Advertisement

Health Services Data: The Centers for Medicare and Medicaid Services (CMS) Claims Records

  • Ross M. MullnerEmail author
Reference work entry
Part of the Health Services Research book series (HEALTHSR)

Abstract

The US Centers for Medicare and Medicaid Services (CMS) is the largest purchaser of healthcare in the nation – serving almost 123 million people, more than one in three Americans. CMS is responsible for administering and overseeing three of the nation’s largest ongoing healthcare programs: Medicare, Medicaid, and the Children’s Health Insurance Program (CHIP). The Medicare program provides government-sponsored health insurance for people 65 or older and under age 65 with certain diseases and disabilities. The Medicaid program, which is a joint state-federal program, provides healthcare for the poor. CHIP is a grant program that provides health insurance to targeted low-income children in families with incomes above Medicaid eligibility levels. CMS sponsors many data and information initiatives for health services researchers, policymakers, educators, students, and the general public. In 2014, CMS established the Office of Enterprise Data and Analytics (OEDA) to better oversee and coordinate its large portfolio of data and information. The office also funds the privately run Research Data Assistance Center (ResDAC), which provides training and technical assistance to individuals requesting the agency’s data files. CMS information products include an online research journal Medicare and Medicaid Research Review (MMRR); other publications including Medicare and Medicaid Statistical Supplement, Statistics Reference Booklet, and CMS Fast Facts; a data navigator; and several interactive dashboards. Its data products include numerous Medicare and Medicaid public use data files, the Chronic Conditions Data Warehouse (CCW), the Medicare Current Beneficiary Survey (MCBS) files, and the Medicare Qualified Entity (QE) Program. Many examples of CMS’ information and data products are highlighted and discussed.

References

  1. Adler GS. A profile of the medicare current beneficiary survey. Health Care Financ Rev. 1994;15(4):153–63. Available at: www.cms.gov/Research-Statistics-Data-and-Systems/Research/HealthCareFinancingReview/Downloads/CMS1191330dl.pdf
  2. Asper F. Introduction to Medicare cost reports. Slide presentation. Minneapolis: Research Data Assistance Center; 2013. Available at: www.resdac.org/sites/resdac.org/files/IntroductiontoMedicare Cost Reports (Slides).pdf
  3. Baker LC, Kate Bundorf M, Kessler DP. Patients’ preferences explain a small but significant share of regional variation in Medicare spending. Health Aff. 2014;33(6):957–63.CrossRefGoogle Scholar
  4. Blumenthal D, Davis K, Guterman S. Medicare at 50 – moving forward. N Engl J Med. 2015;372(7):671–7. Available at: www.nejm.org/doi/full/10.1056/NEJMhpr1414856CrossRefGoogle Scholar
  5. Borck R, Laura R, Vivian B, Wagnerman K. The Medicaid analytic extract 2010 chartbook. Baltimore: Centers for Medicare and Medicaid Services; 2014. Available at: www.mathematica-mpr.com/~/media/publications/pdfs/health/maxchartbook_2010.pdf
  6. Bowen SE. Evaluating outcomes of care and targeting quality improvement using Medicare Health Outcomes Survey data. J Ambul Care Manage. 2012;35(4):260–2.CrossRefGoogle Scholar
  7. Brennan N, Oelschlaeger A, Cox C, Tavenner M. Leveraging the big-data revolution: CMS is expanding capabilities to spur health system transformation. Health Aff. 2014;33(7):1195–202.CrossRefGoogle Scholar
  8. Briesacher BA, Tjia J, Doubeni CA, Chen Y, Rao SR. Methodological issues in using multiple years of the medicare current beneficiary survey. Medicare Medicaid Res Rev. 2012;2(1):E1–19. Available at: www.cms.gov/mmrr/downloads/mmrr2012_002_01_a04.pdfCrossRefGoogle Scholar
  9. Buccaneer Computer Systems and Service. Chronic conditions data warehouse: Medicare administrative data user guide. Version 3.1. 2015. Available at: www.ccwdata.org
  10. Bundy DG, Solomon BS, Kim JM, et al. Accuracy and usefulness of the HEDIS childhood immunization measures. Pediatrics. 2012;129(4):648–56. Available at: www.ncbi.nlm.nih.gov/pmc/articles/PMC3313643/CrossRefGoogle Scholar
  11. Burwell SM. Setting value-based payment goals – HHS efforts to improve U.S. health care. N Engl J Med. 2015;372(10):897–9. Available at: www.nejm.org/doi/full/10.1056/NEJMp1500445CrossRefGoogle Scholar
  12. Centers for Medicare and Medicaid Services (CMS). CMS announces data and information initiative. Fact Sheet. 2012. Available at: www.cms.gov/Research-Statistics-Data-and-Systems/Research/ResearchGeninfo/Downloads/OIPDA_Fact_Sheet.pdf
  13. Centers for Medicare and Medicaid Services (CMS). Centers for Medicare and Medicaid services: justification of estimates for appropriations committees. Baltimore: Centers for Medicare and Medicaid Services; 2015, p. 2. Available at: www.cms.gov/About-CMS/Agency-Information/PerformanceBudget/Downloads/FY2015-CJ-Final.pdf
  14. Centers for Medicare and Medicaid Services (CMS). CMS strategy: the road forward: 2013–2017. Baltimore: Centers for Medicare and Medicaid Services; 2013. Available at: www.cms.gov/About-CMS/Agency-Information/CMS-Strategy/Downloads/CMS-Strategy.pdf
  15. Centers for Medicare and Medicaid Services (CMS). Medicare and you, 2015. Baltimore: Centers for Medicare and Medicaid Services; 2015. Available at: www.medicare.gov/Pubs/pdf/10050.pdf
  16. Chen C, Petterson S, Phillips R, et al. Spending patterns in region of residency training and subsequent expenditures for care provided by practicing physicians for Medicare beneficiaries. JAMA. 2014;312(22):2385–92.CrossRefGoogle Scholar
  17. Chronic Condition Data Warehouse. About chronic condition data warehouse. Available at: www.ccwdata.org/web/guest/about-ccw
  18. Cohen AB, Colby DC, Wailoo K, Zelizer J, editors. Medicare and Medicaid at 50: America’s entitlement programs in the age of affordable care. New York: Oxford University Press; 2015.Google Scholar
  19. Erdem E, Concannon TW. What do researchers say about proposed Medicare claims public use files? J Comp Eff Res. 2012;1(6):519–25.CrossRefGoogle Scholar
  20. Erdem E, Korda HH, Haffer SC, Sennett C. Medicare claims data as public use files: a new tool for public health surveillance. J Public Health Manag Pract. 2014;20(4):445–52.CrossRefGoogle Scholar
  21. Ewing MT, editor. State Children’s Health Insurance Program (SCHIP). New York: Nova; 2008.Google Scholar
  22. Feder J, Komisar HL. The importance of federal financing to the nation’s long-term care safety net. 2012. Available at: www.thescanfoundation.org
  23. General Dynamics Information Technology. Centers for Medicare and Medicaid Services Chronic Condition Data Warehouse (CCW): national Medicare and Medicaid research database. Fairfax: General Dynamics Information Technology; 2013. Available at: www.gdit.com/globalassets/health/6978_ccw.pdf
  24. Haffer SC, Bowen SE. Measuring and improving health outcomes in Medicare: the Medicare HOS program. Health Care Financ Rev. 2004;25(4):1–3. Available at: www.ncbi.nlm.nih.gov/pmc/articles/PMC4194894/
  25. Henry J. Kaiser Family Foundation. Medicaid moving forward. Kaiser Commission on Medicaid and the Uninsured, Fact Sheet. 2015. Available at: www.kff.org
  26. Henry J. Kaiser Family Foundation. The medicare Part D prescription drug benefit. Fact Sheet. 2014. Available at: www.kff.org
  27. Henry J. Kaiser Family Foundation. State demonstration proposals to align financing and/or administration for dual eligible beneficiaries. February 2015. Fact Sheet. 2015. Available at: www.kff.org
  28. Holmes GM, Pink GH, Friedman SA. The financial performance of rural hospitals and implications for elimination of the critical access hospital program. J Rural Health. 2013;29(2):140–9.CrossRefGoogle Scholar
  29. Hostetter M, Klein S. Medicare data helps fill in picture of health care performance. Quality Matters: The Commonwealth Fund Newsletter. 2013. Available at: www.commonwealthfund.org/publications/newsletters/quality-matters/2013/april-may/in-focus
  30. Kane NM, Magnus SA. The Medicare cost report and the limits of hospital accountability: improving financial accounting data. J Health Polit Policy Law. 2001;26(1):81–106.CrossRefGoogle Scholar
  31. Lutfiyya MN, Gessert CE, Lipsky MS. Nursing home quality: a comparative analysis using CMS nursing home compare data to examine differences between rural and non-rural facilities. J Am Med Dir Assoc. 2013;14(8):593–8.CrossRefGoogle Scholar
  32. National Conference of State Legislatures. Children’s health: trends and options for covering kids. Washington, DC: National Conference of State Legislatures; 2014. Available at: www.ncsl.org/documents/health/coveringkids914.pdf
  33. Office of the Assistant Secretary for Planning and Evaluation, U.S. Department of Health and Human Services. The Medicare advantage program in 2014. ASPE Issue Brief. 2014. Available at: http://aspe.hhs.gov
  34. Orentlicher D. Medicaid at 50: no longer limited to the ‘Deserving’ poor? Yale J Health Policy Law Ethics. 2015;15(1):185–95.PubMedGoogle Scholar
  35. Palmsten K, Huybrechts KF, Kowal MK, et al. Validity of maternal and infant outcomes within nationwide Medicaid data. Pharmacoepidemiol Drug Saf. 2014;23(6):646–55.CrossRefGoogle Scholar
  36. Petroski J, Ferraro D, Chu A. Ever enrolled Medicare population estimates from the MCBS access to care files. Medicare Medicaid Res Rev. 2014;4(2):E1–16. Available at: www.cms.gov/mmrr/Downloads/MMRR2014_004_02_a05.pdfCrossRefGoogle Scholar
  37. Pugh MJV, Marcum ZA, Copeland LA, et al. The quality of quality measures: HEDIS quality measures for mediation management in the elderly and outcomes associated with new exposure. Drugs Aging. 2013;30(8):645–54. Available at: www.ncbi.nlm.nih.gov/pmc/articles/PMC3720786/CrossRefGoogle Scholar
  38. Rust G, Zhang S, Reynolds J. Inhaled corticosteroid adherence and emergency department utilization among Medicaid-enrolled children with asthma. J Asthma. 2013;50(7):769–75. Available at: www.ncbi.nlm.nih.gov/pmc/articles/PMC4017346/CrossRefGoogle Scholar
  39. Saunders MR, Chin MH. Variation in dialysis quality measures by facility, neighborhood, and region. Med Care. 2013;51(5):413–7. Available at: www.ncbi.nlm.nih.gov/pmc/articles/PMC3651911/CrossRefGoogle Scholar
  40. Stein BD, Pangilnan M, Sorbero MJ, et al. Using claims data to generate clinical flags predicting short-term risk of continued psychiatric hospitalizations. Psychiatr Serv. 2014;65(11):1341–6.CrossRefGoogle Scholar
  41. U.S. Government Accountability Office. Health care transparency: actions needed to improve cost and quality information for consumers. Washington, DC: U.S. Government Accountability Office; 2014. Available at: www.gao.gov/products/GAO-15-11
  42. Wennberg JE. Tracking medicine: a researcher’s quest to understand health care. New York: Oxford University Press; 2010.Google Scholar
  43. Werner RM, Bradow ET. Relationship between Medicare’s hospital compare performance measures and mortality rates. JAMA. 2006;296(22):2694–702.CrossRefGoogle Scholar
  44. Williams A, Straker JK, Applebaum R. The nursing home five star rating: how does it compare to resident and family views of care? Gerontologist. 2014.CrossRefGoogle Scholar
  45. Wright A, Feblowitz J, Samal L, et al. The Medicare electronic health record incentive program: provider performance on core and menu measures. Health Serv Res. 2014;49(1 Pt 2):325–46. Available at: www.ncbi.nlm.nih.gov/pmc/articles/PMC3925405/CrossRefGoogle Scholar

Copyright information

© Springer Science+Business Media, LLC, part of Springer Nature 2019

Authors and Affiliations

  1. 1.Division of Health Policy and Administration, School of Public HealthUniversity of IllinoisChicagoUSA

Personalised recommendations