Health care organizations' use of race/ethnicity data to address quality disparities

Measuring Racial Inequities In The Quality Of Care Across Oncology Practices In The US

Racial inequities in clinical performance diminish overall health care system performance; however, quality assessments have rarely incorporated reliable measures of racial inequities. We studied care for more than one million Medicare fee-for-service beneficiaries with cancer to assess the feasibility of calculating reliable practice-level measures of racial inequities in chemotherapy-associated emergency department (ED) visits and hospitalizations. Specifically, we used hierarchical models to estimate adjusted practice-level Black-White differences in these events and described differences across practices. We calculated reliable inequity measures for 426 and 322 practices, depending on the measure. These practices reflected fewer than 10 percent of practices treating Medicare beneficiaries with chemotherapy, but they treated approximately half of all White and Black Medicare beneficiaries receiving chemotherapy and two-thirds of Black Medicare beneficiaries receiving chemotherapy. Black patients experienced chemotherapy-associated ED visits and hospitalizations at higher rates (54.2 percent and 35.8 percent, respectively) than White patients (45.7 percent and 31.9 percent, respectively). The median within-practice Black-White difference was 8.1 percentage points for chemotherapy-associated ED visits and 2.7 percentage points for chemotherapy-associated hospitalizations. Additional research is needed to identify other reliable measures of racial inequities in health care quality, measure care inequities in smaller practices, and assess whether providing practice-level feedback could improve equity.

Simplified data science approach to extract social and behavioural determinants: a retrospective chart review

OBJECTIVES

We aim to extract a subset of social factors from clinical notes using common text classification methods.

DESIGN

Retrospective chart review.

SETTING

We collaborated with a local level I trauma hospital located in an underserved area that has a housing unstable patient population of about 6.5% and extracted text notes related to various social determinants for acute care patients.

PARTICIPANTS

Notes were retrospectively extracted from 43 798 acute care patients.

METHODS

We solely use open source Python packages to test simple text classification methods that can potentially be easily generalisable and implemented. We extracted social history text from various sources, such as admission and emergency department notes, over a 5-year timeframe and performed manual chart reviews to ensure data quality. We manually labelled the sentiment of the notes, treating each text entry independently. Four different models with two different feature selection methods (bag of words and bigrams) were used to classify and predict housing stability, tobacco use and alcohol use status for the extracted clinical text.

RESULTS

From our analysis, we found overall positive results and metrics in applying open-source classification techniques; the accuracy scores were 91.2%, 84.7%, 82.8% for housing stability, tobacco use and alcohol use, respectively. There were many limitations in our analysis including social factors not present due to patient condition, multiple copy-forward entries and shorthand. Additionally, it was difficult to translate usage degrees for tobacco and alcohol use. However, when compared with structured data sources, our classification approach on unstructured notes yielded more results for housing and alcohol use; tobacco use proved less fruitful for unstructured notes.

Prenatal and Postpartum Care Disparities in a Large Medicaid Program

Objectives Pennsylvania's maternal mortality, infant mortality, and preterm birth rates rank 24th, 35th, and 25th in the country, and are higher among racial and ethnic minorities. Provision of prenatal and postpartum care represents one way to improve these outcomes. We assessed the extent of disparities in the provision and timeliness of prenatal and postpartum care for women enrolled in Pennsylvania Medicaid. Methods We performed a cross-sectional evaluation of representative samples of women who delivered live births from November 2011 to 2015. Our outcomes were three binary effectiveness-of-care measures: prenatal care timeliness, frequency of prenatal care, and postpartum care timeliness. Pennsylvania's Managed Care Organizations (MCOs) were required to submit these outcomes to the state after reviewing administrative and medical records through a standardized, validated sampling process. We assessed for differences in outcomes by race, ethnicity, region, year, and MCO using logistic regression. Results We analyzed data for 12,228 women who were 49% White, 31% Black/African American, 4% Asian, and 15% Hispanic/Latina. Compared to Black/African American women, white and Asian women had higher odds of prenatal and postpartum care. Hispanic/Latina women had higher frequency of prenatal care than non-Hispanic women. Pennsylvania's Southeast had lower prenatal care and Northwest had lower postpartum care than other regions. Prenatal care significantly decreased in 2014 and increased in 2015. We observed differences between MCOs, and as MCO performance diminished, racial disparities within each plan widened. We explored hypotheses for observed disparities in secondary analyses. Conclusions for Practice Our data demonstrate that interventions should address disparities by race, region, and MCO in equity-promoting measures.

What Influences Participation in QI? A Randomized Trial of Addiction Treatment Organizations

Healthcare providers have increased the use of quality improvement (QI) techniques, but organizational variables that affect QI uptake and implementation warrant further exploration. This study investigates organizational characteristics associated with clinics that enroll and participate over time in QI. The Network for the Improvement of Addiction Treatment (NIATx) conducted a large cluster-randomized trial of outpatient addiction treatment clinics, called NIATx 200, which randomized clinics to one of four QI implementation strategies: (1) interest circle calls, (2) coaching, (3) learning sessions, and (4) the combination of all three components. Data on organizational culture and structure were collected before, after randomization, and during the 18-month intervention. Using univariate descriptive analyses and regression techniques, the study identified two significant differences between clinics that enrolled in the QI study (n = 201) versus those that did not (n = 447). Larger programs were more likely to enroll and clinics serving more African Americans were less likely to enroll. Once enrolled, higher rates of QI participation were associated with clinics' not having a hospital affiliation, being privately owned, and having staff who perceived management support for QI. The study discusses lessons for the field and future research needs.

Health policy, disparities, and the kidney

Kidney care and public policy have been linked for 40 years, with various consequences to outcomes. The 1972 Social Security Amendment, Section 2991, expanded Medicare coverage for all modalities of dialysis and transplant services and non-kidney-related care to those with end-stage renal disease (ESRD) regardless of age. This first and only disease-specific entitlement program was a step toward decreasing disparities in access to care. Despite this, disparities in kidney disease outcomes continue as they are based on many factors. Over the last 4 decades, policies have been enacted to understand and improve the delivery of ESRD care. More recent policies include novel shared-risk payment models to ensure quality and decrease costs. This article discusses the impact or potential impact of selected policies on health disparities in advanced chronic kidney disease and ESRD. Although it is too early to know the consequences of newer policies (Affordable Care Act, ESRD Prospective Payment System, Quality Incentive Program, Accountable Care Organizations), their goal of improving access to timely patient-centered appropriate affordable and quality care should lessen the disparity gap. The Nephrology community must leverage this dynamic state of care-delivery model redesign to decrease kidney-related health disparities.

The role of data in health care disparities in Medicaid managed care

BACKGROUND

The Affordable Care Act includes provisions to standardize the collection of data on health care quality that can be used to measure disparities. We conducted a qualitative study among leaders of Medicaid managed care plans, that currently have access to standardized quality data stratified by race and ethnicity, to learn how they use it to address disparities.

METHODS

We conducted semi-structured interviews with 21 health plan leaders across 9 Medicaid managed care plans in California. We used purposive sampling to maximize heterogeneity in geography and plan type (e.g., non-profit, commercial). We performed a thematic analysis based on iterative coding by two investigators.

RESULTS

We found 4 major themes. Improving overall quality was tightly linked to a focus on standardized metrics that are integral to meeting regulatory or financial incentives. However, reducing disparities was not driven by standardized data, but by a mix of factors. Data were frequently only examined by race and ethnicity when overall performance was low. Disparities were attributed to either individual choices or cultural and linguistic factors, with plans focusing interventions on recently immigrated groups.

CONCLUSIONS

While plans' efforts to address overall quality were often informed by standardized data, actions to reduce disparities were not, at least partly because there were few regulatory or financial incentives driving meaningful use of data on disparities. Standardized data, as envisaged by the Affordable Care Act, could become more useful for addressing disparities if they are combined with policies and regulations that promote health care equity.

Improving quality and reducing inequities: a challenge in achieving best care

The health care quality chasm is better described as a gulf for certain segments of the population, such as racial and ethnic minority groups, given the gap between actual care received and ideal or best care quality. The landmark Institute of Medicine report Crossing the Quality Chasm: A New Health System for the 21st Century challenges all health care organizations to pursue six major aims of health care improvement: safety, timeliness, effectiveness, efficiency, equity, and patient-centeredness. "Equity" aims to ensure that quality care is available to all and that the quality of care provided does not differ by race, ethnicity, or other personal characteristics unrelated to a patient's reason for seeking care. Baylor Health Care System is in the unique position of being able to examine the current state of equity in a typical health care delivery system and to lead the way in health equity research. Its organizational vision, "culture of quality," and involved leadership bode well for achieving equitable best care. However, inequities in access, use, and outcomes of health care must be scrutinized; the moral, ethical, and economic issues they raise and the critical injustice they create must be remedied if this goal is to be achieved. Eliminating any observed inequities in health care must be synergistically integrated with quality improvement. Quality performance indicators currently collected and evaluated indicate that Baylor Health Care System often performs better than the national average. However, there are significant variations in care by age, gender, race/ethnicity, and socioeconomic status that indicate the many remaining challenges in achieving "best care" for all.

Leveraging quality improvement to achieve equity in health care

INEQUALITY IN QUALITY: Disparities in health care and quality for racial, ethnic, linguistic, and other disadvantaged groups are widespread and persistent. Health care organizations are engaged in efforts to improve quality in general but often make little attempt to address disparities.

STANDARD VERSUS CULTURALLY COMPETENT QUALITY IMPROVEMENT (QI)

Most QI interventions are broadly targeted to the general population-a "one-size-fits-all" approach. These standard QI efforts may preferentially improve quality for more advantaged patients and maintain or even worsen existing disparities. Culturally competent QI interventions place specific emphasis on addressing the unique needs of minority groups and the root causes of disparities.

HOW QI CAN REDUCE DISPARITIES

QI interventions can reduce disparities in at least three ways: (1) In some cases, standard QI interventions can improve quality more for those with the lowest quality, but this is unreliable; (2) group-targeted QI interventions can reduce disparities by preferentially targeting disparity groups; and (3) culturally competent QI interventions, by tailoring care to cultural and linguistic barriers that cause disparities, can improve care for everyone but especially for disparity groups.

GUIDELINES FOR CULTURALLY COMPETENT QI

A culturally competent approach to QI should (1) identify disparities and use disparities data to guide and monitor interventions, (2) address barriers unique to specific disparity groups, and (3) address barriers common to many disparity group.

CONCLUSIONS

To achieve equity in health care, hospitals and other health care organizations should move toward culturally competent QI and disparities-targeted QI interventions to achieve equity in health care, a key pillar of quality.

How health care organizations are using data on patients' race and ethnicity to improve quality of care

CONTEXT

Racial and ethnic disparities in the quality of health care are well documented in the U.S. health care system. Reducing these disparities requires action by health care organizations. Collecting accurate data from patients about their race and ethnicity is an essential first step for health care organizations to take such action, but these data are not systematically collected and used for quality improvement purposes in the United States. This study explores the challenges encountered by health care organizations that attempted to collect and use these data to reduce disparities.

METHODS

Purposive sampling was used to identify eight health care organizations that collected race and ethnicity data to measure and reduce disparities in the quality and outcomes of health care. Staff, including senior managers and data analysts, were interviewed at each site, using a semi-structured interview format about the following themes: the challenges of collecting and collating accurate data from patients, how organizations defined a disparity and analyzed data, and the impact and uses of their findings.

FINDINGS

To collect accurate self-reported data on race and ethnicity from patients, most organizations had upgraded or modified their IT systems to capture data and trained staff to collect and input these data from patients. By stratifying nationally validated indicators of quality for hospitals and ambulatory care by race and ethnicity, most organizations had then used these data to identify disparities in the quality of care. In this process, organizations were taking different approaches to defining and measuring disparities. Through these various methods, all organizations had found some disparities, and some had invested in interventions designed to address them, such as extra staff, extended hours, or services in new locations.

CONCLUSION

If policymakers wish to hold health care organizations accountable for disparities in the quality of the care they deliver, common standards will be needed for organizations' data measurement, analysis, and use to guide systematic analysis and robust investment in potential solutions to reduce and eliminate disparities.

Colonoscopy screening rates among patients of colonoscopy-trained African American primary care physicians

BACKGROUND

When performed competently, colonoscopy screening can reduce colorectal cancer rates, especially in high-risk groups such as African Americans. Training primary care physicians (PCPs) to perform colonoscopy may improve screening rates among underserved high-risk populations.

METHODS

The authors compared colonoscopy screening rates and computed adjusted odds ratios for colonoscopy-eligible patients of trained African American PCPs (study group) versus untrained PCPs (comparison group), before and after initiating colonoscopy training. All colonoscopies were performed at a licensed ambulatory surgery center with specialist standby support. Retrospective chart review was conducted on 200 consecutive, established outpatients aged ≥50 years at each of 12 PCP offices (7 trained African American PCPs and 5 untrained PCPs, practicing in the same geographic region). There were a total of 1244 study group and 923 comparison group patients.

RESULTS

Post-training colonoscopy rates in both groups were higher than pretraining rates: 48.3% versus 9.3% in the study group, 29.6% versus 9.8% in the comparison group (both P < .001). African American patients in the study group showed a >5-fold increase (8.9% pretraining vs 52.8% post-training), with no change among whites (18.2% vs 25.0%). Corresponding pretraining and post-training rates among comparison patients were 10.4%% and 38.7%, respectively, among African Americans (P < .001), and 13.3% versus 13.2%, respectively, among whites. After adjusting for demographics, duration since becoming the PCP's patient, and health insurance, the study group had a 66% higher likelihood of colonoscopy in the post-training period (odds ratio, 1.66; 95% confidence interval, 1.30-2.13), and African Americans had a 5-fold increased likelihood of colonoscopy relative to whites.

CONCLUSIONS

Colonoscopy-trained PCPs may help reduce colorectal cancer disparities.

A simulation model approach to analysis of the business case for eliminating health care disparities

BACKGROUND

Purchasers can play an important role in eliminating racial and ethnic disparities in health care. A need exists to develop a compelling "business case" from the employer perspective to put, and keep, the issue of racial/ethnic disparities in health care on the quality improvement agenda for health plans and providers.

METHODS

To illustrate a method for calculating an employer business case for disparity reduction and to compare the business case in two clinical areas, we conducted analyses of the direct (medical care costs paid by employers) and indirect (absenteeism, productivity) effects of eliminating known racial/ethnic disparities in mammography screening and appropriate medication use for patients with asthma. We used Markov simulation models to estimate the consequences, for defined populations of African-American employees or health plan members, of a 10% increase in HEDIS mammography rates or a 10% increase in appropriate medication use among either adults or children/adolescents with asthma.

RESULTS

The savings per employed African-American woman aged 50-65 associated with a 10% increase in HEDIS mammography rate, from direct medical expenses and indirect costs (absenteeism, productivity) combined, was $50. The findings for asthma were more favorable from an employer point of view at approximately $1,660 per person if raising medication adherence rates in African-American employees or dependents by 10%.

CONCLUSIONS

For the employer business case, both clinical scenarios modeled showed positive results. There is a greater potential financial gain related to eliminating a disparity in asthma medications than there is for eliminating a disparity in mammography rates.

Engagement of health plans and employers in addressing racial and ethnic disparities in health care

Disparities in access to and quality of health care along racial and ethnic lines are an important national problem. Health care purchasers and payers have a potentially important role to play in alleviating this problem. Using national surveys of 609 employers and 252 health plans with HMO products in 41 U.S. markets, we examined awareness of racial and ethnic disparities in health care access and quality, perceptions of employer and health plan role in addressing disparities, and reported efforts to measure and reduce disparities. Our findings suggest that most health plans and many employers are aware of the existence of substantial disparities and that health plans, but not employers, have taken steps to examine and influence patterns of care by race and ethnicity among their members.

Racial disparities in access to long-term care: the illusive pursuit of equity

While nursing homes were insulated from civil-rights enforcement at the time of the implementation of the Medicare program and lagged behind other parts of the health sector in providing comparable access to minorities, they are the only providers for which current reporting requirements make it possible to fully assess racial disparities in use and quality of care. We find that African Americans' use of nursing homes in 2000 in the United States was 14 percent higher than Caucasians' use. The largest relative African American use of nursing homes in 2000 took place in the South and West. Average nursing-home case-mix acuity for African Americans and Caucasians were essentially identical, suggesting that shifts in payment incentives have eliminated the selective admission of easy-care private-pay (predominantly Caucasian) patients and helped fuel the growth of private pay home care and assisted living for this segment of the population. While these shifts in incentives helped increase the use of nursing homes by African Americans, a high degree of segregation and disparity in the quality of the nursing homes used by African Americans persists. Parity in use is an illusive benchmark for measuring progress in assuring equity in treatment.

Reducing disparities downstream: prospects and challenges

Addressing upstream or fundamental causes (such as poverty, limited education, and compromised healthcare access) is essential to reduce healthcare disparities. But such approaches are not sufficient, and downstream interventions, addressing the consequences of those fundamental causes within the context of any existing health system, are also necessary. We present a definition of healthcare disparities and two key principles (that healthcare is a social good and disparities in outcomes are a quality problem) that together provide a framework for addressing disparities downstream. Adapting the chronic care model, we examine a hierarchy of three domains for interventions (health system, provider-patient interactions, and clinical decision making) to reduce disparities downstream and discuss challenges to implementing the necessary changes.

Reducing racial, ethnic, and socioeconomic disparities in health care: opportunities in national health reform

Policy often focuses on reducing health care disparities through interventions at the patient and provider level. While unquestionably important, system-wide reforms to reduce uninsurance, improve geographic availability of services, increase workforce diversity, and promote clinical best practices are essential for progress in reducing disparities.

Pay for performance, public reporting, and racial disparities in health care: how are programs being designed?

Pay-for-performance and public reporting programs may have a neutral, narrowing, or widening effect on racial disparities in health care. The authors begin this article by suggesting that certain characteristics of these programs may affect disparities. They then present results from a systematic review of the literature on the effects of performance incentive programs on racial disparities in health care. The review revealed that only one empirical study provided data on this issue: It showed that a major public reporting program increased disparities in coronary artery bypass graft rates. The authors then present the results of interviews with leaders of 15 major performance incentive programs in the United States. The interviews indicated that current programs are not designed to reduce disparities and often lack characteristics that may be important in reducing disparities. The article concludes with program leaders' recommendations on how performance incentive programs could be designed to reduce disparities.

The double burden on safety net providers: Placing health disparities in the context of the privatization of health care in the US

The US Institute of Medicine's (IOM) influential 2003 report has focused attention on disparities in treatment outcomes and health status for American minorities, zeroing in on the role of unconscious bias in the unequal clinical disposition of minority patients. In keeping with the IOM's focus, current examinations of health disparities in the US tend to explore bias in clinical decision-making to the neglect of the political economic trends that buffet health care safety net sites and create the need for financial shortcuts. This paper recontextualizes the study of health disparities in the US by placing it against the backdrop of private sector trends emphasizing fiscal austerity and increased workforce productivity in health care. The social science literature on workers in human service bureaucracies, only recently applied to health care workers, suggests that higher demands for system "accountability" and worker "efficiency" may encourage providers to take shortcuts by treating individuals as mass categories. This ethnography of a Latino mental health clinic in the Northwestern USA shows that new private-sector measures of "productivity" take a toll on both the Latina clinicians whose invisible work subsidizes the system as well as on particular categories of patients--the uninsured and immigrants with serious psychosocial issues. While clinicians attempt to buffer the impacts of such reforms on patients, they also resort to means to increase their productivity such as firing repeated no-show patients and denial of care to the uninsured. This study is relevant for the health care of the poor in all health care systems considering restructuring along managerial principles to increase system 'efficiencies.'

Addressing racial and ethnic disparities in health care: using federal data to support local programs to eliminate disparities

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.

Use of geocoding and surname analysis to estimate race and ethnicity

OBJECTIVE

To review two indirect methods, geocoding and surname analysis, for estimating race/ethnicity as a means for health plans to assess disparities in care.

STUDY DESIGN

Review of published articles and unpublished data on the use of geocoding and surname analyses.

PRINCIPAL FINDINGS

Few published studies have evaluated use of geocoding to estimate racial and ethnic characteristics of a patient population or to assess disparities in health care. Three of four studies showed similar estimates of the proportion of blacks and one showed nearly identical estimates of racial disparities, regardless of whether indirect or more direct measures (e.g., death certificate or CMS data) were used. However, accuracy depended on racial segregation levels in the population and region assessed and geocoding was unreliable for identifying Hispanics and Asians/Pacific Islanders. Similarly, several studies suggest surname analyses produces reasonable estimates of whether an enrollee is Hispanic or Asian/Pacific Islander and can identify disparities in care. However, accuracy depends on the concentrations of Asians or Hispanics in areas assessed. It is less accurate for women and more acculturated and higher SES persons due intermarriage, name changes, and adoption. Surname analysis is not accurate for identifying African Americans. Recent unpublished analyses suggest plans can successfully use a combined geocoding/surname analyses approach to identify disparities in care in most regions. Refinements based on Bayesian methods may make geocoding/surname analyses appropriate for use in areas where the accuracy is currently poor, but validation of these preliminary results is needed.

CONCLUSIONS

Geocoding and surname analysis show promise for estimating racial/ethnic health plan composition of enrollees when direct data on major racial and ethnic groups are lacking. These data can be used to assess disparities in care, pending availability of self-reported race/ethnicity data.

Evidence into policy and practice? Measuring the progress of U.S. and U.K. policies to tackle disparities and inequalities in U.S. and U.K. health and health care

Health policy in both the United States and the United Kingdom has recently shifted toward a much greater concern with disparities and inequalities in health and health care. As evidence for these disparities and inequalities mounts, the different approaches in each country present specific challenges for policy and practice. These differences are most apparent in the mechanisms by which the progress of such policies is measured. This article compares the United States' and United Kingdom's strategies to gauge the challenges for policymakers in order to inform policy and practice. A cross-national comparison of selected measurement mechanisms identifies lessons for policy and practice in both countries.