scholarly journals Foreword: Big Data and its Application in Health Disparities Research

2017 ◽  
Vol 27 (2) ◽  
pp. 69 ◽  
Author(s):  
Eberechukwu Onukwugha ◽  
O. Kenrik Duru ◽  
Emmanuel Peprah
Keyword(s):  
Health Care ◽  
Big Data ◽  
Health Disparities ◽  
Health Care Disparities ◽  
Special Issue

<p>The articles presented in this special issue advance the conversation by describing the current efforts, findings and concerns related to Big Data and health disparities. They offer important recommendations and perspectives to consider when designing systems that can usefully leverage Big Data to reduce health disparities. We hope that ongoing Big Data efforts can build on these contributions to advance the conversation, address our embedded assumptions, and identify levers for action to reduce health care disparities.</p><p><em>Ethn Dis. </em>2017;27(2):69-72; doi:10.18865/ed.27.2.69.</p>

scholarly journals An Overview of Cancer Health Disparities: New Approaches and Insights and Why They Matter

2020 ◽  
Author(s):  
Tsion Zewdu Minas ◽  
Maeve Kiely ◽  
Anuoluwapo Ajao ◽  
Stefan Ambs
Keyword(s):  
Health Care ◽  
Health Disparities ◽  
Social Stress ◽  
Access To Health Care ◽  
Health Care Disparities ◽  
Underserved Populations ◽  
Tumor Biology ◽  
Cultural Barriers ◽  
Cancer Therapies ◽  
Cancer Health Disparities

Abstract Cancer health disparities remain stubbornly entrenched in the US health care system. The Affordable Care Act was legislation to target these disparities in health outcomes. Expanded access to health care, reduction in tobacco use, uptake of other preventive measures and cancer screening, and improved cancer therapies greatly reduced cancer mortality among women and men and underserved communities in this country. Yet, disparities in cancer outcomes remain. Underserved populations continue to experience an excessive cancer burden. This burden is largely explained by health care disparities, lifestyle factors, cultural barriers, and disparate exposures to carcinogens and pathogens, as exemplified by the COVID-19 epidemic. However, research also shows that comorbidities, social stress, ancestral and immunobiological factors, and the microbiome, may contribute to health disparities in cancer risk and survival. Recent studies revealed that comorbid conditions can induce an adverse tumor biology, leading to a more aggressive disease and decreased patient survival. In this review, we will discuss unanswered questions and new opportunities in cancer health disparity research related to comorbid chronic diseases, stress signaling, the immune response, and the microbiome, and what contribution these factors may have as causes of cancer health disparities.

Health and health care disparities among women in mainland China

2017 ◽  
Vol 6 (2) ◽  
pp. 166-178
Author(s):  
Xiaofei Wang ◽  
Jiehua Lu
Keyword(s):  
Health Care ◽  
Health Disparities ◽  
Social Status ◽  
Women’S Health ◽  
Women's Health ◽  
Health Care Disparities ◽  
Well Being ◽  
Working Environment ◽  
Female Population ◽  
Content Type

Purpose Women’s health is considered a big public health issue, impacting personal well-being, family reproduction, and society’s development. Since the foundation of the People’s Republic of China, major improvements in women’s social status and health have been made. However, far less has been achieved with respect to gender equality and women still face health disparities. The purpose of this paper is to provide a better understanding of health and health care disparities among women and their determinants in China today. Design/methodology/approach This paper used the Statistical Yearbook of Health and Family Planning 2014, the 2010 Women’s Social Status Survey and 2010 census data from the National Bureau of Statistics to give an overall description of disparity in health care and health outcome facing women. Findings Progress in health is not equally shared by the female population, and the differences in women’s health by region and in urban and rural areas are considerable. The existing health disparities are still faced by women in terms of life expectancy, hazardous working environment, and health care services. As to gender differences among the elderly aged 60+, men have better health status compared to women. In addition, women are more financially dependent on other family members for the main source of daily living, reflecting their economic disadvantages. Originality/value This study gives a comprehensive and the latest overview of trends of women’s health progress, disparities in health care, and health outcomes both in female population and between genders by using three data sources.

scholarly journals Beyond Black and White: Mapping Misclassification of Medicare Beneficiaries Race and Ethnicity

2020 ◽  
pp. 107755872093573
Author(s):  
Irina B. Grafova ◽  
Olga F. Jarrín
Keyword(s):  
Health Care ◽  
Health Disparities ◽  
Administrative Data ◽  
Home Health Care ◽  
Asian American ◽  
Minority Health ◽  
Health Care Disparities ◽  
State Level ◽  
Home Health ◽  
Medicare Beneficiaries

The Centers for Medicare and Medicaid Services administrative data contains two variables that are used for research and evaluation of health disparities: the enrollment database (EDB) beneficiary race code and the Research Triangle Institute (RTI) race code. The objective of this article is to examine state-level variation in racial/ethnic misclassification of EDB and RTI race codes compared with self-reported data collected during home health care. The study population included 4,231,370 Medicare beneficiaries who utilized home health care services in 2015. We found substantial variation between states in Medicare administrative data misclassification of self-identified Hispanic, Asian American/Pacific Islander, and American Indian/Alaska Native beneficiaries. Caution should be used when interpreting state-level health care disparities and minority health outcomes based on existing race variables contained in Medicare data sets. Self-reported race/ethnicity data collected during routine care of Medicare beneficiaries may be used to improve the accuracy of minority health and health disparities reporting and research.

scholarly journals Big Data Science: Opportunities and Challenges to Address Minority Health and Health Disparities in the 21st Century

2017 ◽  
Vol 27 (2) ◽  
pp. 95 ◽  
Author(s):  
Xinzhi Zhang ◽  
Eliseo J. Pérez-Stable ◽  
Philip E. Bourne ◽  
Emmanuel Peprah ◽  
O. Kenrik Duru ◽  
...  
Keyword(s):  
Big Data ◽  
Health Disparities ◽  
Social Determinants ◽  
Minority Health ◽  
Data Privacy ◽  
Data Science ◽  
Health Care Disparities ◽  
Small Sample ◽  
Digital Data ◽  
Digital Divides

<p class="Default">Addressing minority health and health disparities has been a missing piece of the puzzle in Big Data science. This article focuses on three priority opportunities that Big Data science may offer to the reduction of health and health care disparities. One opportunity is to incorporate standardized information on demographic and social determinants in electronic health records in order to target ways to improve quality of care for the most disadvantaged popula­tions over time. A second opportunity is to enhance public health surveillance by linking geographical variables and social determinants of health for geographically defined populations to clinical data and health outcomes. Third and most impor­tantly, Big Data science may lead to a better understanding of the etiology of health disparities and understanding of minority health in order to guide intervention devel­opment. However, the promise of Big Data needs to be considered in light of significant challenges that threaten to widen health dis­parities. Care must be taken to incorporate diverse populations to realize the potential benefits. Specific recommendations include investing in data collection on small sample populations, building a diverse workforce pipeline for data science, actively seeking to reduce digital divides, developing novel ways to assure digital data privacy for small populations, and promoting widespread data sharing to benefit under-resourced minority-serving institutions and minority researchers. With deliberate efforts, Big Data presents a dramatic opportunity for re­ducing health disparities but without active engagement, it risks further widening them.</p><p class="Default"><em>Ethn.Dis;</em>2017;27(2):95-106; doi:10.18865/ed.27.2.95.</p>

scholarly journals The Impact of Disasters on Populations With Health and Health Care Disparities

2010 ◽  
Vol 4 (1) ◽  
pp. 30-38 ◽  
Author(s):  
Jennifer R. Davis ◽  
Sacoby Wilson ◽  
Amy Brock-Martin ◽  
Saundra Glover ◽  
Erik R. Svendsen
Keyword(s):  
Health Care ◽  
Health Disparities ◽  
Rural Areas ◽  
Health Care Disparities ◽  
Underserved Populations ◽  
Health Resources ◽  
Medically Underserved ◽  
Disaster Studies ◽  
Before And After ◽  
The Impact

ABSTRACTContext:A disaster is indiscriminate in whom it affects. Limited research has shown that the poor and medically underserved, especially in rural areas, bear an inequitable amount of the burden.Objective:To review the literature on the combined effects of a disaster and living in an area with existing health or health care disparities on a community's health, access to health resources, and quality of life.Methods:We performed a systematic literature review using the following search terms: disaster, health disparities, health care disparities, medically underserved, and rural. Our inclusion criteria were peer-reviewed, US studies that discussed the delayed or persistent health effects of disasters in medically underserved areas.Results:There has been extensive research published on disasters, health disparities, health care disparities, and medically underserved populations individually, but not collectively.Conclusions:The current literature does not capture the strain of health and health care disparities before and after a disaster in medically underserved communities. Future disaster studies and policies should account for differences in health profiles and access to care before and after a disaster.(Disaster Med Public Health Preparedness. 2010;4:30-38)

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