title: Macro influencers of electronic health records adoption.
abstract: While adoption rates for electronic health records (EHRs) have improved, the reasons for significant geographical differences in EHR adoption within the USA have remained unclear. To understand the reasons for these variations across states, we have compiled from secondary sources a profile of different states within the USA, based on macroeconomic and macro health-environment factors. Regression analyses were performed using these indicator factors on EHR adoption. The results showed that internet usage and literacy are significantly associated with certain measures of EHR adoption. Income level was not significantly associated with EHR adoption. Per capita patient days (a proxy for healthcare need intensity within a state) is negatively correlated with EHR adoption rate. Health insurance coverage is positively correlated with EHR adoption rate. Older physicians (>60 years) tend to adopt EHR systems less than their younger counterparts. These findings have policy implications on formulating regionally focused incentive programs.
authors.affiliation: 1 Department of Business Informatics, GH 549 College of Informatics, Northern Kentucky University, Highland Heights, KY 41099, USA.
authors.forename: Vijay V
authors.initials: VV
authors.lastname: Raghavan
authors.affiliation: 2 Department of Business Administration, Auburn University at Montgomery, Montgomery, AL 36177, USA.
authors.forename: Ravi
authors.initials: R
authors.lastname: Chinta
authors.affiliation: 3 IBM Bay Area Lab, 1001 E Hillsdale Blvd., Suite 400, Foster City, CA 94404, USA.
authors.forename: Nikita
authors.initials: N
authors.lastname: Zhirkin
mesh_terms: D000367:Age Factors; D001292:Attitude to Computers; D057286:Electronic Health Records / Q000706:statistics & numerical data*; D006801:Humans; D019458:Insurance Coverage; D020380:Needs Assessment; D012044:Regression Analysis; D012111:Residence Characteristics / Q000706:statistics & numerical data*
keywords: EHR adoption; EHRs; USA; United States; e-healthcare; electronic health records; electronic healthcare; health insurance coverage; income level; internet usage; literacy; macro health environment; macroeconomic factors; per capita patient days; physician age; regional incentive programmes