Journal of the National Cancer Institute, Vol. 98, No. 3, February 1, 2006 ARTICLES 163
Associations Between Hospital and Surgeon Procedure Volumes
and Patient Outcomes After Ovarian Cancer Resection
Deborah Schrag , Craig Earle , Feng Xu , Katherine S. Panageas , K. Robin Yabroff ,
Robert E. Bristow , Edward L. Trimble , Joan L. Warren
Background: Strong associations between provider (i.e., hospi-
tal or surgeon) procedure volumes and patient outcomes have
been demonstrated for many types of cancer operation. We
performed a population-based cohort study to examine these
associations for ovarian cancer resections. Methods: We used
the Surveillance, Epidemiology, and End Results (SEER) –
Medicare linked database to identify 2952 patients aged 65
years or older who had surgery for a primary ovarian cancer
diagnosed from 1992 through 1999. Hospital- and surgeon-
specifi c procedure volumes were ascertained based on the
number of claims submitted during the 8-year study period.
Primary outcome measures were mortality at 60 days and
2 years after surgery, and overall survival. Length of hospital
stay was also examined. Patient age at diagnosis, race, marital
status, comorbid illness, cancer stage, and median income and
population density in the area of residence were used to adjust
for differences in case mix. All P values are two-sided. Results:
Neither hospital- nor surgeon-specifi c procedure volume was
statistically signifi cantly associated with 60-day mortality fol-
lowing primary ovarian cancer resection. However, differences
by hospital volume were seen with 2-year mortality; patients
treated at the low-, intermediate-, and high-volume hospitals
had 2-year mortality rates of 45.2% (95% confi dence interval
[CI] = 42.1% to 48.4%), 41.1% (95% CI = 38.1% to 44.3%),
and 40.4% (95% CI = 37.4% to 43.4%), respectively. The
inverse association between hospital procedure volume and
2-year mortality was statistically signifi cant both before
( P = .011) and after ( P = .006) case-mix adjustment but not
after adjustment for surgeon volume. Two-year mortality for
patients treated by low-, intermediate-, and high-volume
surgeons was 43.2% (95% CI = 40.7% to 45.8%), 42.9% (95%
CI = 39.5% to 46.4%), and 39.5% (95% CI = 36.0% to 43.2%),
respectively; there was no association between 2-year mortal-
ity and surgeon procedure volume, with or without case-mix
adjustment. After case-mix adjustment, neither hospital vol-
ume ( P = .031) nor surgeon volume ( P = .062) was strongly
associated with overall survival. Conclusion: Hospital- and
surgeon-specifi c procedure volumes are not strong predictors
of survival outcomes following surgery for ovarian cancer
among women aged 65 years or older. [J Natl Cancer Inst
2006;98:163 – 71]
Compelling evidence from multiple studies ( 1 – 5 ) suggests
that cancer patients whose surgical resections are performed in
hospitals with large case volumes have better outcomes than
patients treated in hospitals with low case volumes. Results of
another study ( 6 ) suggest that the case volume of the individual
surgeon is a more powerful determinant of outcome than the
case volume of hospital in which a resection is performed. The
sustained interest in volume – outcome studies in the medical
literature and in the lay press has led patients to ask practical
questions about how they should weigh information about the
case volumes of the hospital and of the individual surgeon
in their decisions about where and from whom to seek medical
care. From a policy perspective, the most important sources
of variation in outcomes need to be identifi ed to optimize the
quality of care.
We examined the roles of surgeon procedure volume and
hospital procedure volume as determinants of outcomes for a
population-based cohort of female Medicare benefi ciaries
diagnosed with epithelial ovarian cancer during the 1990s. We
sought to determine whether patients treated by high-volume
providers (i.e., hospitals and surgeons) achieve better outcomes
than patients treated by low-volume providers. In particular, we
wanted to know whether selecting an ovarian cancer surgeon on
the basis of his or her case volume represents a good strategy
for optimizing outcomes, independent of the surgeon’s specialty
(i.e., gynecologic oncology, general gynecology, or general
surgery). We anticipated that there might be some general
gynecologists and general surgeons who achieved outcomes
comparable to those of gynecologic oncologists because they
performed ovarian cancer operations frequently.
We identifi ed a cohort of elderly ovarian cancer patients from
a database ( 7 ) that links the Surveillance, Epidemiology, and
End Results (SEER) population-based cancer registries with a
Center for Medicare Services’s health care claims. We used the
unique provider identifi cation numbers (UPINs) included on all
Affi liations of authors: Department of Epidemiology and Biostatistics,
Memorial Sloan-Kettering Cancer Center, New York, NY (DS, FX, KSP); Center
for Outcomes and Policy Research, Dana-Farber Cancer Institute, Boston, MA
(CE); Department of Gynecology and Obstetrics, The Johns Hopkins Medical In-
stitutions, Baltimore, MD (REB); Applied Research Program (KRY, JLW), Cancer
Therapy and Evaluation Program (ELT), National Cancer Institute, Bethesda, MD .
Correspondence to: Deborah Schrag, MD, Department of Epidemiology
and Biostatistics, Box 221, Memorial Sloan-Kettering Cancer Center, 1275
York Ave., New York, NY 10021 (e-mail: firstname.lastname@example.org ).
See “ Notes ” following “ References. ”
© The Author 2006. Published by Oxford University Press. All rights reserved.
For Permissions, please e-mail: email@example.com.
by guest on October 27, 2015
164 ARTICLES Journal of the National Cancer Institute, Vol. 98, No. 3, February 1, 2006
claims submitted for reimbursement to Medicare since 1991 to
obtain information about the patients’ providers (i.e., hospitals
The SEER registries ascertain all incident cancer cases diag-
nosed in fi ve states and six U.S. metropolitan areas, which together
represent approximately 14% of the U.S. population ( 8 ). The
SEER program collects information on each incident cancer,
including the primary site and histology [classifi ed according to
the International Classifi cation of Disease for Oncology, 2nd
edition ( 9 ) ], the tumor stage at diagnosis, and patient demographics
( 8 , 9 ) . SEER data do not include detailed information about cancer
treatment; however, this information can be ascertained for Medi-
care benefi ciaries from billing claims. Given that ovarian cancer
typically strikes women in their 60s and 70s ( 11) and that the
Medicare program provides health insurance for 97% of the U.S.
population aged 65 years or older (12) , linkage of the SEER
registries with Medicare claims data allowed us to identify a large,
nationally representative cohort of women with this disease ( 7 ).
Among SEER registry patients aged 65 years or older, 94% have
been linked to their Medicare records ( 12 ) . Data from the 2000
U.S. Census have also been linked to SEER – Medicare data,
allowing us to characterize patients represented in the SEER –
Medicare database with respect to sociodemographic factors.
We used Medicare Provider Analysis and Review (MEDPAR)
fi les to obtain details of all hospitalizations for persons eligible
for Medicare Part A. To receive payment, hospitals submit claims
to Medicare that code up to 10 diagnoses and 10 procedures that
are classifi ed according to the International Classifi cation of
Diseases, 9th Revision, Clinical Modifi cation (ICD-9-CM) ( 13 ) .
For the 96% of Medicare benefi ciaries who opt for Part B cover-
age, claims for care delivered in hospital outpatient departments
or in physicians’ offi ces are also recorded. Medicare documents
the date of death for its benefi ciaries using information provided
by the Social Security Administration.
Cohort Defi nition
All Medicare-enrolled patients aged 65 years or older who
were diagnosed with primary ovarian cancer while residing in a
area covered by the SEER program between 1992 and 1999 were
potentially eligible for inclusion in our study. We restricted our
cohort to patients with a histologic diagnosis consistent with
epithelial cell tumors and excluded patients with germ-cell
tumors and ovarian tumors of borderline malignancy. We also
excluded patients whose diagnoses were noted exclusively on
death certifi cates or at autopsy as well as those for whom the
month of diagnosis was not known. We excluded the 24% of
ovarian cancer patients living in areas covered by SEER programs
who were enrolled in a health maintenance organization (HMO)
at diagnosis because HMOs do not report claims detailing the
specifi c procedures and noncancer diagnoses to the Center for
Medicare Services. All patients in our cohort were enrolled
continuously in Medicare Parts A and B after diagnosis. Our
sample size is slightly smaller than that of the companion paper
by Earle et al. ( 14 ) because our analysis required that both the
surgeon and hospital be identifi ed for each patient.
Identifi cation of Ovarian Cancer Operations
Both SEER registries and Medicare record information about
a patient’s initial surgery. In collaboration with a panel of four
gynecologic surgeons (Diane C. Bodurka, Department of Gyne-
cologic Oncology, University of Texas M. D. Anderson Cancer
Center; Michael Carney, Department of Obstetrics, Gynecology,
and Women’s Health, Kapiolani Medical Center for Women and
Children; ELT; and REB), we identifi ed the SEER variables and
the Medicare billing codes that correspond to a primary surgery
for ovarian cancer and searched for those variables and diag nosis
and procedure codes in 1) inpatient claims submitted by hospitals
using ICD-9-CM ( 13 ) ; 2) claims submitted by surgeons using
the Current Procedural Terminology (CPT) codes ( 15,16 ) ; and
3) information from the SEER registries about the type of cancer-
directed surgery performed ( 8 ) . Our analysis included only pa-
tients who underwent surgery at hospitals located in one of the
nine states covered by one of the 11 SEER registries because we
could not reliably measure procedure volume at institutions
outside SEER areas.
Specifi cation of Cohort Characteristics
Demographic variables, including age at diagnosis and race,
were defi ned on the basis of information ascertained by the SEER
registrars. Cancer stage was assigned according to the American
Joint Committee on Cancer (AJCC) classifi cation schema re-
corded by SEER ( 17 ) . We used the Romano modifi cation ( 18 )
of the Charlson comorbidity index ( 10 ) to ascertain comor -
bidities among our cohort. To categorize comorbidities, we exam-
ined all inpatient Medicare claims for the 12 months prior to the
index surgical admission as well as claims fi led during the index
admission and used these records to assign to each patient the
maximal comorbidity observed. Information about marital status,
median income in the census tract of patient residence, and the
population density in the area of residence was obtained from
Medicare fi les.
Outcomes After Ovarian Cancer Surgery
Outcome measures included 60-day and 2-year postoperative
mortality and overall survival. Survival was defi ned as the inter-
val from the date of hospitalization for resection until the date of
death as reported to Medicare or December 31, 2001 (i.e., when
censoring occurred), whichever occurred fi rst. Other outcome
measures were the length of hospital stay and the rate of opera-
tions that were accompanied by creation of an intestinal stoma
(i.e., ostomy rate). Ovarian cancer resections that required
an ileostomy or colostomy were identifi ed in SEER – Medicare
data on the basis of accompanying ICD-9 or CPT codes. We did
not consider other complications as outcomes because we were
concerned that their coding might vary according to local physi-
cian and hospital practices.
Hospitals were ranked by volume according to the total num-
ber of ovarian cancer operations performed from January 1, 1992,
through December 31, 1999, as identifi ed from the Medicare fi les.
We used an analogous approach to ascertain surgeon-specifi c
procedure volume. Surgeons were ranked according to their total
volume of claims for ovarian cancer resections performed on
cohort members from January 1, 1992, through December 31,
1999. Patients whose claims lacked a UPIN for the primary
surgeon were categorized as having been treated by a surgeon
with an unknown procedure volume. We could not determine the
by guest on October 27, 2015
Journal of the National Cancer Institute, Vol. 98, No. 3, February 1, 2006 ARTICLES 171
(1) Bach PB, Cramer LD, Schrag D, Downey RJ, Gelfand SE, Begg CB. The
infl uence of hospital volume on survival after resection for lung cancer.
N Engl J Med 2001 ; 345 : 181 – 8.
(2) Begg CB, Cramer LD, Hoskins WJ, Brennan MF. Impact of hospital vol-
ume on operative mortality for major cancer surgery. JAMA 1998 ; 280 :
1747 – 51.
(3) Birkmeyer JD, Siewers AE, Finlayson EV, Stukel TA, Lucas FL, Batista I,
et al. Hospital volume and surgical mortality in the United States. N Engl J
Med 2002 ; 346 : 1128 – 37.
(4) Halm EA, Lee C, Chassin MR. Is volume related to outcome in health care?
A systematic review and methodologic critique of the literature. Ann Intern
Med 2002 ; 137 : 511 – 20.
(5) Schrag D, Cramer LD, Bach PB, Cohen AM, Warren JL, Begg CB. Infl uence
of hospital procedure volume on outcomes following surgery for colon
cancer. JAMA 2000 ; 284 : 3028 – 35.
(6) Birkmeyer JD, Stukel TA, Siewers AE, Goodney PP, Wennberg DE,
Lucas FL. Surgeon volume and operative mortality in the United States.
N Engl J Med 2003 ; 349 : 2117 – 27.
(7) National Cancer Institute. Surveillance, epidemiology, and end results
(SEER)-Medicare. Available at: http://healthservices.cancer.gov/seermedi
care . [Last accessed: August 1, 2005 .]
(8) National Cancer Institute. Surveillance, epidemiology, and end results
(SEER). Available at: http://seer.cancer.gov . [Last accessed: August 1,
(9) Percy C, Van Holton V, Muir CE. International classifi cation of diseases
for oncology. 2nd ed. Geneva (Switzerland): World Health Organization;
(10) Charlson ME, Pompei P, Ales KL, MacKenzie CR. A new method of
classifying prognostic comorbidity in longitudinal studies: development and
validation. J Chronic Dis 1987 ; 40 : 373 – 83.
(11) Sonoda Y. Management of early ovarian cancer. Oncology (Huntingt)
2004 ; 18 : 343 – 56; discussion 358, 361 – 2.
(12) Potosky AL, Riley GF, Lubitz JD, Mentnech RM, Kessler LG. Potential
for cancer related health services research using a linked Medicare-tumor
registry database. Med Care 1993 ; 31 : 732 – 48.
(13) International Classifi cation of Diseases, 9th Revision (ICD-9-CM). Chicago
(IL): American Medical Association Publications; 2000 .
(14) Earle CC, Schrag D, Neville BA, Yabroff KR, Topor M, Fahey A, et al.
Effect of surgeon specialty on processes of care and outcomes for ovarian
cancer patients. J Natl Cancer Inst 2006 ; 98 : 172 – 80.
(15) Current Procedural Terminology 1999. Chicago (IL): American Medical
Association Publications; 1999 .
(16) Beebe M, American Medical Association. CPT 2005: current procedural
terminology. 4th ed. Chicago (IL): American Medical Association; 2004 .
(17) Greene FL, Cancer. AJCo. AJCC Cancer Staging Manual. 6th ed. New York;
London (UK): Springer; 2002 .
(18) Romano PS, Roos LL, Jollis JG. Adapting a clinical comorbidity index
for use with ICD-9-CM administrative data: differing perspectives. J Clin
Epidemiol 1993 ; 46 : 1075 – 9; discussion 1081 – 90.
(19) Panageas KS, Schrag D, Riedel E, Bach PB, Begg CB. The effect of
clu stering of outcomes on the association of procedure volume and surgical
outcomes. Ann Intern Med 2003 ; 139 : 658 – 65.
(20) Liang KY, Zeger SL. Longitudinal data-analysis using generalized linear-
models. Biometrika 1986 ; 73 : 13 – 22.
(21) National Comprehensive Cancer Centers Practice Guidelines. Available at:
http://www.nccn.org/professionals/physician_gls/default.as . [Last accessed:
August 1, 2005 .]
(22) Meyerhardt JA, Catalano PJ, Schrag D, Ayanian JZ, Haller DG, Mayer RJ,
et al. Association of hospital procedure volume and outcomes in patients with
colon cancer at high risk for recurrence. Ann Intern Med 2003 ; 139 : 649 – 57.
(23) Meyerhardt JA, Tepper JE, Niedzwiecki D, Hollis DR, Schrag D,
Ayanian JZ, et al. Impact of hospital procedure volume on surgical opera-
tion and long-term outcomes in high-risk curatively resected rectal cancer:
fi ndings from the Intergroup 0114 Study. J Clin Oncol 2004 ; 22 : 166 – 74.
(24) Kumpulainen S, Grenman S, Kyyronen P, Pukkala E, Sankila R. Evidence
of benefi t from centralised treatment of ovarian cancer: a nationwide
population-based survival analysis in Finland. Int J Cancer 2002 ; 102 : 541 – 4.
(25) Tingulstad S, Skjeldestad FE, Hagen B. The effect of centralization of
primary surgery on survival in ovarian cancer patients. Obstet Gynecol
2003 ; 102 : 499 – 505.
(26) Ioka A, Tsukuma H, Ajiki W, Oshima A. Infl uence of hospital procedure
volume on ovarian cancer survival in Japan, a country with low incidence of
ovarian cancer. Cancer Sci 2004 ; 95 : 233 – 7.
(27) Bristow RE, Zahurak ML, del Carmen MG, Gordon TA, Fox HE, Trimble
EL, et al. Ovarian cancer surgery in Maryland: volume-based access to care.
Gynecol Oncol 2004 ; 93 : 353 – 60.
(28) The Leapfrog Group. Available at: http://www.leapfroggroup.org/ .
We thank the Applied Research Program, NCI; the Offi ce of Information
Services, and the Offi ce of Strategic Planning, CMS; Information Management
Services Inc.; and the Surveillance, Epidemiology, and End Results (SEER) Pro-
gram tumor registries in the creation of the SEER – Medicare database used in this
study. Drs. Diane Bodurka and Michael Carney provided valuable input into the
defi nition of surgical procedures used in this analysis.
Supported by the Health Services and Economics Branch, Division of Cancer
Control and Population Sciences and the Cancer Therapy and Evaluation Branch
of the National Cancer Institute. The study authors were solely responsible for
the data collection, analysis, and interpretation, manuscript preparation, and the
decision to submit the manuscript for publication .
Manuscript received April 15, 2005 ; revised November 18, 2005 ; accepted
December 6, 2005.
by guest on October 27, 2015