Use of the Medicare database in epidemiologic and health services research: a valuable source of real-world evidence on the older and disabled populations in the US

Abstract

Medicare is the federal health insurance program for individuals in the US who are aged ≥65 years, select individuals with disabilities aged <65 years, and individuals with end-stage renal disease. The Centers for Medicare and Medicaid Services grants researchers access to Medicare administrative claims databases for epidemiologic and health outcomes research. The data cover beneficiaries’ encounters with the health care system and receipt of therapeutic interventions, including medications, procedures, and services. Medicare data have been used to describe patterns of morbidity and mortality, describe burden of disease, compare effectiveness of pharmacologic therapies, examine cost of care, evaluate the effects of provider practices on the delivery of care and patient outcomes, and explore the health impacts of important Medicare policy changes. Considering that the vast majority of US citizens ≥65 years of age have Medicare insurance, analyses of Medicare data are now essential for understanding the provision of health care among older individuals in the US and are critical for providing real-world evidence to guide decision makers. This review is designed to provide researchers with a summary of Medicare data, including the types of data that are captured, and how they may be used in epidemiologic and health outcomes research. We highlight strengths, limitations, and key considerations when designing a study using Medicare data. Additionally, we illustrate the potential impact that Centers for Medicare and Medicaid Services policy changes may have on data collection, coding, and ultimately on findings derived from the data.

Linkage between Utah All Payers Claims Database and Central Cancer Registry

“…Electronic health claims datasets represent an excellent resource for improving our understanding or health and health care, although obstacles and limitations exist . Cancer registries generate high‐quality cancer incidence and diagnostic information, but lack treatment details, comorbidities, and recurrence.…”

“…According to Utah Insurance Department information, 15 Electronic health claims datasets represent an excellent resource for improving our understanding or health and health care, although obstacles and limitations exist. 18,19 Cancer registries generate high-quality cancer incidence and diagnostic information, but lack treatment details, comorbidities, and recurrence. Claims data can potentially fill these cancer data gaps, 5,6,20 and, as noted above, the linked SEER-Medicare database has demonstrated the power of linkage of registry data with claims to obtain rich research data for individuals diagnosed with cancer at age 65 and older.…”

Regional clinical practice variation in urology: Usage example of the Open Data of the National Database of Health Insurance Claims and Specific Health Checkups of Japan

“…A database with near‐complete capture of healthcare services like the NDB has a great potential to solve a wide range of clinical and healthcare questions. In the USA, 100% of the Medicare dataset was used for several analyses including epidemiology study; treatment utilization variation; the relationship among cost, safety, effectiveness and quality; and the impact of policy change on clinical practice and outcome . So far, the NDB dataset involves several problems, including the data‐matching process and epidemiological use being limited; however, it will not be too long before long‐term data accumulation makes the clinical course traceable.…”

“…impact of policy change on clinical practice and outcome. 4 So far, the NDB dataset involves several problems, including the data-matching process and epidemiological use being limited; however, it will not be too long before long-term data accumulation makes the clinical course traceable. Newly emerging healthcare big data technology will accelerate such investigations based on real-world evidence.…”

Exploration Of The Timeliness Of ICD Codes In Administrative Databases: A Nationwide Study

“…Overtime the importance of epidemiological and external factors might evolve: a query built at a given time for patient selection may not be relevant at a later date, and lead to errors of interpretation. Mues et al [21] discussed the influence of the Centers for Medicare and Medicaid Services policy on data collection and coding between 2005 and 2012. The authors show that the percentage of inpatient claims with a diagnosis code for coronary atherosclerosis suddenly increased in 2010 because of the expansion of the number of ICD-9/10 diagnosis and procedure code fields on a claim.…”