The Center for Medicare and Medicaid Services (CMS) has acknowledged its commitment to promoting widespread Meaningful Use (MU) of Electronic Health Records (EHRs) through over $30 billion investment of funds from the Health Information Technology for Economic and Clinical Health (HITECH) Act of 2009, through the CMS Promoting Interoperability (MPI) program. Underlying this effort is the potential gain of improved health outcomes through the timely transfer of electronic health information across the care continuum. The Florida Medicaid Promoting Interoperability (FMPI) program started in 2011 through 2021, but less than half of Medicaid providers attested to MU (i.e., advanced EHR functions) of EHRs as of 2018, potentially creating an advanced use “digital divide” in the State. Medicaid/CHIP serves over 83.6 million beneficiaries in the United States, many of whom are traditionally low-income, vulnerable individuals with multiple comorbidities. It is thus critical to assess whether Federal funding designed to promote MU adoption is effective rather than inadvertently exacerbate health information technology disparities. The overall objective of this proposal is to data from the FMPI to estimate local-area MU rates of EHRs and assess whether MU of EHRs is lagging in areas with a high concentration of traditionally underserved populations. More specifically, the aims of this proposal are: Aim 1: Estimate MU rates of EHRs in areas with high concentration of low-income residents; assess whether MU rates are lagging in these areas; and examine the factors associated with MU rates in these areas. Aim 2: Estimate MU rates of EHRs in areas with high concentration of racial and ethnic minority residents; assess whether MU rates are lagging in these areas; and examine the factors associated with MU rates in these areas. Aim 3: Estimate MU rates of EHRs in rural areas and inner cities; assess whether MU rates are lagging in these areas; and examine the factors associated with MU rates in these areas. We will conduct a retrospective cohort study using records of 8748 medical practices from the FMPI’s Provider Participation Database. Using the participant’s 10-digit national provider identification (NPI) and county identifier, this database will be linked to other datasets from state and federal data sources. Innovative theoretical framework (Resource Dependence Theory) and estimation techniques (power analysis, logistic and probit random effects models, clustered standard errors, unobserved heterogeneity “debiasing method”, Heckman selection, and Hierarchical Generalized Linear Model (HGLM)) will be used. As an Academic Research Enhancement Award (AREA), we will involve graduate and undergraduate students in all aspects of the study as integral members of the research team, providing intensive exposure to and training in research. We will disseminate our research through digital, print, and presentation forums, and FAU open-access digital resource repositories, local community venues, and peer-reviewed journals.

Public Health Relevance Statement Despite the national uptake in Electronic Health Records (EHRs) adoption among impecunious and smaller providers, as of 2018 less than half of Florida Medicaid providers use their systems to the full capacity, potentially creating an advanced use “digital divide.” Evidence is overwhelming that Health Information Technology (Health IT) has tremendous potential for increasing health equity for racial and ethnic, socioeconomic populations, and other disparity populations, but no research has yet systematically estimated local-area Meaningful Use rates of EHRs and assessed if rates are lagging in areas with a high concentration of traditionally underserved populations. The potential for leveraging advanced functions inherent to improve public and population health outcomes for populations experiencing the greatest health disparities exists now; findings from this proposal will further support policymakers with insights to champion interventions to optimize technology use for underserved populations.