Abstract
Medicaid is the largest health care program for persons with low income in the US and is jointly funded by the federal and individual state governments, while Medicare is solely funded by the federal government and provides health care for the vast majority of elderly persons. Both programs were established in 1965 and are overseen by the Centers of Medicare and Medicaid Services (CMS) of the United States Department of Health and Human Services.
This is a preview of subscription content, log in via an institution to check access.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Similar content being viewed by others
References
Brouwer ES, Napravnik S, Eron JJ Jr et al (2015) Validation of medicaid claims-based diagnosis of myocardial infarction using an HIV clinical cohort. Med Care 53(6):e41–e48. https://doi.org/10.1097/MLR.0b013e318287d6fd
Centers for Medicare and Medicaid Services (2012) MSIS Tables. https://www.cms.gov/Research-Statistics-Data-and-Systems/Computer-Data-and-Systems/MedicaidDataSourcesGenInfo/MSIS-Tables.html. Accessed 1st Feb 2018
Centers for Medicare and Medicaid Services (2016) MAX validation reports. https://www.cms.gov/Research-Statistics-Data-and-Systems/Computer-Data-and-Systems/MedicaidDataSourcesGenInfo/MAX-Validation-Reports.html. Accessed 04 Jan 2018
Centers for Medicare and Medicaid Services (2017) Medicare and medicaid statistical supplement 2013 edition. https://www.cms.gov/Research-Statistics-Data-and-Systems/Statistics-Trends-and-Reports/MedicareMedicaidStatSupp/2013.html. Accessed 2 Feb 2020
Centers for Medicare and Medicaid Services (2019a) CMS fast facts. https://www.cms.gov/Research-Statistics-Data-and-Systems/Statistics-Trends-and-Reports/CMS-Fast-Facts/index.html. Accessed 2 Feb 2020
Centers for Medicare and Medicaid Services (2019b) Total medicare enrollment: part A and/or part B enrollees, by demographic characteristics, calendar year 2015. https://www.cms.gov/Research-Statistics-Data-and-Systems/Statistics-Trends-and-Reports/CMSProgramStatistics/2015/2015_Enrollment.html. Accessed 2 Feb 2020
Centers for Medicare and Medicaid Services (2020) Medicare-medicaid enrollment (MME): total medicare-medicaid enrollees by type of eligibility, calendar years 2010–2017. https://www.cms.gov/Research-Statistics-Data-and-Systems/Statistics-Trends-and-Reports/CMSProgramStatistics/2017/2017_Enrollment.html. Accessed 2 Feb 2020
Choudhry NK, Shrank WH (2010) Four-dollar generics—increased accessibility, impaired quality assurance. N Engl J Med 363(20):1885–1887. https://doi.org/10.1056/NEJMp1006189
Colantonio LD, Kent ST, Kilgore ML et al (2016) Agreement between medicare pharmacy claims, self-report, and medication inventory for assessing lipid-lowering medication use. Pharmacoepidemiol Drug Saf 25(7):827–835. https://doi.org/10.1002/pds.3970
Gilbertson DT, Bradbury BD, Wetmore JB et al (2016) Controlling confounding of treatment effects in administrative data in the presence of time-varying baseline confounders. Pharmacoepidemiol Drug Saf 25(3):269–277. https://doi.org/10.1002/pds.3922
Gokhale M, Buse JB, Pate V et al (2016) More realistic power estimation for new user, active comparator studies: an empirical example. Pharmacoepidemiol Drug Saf 25(4):462–466. https://doi.org/10.1002/pds.3872
Hammill BG, Curtis LH, Qualls LG et al (2015) Linkage of laboratory results to medicare fee-for-service claims. Med Care 53(11):974–979. https://doi.org/10.1097/mlr.0000000000000420
Hanlon JT, Donohue J (2010) Medicare part D data: a valuable tool for pharmacoepidemiology and pharmacoeconomic research. Am J Geriatric Pharmacother 8(6):483–484. https://doi.org/10.1016/S1543-5946(10)80001-7
Hennessy S, Leonard CE, Freeman CP et al (2010) Validation of diagnostic codes for outpatient-originating sudden cardiac death and ventricular arrhythmia in medicaid and medicare claims data. Pharmacoepidemiol Drug Saf 19(6):555–562. https://doi.org/10.1002/pds.1869
Hennessy S, Palumbo Freeman C, Cunningham F (2012a) US government claims databases. In: Strom BL, Kimmel SE, Hennessy S (eds) Pharmacoepidemiology, 5th edn. Wiley, Chichester, pp 209–223
Hennessy S, Palumbo Freeman C, Cunningham F (2012b) US Government claims databases. In: Strom BL, Kimmel SE, Hennessy S (eds) Pharmacoepidemiology, 5th edn. Wiley, Chichester
Hernandez-Trujillo H, Orange JS, Roy JA et al (2015) Validity of primary immunodeficiency disease diagnoses in United States medicaid data. J Clin Immunol 35(6):566–572. https://doi.org/10.1007/s10875-015-0185-x
Leonard CE, Brensinger CM, Nam Y et al (2017) The quality of medicaid and medicare data obtained from CMS and its contractors: implications for pharmacoepidemiology. BMC Health Serv Res 17(304). https://doi.org/10.1186/s12913-017-2247-7
Leonard CE, Han X, Brensinger CM et al (2018) Comparative risk of serious hypoglycemia with oral antidiabetic monotherapy: a retrospective cohort study. Pharmacoepidemiol Drug Saf 27(1):9–18. https://doi.org/10.1002/pds.4337
Lessler JT, Harris BSH (1984) Medicaid data as a source for postmarketing surveillance information: final report. Research Triangle Institute, Research Triangle Park, NC
Medicaid and CHIP Payment and Access Commission (2019) MACStats: medicaid and CHIP data book. https://www.macpac.gov/publication/macstats-medicaid-and-chip-data-book-2/. Accessed 2 Feb 2020
Muntner P, Gutierrez OM, Zhao H et al (2015) Validation study of medicare claims to identify older US adults with CKD using the reasons for geographic and racial differences in stroke (REGARDS) study. Am J Kidney Dis 65(2):249–258. https://doi.org/10.1053/j.ajkd.2014.07.012
Office for Civil Rights (2018) HIPAA privacy. https://www.hhs.gov/hipaa/for-professionals/special-topics/research/index.html. Accessed 2 Feb 2020
Palmsten K, Huybrechts KF, Mogun H et al (2013) Harnessing the medicaid analytic extract (MAX) to evaluate medications in pregnancy: design considerations. PLoS ONE 8(6):e67405. https://doi.org/10.1371/journal.pone.0067405
Patrick AR, Brookhart MA, Losina E et al (2010) The complex relation between bisphosphonate adherence and fracture reduction. J Clin Endocrinol Metab 95(7):3251–3259. https://doi.org/10.1210/jc.2009-2778
Ray WA, Liu Q, Shepherd BE (2015) Performance of time-dependent propensity scores: a pharmacoepidemiology case study. Pharmacoepidemiol Drug Saf 24(1):98–106. https://doi.org/10.1002/pds.3727
Research Data Assistance Center (2020a) Requirements for institutional review board (IRB) review and HIPAA waiver documentation for RIF DUA request submissions. https://www.resdac.org/articles/requirements-institutional-review-board-irb-review-and-hipaa-waiver-documentation-rif-dua. Accessed 2 Feb 2020
Research Data Assistance Center (2020b) Research identifiable files (RIF) requests. https://www.resdac.org/cms-data/request/research-identifiable-files. Accessed 2 Feb 2020
Roumie CL, Choma NN, Kaltenbach L et al (2009) Non-aspirin NSAIDs, Cyclooxygenase-2 Inhibitors and Risk for cardiovascular events—stroke, acute myocardial infarction, and death from coronary heart disease. Pharmacoepidemiol Drug Saf 18(11):1053–1063. https://doi.org/10.1002/pds.1820
Santos CA, Brennan DC, Saeed MJ et al (2016) Pharmacoepidemiology of cytomegalovirus prophylaxis in a large retrospective cohort of kidney transplant recipients with medicare part D coverage. Clin Transplant 30(4):435–444. https://doi.org/10.1111/ctr.12706
Schneeweiss S, Rassen JA, Glynn RJ et al (2009) High-dimensional propensity score adjustment in studies of treatment effects using health care claims data. Epidemiology 20(4):512–522. https://doi.org/10.1097/EDE.0b013e3181a663cc
Stürmer T, Schneeweiss S, Brookhart MA et al (2005) Analytic strategies to adjust confounding using exposure propensity scores and disease risk scores: nonsteroidal antiinflammatory drugs and short-term mortality in the elderly. Am J Epidemiol 161(9):891–898. https://doi.org/10.1093/aje/kwi106
U.S. Census Bureau Population Division (2018) Annual estimates of the resident population: April 1, 2010 to July 1, 2018. https://factfinder.census.gov. Accessed 2 Feb 2020
Varghese D, Kirkwood CK, Carroll NV (2016) Prevalence of antidiabetic and antilipidemic medications in children and adolescents treated with atypical antipsychotics in a virginia medicaid population. Ann Pharmacother 50(6):463–470. https://doi.org/10.1177/1060028016638861
Wright NC, Delzell ES, Smith WK et al (2017) Improving medical record retrieval for validation studies in medicare data. Pharmacoepidemiol Drug Saf 26(4):393–401. https://doi.org/10.1002/pds.4131
Wysowski DK, Baum C (1993) The validity of medicaid diagnoses of hip fracture. Am J Public Health 83(5):770
Author information
Authors and Affiliations
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2021 Springer Nature Switzerland AG
About this chapter
Cite this chapter
Enders, D., Schink, T., Stürmer, T. (2021). Medicaid and Medicare. In: Sturkenboom, M., Schink, T. (eds) Databases for Pharmacoepidemiological Research. Springer Series on Epidemiology and Public Health. Springer, Cham. https://doi.org/10.1007/978-3-030-51455-6_19
Download citation
DOI: https://doi.org/10.1007/978-3-030-51455-6_19
Published:
Publisher Name: Springer, Cham
Print ISBN: 978-3-030-51454-9
Online ISBN: 978-3-030-51455-6
eBook Packages: MedicineMedicine (R0)