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      Which veterans enroll in a VA health information exchange program?

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          Abstract

          Objective: To characterize patients who voluntarily enrolled in an electronic health information exchange (HIE) program designed to share data between Veterans Health Administration (VHA) and non-VHA institutions. Materials and Methods: Patients who agreed to participate in the HIE program were compared to those who did not. Patient characteristics associated with HIE enrollment were examined using a multivariable logistic regression model. Variables selected for inclusion were guided by a health care utilization model adapted to explain HIE enrollment. Data about patients’ sociodemographics (age, gender), comorbidity (Charlson index score), utilization (primary and specialty care visits), and access (distance to VHA medical center, insurance, VHA benefits) were obtained from VHA and HIE electronic health records. Results: Among 57 072 patients, 6627 (12%) enrolled in the HIE program during its first year. The likelihood of HIE enrollment increased among patients ages 50–64, of female gender, with higher comorbidity, and with increasing utilization. Living in a rural area and being unmarried were associated with decreased likelihood of enrollment. Discussion and Conclusion: Enrollment in HIE is complex, with several factors involved in a patient’s decision to enroll. To broaden HIE participation, populations less likely to enroll should be targeted with tailored recruitment and educational strategies. Moreover, inclusion of special populations, such as patients with higher comorbidity or high utilizers, may help refine the definition of success with respect to HIE implementation.

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          Most cited references30

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          Review: electronic health records and the reliability and validity of quality measures: a review of the literature.

          Previous reviews of research on electronic health record (EHR) data quality have not focused on the needs of quality measurement. The authors reviewed empirical studies of EHR data quality, published from January 2004, with an emphasis on data attributes relevant to quality measurement. Many of the 35 studies reviewed examined multiple aspects of data quality. Sixty-six percent evaluated data accuracy, 57% data completeness, and 23% data comparability. The diversity in data element, study setting, population, health condition, and EHR system studied within this body of literature made drawing specific conclusions regarding EHR data quality challenging. Future research should focus on the quality of data from specific EHR components and important data attributes for quality measurement such as granularity, timeliness, and comparability. Finally, factors associated with poor or variability in data quality need to be better understood and effective interventions developed.
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            Differences in the patterns of health care system distrust between blacks and whites.

            Although health care-related distrust may contribute to racial disparities in health and health care in the US, current evidence about racial differences in distrust is often conflicting, largely limited to measures of physician trust, and rarely linked to multidimensional trust or distrust. To test the hypothesis that racial differences in health care system distrust are more closely linked to values distrust than to competence distrust. Cross-sectional telephone survey. Two hundred fifty-five individuals (144 black, 92 white) who had been treated in primary care practices or the emergency department of a large, urban Mid-Atlantic health system. Race, scores on the overall health care system distrust scale and on the 2 distrust subscales, values distrust and competence distrust. In univariate analysis, overall health care system distrust scores were slightly higher among blacks than whites (25.8 vs 24.1, p = .05); however, this difference was driven by racial differences in values distrust scores (15.4 vs 13.8, p = .003) rather than in competence distrust scores (10.4 vs 10.3, p = .85). After adjustment for socioeconomic status, health/psychological status, and health care access, individuals in the top quartile of values distrust were significantly more likely to be black (odds ratio = 2.60, 95% confidence interval = 1.03-6.58), but there was no significant association between race and competence distrust. Racial differences in health care system distrust are complex with far greater differences seen in the domain of values distrust than in competence distrust. This framework may be useful for explaining the mixed results of studies of race and health care-related distrust to date, for the design of future studies exploring the causes of racial disparities in health and health care, and for the development and testing of novel strategies for reducing these disparities.
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              Despite substantial progress In EHR adoption, health information exchange and patient engagement remain low in office settings.

              The United States is making substantial investments to accelerate the adoption and use of interoperable electronic health record (EHR) systems. Using data from the 2009-13 Electronic Health Records Survey, we found that EHR adoption continues to grow: In 2013, 78 percent of office-based physicians had adopted some type of EHR, and 48 percent had the capabilities required for a basic EHR system. However, we also found persistent gaps in EHR adoption, with physicians in solo practices and non-primary care specialties lagging behind others. Physicians' electronic health information exchange with other providers was limited, with only 14 percent sharing data with providers outside their organization. Finally, we found that 30 percent of physicians routinely used capabilities for secure messaging with patients, and 24 percent routinely provided patients with the ability to view online, download, or transmit their health record. These findings suggest that although EHR adoption continues to grow, policies to support health information exchange and patient engagement will require ongoing attention.
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                Author and article information

                Journal
                Journal of the American Medical Informatics Association
                J Am Med Inform Assoc
                Oxford University Press (OUP)
                1067-5027
                1527-974X
                December 30 2016
                January 2017
                January 2017
                June 06 2016
                : 24
                : 1
                : 96-105
                Article
                10.1093/jamia/ocw058
                7654084
                27274014
                81bdafda-a1e4-4bf5-8900-ec856c49a0d0
                © 2016
                History

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