Posted: August 1st, 2022

Economic Data Analysis

PART 1

The decade since the Patient Protection and Affordable Care Act went into effect in 2010 has seen fundamental shifts in the cost and practices in health care and insurance. Studying the data from this period of transformation in the United States can help us to understand the movement of health care costs in the years to come. 

-Review the Dartmouth Atlas of Health Care 2018 Data Update.(ATTACHED)  

Write a 525- to 700-word analysis that includes the following:

-Identify the results for your area of the United States (state or region).  

-Analyze the results for your area and write a 525- to 700-word summary of why you think the trends in utilization and cost are either positive or negative.  

-Examine and explain whether you think the utilization and costs information for your organization or geography can be used to build a stronger brand for health care. 

-Cite any references to support your assignment.  

-Format your citations according to APA guidelines.

Part 2

Respond to the following in a minimum of 175 words: 

If mergers and market consolidation in health care do not increase access or lower prices for consumers, why have they been so prevalent in the last 20 years in the United States?  

Are there economic theories or concepts that help to explain the regional variation in health care utilization and cost, as outlined by the Dartmouth Atlas of Healthcare report? 

Part 3

Will post part 3 Friday

The Dartmouth Atlas of Health Care:
2018 Data Update

The period since 2010 has been one of transition for health care in America.
In addition to reforming the insurance market and increasing the number
of people with insurance coverage (both private and Medicaid), the 2010
Patient Protection and Affordable Care Act (or the ACA) included provi-
sions intended to both improve the quality and reduce the cost of health
care. Among these were a renewed focus on primary and preventive care,
including screening for patients with chronic diseases such as diabetes,1
and on reducing both unnecessary hospitalizations2 and readmissions after
patients leave the hospital.3 While not explicitly included in the ACA, pro-
grams established via the Centers for Medicare & Medicaid Services (CMS)
Innovation Center, created under the law, have also focused on improving
the quality of end-of-life care via reimbursement for advance care planning
and improving the availability and quality of hospice care.

4

The emphasis on these goals is partially reflected in the Dartmouth Atlas
Project’s 2018 data update. While reimbursements to hospitals and skilled
nursing facilities for inpatient services decreased as a proportion of overall
Medicare reimbursements between 2011 and 2018, the proportion spent on
hospice services remained unchanged. Use of hospice, however, increased
among enrollees with serious chronic illnesses. Chronically ill Medicare en-
rollees were less likely to die in the hospital in 2018 than in 2011, and they
spent fewer days in the hospital during their last six months of life, but
they visited a larger number of different physicians as they neared the end
of life. There was a small reduction in readmissions within 30 days of dis-
charge following a medical admission; the magnitude of this decrease was
greater for specific conditions targeted by CMS. The percentage of Medi-
care enrollees having a primary care visit increased slightly, as did rates of
breast cancer screening and diabetes management screening tests. Data
for these measures and more are available from the Dartmouth Atlas web-
site: data.dartmouthatlas.org.

While we experienced delays in processing the 2018 data, the 2019 Atlas
report is already in progress; we plan to focus on racial and ethnic dispari-
ties in health and health care among Medicare enrollees. In light of the CO-
VID-19 pandemic, we are planning a 2020 Atlas report that will document
the tragic regional patterns of mortality, as well as expenditures and utili-
zation, among the older (age 65+) population.

August 18, 202

1

Kristen Bronner, MA, Editor

M. Scottie Eliassen, MS
Ashleigh King, MPH
Christopher Leggett, PhD
Sukdith Punjasthitkul, MS
Jonathan Skinner, PhD

Untitled

Medicare Reimbursements

Total Medicare reimbursements for enrollees in fee-for-service Medicare
(not including the Part D prescription drug program) remained relatively
constant between 2011 and 2018 after adjusting for inflation. The national
average reimbursement rate was $10,936 per enrollee in 2011 (2018 dollars)
and $10,786 per enrollee in 2018. The variation in total reimbursement rates
among the 306 hospital referral regions (HRRs) in the United States also
decreased between 2011 and 2018; the rate varied about twofold in 2011 and
by a factor of 1.72 in 2018 after adjusting for regional differences in age, sex,
race, and prices. The change in the interquartile ratio was minimal, however,
indicating that the reduced variation was mostly due to a decrease in the
highest rates (Figure 1).

There was considerable varia-
tion in the changes in Medi-
care spending across HRRs.
While Miami remained the
region with the highest re-
imbursements per enrollee
in 2018 ($13,678), this rep-
resented a decrease of 12%
from the inflation-adjusted
reimbursement rate in 2011
($15,603). The rate in the HRR
with the second highest reim-
bursements in 2011—McAllen,
Texas—declined 11%, from
$15,039 per enrollee to $13,372
in 2018. These declines can be
attributed in part to efforts by
federal strike forces targeting
fraudulent behavior in these
regions.5 Meanwhile, Medicare
reimbursements per enrollee
increased more than 15% in
Rochester, New York ($8,713
to $10,344) and Mason City,
Iowa ($8,588 to $9,963) from
2011 to 2018.

As shown in Map 1, there is
considerable variation across
the U.S. with regard to overall
Medicare expenditures that is
not a consequence of differ-

Figure 1. Hospital Referral Region (N=306) Variation in Total Medi-
care Reimbursements per Enrollee (2011-18)

2 The Dartmouth Atlas of Health Care: 2018 Data Update

Changes in Variation among Hospital Referral Regions

The figure shows the annual variation in Medicare reimbursements per en-
rollee from 2011 to 2018. The dashes at each end of the vertical lines show the
highest and lowest rates, and the table gives the ratio of the highest to lowest
value (extremal ratio). The top line of each gray box represents the rate at the
75th percentile among HRRs, and the bottom line shows the rate at the 25th
percentile; the table gives the ratio of these values (interquartile ratio). The
blue squares show the national average for each year. All spending measures
are expressed in 2018 dollars using the GDP deflator to adjust for inflation.

2011 2012 2013 2014 2015 2016 2017 201

8

U.S. average $10,936 $10,693 $10,349 $10,212 $10,258 $10,628 $10,688 $10,786

Extremal ratio 2.03 2.02 2.00 1.91 1.84 1.81 1.74 1.72

Interquartile ratio 1.23 1.22 1.21 1.21 1.20 1.18 1.17 1.18

Coefficient of
variation

13.8 13.5 13.0 12.9 12.1 11.8 11.4 11.

5

$7,00

0

$8,000

$9,000

$10,000

$11,000

$12,000

$13,000

$14,000

$15,000

$16,000

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)

ences in age, sex, race, or Medicare reimbursement
rates. In addition to Miami, Medicare reimburse-
ment rates in 2018 were also high for enrollees liv-
ing in the Munster, Indiana ($13,622), Monroe, Loui-
siana ($13,619), Los Angeles ($13,514), and Wichita
Falls, Texas ($13,402) HRRs. Medicare spent much
less per capita for enrollees in Santa Cruz, Califor-
nia ($7,967), Honolulu ($8,090), Grand Junction,
Colorado ($8,101), Burlington, Vermont ($8,202),
and Anchorage ($8,251) (Map 1).

Map 1. Price-Adjusted Total Medicare
Reimbursements per Enrollee by
Hospital Referral Region (2018)

A Report of the Dartmouth Atlas Project 3

Between 2011 and 2018, the percent of total Medicare reimbursements paid
to hospitals and skilled nursing facilities for services delivered during inpa-
tient stays decreased from 48% to 42%, while reimbursements to outpa-
tient facilities increased from 12% to 19% of overall spending. These changes
could reflect efforts to reduce the number of preventable hospitalizations
and instead treat patients in less expensive settings. Reimbursements for
physician, hospice, and other services (home health services and durable
medical equipment) remained relatively constant (Figure 2).

Despite the lack of increase in hospice spending as a proportion of overall
reimbursements, use of hospice services during the last six months of life
rose among Medicare enrollees with serious chronic illnesses. The percent
of chronically ill Medicare decedents enrolled in hospice during the last six
months of life grew from 49% of those dying in 2011 to 56% in 2018. The
number of days these patients spent receiving hospice services increased
more than 20%, from about 22 to 26 days. However, this change in hospice
use was far from uniform across HRRs. In McAllen, Texas, there was an in-
crease of more than 70% in the percent of chronically ill Medicare enrollees
using hospice during the last six months of life—from 30.5% of those dying
in 2011 to 52.2% in 2018—though the region still ranked in the bottom half

of HRRs in 2018. By contrast, the
rate of hospice use in Bismarck,
North Dakota—already among the
lowest-ranked HRRs in 2011, at
24.4%—declined to 22.5% in 2018.
The percent of chronically ill de-
cedents dying in 2018 who used
hospice services during the last
six months of life was also low in
Minot, North Dakota (22.8%) and
several regions in New York, in-
cluding Elmira (22.8%), Syracuse
(25.0%), and the Bronx (26.4%).
Rates of hospice use were about
three times higher in Ormond
Beach, Florida (73.1%), Ogden,
Utah (71.6%), Provo, Utah (71.5%),
and Mesa, Arizona (71.1%) (Map 2).

Figure 2. Percent of Total Medicare Reimbursements by Program
Component (2011-18)

4 The Dartmouth Atlas of Health Care: 2018 Data Update

Changes in Spending by Program Component

48% 46% 45% 44% 44% 44% 43% 42%

28% 28% 28% 28% 28% 28% 28% 28%

12% 14% 15% 16% 17% 17% 18% 19%

4% 4% 4% 4% 4% 4% 4% 4%
9% 8% 8% 8% 8% 7% 7% 7%

0%

10%

20%

30%

40%

50%

60%

70%

80%

90%

100%

2011 2012 2013 2014 2015 2016 2017 2018

P
er

ce
nt

o
f t

ot
al

M
ed
ic
ar
e
re
im
bu
rs
em
en
ts

Hospital/SNF Physician Outpatient Hospice Other

Map 2. Percent of Chronically Ill Patients
Enrolled in Hospice during the Last Six
Months of Life by Hospital Referral Region
(2018 deaths)

A Report of the Dartmouth Atlas Project 5

End-of-Life Care for Patients with Chronic Illness

The increase in use of hospice services among Medicare enrollees with seri-
ous chronic illness was accompanied by a reduction in the intensity of hos-
pital utilization during the last six months of life. The percent of chroni-
cally ill Medicare patients dying in the hospital decreased from 24.1% in
2011 to 20.4% in 2018, and the percent of patients having a hospitalized
death whose final admission included an intensive care stay declined from
16.3% to 14.9%. The number of days that chronically ill patients spent in the
hospital during the last six months of life decreased from 9.8 to 8.5 days,
though the number of days spent in intensive care remained relatively flat
(Figure 3). While chronically ill patients dying in 2018 spent fewer days in
the hospital during the last six months of life than in 2011 in most HRRs, this
was not the case for every region. Medicare decedents in Santa Rosa, Cali-
fornia spent more than two additional days in the hospital during the last
six months of life in 2018 (8.5 days) than in 2011 (6.2 days) on average, while
those in Olympia, Washington (6.7 to 7.9 days, 2011 to 2018) and Bend, Or-
egon (4.4 to 5.5 days) spent one additional day in the hospital. By contrast,
the amount of time that decedents in Johnstown, Pennsylvania spent in the
hospital during the last six months of life decreased by more than three
days between 2011 and 2018, from 11.9 to 8.2.

Chronically ill Medicare patients
who died in 2018 spent about two
weeks in the hospital during their
last six months of life in the New
York City metropolitan HRRs of
Manhattan (14.1 days), the Bronx
(13.9), and East Long Island (13.8).
Chronically ill patients in Utah
HRRs spent fewer than 5 days in
the hospital at the end of life: Og-
den (4.0), Provo (4.4), and Salt
Lake City (4.8) (Map 3).

Figure 3. Inpatient Days per Chronically Ill Medicare Enrollee
during the Last Six Months of Life (2011-18 deaths)

6 The Dartmouth Atlas of Health Care: 2018 Data Update

Hospital Utilization

8.5

9.8

4.

9

5.9

3.63.8

1

3

5

7

9

11

2011 2012 2013 2014 2015 2016 2017 2018

In
pa

tie
nt

d
ay

s
du

ri
ng

th
e

la
st

s
ix

m
on

th
s

of
li

fe

All Inpatient Days Medical & Surgical Units Intensive Care Units

Map 3. Inpatient Days per Chronically
Ill Medicare Enrollee during the Last Six
Months of Life by Hospital Referral Region
(2018 deaths)

A Report of the Dartmouth Atlas Project 7

The overall number of physician visits also declined, from 28.8 visits per
chronically ill Medicare decedent during the last six months of life for those
dying in 2011 to 26.3 visits in 2018. However, the number of different phy-
sicians seen by chronically ill patients increased from about 10 in 2011 to
about 12 in 2018. The percent of chronically ill patients seeing 10 or more
different physicians during the last six months of life increased from an av-
erage of 43.2% of patients dying in 2011 to 51.2% in 2018, an increase of
more than 18% (Figure 4). This rate increased in all but two HRRs: McAllen,
Texas—where the percent seeing 10 or more physicians dropped from 63%
to 60%—and New Orleans, where the rate remained about 49%. Meanwhile,
the rate increased by more than 70% in Idaho Falls, Idaho (13.5% to 24.8%)
and Pueblo, Colorado (32.6% to 56.4%).

The coordination of care for chronically ill patients is more difficult when
patients are being seen by many different physicians. The percent of chroni-
cally ill Medicare patients seeing 10 or more different physicians during the
last six months of life varied more than twofold across HRRs for those dying
in 2018, from less than 25% to more than 65%. Rates were particularly high
in several regions in New York and New Jersey, including East Long Island,

New York (68.3%), Paterson, New
Jersey (67.6%), White Plains, New
York (67.3%), Ridgewood, New
Jersey (66.8%), and New Bruns-
wick, New Jersey (66.6%). Dece-
dents were much less likely to see
10 or more different physicians in
Marquette, Michigan (28.1%), Mis-
soula, Montana (28.8%), Apple-
ton, Wisconsin (30.4%), and Salt
Lake City (31.1%). Despite the
rapid increase in Idaho Falls, it re-
mained the lowest-ranked HRR in
2018 (Map 4).

Figure 4. Physician Utilization among Chronically Ill Medicare
Enrollees during the Last Six Months of Life (2011-18 deaths)

8 The Dartmouth Atlas of Health Care: 2018 Data Update

Physician Utilization

51.2

43.2

26.3
28.8

12.2
10.2

0

10

20

30

40

50

60

2011 2012 2013 2014 2015 2016 2017 2018P
hy

si
ci

an
u

til
iz

at
io

n
du

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ng
th
e
la
st
s
ix
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on
th
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of
li
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Percent seeing 10 or more physicians Physician visits per decedent

Number of different physicians seen

Map 4. Percent of Chronically Ill Medicare
Enrollees Seeing 10 or More Different
Physicians during the Last Six Months of
Life by Hospital Referral Region (2018 deaths)

A Report of the Dartmouth Atlas Project 9

The intensity of care for chronically ill patients varied to an even greater
degree across individual hospitals than HRRs. Among the hospitals most
heavily used by patients who died in 2018—those with at least 500 dece-
dents who received most of their inpatient care during the last two years of
life at these hospitals (N=371)—the average number of days patients with
chronic illnesses spent in the hospital in their last six months of life varied
more than threefold, from less than one week to nearly three (Figure 5). As
the New York City metropolitan HRRs ranked the highest for inpatient days
in the regional analysis, it should not be surprising that nine of the top ten
general hospitals ranked on this measure are located in the Manhattan and
East Long Island regions. Patients who received most of their inpatient care
at Mount Sinai Beth Israel Hospital in Manhattan spent an average of 19.1
days in the hospital during the last six months of life; total inpatient day
rates were also high at Maimonides Medical Center in Brooklyn (18.8 days),

North Shore University Hospital in
Manhasset (18.7), and New York-
Presbyterian Hospital in Manhat-
tan (18.5). By contrast, patients
spent fewer than seven days in the
hospital during the last six months
of life at four hospitals, including
two in the Salt Lake City region:
Intermountain Medical Center in
Murray (6.3) and Dixie Regional
Medical Center in St. George (6.6).
While some of this variation might
be the consequence of different
patients being served—more seri-
ously ill patients within a region
might be sent to tertiary academic
medical centers or to hospitals
specializing in cancer—there re-
mains considerable variation in
utilization across hospitals even
after adjusting for patient charac-
teristics.

While New York City hospitals
ranked highest for total inpatient
days, this was not the case for in-
tensive care days. Three hospitals
in Florida and three in New Jersey

Figure 5. Inpatient Days per Chronically Ill Medicare Enrollee during
the Last Six Months of Life among Hospitals with At Least 500
Deaths (N=371) (2018 deaths among enrollees with at least one
hospitalization during the last two years of life)

10 The Dartmouth Atlas of Health Care: 2018 Data Update

Hospital-level Variation

0
4
8

12

16

20

24

In
pa
tie
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d
ay
s
du
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ng
th
e
la
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s
ix
m
on
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s
of
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All
inpatient

days

Medical &
surgical

units

Intensive
care
units

U.S. average 10.6 6.2 4.4

Extremal ratio 3.15 12.2 15.8

Interquartile ratio 1.25 1.79 2.28

Coefficient of
variation

20.4 42.0 50.0

A Report of the Dartmouth Atlas Project 11

were among those where patients spent at least 10 days in intensive care
during the last six months of life, including Florida Hospital in Orlando (11.6),
St. Anthony’s Hospital in St. Petersburg (10.2), and Delray Medical Center in
Delray Beach (10.0) in Florida; and Kennedy University Hospital in Stratford
(10.4), Robert Wood Johnson University Hospital in New Brunswick (10.4),
and Riverview Medical Center in Red Bank (10.0) in New Jersey. Chronically
ill patients only spent about one day in intensive care at Concord Hospital in
Concord, New Hampshire (1.0), Berkshire Medical Center in Pittsfield, Massa-
chusetts (1.0), University of Colorado Memorial Hospital in Colorado Springs
(1.0), and St. Luke’s Regional Medical Center in Boise, Idaho (1.0).

Among the hospitals used most frequently by chronically ill patients who
died in 2018, there were 10 whose patient populations visited a particularly
large number of physicians, all located in New York, New Jersey, and Florida.
At Delray Medical Center, 85.8% of patients saw 10 or more different doctors
during their last six months of life, and the average patient saw 21 doctors;
similarly, 82.8% of patients at St. Francis Hospital in Roslyn, New York saw
at least 10 doctors, with an average of 25 doctors seen per patient. Less than
half of patients saw 10 or more different physicians at Dixie Regional Medical
Center in St. George, Utah (47.7%), Intermountain Medical Center in Murray,
Utah (48.2%), Mercy Medical Center in Redding, California (49.3%), and Nor-
man Regional Health System in Norman, Oklahoma (49.9%).

Thirty-Day Readmissions

In 2012, the Centers for Medicare & Medicaid Services (CMS) began penal-
izing hospitals for excessive readmissions within 30 days of discharge for
certain medical conditions and surgical procedures under the Hospital Re-
admissions Reduction Program (HRRP);3 these penalties were estimated to
have amounted to over $2.5 billion by fiscal year 2018.6 The average per-
cent of Medicare enrollees readmitted within 30 days following discharge
decreased between 2011 and 2018 for several medical conditions specifically
targeted by the HRRP, including heart failure (21.1% to 19.7%), acute myo-
cardial infarction (17.8% to 15.8%), and pneumonia (15.3% to 14.4%). De-
spite these reductions, the 30-day readmission rate following discharge for
any medical condition declined only slightly, from 15.9% to 15.1% (Figure 6).
Much of the reduction in 30-day readmission rates occurred between 2011
and 2014, perhaps suggesting that the initial focus on avoiding penalties in
the early years of the program has waned.

Across HRRs, the percent of Medicare enrollees readmitted within 30 days
of a medical discharge varied by a factor of 1.5 in 2018. More than 17% of
patients were readmitted in Miami (17.7%), Metairie, Louisiana (17.5%),

Jonesboro, Arkansas (17.3%),
Gainesville, Florida (17.2%), and
Dearborn, Michigan (17.2%). Less
than 13% of patients were read-
mitted in 12 HRRs, including Idaho
Falls, Idaho (12.1%) and all three
HRRs in Utah: Salt Lake City, Pro-
vo, and Ogden (all 12.2%) (Map 5).
The variation was higher for three
of the conditions targeted by CMS.
Readmissions within 30 days of
discharge varied about twofold
for congestive heart failure, from
12.4% to 25.4%; more than twofold
for acute myocardial infarction,
from 9.2% to 23.1%; and nearly
fourfold for pneumonia, from 5.6%
to 21.5%.

Figure 6. Percent of Medicare Enrollees Readmitted within 30
Days of Discharge Following a Medical Admission (2011-18)

12 The Dartmouth Atlas of Health Care: 2018 Data Update

Medical Discharges

19.7%

21.1%

15.8%

17.8%

15.1%

15.9%

14.4%15.3%

10%

15%

20%

25%

2011 2012 2013 2014 2015 2016 2017 2018
P
er
ce
nt

r
ea

dm
itt

ed
w

ith
in

3
0

da
ys

o
f d

is
ch

ar
ge

Heart Failure Acute Myocardial Infarction
All Medical Admissions Pneumonia

Map 5. Percent of Medicare Enrollees Readmit-
ted within 30 Days of Discharge Following a
Medical Admission by Hospital Referral Region
(2018)

A Report of the Dartmouth Atlas Project 13

*Maryland regions are not reported. Maryland hospitals
are exempt from HRRP payment reductions under a
separate agreement between CMS and Maryland.3

Primary Care and Preventive Services

Because primary and preventive services were already largely covered by
Medicare, the Affordable Care Act may have had a smaller impact on Medi-
care enrollees than on populations who gained insurance coverage after its
passage. There was a small overall increase in the use of primary care by
Medicare enrollees from 2011 to 2018; on average, the percent of enrollees
having at least one ambulatory visit to a primary care physician rose from
about 78% to 80%, despite a nationwide overall downward trend in the
number of primary care visits per person.7

The percent seeing a primary care physician in an ambulatory setting varied
by a factor of 1.6 across HRRs in 2018. About 90% of enrollees had a primary
care visit in Tupelo, Mississippi (90.8%), Albany, Georgia (90.3%), Oxford,
Mississippi (90.1%), Wilmington, North Carolina (90.0%), and Hattiesburg,
Mississippi (89.8%). Medicare enrollees were less likely than average to
see a primary care physician in the Bronx, New York (62.1%), San Francisco
(65.9%), Lebanon, New Hampshire (66.0%), Duluth, Minnesota (66.2%),
and Miami (66.6%) (Map 6).i

i These regions were among the lowest with regard to averaging over a longer period. Sudden
declines in rates of primary care visits were observed in several regions—for example, Port-
land, Maine and Elyria, Ohio—between 2015 and 2016. We ruled out several candidates (e.g.,
shifts in the population covered under fee-for-service Medicare); ultimately, we suspected
but could not prove that the declines were due to an increase in the number of primary care
alternative payment models, where visits are bundled and thus not necessarily reported in
the fee-for-service claims data. Caution should be used in interpreting longitudinal data for
primary care measures going forward.

14 The Dartmouth Atlas of Health Care: 2018 Data Update

Percent Seeing a Primary Care Physician

Map 6. Percent of Medicare Enrollees Having
At Least One Visit to a Primary Care Physician
in an Ambulatory Setting by Hospital Referral
Region (2018)

A Report of the Dartmouth Atlas Project 15

The National Committee for Quality Assurance (NCQA) recommends that di-
abetic patients between the ages of 18 and 75 receive annual screening tests
in order to manage their condition and reduce the risk of complications, in-
cluding hemoglobin A1c testing to measure blood glucose levels and retinal
examinations to reduce the risk of blindness.8 Among Medicare enrollees
with diabetes aged 65 to 75, the likelihood of receiving these tests remained
relatively static between 2011 and 2018, on average (Figure 7).ii

There was considerable variation in rates of both screening tests for diabet-
ic Medicare enrollees aged 65 to 75 among HRRs in 2018. Just over half had
an eye exam in the Texas regions of Odessa (52.2%) and Lubbock (56.2%),
while about 80% did so in the Iowa regions of Cedar Rapids (80.6%) and
Waterloo (79.5%). The rate for hemoglobin A1c screening was under 70% in
Great Falls, Montana (58.6%) and Albuquerque, New Mexico (68.0%) and
over 92% in the Wisconsin regions of Neenah (94.1%), Appleton (92.7%),
Green Bay (92.2%), and Madison (92.1%).

The percent of female Medicare enrollees aged 67 to 69 having at least one
mammogram every two years also showed a slight increase from 2011 to

2018, from about 63% to 65% (Fig-
ure 7). The mammography rate
rose by more than 20% in Coving-
ton, Kentucky (55.6% to 69.4%),
Pittsburgh (53.5% to 66.1%), and
Sioux City, Iowa (58.2% to 70.1%).
A lower percent of female Medi-
care enrollees received mam-
mograms in 2018 than in 2011 in
the California regions of Redding
(64.3% to 58.5%) and Salinas
(64.3% to 58.8%). In 2018, the rate
ranged from about half of wom-
en in Odessa, Texas (46.9%), El
Paso, Texas (52.6%), and Casper,

Figure 7. Percent of Medicare Enrollees Receiving Recommended
Screening Tests (2011-18)

16 The Dartmouth Atlas of Health Care: 2018 Data Update

Preventive Screening Tests

84.2%
86.7%

66.7%
68.0%

62.9%
65.0%

50%
60%
70%
80%
90%
2011 2012 2013 2014 2015 2016 2017 2018
P
er
ce
nt

o
f e

nr
ol

le
es

r
ec

ei
vi

ng
s

cr
ee

ni
ng

te
st

HbA1c Test (diabetics aged 65-75) Eye Exam (diabetics aged 65-75)

Mammography (women aged 67-69)

ii As with primary care visits, we noted large
changes in rates of secondary screening
for diabetics for a few regions between
2017 and 2018, including substantial de-
creases in hemoglobin A1c testing in sev-
eral HRRs in Montana and North Dakota.
Again, we could not establish a conclusive
explanation for these changes, especially
in smaller rural areas; caution should be
used in interpreting longitudinal data for
these measures.

Wyoming (52.7%) to more than three quarters of
women in Neenah, Wisconsin (78.5%), Cedar Rap-
ids, Iowa (78.2%), and Boston (77.2%) (Map 7). Al-
though the NCQA revised its quality metric in 2014
to include women aged 70 to 74,9 women between
the ages of 60 and 69 are most likely to benefit
from mammography,10 so the Dartmouth Atlas has
kept this measure constant in order to allow trends
to be analyzed.

Map 7. Percent of Female Medicare
Enrollees Aged 67-69 Receiving At Least
One Mammogram in the Last Two Years
by Hospital Referral Region (2018)

A Report of the Dartmouth Atlas Project 17

Summing Up

18 The Dartmouth Atlas of Health Care: 2018 Data Update

This short Atlas report updated measures of Medicare expenditures, end-of-
life care, readmission rates, and the quality of ambulatory care using 2018
Medicare claims data. There are some hopeful signs in the trends; inflation-
adjusted Medicare expenditures per enrollee were relatively constant—one
of the few cases in health care where expenditures per person have not
grown—while the influence of “outlier” regions such as Miami and McAllen,
Texas has diminished. Readmission rates have declined, while quality mea-
sures have risen. Despite these aggregate improvements, however, changes
over time in expenditures, readmission rates, and quality of care continue
to exhibit wide variation, with little change in the interquartile ranges (the
ratio of spending and other measures between the 75th to the 25th percentile
HRR). Furthermore, the averages mask considerable geographic variability
in changes over time. In some regions, for example, rates of mammography
rose, while in others they fell. Documenting these changes over time is es-
sential for providers and policymakers to understand whether their efforts
to reduce expenditures and improve quality have been successful; a more
difficult question is why some regions improved so much, while others did
not.

With 2019 data becoming available, a new Atlas focusing on racial and eth-
nic disparities in health and health care and how these disparities interact
with regions11 is under development. The 2020 Atlas report will address the
geographic variability in both mortality and expenditures across HRRs that
has arisen during the COVID-19 pandemic. As these reports will continue to
demonstrate, the influence of place in health and health care has only be-
come more important.

1. National Conference of State Legislatures. The Affordable Care Act: A Brief Sum-
mary. Available from: https://www.ncsl.org/research/health/the-affordable-care-
act-brief-summary.aspx (Accessed April 16, 2021).

2. Forum on Medical and Public Health Preparedness for Catastrophic Events;
Board on Health Sciences Policy; Board on Health Care Services; Institute of
Medicine. The Impacts of the Affordable Care Act on Preparedness Resources and
Programs: Workshop Summary. Washington (DC): National Academies Press (US);
2014 Aug 27. F, Key Features of the Affordable Care Act by Year. Available from:
https://www.ncbi.nlm.nih.gov/books/NBK241401/ (Accessed April 16, 2021).

3. Centers for Medicare & Medicaid Services. Hospital Readmissions Reduction
Program (HRRP). Available from: https://www.cms.gov/Medicare/Quality-Initia-
tives-Patient-Assessment-Instruments/Value-Based-Programs/HRRP/Hospital-
Readmission-Reduction-Program (Accessed April 16, 2021).

4. Parikh RB, Wright AA. The Affordable Care Act and End-of-Life Care for Patients
with Cancer. Cancer J. 2017 May/Jun;23(3):190-193.

5. O’Malley AJ, Bubolz TA, Skinner JS. The Diffusion of Health Care Fraud: A Net-
work Analysis. National Bureau of Economic Research, 2021. Working Paper. Avail-
able from: https://www.nber.org/papers/w28560 (Accessed April 29, 2021).

6. American Hospital Association. Hospital Readmission Reduction Program.
Available from: https://www.aha.org/hospital-readmission-reduction-program/
home (Accessed April 16, 2021).

7. Ganguli, I., Lee, T.H. & Mehrotra, A. Evidence and implications behind a national
decline in primary care visits. J Gen Intern Med. 2019 Oct;34(10):2260-2263.

8. National Committee for Quality Assurance. Comprehensive Diabetes Care
(CDC). Available from: https://www.ncqa.org/hedis/measures/comprehensive-dia-
betes-care/ (Accessed April 16, 2021).

9. Onega T, Haas JS, Bitton A, Brackett C, Weiss J, Goodrich M, Harris K, Pyle S,
Tosteson AN. Alignment of breast cancer screening guidelines, accountability met-
rics, and practice patterns. Am J Manag Care. 2017 Jan;23(1):35-40.

10. U.S Preventive Services Task force. Breast Cancer: Screening. Available from:
https://www.uspreventiveservicestaskforce.org/uspstf/recommendation/breast-
cancer-screening (Accessed April 16, 2021).

11. Baicker K, Chandra A, Skinner JS, Wennberg JE. Who you are and where you
live: How race and geography affect the treatment of Medicare beneficiaries.
Health Aff (Millwood). 2004;Suppl Variation:VAR33-44. doi: 10.1377/hlthaff.var.33.

A Report of the Dartmouth Atlas Project 19

References

https://www.ncsl.org/research/health/the-affordable-care-act-brief-summary.aspx

https://www.ncsl.org/research/health/the-affordable-care-act-brief-summary.aspx

https://www.ncbi.nlm.nih.gov/books/NBK241401/

https://www.cms.gov/Medicare/Quality-Initiatives-Patient-Assessment-Instruments/Value-Based-Programs/HRRP/Hospital-Readmission-Reduction-Program

https://www.cms.gov/Medicare/Quality-Initiatives-Patient-Assessment-Instruments/Value-Based-Programs/HRRP/Hospital-Readmission-Reduction-Program

https://www.cms.gov/Medicare/Quality-Initiatives-Patient-Assessment-Instruments/Value-Based-Programs/HRRP/Hospital-Readmission-Reduction-Program

https://www.nber.org/papers/w28560

https://www.aha.org/hospital-readmission-reduction-program/home

https://www.aha.org/hospital-readmission-reduction-program/home

Comprehensive Diabetes Care

Comprehensive Diabetes Care

https://www.uspreventiveservicestaskforce.org/uspstf/recommendation/breast-cancer-screening

https://www.uspreventiveservicestaskforce.org/uspstf/recommendation/breast-cancer-screening

Contact:
Media inquiries: TDI.Communications@dartmouth.edu
General inquiries: TDI.Atlas@dartmouth.edu

The Dartmouth Atlas Working Group:
Kristen Bronner, MA
M. Scottie Eliassen, MS
Elliott Fisher, MD, PhD
David Goodman, MD, MS
Ashleigh King, MPH
Christopher Leggett, PhD
Sukdith Punjasthitkul, MS
Jonathan Skinner, PhD
John Wennberg, MD, MPH

Copyright 2021 The Trustees of Dartmouth College

mailto:TDI.Communications%40dartmouth.edu?subject=2018%20Data%20Report

mailto:TDI.Atlas%40dartmouth.edu?subject=2018%20Data%20Report

RESPOND TO EACH RESPONSE WITH 50 WORDS MINIMUM
 
R1
The reason why mergers and market consolidation in healthcare have been so prevalent in the last 20years despite prices hardly changing for consumers are due to a variety of factors. Consolidation and mergers offer possible advantages, such as competition elimination and price increases. Hospitals in highly focused markets can charge higher prices for medical services and have greater leverage to negotiate higher prices from healthcare insurance providers. This leads to ever increasing healthcare costs for individuals and families. While the hospitals are benefiting from these mergers and consolidations, consumers have not benefited at all, nor through quality of care or price reductions. Many studies have concluded that these mergers are for the sole purpose of negotiating power with payers and therefore did not lead to true integration.
 
According to the Dartmouth report, regional variations in the different states mentioned are changes in Medicare spending across hospital referral regions. Death rates in areas where there is less capacity and less utilization are not higher than deaths rates in areas where there is much higher capacity and utilization. Another reason for variation in efficiency is that it is related to practice style as it relates to the way Physicians in the region practice medicine.
 
R2
The main reason why mergers and market consolidations in the health care sector have become so prevalent over the past two decades is because the advocate believed that they could increase efficiencies and reduce costs in the medical field. In practice, however, mergers and market consolidations result in a monopoly on patients’ service, raising medical costs, and increasing health care management costs through the purchase of new buildings and the increase in hiring of health care workers.
 
The increase in the use of hospice services by Medicare members with chronic diseases was attended by a decrease in hospital use. The proportion of chronically ill Medicare patients dying in hospitals fell from 24.1% in 2011 to 20.4% in 2018. Among Chronically ill Medicare patients who died in 2018, patients in metropolitan New York City spent about two weeks in a hospital during the last six months, while patients in Utah spent less than five days in a dying hospital. Personally, I think this is because patients in large cities are easy to have an access to hospitals.
 
References:
 
Bronner, K., Eliassen. M. S., King, A., Leggett, C., Punjasthitkul, S., & Skinner, J. (2021). The Dartmouth Atlas of Health Care: 2018 Data Update. Dartmouth Atlas Project.
 
 
Gale, A. H. (2015). Bigger But Not Better: Hospital Mergers Increase Costs and Do Not Improve Quality. National Library of Medicine. https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6170097/
 
R3
Are mergers and acquisitions ever good in healthcare? Can they bring the promised efficiency, cost savings, and improved patient care that is always promised when they are proposed?
 
 
Deloitte’s Center for Health Solutions in collaboration with the Healthcare Financial Management Association, (HFMA), seems to think so.
 
According to HFMA and Deloitte “Hospital mergers and acquisitions When done well, M&A can achieve valuable outcomes” (n.d.),  “In our survey, we also found other positive outcomes associated with mergers and acquisitions in the health care industry, including the ability to make capital investments and achieve cost efficiencies from economies of scale.” (para. 3)

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