Engaging providers in underserved areas to adopt electronic health records.
ABSTRACT Objectives: To assess Regional Extension Centers' (RECs') health IT outreach and provider engagement efforts among primary care providers (PCPs) based in underserved areas. Study Design: A retrospective assessment of REC program enrollment. Methods: We computed REC program enrollment rates among PCPs for the entire United States and across census regions and compared enrollment in underserved areas relative to non-underserved areas. Measures of area-level underserved status included rural and health professional shortage area (HPSA) designations. Results: Of the estimated 302,689 ambulatory PCPs practicing in the United States, 120,783 (39.9%) were enrolled in an REC. REC enrollment rates among PCPs were higher in large rural (47.3%) and small rural (56.1%) areas relative to urban (37.9%) areas. REC enrollment rates among PCPs were also higher for single-county HPSAs (51.9%) relative to non-HPSAs (40.0%), geographic HPSAs (41.7%), and population group HPSAs (38.6%). The Northeast region exhibited the highest REC enrollment rates overall and across categories of underserved status relative to all other census regions. Conclusions: The REC program serves as a unique opportunity to address the health information technology needs of PCPs working in underserved areas. Over the course of 2 years, the program has exceeded its goal of enrolling 100,000 priority primary care providers. Provider engagement is the first step in a 3-step process aimed at getting providers to adopt and become meaningful users of electronic health records. Significant work remains for the RECs to meet these objectives, and future research should evaluate the success of the REC program in meeting subsequent milestones.
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ABSTRACT: To identify area-level correlates of electronic health record (EHR) adoption and meaningful use (MU) among primary care providers (PCPs) enrolled in the Regional Extension Center (REC) Program. County-level data on 2013 EHR adoption and MU among REC-enrolled PCPs were obtained from the Office of the National Coordinator for Health Information Technology and linked with other county-level data sources including the Area Resource File, American Community Survey, and Federal Communications Commission's broadband availability database. Hierarchical models with random intercepts for RECs were employed to assess associations between a broad set of area-level factors and county-level rates of EHR adoption and MU. Among the 2715 counties examined, the average county-level EHR adoption and MU rates for REC-enrolled PCPs were 87.5% and 54.2%, respectively. Community health center presence and Medicaid enrollment concentration were positively associated with EHR adoption, while metropolitan status and Medicare Advantage enrollment concentration were positively associated with MU. Health professional shortage area status and minority concentration were negatively associated with EHR adoption and MU. Increased financial incentives in areas with greater concentrations of Medicaid and Medicare enrollees may be encouraging EHR adoption and MU among REC-enrolled PCPs. Disparities in EHR adoption and MU in some low-resource and underserved areas remain a concern. Federal efforts to spur EHR adoption and MU have demonstrated some early success; however, some geographic variations in EHR diffusion indicate that greater attention needs to be paid to ensuring equitable uptake and use of EHRs throughout the US.Journal of the American Medical Informatics Association 05/2014; 21(6). DOI:10.1136/amiajnl-2013-002347 · 3.93 Impact Factor
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ABSTRACT: PurposeMost recent research has not found significant differences in electronic medical record (EMR) adoption rates between rural and urban physicians. However, few studies have assessed rural/urban differences at a lower level—for instance, by specialty or size of practice. Determinants of EMR adoption by physician practices in Oklahoma are explored, including the potential role of broadband availability (which is required for EMR interoperability).Methods Surveys of 2,800 unique Oklahoma physician practices in 2011 were meshed with data from the National Broadband Map for that same year. Summary statistics from the survey data allowed for comparison of EMR adoption rates by sub category. Logistic regressions were used to tease out the impact of location, specialty, and broadband availability on the EMR adoption decision.FindingsSimilar overall EMR adoption rates in rural and urban practices masked significant differences among specific subcategories. In particular, solo practices in rural areas are much more likely to adopt EMRs than are their urban counterparts (41% vs 33%, P < .01); rural psychiatric practices also have measurably higher adoption rates (59% vs 25%, P < .01). Logistic regression results demonstrate that determinants of adoption do vary between rural and urban practices. No statistical relationship between EMR adoption and measures of broadband availability was found.Conclusions Measurable differences in EMR adoption rates do exist between rural and urban practices for specific physician categories in Oklahoma. Targeted policies may be important for increasing EMR adoption, but policy efforts focusing solely on broadband availability for private practices are likely misguided.The Journal of Rural Health 08/2014; 31(1). DOI:10.1111/jrh.12086 · 1.77 Impact Factor
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ABSTRACT: To describe small area variation in ambulatory electronic health record (EHR) adoption and assess evidence of a "digital divide" in whether adoption is lagging in traditionally underserved communities. Survey data on U.S. ambulatory health care sites (261,973 sites representing 716,160 providers) collected by SK&A Information Services in 2011. We examined cross-sectional variation in two measures of local area EHR adoption: share of providers at sites using an EHR with e-prescribing functionality; and predicted probability of EHR adoption for the average site. Local areas were defined as Public Use Microdata Areas (n = 2,068). Using multivariate regression, we examined the association between adoption and three area characteristics: high concentration of minority population; high concentration of low-income population; and metropolitan status. EHR adoption varied significantly across local areas, ranging from 8 to 88 percent with a median of 41 percent. Adoption was lower in large metropolitan areas; areas with high concentration of minority population in the Northeast and West; and areas with high concentration of low-income population in the Midwest. Our 2011 estimates suggest there was substantial room for increased EHR adoption across the United States, including some underserved areas with relatively low EHR adoption rates. Further research should monitor policy initiatives in these areas and examine sources of heterogeneity in low- and high-adoption communities.Health Services Research 06/2013; DOI:10.1111/1475-6773.12078 · 2.49 Impact Factor