Health equity engineering: Optimizing hope for a new generation of healthcare.

Autor:	Enders FT; Department of Quantitative Health Sciences, Mayo Clinic, Rochester, MN, USA., Golembiewski EH; Division of Endocrinology, Diabetes, Metabolism, and Nutrition, Mayo Clinic, Rochester, MN, USA., Balls-Berry JE; Department of Neurology, Washington University School of Medicine, St. Louis. MO, USA., Brooks TR; Center for Clinical and Translational Science, Mayo Clinic Graduate School of Biomedical Sciences, Rochester, MN, USA., Carr AR; Center for Clinical and Translational Science, Mayo Clinic Graduate School of Biomedical Sciences, Rochester, MN, USA., Cullen JP; Clinical and Translational Science Institute, Center for Community Health and Prevention and Health Humanities and Bioethics, University of Rochester Medical Center, Rochester, NY, USA., DiazGranados D; School of Medicine, Virginia Commonwealth University, Richmond, VA, USA., Gaba A; Department of Counseling & Clinical Psychology, Teachers College, Columbia University, New York, NY, USA., Johnson L; Clinical & Translational Science Institute, New York University Langone Health, New York, NY, USA., Menser T; Division of Health Care Delivery, Mayo Clinic, Jacksonville, FL, USA., Messinger S; Department of Public Health Sciences, University of Miami Miller School of Medicine, Miami, FL, USA., Milam AJ; Department of Anesthesiology and Perioperative Medicine, Mayo Clinic, Rochester, MN, USA., Orellana MA; Department of Obstetrics and Gynecology, University of Washington, Seattle, WA, USA., Perkins SM; Department of Biostatistics and Health Data Science, Indiana University School of Medicine, Indianapolis, IN, USA., Pineda TDC; College of Journalism, University of Florida, Gainesville, FL, USA., Thurston SW; Department of Biostatistics and Computational Biology, University of Rochester Medical Center, Rochester, NY, USA., Periyakoil VS; Department of Medicine, Stanford University School of Medicine, Palo Alto, CA, USA., Hanlon AL; Department of Statistics, Virginia Tech, Blacksburg, VA, USA.
Jazyk:	angličtina
Zdroj:	Journal of clinical and translational science [J Clin Transl Sci] 2024 May 23; Vol. 8 (1), pp. e136. Date of Electronic Publication: 2024 May 23 (Print Publication: 2024).
DOI:	10.1017/cts.2024.549
Abstrakt:	Medical researchers are increasingly prioritizing the inclusion of underserved communities in clinical studies. However, mere inclusion is not enough. People from underserved communities frequently experience chronic stress that may lead to accelerated biological aging and early morbidity and mortality. It is our hope and intent that the medical community come together to engineer improved health outcomes for vulnerable populations. Here, we introduce Health Equity Engineering (HEE), a comprehensive scientific framework to guide research on the development of tools to identify individuals at risk of poor health outcomes due to chronic stress, the integration of these tools within existing healthcare system infrastructures, and a robust assessment of their effectiveness and sustainability. HEE is anchored in the premise that strategic intervention at the individual level, tailored to the needs of the most at-risk people, can pave the way for achieving equitable health standards at a broader population level. HEE provides a scientific framework guiding health equity research to equip the medical community with a robust set of tools to enhance health equity for current and future generations. Competing Interests: The authors declare none. (© The Author(s) 2024.)
Databáze:	MEDLINE
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