PROJECT SUMMARY
A substantial amount of research over the past 50 years involving Medicare and other health insurance claims
data has focused on evaluating variation in health care use and outcomes across geographic regions. For
example, over the last quarter-century, the Dartmouth Atlas Project has focused on variation in Medicare fee-
for-service health care use for diagnostically defined cohorts of patients, often conditioning on future outcomes
(e.g., death) to account for variation in health status. Numerous other claims studies have also used Medicare
claims data to estimate comparative effectiveness of different treatments and procedures. Almost all of these
types of research studies have used a nationwide measure of health care markets created at Dartmouth known
as “hospital referral regions (HRRs).” These regional markets, and the methodology underlying their
delineation, have remained largely unchanged for nearly 30 years. In addition, because Medicare primarily
covers people aged 65 and over, these regional measures—even at the time—are not representative of the
whole population, leading to questions regarding the external validity of the published results especially given
the tendency to equate such findings with the whole population. Motivated by the recent surge of interest in
health and health care inequities, a growing concern in algorithmic bias, availability of newer and more
extensive data on younger populations, and advances in network and geospatial analysis, this project
proposes to revisit the methodology, definitions, and practical applications of regional and network measures of
health care use and outcomes. These new approaches will avoid the potential biases of prior geographic
measures by better capturing care patterns of underserved populations, and will facilitate geographic variations
and comparative-effectiveness research that overcomes bias and possesses greater statistical power to detect
effects of interest. Secondly, this project will develop new measures that quantify heterogeneity of geographic
and other variations in use and spending across population strata, including disparity indices. Thirdly, this
project will evaluate the bias of Medicare estimates and develop procedures to generalize results to other
populations. Results of all analyses, including the algorithms for HRR delineation, will be used to modernize
statistical and geographic approaches to characterizing health care access and health outcomes. These will be
widely disseminated to research and stakeholder communities, thus empowering public health professionals
and researchers to define analysis and administrative units pertaining to their specific health care systems and
needs. This project will have a major impact on the research communities engaged in the evaluation of
geographic variation in health care delivery and health outcomes.