Growing disparities in patient-provider messaging:trend analysis before and after supportive policy

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Abstract

Background: Public policy introduced since 2011 has supported provider adoption of electronic medical records (EMRs) and patient-provider messaging, primarily through financial incentives. It is unclear how disparities in patients’ use of incentivized electronic health (eHealth) tools, like patient-provider messaging, have changed over time relative to disparities in use of eHealth tools that were not directly incentivized. Objective: This study examines trends in eHealth disparities before and after the introduction of US federal financial incentives. We compare rates of patient-provider messaging, which was directly incentivized, with rates of looking for health information on the Web, which was not directly incentivized. Methods: We used nationally representative Health Information National Trends Survey data from 2003 to 2018 (N=37,300) to describe disparities in patient-provider messaging and looking for health information on the Web. We first reported the percentage of individuals across education and racial and ethnic groups who reported using these tools in each survey year and compared changes in unadjusted disparities during preincentive (2003-2011) and postincentive (2011-2018) periods. Using multivariable linear probability models, we then examined adjusted effects of education and race and ethnicity in 3 periods—preincentive (2003-2005), early incentive (2011-2013), and postincentive (2017-2018)—controlling for sociodemographic and health factors. In the postincentive period, an additional model tested whether internet adoption, provider access, or providers’ use of EMRs explained disparities. Results: From 2003 to 2018, overall rates of provider messaging increased from 4% to 36%. The gap in provider messaging between the highest and lowest education groups increased by 10 percentage points preincentive (P

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Senft, N., Butler, E., & Everson, J. (2019). Growing disparities in patient-provider messaging:trend analysis before and after supportive policy. Journal of Medical Internet Research, 21(10). https://doi.org/10.2196/14976

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