Health care quality & health disparities Flashcards
Jean-Jacques, Persell, Hasnain-Wynia, Thompson, & Baker. (2011). The implications of using adjusted versus unadjusted methods to measure health care disparities at the practice level.
Gist: Disparities have been defined using 3 main conceptual models: (1) difference in health or health care between groups regardless of cause; (2) residual difference attributed to characteristic of interest; (3) differences considered to be result of legitimate reasons & differences considered to be result of unjust or illegitimate reasons. The authors focus on the first 2 definitions to look at whether the pattern of disparities remains the same whether other factors are controlled or not.
Race: Racial differences for 9/18 measures in the adjusted & for 8 of the measures blacks had higher deficits than whites. When adjusted, only 4 measures showed black-white differences.
Sex: Differences by sex & pattern same for unadjusted & adjusted analyses.
Neighborhood-level SES: 6 measures different based on neighborhood-level poverty in unadjusted & only 1 remained with a difference after adjustment. Similarly, 5 measures were different based on neighborhood-level education & only 2 remained different after adjusted analyses.
The current article doesn’t answer how disparities should be defined but does try to tease apart disparity for a particular characteristic separate from other covarying factors. Most research uses adjusted methods, but the authors make the case that with the wider use of EHRs, this is also possible to do in clinical setting.
Johnson, Roter, Powe, & Cooper. (2013). Patient race/ethnicity and quality of patient physician communication during medical visits.
Gist: examined association between patient race/ethnicity & patient-physician communication during medical visits. Found that communication differs among black vs white patients. Physicians were more verbally dominant & engaged in less patient-centered communication with black patients than white patients. Black patients & their physicians also had lower levels of positive affect than white patients & their physicians. Interventions need to increase physicians’ patient-centeredness & awareness of affective cues with black patients.
van Ryn & Burke. (2013). The effect of patient race and socioeconomic status on physicians’ perceptions of patients.
Gist: Physicians’ perceptions of patients were influenced by patients’ sociodemographic characteristics. Physicians perceived blacks & members of low & middle SES groups more negatively on numerous dimensions than for whites & upper SES patients. Patient race was associated with physicians’ assessment of patient intelligence, feelings of affiliation toward patient, & beliefs about patient’s likelihood of risk behavior & adherence to medical advice. Patient SES was associated with physicians’ perceptions of patients’ personality, abilities, behavioral tendencies, & role demands.
Fremont et al. (2005). Use of geocoding in managed care settings to identify quality disparities.
Gist: There’s little research about disparities in managed care settings & few plans collect information about race/ethnicity and SES. The authors used Medicare+Choice plans and commercial plans. They proposed geocoding patients to the census block level & using neighborhood-level estimates of race/ethnicity & SES as indirect proxies for individual-level measurements. The plans contained measures of individual race/ethnicity, so they were able to compare the use of two estimates for validity. Six 2000 HEDIS measures were the health outcomes. There were racial/ethnic & SES disparities for most of the process measures for enrollees. Overall, geocoding offers managed care plans & other health care providers with an opportunity to look at disparities without having directly measured data. On several measures, both race/ethnicity & SES had independent effects on outcomes. Disparities were evident but of smaller magnitude for some outcomes for commercial enrollees.
van Ryn & Fu. (2003). Paved with good intentions: Do public health and human service providers contribute to racial/ethnic disparities in health?
Gist: Evidence of racial/ethnic disparities in receipt of healthcare, but potential contribution of provider behavior to disparities has been largely unexplored. Review of evidence regarding provider contributions to disparities & causal model representing integrated set of mechanisms. Different mechanisms include help-seeking behavior, class, culture, provider beliefs about help seeking, provider interpretation of information/symptoms, professional decision-making, provider interpersonal behavior, etc.
Kilbourne et al. (2006). Advancing health disparities research within the health care system: A conceptual framework.
Gist: Provide framework to guide future health disparities research in areas ranging from detecting differences in health & health care to understanding determinants. Key factors to understanding disparities were multilevel determinants of health disparities, including individual beliefs & preferences, effective patient-provider communication, & the organizational culture of the health care system. Need interventions that provide generalizable data on effectiveness & promote further engagement of communities, providers, & policymakers.
Lillie-Blanton, Maleque, & Miller. (2008). Reducing racial, ethnic, and socioeconomic disparities in health care: Opportunities in national health reform.
Gist: Ultimate design of a reformed system of healthcare must address both health status disparities & health care disparities. Health insurance coverage is patterned by race/ethnicity & income. Uninsurance affects disadvantaged populations through its impact on health care services available within communities (access to primary care & availability of specialized medical services for uninsured & insured). Low-income persons & minority members often share same set of providers (community health centers, public clinics, hospital outpatient & emergency departments). Health care access impacted by geographic availability of health services, diversity of the health care workforce, & best practice development & use.
Pastor & Morello-Frosch. (2014). Integrating public health and community development to tackle neighborhood distress and promote well-being.
Gist: Call for public health to reconnect to urban planning in ways that emphasize impact of place on health & address fundamental causes of poor health. Article reviews recent shifts in community development & examples of programs at intersection of community development, public health, & civic engagement.
Example: Sacramento, CA Building Healthy Communities program - promoted creation of community gardens & bike paths & redevelopment of brownfields
Example: San Francisco, CA housing revitalization initiative - transformed largest public housing site into mixed-income community providing existing residents with new housing, infrastructure, services, & amenities.
Nerenz. (2005). Health care organizations’ sue of race/ethnicity data to address quality disparities.
Gist: Having data on race/ethnicity is a basic first step toward using data to address disparities. There is evidence demonstrating that health care organizations can use data on patients’ race/ethnicity to identify disparities in quality of care & to organize QI projects to reduce or eliminate disparities.
Projects to improve quality that have reduced disparities: (1) hemodialysis - improve adequacy of dialysis anemia management, & nutritional status among pts receiving hemodialysis; used quality metrics, regular feedback of results to dialysis sites, & workshops/direct supervision for poorly performing facilities; (2) childhood immunization rates - saw low varicella immunization rates relative to other immunizations & characterized by disparity; initiative with mailings to network providers that included lists of children over due for immunizations, member newsletter articles (bilingual) about immunizations, low-literacy member education materials in 5 languages, & specific mailing to parents of children due for immunization.
Projects using data to improve care for minorities: (1) Medicaid managed care - HRSA sponsored 6-state demonstration project using HEDIS & CAHPS data; (2) community health centers - collaboratives organized among regional networks of CHCs to focus on chronic diseases.
Projects using data to improve quality but not necessarily address disparities: (1) primary care for inner-city children - target primary care practices in a reminder, recall, & outreach program to promote immunizations; (2) depression care - modest tailoring for minority patients to improve quality of care for patients with depression.
Betancourt, Green, Carrillo, & Park. (2005). Cultural competence and health care disparities: Key perspectives and trends.
Gist: The goal of cultural competence is to create a health care system that can deliver the highest-quality care to every patient regardless of race, ethnicity, culture, or language proficiency. Research has already shown that physician-patient communication is linked to patient satisfaction, medical adherence, & health outcomes. Cultural competence has meaning for managed care, academia, and government. It is an emerging field in health care and can impact multiple levels of care.
Eichner & Vladeck. (2005). Medicare as a catalyst for reducing health disparities.
Gist: Medicare is nation’s largest purchaser & regulator of health care, so is positioned to be a leader in reducing racial/ethnic health disparities. Example, it’s leverage was demonstrated in 1966 (year of Medicare’s inception) when hospitals desegregated as a condition for Medicare reimbursement. Medicare should focus its efforts in quality of care, payment approaches, data collection & usage, civil rights enforcement, cultural competency & language, & whether Medicare should attempt parity for health outcomes as well as health care.
Horton. (2006). The double burden on safety net providers: Placing health disparities in the context of privatization of health care in the US.
Gist: Keeping with IOM’s 2003 report’s focus, examinations of health disparities in US tend to neglect the political economic trends that buffet health care safety net sites & create need for financial shortcuts. Study of health disparities is placed against backdrop of private sector trends emphasizing fiscal austerity & increased workforce productivity in health care. Higher demands for system “accountability” and worker “efficiency” may encourage providers to take shortcuts by treating individuals as mass categories. New private-sector measures of “productivity” take a toll on both Latina clinicians whose invisible work subsidizes the system & particular categories of patients - the uninsured & immigrants with serious psychosocial issues. While clinicians attempt to buffer impacts of such reforms on patients, they also fire repeat no-show patients & deny care to the uninsured to increase productivity.
