Unformatted text preview: Chapter 12 References DOE. 2014a. Appliance and Equipment Standards Program. U.S. Department of Energy, Office of Energy
Efficiency and Renewable Energy. Available at: . (Accessed: February 27,
DOE. 2014b. Saving Energy and Money with Appliance and Equipment Standards in the United States.
DOE/EE-1086. May 2014. U.S. Department of Energy, Office of Energy Efficiency and Renewable
Energy. Available at:
f. (Accessed: February 27, 2018).
DOE. 2015a. Climate Change and the U.S. Energy Sector: Regional Vulnerabilities and Resilience
Solutions. DOE/EPSA-0005. October 2015. U.S. Department of Energy, Office of Energy Policy and
Systems Analysis. Available at:
olutions_0.pdf. (Accessed: February 27, 2018).
DOE. 2015a. citing CIG. 2013. Climate Change in the Northwest: Implications for Our Landscapes,
Waters, and Communities. [Dalton, M., P. Mote, and A. Snover (Eds)]. Island Press: Washington, D.C.
Available at: . (Accessed: February 26, 2018).
DOE. 2015a. citing DOE. 2013c. U.S. Energy Sector Vulnerabilities to Climate Change and Extreme
Weather. DOE/PL-0013. July 2013. U.S. Department of Energy. Available at:
. (Accessed: February 27, 2018).
DOE. 2015a. citing GCRP. 2014. Global Climate Change Impacts in the United States: The Third National
Climate Assessment. U.S. Global Change Research Program. [Melillo, J.M, T.C. Richmond, and G.W.
Yohe (Eds.)]. U.S. Government Printing Office: Washington, D.C. 841 pp. doi:10.7930/J0Z31WJ2.
Available at: .
DOE. 2015b. Climate Change and Energy Infrastructure Exposure to Storm Surge and Sea-Level Rise. U.S.
Department of Energy, Office of Energy Policy and Systems Analysis andOak Ridge National
Laboratory. Available at:
e%20and%20Sea-Level%20Rise_0.pdf. (Accessed: June 18, 2018).
DOE. 2016a. Advanced Transmission Technologies. U.S. Department of Energy, Office of Energy
Efficiency and Renewable Energy. Available at:
. (Accessed: February 27, 2018).
DOE. 2016b. Flex Fuel Vehicles. U.S. Department of Energy, Office of Energy Efficiency and Renewable
Energy. Available at: . (Accessed: February 27,
2018). 12-14 TABLE In 2018, influenza vaccination rates for contracts serving
exclusively Arizona varied, with lower rates among SNP contracts 13–9 Share of enrollment
under age 65
in December 2016 Contract SNP status and enrollment distribution, 2018 H0354 Non-SNP (91 percent of enrollment) and C–SNP H2593 Non-SNP (48 percent); C–SNP (40 percent); I–SNP (12 percent);
(In 2019, Maricopa County has only 1 I–SNP available) 9% Influenza
77% 14 72 H0302 Non-SNP only 9 71 R7220 Non-SNP only (regional PPO plan) N/A 68 H0351 Non-SNP (89 percent) and C–SNP 14 65 H5580 SNP-only contract, 100 percent D–SNP 45 65 H0321 SNP-only contract, 100 percent D–SNP 44 64 H4931 SNP-only contract, 100 percent D–SNP 42 63 H5430 SNP-only contract, 100 percent D–SNP 49 61 H5587 SNP-only contract, 100 percent D–SNP 49 55 Note: SNP (special needs plan), C–SNP (chronic conditions SNP), I–SNP (institutional SNP), PPO (preferred provider organization), D–SNP (dual-eligible SNP). Source: MedPAC analysis of CMS enrollment data and plan reports, CMS data on CAHPS® (Consumer Assessment of Healthcare Providers and Systems Survey®)
vaccination rates. enrolled residents of Arizona (though one of those
contracts will no longer be an Arizona-only contract
because in 2019 it is being consolidated with Texas and
Tennessee contracts). Table 13-9 shows the variation in
CAHPS influenza vaccination rates among those contracts
and the features of those contracts that may explain some
of the variation.
Among the contracts listed in Table 13-9, all contracts
that exclusively serve Medicare–Medicaid dually eligible
beneficiaries (and that have high shares of beneficiaries
entitled to Medicare based on disability) perform relatively
poorly on the influenza vaccination measure. Although
the influenza vaccination rate was a measure that CMS
evaluated for adjustment based on low-income status and
disability through the peer-grouping process used for
MA plan star ratings (the categorical adjustment index),
CMS concluded that the measure did not have significant
systematic differences across the population categories
within MA plans (though one might argue, based on the
Arizona data, that a reevaluation of this conclusion result
may be worthwhile). In our hypothetical example of a resident of Phoenix,
a Medicare–Medicare dually eligible beneficiary
considering enrolling in one of the D–SNP-only
contracts might decide to choose FFS based on the
sector’s apparently better performance on the influenza
vaccination rate. However, the FFS rate of 74 percent
may be misleading. The vaccination rate differences that
we see between D–SNPs and non-SNP plans suggest
that there are significant differences in vaccination rates
based on beneficiaries’ dual-eligibility status. If dual
status, in Arizona at least, explains differences in influenza
vaccination rates, the FFS rate (and plan rates in a
geographic area) should be stratified by dual-eligible status
to better compare FFS and MA results and to compare
results within the MA sector. The 74 percent vaccination
rate in FFS is the result for a population that, as of
December 2016, in Arizona, consisted of 90 percent nondual-eligibles and 10 percent dually eligible beneficiaries,
as compared with the MA population consisting of 71
percent non-dual-eligibles and 29 percent dually eligible
beneficiaries. Report to the Congress: Medicare Payment Policy | March 2019 371 Chapter 12 References DOE. 2018a. Energy Intensity Indicators: Highlights. U.S. Department of Energy, Office of Energy
Efficiency and Renewable Energy. Available at: . (Accessed: April 12, 2018).
DOE. 2018b. Hydrogen and Fuel Cell Program Overview. U.S. Department of Energy, Office of Energy
Efficiency and Renewable Energy. Available at:
June 21, 2018).
DOI (U.S. Department of the Interior). 2005. Water 2025—Preventing Crises and Conflict in the West.
U.S. Department of the Interior: Washington, D.C. Available at:
&isAllowed=y. (Accessed: February 27, 2018).
DOT (U.S. Department of Transportation). 2009. Statement from the U.S. Department of Transportation.
January 7, 2009. Available at: . (Accessed: June 4, 2012).
DOT. 2014. Final Guidance on MAP-21 Section 1319 Accelerated Decision Making in Environmental
Reviews. U.S. Department of Transportation. Available at: .
(Accessed: May 4, 2015).
DOT. 2016a. Table 4-23: Average Fuel Efficiency of U.S. Light Duty Vehicles. U.S. Department of
Transportation, Bureau of Transportation Statistics. Available at:
stics/html/table_04_23.html. (Accessed: February 26, 2018).
DOT. 2016b. Department of Transportation Environmental Justice Strategy. U.S. Department of
Transportation. Last revised: January 5, 2016. Available at: . (Accessed: February 27,
DOT. 2016c. VMT per Capita. U.S. Department of Transportation. Last revised: February 2, 2016.
Available at: . (Accessed: February 27,
Dubowsky Adar, S., G. Adamkiewicz, D.R. Gold, J. Schwartz, B.A. Coull, and H. Suh. 2007. Ambient and
Microenvironmental Particles and Exhaled Nitric Oxide before and after a Group Bus Trip.
Environmental Health Perspectives 115(4):507–512. doi:10.1289/ehp.9386. Available at:
. (Accessed: February 27, 2018).
Dubreuil, A., L. Bushi, S. Das, A. Tharumarajah, and G. Xianzheng. 2010. A Comparative Life Cycle
Assessment of Magnesium Front End Autoparts: A Revision to 2010-01-0275. P. SAE Technical Paper
2012-01-2325. SAE International. doi:10.4271/2012-01-2325.
Dunn, J.B., L. Gaines, J. Sullivan, J., and M.Q. Wang. 2012. Impact of recycling on cradle-to-gate energy
consumption and greenhouse gas emissions of automotive lithium-ion batteries. Environmental
Science & Technology 46(22):12704-12710. doi:10.1021/es302420z. 12-15 Stratification of results would require sufficient sample
sizes for the CAHPS measures based on surveys,
measures based on the Health Outcomes Survey, and the
many measures that MA plans report that are based on a
sampling of medical records. The National Committee
for Quality Assurance (NCQA) is requiring MA plans
to report certain Healthcare Effectiveness Data and
Information Set® (HEDIS®) measures on a stratified basis
beginning in 2019. The four measures are breast cancer
screening, all-cause readmissions, and two measures that
plans report based on medical record sampling: colorectal
cancer screening and eye exams for diabetics. Measures
are to be reported by low-income-subsidy status, Medicaid
dual-eligibility status, and disability status. The rationale
for the stratified reporting is that NCQA found that “a
Medicare Advantage plan’s performance on quality
measures is sensitive to its proportion of beneficiaries who
have lower socioeconomic status” (National Committee
for Quality Assurance 2018).
Current quality results
As discussed in our March 2018 report to the Congress,
with the wave of consolidations, it has become more
difficult to make general statements about the quality of
care in MA and changes from year to year. The approach
settled on in that report was to rely on enrollmentweighted average results across all contracts as the
most logical way of providing a general picture of MA
quality. Below, we provide an update to the reporting of
enrollment-weighted measure results, but the approach is
not entirely satisfactory because a number of important
measures are determined through a sampling of a small
number of medical records at the contract level (411
per contract). To the extent that a contract covers a wide
geographic area, each area will represent a small segment
of the sample, and geographic variation in measure results
may not be adequately captured. This issue and additional
issues in the determination of star ratings are discussed in
detail after the review of current quality results.
Using CMS data on weighted average HEDIS results and
comparing data from the most recent year to the prior
year’s data, the large majority of the 50 measures that
can be compared showed little change (a change of 3
percent or less) between 2017 and 2018. Two measures
used for star ratings improved at relatively substantial
rates: osteoporosis management in women with a fracture
(improving by 12 percent, to 51.9 percent) and medication
reconciliation postdischarge (improving by 8 percent,
to 63.2 percent). Seven measures—none of which are 372 The Medicare Advantage program: Status report used for star ratings—showed a decline of greater than 3
percent between 2017 and 2018. One declining measure
was the frequency of prescribing high-risk medications
for the elderly (that is, plans reported higher rates of
such use). The remaining six measures that declined
pertained to treatment of mental health or alcohol/
drug dependency. (The star measures include only one
mental health measure, which is the Health Outcomes
Survey (HOS) measure of whether a beneficiary reports
maintenance or improvement in his or her mental health.
The Commission’s March 2010 report to the Congress
noted that CMS advised us at that time that the available
mental health measures applied to too few people to be
included as star measures (Medicare Payment Advisory
Between 2017 and 2018, the enrollment-weighted
average rates were unchanged for the star-related HEDIS
measures collected through the HOS (monitoring physical
activity, reducing the risk of falling, and improving
bladder control). The same is true for the HOS-based
measures of whether beneficiaries reported improvement
or maintenance of their physical health (one measure) or
their mental health (a separate measure). There was also
virtually no change in the six star measures taken from
the CAHPS patient experience surveys or the influenza
vaccination rate measure collected through the CAHPS
survey (Table 13-10).
We used the enrollment-weighted approach to examine 19
HEDIS, HOS, and CAHPS star-rating measures that we
were able to compare over a longer period of time (over
the last 4 years, 2016 to 2019, or 3 periods of year-to-year
changes) and that we examined separately for HMOs
and local PPOs. The majority of measures did not show
major changes over this period. For example, among the
measures included in Table 13-10, for both HMOs and
local PPOs, there was virtually no change in CAHPS
measure results or the influenza vaccination rates over the
three-year period. However, the measure of reducing the
risk of falling declined between 2016 and 2019 for both
HMOs (by 6 percent) and local PPOs (by 5 percent); and
among local HMOs, the measurement of maintenance or
improvement of mental health improved by 5 percent.
Overall among HMOs, 5 of 19 measures improved by 3
percent or more, and only the measure of reducing the risk
of falling declined in the 2016 to 2019 period. A measure
showing major improvement was the osteoporosis
management measure (improving by 22 percent). Trending ...
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