Explaining racial-ethnic differences in hypertension and diabetes control among veterans before and after patient-centered medical home implementation

Investigation of the role of perceived access to primary care in mediating and moderating racial and ethnic disparities in chronic disease control in the veterans health administration

OBJECTIVE

To examine the role of patient-perceived access to primary care in mediating and moderating racial and ethnic disparities in hypertension control and diabetes control among Veterans Health Administration (VA) users.

DATA SOURCE AND STUDY SETTING

We performed a secondary analysis of national VA user administrative data for fiscal years 2016-2019.

STUDY DESIGN

Our primary exposure was race or ethnicity and primary outcomes were binary indicators of hypertension control (<140/90 mmHg) and diabetes control (HgbA1c < 9%) among patients with known disease. We used the inverse odds-weighting method to test for mediation and logistic regression with race and ethnicity-by-perceived access interaction product terms to test moderation. All models were adjusted for age, sex, socioeconomic status, rurality, education, self-rated physical and mental health, and comorbidities.

DATA COLLECTION/EXTRACTION METHODS

We included VA users with hypertension and diabetes control data from the External Peer Review Program who had contemporaneously completed the Survey of Healthcare Experience of Patients-Patient-Centered Medical Home. Hypertension (34,233 patients) and diabetes (23,039 patients) samples were analyzed separately.

PRINCIPAL FINDINGS

After adjustment, Black patients had significantly lower rates of hypertension control than White patients (75.5% vs. 78.8%, p < 0.01); both Black (81.8%) and Hispanic (80.4%) patients had significantly lower rates of diabetes control than White patients (85.9%, p < 0.01 for both differences). Perceived access was lower among Black, Multi-Race and Native Hawaiian and Other Pacific Islanders compared to White patients in both samples. There was no evidence that perceived access mediated or moderated associations between Black race, Hispanic ethnicity, and hypertension or diabetes control.

CONCLUSIONS

We observed disparities in hypertension and diabetes control among minoritized patients. There was no evidence that patients' perception of access to primary care mediated or moderated these disparities. Reducing racial and ethnic disparities within VA in hypertension and diabetes control may require interventions beyond those focused on improving patient access.

Rural and Urban Hispanic Patients of the Veterans Health Administration

Hispanic Veterans are the largest growing racial and ethnic minority group in the Veterans Health Administration (VA) system. Though recent research has found increasing suicide rates in this population and a growing rural-urban disparity, literature on core population characteristics remains sparse. We used extensive patient demographic and clinical data from VA's electronic medical record repository to examine geographic and longitudinal variation in Hispanic VA patients from 2001 to 2018. As the first such detailed characterization of this population, this study was largely descriptive in nature, and included heatmaps of Hispanic patient residence across rural and urban US counties, along with descriptive measures of patient characteristics by rurality, and first year of VA use. We found that Hispanic patients (n = 722,893) represented 5.2% of new VA users between 2001 and 2018, a proportion which grew nearly 90% from 4.0% (2001-2006) to 7.5% (2013-2018). Hispanic patients were largely White, male, under age 50, and had minimal illness or disability. The highest prevalence of Hispanic patients was in the Southwest US/Mexico border region, while the Midwest experienced the largest growth of Hispanic patients. Rural Hispanic patients were more likely to be older, male, and to live in areas characterized by small foreign-born populations and high socioeconomic deprivation. Compared with Hispanic patients entering the VA system in 2001-2006, patients in 2013-2018 were younger, more likely to be female, and to live in urban areas. These findings illustrate the wide range of demographic, clinical, and geographic experiences in the growing VA Hispanic population and demonstrate that culturally competent care for Hispanic Veterans must reflect their intra-ethnic diversity.

Nursing leadership and influence in practice domains at a Veterans Affairs Health Care System

BACKGROUND

Studies in Veteran populations have examined disparities in health service use, care quality, outcomes and increased demands for behavioral health.

PURPOSE

The purpose is to describe the development of nursing leadership roles that influenced practice improvements and demonstrated outcomes related to health disparities in a Veterans Affairs (VA) population over a 12-year period.

METHODS

The Sundean and colleagues' concept analysis of nurse leadership influence was applied to frame the initiative process and impacts.

DISCUSSION

Antecedents and processes that facilitated leadership development included mentorship, disparities expertise, partnerships, consultation, scholarship, dissemination, advocacy, education, and strong coauthor collaboration. Improvements and outcomes included access to services, improved health indicators, tools, workforce, funding, innovations, and nurse investigator studies, consistent with VA priorities and policy related to disparities and equity. Limitations and barriers were addressed.

CONCLUSION

This initiative models' strategies to increase nurse leadership in health equity and care transformation in health systems and community practices.

Using medical expenditure panel survey data to explore the relationship between patient-centered medical homes and racial disparities in severe maternal morbidity outcomes

BACKGROUND

There are persistent racial/ethnic disparities in the occurrence of severe maternal morbidity. Patient-centered medical home care has the potential to address disparities in maternal outcomes.

OBJECTIVES

To examine (1) the association between receiving patient-centered medical home care and severe maternal morbidity outcomes and (2) the interaction of race/ethnicity on patient-centered medical home status and severe maternal morbidity.

DESIGN/METHODS

Using 2007 to 2016 data from the Medical Expenditures Panel Survey, we conducted a cross-sectional study to estimate the association between receipt of care from a patient-centered medical home and the occurrence of severe maternal morbidity, and racial-specific (White, Black, Asian, Other) relative risks of severe maternal morbidity. Our study used race as a proxy measure for exposure racism. We identified mothers (⩾15 years) who gave birth during the study period. We identified patient-centered medical home qualities using 11 Medical Expenditures Panel Survey questions and severe maternal morbidities using medical claims, and calculated generalized estimating equation models to estimate odds ratios of severe maternal morbidity and 95% confidence intervals.

RESULTS

Among all mothers who gave birth (N = 2801; representing 5,362,782 US lives), only 25% received some exposure patient-centered medical home care. Two percent experienced severe maternal morbidity, and this did not differ statistically (p = 0.11) by patient-centered medical home status. However, our findings suggest a 85% decrease in the risk of severe maternal morbidity among mothers who were defined as always attending a patient-centered medical home (odds ratios: 0.15; 95% confidence interval:0.01-1.87; p = 0.14) and no difference in the risk of severe maternal morbidity among mothers who were defined as sometimes attending a patient-centered medical home (odds ratios: 1.00; 95% confidence interval:0.16-6.42; p = 1.00). There was no overall interaction effect in the model between race and patient-centered medical home groups (p = 0.82), or ethnicity and patient-centered medical home groups (p = 0.62) on the severe maternal morbidity outcome.

CONCLUSION

While the rate of severe maternal morbidity was similar to US rates, few mothers received care from a patient-centered medical home which may be due to underreporting. Future research should further investigate the potential for patient-centered medical home-based care to reduce odds of severe maternal morbidity across racial/ethnic groups.

Optimizing Data on Race and Ethnicity for Veterans Affairs Patients

INTRODUCTION

Maintaining accurate race and ethnicity data among patients of the Veterans Affairs (VA) healthcare system has historically been a challenge. This work expands on previous efforts to optimize race and ethnicity values by combining multiple VA data sources and exploring race- and ethnicity-specific collation algorithms.

MATERIALS AND METHODS

We linked VA patient data from 2000 to 2018 with race and ethnicity data from four administrative and electronic health record sources: VA Medical SAS files (MedSAS), Corporate Data Warehouse (CDW), VA Centers for Medicare extracts (CMS), and VA Defense Identity Repository Data (VADIR). To assess the accuracy of each data source, we compared race and ethnicity values to self-reported data from the Survey of Health Experiences of Patients (SHEP). We used Cohen's Kappa to assess overall (holistic) source agreement and positive predictive values (PPV) to determine the accuracy of sources for each race and ethnicity separately.

RESULTS

Holistic agreement with SHEP data was excellent (K > 0.80 for all sources), while race- and ethnicity-specific agreement varied. All sources were best at identifying White and Black users (average PPV = 0.94, 0.93, respectively). When applied to the full VA user population, both holistic and race-specific algorithms substantially reduced unknown values, as compared to single-source methods.

CONCLUSIONS

Combining multiple sources to generate race and ethnicity values improves data accuracy among VA patients. Based on the overall agreement with self-reported data, we recommend using non-missing values from sources in the following order to fill in race values-SHEP, CMS, CDW, MedSAS, and VADIR-and in the following order to fill in ethnicity values-SHEP, CDW, MedSAS, VADIR, and CMS.