hospital (for a 0.1-log increase
in distance, OR, 0.76; 95% CI, 0.76-0.77; P<.001),
but increasing distance to the nearest higher-mortality hospital increased
the odds of admission to a lower-mortality center (for a 0.1-log increase
in distance, OR, 1.45; 95% CI, 1.44-1.46; P<.001).
When we restricted the sample to patients living within 25 miles of
both a lower-mortality and higher-mortality hospital, the results were similar.
Compared with patients with private FFS insurance, patients with private managed
care insurance were less likely to undergo CABG surgery at a lower-mortality
hospital (RR, 0.62; 95% CI, 0.58-0.66; P<.001),
as were patients with Medicare managed care insurance (RR, 0.57; 95% CI, 0.48-0.66; P<.001) and, to a smaller degree, Medicare FFS insurance
(RR, 0.92; 95% CI, 0.88-0.96; P<.001).
Table 3 shows the sensitivity
of these results to changes in the cut point for inclusion in the lower-mortality
group at between 38% and 68%, which was as close as the data would allow to
division at the upper and lower tertiles. Regardless of the threshold, patients
with private managed care or Medicare managed care insurance were significantly
less likely than patients with private FFS insurance to use a lower-mortality
center. Medicare FFS estimates of use were slightly lower than those for private
FFS at all cut points as well.
In subgroups stratified by region (New York City vs upstate New York
and Long Island), admission type (nonurgent vs urgent or emergent), age, and
patient race/ethnicity, patients with private managed care and Medicare managed
care insurance were significantly less likely to use lower-mortality centers
than patients with private FFS insurance (Table 3). Patients with Medicare FFS insurance had rates of use
much closer to those with private FFS insurance, with nonsignificant differences
in several patient subgroups (New York City, nonurgent admissions, and non-Hispanic
When we examined 4 delimited areas (Buffalo, Rochester, New York City,
and Long Island), patients with private managed care and, particularly, Medicare
managed care insurance were virtually excluded from many of the hospitals
in a given area (Table 4). For
example, of 3 hospitals in the Buffalo area, 99% of patients in Medicare managed
care plans were admitted to a single (higher-mortality) hospital that otherwise
accounted for only 59% of that region's caseload. Those admitted to hospitals
in Long Island were restricted to the 3 hospitals with the highest adjusted
mortality rates among 5 hospitals. Medicare managed care patients admitted
to hospitals in New York City were admitted to 8 of 14 hospitals, and 46%
were admitted to a single higher-mortality hospital that otherwise accounted
for only 11% of the region's caseload.
In all, 4 (13%) of 31 hospitals admitted no CABG surgery patients with
private managed care insurance. Fourteen (45%) admitted no patients with Medicare
managed care plans. Restricting the sample to patients admitted to the 17
hospitals that admitted at least 1 patient with Medicare managed care insurance
did not significantly change the results of multivariate analysis. Compared
with patients with private FFS insurance, the corrected odds of being admitted
to a lower-mortality center were still lower for patients with private managed
care (RR, 0.66; 95% CI, 0.62-0.71; P<.001) and
Medicare managed care (RR, 0.64; 95% CI, 0.56-0.73; P<.001)
insurance, but to a lesser extent for Medicare FFS insurance (RR, 0.92; 95%
CI, 0.87-0.97; P=.002).
To investigate the possible role of lag-time effects in these results,
we repeated the analysis examining only patients admitted in the second half
of the study (1995-1996), using public data from the first half of the study
(1993-1994) to designate lower-mortality centers. Compared with patients with
private FFS insurance, those with private managed care insurance were less
likely to use a lower-mortality center (RR, 0.69; 95% CI, 0.65-0.73; P<.001), as were patients with Medicare managed care
(RR, 0.49; 95% CI, 0.40-0.58; P<.001) and Medicare
FFS (RR, 0.75; 95% CI, 0.69-0.80; P<.001) insurance.
Over the period of the present study, patients in New York State with
managed care insurance were significantly less likely to undergo CABG surgery
at a hospital with lower CABG mortality compared with patients with FFS insurance.
This finding remained significant within categories of age, race, urgency,
and region. The findings were not sensitive to the threshold used to define
lower-mortality hospitals, nor did they appear to be a manifestation of a
differential lag time in the recognition of changing hospital outcomes.
Some insight into the mechanisms of these differences in hospital use
patterns can be gained by examining insurance-specific use on a hospital-by-hospital
basis. Patients with managed care insurance and, particularly, managed Medicare
insurance were often excluded from many lower-mortality hospitals entirely,
implicating relatively powerful disincentives, such as use restrictions set
by insurance companies, rather than differences in patient or referring physician
preferences. Such restrictions could include removing a hospital from a plan's
preferred provider list or requiring a significant patient copayment for the
use of that hospital.
How do we reconcile our finding that New York State managed health plans
appeared to ignore risk-adjusted mortality rates in contracting decisions
with the finding that patients in California health plans appeared more likely
to use lower-mortality hospitals?1 The absence
of public data on risk-adjusted mortality in California makes it unlikely
that mortality rates played a significant, if any, role in health plans' decision
making. In a commentary to the study by Escarce et al, Hannan20
suggests that another reason for the difference between California and Florida
may be that, because California has no certificate-of-need system, numerous
low-volume hospitals with high mortality rates perform CABG surgery. Because
low volumes make contracting unattractive, managed care plans in California
avoid sending their patients to the highest-mortality hospitals. This indirect
effect of CABG surgical volume would not be present in New York, where the
certificate-of-need program dictates that all CABG surgery hospitals have
high surgical volumes.
Our study was possible because of the New York Hospital Discharge Datasets
(SPARCS), which are large, independently administered data sets maintained
by the New York Department of Health. Administrative data sets have certain
disadvantages relative to prospectively collected clinical data sets, particularly
with respect to the consistency and precision with which variables used in
risk adjustment are defined and collected.21- 24
With respect to use of lower-mortality hospitals, however, illness severity
is less relevant than other potential confounders, such as urgency of the
admission, patient socioeconomic status, and the geographic relationship between
the residence of the patient and area hospitals. In the present study, we
were able to control for each of these variables, except that an ecological
proxy, ZIP code median family income, was the only measure of socioeconomic
status available. The use of this type of ecological variable has major drawbacks,25,26 but in the present study it allowed
some adjustment for affluence, as it has in other studies on access to medical
care.27,28 Despite the strong
relationship of race/ethnicity to socioeconomic status,29- 31
we did not include it as a covariate in our main analysis both because of
significant missing data and because of limitations on the interpretation
of racial and ethnic information.32- 34
Nonetheless, in a supplementary analysis that stratified by race/ethnicity,
the effects of insurance type on the use of lower-mortality centers was generally
consistent with those noted in the nonstratified model.
It must be noted that the results of the present study may not generalize
beyond New York State. Because the nature of managed care, the availability
of hospital quality information, and the types of hospitals performing CABG
surgery vary substantially from state to state, these relationships could
differ in other parts of the country.
Despite these limitations, our findings suggest that explicit monitoring
of the process and outcomes of care could play an important role in identifying
problems with the quality of care for managed care enrollees. The role of
managed care organizations in the reduced use of lower-mortality centers among
their beneficiaries is likely to be complex and multifactorial. Plans may
enter into relationships with hospitals largely on the basis of anticipated
costs and may create incentives for primary care providers and patients to
use lower-cost centers as well. It is also possible that lower-mortality centers
may themselves be unwilling to contract with managed care organizations, if
they expect better remuneration from other payers. Meanwhile, by limiting
patient choices, managed care organizations may prevent patients and their
advocates from taking full advantage of available information about hospital
quality. This could inadvertently stifle incentives for hospitals to compete
on the quality of care. Additional studies on the impact of quality information
on health plans' contracting decisions will be important as price competition
among health plans becomes more intense.