Decolonial education and geography: Beyond the 2017 Royal Geographical Society with the Institute of British Geographers annual conference

This review is inspired by the recent resurgence of grassroots movements aimed at the decolonisation of education. The departure point of the paper are the numerous, recent academic responses to campaigns such as Rhodes Must Fall, Why is My Curriculum White?, Why Isn't My Professor Black?, and #LiberateMyDegree. Following from there, the narrative is divided into two sections. The first part reviews theoretical approaches to decolonial education, especially those rooted in the modernity/coloniality/decoloniality paradigm. The second part analyses the ways in which geographers have applied these ideas to our discipline. The review pays particular attention to the 2017 Royal Geographical Society with the Institute of British Geographers annual conference, curated under the “Decolonising geographical knowledges” theme. I argue that as geographers, we have to continue reflecting on the meaning of decolonial praxis, especially in relation to geographical education, beyond the recent conference. To these ends, the review concludes with seven specific questions for geographers to consider in the near future

Health plan administrative records versus birth certificate records: quality of race and ethnicity information in children

<p>Abstract</p> <p>Background</p> <p>To understand racial and ethnic disparities in health care utilization and their potential underlying causes, valid information on race and ethnicity is necessary. However, the validity of pediatric race and ethnicity information in administrative records from large integrated health care systems using electronic medical records is largely unknown.</p> <p>Methods</p> <p>Information on race and ethnicity of 325,810 children born between 1998-2008 was extracted from health plan administrative records and compared to birth certificate records. Positive predictive values (PPV) were calculated for correct classification of race and ethnicity in administrative records compared to birth certificate records.</p> <p>Results</p> <p>Misclassification of ethnicity and race in administrative records occurred in 23.1% and 33.6% children, respectively; the majority due to missing ethnicity (48.3%) and race (40.9%) information. Misclassification was most common in children of minority groups. PPV for White, Black, Asian/Pacific Islander, American Indian/Alaskan Native, multiple and other was 89.3%, 86.6%, 73.8%, 18.2%, 51.8% and 1.2%, respectively. PPV for Hispanic ethnicity was 95.6%. Racial and ethnic information improved with increasing number of medical visits. Subgroup analyses comparing racial classification between non-Hispanics and Hispanics showed White, Black and Asian race was more accurate among non-Hispanics than Hispanics.</p> <p>Conclusions</p> <p>In children, race and ethnicity information from administrative records has significant limitations in accurately identifying small minority groups. These results suggest that the quality of racial information obtained from administrative records may benefit from additional supplementation by birth certificate data.</p

Using a Spanish Surname Match to Improve Identification of Hispanic Women in Medicare Administrative Data

OBJECTIVE: To assess the effectiveness of a Spanish surname match for improving the identification of Hispanic women in Medicare administrative data in which Hispanics are historically underrepresented. DATA SOURCES: We collected self-identified race/ethnicity data (N = 2,997) from a mailed survey sent to elderly Medicare beneficiaries who resided in 11 geographic areas consisting of eight metropolitan counties and three nonmetropolitan areas (171 counties) in the fall of 2004. The 1990 Census Spanish Surname list was used to identify Hispanics in the Medicare data. In addition, we used data published on the U.S. Census Bureau website to obtain estimates of elderly Hispanics. STUDY DESIGN: We used self-identified race/ethnicity as the gold standard to examine the agreement with Medicare race code alone, and with Medicare race code+Spanish surname match. Additionally, we estimated the proportions of Hispanic women and men, in each of the 11 geographic areas in our survey, using the Medicare race code alone and the Medicare race code+Spanish surname match, and compared those estimates with estimates derived from U.S. Census 2000 data. PRINCIPAL FINDINGS: The Spanish surname match dramatically increased the accuracy of the Medicare race code for identifying both Hispanic and white women, producing improvements comparable with those seen for men. CONCLUSIONS: We recommend the addition of a proxy race code in the Medicare data using the Spanish surname match to improve the accuracy of racial/ethnic representation

Methods for Using Medicare Data to Compare Procedure Rates among Asians, Blacks, Hispanics, Native Americans, and Whites

OBJECTIVE: Small sample sizes in Asian, Hispanic, and Native American groups and misreporting of race/ethnicity across all groups (including blacks and whites) limit the usefulness of racial/ethnic comparisons based on Medicare data. The objective of this paper is to compare procedure rates for these groups using Medicare data, to assess how small sample size and misreporting affect the validity of comparisons, and to compare rates after correcting for misreporting. DATA: We use 1997 physician claims data for a 5 percent sample of Medicare beneficiaries aged 65 and older to study cardiac procedures and tests. STUDY DESIGN: We calculate age and sex-adjusted rates and confidence intervals by race/ethnicity. Confidence intervals are compared among the groups. Out-of-sample data on misreporting of race/ethnicity are used to assess potential bias due to misreporting, and to correct for the bias. PRINCIPAL FINDINGS: Sample sizes are sufficient to find significant ethnic and racial differences for most procedures studied. Blacks' rates tend to be lower than whites. Asian and Hispanic rates also tend to be lower than whites', and about the same as blacks'. Sample sizes for Native Americans are very small (about .1 percent of the data); nonetheless, some significant differences from whites can still be identified. Biases in rates due to misreporting are small (less than 10 percent) for blacks, Hispanics, and whites. Biases in rates for Asians and Native Americans are greater, and exceed 20 percent for some procedures. CONCLUSIONS: Sample sizes for Asians, blacks, and Hispanics are generally adequate to permit meaningful comparisons with whites. Implementing a correction for misreporting makes Medicare data useful for all ethnic groups. Misreporting race/ethnicity and small sample sizes do not materially limit the usefulness of Medicare data for comparing rates among racial and ethnic groups

Addressing Racial and Ethnic Disparities in Health Care: Using Federal Data to Support Local Programs to Eliminate Disparities: Current Accuracy and Recent Improvements

To reduce racial and ethnic disparities in health care, managers, policy makers, and researchers need valid and reliable data on the race and ethnicity of individuals and populations. The federal government is one of the most important sources of such data. In this paper we review the strengths and weaknesses of federal data that pertain to racial and ethnic disparities in health care. We describe recent developments that are likely to influence how these data can be used in the future and discuss how local programs could make use of these data