Real-World Data Versus Probability Surveys for Estimating Health Conditions at the State Level
Year: 2024
Type: article
Abstract: Government statistical offices worldwide are under pressure to produce statistics rapidly and for more detailed geographies, to compete with unofficial estimates available from web-based big data sources or from private companies. Commonly suggested sources of improved health information are electronic health records (EHRs) and medical claims data. These data sources are collectively known as real world data (RWD) because they are generated from routine health care processes, and they are available for millions of patients. It is clear that RWD can provide estimates that are more timely and less expensive to produce- but a key question is whether or not they are very accurate. To test this, we took advantage of a unique health data source that includes a full range of sociodemographic variables and compare estimates using all of those potential weighting variables, versus estimates derived when only age and sex are available for weighting (as is common with most RWD sources). We show that not accounting for other variables can produce misleading, and quite inaccurate, health estimates.
Authors: David A Marker, Charity Hilton, Jacob Zelko, Jon Duke, Deborah Rolka, Rachel Kaufmann, Richard Boyd
Language: English
Subfield: Health Information Management
Field: Health Professions
Domain: Health Sciences
Open Access status: green
Awards: G3579833509, G490354628, G7543494365
OpenAlex ID: W4402947928
