Download Hospital and Physician Volume or Specialization and

Survey
yes no Was this document useful for you?
   Thank you for your participation!

* Your assessment is very important for improving the workof artificial intelligence, which forms the content of this project

Document related concepts
no text concepts found
Transcript
REVIEW ARTICLE
Hospital and Physician Volume or Specialization and
Outcomes in Cancer Treatment: Importance in Quality of
Cancer Care
By Bruce E. Hillner, Thomas J. Smith, and Christopher E. Desch
Purpose: To conduct a comprehensive review of the
health services literature to search for evidence that
hospital or physician volume or specialty affects the
outcome of cancer care.
Methods: We reviewed the 1988 to 1999 MEDLINE
literature that considered the hypothesis that higher
volume or specialization equals better outcome in processes or outcomes of cancer treatments.
Results: An extensive, consistent literature that supported a volume-outcome relationship was found for
cancers treated with technologically complex surgical
procedures, eg, most intra-abdominal and lung cancers. These studies predominantly measured in-hospital
or 30-day mortality and used the hospital as the unit of
analysis. For cancer primarily treated with low-risk
surgery, there were fewer studies. An association with
hospital and surgeon volume in colon cancer varied
with the volume threshold. For breast cancer, British
studies found that physician specialty and volume were
associated with improved long-term outcomes, and the
single American report showed an association between
hospital volume of initial surgery and better 5-year
survival. Studies of nonsurgical cancers, principally
lymphomas and testicular cancer, were few but consistently showed better long-term outcomes associated
with larger hospital volume or specialty focus. Studies in
recurrent or metastatic cancer were absent. Across studies, the absolute benefit from care at high-volume centers
exceeds the benefit from break-through treatments.
Conclusion: Although these reports are all retrospective, rely on registries with dated data, rarely have
predefined hypotheses, and may have publication and
self-interest biases, most support a positive volumeoutcome relationship in initial cancer treatment. Given
the public fear of cancer, its well-defined first identification, and the tumor-node-metastasis taxonomy, actual cancer care should and can be prospectively measured, assessed, and benchmarked. The literature
suggests that, for all forms of cancer, efforts to concentrate its initial care would be appropriate.
J Clin Oncol 18:2327-2340. © 2000 by American
Society of Clinical Oncology.
ECAUSE OF A GROWING lack of public confidence
in the United States health care system, the National
Cancer Policy Board undertook a comprehensive review on
the effectiveness of cancer services and their delivery.1 At
the Board’s request, we initiated a comprehensive review of
the health services literature looking for evidence that
characteristics of providers, facilities, or delivery systems
affect the quality of cancer care. The scope of this review is
limited to what was found to be the largest body of evidence
for an association with quality of cancer care: the relationship between outcomes and hospital or physician volume or
specialty. The higher volume– better outcome association
was first described 20 years ago by Luft et al.2
A succinct definition of quality of care, prepared by the
Institute of Medicine, is as follows: “quality of care is the
degree to which health services for individuals and populations increase the likelihood of desired outcome and are
consistent with current professional knowledge.”3 The three
classic components of quality of care are structure, process,
and outcome and can be assessed using process data,
outcome data, or both.4,5 The least satisfactory assessments
are implicit reviews, usually of the medical record or
secondary data (insurance claim or registry), in which no
prior standards or agreement about good or better care
exists. Preferred are evaluations that use explicit process
criteria, ie, whether a breast cancer patient had an estrogen
receptor assay performed, whether its results were recorded,
and the result expressed as the proportion of criteria that
were met. This last step requires setting targets or benchmarks. Almost all cancer studies are implicit reviews that
seldom demonstrate where target levels for specific process
B
From the Massey Cancer Center and Department of Internal
Medicine, Medical College of Virginia at Virginia Commonwealth
University, Richmond, VA.
Submitted July 8, 1999; accepted February 15, 2000.
Supported in part by the following grants: Faculty Research Award
from the American Cancer Society, Atlanta, GA (B.E.H.), Faculty
Scholar Award, Project on Death in America, Open Society, New York,
NY (T.J.S.), grant no. RFP CO 94388-63 from the Office of Cancer
Communications, National Cancer Institute, Bethesda, MD (T.J.S.),
grant from the National Cancer Policy Board of the Institute of
Medicine, Washington, DC, and grant from the Virginia Commonwealth University Outcomes Research Center, Richmond, VA.
Address reprint requests to Bruce E. Hillner, MD, FACP, Virginia
Commonwealth University, Box 980170, Richmond, VA 23298-0170;
email [email protected].
© 2000 by American Society of Clinical Oncology.
0732-183X/00/1811-2327
Journal of Clinical Oncology, Vol 18, No 11 (June), 2000: pp 2327-2340
2327
2328
Table 1.
HILLNER, SMITH, AND DESCH
Framework of Factors Affecting Treatment Processes and
Outcome
Patient
Treatment processes and outcome
Education
Income
Comorbidity
Insurer
Access
Coordination of services
Barriers to referral
Geography
Location
Distance from treatment
Physician provider
Specialty training or focus
Case volume
Research focus
Medical center
Size and scope of services
Case volume
Academic
Multidisciplinary
Table 2.
Conceptual Overview of Support for Volume-Outcome in Cancer
Care
Therapy Intent and Outcome Time Frame
Principal Treatment
Modality
Surgery
Chemotherapy
Radiation
Curative
Short-Term
Curative
Long-Term
Palliative
Large
None
None
Modest
Modest
None
N/A
None
None
Abbreviation: N/A, not applicable.
subsequently narrowed the focus to the relationship of volume and
outcome. Excluded were reports related to screening or early detection
and surveys of physician attitudes or practices based on hypothetical
patients. We used the following MEDLINE terms: disease management, epidemiology, medical audit, outcome assessment, outcome and
process assessment, physician practice patterns, quality assurance,
health care quality indicators, quality of health care, registries, standards, and treatment outcome. These terms were combined with
individual cancer terms. The bibliography of each article was reviewed
for other potentially relevant citations.
Quality Assessment
components or outcomes were assessed. The optimal assessment is to show an association between achieving the
targets or ordinal descriptions (poor, fair, or good) and
subsequent outcome.
Studies in other conditions have found various nontreatment factors associated with better outcomes (Table 1).
Patient factors are the most obvious and the most studied in
cancer. Patients with less education or lower income and/or
comorbidity commonly have poorer outcomes.6 A patient’s
insurer may affect access to care and coordination of
services by creating barriers to referral. Geographic variation in care, especially surgery (specifically, radical prostatectomy [RP] and mastectomy), is well known.7,8 Physician
characteristics, such as specialty training focus, research
interest, and case volume, should convey that the physician’s management is state-of-the-art. The same is true for
hospitals or medical centers where the size and scope of
services, case volume, presence of multidisciplinary clinics,
and academic affiliation are associated with high quality.
These characteristics should translate into processes that
physicians know or believe to be associated with better
outcomes. These processes include the following: adopting
new beneficial therapy early, delivering higher rates of
well-established, effective therapy, improving delivery of
therapy, and providing superior coordination of care.
METHODS
Information Sources
We reviewed the published literature cited in MEDLINE from 1988
to 1999 that was potentially related to quality of cancer care, and we
Identified papers were reviewed for their completeness in controlling
for potential biases. 9,10 Only studies that stratified or adjusted for
clinical stage were included. In addition, each was assessed regarding
whether it identified and controlled for case mix by adjusting for
differences in demographics and/or comorbidity. The studies that
included adjustments for comorbidity were specifically highlighted. All
studies were classified by type (process or outcome), data sources, units
of analysis, country, and attribute assessed.
RESULTS
The review found numerous methodology limitations in
almost all studies. All but one report used retrospective data.
The vast majority were not hypothesis-driven. Almost all
used convenience samples and had no preplanned statistical
power or effect-size estimates. Reports that considered
processes of care focused on variation between groups or
sites of care, not on variation from specific targets. Comorbidity was usually inferred from administrative claims, not
specific clinical indices or databases.
An overview of the results is shown in Tables 2 and 3.
Table 2 categorizes the results by the principal treatment
modality, therapeutic intent, and time frame. The vast
majority of studies, which will be discussed subsequently in
detail, focused on the short-term outcomes of cancers for
which the primary mode of therapy was surgery performed
with curative intent. Long-term outcomes of these surgical
therapies were substantially fewer. There were fewer than
10 studies of cancers for which the principal treatment was
chemotherapy. The specific processes that lead to or that are
associated with the superior outcomes in specific hospitals
or physician specialties have not been deciphered. No
2329
VOLUME/SPECIALIZATION AND CANCER CARE OUTCOMES
Table 3.
Pancreas
Hospital volume
Acute
Long-term
Hospital specialty
Physician volume
Physician specialty
Overview of Positive Volume-Outcome Effects for Nine Common Cancer Categories
Other GI
Surgery
Lung
Colorectal
Breast
Ovary
**
**
**
**,⌽
*
*
*
***
*
*
Symbols: *** Five or more studies; ** two to four studies; * one study;
⌽
Testes
**
**
*
*
**
*
**
two or more studies not showing volume-outcome effect.
studies were found of hospital or physician characteristics
related to outcomes, such as level of pain control or
patient/family satisfaction, after radiation therapy in which
the goal was palliative,.
Table 3 lists the numbers of studies found for each of nine
common cancers, stratified by four characteristics: hospital
volume, hospital specialization, physician volume, and physician specialization. The only paired characteristic and
cancer category that had five or more studies that supported
the volume-outcome hypothesis was hospital volume and
surgery for pancreatic cancer.
Cancers Associated With High-Risk Surgery
The quality of cancer care might be superior in terms of
its association with physician specialty or hospital volume
in cases in which the primary therapy is a high-risk surgical
intervention. Cancers that fit this category are non–smallcell lung cancer (NSCLC) and pancreatic, esophageal, and
gastric cancer. The unit of analysis has principally been the
hospital, with little evaluation of the effect of specific
surgeon volume.
Pancreatic. Numerous studies show a consistent trend
toward hospital case volume predicting better outcome in
pancreas surgery. These studies offer the most compelling
Table 4.
Lymphoma
*
**
**
*
Prostate
support of the hospital case volume– better outcome hypothesis because of their size and diversity of study designs.
Glasgow and Mulvihill11 in California and Lieberman et
12
al in New York performed similar studies (Table 4) in
which statewide hospital discharge records were used to
evaluate hospital volume for major pancreatic resections. In
both states, centers with higher volume had better profiles in
mortality, costs, and length of hospitalizations. Of 298
hospitals in California from 1990 to 1994, 88% treated an
average of two or fewer patients per year with pancreatic
resection. The risk-adjusted mortality in hospitals that
treated an average of one or less cases per year was 14.1%,
compared with 3.5% at hospitals that averaged more than 10
per year. In New York state between 1984 and 1991,
approximately 25% of hospitals averaged one surgery per
year and approximately 75% of hospitals averaged fewer
than seven per year. In New York, the logistic regression
model that adjusted for hospital volume, comorbidity,
clinical variables, and time trends did not find that individual physician volume was a predictor of better outcome.
Janes et al13 evaluated and compared the national patterns
of care for pancreatic cancer for the period from 1983 to
1990 using the National Cancer Database of the American
College of Surgeons. Unadjusted operative mortality was
Pancreatectomy In-Hospital Mortality and Hospital Volume in Two States
Average Annual Volumes of Pancreatic Resections
ⱕ1
No.
California, 1990-1994
(n ⫽ 1,705)
Hospitals
Patients
Risk-adjusted mortality
New York, 1984-1991
(n ⫽ 1,972)
Hospitals
Patients
Risk-adjusted mortality
%
⬎ 1-10
Range (%)
263
No.
%
⬎ 10
Range (%)
33
53
8
3.5
6.9-8.7
58
24
18.9
%
2
38
9.6-14.1
124
No.
2
57
19
11.8-12.9
5.5
NOTE. Some categories were collapsed to allow direct comparison. Therefore, ranges of risk-adjusted mortality rates are shown. Data adapted from Glasgow
and Mulvihill11 and Lieberman et al.12.
2330
HILLNER, SMITH, AND DESCH
Table 5.
Procedure
Pancreatectomy
Esophagectomy
Pneumonectomy
Hepatic resection
Pelvic exenteration
Thirty-Day Mortality for Selected Cancer Surgeries in the Elderly, 1984 to 1993
No. of
Incident
Cases
Surgeries
Performed
(%)
1-5 Cases
6-10 Cases
11⫹ Cases
19,205
6,782
103,425
126,395
185,305
3.9
7.4
1.3
0.6
0.9
12.9
17.3
3.7
5.4
3.7
7.7
3.9
14.1
3.5
3.2
5.8
3.4
10.7
1.7
1.5
Hospital Volume and 30-Day Mortality (%)
NOTE. Data adapted from Begg et al.18
7.7% for hospitals in which fewer than five patients per year
were treated for this disease and 4.2% for those in which 20
or more patients per year were treated.
A series of papers from Johns Hopkins addressed the
effects of regionalizing this procedure. Gordon et al,14 using
hospital discharge reports, compared the hospital mortality,
length of stay, and costs for the period from 1988 to 1993
between Johns Hopkins and the rest of Maryland (a total of
38 hospitals). The results were striking: in-hospital mortality was 2.2% versus 13.5% (relative risk [RR], 6.1; 95%
confidence interval [CI], 2.9 to 12.7), and mean length of
stay (23 v 27 days) and mean total charges were 20% greater
outside Johns Hopkins. A follow-up study attributed the
decline in the Maryland in-hospital mortality for pancreas
surgery from 17.2% in 1984 to 4.9% in 1995 (a 61%
decrease) to the increase in share of discharges at the
high-volume provider, Johns Hopkins.15 A second follow-up report for the period from 1990 to 1995 considered
correlations between the effect of hospital case volume and
that of the individual surgeon (⬍ five, five to 50, and ⬎ 50
patients for 5 years).16 No independent effect of surgeon
volume was observed, but only four surgeons were classified as high-volume surgeons, each of whom practiced at
Johns Hopkins, and 27 were medium volume.
Birkmeyer et al17 showed that hospital volume is also
associated with an improved late survival in the elderly who
are undergoing pancreaticoduodenectomy. He assessed a
retrospective cohort of all 7,229 patients in the United States
older than 65 years who had undergone this procedure and
stratified hospitals by annual averages of less than one, one
to two, two to five, and five or more cases per year. Overall,
3-year survival was 37% at the high-volume centers and
25% to 29% at the lower volume centers. The RR ratio after
adjusting for case mix was 0.69 (95% CI, 0.62 to 0.76).
Esophageal, gastric, and hepatic resection. Begg et al18
recently assessed 30-day mortality and hospital volume in
the elderly using linked Medicare/Surveillance, Epidemiology, and End-Results (SEER) databases for the period from
1984 to 1993. The study was the only one that was identified
as having an a priori hypothesis, although the size of
anticipated differences was not given. The linked databases
identified precise details of the surgical procedures, comorbidity, and stage for a variety of surgical procedures (Table
5). These procedures were chosen because they “involve
preoperative judgement, diagnostic accuracy, meticulous
surgical technique, and demanding postoperative care.”18
Curative surgery is rarely performed for these cancers in
the elderly. Table 5 shows that for all incident cancers over
the 10-year period, the number of procedures within 2
months of diagnosis (excluding hepatic resection) ranged
from approximately 1% to 7%. Yet, within this small subset
of patients undergoing surgery, a distinct trend of decreasing mortality with increasing volume was observed for all
conditions except for pneumonectomy. There was no difference in the relative comorbidity across hospitals and no
evidence that high- (or low-) volume centers operated on a
lower risk set of patients.
The only other study that addressed esophagectomy used
California discharge abstracts from 1990 to 1994 of 273
hospitals and 1,561 patients.19 Eighty-eight percent of
hospitals averaged two or fewer cases per year, which
accounted for 50% of all patients treated. Annual crude and
risk-adjusted hospital mortality rates all decreased in the
period from 1990 to 1994. Hospital volume was the largest
independent variable that affected mortality: average mortality at a center in which more than 30 cases were treated
was 4.8%, compared with 16% at those that treated fewer
than 30 cases.
The Johns Hopkins group addressed hepatic resection
in-hospital mortality using the identical method that they
used for pancreatic surgery. Johns Hopkins performed
almost one half of all hepatic resections in Maryland.
Approximately one half of these resections were for metastatic cancer and 18% for primary liver cancer. Comorbidity
was not different between high- and low-volume centers.
In-hospital mortality at Johns Hopkins was 1.5%, compared
with 7.9% in the remainder of Maryland.20
NSCLC. Despite NSCLC being the leading cancer
cause of death in the United States, only three studies of it
were found, all of which addressed its surgical care.
2331
VOLUME/SPECIALIZATION AND CANCER CARE OUTCOMES
Table 6.
California Postoperative Mortality With Lung Cancer Surgery, 1983 to 1986
Annual Hospital Volume for All Lung Cancer Procedures
Lesser resections
Total procedures within category, no.
Adjusted mortality, %
Adjusted odds ratio
95% CI
Pneumonectomy
Total procedures within category
Adjusted mortality (%)
Adjusted odds ratio
95% CI
⬍9
9-16
17-24
⬎ 24
2,588
5.2
1.0
2,945
4.1
0.7
0.6-1.0
2,553
3.5
0.6
0.5-0.8
2,822
3.4
0.6
0.4-0.8
365
13.6
1.0
374
11.4
0.8
0.5-1.2
377
11.7
0.8
0.5-1.3
413
9.7
0.6
0.4-1.0
NOTE. Data adapted from Romano and Mark.23
Numerous surveys of physician attitudes concerning optimal care were found, but they were excluded because actual
care was not described.
Surgical resection continues to be the preferred treatment
for early-stage NSCLC. Despite improved imaging techniques, approximately one third of all patients with NSCLC
have an initial surgical procedure. Expected perioperative
mortality varied with the extent of the surgery: pneumonectomy, ⬃6%; lobectomy, ⬃3%; segmental resection, ⬃1%,
and age, stage, and comorbidity.21 These mortality estimates are typical of university center reports. However,
Whittle et al22 found a 17% 30-day mortality rate after
pneumonectomy in a national sampling of Medicare claims
from the early 1980s.
Romano and Mark23 assessed 12,439 hospital discharges
from 499 hospitals from the state of California who underwent pulmonary resections in the period from 1983 to 1986.
The mean age was 62 years for pneumonectomy and 65
years for lesser procedures. A multivariate regression model
that included demographic data and clinical comorbidity
found no difference in the risk of in-hospital death associated with teaching hospitals. Table 6 shows a consistently
lower operative mortality rate at higher volume centers. The
effect of individual surgeon volume was not addressed. A
more recent study by Silvestri et al24 used a South Carolina
statewide severity-adjusted database to compare general
with thoracic surgeons. From 1991 to 1995, 1,720 resections were performed, of which 90% were lobectomies.
General surgeons performed approximately one half of all
procedures. No differences were observed in demographics
or comorbidity in patients by physician specialty. Lobectomy mortality was higher among patients treated by general surgeons: 5.3% v 3.0%, P ⬍ .05. Seventy percent of
thoracic surgeons performed more than 10 resections per
year, whereas 75% of general surgeons performed fewer
than 10. The third study by Begg has been described
previously. For pneumonectomy, the 30-day mortality rates
showed a non–statistically significant trend of higher volumes (P ⬍ .29).
No studies were identified that addressed variation in the
process of care for NSCLC associated with physician
specialty or hospital type. Specifically, no studies addressed
referral patterns to medical or radiation oncologists, staging,
especially for stage III disease, the types and quantity of
radiation therapy, the use of first- or second-line chemotherapy, or the effectiveness in end-stage symptom control.
Common Cancers With Low Surgical Risk
The hypothesis that hospital or physician volume leads to
better outcome has been studied in colon, breast, prostate,
and ovarian cancers. For each of these cancers, the perioperative risks associated with the primary therapy are low.
Given the high incidence of these cancers and the high
frequency of multimodal postsurgical therapies, each condition could provide insights into volume-outcome benefits
from superior coordination of care. In addition, colon
cancer– and breast cancer–associated procedures are predominantly performed by generalist surgeons. Therefore,
the physician volume– outcome hypothesis is also the most
threatening to general surgeons.
Colon cancer. Measurable, modest improvements in
overall and stage-specific survival that have occurred in the
past 30 years, which are attributed to improvements in
surgical technique by reducing perioperative mortality and
the addition of adjuvant chemotherapy, are unlikely to be
confounded by significant stage migration. Benefits associated with physician specialization and hospital volume have
been inconsistently observed, possibly because of a difference in the volume thresholds used. When found, these have
been observed predominantly in rectal cancer. Most studies
focused on short-term operative mortality, and none addressed preoperative evaluation, adjuvant chemotherapy in
2332
Table 7.
HILLNER, SMITH, AND DESCH
Colorectal Resection by Surgeon and Hospital Volume Association With In-Hospital Mortality in 9,739 Resections in Maryland, 1992 to 1996
Surgeon Annual Volume*
⬍5
% of group
% of all cases
Average annual
case volume
Crude mortality, %
Adjusted relative
risk
80
36
1.8
4.5
1.00
⬎ 10
5-10
14
37
7.0
6
27
14.0
3.3
0.79
2.6
0.64
Hospital Annual Volume*
Total
—
—
3.1
3.5
—
⬍ 40
58
32
21.5
4.7
1.00
40-70
28
36
50
3.0
0.79
⬎ 70
14
32
89.9
3.0
0.78
Total
—
—
39
3.5
—
NOTE. Data adapted from Harmon et al.29
*Numbers in each group were 812 surgeons and 50 hospitals.
stage III disease, or actual (v survey) patterns of follow-up
care.
Numerous British studies have not consistently found
volume or specialty effect. An older Scottish report by
McArdle and Hole25 from 1974 to 1979 found a four-fold
variation in survival and complications based on a surgeon’s
specialty volume and interest in colorectal disease. Subsequently, Kingston et al26 evaluated the care of 578 patients
by 12 community surgeons interested in colorectal cancer
compared with university care and found no benefit from
university care. The audit of Mella et al27 of short-term
outcomes of 3,221 patients diagnosed in 1992 to 1993 in
Wales and Scotland found no effect for surgeon volume
(using ⬍ 10 or ⬍ 30 cases per year) or specialty interest.
Overall, 30-day mortality was 7.6%. Kee et al28 reviewed a
cohort of 3,217 new patients in Northern Ireland diagnosed
between 1990 and 1994. After a median follow-up of 4.5
years, they found no long-term benefit associated with
surgeon or hospital volume. Seventy-one surgeons operated
at 19 hospitals. Only 20% of cases were managed by
surgeons who averaged ⱕ 10 cases per year. Neither
in-hospital nor 30-day mortality was reported.
Harmon et al29 from Johns Hopkins conducted the best
American study, in which they performed a cross-sectional
analysis of all colorectal cancer surgery using Maryland
state discharge data from 1992 to 1996. This study was
unique in that it was large enough to examine the independent effect of surgeon and hospital volume. Table 7 shows
the distribution of case volume by surgeon and hospital and
the observed in-hospital mortality rates and RRs. In contrast
to the 20% in Northern Ireland, 74% of cases were managed
by surgeons who averaged fewer than 10 cases per year.
Seven hospitals, including Johns Hopkins, were defined as
high-volume. We estimate that the proportion of surgeons to
population was approximately three-fold greater in Maryland than in Northern Ireland. Higher surgeon volume was
associated with significant improvement in in-hospital
death, length of stay, and costs. Medium-volume surgeons
achieved results equivalent to those of high-volume surgeons when they operated at high-to-medium–volume hospitals.
All other American studies before and after 1988 have
addressed all forms of colorectal resection, not just those
performed for colorectal cancers. This is an important
distinction because the case-volume thresholds are not
directly comparable. Khuri et al,30 as part of the Veteran
Affairs National Surgical Quality Improvement Program,
assessed eight commonly performed surgeries of intermediate complexity, including partial colectomy. This was the
only identified study that used prospectively collected data.
They found no differences in risk-adjusted 30-day mortality
between 1994 and 1998 at 125 hospitals among 13,000
patients based on volume, but the average crude mortality
rate was high at 6.9%. Rosen et al31 compared six colorectal
specialty surgeons with 33 other surgeons for the period
from 1986 to 1994 at two university-affiliated hospitals in
Pennsylvania. The hospitals had accredited colon and rectal
and general surgery training programs. Before and after the
adjustment for comorbidity, specialty surgeons had lower
in-hospital mortality in 2,805 patients: 8-year mean, 1.4% v
7.3% (P ⬍ .0001). This benefit was primarily observed in
the 54% of patients with higher comorbidity.
Studies limited to rectal cancer are few, but all show a
volume or specialty effect. Porter et al32 addressed care
between 1983 and 1990 at five Edmonton, Canada, hospitals
of 683 patients with rectal cancer treated by 52 surgeons, of
whom five had specific training in colorectal surgery. Local
recurrence is an especially strong indicator of surgical
technique. Multivariate analysis showed that local recurrence and disease-specific survival were both worse if
treated by a non–specialty trained (RR 2.5; 95% CI, 1.35 to
2.40) or low-volume surgeons (⬍ 21 cases in 7 years; RR
1.8; 95% CI, 1.35 to 2.40). Holm et al32a found in 1,399
patients within the clinical trial setting that patients at higher
volume (⬎ 10 cases per year) or university hospitals had a
2333
VOLUME/SPECIALIZATION AND CANCER CARE OUTCOMES
lower incidence of risk-adjusted local recurrence and deaths
from rectal cancer.
Breast cancer. Given its high incidence and long history of patient advocacy, breast cancer has generated the
most concern about the quality of its care. In the United
States, research has primarily focused on factors associated
with breast-conserving surgery (BCS) but not on physician
or hospital factors associated with better long-term outcomes or processes.
Two British studies addressed surgeon characteristics.
Sainsbury et al33 evaluated 12,861 women by geographic
district and individual surgeon between 1979 and 1988 in
Yorkshire. They found a benefit in cases in which a
surgeon’s volume averaged more than 30 cases per year
(RR, 0.85; 95% CI, 0.77 to 0.93). These surgeons provided
care for approximately 50% of the cases. A multivariate
analysis found an absolute 8% survival benefit that was
attributed to greater use of chemotherapy. Gillis and Hole34
performed a similar assessment in western Scotland between 1980 and 1988. Specialist surgeons were defined as
those who were involved in a dedicated breast clinic or
clinical trials and who kept separate records of patients with
breast cancer. Such specialists provided care for approximately 25% of 3,786 cases. They found absolute benefit in
survival rates of 9% and 8% for groups at 5 and 10 years,
respectively, and an adjusted RR of death of 0.84 (95% CI,
0.75 to 0.94). The benefit was seen for all patient clinical
and social subgroups.
Bonett et al35 evaluated the 5-year survival by hospital
type in South Australia of 2,589 cases from 1980 to 1986.
After adjusting for stage, no significant differences were
found between large public (n ⫽ 4), large private (n ⫽ 5),
and smaller hospitals (n ⫽ 71).
Only two outcome studies from the United States were
found. These addressed hospital factors associated with
breast cancer survival. The most prominent and disturbing
was by Roohan et al,36 which used New York state hospital
discharge summaries that were linked to the state cancer
registry. From 1984 to 1989, 47,890 women with presenting
summary stage (in situ, local, regional, or metastatic) were
hospitalized at 266 hospitals. Cases were stratified by initial
summary stage and risk-adjusted for age at diagnosis. An
association of higher hospital volume with better 5-year
survival was seen in all stages. Table 8 shows the risk ratios
for all causes of mortality after 5 years, after adjusting for
comorbidity, socioeconomic status, and stage. The highest
volume hospitals provided only approximately 22% of the
care but were associated with a 19% to 60% improvement in
survival.36 The other prominent, but flawed, study by
Lee-Feldstein et al37 evaluated 5,892 white women from
1984 to 1990 treated at Southern California hospitals that
Table 8.
Five-Year Breast Cancer Survival by Hospital Volume in New
York State, Diagnosed in 1984 to 1989
Hospital Annual Volume
Patients treated over
5 years
No.
%
Relative risk of death
at 5 years
95% CI
⬍ 10
10-50
958
2
1.60
14,440
30
1.30
22,230
10,262
47
22
1.19
1.00
1.42-1.81
1.22-1.37
1.12-1.25
NOTE. Data adapted from Roohan et al.
50-150
⬎ 150
36
were stratified into the following categories: small community, census fewer than 200; large community, census more
than 200; Health Maintenance Organization, average census
not reported; or teaching hospitals. Because lymph node
involvement was unknown in 15% of patients and comorbidity was not included in the multivariate survival analysis,
all of the results are suspect. For example, women with local
or regional disease treated by mastectomy compared with
BCS with radiation had a 1.45 RR of death, which is
inconsistent with all other reports.
The literature regarding the process of breast cancer care
has principally focused on factors and temporal trends
associated with the use of BCS versus total mastectomy.
Hospital characteristics associated with the greater use of
BCS, such as teaching affiliation, larger size, on-site radiation therapy, and urban location, have been relatively
consistent across studies. These factors may not be predictive today. In a recent, 1993 to 1995 cross-sectional comparison of care, Guadagnoli et al38,39 evaluated BCS and
other indicators of process of initial care in more than 2,500
women at 18 randomly selected Massachusetts hospitals
and 30 Minnesota hospitals. They found that practice was
generally consistent with the results of national consensus
conferences. They also found that only teaching hospitals in
Massachusetts were associated with greater BCS use but
were less likely to perform axillary node dissection.
In contrast to type of surgery, the use and type of adjuvant
therapy does make a difference in survival. Although the
SEER registry shows a temporal increase in adjuvant
therapies since the mid-1980s, only one report was found
that addressed physician factors. Johnson et al40 found a
marked increase in the use of adjuvant therapy in nodenegative patients seen by a medical oncologist after the May
1998 National Cancer Institute (NCI) Clinical Alert. However, a detailed multivariate analysis of other patient characteristics was not presented; therefore, a spectrum bias is
possible. Important differences in radiation therapy processes of care or treatment planning associated with physi-
2334
HILLNER, SMITH, AND DESCH
Table 9.
Hospital Volume and Radical Prostatectomy Events in Medicare Enrollees, 1991 to 1994
Hospital Annual Volume
Mean 30-day mortality
%
Range
Relative risk
30-day mortality
Range
Readmission rate
Range
Serious complication
Range
Low (⬍ 39)
Medium Low
(39-74)
Medium High
(75-140)
High
(⬎ 140)
0.63
0.53-0.73
0.59
0.49-0.68
0.56
0.47-0.66
0.39
0.31-0.46
1.53
1.25-1.77
1.30
1.21-1.39
1.43
1.37-1.48
1.43
1.17-1.69
1.16
1.07-1.25
1.25
1.19-1.25
1.41
1.16-1.68
1.08
0.99-1.17
1.09
1.03-1.15
1.00
1.00
1.00
NOTE. 15.5% of cases were performed at teaching hospitals. 86.7% of cases were performed by urologists. Relative risk adjustments included age, race, surgeon
specialty, hospital teaching status, and year of diagnosis and comorbidity. Data adapted from Yao.43
cian volume or facility characteristics were either not
identified or not presented in the two breast cancer–specific
American College of Radiology Patterns of Care studies.41,42
Breast cancer–specific processes of care associated with
physician or hospital factors were sought but not found.
These included detailed evaluations related to the reporting
and use of estrogen receptor status, the use, extent, and
complications of axillary node dissection, and the duration
of hormonal therapy and the type of chemotherapy. No
studies were found that were related to physician, hospital,
or health system predictors of evaluation and treatment for
advanced breast cancer. In particular, no reports were found
that addressed predictors of type of first- or second-line
treatment or stopping rules for metastatic disease.
Prostate cancer. There is no consensus on the optimal
therapy for early- or late-stage prostate cancer, and care
patterns have markedly changed over the last 15 years. For
early-stage disease, there has been a marked increase in the
RP rate, which seems to have crested since 1992. The
impact of hospital and physician volumes on perioperative
mortality is just beginning to be addressed. An important
report by Yao and Lu-Yao43 describes a 1991 to 1994
Medicare claims analysis of 101,604 men who underwent
RP that addressed 30-day mortality and complication rates
related to hospital volume. This analysis was unusual in that
hospital teaching status and surgeon specialty were factors
included in the risk adjustment model. Although the absolute differences in 30-day mortality were small (0.39% to
0.65%), a clear gradient effect of hospital volume by
quartiles and outcomes was observed (Table 9). A study by
Karakiewicz et al45 with similar design but broader time
frame that included 4,997 RPs in Quebec from 1988 to 1996
found a lower 30-day mortality of 0.45% at academic
centers, which treated 37% of the total cases, versus 0.72%
at community centers.
Ovarian cancer. Assessments in ovarian cancer have
focused on the effect of the type of surgeon. Nguyen et al44
performed the most prominent but oldest of the studies
found, in which they used detailed hospital data from more
than 900 hospitals of 25 consecutive cases at each hospital
of 5,156 patients from 1983 and 7,160 patients from 1988.
An exploratory surgical procedure was performed in the
initial management of 96% of patients. The breakdown by
surgeon’s specialty was 20% general surgeons, 20% gynecologic oncologists, and 45% general gynecologists. Approximately one half of patients of gynecologists had stage
III or IV disease, compared with two thirds of patients of
gynecologic oncologists or general surgeons. Appropriate
surgical staging, completeness of debulking, and median
survival all correlated with specialty. Table 10 shows that
the stage-stratified 5-year survival rates varied by clinically
meaningful amounts.
Two British studies also showed an association between
surgical specialty and survival. Kehoe et al46 assessed
approximately 1,200 patients in central England between
1985 and 1987. Patients who were treated by general
surgeons had more advanced disease compared with those
treated by gynecologists. A multivariate model found care
by a general surgeon to be an independent prognostic factor,
with a 5-year RR of death of 1.34 (95% CI, 1.07 to 1.51).
Woodman et al47 found similar results in a study of 691
women diagnosed in 1991, in which those treated by general
surgeons, compared with those treated by gynecologists,
had an adjusted RR of death of 1.58 (95% CI, 1.19 to 2.10).
In this study, a surgeon’s volume was not predictive of
survival, but referral to a medical oncologist was strongly
predictive (RR, 0.54; 95% CI, 0.43 to 0.68).
2335
VOLUME/SPECIALIZATION AND CANCER CARE OUTCOMES
Table 10.
Stage
I
II
III
IV
Ovarian Cancer Survival by Physician’s Specialty, Diagnosed in 1983
No. of
Patients
1,377
448
1.355
1,080
5-Year Survival (mean ⫾ SD, %)
GYO
OBG
GS
88.6 ⫾ 2.5
62.6 ⫾ 5.9
25.2 ⫾ 2.6
10.4 ⫾ 2.6
89.6 ⫾ 1.1
60.9 ⫾ 3.1
29.2 ⫾ 1.9
16.8 ⫾ 1.8
87.8 ⫾ 2.1
47.4 ⫾ 5.5
16.8 ⫾ 2.0
10.9 ⫾ 1.6
NOTE. Data adapted from Nguyen et al.44
Abbreviations: GYO, gynecologic oncologist; OBG, general gynecologist; GS, general surgeon.
Only two studies addressed hospital factors. Junor et al48
audited 479 of the 533 new cases in Scotland in 1987.
Patients first seen or operated on by a nongynecologist had
worse mortality (RR 1.34 and 1.37, respectively; 95% CI,
1.05 to 1.77). Twenty-seven percent of patients were referred postoperatively to a multidisciplinary referral clinic.
After the adjustment for clinical factors and the use of
platinum chemotherapy (given to approximately 50% of
patients aged ⬍ 65 years), patients referred to the specialized center had a 0.73 RR of death. Munoz et al49 retrospectively assessed processes of care in 785 women in 1991
who were identified from SEER registries. Only 10% of
women with presumptive stages I and II disease, 71% with
stage III disease, and 53% with stage IV disease received
recommended staging and treatment. The only physician or
organizational feature assessed was whether the reporting
hospital had a gynecology residency program, and this
feature was associated with an increased odds ratio (1.9) for
appropriate care. No studies addressed the effect of provider
specialty in advanced ovarian cancer, such as physician
specialty effects on the use and patterns of chemotherapy,
survival, and elements of palliative care.
Cancers Principally Treated Nonsurgically
Lymphomas. Because chemotherapy and/or radiation
therapies are the primary treatments for lymphoma, they
should provide the best opportunity to find practice variation and infer quality differences in nonsurgical cancer care.
However, after an extensive search of the literature, no
studies were found since 1988. This is especially disappointing in light of the report of Davis et al,50 which
contrasted survival in 3,607 patients with Hodgkin’s disease
registered by SEER (community care) with 2,278 patients
treated at one of 21 comprehensive cancer centers, all of
whom were diagnosed between 1977 and 1982. Modest
differences in age, histology, and stage distributions were
adjusted for in the multivariate comparison. The rate of
death among patients initially treated at SEER hospitals was
higher (RR, 1.5; 95% CI, 1.3 to 1.7) than at comprehensive
centers and was consistently observed for all stages, histologies, and ages.
Testicular cancer. Only one American study of testicular cancer was found. An indirect, retrospective survival
comparison was performed by Feuer et al51 of patients with
metastatic testicular cancer treated at the Memorial SloanKettering Cancer Center (n ⫽ 133) and of cases identified
from five SEER registries (n ⫽ 172) from 1978 to 1984.
Although 89% of the SEER cases received chemotherapy
and 95% of these used cisplatin, the 3-year survival was
markedly better at the Memorial Sloan-Kettering Cancer
Center. This benefit in the latter group compared with the
former was more striking for patients with minimal or
moderate disease (94% v 73%) than for those with advanced
cases (52% v 40%, respectively). The authors speculated on
numerous potential sources for the better outcomes, including differences in chemotherapy regimen, dose-intensity,
salvage therapies, and institutional factors.
Three European studies have addressed hospital volume
primarily within participating centers in clinical trials.
Because hospitals that participate in clinical trials are likely
to be a self-selected group that are commonly expected to
have higher volume than nontrial hospitals, these are a
particularly compelling set of studies. Harding et al52
performed a population-based audit of 440 men diagnosed
between 1977 and 1989 with nonseminomatous germ cell
tumors in western Scotland. All but 11 patients were treated
at tertiary referral centers: 235 at a single unit and 194 at
four other units. Independent prognostic factors included
extent of tumor, 5-year period of diagnosis (1975 to 1979 v
1985 to 1989), and treatment unit (unit 1 v units 2 through
5). Unit 1 had the best survival rates, treated the most
patients (53%), and had the majority of patients (70%) with
the worst prognosis. Ninety-seven percent of patients at unit
1 versus 61% at units 2 through 5 were treated on a
nationally agreed protocol. After adjustment for prognostic
factors and for those treated on protocol, the risk of death
was much higher for patients outside of unit 1 (RR, 2.8; CI,
1.5 to 5.2). Collette et al53 analyzed 380 patients treated at
49 hospitals that participated in a European Organization for
Research and Treatment of Cancer trial of poor-prognosis
germ cell tumors. Patients who were treated in the 26
centers that each entered fewer than five patients and who
2336
HILLNER, SMITH, AND DESCH
represented 14% of all patients had an RR of death of 1.85
(95% CI, 1.16 to 3.03) and a 2-year survival rate of 62%
versus 77%, compared with the other 23 centers. Aass et
al54 noted a similar effect in an earlier, smaller study in
which 193 patients were studied who participated in clinical
trials at 14 Scandinavian centers between 1981 and 1986. A
multivariate analysis found that patients treated at the
institution with the highest volume (46%) after adjustment
for prognostic factors had a lower risk of death compared
with those treated at the other institutions (RR, 0.72; 3-year
survival rate, 84% v 60%, respectively).
Leukemia. The only study of acute leukemia care,
excluding those that considered transplantation, was of 879
adolescents and young adults diagnosed between 1984 and
1994 in regions of England and Wales that kept and
maintained leukemia registries.55 No differences in survival
were observed that were associated with treatment on a
national clinical trial, care at a teaching hospital, or hospital
annual case volume.
The International Bone Marrow Transplantation Registry
addressed the volume-outcome relationship with allotransplantation.56 Survival for 1,313 patients between 1983 and
1988 of HLA-identical sibling bone marrow transplantations for acute leukemia in first remission or chronic
myelogenous leukemia in first chronic phase was assessed
by center volume. Twenty-four percent of centers performed five or fewer transplantations per year, and five (6%)
performed more than 40 per year. After adjustment for
patient and disease characteristics, treatment-related mortality (RR, 1.53; P ⬍ .01) and treatment failure (RR, 1.38; P ⬍
.04) were higher at centers that performed five or fewer
transplantations per year. High-volume centers had an
absolute 10% benefit in 2-year survival compared with all
other centers (65% v 55%). No differences were observed in
centers that performed more than five but fewer or equal to
40 transplantations per year. This registry has not reported
any volume-outcome evaluations for other conditions.
DISCUSSION
Patients and their families are increasingly seeking information to guide their therapy for cancer. Sites related to
medical information are one of the largest categories of
Internet use. Although information is increasingly available,
it is often not readily understandable, of widely variable
accuracy, and of questionable relevance. In addition to
specific treatments, socioeconomic and organizational factors are known to affect processes and outcome for many
noncancer conditions. For cancer patients, does where they
live, insurance status, physician’s specialty, or type of medical
center and volume of cases of a specific cancer matter?
With the exception of factors associated with BCS and
local radiation for early-stage breast cancer, the answers are
unknown and, for most conditions, unexamined. This may
not be surprising because the organization of cancer care in
the United States is so diffuse and diverse that providers
have not had to be accountable for specific processes or
outcomes. Where organizational factors have been assessed,
the predominant relationship is between higher volumes and
better outcomes, particularly for complex surgical procedures.
Besides case volume, a variety of hospital or organizational factors, such as the breadth of services and technology, nurse staff levels, multidisciplinary teams, internal
quality programs, American Cancer Society or NCI designation, have been suggested to be associated with or to be
indicators of superior cancer care. We found only an
occasional study that considered these factors, likely because these factors are too detailed to abstract. For example,
studies of hospital characteristics include at most three
variables: size, residency status, and type (usually categorized as university, large community, or small community).
However, when available, these characteristics describe an
entire hospital, not just its cancer program. Additional,
unexplored factors that may affect oncology include the
stage of managed care in the local marketplace and other
indicators of competition. This does not mean, however,
that these factors do not have face validity or are not
important to insurers in their selection of physicians or
medical centers. One process area that may account for better
outcomes is the reorganizing of care from diversified locations
into a single-site multidisciplinary clinic. Although many
hospitals advertise their integrated approach for common
cancers, this benefit must be considered only to be intuitively
better because no pre- versus posttreatment comparisons from
single centers or between centers were found.
The motivations behind and limitations of the articles that
cited an association of higher volume with better outcome
could affect the strength of their methods and conclusions.
These include the importance and relevance of when data
was gathered, the data source itself, the completeness of
efforts to control and adjust for case mix, the motives of the
single supercenters who write about their superiority, and
the high probability of publication bias. All reports were
retrospective and predominantly used data collected in the
1980s. The question of the usefulness of such old data
highlights the need to create tools that allow collection that
is more rapid and timely for reporting. In this review, only
studies that stratified or adjusted for clinical stage were
included. In addition, each was assessed for whether it
identified and controlled for case mix by adjusting for
differences in demographics and comorbidity. However, the
ability to adequately control for case mix is weaker when
VOLUME/SPECIALIZATION AND CANCER CARE OUTCOMES
discharge summary diagnoses from administrative data are
used, which was the case in almost all studies, and not from
clinical databases.57
One interesting issue is how to assess single-institutions,
compared among themselves (all of which have complete
detailed data on their patients), with an external data set.
Examples of this are the comparisons of the surgical reports
from Johns Hopkins with the Maryland state hospital
discharge summaries, of Memorial Sloan-Kettering Cancer
Center with SEER, and of comprehensive cancer centers
with SEER. These reports each suggest that bigger is better
but are also consistent with studies published only for their
self-interest. Should these findings be viewed as analogous
to comparing phase II data with historical controls? The
absolute long-term survival differences between the highvolume and specialty centers in the care of breast cancer,
Hodgkin’s disease, and testicular and ovarian cancers were all
markedly greater than the overall temporal trend of improvements in survival over the last 20 years. Were there subtle
differences in the populations that attended SEER sites and
non–Johns Hopkins hospitals, or should major quality improvement efforts begin to include the direction of patients to
selected centers? Ultimately, the question is who should judge
and on what data should this judgement be based.
Although a relationship between higher volume and
better outcome is intuitively attractive, it is often difficult to
determine the direction of the causal relationship: whether
volume affects quality or whether better units and clinicians
attract more patients.10,58 If the relationship is true, why are
higher volume centers associated with better outcomes? For
30-day mortality, the associated processes are predominantly the technical expertise of the primary physician,
usually a surgeon, and his or her team. The advocate of the
high-volume center will speculate that the surgeon does a
more complete primary procedure, that the care of the
intensive care unit is more effective, and that the increased
availability of consultants and the relationship between
high-volume surgeons and high-volume radiation therapists
or medical oncologists improve the hand off of care into the
adjuvant setting. What have not yet been dissected are the
individual processes, such as the use of specific procedures
or drugs that could be included in a practice guideline. The
skeptic will point out that most noncancer studies that make
the best adjustments for case mix show less benefit from
increased volume and a decreasing effect over time. A
research agenda that addresses this issue should be initiated
now, with or without efforts to concentrate care today.
The relationship between volume and outcome deserves
careful study to determine the clinical differences that
produce the better outcome. As Hannan58 noted in a recent
editorial related to hospital volume and outcomes for acute
2337
myocardial infarction, a dialog between providers, insurers,
and the general public needs to begin regarding how these
studies should be incorporated into policies aimed at improving the quality of care. Results presented here should
prompt patients and their families to seek out high-volume
services. However, there will be varying levels of resistance
to patients moving large distances for their care. Of all
patients with breast or lung cancer, only approximately 4%
are treated at NCI-designated centers and another 17% at
teaching hospitals. Alternatively, if the clinical mechanisms
that explain these differences were clearer, local initiatives
could be put into place that address shortcomings that would
improve results. Acting on the results presented above may
change outcomes for large populations of patients. However, which action to take to define models of excellence,
such as moving patients, providing better training, or
requiring local attention to specific clinical procedures, is
difficult to sort out based on current information.59
Assuming that the volume-outcome relationship holds up
to careful scrutiny, it will be important to ask how specialized the specialist has to be to achieve the best outcome and
who will set the thresholds. How few is enough is a highly
charged issue, particularly among surgeons. For instance,
should the initial treatment of sarcoma be performed by a
general surgeon, a surgical oncologist, a specialized sarcoma surgical oncologist, or a specialized sarcoma surgical
oncologist only if he or she operates in a high-volume
hospital with a designated sarcoma service? Is it proper for
a community medical oncologist to provide adjuvant therapy for breast cancer, or should all women who require
adjuvant therapy be treated by a breast cancer medical
oncologist at a special site that may be 100 miles away?
These are the central questions in response to these findings.
There is no evidence to support the claim that care in the
United States for the less common cancers is currently being
directed to high-volume centers based on data from National
Cancer Database reports (Table 11). For testicular and pancreatic cancer, both relatively rare and with strong evidence of a
volume-outcome effect, the distribution of treatment location
was no different from that of the most common cancers. The
national median hospital volume for new cases of ovarian
cancer was only 11 cases per year in 1993.64
The image of insurers and regulators as those who
construct barriers to care is evolving. For years, many
insurers have had centers of excellence programs for organ
transplantation. At least one national insurer (UnitedHealthcare, Minneapolis, MN) intends to soon open a similar
program for cancer surgery (Richard Watt, personal communication, December 1999). An important concern of
patients is whether their insurers impede prompt access to
cancer-specific evaluation and specialty care. Variation in
2338
HILLNER, SMITH, AND DESCH
Table 11.
Cancer
Source
Uncommon
Pancreas
Testes
Common
Lung
Colon
Breast
Stratification of Relative Percent of Individual Cancers Initially Treated by the Total Annual Hospital Cancer Volume
Annual Hospital Cancer Volume for New Cases of All Types (%)
⬎ 1000
500-599
150-499
⬍ 150
Unknown
32.0
36.6
37.7
35.0
18.3
19.2
0.7
8.0
11.2
1.2
29.0
30.0
35.2
40.7
42.5
41.5
20.4
23.5
19.8
0.9
2.4
1.6
8.9
1.6
1.9
NOTE. Data abstracted from National Cancer Database reports on cancer of the pancreas,13 testes,60 lung,61 Colon,62 and breast.63
indicators of the process of care, such as delays in getting to
see a physician or specialist, and clinical process indicators
in the perioperative, adjuvant, or follow-up care are major
concerns of patients, advocacy groups, and clinicians. Barriers on a case-by-case basis certainly exist. Most patients
are familiar with techniques of health care rationing through
inconvenience, such as prolonged waiting on hold while on
the telephone, preauthorization of services being referred
for review, and limited access to emergency care. However,
a detailed dissection of the taxonomy by cancer type,
insurer, location, and type of treatment will be needed to
determine this effect on processes and outcomes.
The appropriateness of physician self-referral is an ongoing ethical and economic challenge in oncology. It is
uncertain whether it is a problem of quality for the most
common cancer, but it is an obvious barrier to concentration
of care. The number of surgeons who performed colectomies for colorectal cancer in Maryland was approximately
three-fold that in Ireland in 1989. Mitchell and Sunshine65
found that the frequency and costs of radiation therapy at
free-standing centers in Florida were 40% to 60% higher
than in the rest of the country. Medical oncologists are the
only specialty physicians to sell a high-priced, high-volume
commodity from their practice. Kurowski66 reports that
40% to 60% of a medical oncologist’s income is derived
from revenue related to office-based drug administration.
Whether these issues relate to differences in quality and
patient outcomes in unknown. Future studies could audit
processes of care for appropriateness and use the financial
organization of the site of care as the unit of analysis.
Lastly, should either the public or insurers give cancer merit
special attention, compared with all other medical conditions,
in explicitly defining quality? We believe the answer is yes, but
it will require substantial changes in how information is
collected and shared. The focus needs to shift from quantifying
the cancer burden to how to maximize the quality of its care.
Cancer is the number-one health condition that the public fears,
and there is only one chance for cure, if there is one at all. From
a conceptual framework, cancer also has compelling data
characteristics that can be readily combined to define prospectively quality processes (Table 12).67 First, it is necessary to
know when disease is first identified. Cancer is the only
chronic disease, other than human immunodeficiency virus, for
which the incidences are registered. Second, disease severity
must be known when the disease is first identified. The
tumor-node-metastasis system for cancer is the most widely
agreed on taxonomy for severity of any medical condition.
These two essential elements are collected by national registries. However, because these data are hospital-based, they are
not readily available to insurers, providers, patients, or researchers. Third, the relevant processes of care must be defined
and tracked. Obtaining this information will be the primary
barrier. Processes of care that describe evaluation and treatment are principally documented in administrative claims that
may not be available at the particular hospital that is the site of
the cancer registry. New creative arrangements and alliances
need to be explored that allow different sources to exchange
data in a much more real-time, anonymous manner. Fourth,
substantial variation in processes and outcomes of cancer care
exist as noted in this review. Lastly, a relationship between the
process of care and outcomes must be established. This
relationship may seem obvious but has only been shown for
selected high-risk surgery. The process factors associated with
long-term recurrence-free or overall survival, such as coordination between specialists and the use of adjuvant therapy,
have only been superficially studied.
In 1996, the National Coalition for Cancer Survivorship
prepared a report on imperatives and principles for quality
Table 12.
●
●
●
●
Data Elements Needed for Identifying Quality Care
When is condition first identified?
How severe is the disease (stage)?
Processes of care units must be defined.
Meaningful variation in processes and outcomes of care must be
identified.
● Relationship between processes of care and outcomes must be
established.
2339
VOLUME/SPECIALIZATION AND CANCER CARE OUTCOMES
of cancer care, which was followed in 1998 by an American
Federation of Clinical Oncologic Societies statement related
to access to quality cancer care.68,69 Neither of these seems
to have initiated change on the national level to define and
measure a core set of quality indicators for cancer. In April
1999, the National Cancer Policy Board made 10 detailed
recommendations for ensuring quality cancer care. This
report provides strong background for the Policy Board’s
first recommendation: “Ensure that patients undergoing
procedures that are technically difficult to perform and have
been associated with higher mortality in lower-volume
settings receive care at facilities with extensive experience.“
This should be done concurrently with the development,
measurement, and monitoring of a core set of quality
measures for cancer for which hospitals, provider groups,
and managed care systems should be accountable.1
REFERENCES
1. Ensuring Quality Cancer Care. Washington, DC, National Academy Press, 1999
2. Luft HS, Bunker JP, Enthoven AC: Should operations be regionalized? The empirical relation between surgical volume and mortality.
N Engl J Med 301:1364-1369, 1979
3. Medicare: A strategy for quality assurance. Washington, DC,
National Academy Press, 1990
4. Blumenthal D: Part 1: Quality of care—What is it? [see comments] N Engl J Med 335:891-894, 1996 (editorial)
5. Brook RH, McGlynn EA, Cleary PD: Quality of health care: Part
2—Measuring quality of care [see comments]. N Engl J Med 335:966970, 1996 (editorial)
6. Cella DF, Orav EJ, Kornblith AB, et al: Socioeconomic status and
cancer survival. J Clin Oncol 9:1500-1509, 1991
7. Lu-Yao GL, McLerran D, Wasson J, et al: An assessment of
radical prostatectomy: Time trends, geographic variation, and outcomes. JAMA 269:2633-2636, 1993
8. Nattinger AB, Gottlieb MS, Veum J, et al: Geographic variation
in the use of breast-conserving treatment for breast cancer [see
comments]. N Engl J Med 326:1102-1107, 1992
9. Grilli R, Minozzi S, Tinazzi A, et al: Do specialists do it better?
The impact of specialization on the processes and outcomes of care for
cancer patients. Ann Oncol 9:365-374, 1998
10. Sowden AJ, Deeks JJ, Sheldon TA: Volume and outcome in
coronary artery bypass graft surgery: True association or artefact? [see
comments]. BMJ 311:151-155, 1995
11. Glasgow RE, Mulvihill SJ: Hospital volume influences outcome
in patients undergoing pancreatic resection for cancer. West J Med
165:294-300, 1996
12. Lieberman MD, Kilburn H, Lindsey M, et al: Relation of
perioperative deaths to hospital volume among patients undergoing
pancreatic resection for malignancy. Ann Surg 222:638-645, 1995
13. Janes RH Jr, Niederhuber JE, Chmiel JS, et al: National patterns
of care for pancreatic cancer: Results of a survey by the Commission on
Cancer. Ann Surg 223:261-272, 1996
14. Gordon TA, Burleyson GP, Tielsch JM, et al: The effects of
regionalization on cost and outcome for one general high-risk surgical
procedure [see comments]. Ann Surg 221:43-49, 1995
15. Gordon TA, Bowman HM, Tielsch JM, et al: Statewide regionalization of pancreaticoduodenectomy and its effect on in-hospital
mortality. Ann Surg 228:71-78, 1998
16. Sosa JA, Bowman HM, Gordon TA, et al: Importance of
hospital volume in the overall management of pancreatic cancer. Ann
Surg 228:429-438, 1998
17. Birkmeyer JD, Warshaw AL, Finlayson SR, et al: Relationship
between hospital volume and late survival after pancreaticoduodenectomy. Surgery 126:178-183, 1999
18. Begg CB, Cramer LD, Hoskins WJ, et al: Impact of hospital
volume on operative mortality for major cancer surgery [see comments]. JAMA 280:1747-1751, 1998
19. Patti MG, Corvera CU, Glasgow RE, et al: A hospital’s annual
rate of esophagectomy influences the operative mortality rate.
J Gastrointest Surg 2:186-192, 1998
20. Choti MA, Bowman HM, Pitt HA, et al: Should hepatic
resections be performed at high-volume referral centers? J Gastrointest
Surg 2:11-20, 1998
21. Ginsberg RJ, Vokes EE: Non-small cell lung cancer, in Devita
VT, Hellman S, Rosenberg SA (eds): Cancer: Principles and Practice of
Oncology. Philadelphia, PA, Lippincott-Raven, 1997, pp 858-910
22. Whittle J, Steinberg EP, Anderson GF, et al: Use of Medicare
claims data to evaluate outcomes in elderly patients undergoing lung
resection for lung cancer [see comments]. Chest 100:729-734, 1991
23. Romano PS, Mark DH: Patient and hospital characteristics
related to in-hospital mortality after lung cancer resection. Chest
101:1332-1337, 1992
24. Silvestri GA, Handy J, Lackland D, et al: Specialists achieve
better outcomes than generalists for lung cancer surgery [see comments]. Chest 114:675-680, 1998
25. McArdle CS, Hole D: Impact of variability among surgeons on
postoperative morbidity and mortality and ultimate survival [see
comments]. BMJ 302:1501-1505, 1991
26. Kingston RD, Walsh S, Jeacock J: Curative resection: The major
determinant of survival in patients with large bowel cancer. J R Coll
Surg Edinb 36:298-302, 1991
27. Mella J, Biffin A, Radcliffe AG, et al: Population-based audit of
colorectal cancer management in two UK health regions: Colorectal
Cancer Working Group, Royal College of Surgeons of England
Clinical Epidemiology and Audit Unit. Br J Surg 84:1731-1736, 1997
28. Kee F, Wilson RH, Harper C, et al: Influence of hospital and
clinician workload on survival from colorectal cancer: Cohort study
[see comments]. BMJ 318:1381-1385, 1999
29. Harmon JW, Tang DG, Gordon TA, et al: Hospital volume can
serve as a surrogate for surgeon volume for achieving excellent
outcomes in colorectal resection. Ann Surg 230:404-411, 1999
30. Khuri SF, Daley J, Henderson, et al: Relation of surgical volume
to outcome in eight common operations: Results from the VA National
Surgical Quality Improvement Program. Ann Surg 230:414-429,
1999
31. Rosen L, Stasik JJ Jr, Reed JF III, et al: Variations in colon and
rectal surgical mortality: Comparison of specialties with a statelegislated database. Dis Colon Rectum 39:129-135, 1996
32. Porter GA, Soskolne CL, Yakimets WW, et al: Surgeon-related
factors and outcome in rectal cancer [see comments]. Ann Surg
227:157-167, 1998
2340
32a. Holm T, Johansson H, Cedermark B, et al: Influence of hospital
and surgeon-related factors on outcome of rectal cancer with or without
preoperative radiotherapy. Br J Surg 84:657-663, 1997
33. Sainsbury R, Haward B, Rider L, et al: Influence of clinician
workload and patterns of treatment on survival from breast cancer.
Lancet 345:1265-1270, 1995
34. Gillis CR, Hole DJ: Survival outcome of care by specialist
surgeons in breast cancer: A study of 3786 patients in the west of
Scotland [see comments]. BMJ 312:145-148, 1996
35. Bonett A, Roder D, Esterman A: Case-survival rates for infiltrating ductal carcinomas by category of hospital at diagnosis in South
Australia. Med J Aust 154:695-697, 1991
36. Roohan PJ, Bickell NA, Baptiste MS, et al: Hospital volume
differences and five-year survival from breast cancer. Am J Public
Health 88:454-457, 1998
37. Lee-Feldstein A, Anton-Culver H, Feldstein PJ: Treatment
differences and other prognostic factors related to breast cancer
survival: Delivery systems and medical outcomes [see comments].
JAMA 271:1163-1168, 1994
38. Guadagnoli E, Weeks JC, Shapiro CL, et al: Use of breastconserving surgery for treatment of stage I and stage II breast cancer.
J Clin Oncol 16:101-106, 1998
39. Guadagnoli E, Shapiro CL, Weeks JC, et al: The quality of care
for treatment of early stage breast carcinoma: Is it consistent with
national guidelines? Cancer 83:302-309, 1998
40. Johnson TP, Ford L, Warnecke RB, et al: Effect of a National
Cancer Institute Clinical Alert on breast cancer practice patterns. J Clin
Oncol 12:1783-1788, 1994
41. Solin LJ, Fowble BL, Martz KL, et al: Results of the 1983
patterns of care process survey for definitive breast irradiation. Int J
Radiat Oncol Biol Phys 20:105-111, 1991
42. Kutcher GJ, Smith AR, Fowble BL, et al: Treatment planning
for primary breast cancer: A patterns of care study. Int J Radiat Oncol
Biol Phys 36:731-737, 1996
43. Yao SL, Lu-Yao G: Population-based study of relationships
between hospital volume of prostatectomies, patient outcomes, and
length of hospital stay. J Natl Cancer Inst 91:1950-1956, 1999
44. Nguyen HN, Averette HE, Hoskins W, et al: National survey of
ovarian carcinoma: Part V—The impact of physician’s specialty on
patients’ survival. Cancer 72:3663-3670, 1993
45. Karakiewicz PI, Bazinet M, Aprikian AG, et al: Thirty-day
mortality rates and cumulative survival after radical retropubic prostatectomy. Urology 52:1041-1046, 1998
46. Kehoe S, Powell J, Wilson S, et al: The influence of the
operating surgeon’s specialisation on patient survival in ovarian carcinoma. Br J Cancer 70:1014-1017, 1994
47. Woodman C, Baghdady A, Collins S, et al: What changes in the
organisation of cancer services will improve the outcome for women
with ovarian cancer? Br J Obstet Gynaecol 104:135-139, 1997
48. Junor EJ, Hole DJ, Gillis CR: Management of ovarian cancer:
Referral to a multidisciplinary team matters. Br J Cancer 70:363-370,
1994
49. Munoz KA, Harlan LC, Trimble EL: Patterns of care for women
with ovarian cancer in the United States. J Clin Oncol 15:3408-3415,
1997
50. Davis S, Dahlberg S, Myers MH, et al: Hodgkin’s disease in the
United States: A comparison of patient characteristics and survival in
the Centralized Cancer Patient Data System and the Surveillance,
Epidemiology, and End Results Program. J Natl Cancer Inst 78:471478, 1987
HILLNER, SMITH, AND DESCH
51. Feuer EJ, Frey CM, Brawley OW, et al: After a treatment
breakthrough: A comparison of trial and population-based data for
advanced testicular cancer. J Clin Oncol 12:368-377, 1994
52. Harding MJ, Paul J, Gillis CR, et al: Management of malignant
teratoma: Does referral to a specialist unit matter? [see comments]
Lancet 341:999-1002, 1993
53. Collette L, Sylvester RJ, Stenning SP, et al: Impact of the
treating institution on survival of patients with “poor-prognosis”
metastatic nonseminoma: European Organization for Research and
Treatment of Cancer Genito-Urinary Tract Cancer Collaborative Group
and the Medical Research Council Testicular Cancer Working Party
[see comments]. J Natl Cancer Inst 91:839-846, 1999
54. Aass N, Klepp O, Cavallin-Stahl E, et al: Prognostic factors in
unselected patients with nonseminomatous metastatic testicular cancer:
A multicenter experience. J Clin Oncol 9:818-826, 1991
55. Stiller CA, Benjamin S, Cartwright RA, et al: Patterns of care
and survival for adolescents and young adults with acute leukaemia: A
population-based study. Br J Cancer 79:658-665, 1999
56. Horowitz MM, Przepiorka D, Champlin RE, et al: Should
HLA-identical sibling bone marrow transplants for leukemia be restricted to large centers? [see comments] Blood 79:2771-2774, 1992
57. Jollis JG, Ancukiewicz M, DeLong ER, et al: Discordance of
databases designed for claims payment versus clinical information
systems. Ann Intern Med 119:844-850, 1993
58. Hannan EL: The relation between volume and outcome in health
care. N Engl J Med 340:1677-1679, 1999 (editorial)
59. Smith TJ, Hillner BE, Desch CE: The Quality of Cancer Care:
Models of Excellence. Background paper prepared from the National
Cancer Policy Board, 1999. http://www4.nas.edu/IOM/IOMHome.nsf/
Pages/National%2bCancer%2bPolicy%2bBoard1999. Accessed July 8,
1999
60. Steele GS, Richie JP, Stewart AK, et al: The national cancer data
base report on patterns of care for testicular carcinoma, 1985-. Cancer
86:2171-2183, 1999
61. Fry WA, Menck HR, Winchester DP: The National Cancer Data
Base report on lung cancer. Cancer 77:1947-1955, 1996
62. Jessup JM, McGinnis LS, Steele GD Jr, et al: The National
Cancer Data Base: Report on colon cancer. Cancer 78:918-926, 1996
63. Jessup JM, Menck HR, Winchester DP, et al: The National
Cancer Data Base report on patterns of hospital reporting. Cancer
78:1829-1837, 1996
64. Partridge EE, Phillips JL, Menck HR: The National Cancer Data
Base report on ovarian cancer treatment in United States hospitals.
Cancer 78:2236-2246, 1996
65. Mitchell JM, Sunshine JH: Consequences of physicians’ ownership of health care facilities: Joint ventures in radiation therapy [see
comments]. N Engl J Med 327:1497-1501, 1992
66. Kurowski B: Cancer carve outs, specialty networks, and disease
management: A review of their evolution, effectiveness, and prognosis.
Am J Manag Care 4:SP71-SP89, 1998 (suppl)
67. Hillner BE, Smith TJ: Hospital volume and patient outcomes in
major cancer surgery: A catalyst for quality assessment and concentration of cancer services. JAMA 280:1783-1784, 1998 (editorial)
68. Imperatives for Quality Cancer Care: Access, Advocacy, Action, and Accountability, 1996. [Position paper presented at the
Congress Leadership Forum and posted on CancerNet, a Web site of
the National Cancer Institute.] http://cancernet.nci.nih.gov/imperatives/
quality.htm. Accessed July 8, 1999
69. Access to quality cancer care: Consensus statement—American
Federation of Clinical Oncologic Societies [published erratum appears
in J Clin Oncol 16:2001, 1998]. J Clin Oncol 16:1628-1630, 1998