Health information technology and the collection of race, ethnicity, and language data to reduce disparities in quality of care

Racial Disparities in Administration of Venous Thromboembolism Prophylaxis After Severe Traumatic Injuries

BACKGROUND

Race is associated with differences in quality of care process measures and incidence of venous thromboembolism (VTE) in trauma patients. We aimed to investigate if racial disparities exist in the administration of VTE prophylaxis in trauma patients.

METHODS

We queried the Trauma Quality Improvement Project database from 2017 to 2019. Patients ages ≥16 years old with ISS ≥15 were included. Patients with no signs of life on arrival, any AIS ≥6, hospital length of stay <1 day, anticoagulant use before admission, or without recorded race were excluded. Patients were grouped by race: white, black, Asian, American Indian, and Native Hawaiian or Pacific Islander. The association between VTE prophylaxis administration and race was determined using a Poisson regression model with robust standard errors to adjust for confounders.

RESULTS

A total of 285,341 patients were included. Black patients had the highest rates of VTE prophylaxis exposure (73.8%), shortest time to administration (1.6 days), and highest use of low molecular weight heparin (56%). Black patients also had the highest incidence of deep vein thrombosis (2.8%) and pulmonary embolism (1.4%). Black patients were 4% more likely to receive VTE prophylaxis than white patients [adj. IRR (95% CI): 1.04 (1.03-1.05), P < .001]. American Indians were 8% less likely to receive VTE prophylaxis [adj. IRR (95% CI): .92 (.88-.97), P < .001] than white patients. No differences between white and Asian or Native Hawaiian or Pacific Islander patients existed.

DISCUSSION

While black patients had the highest incidence of DVT and PE, they had higher administration rates and earlier initiation of VTE prophylaxis. Further work can elucidate modifiable causes of these differences.

A case study of the 1115 waiver using population health informatics to address disparities

As participants in the California Medicaid 1115 waiver, the University of California San Diego Health (UCSDH) used population health informatics tools to address health disparities. This case study describes a modern application of health informatics to improve data capture, describe health disparities through demographic stratification, and drive reliable care through electronic medical record-based registries. We provide a details in our successful approach using (1) standardized collection of race, ethnicity, language, sexual orientation, and gender identity data, (2) stratification of 8 quality measures by demographic profile, and (3) improved quality performance through registries for wellness, social determinants of health, and chronic disease. A strong population health platform paired with executive support, physician leadership, education and training, and workflow redesign can improve the representation of diversity and drive reliable processes for care delivery that improve health equity.

Examining Racial and Ethnic Differences in Nursing Home Quality

BACKGROUND

Identifying racial/ethnic differences in quality is central to identifying, monitoring, and reducing disparities. Although disparities across all individual nursing home residents and disparities associated with between-nursing home differences have been established, little is known about the degree to which quality of care varies by race//ethnicity within nursing homes. A study was conducted to measure within-facility differences for a range of publicly reported nursing home quality measures.

METHODS

Resident assessment data on approximately 15,000 nursing homes and approximately 3 million residents (2009) were used to assess eight commonly used and publicly reported long-stay quality measures: the proportion of residents with weight loss, with high-risk and low-risk pressure ulcers, with incontinence, with depressive symptoms, in restraints daily, and who experienced a urinary tract infection or functional decline. Each measure was stratified by resident race/ethnicity (non-Hispanic white, non-Hispanic black, and Hispanic), and within-facility differences were examined.

RESULTS

Small but significant differences in care on average were found, often in an unexpected direction; in many cases, white residents were experiencing poorer outcomes than black and Hispanic residents in the same facility. However, a broad range of differences in care by race/ethnicity within nursing homes was also found.

CONCLUSION

The results suggest that care is delivered equally across all racial/ethnic groups in the same nursing home, on average. The results support the call for publicly reporting stratified nursing home quality measures and suggest that nursing home providers should attempt to identify racial/ethnic within-facility differences in care.

Eliminating Health Care Disparities With Mandatory Clinical Decision Support: The Venous Thromboembolism (VTE) Example

BACKGROUND

All hospitalized patients should be assessed for venous thromboembolism (VTE) risk factors and prescribed appropriate prophylaxis. To improve best-practice VTE prophylaxis prescription for all hospitalized patients, we implemented a mandatory computerized clinical decision support (CCDS) tool. The tool requires completion of checklists to evaluate VTE risk factors and contraindications to pharmacological prophylaxis, and then recommends the risk-appropriate VTE prophylaxis regimen.

OBJECTIVES

The objective of the study was to examine the effect of a quality improvement intervention on race-based and sex-based health care disparities across 2 distinct clinical services.

RESEARCH DESIGN

This was a retrospective cohort study of a quality improvement intervention.

SUBJECTS

The study included 1942 hospitalized medical patients and 1599 hospitalized adult trauma patients.

MEASURES

In this study, the proportion of patients prescribed risk-appropriate, best-practice VTE prophylaxis was evaluated.

RESULTS

Racial disparities existed in prescription of best-practice VTE prophylaxis in the preimplementation period between black and white patients on both the trauma (70.1% vs. 56.6%, P=0.025) and medicine (69.5% vs. 61.7%, P=0.015) services. After implementation of the CCDS tool, compliance improved for all patients, and disparities in best-practice prophylaxis prescription between black and white patients were eliminated on both services: trauma (84.5% vs. 85.5%, P=0.99) and medicine (91.8% vs. 88.0%, P=0.082). Similar findings were noted for sex disparities in the trauma cohort.

CONCLUSIONS

Despite the fact that risk-appropriate prophylaxis should be prescribed equally to all hospitalized patients regardless of race and sex, practice varied widely before our quality improvement intervention. Our CCDS tool eliminated racial disparities in VTE prophylaxis prescription across 2 distinct clinical services. Health information technology approaches to care standardization are effective to eliminate health care disparities.

Minority trauma patients tend to cluster at trauma centers with worse-than-expected mortality: can this phenomenon help explain racial disparities in trauma outcomes?

OBJECTIVES

To determine whether minority trauma patients are more commonly treated at trauma centers (TCs) with worse observed-to-expected (O/E) survival.

BACKGROUND

Racial disparities in survival after traumatic injury have been described. However, the mechanisms that lead to these inequities are not well understood.

METHODS

Analysis of level I/II TCs included in the National Trauma Data Bank 2007-2010. White, Black, and Hispanic patients 16 years or older sustaining blunt/penetrating injuries with an Injury Severity Score of 9 or more were included. TCs with 50% or more Hispanic or Black patients were classified as predominantly minority TCs. Multivariate logistic regression adjusting for several patient/injury characteristics was used to predict the expected number of deaths for each TC. O/E mortality ratios were then generated and used to rank individual TCs as low (O/E <1), intermediate, or high mortality (O/E >1).

RESULTS

A total of 556,720 patients from 181 TCs were analyzed; 86 TCs (48%) were classified as low mortality, 6 (3%) intermediate, and 89 (49%) as high mortality. More of the predominantly minority TCs [(82% (22/27) vs 44% (67/154)] were classified as high mortality (P < 0.001). Approximately 64% of Black patients (55,673/87,575) were treated at high-mortality TCs compared with 54% Hispanics (32,677/60,761) and 41% Whites (165,494/408,384) (P < 0.001).

CONCLUSIONS

Minority trauma patients are clustered at hospitals with significantly higher-than-expected mortality. Black and Hispanic patients treated at low-mortality hospitals have a significantly lower odds of death than similar patients treated at high-mortality hospitals. Differences in TC outcomes and quality of care may partially explain trauma outcomes disparities.

Disparities in mortality after blunt injury: does insurance type matter?

BACKGROUND

Insurance-related outcomes disparities are well-known, but associations between distinct insurance types and trauma outcomes remain unclear. Prior studies have generally merged various insurance types into broad groups. The purpose of this study is to determine the association of specific insurance types with mortality after blunt injury.

MATERIALS AND METHODS

Cases of blunt injury among adults aged 18-64 y with an injury severity score >9 were identified using the 2007-2009 National Trauma Data Bank. Crude mortality was calculated for 10 insurance types. Multivariable logistic regression was employed to determine difference in odds of death between insurance types, controlling for injury severity score, Glasgow Coma Scale motor, mechanism of injury, sex, race, and hypotension. Clustering was used to account for possible inter-facility variations.

RESULTS

A total of 312,312 cases met inclusion criteria. Crude mortality ranged from 3.2 to 6.0% by insurance type. Private Insurance, Blue Cross Blue Shield, Workers Compensation, and Medicaid yielded the lowest relative odds of death, while Not Billed and Self Pay yielded the highest. Compared with Private Insurance, odds of death were higher for No Fault (OR 1.25, P = 0.022), Not Billed (OR 1.77, P < 0.001), and Self Pay (OR 1.77, P < 0.001). Odds of death were higher for Medicare (OR 1.52, P < 0.001) and Other Government (OR 1.35, P = 0.049), while odds of death were lower for Medicaid (OR 0.89, P = 0.015).

CONCLUSIONS

Significant differences in mortality after blunt injury were seen between insurance types, even among those commonly grouped in other studies. Policymakers may use this information to implement programs to monitor and reduce insurance-related disparities.