Association Between the Medicare Modernization Act of 2003 and Patient Wait Times and Travel Distance for Chemotherapy

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Abstract
The Medicare Prescription Drug, Improvement, and Modernization Act of 2003 (MMA) altered reimbursements for outpatient chemotherapy drugs and drug administration services. Anecdotal reports suggest that these adjustments may have negatively affected access to chemotherapy for Medicare beneficiaries. To compare patient wait times and travel distances for chemotherapy before and after the enactment of the MMA. Analysis of a nationally representative 5% sample of claims from the Centers for Medicare & Medicaid Services for the period 2003 through 2006. Patients were Medicare beneficiaries with incident breast cancer, colorectal cancer, leukemia, lung cancer, or lymphoma who received chemotherapy in inpatient hospital, institutional outpatient, or physician office settings. Days from incident diagnosis to first chemotherapy visit and distance traveled for treatment, controlling for age, sex, race/ethnicity, cancer type, geographic region, comorbid conditions, and year of diagnosis and treatment. There were 5082 incident cases of breast cancer, colorectal cancer, leukemia, lung cancer, or lymphoma in 2003; 5379 cases in 2004; 5116 cases in 2005; and 5288 cases in 2006. Approximately 70% of patients received treatment in physician office settings in each year. Although the distribution of treatment settings in 2004 and 2005 was not significantly different from 2003 (P = .24 and P = .72, respectively), there was a small but significant change from 2003 to 2006 (P = .02). The proportion of patients receiving chemotherapy in inpatient settings decreased from 10.2% in 2003 to 8.8% in 2006 (P = .03), and the proportion in institutional outpatient settings increased from 21.1% to 22.5% (P = .004). The proportion in physician offices remained at 68.7% (P = .29). The median time from diagnosis to initial chemotherapy visit was 28 days in 2003, 27 days in 2004, 29 days in 2005, and 28 days in 2006. In multivariate analyses, average wait times for chemotherapy were 1.96 days longer in 2005 than in 2003 (95% confidence interval [CI], 0.11-3.80 days; P = .04) but not significantly different in 2006 (0.88 days; 95% CI, -0.96 to 2.71 days; P = .35). Median travel distance was 7 miles (11.2 km) in 2003 and 8 miles (12.8 km) in 2004 through 2006. After adjustment, average travel distance remained slightly longer in 2004 (1.47 miles [2.35 km]; 95% CI, 0.87-2.07 miles [1.39-3.31 km]; P < .001), 2005 (1.19 miles [1.90 km]; 95% CI, 0.58-1.80 miles [0.93-2.88 km]; P < .001), and 2006 (1.30 miles [2.08 km]; 95% CI, 0.69-1.90 miles [1.10-3.04 km]; P < .001) compared with 2003. There have not been major changes in travel distance and patient wait times for chemotherapy in the Medicare population since 2003, the year before MMA-related changes in reimbursement.

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ORIGINAL CONTRIBUTION
Association Between the Medicare
Modernization Act of 2003 and Patient Wait
Times and Travel Distance for Chemotherapy
Alisa M. Shea, MPH
Lesley H. Curtis, PhD
Bradley G. Hammill, MS
Lisa D. DiMartino, MPH
Amy P. Abernethy, MD
Kevin A. Schulman, MD
I
N ADDITION TO ESTABLISHING AN
outpatient prescription drug ben-
efit for Medicare beneficiaries, the
Medicare Prescription Drug, Im-
provement, and Modernization Act of
2003 (MMA) changed physician reim-
bursement for chemotherapy-related
drugs and administration services. Be-
fore the enactment of the MMA, Medi-
care reimbursement to physicians for
chemotherapy drugs often exceeded ac-
quisition costs
1
because many physi-
cians obtained the drugs at substan-
tially discounted prices. Some estimates
placed Medicare payments at 3 times
the cost of acquisition.
2
In an effort to curtail this overpay-
ment and align reimbursement more
closely with market prices, the MMA
reduced payments for chemotherapy
drugs from 95% of average wholesale
prices in 2003 to 85% in 2004. In 2005,
payments were further reduced to 106%
of manufacturer-reported average sales
prices, which reflect the actual trans-
action prices of drug acquisition and are
typically lower than the correspond-
ing wholesale values.
3
To offset the re-
ductions, the MMA also increased re-
imbursement for drug administration
services.
4
The US Government Account-
ability Office estimated conservatively
that Medicare payments for the 16 most
commonly billed chemotherapy-
related drugs would continue to ex-
ceed physicians’ costs after the changes
Author Affiliations are listed at the end of this article.
Corresponding Author: Lesley H. Curtis, PhD, Cen-
ter for Clinical and Genetic Economics, Duke Clinical
Research Institute, PO Box 17969, Durham, NC 27715
(lesley.curtis@duke.edu).
Context The Medicare Prescription Drug, Improvement, and Modernization Act of
2003 (MMA) altered reimbursements for outpatient chemotherapy drugs and drug
administration services. Anecdotal reports suggest that these adjustments may have
negatively affected access to chemotherapy for Medicare beneficiaries.
Objective To compare patient wait times and travel distances for chemotherapy be-
fore and after the enactment of the MMA.
Design, Setting, and Patients Analysis of a nationally representative 5% sample
of claims from the Centers for Medicare & Medicaid Services for the period 2003 through
2006. Patients were Medicare beneficiaries with incident breast cancer, colorectal can-
cer, leukemia, lung cancer, or lymphoma who received chemotherapy in inpatient hos-
pital, institutional outpatient, or physician office settings.
Main Outcome Measures Days from incident diagnosis to first chemotherapy visit
and distance traveled for treatment, controlling for age, sex, race/ethnicity, cancer type,
geographic region, comorbid conditions, and year of diagnosis and treatment.
Results There were 5082 incident cases of breast cancer, colorectal cancer, leukemia,
lung cancer, or lymphoma in 2003; 5379 cases in 2004; 5116 cases in 2005; and 5288 cases
in 2006. Approximately 70% of patients received treatment in physician office settings in
each year. Although the distribution of treatment settings in 2004 and 2005 was not sig-
nificantly different from 2003 (P=.24 and P=.72, respectively), there was a small but sig-
nificant change from 2003 to 2006 (P=.02). The proportion of patients receiving chemo-
therapy in inpatient settings decreased from 10.2% in 2003 to 8.8% in 2006 (P=.03), and
the proportion in institutional outpatient settings increased from 21.1% to 22.5% (P=.004).
The proportion in physician offices remained at 68.7% (P=.29). The median time from di-
agnosis to initial chemotherapy visit was 28 days in 2003, 27 days in 2004, 29 days in 2005,
and 28 days in 2006. In multivariate analyses, average wait times for chemotherapy were
1.96 days longer in 2005 than in 2003 (95% confidence interval [CI], 0.11-3.80 days; P=.04)
but not significantly different in 2006 (0.88 days; 95% CI, –0.96 to 2.71 days; P=.35). Me-
dian travel distance was 7 miles (11.2 km) in 2003 and 8 miles (12.8 km) in 2004 through
2006. After adjustment, average travel distance remained slightly longer in 2004 (1.47 miles
[2.35 km]; 95% CI, 0.87-2.07 miles [1.39-3.31 km]; P.001), 2005 (1.19 miles [1.90 km];
95% CI, 0.58-1.80 miles [0.93-2.88 km]; P.001), and 2006 (1.30 miles [2.08 km]; 95%
CI, 0.69-1.90 miles [1.10-3.04 km]; P.001) compared with 2003.
Conclusion There have not been major changes in travel distance and patient wait
times for chemotherapy in the Medicare population since 2003, the year before MMA-
related changes in reimbursement.
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Page 1
in reimbursement but by a smaller mar-
gin (22% in 2004 and 6% in 2005).
1
Changes mandated by the MMA were
directed at physician reimbursement
and did not include substantial changes
in reimbursement to institutions.
Therefore, there was concern that the
reduction in physician reimburse-
ment would lead to closures of some
private oncology practices, requiring the
80% of cancer patients who receive
treatment in community settings to
travel farther from their homes to lo-
cal hospitals for treatment.
5-9
More-
over, without sufficient opportunity to
plan and expand their services and
without financial incentive to do so,
hospital-based clinics might not have
adequate resources to support the an-
ticipated rapid influx of patients seek-
ing chemotherapy, thereby further de-
laying provision of care.
7
Opponents of
the MMA also warned that quality of
care might be negatively affected be-
cause financial constraints would ne-
cessitate the elimination of nursing and
support staff
4
and because cost shift-
ing to patients in the form of co-
payments might lead some patients to
forgo care altogether.
10
Despite these concerns, recent stud-
ies by the Medicare Payment Advisory
Commission (MedPAC) and the Na-
tional Patient Advocate Foundation
found that patients were generally sat-
isfied with their care and did not per-
ceive changes in treatment following the
enactment of the MMA.
3,10,11
Still, there
is limited empirical evidence about
whether changes in reimbursement
policy have influenced the location or
timeliness of chemotherapy. There-
fore, we examined patient wait times
and travel distance for chemotherapy
before and after the enactment of the
MMA in a nationally representative
sample of Medicare beneficiaries from
2003 through 2006.
METHODS
We analyzed a 5% national sample of
Medicare standard analytic files and cor-
responding denominator files for inpa-
tient, outpatient, carrier, and durable
medical equipment claims. The files are
available from the Centers for Medi-
care & Medicaid Services (CMS) and
represent a quasi-random sample of 5%
of all Medicare beneficiaries. Beneficia-
ries are selected for the sample based
on the last 2 digits of their Medicare
beneficiary identification number.
12
The
inpatient files contain institutional
claims for facility costs covered under
Medicare Part A, and the outpatient files
contain claims by institutional outpa-
tient providers (eg, hospital outpa-
tient departments, ambulatory sur-
gery centers). The carrier files contain
provider claims for services covered un-
der Medicare Part B. The denominator
files contain beneficiary identifiers, sex,
race/ethnicity, birth dates, dates of
death, zip codes, and information about
program eligibility and enrollment.
We obtained all files for calendar
years 2002 through 2006 from CMS.
We eliminated invalid records and lim-
ited the analysis to persons living in the
United States. For the carrier claims, we
used the provider zip codes in the CMS
files to determine locations of treat-
ment. For inpatient and outpatient in-
stitutional claims, we linked Medicare
provider identification numbers to
Medicare cost report data to deter-
mine facility zip codes. The institu-
tional review board of the Duke Uni-
versity Health System approved the
study.
Study Population
We included Medicare beneficiaries for
whom a diagnosis of breast cancer (In-
ternational Classification of Diseases,
Ninth Revision, Clinical Modification
[ICD-9-CM] diagnosis codes 174.0-
174.9, 175.0-175.9, 233.0, and V10.3),
colorectal cancer (codes 153.0-153.9,
154.0-154.8, 230.3-230.6, 159.0,
V10.05, and V10.06), leukemia (codes
200.00-200.88, 202.00-202.28, 202.80-
202.98, V10.71, and V10.79), lung can-
cer (codes 162.2-162.9, 231.2, and
V10.11), or lymphoma (codes 202.40-
202.48, 203.10, 204.00, 204.10, 204.20,
204.80, 204.90, 205.00, 205.10, 205.20,
205.80, 205.90, 206.00, 206.10, 206.20,
206.80, 206.90, 207.00, 207.10, 207.20,
207.80, 208.00, 208.10, 208.20, 208.80,
208.90, V10.60-V10.63, and V10.69)
was reported on a single inpatient, out-
patient, carrier, or durable medical
equipment claim. We selected these
cancer types because they are preva-
lent among elderly persons and che-
motherapy is often indicated.
To specify the date of disease onset,
we used the date of the earliest ob-
served cancer claim. To be considered
a new-onset or incident case, we re-
quired beneficiaries to have had no
claims for any of the 5 cancer types in
the previous calendar year. Note that
this method does not prohibit the in-
clusion of patients with relapsed dis-
ease who may also have met this crite-
rion. Therefore, the study sample
represents a combination of incident
and relapsed cases. We limited the
sample to beneficiaries aged 67 years
or older to minimize the risk of mis-
classifying prevalent cases as incident.
In the event that a beneficiary was iden-
tified as having an incident case of more
than 1 of the 5 cancer types in a given
year, we retained the claim with the ear-
liest incident date for the analysis.
Inclusion in the incident cohort was
conditional on survival to chemo-
therapy, and the initial chemotherapy
visit was required to be in the same cal-
endar year as the incident diagnosis
(ICD-9-CM diagnosis code V58.1
[V58.11 in 2006]; ICD-9-CM proce-
dure code 99.25; and Current Proce-
dural Terminology, Fourth Edition/
Healthcare Common Procedure Coding
System, Level II, National Codes 96400-
96549, G0345-G0362, Q0083-
Q0085, and J8510-J9999 [C8953-
C8955 in 2006 only]). To identify the
date of the first chemotherapy visit, we
used the date of the earliest observed
chemotherapy claim following an in-
cident cancer diagnosis. We deter-
mined treatment setting from the file
type in which the claim was observed.
Claims in inpatient files represent ser-
vices provided in inpatient facilities.
Claims in outpatient files represent ser-
vices in institutional outpatient facili-
ties, such as hospital outpatient depart-
ments and rural health clinics. Claims
in carrier files are submitted by non-
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196 JAMA, July 9, 2008—Vol 300, No. 2 (Reprinted) ©2008 American Medical Association. All rights reserved.
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tings increased from 21.1% to 22.5%
(P= .004). The proportion of patients
in physician offices remained at 68.7%
(P= .29).
The median wait time for treatment
was about 28 days (T
ABLE 2). Wait
times were shortest for patients under-
going chemotherapy in inpatient set-
tings and longest for patients in insti-
tutional outpatient settings. The median
wait time for treatment in physician of-
fices increased significantly from 29
days in 2003 to 31 days in 2005
(P .001). However, the median wait
time in 2006 was not significantly dif-
ferent from 2003 for any of the treat-
ment settings. Median travel distance
was approximately 8 miles (12.8 km)
and varied little by treatment setting.
Between 2003 and 2006, median travel
distance increased from 7 miles (11.2
km) to 9 miles (14.4 km) for inpatient
settings (P= .01) and from 7 miles to 8
miles for physician offices (P .001)
but remained at 7 miles for institu-
tional outpatient settings (P=.04).
T
ABLE 3 shows median wait times by
cancer type in 2003 and 2006. In both
years, wait times were shorter for pa-
tients with leukemia, lung cancer, or
lymphoma than for patients with breast
or colorectal cancer. Wait times in-
creased by 5 days for patients with co-
lorectal cancer (P=.07) and by 3 days
for patients with breast cancer (P=.15)
or lung cancer (P.001). Wait times de-
creased by 2.5 days for patients with leu-
kemia (P=.15) and by 3 days for pa-
tients with lymphoma (P=.006). Wait
times for patients in rural locations were
3 days longer in 2006 than in 2003
(P =.04), whereas wait times for pa-
tients in urban locations were 1 day
shorter (P=.05) (Table 3). At the 75th
percentile, wait times for patients in ru-
ral locations increased by 5 days. Me-
dian wait times for patients aged 75 years
or older were unchanged (P =.70),
whereas wait times for patients younger
than 75 years increased by 1 day
(P =.80). Similarly, wait times in-
creased by 1 day for patients in coun-
ties with the least poverty (P=.03) but
decreased by 4 days for patients in coun-
ties with the most poverty (P=.006).
Table 3 shows median travel dis-
tance by cancer type in 2003 and 2006.
Distance traveled by patients with lym-
phoma was unchanged (P=.37). Travel
distance increased by 1.2 miles (1.9 km)
for breast cancer (P=.007), 1.5 miles
(2.4 km) for colorectal cancer (P=.003),
0.9 miles (1.4 km) for lung cancer
(P=.08), and 1.4 miles (2.2 km) for leu-
kemia (P=.10). Although patients in ru-
ral areas traveled longer distances than
patients in urban areas, median travel
distance increased by only 1.2 miles in
rural areas (P=.04) and by 0.7 miles
(1.1 km) in urban areas (P .001)
(Table 3). Travel distance increased by
0.7 miles for patients aged 75 years or
older (P=.001) and by 1.2 miles for pa-
tients younger than 75 years (P=.001).
Travel distance increased by about
1 mile (1.6 km) in both high-poverty
(P =.05) and low-poverty (P .001)
counties.
Controlling for age, sex, race/
ethnicity, cancer type, geographic re-
gion, rural-urban status, proportion of
persons living below the poverty level,
and comorbid conditions, average wait
times were not significantly different
from 2003 to 2004 (difference, 0.28 days;
Table 1. Baseline Characteristics of the Study Population by Year of Diagnosis and Initial
Chemotherapy Visit
Characteristics
Year of Diagnosis and Initial
Chemotherapy Visit, No. (%)
P
Value
2003
(n = 5082)
2004
(n = 5379)
2005
(n = 5116)
2006
(n = 5288)
Age, mean (SD), y 75 (5.6) 75 (5.9) 75 (5.9) 75 (6.0) .34
Male 2546 (50.1) 2663 (49.5) 2477 (48.4) 2573 (48.7) .29
Race
Black 362 (7.1) 423 (7.9) 399 (7.8) 373 (7.1)
White 4551 (89.6) 4790 (89.1) 4558 (89.1) 4659 (88.1) .001
Other/unknown 169 (3.3) 166 (3.1) 159 (3.1) 256 (4.8)
Cancer type
Breast cancer 702 (13.8) 759 (14.1) 737 (14.4) 777 (14.7)
Colorectal cancer 1234 (24.3) 1242 (23.1) 1115 (21.8) 1085 (20.5)
Leukemia 325 (6.4) 389 (7.2) 356 (7.0) 414 (7.8) .001
Lung cancer 1930 (38.0) 2008 (37.3) 1948 (38.1) 1931 (36.5)
Lymphoma 891 (17.5) 981 (18.2) 960 (18.8) 1081 (20.4)
Comorbid conditions
Cerebrovascular disease 750 (14.8) 932 (17.3) 840 (16.4) 1007 (19.0) .001
Chronic obstructive pulmonary
disease
1910 (37.6) 2010 (37.4) 1984 (38.8) 2058 (38.9) .23
Dementia 81 (1.6) 100 (1.9) 93 (1.8) 104 (2.0) .54
Diabetes mellitus 1283 (25.2) 1455 (27.0) 1422 (27.8) 1495 (28.3) .003
Hypertension 3296 (64.9) 3721 (69.2) 3646 (71.3) 3840 (72.6) .001
Ischemic heart disease 1747 (34.4) 1876 (34.9) 1774 (34.7) 1887 (35.7) .54
Metastatic cancer 1313 (25.8) 1398 (26.0) 1244 (24.3) 1221 (23.1) .001
Peripheral vascular disease 916 (18.0) 1057 (19.7) 1030 (20.1) 1187 (22.4) .001
Renal disease 275 (5.4) 354 (6.6) 341 (6.7) 422 (8.0) .001
Rural residence 1235 (24.3) 1374 (25.5) 1303 (25.5) 1280 (24.2) .22
Residence in county with high
poverty level
1285 (25.3) 1332 (24.8) 1288 (25.2) 1383 (26.2) .41
US Census region
Midwest 1362 (26.8) 1414 (26.3) 1339 (26.2) 1387 (26.2)
Northeast 1014 (20.0) 1024 (19.0) 1049 (20.5) 1027 (19.4)
.48
South 1955 (38.5) 2177 (40.5) 1997 (39.0) 2131 (40.3)
West 751 (14.8) 764 (14.2) 731 (14.3) 743 (14.1)
Setting of initial chemotherapy visit
Inpatient 518 (10.2) 557 (10.4) 513 (10.0) 466 (8.8)
Outpatient 1071 (21.1) 1062 (19.7) 1111 (21.7) 1191 (22.5) .003
Physician office 3493 (68.7) 3760 (69.9) 3492 (68.3) 3631 (68.7)
MEDICARE MODERNIZATION ACT AND PATIENT WAIT TIMES AND TRAVEL DISTANCE
192 JAMA, July 9, 2008—Vol 300, No. 2 (Reprinted) ©2008 American Medical Association. All rights reserved.
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95% confidence interval [CI], –1.55 to
2.10 days; P=.76) or from 2003 to 2006
(difference, 0.88 days; 95% CI, –0.96 to
2.71 days; P=.35), but there was an in-
crease of approximately 2 days from 2003
to 2005 (difference, 1.96 days; 95% CI,
0.11-3.80 days; P=.04). Patients with a
history of metastatic cancer of a differ-
ent type received chemotherapy 18.1
days sooner than other patients (95% CI,
–19.60 to –16.57 days; P.001). Com-
pared with white patients, black pa-
tients waited an average of 3.7 days
longer for initial chemotherapy (95% CI,
1.21-6.27 days; P=.004).
Patients traveled slightly farther on
average for chemotherapy in 2004 (1.47
miles [2.35 km]; 95% CI, 0.87-2.07
miles [1.39-3.31 km]; P .001), 2005
(1.19 miles [1.90 km]; 95% CI, 0.58-
1.80 miles [0.93-2.88 km]; P =.001),
and 2006 (1.30 miles [2.08 km]; 95%
CI, 0.69-1.90 miles [1.10-3.04 km];
P .001) relative to 2003. Control-
ling for other factors, black patients
traveled 3 miles (4.8 km) less than
white patients (95% CI, –3.88 to –2.21
miles [–6.21 to –3.54 km]; P .001).
Multivariable quantile regression mod-
els on median wait times and travel dis-
tance yielded results consistent with the
linear regression analysis. Relative to
2003, there was no increase in median
days in 2004 (difference, 0.38 days; 95%
CI, –0.77 to 1.54 days; P=.52), an in-
crease of 2.20 days in 2005 (95% CI,
1.05-3.34 days; P .001), and no in-
crease in 2006 (difference, 0.93 days;
95% CI, –0.33 to 2.19 days; P= .15). Me-
dian travel distance increased by 0.70
miles (1.12 km) in 2004 (95% CI, 0.34-
1.06 miles [0.54-1.70 km]; P .001),
0.80 miles (1.28 km) in 2005 (95% CI,
0.43-1.18 miles [0.69-1.89 km];
P.001), and 0.85 (1.36 km) miles in
2006 (95% CI, 0.49-1.20 miles [0.78-
1.92 km]; P.001).
COMMENT
Opponents of the MMA have predicted
negative consequences of the legisla-
tion since before its enactment.
2,5-10,19,20
In anticipation of reduced revenues, on-
cology practices reported closing satel-
lite facilities and reducing office staff.
8,9
However, current available evidence does
not suggest that Medicare beneficiaries
or cancer care providers have been ad-
versely affected. In this analysis of a na-
tionally representative sample of Medi-
care beneficiaries, we did not find a
significant change in the distribution of
patients by treatment setting from 2003
to 2004 or from 2003 to 2005, although
we observed a small shift in the provi-
sion of initial chemotherapy from inpa-
tient facilities to institutional outpa-
tient settings between 2003 and 2006.
This finding contrasts with predictions
that changes in Medicare reimburse-
ment for outpatient chemotherapy would
result in a rapid shift toward provision
of chemotherapy in inpatient settings.
Consistent with predictions of a mi-
gration of patients from community-
based practices to hospital settings, con-
cerns were expressed that increased
travel requirements and longer wait
times at overburdened facilities would
delay the initiation of chemotherapy.
However, in this analysis, median wait
times in 2006 were not significantly dif-
ferent from those in 2003 for any of the
treatment settings. Across all treat-
ment settings and after adjustment for
other factors, there was no significant
change in time to treatment from 2003
to 2004. Patients waited approxi-
mately 2 days longer for chemotherapy
in 2005 compared with 2003, but there
was no difference between 2003 and
2006. Median wait times observed herein
are consistent with or lower than those
reported elsewhere.
21,22
Clinical effects
of delays in treatment remain largely un-
known, but analyses of time to initia-
tion of adjuvant chemotherapy for breast
cancer have shown no difference in dis-
ease-specific or overall mortality for
patients who received treatment within
1 to 3 months of definitive surgery.
23,24
In this study, we evaluated days from
diagnosis—not surgery—to the initial
chemotherapy visit.
The median distance traveled for ini-
tial chemotherapy was 7 miles in 2003
and 8 miles in subsequent years. Across
all treatment settings and after adjust-
ment for age, sex, race/ethnicity, can-
Table 2. Patient Wait Times and Travel Distance for Initial Chemotherapy Visit by Year and
Treatment Setting
Year of Diagnosis and Initial Chemotherapy Visit P Value for
Overall
Trend2003 2004 2005 2006
Wait Time Between Diagnosis and Chemotherapy, d
Median (IQR)
Overall 28 (10-54) 27 (10-55) 29 (12-57) 28 (9-56) .12
Inpatient 11 (5-25) 10 (5-23) 12 (6-29) 10 (5-25) .50
Outpatient 32 (13-61) 32 (13-57) 34 (14-61) 32 (13-61) .55
Physician office 29 (12-55) 29 (12-57) 31 (13-60) 29 (11-58) .42
Mean (SD)
Overall 41.8 (49.5) 41.9 (49.4) 43.8 (48.5) 42.5 (49.0) .12
Inpatient 25.8 (43.4) 22.4 (37.3) 27.9 (43.9) 26.8 (45.4) .50
Outpatient 46.8 (52.8) 44.8 (49.3) 46.3 (48.6) 46.6 (50.8) .55
Physician office 42.6 (48.9) 44.0 (50.4) 45.4 (48.7) 43.2 (48.5) .42
Travel Distance, miles
Median (IQR)
Overall 7 (3-17) 8 (4-19) 8 (4-19) 8 (4-19) .001
Inpatient 7 (3-18) 8 (4-22) 7 (4-20) 9 (4-23) .04
Outpatient 7 (3-15) 8 (3-19) 8 (3-17) 7 (3-19) .07
Physician office 7 (3-17) 8 (4-20) 9 (4-20) 8 (4-19) .001
Mean (SD)
Overall 13.5 (16.7) 15.2 (18.4) 14.9 (17.6) 14.8 (17.7) .001
Inpatient 14.7 (18.6) 16.8 (21.0) 15.8 (20.1) 16.6 (19.1) .04
Outpatient 12.6 (16.6) 14.1 (17.2) 14.0 (17.6) 14.4 (18.4) .07
Physician office 13.7 (16.5) 15.3 (18.3) 15.0 (17.2) 14.7 (17.2) .001
SI conversion: To convert miles to kilometers, multiply by 1.6.
Abbreviation: IQR, interquartile range.
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©2008 American Medical Association. All rights reserved. (Reprinted) JAMA, July 9, 2008—Vol 300, No. 2 193
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Page 5
cer type, geographic region, rural-
urban status, poverty at the county
level, and comorbid conditions, pa-
tients traveled an average of 1.5 miles
farther for treatment in 2004 than in
2003, 1.2 miles farther in 2005 than in
2003, and 1.3 miles farther in 2006 than
in 2003. Previous studies have re-
ported an inverse relationship be-
tween travel distance and likelihood of
radiotherapy
25-28
; however, we are un-
aware of any study that has examined
the relationship between distance trav-
eled and outcomes. Nonetheless, it
seems unlikely that increases in travel
distance of less than 2 miles would be
clinically significant.
In general, our findings are consis-
tent with a recent MedPAC evaluation
of the effects of MMA-related pay-
ment changes using Medicare claims
data, commercial drug information,
provider site visits, and patient focus
groups. MedPAC found that despite
changes in reimbursement, more pa-
tients received chemotherapy in phy-
sician offices and more total chemo-
therapy services were provided in 2004
and 2005 than in 2003. In addition,
these increases were found to be con-
sistent across geographic regions. Of the
patients and providers who partici-
pated in the MedPAC assessment, none
reported a decrease in the quality of can-
cer care following implementation of
the MMA.
3
Echoing these findings, a re-
cent survey of patients who received
chemotherapy either before or after the
enactment of the MMA found no dif-
ference in wait times and equal rates of
satisfaction with oncology care.
11
In a
comparison of 2005 reimbursement
amounts to actual purchase prices for
39 drugs representing more than 94%
of all Medicare hematology/oncology
drug spending, the Office of Inspector
General of the Department of Health
and Human Services found that physi-
cian practices were able to purchase 35
of the 39 drugs at prices lower than the
reimbursed amounts.
29
There are several possible explana-
tions for why we did not observe greater
changes in patient wait times or travel
distance after the enactment of the
MMA. First, it might be too early to as-
sess the full impact of MMA-related
changes in reimbursement. In the short
term, oncology practices may have been
able to absorb financial losses or com-
pensate for those losses by providing
other services. The cumulative, long-
term effects of lower reimbursement
may still lead to office closures and re-
ductions in community-based oncol-
ogy services for Medicare beneficia-
ries. Second, nurses and other support
staff—not patients—may bear the brunt
of the impact of these changes. If prac-
tices have indeed reduced the number
of staff that they employ, remaining em-
ployees may be working longer and
harder to provide care for the same
number of patients. Although there
have been numerous anecdotal re-
ports of staff reductions, a quantita-
tive analysis of this issue has not been
performed. Third, it is possible that the
financial impact of the reimburse-
ment changes has not been as substan-
tial as was initially expected, so the in-
centive to change the delivery of care
was minimal.
Moreover, examining the aggregate
impact of MMA-related changes may
obscure important changes in access to
care for certain subgroups. It is plau-
sible that patients in rural or under-
served areas or those with limited re-
Table 3. Wait Times and Travel Distance in 2003 vs 2006 by Cancer Type and Patient
Demographic Characteristics
Characteristics
Year
P
Value
a
2003 2006
Wait Time Between Diagnosis and Chemotherapy, Median (IQR), d
Cancer type
Breast cancer 40 (13-71) 43 (14-75) .15
Colorectal cancer 41 (20-66) 46 (19-73) .07
Leukemia 14 (4-53) 12 (2-44) .15
Lung cancer 21 (9-41) 24 (11-47) .001
Lymphoma 20 (8-40) 17 (4-38) .006
Demographic characteristics
Residence
Rural 26 (10-50) 29 (11-55) .04
Urban 28 (10-55) 27 (9-56) .001
Age, y
75 28 (10-56) 28 (9-57) .70
75 27 (11-52) 28 (9-55) .001
Residence in county with high poverty level 27 (10-53) 23 (5-53) .05
Residence in county with low poverty level 28 (10-55) 29 (11-57) .001
Travel Distance, Median (IQR), miles
Cancer type
Breast cancer 6.8 (3.1-16.2) 8.0 (3.6-20.0) .007
Colorectal cancer 6.6 (3.1-16.5) 8.1 (3.6-18.7) .003
Leukemia 7.7 (3.1-19.8) 9.1 (4.0-22.4) .10
Lung cancer 7.5 (3.5-16.9) 8.4 (3.5-19.2) .08
Lymphoma 7.8 (3.1-17.5) 7.8 (4.0-18.0) .37
Demographic characteristics
Residence
Rural 22.7 (7.0-40.8) 23.9 (9.4-41.0) .04
Urban 6.1 (3.1-11.6) 6.8 (3.3-12.6) .001
Age, y
75 6.7 (3.0-15.2) 7.4 (3.3-16.7) .001
75 8.0 (3.6-19.0) 9.2 (4.0-21.4) .001
Residence in county with high poverty level 7.8 (3.1-23.2) 8.8 (3.5-24.6) .05
Residence in county with low poverty level 7.1 (3.3-15.6) 8.0 (3.7-17.7) .001
SI conversion: To convert miles to kilometers, multiply by 1.6.
Abbreviation: IQR, interquartile range.
a
P values calculated from Wilcoxon rank sum tests for comparisons between 2003 and 2006.
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194 JAMA, July 9, 2008—Vol 300, No. 2 (Reprinted) ©2008 American Medical Association. All rights reserved.
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Page 6
sources might have been affected more
dramatically. When we stratified our
analysis by rural-urban status, we found
that the median wait time for patients
in rural areas increased by 3 days from
2003 to 2006 and that wait times for the
top quartile of patients in rural areas in-
creased by 5 days. The clinical signifi-
cance of this difference is unclear, but
the magnitude of the difference is
greater than that observed in other sub-
groups. Careful analysis of the impact
of MMA-related changes on patients in
rural areas using a larger sample of
Medicare beneficiaries may be war-
ranted. Moreover, analyses stratified by
cancer type suggest that wait times and
travel distance increased for some can-
cer types and decreased for others.
These changes may reflect temporal
changes in treatment regimens, but we
cannot explore this possibility with-
out detailed clinical data.
Our analysis has some limitations.
First, the coding of diagnoses and pro-
cedures in claims data may not always
be accurate or complete and the qual-
ity of care received is unknown. How-
ever, previous studies have shown that
diagnosis information in Medicare
claims can be used to identify incident
cancer with high specificity
30
and that
claims are a valid source of informa-
tion for the identification of chemo-
therapy services.
31-33
Second, Medicare data do not in-
clude claims for beneficiaries during pe-
riods of enrollment in managed care.
Similarly, ascertainment bias results
when a person does not have contact
with the health care system. A cancer
diagnosis can only be recorded if there
was a visit; therefore, the effect of as-
certainment bias is a bias toward ac-
cepting the null hypothesis.
Third, the effects of reimbursement
changes may have been mitigated by
other factors. For example, payments
made to physicians for concurrent CMS
demonstration projects may have off-
set reductions in reimbursement, and
physicians may not have fully re-
sponded to the implications of the new
reimbursement system by 2006. In ad-
dition, where fixed costs are high, phy-
sicians may have limited ability to make
sudden changes to their practice.
Fourth, our analysis of distance re-
lies on measurements between zip code
centroids. Previous research has shown
a high correlation between travel times
and straight-line distances between zip
code centroids.
34
Nevertheless, some zip
codes encompass large geographic areas,
and our analysis does not include any
measurement of travel times.
Fifth, the sample size allowed us to
detect differences of approximately
1 mile and 2.8 days with 80% power.
Although statistically significant, these
differences are unlikely to be clinically
meaningful. Finally, in this analysis, we
implicitly assumed that temporal changes
were related to the MMA when, in fact,
random variation exists over time.
CONCLUSION
As measured by travel distance and time
to chemotherapy, our findings do not
support anecdotal reports that the en-
actment of the MMA has changed ac-
cess to chemotherapy in a meaningful
way. Given the slow transition to full
implementation of the reimbursement
changes mandated by the MMA and the
limited amount of follow-up data avail-
able at present, it may be premature to
observe a relationship between these
changes and delivery of care. With the
aging of the US population, the number
of elderly individuals with cancer is ex-
pected to increase proportionally, with
incidence doubling in less than 30
years.
35
As the burden increases, re-
searchers should continue to monitor the
effects of major policy changes on Medi-
care beneficiaries’ access to care.
Author Affiliations: Center for Clinical and Genetic Eco-
nomics, Duke Clinical Research Institute (Mss Shea and
DiMartino, Drs Curtis and Schulman, and Mr Ham-
mill), and Department of Medicine (Drs Curtis, Aber-
nethy, and Schulman), Duke University School of Medi-
cine, Durham, North Carolina.
Author Contributions: Ms Shea and Dr Curtis had full
access to all of the data in the study and take respon-
sibility for the integrity of the data and the accuracy
of the data analysis.
Study concept and design: Shea, Curtis, Schulman.
Acquisition of data: Shea.
Analysis and interpretation of data: Shea, Curtis,
Hammill, DiMartino, Abernethy, Schulman.
Drafting of the manuscript: Shea.
Critical revision of the manuscript for important in-
tellectual content: Shea, Curtis, Hammill, DiMartino,
Abernethy, Schulman.
Statistical analysis: Shea, Curtis, Hammill.
Obtained funding: Schulman.
Administrative, technical, or material support: Shea,
DiMartino, Schulman.
Study supervision: Curtis, Schulman.
Financial Disclosures: Dr Curtis reports receiving re-
search and salary support from Allergan Pharmaceu-
ticals, GlaxoSmithKline, Lilly, Medtronic, Novartis, Or-
tho Biotech, OSI Eyetech, Pfizer, and Sanofi-Aventis.
Dr Curtis has made available online a detailed listing
of financial disclosures (http://www.dcri.duke.edu
/research/coi.jsp). Dr Schulman reports receiving re-
search and/or salary support from Actelion, Aller-
gan, Amgen, Arthritis Foundation, Astellas Pharma,
Bristol-Myers Squibb, The Duke Endowment, Genen-
tech, Inspire Pharmaceuticals, Johnson & Johnson,
Kureha Corporation, LifeMasters Supported Self-
Care, Medtronic, Merck, Nabi Biopharmaceuticals, Na-
tional Patient Advocate Foundation, North Carolina
Biotechnology Center, Novartis, OSI Eyetech, Pfizer,
Roche, Sanofi-Aventis, Schering-Plough, Scios, Ten-
gion, Theravance, Thomson Healthcare, Vertex Phar-
maceuticals, Wyeth, and Yamanouchi USA Founda-
tion; receiving personal income for consulting from
Avalere Health, LifeMasters Supported SelfCare,
McKinsey & Co, and the National Pharmaceutical
Council; having equity in and serving on the board of
directors of Cancer Consultants; having equity in and
serving on the executive board of Faculty Connec-
tion LLC; and having equity in Alnylam Pharmaceu-
ticals. Dr Schulman has made available online a de-
tailed listing of financial disclosures (http://www.dcri
.duke.edu/research/coi.jsp). No other disclosures were
reported.
Funding/Support: This study was funded by a grant
to Duke University from the National Patient Advo-
cate Foundation as manager of the Global Access
Project, Washington, DC.
Role of the Sponsor: The National Patient Advocate
Foundation had no role in the design and conduct
of the study or the collection, analysis, and inter-
pretation of the data. Representatives of the spon-
sor reviewed a draft of the manuscript. The authors
had full control over the preparation of the manu-
script and the decision to submit the manuscript for
publication.
Previous Presentations: This study was presented in
part at a meeting of the Global Access Project, Sep-
tember 20, 2007, Washington, DC; and at the Acad-
emyHealth Annual Research Meeting, June 10, 2008;
Washington, DC.
Additional Contributions: We thank Damon M. Seils,
MA, Duke University, for editorial assistance and manu-
script preparation. Mr Seils did not receive compen-
sation for his assistance apart from his employment
at the institution where the study was conducted.
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    • "km. Travel distance for chemotherapy in the Medicare population has not seen major changes after the enactment of the MMA [5]. "
    [Show abstract] [Hide abstract] ABSTRACT: Cancer creates a tremendous financial burden. Cancer-related costs are categorized into direct, indirect, and psychosocial costs. Although there have been many reports on medical care costs, which are direct, those on other costs are extremely scarce. We estimated travel time and costs required for cancer patients to receive outpatient treatment. We studied 521 cancer patients receiving anti-cancer treatment between February 2009 and December 2012 at the Outpatient Chemotherapy Center of Teikyo University Chiba Medical Center. Address data were extracted from Data Warehouse electronic medical records, and travel distance and time required for outpatient treatment were calculated via MapInfo and ACT Distance Calculator Package. Transportation costs were estimated on the basis of ¥274 (=$3.00) per kilometer. The study design was approved by an ethics review board of Teikyo University (12–851). Average round-trip travel distance, time, and cost for all patients were 26.7 km, 72.5 min, and ¥7,303 ($79.99), respectively. Cancer patients incurred a travel cost of ¥4000–¥9000 ($40.00 to $100.00) for each outpatient treatment. With population aging, seniors living alone and senior households are increasing, and outpatient visits are becoming a common burden.
    Full-text · Article · Dec 2014
    • "Even with declining DXA reimbursement, particularly affecting non-facility DXA providers, it is unlikely that all of them would stop providing this service. A recent analysis that evaluated the relationship between travel distance and receipt of chemotherapy as a result of the Medicare modernization act in 2003 that shifted some oncology services from physician offices to facility settings showed only modest effects of this policy change in terms of travel distance and wait times [22]. However, a subgroup analysis showed that those most affected were individuals living in rural areas, which is consistent with observations in our study. "
    [Show abstract] [Hide abstract] ABSTRACT: Using national Medicare data from 1999-2006, we evaluated the relationship between travel distance and receipt of dual-energy X-ray absorptiometry (DXA). After adjusting for potentially confounding factors, travel distance was strongly associated with DXA testing. Rural residents were most strongly dependent on the availability of DXAs performed in physician offices. Medicare reimbursement for DXAs performed in non-facility settings (e.g., physician offices) decreased in 2007. With declining reimbursement, some DXA providers may cease providing this service, which would increase travel distance for some people. The impact of travel distance on access to DXA is unclear. Using national Medicare data, we identified claims for DXA to evaluate trends in the number and locations of DXAs performed. Travel distance was the distance from beneficiaries' residence and the nearest DXA provider. Binomial regression evaluated the relationship between travel distance and receipt of DXA. In 2006, 2.9 million DXAs were performed, a 103% increase since 1999. In 2005-2006, 8.0% of persons were tested at non-facility sites versus 4.2% at facility sites. The remainder (88%) had no DXA. Persons traveling 5-9, 10-24, 25-39, and 40-54, and > or = 55 miles were less likely to receive DXA (adjusted risk ratios = 0.92, 0.79, 0.43, 0.32, and 0.26, respectively, < 5 miles referent). Rural residents were more dependent than urban residents on the availability of DXA from non-facility providers. Approximately two-thirds of DXAs in 2005-2006 were performed in non-facility settings (e.g., physician offices). Rural residents would have preferentially reduced access to DXA if there were fewer non-facility sites.
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    J R CurtisJ R CurtisA LasterA LasterD J BeckerD J Becker+1more author...[...]
  • [Show abstract] [Hide abstract] ABSTRACT: agents administered during hospi- talization at a tertiary care acade- mic medical center. The retrospec- tive analysis was conducted over 1 year. A total of 416 allergies were reported among 300 patients; more than 1 allergy was reported by more than one-fourth of study patients (82/300 (27.3%)). Only 36.3% (151/416) of allergies reported were accompanied by a reaction description (95% confi- dence interval (CI), 31.7% to
    Article · · Osteoporosis International
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