The Economic Burden of Racial, Ethnic, and Educational Health Inequities in the US.

Importance: Health inequities exist for racial and ethnic minorities and persons with lower educational attainment due to differential exposure to economic, social, structural, and environmental health risks and limited access to health care. Objective: To estimate the economic burden of health inequities for racial and ethnic minority populations (American Indian and Alaska Native, Asian, Black, Latino, and Native Hawaiian and Other Pacific Islander) and adults 25 years and older with less than a 4-year college degree in the US. Outcomes include the sum of excess medical care expenditures, lost labor market productivity, and the value of excess premature death (younger than 78 years) by race and ethnicity and the highest level of educational attainment compared with health equity goals. Evidence Review: Analysis of 2016-2019 data from the Medical Expenditure Panel Survey (MEPS) and state-level Behavioral Risk Factor Surveillance System (BRFSS) and 2016-2018 mortality data from the National Vital Statistics System and 2018 IPUMS American Community Survey. There were 87 855 survey respondents to MEPS, 1 792 023 survey respondents to the BRFSS, and 8 416 203 death records from the National Vital Statistics System. Findings: In 2018, the estimated economic burden of racial and ethnic health inequities was $421 billion (using MEPS) or $451 billion (using BRFSS data) and the estimated burden of education-related health inequities was $940 billion (using MEPS) or $978 billion (using BRFSS). Most of the economic burden was attributable to the poor health of the Black population; however, the burden attributable to American Indian or Alaska Native and Native Hawaiian or Other Pacific Islander populations was disproportionately greater than their share of the population. Most of the education-related economic burden was incurred by adults with a high school diploma or General Educational Development equivalency credential. However, adults with less than a high school diploma accounted for a disproportionate share of the burden. Although they make up only 9% of the population, they bore 26% of the costs. Conclusions and Relevance: The economic burden of racial and ethnic and educational health inequities is unacceptably high. Federal, state, and local policy makers should continue to invest resources to develop research, policies, and practices to eliminate health inequities in the US.

The PhenX Toolkit: Measurement Protocols for Assessment of Social Determinants of Health.

INTRODUCTION: Social determinants are structures and conditions in the biological, physical, built, and social environments that affect health, social and physical functioning, health risk, quality of life, and health outcomes. The adoption of recommended, standard measurement protocols for social determinants of health will advance the science of minority health and health disparities research and provide standard social determinants of health protocols for inclusion in all studies with human participants. METHODS: A PhenX (consensus measures for Phenotypes and eXposures) Working Group of social determinants of health experts was convened from October 2018 to May 2020 and followed a well-established consensus process to identify and recommend social determinants of health measurement protocols. The PhenX Toolkit contains data collection protocols suitable for inclusion in a wide range of research studies. The recommended social determinants of health protocols were shared with the broader scientific community to invite review and feedback before being added to the Toolkit. RESULTS: Nineteen social determinants of health protocols were released in the PhenX Toolkit (https://www.phenxtoolkit.org) in May 2020 to provide measures at the individual and structural levels for built and natural environments, structural racism, economic resources, employment status, occupational health and safety, education, environmental exposures, food environment, health and health care, and sociocultural community context. CONCLUSIONS: Promoting the adoption of well-established social determinants of health protocols can enable consistent data collection and facilitate comparing and combining studies, with the potential to increase their scientific impact.

A History of Health Economics and Healthcare Delivery Research at the National Cancer Institute.

With increased attention to the financing and structure of healthcare, dramatic increases in the cost of diagnosing and treating cancer, and corresponding disparities in access, the study of healthcare economics and delivery has become increasingly important. The Healthcare Delivery Research Program (HDRP) in the Division of Cancer Control and Population Sciences at the National Cancer Institute (NCI) was formed in 2015 to provide a hub for cancer-related healthcare delivery and economics research. However, the roots of this program trace back much farther, at least to the formation of the NCI Division of Cancer Prevention and Control in 1983. The creation of a division focused on understanding and explaining trends in cancer morbidity and mortality was instrumental in setting the direction of cancer-related healthcare delivery and health economics research over the subsequent decades. In this commentary, we provide a brief history of health economics and healthcare delivery research at NCI, describing the organizational structure and highlighting key initiatives developed by the division, and also briefly discuss future directions. HDRP and its predecessors have supported the growth and evolution of these fields through the funding of grants and contracts; the development of data, tools, and other research resources; and thought leadership including stimulation of research on previously understudied topics. As the availability of new data, methods, and computing capacity to evaluate cancer-related healthcare delivery and economics expand, HDRP aims to continue to support this growth and evolution.

Using Economic Evaluation to Hasten Health Equity.

Achieving health equity has proven elusive for two reasons. First, most research has focused on changing the behavior of individuals; however, policies that address socioeconomic factors or change the context to facilitate healthy decisions tend to be more effective. Second, health disparity science and evidence are not consistently used to guide policy makers, even those seeking health equity. In this perspective, we discuss economic evaluation tools that researchers can use to assist decision-makers in conducting research or evaluating policy: self-reported health-related quality of life surveys and cost-benefit analysis evaluations informed with willingness to pay research and analyses.

The determination of thiocyanate in the blood plasma and holding water of Amphiprion clarkii after exposure to cyanide.

The illegal practice of cyanide fishing continues throughout the Indo-Pacific. To combat this destructive fishing method, a reliable test to detect whether a fish has been captured using cyanide (CN) is needed. We report on the toxicokinetics of acute, pulsed CN exposure and chronic thiocyanate (SCN) exposure, the major metabolite of CN, in the clownfish species, Amphiprion clarkii. Fish were pulse exposed to 50 ppm CN for 20 or 45 s or chronically exposed to 100 ppm SCN for 12 days and blood plasma levels of SCN were measured. SCN blood plasma levels reached a maximum concentration (301-468 ppb) 0.13-0.17 days after exposure to CN and had a 0.1 to 1.2 day half-life. The half-life of blood plasma SCN after chronic exposure to SCN was found to be 0.13 days. Interestingly, we observed that when a fish, with no previous CN or SCN exposure, was placed in holding water spiked to 20 ppb SCN, there was a steady decrease in the SCN concentration in the holding water until it could no longer be detected at 24 hrs. Under chronic exposure conditions (100 ppm, 12 days), trace levels of SCN (∼40 ppb) were detected in the holding water during depuration but decreased to below detection within the first 24 hrs. Our holding water experiments demonstrate that low levels of SCN in the holding water of A. clarkii will not persist, but rather will quickly and steadily decrease to below detection limits refuting several publications. After CN exposure, A. clarkii exhibits a classic two compartment model where SCN is eliminated from the blood plasma and is likely distributed throughout the body. Similar studies of other species must be examined to continue to develop our understanding of CN metabolism in marine fish before a reliable cyanide detection test can be developed.

The Importance of Health Insurance in Addressing Asian American Disparities in Utilization of Clinical Preventive Services: 12-Year Pooled Data from California.

Purpose: Previous research has shown that Asian Americans are less likely to receive recommended clinical preventive services especially for cancer compared with non-Hispanic whites. Health insurance expansion has been recommended as a way to increase use of these preventive services. This study examines the extent to which utilization of preventive services by Asians overall and by ethnicity compared with non-Hispanic whites is moderated by health insurance. Methods: Data from the California Health Interview Survey (CHIS) was used to examine preventive service utilization among non-Hispanic whites, Asians, and Asian subgroups 50-64 years of age by insurance status. Six waves of CHIS data from 2001 to 2011 were combined to allow analysis of Asian subgroups. Logistic regression models were run to predict the effect of insurance on receipt of mammography, colorectal cancer (CRC) screening, and flu shots among Asians overall and by ethnicity compared with whites. Results: Privately insured Asians reported significantly lower adjusted rates of mammography (83.1% vs. 87.6%) and CRC screening (54.7% vs. 59.4%), and higher rates of influenza vaccination (48.7% vs. 38.5%) than privately insured non-Hispanic whites. Adjusted rates of cancer screening were lower among Koreans and Chinese for mammography, and lower among Filipinos for CRC screening. Conclusion: This study highlights the limitations of providing insurance coverage as a strategy to eliminate disparities for cancer screening among Asians without addressing cultural factors.

Translational Health Disparities Research in a Data-Rich World.

Background: Despite decades of research and interventions, significant health disparities persist. Seventeen years is the estimated time to translate scientific discoveries into public health action. This Narrative Review argues that the translation process could be accelerated if representative data were gathered and used in more innovative and efficient ways. Methods: The National Institute on Minority Health and Health Disparities led a multiyear visioning process to identify research opportunities designed to frame the next decade of research and actions to improve minority health and reduce health disparities. "Big data" was identified as a research opportunity and experts collaborated on a systematic vision of how to use big data both to improve the granularity of information for place-based study and to efficiently translate health disparities research into improved population health. This Narrative Review is the result of that collaboration. Results: Big data could enhance the process of translating scientific findings into reduced health disparities by contributing information at fine spatial and temporal scales suited to interventions. In addition, big data could fill pressing needs for health care system, genomic, and social determinant data to understand mechanisms. Finally, big data could lead to appropriately personalized health care for demographic groups. Rich new resources, including social media, electronic health records, sensor information from digital devices, and crowd-sourced and citizen-collected data, have the potential to complement more traditional data from health surveys, administrative data, and investigator-initiated registries or cohorts. This Narrative Review argues for a renewed focus on translational research cycles to accomplish this continual assessment. Conclusion: The promise of big data extends from etiology research to the evaluation of large-scale interventions and offers the opportunity to accelerate translation of health disparities studies. This data-rich world for health disparities research, however, will require continual assessment for efficacy, ethical rigor, and potential algorithmic or system bias.

On the half-life of thiocyanate in the plasma of the marine fish Amphiprion ocellaris: implications for cyanide detection.

The illegal practice of using cyanide (CN) as a stunning agent to collect fish for both the marine aquarium and live fish food trades has been used throughout the Indo-Pacific for over 50 years. CN fishing is destructive to all life forms within the coral reef ecosystems where it is used and is certainly one of many anthropogenic activities that have led to 95% of the reefs in the Indo-Pacific being labeled at risk for degradation and loss. A field-deployable test for detecting fish caught using CN would assist in combating the use of this destructive practice, however, no reliable and robust test exists. Further, there is little toxicokinetic data available on marine fish to support the development of such a test, yet such data is critical to establishing the concentration range and time scale over which such a test would be viable. This study presents the first direct measurement of the half-life of the metabolite thiocyanate (SCN) after pulsed exposure to CN in a marine fish. SCN was measured in the plasma of Amphiprion ocellaris after exposure to 50 ppm CN for three exposure times (20, 45, and 60 s) using HPLC-UV and a C30 column pre-treated with polyethylene glycol. Plasma SCN levels observed are dose-dependent, reflecting a longer time for conversion of CN to SCN as the dose of CN increases. SCN plasma levels reached a maximum concentration (1.2-2.3 ppm) 12-20 h after exposure to CN. The half-life for the elimination of SCN was 1.01 ± 0.26 days for 45 s exposure and 0.44 ± 0.15 days for 20 s exposure. Fish were also directly exposed to SCN (100 ppm for 11 days) and the observed half-life for SCN elimination was 0.35 ± 0.07 days. Plasma SCN levels did not return to control levels, even after 41 days when exposed to CN but did return to control levels after 48 days when exposed to SCN. The similar half-lives observed for CN and SCN exposure suggests that SCN exposure can be used as a proxy for measuring the rate of SCN elimination following CN exposure. In order for plasma SCN to be used as a marker for CN exposure, these results must be extended to other species and endogenous levels of SCN in wild caught fish must be established.

Time to Follow-up After Colorectal Cancer Screening by Health Insurance Type.

INTRODUCTION: The purpose of this study was to test the hypothesis that patients with Medicaid insurance or Medicaid-like coverage would have longer times to follow-up and be less likely to complete colonoscopy compared with patients with commercial insurance within the same healthcare systems. METHODS: A total of 35,009 patients aged 50-64years with a positive fecal immunochemical test were evaluated in Northern and Southern California Kaiser Permanente systems and in a North Texas safety-net system between 2011 and 2012. Kaplan-Meier estimation was used between 2016 and 2017 to calculate the probability of having follow-up colonoscopy by coverage type. Among Kaiser Permanente patients, Cox regression was used to estimate hazard ratios and 95% CIs for the association between coverage type and receipt of follow-up, adjusting for sociodemographics and health status. RESULTS: Even within the same integrated system with organized follow-up, patients with Medicaid were 24% less likely to complete follow-up as those with commercial insurance. Percentage receiving colonoscopy within 3 months after a positive fecal immunochemical test was 74.6% for commercial insurance, 63.10% for Medicaid only, and 37.5% for patients served by the integrated safety-net system. CONCLUSIONS: This study found that patients with Medicaid were less likely than those with commercial insurance to complete follow-up colonoscopy after a positive fecal immunochemical test and had longer average times to follow-up. With the future of coverage mechanisms uncertain, it is important and timely to assess influences of health insurance coverage on likelihood of follow-up colonoscopy and identify potential disparities in screening completion.

The Importance of Evaluating Health Disparities Research.

Health disparity populations are socially disadvantaged, and the multiple levels of discrimination they often experience mean that their characteristics and attributes differ from those of the mainstream. Programs and policies targeted at reducing health disparities or improving minority health must consider these differences. Despite the importance of evaluating health disparities research to produce high-quality data that can guide decision-making, it is not yet a customary practice. Although health disparities evaluations incorporate the same scientific methods as all evaluations, they have unique components such as population characteristics, sociocultural context, and the lack of health disparity common indicators and metrics that must be considered in every phase of the research. This article describes evaluation strategies grouped into 3 components: formative (needs assessments and process), design and methodology (multilevel designs used in real-world settings), and summative (outcomes, impacts, and cost). Each section will describe the standards for each component, discuss the unique health disparity aspects, and provide strategies from the National Institute on Minority Health and Health Disparities Metrics and Measures Visioning Workshop (April 2016) to advance the evaluation of health disparities research.

Methodological Approaches to Understanding Causes of Health Disparities.

Understanding health disparity causes is an important first step toward developing policies or interventions to eliminate disparities, but their nature makes identifying and addressing their causes challenging. Potential causal factors are often correlated, making it difficult to distinguish their effects. These factors may exist at different organizational levels (e.g., individual, family, neighborhood), each of which needs to be appropriately conceptualized and measured. The processes that generate health disparities may include complex relationships with feedback loops and dynamic properties that traditional statistical models represent poorly. Because of this complexity, identifying disparities' causes and remedies requires integrating findings from multiple methodologies. We highlight analytic methods and designs, multilevel approaches, complex systems modeling techniques, and qualitative methods that should be more broadly employed and adapted to advance health disparities research and identify approaches to mitigate them.

Prevalence of Out-Of-Pocket Payments for Mammography Screening Among Recently Screened Women.

Background: Because cost may be a barrier to receiving mammography screening, cost sharing for "in-network" screening mammograms was eliminated in many insurance plans with implementation of the Affordable Care Act. We examined prevalence of out-of-pocket payments for screening mammography after elimination in many plans. Materials and Methods: Using 2015 National Health Interview Survey data, we examined whether women aged 50-74 years who had screening mammography within the previous year (n = 3,278) reported paying any cost for mammograms. Logistic regression models stratified by age (50-64 and 65-74 years) examined out-of-pocket payment by demographics and insurance (ages 50-64 years: private, Medicaid, other, and uninsured; ages 65-74 years: private ± Medicare, Medicare+Medicaid, Medicare Advantage, Medicare only, and other). Results: Of women aged 50-64 years, 23.5% reported payment, including 39.1% of uninsured women. Compared with that of privately insured women, payment was less likely for women with Medicaid (adjusted OR 0.17 [95% CI 0.07-0.41]) or other insurance (0.49 [0.25-0.96]) and more likely for uninsured women (1.99 [0.99-4.02]) (p < 0.001 across groups). For women aged 65-74 years, 11.9% reported payment, including 22.5% of Medicare-only beneficiaries. Compared with private ± Medicare beneficiaries, payment was less likely for Medicare+Medicaid beneficiaries (adjusted OR 0.21 [95% CI 0.06-0.73]) and more likely for Medicare-only beneficiaries (1.83 [1.01-3.32]) (p = 0.005 across groups). Conclusions: Although most women reported no payment for their most recent screening mammogram in 2015, some payment was reported by >20% of women aged 50-64 years or aged 65-74 years with Medicare only, and by almost 40% of uninsured women aged 50-64 years. Efforts are needed to understand why many women in some groups report paying out of pocket for mammograms and whether this impacts screening use.

Statistical inferences of extended concentration indices for directly standardized rates.

The relative concentration index (RCI) and the absolute concentration index (ACI) have been widely used for monitoring health disparities with ranked health determinants. The RCI has been extended to allow value judgments about inequality aversion by Pereira in 1998 and by Wagstaff in 2002. Previous studies of the extended RCI have focused on survey sample data. This paper adapts the extended RCI for use with directly standardized rates (DSRs) calculated from population-based surveillance data. A Taylor series linearization (TL)-based variance estimator is developed and evaluated using simulations. A simulation-based Monte Carlo (MC) variance estimator is also evaluated as a comparison. Following Wagstaff's approach in 1991, we extend the ACI for use with DSRs. In all simulations, both the TL and MC methods produce valid variance estimates. The TL variance estimator has a simple, closed form that is attractive to users without sophisticated programming skills. The TL and MC estimators have been incorporated into a beta version of the National Cancer Institute's Health Disparities Calculator, a free statistical software tool that enables the estimation of 11 commonly used summary measures of health disparities for DSRs.

Correction: Can excreted thiocyanate be used to detect cyanide exposure in live reef fish?

[This corrects the article DOI: 10.1371/journal.pone.0196841.].

Patterns and Trends in Cancer Screening in the United States.

INTRODUCTION: We examined the prevalence of cancer screening reported in 2015 among US adults, adjusted for important sociodemographic and access-to-care variables. By using data from the National Health Interview Survey (NHIS) for 2000 through 2015, we examined trends in prevalence of cancer screening that adhered to US Preventive Services Task Force screening recommendations in order to monitor screening progress among traditionally underserved population subgroups. METHODS: We analyzed NHIS data from surveys from 2000 through 2015 to estimate prevalence and trends in use of recommended screening tests for breast, cervical, colorectal, and prostate cancers. We used logistic regression and report predictive margins for population subgroups adjusted for various socioeconomic and demographic variables. RESULTS: Colorectal cancer screening was the only test that increased during the study period. We found disparities in prevalence of test use among subgroups for all tests examined. Factors that reduced the use of screening tests included no contact with a doctor in the past year, no usual source of health care, and no insurance coverage. CONCLUSION: Understanding use of cancer screening tests among different population subgroups is vital for planning public health interventions with potential to increase screening uptake and reduce disparities in cancer morbidity and mortality. Overarching goals of Healthy People 2020 are to "achieve health equity, eliminate disparities, and improve the health of all groups." Adjusted findings for 2015, compared with previous years, show persistent screening disparities, particularly among the uninsured, and progress for colorectal cancer screening only.

Can excreted thiocyanate be used to detect cyanide exposure in live reef fish?

Cyanide fishing, where a solution of sodium or potassium cyanide is used to stun reef fish for easy capture for the marine aquarium and live fish food trades, continues to be pervasive despite being illegal in many countries and destructive to coral reef ecosystems. Currently, there is no easy, reliable and universally accepted method to detect if a fish has been exposed to cyanide during the capture process. A promising non-invasive technique for detecting thiocyanate ions, the metabolic byproduct excreted by exposed fish, has been reported in the literature. In an effort to validate this method, four cyanide exposure studies on Amphiprion ocellaris (common clownfish) were carried out over three years. Fish were either exposed to the same (25 ppm) or twice the concentration (50 ppm) as the previsouly published method. Over 100 water samples of fish exposed to cyanide were analyzed by reverse phase HPLC with a C30 column treated with polyethylene glycol and UV detector operating at 220 nm. No thiocyanate was detected beyond the analytical standards and positive controls prepared in seawater. As an alternate means of detecting thiocyanate, water samples and thiocyanate standards from these exposures were derivatized with monobromobimane (MBB) for LC-MS/MS analysis. Thiocyanate was detected in standards with concentrations as low as 0.6 µg/L and quantified to 1 µg/L, but thiocyanate could not be detected in any of the water samples from fish exposed to cyanide with this method either, confirming the HPLC results. Further, we calculated both the mass balance of thiocyanate and the resultant plausible dosage of cyanide from the data reported in the previously published method. These calculations, along with the known lethal dosage of cyanide, further suggests that the detection of thiocyanate in aquarium water is not a viable method for assessing fish exposure to cyanide.

An Exploration of Changes in the Measurement of Mammography in the National Health Interview Survey.

Background: Using the National Health Interview Survey (NHIS), we examined the effect of question wording on estimates of past-year mammography among racially/ethnically diverse women ages 40-49 and 50-74 without a history of breast cancer.Methods: Data from one-part ("Have you had a mammogram during the past 12 months?") and two-part ("Have you ever had a mammogram"; "When did you have your most recent mammogram?") mammography history questions administered in the 2008, 2011, and 2013 NHIS were analyzed. χ2 tests provided estimates of changes in mammography when question wording was either the same (two-part question) or differed (two-part question followed by one-part question) in the two survey years compared. Crosstabulations and regression models assessed the type, extent, and correlates of inconsistent responses to the two questions in 2013.Results: Reports of past-year mammography were slightly higher in years when the one-part question was asked than when the two-part question was asked. Nearly 10% of women provided inconsistent responses to the two questions asked in 2013. Black women ages 50 to 74 [adjusted OR (aOR), 1.50; 95% confidence interval (CI), 1.16-1.93] and women ages 40-49 in poor health (aOR, 2.22; 95% CI, 1.09-4.52) had higher odds of inconsistent responses; women without a usual source of care had lower odds (40-49: aOR, 0.42; 95% CI, 0.21-0.85; 50-74: aOR, 0.42; 95% CI, 0.24-0.74).Conclusions: Self-reports of mammography are sensitive to question wording. Researchers should use equivalent questions that have been designed to minimize response biases such as telescoping and social desirability.Impact: Trend analyses relying on differently worded questions may be misleading and conceal disparities. Cancer Epidemiol Biomarkers Prev; 26(11); 1611-8. ©2017 AACR.

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

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.