2341_sejda-DYJ.pdf - Chapter 12 References DOE 2014a Appliance and Equipment Standards Program U.S Department of Energy Office of Energy Efficiency and

2341_sejda-DYJ.pdf - Chapter 12 References DOE 2014a...

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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, 2018). 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 vaccination rate, 2018 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: . (Accessed: 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, 2018). DOT. 2016c. VMT per Capita. U.S. Department of Transportation. Last revised: February 2, 2016. Available at: . (Accessed: February 27, 2018). 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 Commission 2010).) 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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