Association between prior experiences of discrimination and patients' attitudes towards health care providers collecting information about race and ethnicity

Missing Race and Ethnicity Data among COVID-19 Cases in Massachusetts

Infectious disease surveillance frequently lacks complete information on race and ethnicity, making it difficult to identify health inequities. Greater awareness of this issue has occurred due to the COVID-19 pandemic, during which inequities in cases, hospitalizations, and deaths were reported but with evidence of substantial missing demographic details. Although the problem of missing race and ethnicity data in COVID-19 cases has been well documented, neither its spatiotemporal variation nor its particular drivers have been characterized. Using individual-level data on confirmed COVID-19 cases in Massachusetts from March 2020 to February 2021, we show how missing race and ethnicity data: (1) varied over time, appearing to increase sharply during two different periods of rapid case growth; (2) differed substantially between towns, indicating a nonrandom distribution; and (3) was associated significantly with several individual- and town-level characteristics in a mixed-effects regression model, suggesting a combination of personal and infrastructural drivers of missing data that persisted despite state and federal data-collection mandates. We discuss how a variety of factors may contribute to persistent missing data but could potentially be mitigated in future contexts.

Potential harms associated with routine collection of patient sociodemographic information: A rapid review

Background

Health systems are recommended to capture routine patient sociodemographic data as a key step in providing equitable person‐centred care. However, collection of this information has the potential to cause harm, especially for vulnerable or potentially disadvantaged patients.

Objective

To identify harms perceived or experienced by patients, their families, or health‐care providers from collection of sociodemographic information during routine health‐care visits and to identify best practices for when, by whom and how to collect this information.

Search Strategy

We searched OVID MEDLINE, PubMed “related articles” via NLM and healthevidence.org to the end of January 2018 and assessed reference lists and related citations of included studies.

Inclusion Criteria

We included studies reporting on harms of collecting patient sociodemographic information in health‐care settings.

Data Extraction and Synthesis

Data on study characteristics and types of harms were extracted and summarized narratively.

Main Results

Eighteen studies were included; 13 provided patient perceptions or experiences with the collection of these data and seven studies reported on provider perceptions. Five reported on patient recommendations for collecting sociodemographic information. Patients and providers reported similar potential harms which were grouped into the following themes: altered behaviour which may affect care‐seeking, data misuse or privacy concerns, discomfort, discrimination, offence or negative reactions, and quality of care. Patients suggested that sociodemographic information be collected face to face by a physician.

Discussion and Conclusions

Overall, patients support the collection of sociodemographic information. However, harms are possible, especially for some population subgroups. Harms may be mitigated by providing a rationale for the collection of this information.

Racial Discrimination in Health Care and Utilization of Health Care: a Cross-sectional Study of California Adults

BACKGROUND

Racial and ethnic discrimination in health care have been associated with suboptimal use of health care. However, limited research has examined how facets of health care utilization influence, and are influenced by, discrimination.

OBJECTIVE

This study aimed to determine if type of insurance coverage and location of usual source of care used were associated with perceptions of racial or ethnic discrimination in health care. Additionally, this study examined if perceived racial or ethnic discrimination influenced delaying or forgoing prescriptions or medical care.

DESIGN

Data from the 2015-2016 California Health Interview Survey were used. Logistic regression models estimated odds of perceiving racial or ethnic discrimination from insurance type and location of usual source of care. Logistic regression models estimated odds of delaying or forgoing medical care or prescriptions.

PARTICIPANTS

Responses for 39,171 adults aged 18 and over were used.

MAIN MEASURES

Key health care utilization variables were as follows: current insurance coverage, location of usual source of care, delaying or forgoing medical care, and delaying or forgoing prescriptions. We examined if these effects differed by race. Ever experiencing racial or ethnic discrimination in the health care setting functioned as a dependent and independent variable in analyses.

KEY RESULTS

When insurance type and location of care were included in the same model, only the former was associated with perceived discrimination. Specifically, those with Medicaid had 66% higher odds of perceiving discrimination, relative to those with employer-sponsored coverage (AOR = 1.66; 95% CI 1.11, 2.47). Race did not moderate the impact of discrimination. Perceived discrimination was associated with higher odds of delaying or forgoing both prescriptions (AOR = 1.97; 95% CI 1.26, 3.09) and medical care (AOR = 1.84; 95% CI 1.31, 2.59).

CONCLUSIONS

Health care providers have an opportunity to improve the experiences of their patients, particularly those with publicly sponsored coverage.

Community Efforts to Reduce Racial and Ethnic Health Disparities: Challenges and Facilitators Identified by 16 Multistakeholder Alliances

The Robert Wood Johnson Foundation's Aligning Forces for Quality (AF4Q) program aimed to improve health care quality and reduce racial and ethnic disparities in 16 diverse communities in the United States from 2006 to 2015; yet most communities failed to make substantive progress toward advancing health care equity by the program's end. This qualitative analysis of key stakeholder interviews aims to identify the major contributors to success versus failure in addressing local health disparities during AF4Q and identified five major themes. Three themes highlight challenges related to collecting local data on racial and ethnic health disparities and transitioning from data collection to action. Two themes capture the critical contribution of stakeholder engagement and access to technical expertise to successful efforts. The challenges and facilitators experienced by these 16 AF4Q communities may help inform the disparities reduction efforts of other communities and guide state or federal policies to reduce health disparities.

Use of Electronic Health Record Data to Evaluate the Impact of Race on 30-Day Mortality in Patients Admitted to the Intensive Care Unit

INTRODUCTION

The current body of literature examining the impact of race upon outcomes for patients admitted to the intensive care unit (ICU) is limited. The primary objective of our study was to explore this question using a large cohort drawn from an electronic health record (EHR)-based data source.

METHODS

We conducted a retrospective cohort study using Multiparameter Intelligent Monitoring in Intensive Care (MIMIC-II), an EHR-derived database encompassing ICU admissions to an academic medical center in Boston, Massachusetts, between 2001 and 2008. Adults admitted to a medical or surgical ICU were assessed for the primary outcome of 30-day mortality and secondary outcomes of in-hospital mortality and hospital length-of-stay. Multivariate logistic regression was used to determine the association between race and the primary outcome.

RESULTS

The study cohort consisted of 14,684 adult ICU patients-10,562 White, 1311 Black, 363 Asian, 868 "Other," and 1580 without known race. Thirty-day mortality rates experienced by Black and Asian individuals were significantly lower than mortality among those identified as White, with odds ratios of 0.62 (95 % CI 0.50-0.77) and 0.64 (95 % CI 0.44-0.93), respectively. Patients without known race experienced the highest crude mortality overall (27.4 %) and twice the adjusted odds of mortality compared with the White group.

CONCLUSIONS

In a large, racially diverse cohort of general ICU patients, White patients experienced significantly higher mortality than non-White patients. Our results are consistent with findings from other studies that indicate that the non-White race does not appear to negatively impact short-term survival following ICU admission.

Can ethnicity data collected at an organizational level be useful in addressing health and healthcare inequities?

OBJECTIVE

Following arguments made in the USA, the UK and New Zealand regarding the importance of population-level ethnicity data in understanding health and healthcare inequities, health authorities in several Canadian provinces are considering plans to collect ethnicity data from patients at the point of care within selected healthcare organizations. The purpose of this paper is to examine the potential quality, utility and relevance of ethnicity data collected at an organizational level as a means of addressing health and healthcare inequities.

DESIGN

We draw on findings from a recent Canadian study that examined the implications of collecting ethnicity data in healthcare contexts. Using a qualitative design, data were collected in a large city, and included interviews with 104 patients, community and healthcare leaders, and healthcare workers within diverse clinical contexts. Data were analyzed using interpretive thematic analysis.

RESULTS

Our results are discussed in relation to discourses reflected in the current literature that require consideration in relation to the potential utility and relevancy of ethnicity data collected at the point of care within healthcare organizations. These discourses frame excerpts from the ethnographic data that are used as illustrative examples. Three key challenges to the potential relevance and utility of ethnicity data collected at the level of local healthcare organizations are identified: (a) issues pertaining to quality of the data, (b) the fact that data quality is most problematic for those with the greatest vulnerability to the negative effects of health inequities, and (c) the lack of data reflecting structural disadvantages or discrimination.

CONCLUSION

The quality of ethnicity data collected within healthcare organizations is often unreliable, particularly for people from racialized or visible minority groups, who are most at risk, seriously limiting the usefulness of the data. Quality measures for collecting data reflecting ethnocultural identity in specific healthcare organizations may be warranted - but only if mechanisms exist or are developed for linking ethnicity with measures of perceived discrimination, stigmatization, income level, and other known contributors to inequities. Methods for linking these kinds of data, however, remain underdeveloped or non-existent in most healthcare organizations.

The state of research on racial/ethnic discrimination in the receipt of health care

OBJECTIVES

We conducted a review to examine current literature on the effects of interpersonal and institutional racism and discrimination occurring within health care settings on the health care received by racial/ethnic minority patients.

METHODS

We searched the PsychNet, PubMed, and Scopus databases for articles on US populations published between January 1, 2008 and November 1, 2011. We used various combinations of the following search terms: discrimination, perceived discrimination, race, ethnicity, racism, institutional racism, stereotype, prejudice or bias, and health or health care. Fifty-eight articles were reviewed.

RESULTS

Patient perception of discriminatory treatment and implicit provider biases were the most frequently examined topics in health care settings. Few studies examined the overall prevalence of racial/ethnic discrimination and none examined temporal trends. In general, measures used were insufficient for examining the impact of interpersonal discrimination or institutional racism within health care settings on racial/ethnic disparities in health care.

CONCLUSIONS

Better instrumentation, innovative methodology, and strategies are needed for identifying and tracking racial/ethnic discrimination in health care settings.

Untangling the associations among distrust, race, and neighborhood social environment: a social disorganization perspective

Over the past decade, interest in exploring how health care system distrust is associated with individual health outcomes and behaviors has grown substantially, and the racial difference in distrust has been well documented, with African Americans demonstrating higher distrust than whites. However, relatively little is known about whether the individual-level determinants of distrust differ by various dimensions of distrust, and even less is understood regarding whether the race-distrust association could be moderated by the neighborhood social environment. This study used a dual-dimensional distrust scale (values and competence distrust), and applied social disorganization theory to address these gaps. We combined the 2008 Philadelphia Health Management Corporation's household survey (N = 3746 adult respondents, 51% of which are of African American race) with neighborhood-level data (N = 45 neighborhoods) maintained by the 2000 U.S. Census and the Philadelphia Police Department. Using multilevel modeling, we found that first, after controlling for individual- and neighborhood-level covariates, African American residents have greater values distrust than whites, but no racial difference was found in competence distrust; second, competence distrust is more likely to be determined by personal health status and access to health care services than is values distrust; and third, ceteris paribus, the association between race and values distrust was weakened by the increasing level of neighborhood stability. These results not only indicate that different aspects of distrust may be determined via different mechanisms, but also suggest that establishing a stable neighborhood may ameliorate the level of distrust in the health care system among African Americans. As distrust has been identified as a barrier to medical research, the insight provided by this study can be applied to develop a health care system that is trusted, which will, in turn, improve population health.

Sociodemographic data collection in healthcare settings: an examination of public opinions

BACKGROUND

Federal, provincial, and municipal organizations in Canada have recently begun to promote an equity agenda for their health systems, but much of the necessary data by which to identify those with social disadvantage are not currently collected.

METHODS

We conducted a national survey of 1005 Canadian adults to assess the perceived importance of, and concern about, the collection of personal sociodemographic information by hospitals. We also examined public preference for practical approaches to the future collection of such information.

RESULTS

In this sample of Canadian adults, nearly half did not believe it was important for hospitals to collect individual-level sociodemographic data. The majority had concerns that the collection of these data could negatively affect their or others' care; this was especially true among visible minorities and those who have experienced discrimination. There was substantial variation across participant subgroups in their comfort with the collection of various types of information, but greater discomfort in general for current household income, sexual orientation, and education background. There was consistent discomfort reported from older participants. Participants in general were most comfortable providing this type of information to their family physician.

INTERPRETATION

The importance of collecting patient-level equity-relevant data is not widely appreciated in Canada, and our survey has shown that concern about how these data could be misused are high, especially among certain subgroups. Qualitative research to further explore and understand these concerns, patient education about data usage and privacy issues, and using the family doctor's office as a linked electronic data collection point, will likely be important as we move toward high-quality equity measurement.

Responses of Massachusetts hospitals to a state mandate to collect race, ethnicity and language data from patients: a qualitative study

BACKGROUND

A Massachusetts regulation implemented in 2007 has required all acute care hospitals to report patients' race, ethnicity and preferred language using standardized methodology based on self-reported information from patients. This study assessed implementation of the regulation and its impact on the use of race and ethnicity data in performance monitoring and quality improvement within hospitals.

METHODS

Thematic analysis of semi-structured interviews with executives from a representative sample of 28 Massachusetts hospitals in 2009.

RESULTS

The number of hospitals using race, ethnicity and language data internally beyond refining interpreter services increased substantially from 11 to 21 after the regulation. Thirteen of these hospitals were utilizing patient race and ethnicity data to identify disparities in quality performance measures for a variety of clinical processes and outcomes, while 16 had developed patient services and community outreach programs based on findings from these data. Commonly reported barriers to data utilization include small numbers within categories, insufficient resources, information system requirements, and lack of direction from the state.

CONCLUSIONS

The responses of Massachusetts hospitals to this new state regulation indicate that requiring the collection of race, ethnicity and language data can be an effective method to promote performance monitoring and quality improvement, thereby setting the stage for federal standards and incentive programs to eliminate racial and ethnic disparities in the quality of health care.

Racial/ethnic discrimination in health care: impact on perceived quality of care

BACKGROUND

Racial/ethnic minorities are more likely to report receipt of lower quality of health care; however, the mediators of such patient reports are not known.

OBJECTIVES

To determine (1) whether racial disparities in perceptions of quality of health care are mediated by perceptions of being discriminated against while receiving medical care and (2) whether this association is further mediated by patient sociodemographic characteristics, access to care, and patient satisfaction across racial/ethnic groups.

RESEARCH DESIGN

A cross-sectional analysis of a population-based sample of California adults responding to the 2003 California Health Interview Survey. Multivariable logistic regression was used to examine the relationship between perceived discrimination and perceived quality of health care after adjusting for patient characteristics and reports of access to care.

MAIN RESULTS

A total of 36,831 respondents were included. African Americans (68.7%) and Asian/Pacific Islanders (64.5%) were less likely than non-Hispanic whites (72.8%) and Hispanics (74.9%) to rate their health care quality highly. African Americans (13.1%) and Hispanics (13.4%) were the most likely to report discrimination, followed by Asian/Pacific Islanders (7.3%) and non-Hispanic whites (2.6%). Racial/ethnic discrimination in health care was negatively associated with ratings of health care quality within each racial/ethnic group, even after adjusting for sociodemographic variables and other indicators of access and satisfaction. Feeling discriminated against fully accounted for the difference in low ratings of quality care between African Americans and whites, but not for other racial/ethnic minorities.

CONCLUSIONS

Patient perceptions of discrimination may play an important, yet variable role in ratings of health care quality across racial/ethnic minority groups. Health care institutions should consider how to address this patient concern as a part of routine quality improvement.