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1.
Article in English | MEDLINE | ID: mdl-36554864

ABSTRACT

Funded by the National Institutes of Health (NIH), the Research Centers in Minority Institutions (RCMI) Program fosters the development and implementation of innovative research aimed at improving minority health and reducing or eliminating health disparities. Currently, there are 21 RCMI Specialized (U54) Centers that share the same framework, comprising four required core components, namely the Administrative, Research Infrastructure, Investigator Development, and Community Engagement Cores. The Research Infrastructure Core (RIC) is fundamentally important for biomedical and health disparities research as a critical function domain. This paper aims to assess the research resources and services provided and evaluate the best practices in research resources management and networking across the RCMI Consortium. We conducted a REDCap-based survey and collected responses from 57 RIC Directors and Co-Directors from 98 core leaders. Our findings indicated that the RIC facilities across the 21 RCMI Centers provide access to major research equipment and are managed by experienced faculty and staff who provide expert consultative and technical services. However, several impediments to RIC facilities operation and management have been identified, and these are currently being addressed through implementation of cost-effective strategies and best practices of laboratory management and operation.


Subject(s)
Biomedical Research , United States , Humans , Minority Groups , National Institutes of Health (U.S.) , Minority Health , Research Personnel
2.
Article in English | MEDLINE | ID: mdl-34202383

ABSTRACT

The Research Centers in Minority Institutions, (RCMI) Program was established by Congress to address the health research and training needs of minority populations, by preparing future generations of scientists at these institutions, with a track record of producing minority scholars in medicine, science, and technology. The RCMI Consortium consists of the RCMI Specialized Centers and a Coordinating Center (CC). The RCMI-CC leverages the scientific expertise, technologies, and innovations of RCMI Centers to accelerate the delivery of solutions to address health disparities in communities that are most impacted. There is increasing recognition that the gap in representation of racial/ethnic groups and women is perpetuated by institutional cultures lacking inclusion and equity. The objective of this work is to provide a framework for inclusive excellence by developing a systematic evaluation process with common data elements that can track the inter-linked goals of workforce diversity and health equity. At its core, the RCMI Program embodies the trinity of diversity, equity, and inclusion. We propose a realist evaluation framework and a logic model that integrates the institutional context to develop common data metrics for inclusive excellence. The RCMI-CC will collaborate with NIH-funded institutions and research consortia to disseminate and scale this model.


Subject(s)
Health Equity , Minority Groups , Ethnicity , Humans , Racial Groups , Workforce
3.
Article in English | MEDLINE | ID: mdl-31083298

ABSTRACT

African Americans, other minorities and underserved populations are consistently under- represented in clinical trials. Such underrepresentation results in a gap in the evidence base, and health disparities. The ABC Cardiovascular Implementation Study (CVIS) is a comprehensive prospective cohort registry that integrates social determinants of health. ABC CVIS uses real world clinical practice data to address critical gaps in care by facilitating robust participation of African Americans and other minorities in clinical trials. ABC CVIS will include diverse patients from collaborating ABC member private practices, as well as patients from academic health centers and Federally Qualified Health Centers (FQHCs). This paper describes the rationale and design of the ABC CVIS Registry. The registry will: (1) prospectively collect socio-demographic, clinical and biospecimen data from enrolled adults, adolescents and children with prioritized cardiovascular diseases; (2) Evaluate the safety and clinical outcomes of new therapeutic agents, including post marketing surveillance and pharmacovigilance; (3) Support National Institutes of Health (NIH) and industry sponsored research; (4) Support Quality Measures standards from the Center for Medicare and Medicaid Services (CMS) and Commercial Health Plans. The registry will utilize novel data and technology tools to facilitate mobile health technology application programming interface (API) to health system or practice electronic health records (EHR). Long term, CVIS will become the most comprehensive patient registry for underserved diverse patients with cardiovascular disease (CVD) and co morbid conditions, providing real world data to address health disparities. At least 10,000 patients will be enrolled from 50 sites across the United States.


Subject(s)
Black or African American/statistics & numerical data , Social Determinants of Health/statistics & numerical data , Vulnerable Populations/statistics & numerical data , Georgia , Humans , Prospective Studies , Registries
4.
Ethn Dis ; 29(Suppl 1): 135-144, 2019.
Article in English | MEDLINE | ID: mdl-30906162

ABSTRACT

The Research Centers in Minority Institutions (RCMI) program was established by the US Congress to support the development of biomedical research infrastructure at minority-serving institutions granting doctoral degrees in the health professions or in a health-related science. RCMI institutions also conduct research on diseases that disproportionately affect racial and ethnic minorities (ie, African Americans/Blacks, American Indians and Alaska Natives, Hispanics, Native Hawaiians and Other Pacific Islanders), those of low socioeconomic status, and rural persons. Quantitative metrics, including the numbers of doctoral science degrees granted to underrepresented students, NIH peer-reviewed research funding, peer-reviewed publications, and numbers of racial and ethnic minorities participating in sponsored research, demonstrate that RCMI grantee institutions have made substantial progress toward the intent of the Congressional legislation, as well as the NIH/NIMHD-linked goals of addressing workforce diversity and health disparities. Despite this progress, nationally, many challenges remain, including persistent disparities in research and career development awards to minority investigators. The continuing underrepresentation of minority investigators in NIH-sponsored research across multiple disease areas is of concern, in the face of unrelenting national health inequities. With the collaborative network support by the RCMI Translational Research Network (RTRN), the RCMI community is uniquely positioned to address these challenges through its community engagement and strategic partnerships with non-RCMI institutions. Funding agencies can play an important role by incentivizing such collaborations, and incorporating metrics for research funding that address underrepresented populations, workforce diversity and health equity.


Subject(s)
Behavioral Research , Biomedical Research , Minority Groups , Minority Health , Translational Research, Biomedical , Behavioral Research/methods , Behavioral Research/organization & administration , Biomedical Research/methods , Biomedical Research/organization & administration , Cultural Diversity , Ethnicity/education , Ethnicity/statistics & numerical data , Health Status Disparities , Humans , Minority Groups/education , Minority Groups/statistics & numerical data , Minority Health/education , Minority Health/ethnology , Research Personnel , Research Support as Topic , Translational Research, Biomedical/methods , Translational Research, Biomedical/organization & administration , United States , Workforce
5.
Int J Environ Res Public Health ; 13(1): ijerph13010002, 2015 Dec 22.
Article in English | MEDLINE | ID: mdl-26703652

ABSTRACT

PURPOSE: There is abundant evidence that neighborhood characteristics are significantly linked to the health of the inhabitants of a given space within a given time frame. This study is to statistically validate a web-based GIS application designed to support cardiovascular-related research developed by the NIH funded Research Centers in Minority Institutions (RCMI) Translational Research Network (RTRN) Data Coordinating Center (DCC) and discuss its applicability to cardiovascular studies. METHODS: Geo-referencing, geocoding and geospatial analyses were conducted for 500 randomly selected home addresses in a U.S. southeastern Metropolitan area. The correlation coefficient, factor analysis and Cronbach's alpha (α) were estimated to quantify measures of the internal consistency, reliability and construct/criterion/discriminant validity of the cardiovascular-related geospatial variables (walk score, number of hospitals, fast food restaurants, parks and sidewalks). RESULTS: Cronbach's α for CVD GEOSPATIAL variables was 95.5%, implying successful internal consistency. Walk scores were significantly correlated with number of hospitals (r = 0.715; p < 0.0001), fast food restaurants (r = 0.729; p < 0.0001), parks (r = 0.773; p < 0.0001) and sidewalks (r = 0.648; p < 0.0001) within a mile from homes. It was also significantly associated with diversity index (r = 0.138, p = 0.0023), median household incomes (r = -0.181; p < 0.0001), and owner occupied rates (r = -0.440; p < 0.0001). However, its non-significant correlation was found with median age, vulnerability, unemployment rate, labor force, and population growth rate. CONCLUSION: Our data demonstrates that geospatial data generated by the web-based application were internally consistent and demonstrated satisfactory validity. Therefore, the GIS application may be useful to apply to cardiovascular-related studies aimed to investigate potential impact of geospatial factors on diseases and/or the long-term effect of clinical trials.


Subject(s)
Cardiovascular Diseases/prevention & control , Cities/statistics & numerical data , Fast Foods/statistics & numerical data , Geographic Information Systems , Hospitals/statistics & numerical data , Parks, Recreational/statistics & numerical data , Walking/statistics & numerical data , Adult , Aged , Data Interpretation, Statistical , Environment Design , Factor Analysis, Statistical , Female , Humans , Internet , Male , Middle Aged , Reproducibility of Results , Residence Characteristics , Southeastern United States , Young Adult
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