BACKGROUND
Although the Health Information Technology for Economic and Clinical Health (HITECH) Act has accelerated the adoption of Meaningful Use of Electronic Health Records (EHRs) among Medicaid providers, only about half achieve Meaningful Use. Furthermore, the validity of public health reporting of COVID-19 outcomes, which relies on Meaningful Use advanced functions, remains unknown.
OBJECTIVE
This study aims to examine the difference between Medicaid providers who did and did not achieve Meaningful Use regarding Florida county-level incidence rates of COVID-19 cases and deaths, accounting for county-level race/ethnicity, unemployment, income, prevalence of respiratory diseases, age, poverty, and healthcare environment.
METHODS
This cross-sectional ecologic study examined the association between Meaningful Use achievement by Medicaid providers and COVID-19 cases and death rates from 67 Florida counties as of November 19, 2020. Provider information was obtained from the publicly available database from the Florida Medicaid Promoting Interoperability Program, formerly Electronic Health Record Incentive Program. The database includes the Area Health Resources File, capturing provider characteristics and population demographic and socioeconomic characteristics at the county level. Cumulative COVID-19 cases and deaths were obtained from the Florida Department of Health Open Data (FDOH) for zip codes which were aggregated by county. Rates were obtained by dividing cumulative incidence or prevalence by the U.S. Census County population.
RESULTS
As of November 19, 2020, the cumulative incidence rate of COVID-19 deaths was significantly different between Medicaid providers who achieved Meaningful Use and those who did not (P=.0131), with relatively more deaths reported for those not achieving Meaningful Use. County-level characteristics associated with increased COVID-19 death rates in hierarchical models include greater concentrations of persons of African American or Black race (P<.0001), lower median household income (P<.0001), higher unemployment (P<.0001), and higher concentrations of those living in poverty (P<.0001) and without health insurance (P<.0001).
CONCLUSIONS
Although Federal subsidies successfully influenced the adoption of Electronic Health Records, our findings suggest an emerging further digital "advanced use" divide among patients cared for by Medicaid providers. Policy interventions need to be reevaluated to address disparities in COVID-19 clinical outcomes which appear exacerbated by the limited use of advanced Electronic Health Records functions.
CLINICALTRIAL
not applicable
The impact of electronic health records on healthcare quality: a systematic review and meta-analysis
