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      The health equity implementation framework: proposal and preliminary study of hepatitis C virus treatment

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          Abstract

          Background

          Researchers could benefit from methodological advancements to advance uptake of new treatments while also reducing healthcare disparities. A comprehensive determinants framework for healthcare disparity implementation challenges is essential to accurately understand an implementation problem and select implementation strategies.

          Methods

          We integrated and modified two conceptual frameworks—one from implementation science and one from healthcare disparities research to develop the Health Equity Implementation Framework. We applied the Health Equity Implementation Framework to a historical healthcare disparity challenge—hepatitis C virus (HCV) and its treatment among Black patients seeking care in the US Department of Veterans Affairs (VA). A specific implementation assessment at the patient level was needed to understand any barriers to increasing uptake of HCV treatment, independent of cost. We conducted a preliminary study to assess how feasible it was for researchers to use the Health Equity Implementation Framework. We applied the framework to design the qualitative interview guide and interpret results. Using quantitative data to screen potential participants, this preliminary study consisted of semi-structured interviews with a purposively selected sample of Black, rural-dwelling, older adult VA patients ( N = 12), living with HCV, from VA medical clinics in the Southern part of the USA.

          Results

          The Health Equity Implementation Framework was feasible for implementation researchers. Barriers and facilitators were identified at all levels including the patient, provider (recipients), patient-provider interaction (clinical encounter), characteristics of treatment (innovation), and healthcare system (inner and outer context). Some barriers reflected general implementation issues (e.g., poor care coordination after testing positive for HCV). Other barriers were related to healthcare disparities and likely unique to racial minority patients (e.g., testimonials from Black peers about racial discrimination at VA). We identified several facilitators, including patient enthusiasm to obtain treatment because of its high cure rates, and VA clinics that offset HCV stigma by protecting patient confidentiality.

          Conclusion

          The Health Equity Implementation Framework showcases one way to modify an implementation framework to better assess health equity determinants as well. Researchers may be able to optimize the scientific yield of research inquiries by identifying and addressing factors that promote or impede implementation of novel treatments in addition to eliminating healthcare disparities.

          Electronic supplementary material

          The online version of this article (10.1186/s13012-019-0861-y) contains supplementary material, which is available to authorized users.

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          Most cited references44

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          The prevalence of hepatitis C virus infection in the United States, 1999 through 2002.

          Defining the primary characteristics of persons infected with hepatitis C virus (HCV) enables physicians to more easily identify persons who are most likely to benefit from testing for the disease. To describe the HCV-infected population in the United States. Nationally representative household survey. U.S. civilian, noninstitutionalized population. 15,079 participants in the National Health and Nutrition Examination Survey between 1999 and 2002. All participants provided medical histories, and those who were 20 to 59 years of age provided histories of drug use and sexual practices. Participants were tested for antibodies to HCV (anti-HCV) and HCV RNA, and their serum alanine aminotransferase (ALT) levels were measured. The prevalence of anti-HCV in the United States was 1.6% (95% CI, 1.3% to 1.9%), equating to an estimated 4.1 million (CI, 3.4 million to 4.9 million) anti-HCV-positive persons nationwide; 1.3% or 3.2 million (CI, 2.7 million to 3.9 million) persons had chronic HCV infection. Peak prevalence of anti-HCV (4.3%) was observed among persons 40 to 49 years of age. A total of 48.4% of anti-HCV-positive persons between 20 and 59 years of age reported a history of injection drug use, the strongest risk factor for HCV infection. Of all persons reporting such a history, 83.3% had not used injection drugs for at least 1 year before the survey. Other significant risk factors included 20 or more lifetime sex partners and blood transfusion before 1992. Abnormal serum ALT levels were found in 58.7% of HCV RNA-positive persons. Three characteristics (abnormal serum ALT level, any history of injection drug use, and history of blood transfusion before 1992) identified 85.1% of HCV RNA-positive participants between 20 and 59 years of age. Incarcerated and homeless persons were not included in the survey. Many Americans are infected with HCV. Most were born between 1945 and 1964 and can be identified with current screening criteria. History of injection drug use is the strongest risk factor for infection.
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            Physicians and implicit bias: how doctors may unwittingly perpetuate health care disparities.

            Although the medical profession strives for equal treatment of all patients, disparities in health care are prevalent. Cultural stereotypes may not be consciously endorsed, but their mere existence influences how information about an individual is processed and leads to unintended biases in decision-making, so called "implicit bias". All of society is susceptible to these biases, including physicians. Research suggests that implicit bias may contribute to health care disparities by shaping physician behavior and producing differences in medical treatment along the lines of race, ethnicity, gender or other characteristics. We review the origins of implicit bias, cite research documenting the existence of implicit bias among physicians, and describe studies that demonstrate implicit bias in clinical decision-making. We then present the bias-reducing strategies of consciously taking patients' perspectives and intentionally focusing on individual patients' information apart from their social group. We conclude that the contribution of implicit bias to health care disparities could decrease if all physicians acknowledged their susceptibility to it, and deliberately practiced perspective-taking and individuation when providing patient care. We further conclude that increasing the number of African American/Black physicians could reduce the impact of implicit bias on health care disparities because they exhibit significantly less implicit race bias.
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              A typology of mixed methods research designs

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                Author and article information

                Contributors
                501-257-1745 , Eva.woodward2@va.gov
                mmatthie@slu.edu
                uuchendu@healthmanagement.com
                rogalss@upmc.edu
                joann.kirchner@va.gov
                Journal
                Implement Sci
                Implement Sci
                Implementation Science : IS
                BioMed Central (London )
                1748-5908
                12 March 2019
                12 March 2019
                2019
                : 14
                : 26
                Affiliations
                [1 ]ISNI 0000 0004 0478 7015, GRID grid.418356.d, Center for Mental Healthcare & Outcomes Research, Central Arkansas Veterans Healthcare System, , U.S. Department of Veterans Affairs, ; 2200 Fort Roots Drive, 152 NLR, North Little Rock, AR 72114 USA
                [2 ]ISNI 0000 0004 4687 1637, GRID grid.241054.6, Department of Psychiatry, , University of Arkansas for Medical Sciences, ; Little Rock, AR USA
                [3 ]ISNI 0000 0004 1936 9342, GRID grid.262962.b, College for Public Health and Social Justice, School of Social Work, , Saint Louis University, ; St. Louis, MO USA
                [4 ]Health Management Associates, Washington, DC USA
                [5 ]ISNI 0000 0004 0420 3665, GRID grid.413935.9, VA Pittsburgh Healthcare System, Center for Health Equity Research and Promotion, ; Pittsburgh, PA USA
                [6 ]ISNI 0000 0004 1936 9000, GRID grid.21925.3d, Department of Surgery, , University of Pittsburgh, ; Pittsburgh, PA USA
                [7 ]ISNI 0000 0004 1936 9000, GRID grid.21925.3d, Division of Gastroenterology, Hepatology, and Nutrition, , University of Pittsburgh, ; Pittsburgh, PA USA
                [8 ]ISNI 0000 0004 0478 7015, GRID grid.418356.d, VA Team-Based Behavioral Health QUERI, U.S. Department of Veterans Affairs, ; North Little Rock, AR USA
                Author information
                http://orcid.org/0000-0002-7880-0054
                Article
                861
                10.1186/s13012-019-0861-y
                6417278
                30866982
                209687e6-ae3d-4176-b0d1-81cc84f21437
                © The Author(s). 2019

                Open AccessThis article is distributed under the terms of the Creative Commons Attribution 4.0 International License ( http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The Creative Commons Public Domain Dedication waiver ( http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated.

                History
                : 11 May 2018
                : 25 January 2019
                Funding
                Funded by: FundRef http://dx.doi.org/10.13039/100000738, U.S. Department of Veterans Affairs;
                Award ID: Office of Health Equity
                Award ID: South Central Mental Illness Research, Education, and Clinical Center
                Award ID: Office of Academic Affiliations Advanced Fellowship Program in Mental Illness Research and Treatment
                Award Recipient :
                Categories
                Methodology
                Custom metadata
                © The Author(s) 2019

                Medicine
                health disparities,healthcare disparities,implementation science,implementation research,implementation framework,health equity

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