Measuring Hospital Social Commitment Using Charity Care Data
Anthony Paul Andrews, Ph.D.
Governors State University
Differences in the measurement of hospital community benefit requirements posed a significant problem in terms of researching benefit issues relative to social welfare implications. First, the definition of community benefit is not a standard definition across states so community benefit data across hospitals in the same state may differ. While Illinois does have a definition of community benefit, data are collected for charity care, and appears to be more closely defined than that of community benefit data. Thus, using charity care data to say something about hospital social commitment is an area that has not been explored in the literature.
Charity Care data on 214 Illinois hospitals is used to measure hospital social commitment. Charity care is defined as payments which a provider does not expect to receive from patients or a third party. Charity care, as a measure of social welfare, is defined as the ratio of charity care to net revenue of hospitals and will be used to measure the gain or loss to welfare as deviations from some optimal charity care to net revenue ratio.
The methodology for obtaining an optimal charity to net revenue ratio is developed in the context of the Taguchi Loss Function (Taguchi, 2001), which is a parabolic representation that estimates loss when actual characteristics of a variable deviate from a target value (Drezner and Wesolowsky, 1999). The Taguchi Loss Function will be used to approximate social welfare loss or gain in the context of the deviations from the target measure (Dubey, 2007; Pakkala and Rahim, 1999). Loss to Social Welfare is defined in terms of the efficiency of a competitive outcome, or target ratio.
The Taguchi Loss Function methodology has been applied to a number of processes; for example, the real estate sector
(Kethley et al., 2002); selection of suppliers (Snow, 1993); and ranking employee performance (Roseland, 1989). This paper uses the methodology to rank hospital performance with respect to determining an optimal target charity care to net revenue ratio and to estimate the loss to social welfare as deviations from that target value for Illinois hospitals.
The data are from the 2008 Annual Hospital Questionnaire of Illinois hospitals, which is the most recent data on charity care. The hospital charity to net revenue ratio data are seen to provide an optimal data set in that the method:
- addresses the idea of mean shifting or mean drift in the Taguchi modeling process, since the data are cross section and not time series;
- the Taguchi Loss Function provides an empirical estimation of Loss, which will be used to characterize Loss to Society, and provides a better representation of the problem than simplistic loss of consumer surplus based on concentration ratios and Herfindahl-Hirschman indices; and
- the method allows analysis of various levels of societal loss in a revenue context for policy implications.
The paper is essentially, at this point in time, the development of the analytical model and a work in progress. What will be presented are stylized facts of the data, the target charity care to net revenue ratio, and the quadratic distribution of the sample, which models movement from the target value.
Reframing Latino Acculturation Models and Measurements for Public Health Inequities Research
Lisa Aponte-Soto, MHA
University of Illinois at Chicago firstname.lastname@example.org
The primary objective of this paper is to review and compare acculturation measures, constructs, and scales for use with diverse Latino samples in public health research.
Latinos comprise a significant population in the South Suburban Cook County area. Since the 1990s, upward mobility and gentrification of urban, poor Latino communities in the Chicago metropolitan area have contributed to a suburbanization or a reconcentration of Latinos in suburban Cook County, primarily individuals of Mexican and Puerto Rican descent.
The Latino health paradox maintains that individuals of Latin American heritage have more favorable life trajectories than European-Americans, regardless of the fact that Latinos are generally more likely to live below poverty, be underemployed, undereducated, and underinsured. However, the paradox has been challenged by the healthy migrant and salmon bias hypotheses, but predominantly by acculturation.
Extant research assessing the influence of acculturation on the health of Latino immigrants claims that Latinos incur decreasing health benefits with increasing levels of acculturation. Nonetheless, the evidence also suggests that the acculturative process may promote the adopting of healthy behaviors. Most health-related studies measuring acculturation narrowly observe language, nativity, and/or length of stay in the U.S. In addition, the majority of the Latino acculturation scales have been primarily validated with U.S.-born and foreign-born Mexican populations.
Traditional linear approaches may be insufficient for addressing the heterogeneity and distinct acculturative patterns across and within Latino subgroups. For example, Puerto Ricans and Mexicans in the U.S. represent the most economically disadvantaged Latino subgroups; however, Puerto Ricans have poorer health outcomes, which contradict the healthy migrant paradox. Thus, it is important to assess the appropriateness of extant acculturation measures for use across Latino subgroups.
A systematic review of acculturation models for Latino health research was conducted through a Medline and Google Scholar search to comparatively assess the utility of existing measurements and scales among Puerto Rican and Mexican samples.
Most researchers adopt linear models or use proxy measures to assess the impact of acculturation across Latino samples, use Euro-American culture as a standard for assimilation, and/or fail to account for health behavior and health outcomes.
In comparison to multi-dimensional frameworks, this approach is inadequate because it does not capture heterogeneity among Latinos, and the dynamic process of acculturation. In addition, the overemphasis on language proficiency as a predictor of acculturation discounts the influence of biculturalism, which is more pronounced among Puerto Ricans than their Mexican counterparts.
Understanding that Puerto Ricans have a unique health experience from Mexican Americans that does not translate to an epidemiologic paradox, it is important to have acculturation measures that have been validated with diverse Latino samples and tailored to specific Latino subgroups with input from the community under study.
Future directions for measuring acculturation across Latino samples to inform public health research and protective behavioral health interventions also need to be multi-dimensional and account for unique socio-cultural factors that may influence health behavior.
HIV testing: Where Does the Evidence Show Success in Individuals Being Tested?
Nancy H. Burley, MA, BS • Philip Kletke, Ph.D. • Ralph Bell, Ph.D.
Governors State University email@example.com
The purpose of this study is to examine trends and correlates in the proportion of childbearing women who participate in HIV testing, with an emphasis on racial/ethnic disparities.
The number of HIV cases in the United States continues to increase with over a million people infected and many unaware of their status. To reduce the spread of HIV infection, the Centers for Disease Control and Prevention (CDC) recommends routine HIV screening for all adults. Women, in particular, are a vulnerable population and, if pregnant, may potentially transmit the HIV virus to their infants. Most states have initiated an “opt-in” or “opt-out” approach to prenatal testing. This study will examine data on the populations taking advantage of the testing options.
The data for this retrospective cohort study came from the Behavioral Risk Factor Surveillance System (BRFSS). The study examined data for years 1994, 1999, 2004, and 2009 to identify trends in the proportion of individuals ever tested for HIV with respect to sex, age, and race/ethnicity.
The analysis weighted the data to account for differential non-response and for the state-level stratified survey design. Chi-square tests were used to determine the significance of differences in the cross-sectional analysis. Logistic regression analyses were used to examine these relationships in a multivariate context.
Between 1994 and 2009, the proportion of adults tested for HIV increased from 38% to 42%. The increase in this proportion was especially large among women—from 35% to 46%. Most of the increase for women occurred between 1994 and 1999. The proportion of women of childbearing age who were tested for HIV rose from 43% in 1994 to 58% in 2009. The increase among African-American women was significant — from 41% to 80%.
In 2009, among women in childbearing ages, the likelihood of ever being tested was greater among older women (who, by definition, have had more time over which to be tested). The likelihood of having been tested was greater among African-American women and, to a lesser extent, among Hispanic women, than among white women. Women were more likely to have been tested if they were well-educated, lived in the central city of metropolitan areas (rather than a suburb or rural area). Women who had never been married were relatively unlikely to have been tested, whereas those who were divorced or separated or who were part of an unmarried couple were especially likely to have been tested. Women were more likely to have ever had an HIV test if they had ever not received health care due to cost, or if they were out-of-work, retired, or could not work.
Poor, minority women in urban areas are more likely than other women to be tested for HIV. Thus, in this particular instance, these women receive better quality of care than more affluent women in the majority population. The probable reason for this difference is that many poor, minority women in urban areas receive health care from free clinics and public hospitals, which may be more likely to adhere to the CDC recommendation that all adults be screened for HIV. It is appropriate that these women receive HIV testing since they are at greater risk for HIV infection.
Unevenness in Physician Medicaid Participation
Phillip R. Kletke, Ph.D. • Ralph Bell, Ph.D.
Governors State University firstname.lastname@example.org
Past research has shown that most physicians see few Medicaid patients or none at all, and a relatively small number of physicians devote much of their practice to Medicaid patients. The highly skewed distribution of physician Medicaid participation is an important policy concern because it limits Medicaid patients’ options for care and can potentially restrict their access to care. However, little is known about why unevenness in physician Medicaid participation is much greater in some communities than in others.
We used the Gini index to measure unevenness in physician Medicaid participation (i.e., the percent of practice revenues from Medicaid) for both primary care and nonprimary care physicians within each of the 60 study sites of the Community Tracking Study. We used OLS regression on the 60 study sites to determine how community characteristics were related to the level of unevenness. We then used linear hierarchical regression to examine the determinants of Medicaid participation across three levels of variables:
- characteristics of the entire community (population size, racial/ ethnic segregation);
- county-level market characteristics (physician-to-population ratio, percent of population below poverty, Medicaid-to-Medicare fee ratio, etc.); and
- characteristics of individual physicians (country of graduation, race/ethnicity, gender, etc.
We examined cross-level effects to analyze how the determinants of physicians’ Medicaid participations differ in communities that are larger, more competitive, and more highly differentiated.
We analyzed data from 10,659 patient care physicians in 60 study sites who responded to the 2000-2001 Physician Survey of the Community Tracking Study. There was an average of 178 physicians per study site. All but one site had at least 50 physician respondents; and all but 11 sites had at least 100. (We opted not to analyze the more recent 2004-2005 Physician Survey because its sample is only half as large.)
The average percent of physician revenues from Medicaid ranged 6% in West Palm Beach to 23% in Huntington, WV. The Gini index ranged from low values of .42 in Killeen, TX and .43 in the non-metropolitan area of eastern Maine to high values of .83 in New York City and .79 in San Francisco. A regression analysis of the 60 communities indicates that community population size and the physician-to-population ratio have a positive relationship with unevenness in Medicaid participation. Cross-level effects from the hierarchical linear analysis indicate that international medical graduates and minority physicians are especially likely to have greater Medicaid participation in large, highly competitive communities.
Our findings support a basic premise of Amos Hawley and other human ecologists: social systems become more differentiated as they increase in size and their environment becomes more competitive. In large, highly competitive healthcare systems, some physicians find their niche by serving Medicaid patients, and others by serving non-Medicaid patients. Some current efforts to reform the health care system are likely to have unintended consequences. Policies that increase competition among providers and/or reduce physician compensation are also likely to increase unevenness in physicians’ willingness to treat poor, disadvantaged patients — thereby decreasing access to care and furthering the development of a two-tiered health care system.
An Internet-Based Study of the Physical and Mental Health Quality of Life of LGBT Cancer Survivors
Alicia K. Matthews, Ph.D., University of Illinois at Chicago, email@example.com
Co-Authors: Anna Hotton, MPH, Howard Brown Health Center
Amy Johnson, MPH, Howard Brown Health Center
There are an estimated 10.8 million cancer survivors in the United States. Sexual orientation is not routinely collected as part of cancer surveillance efforts and as such, precise data on cancer outcomes among lesbian, gay, bisexual, and transgender (LGBT) persons is unavailable. Nevertheless, the extant literature suggests that sexual minority status may contribute to excess risk for the development of certain types of cancers and for poor outcomes associated with a cancer diagnosis and treatment.
The causes of these disparities are complex and likely influenced by the same types of factors that drive cancer disparity rates among racial and ethnic populations, including higher uninsured rates, poor access to culturally competent health care services, less participation in preventive health care, mistrust of the medical establishment, and discrimination in health care settings. Numerous studies have focused on the physical and mental health outcomes associated with a cancer diagnosis among individuals in the general population. However, much less is known about the impact of a cancer diagnosis among LGBT persons.
The purpose of this study was to investigate the factors influencing the mental and physical health quality of life (QOL) of LGBT individuals with a history of cancer diagnosis and treatment. Research examining the factors that influence QOL in LGBT cancer patient populations addresses a significant gap in the scientific literature and has important implications for research, treatment, and policy aimed at reducing cancer-related health disparities.
Data for this descriptive cross-sectional survey study were collected between 2006 and 2007 via a nationally advertised online survey. The survey was designed to examine the experiences and needs of LGBT cancer survivors. We used a modified version of the Short Form-12 (SF-12), a generic measure of QOL which has been widely used across a range of medical conditions. The SF-12 assesses QOL in two different domains: mental health (MCS-12) and physical health (PCS-12). We tested associations between covariates and mean MCS-12 and PCS-12 scores with t-tests and Pearson correlations. Data were analyzed using SAS version 9.2.
- Participants (N=187) were primarily female (70%), lesbian or gay (84%), and college educated (74%).
- The ethnic diversity of the sample was limited with 85% of the sample being white, 4% African American and 11% a heterogeneous group of other racial/ethnic groups.
- Mean age at diagnosis was 41.5 years (SD 12.2).
- Fifty-four percent of the sample had been diagnosed in the 5 years prior to the survey; 60% had early stage (0-2) cancer.
- Breast (43%) and gynecologic cancers (12%) were most commonly reported.
- Participants reported significant cancer and non-cancer related comorbidities, including cancer-related pain or fatigue (31%), hypertension (23%), high cholesterol (28%) and diabetes (10%).
- Indicators of risk of future cancers were present and included obesity (mean body mass index = 27.4), alcohol use (65.8% of participants), low adherence to recommended daily intake of fruits and vegetables (14%), lack of physical activity (52%), and tobacco use (15%).
- Barriers to physical and mental health care were also reported with 12% 12 (N = 22) of participants reporting perceived discrimination during their cancer care based on their sexual orientation and/or gender identity.
- Only 16% of respondents reported having access to LGBT-specific cancer supportive services; of those, only 25% had utilized these services.
- Overall, the mean PCS-12 score was 48.4 (SD 10.7); the mean MCS-12 score was 44.1 (SD 12.1).
- In general, survivors compared favorably with age- and sex-matched published norms for SF-12 MCS (44.1 vs. 45.3). However, SF-12 PCS data for our sample was somewhat lower than published norms (48.4 vs. 52.8).
- Younger age at diagnosis (<=42 years vs. >42 years) was associated with higher mean PCS-12 scores (p<0.01) but lower mean MCS-12 scores (p<0.05).
- Factors associated with lower PCS-12 scores were the presence of medical co-morbidities (p<0.01), overweight or obesity (p<0.01), current smoking (p<0.05), having experienced a recurrence (p<0.01), and currently in treatment (p<0.05). Lower MCS-12 scores were associated with current smoking (p<0.05), lower rating of the patient-provider relationship (r=0.33, p<0.01), having experienced discrimination in care (p<0.05), fear of cancer recurrence (r=-0.34, p<0.01), and lower levels of social (r=0.40, p<0.01) and emotional support (r=0.40, p<0.01).
These results are the first ever reported on a sample of cancer survivors from diverse sexual orientation backgrounds. Although the findings have implications for direct services and future research, limitations of the data should be noted. As with the majority of research on cancer survivorship research in the general population and research on LGBT persons in particular, the data are from a convenience sample of unknown representativeness.
Further, the data are cross-sectional and as such causality can not be inferred. Online data collection facilitates research on populations that are highly dispersed geographically. However, access to Internet research may be limited for those individuals from lower SES strata. The sample was limited in terms of the racial and ethnic diversity. As such, we were unable to determine the complex ways in which the intersections of race and sexual orientation may have influenced QOL outcomes. Finally, the lack of a heterosexual comparison group reduces our ability to make direct comparisons on survivorship experiences.
This study makes a significant contribution to the extant literature on cancer survivorship by focusing on the experiences and needs of LGBT cancer survivors. Findings suggest that several factors known to influence QOL outcomes in general populations of patients (e.g., age, medical co-morbidities, treatment status), also influence QOL among LGBT cancer survivors. However, factors unique to marginalized populations—low levels of support, experiences of discrimination, and poorer patient provider relationship — significantly impacted the mental health QOL experiences of LGBT survivors in our sample. Given study limitations, additional work is needed to further examine the impact that cancer diagnosis and treatment has on QOL in this highly underserved population.
Enhancing Nurse-Patient Communication Through “Ask Me 3”
Jean M. Mau, APN, Heart Failure Specialist, Advocate Lutheran General Hospital
The scripted Ask Me 3 questions assist nurses in providing clear, concise information, which impacts patient education.
Patient education is an essential component in nursing care. However, confidence and ability to educate patients have been identified as barriers for nurses in providing patient education. Past research has shown that Hispanics, African-Americans, and the frail elderly are at a greater risk for heart failure than other groups. In addition, communication with health care providers may be more problematic for patients who are: less educated, speak another language, and are of a different culture, race or ethnicity than their health care provider. Therefore, this study demonstrates that the use of Ask Me 3 is an important tool for improving health care for these vulnerable populations.
Ask Me 3, created by the Partnership for Clear Health Communication, was developed to promote clear communication between patient and provider. This program encourages patients to ask:
- What is my main problem?
- What do I need to do?
- Why is it important for me to do this?
The answers to these questions help patients assume a more active partnership in their healthcare. Nurses (n=31) received education on Ask Me 3. During the 3-month study period, nurses were encouraged to incorporate Ask Me 3 in all patient-nurse interactions. Pre- and post-implementation surveys were administered evaluating different aspects of nurse-patient interactions. Patients with a diagnosis of HF (n=126) were contacted post-discharge via the HF follow-up telephone call to evaluate patient education received.
A paired T test analysis demonstrated a statistically significant improvement in nurses perceived ability (p<.001) and confidence (p=.002) in providing patient education. 30-day readmission rates for HF decreased from 7.2% to less than 2.5% during the study period.
Nurses have an important role in helping patients understand and adhere to a therapeutic self-care plan. The Ask Me 3 format provides nurses with the confidence and ability to provide effective patient education. The decrease in readmissions for HF suggests an increase in the patient’s ability to understand the education and assume self-care post hospitalization. The significance seen in this study suggests that implementation of Ask Me 3 will foster increased collaboration between health care providers and patients, in chronic care management, thereby decreasing the need for re-hospitalization.
Disparities in the Quality of Care Provided by Home Health Care Agencies
Ricardo Teodoro • Phillip R. Kletke, PhD
Governors State University firstname.lastname@example.org
Home health care agencies (HHAs) provide health care assistance and support to patients in their own homes, making it possible for the disabled and elderly to remain at home rather than in institutionalized residential care or nursing care. This study looks for evidence of disparities in home health care in the state of Illinois. We examine whether quality of care varies with the population characteristics of the HHA service areas.
The data for our analysis came from the Home Health Compare database maintained by the Center for Medicare and Medicaid Services, which provides information on quality of care for over 10,000 Medicare-certified home health agencies throughout the U.S. The Home Health Compare data include:
- A provider file which lists the HHA name, ID, and location.
- A service area file which lists all the zip codes to which an HHA provides services.
- A quality measure file that provides scores for 12 quality measures for each HHA (if data are available) — e.g., the
percent of patients who get better at walking, the percent who get better at getting out of bed, etc.
We merged the HHA service area file with current estimates of the size and characteristics of the population residing in zip code areas. We then aggregated the population data for the HHA zip codes to estimate the total population of each HHA service area, the percent of this population in non-metropolitan areas, the average household income, and the composition with respect to race/ethnicity.
We limited the analysis to 512 HHAs that are licensed by the state of Illinois and that have service area populations mostly in Illinois. These HHAs were divided into four groups based on their service area populations: mostly in Cook County; mostly in the Chicago metro area outside Cook County; mostly in other Illinois metropolitan areas; and mostly non-metropolitan. We used ANOVA and linear regression analyses to determine how each quality measure varied among the 4 types of HHAs. Within metropolitan areas, we examine the relationship between racial/ethnic composition and average income with each HHA quality measure.
Non-metropolitan HHAs had lower scores than metropolitan HHAs on nine of the 12 quality measures. Within metropolitan areas, we generally found little evidence that racial/ethnic composition and average income in HHA service areas were significantly related to HHA quality. However, there were several exceptions. In Cook County, patients of HHAs that serve areas with large black populations did less well on two quality measures—these patients were more likely to be admitted to the hospital, and they were less likely to stay at home at the end of home health care.
In Illinois, HHAs with mostly nonmetropolitan service areas have lower quality scores than HHAs serving mostly metropolitan areas. Within metropolitan areas, several quality of care measures are relatively low for HHAs with large black populations. Further research is needed to better understand why these differences arise and how they affect home health care patients.
Does Masculinity Negatively Impact Outcomes in African American Men?
Terry Thompson, DHA • Rupert Evans, DHA • Steven Berkshire, Ph.D. • Catherine Slade, Ph.D.
Governors State Universitytemail@example.com
Within the healthcare community there exists a myriad of daunting challenges. Not since the Civil War has a topic sparked such polarization as the issues surrounding health care and the health status of America. While the equity curriculum deserves more prominent attention, this research study focuses on a smaller segment of the concern — men’s health. More specifically, the research hypothesis focused on whether masculinity (aggression) affected the self-reported health status of African American males (more specifically young affluent African American males) negatively. In addition, an attempt was made to determine if mistrust issues of African American males’ and their rejection of the health care delivery system supported the initial hypothesis.
The research study design was based on variables found in the Medical Panel Expenditure Survey (MEPS). MEPS consist of two major components: the Household Component (HC) and the Insurance Component (IC). The HC component was used in this research study. Within MEPS is documented respondent data on demographic and socioeconomic characteristics, health status, health conditions, medical service utilizations, access to health services, and provider patient relationships.
The research design was a cross-sectional multiple method quantitative analysis. The multiple methods approach in this study employed both ordinal regression and multiple regression models. When ordinal regression is employed to quantify results, the researcher assumes that the relationships between the independent variables and the logits are the same for all the logits. Ordinal regression is also used with ordinal dependent response variables, where the independents may be categorical factors or continuous covariates.
Multiple regressions were employed to account for (predict) the variance in a dependent interval, based on linear combinations of interval, dichotomous, or dummy independent variables. Multiple regressions can establish the relative predictive importance of the independent variables by comparing ß weighs.
The sampling frame for this study consists of 124 adult (i.e., 18 years of age and older) African American men, with an average age of 39.4 years. Study participants were recruited from a local barbershop, through the distribution of fliers, direct contact, and personal interactions (word of mouth). Recruitment of African American men in places where they frequent (e.g., barbershops) ensures a cross section of African American men from various socioeconomic, educational, and income backgrounds. Study respondents were surveyed using questions from the MEPS.
Past empirical research has shown that African American men suffer enormously higher morbidity and mortality rates, often lack a usual source of care, and visit a health provider less frequently than white males. The initial research hypothesis predicted that masculinity would have a negative impact on African American men’s health status, whereas, receiving patient-centered care would have a positive effect. While the effects of masculinity and patient-centered care on health status were seen, the results were not in the predicted directions. The research results supported another hypothesis: young affluent African American men, who had high masculine levels, self-reported better health status than
low masculine men.
The current research study investigated the effects of masculinity and whether it impacts health outcomes in African American men. The findings of this research study suggest that young affluent African American men who have high levels of masculinity (as defined by aggression) self-report better health status more positively than men of lower masculine levels.
The research proposed two explanations for the unexpected findings:
- High masculine men are normally healthier than low masculine men.
- High masculine men had a more pronounced usual source of care as a result of a higher socioeconomic status.
While masculinity had a positive affect in young affluent African American men in this study, we predict similar empirical results will emerge for a number of variables as researchers sample more diverse communities. In summary, while research studies focusing on health status determinants have been undertaken in the past, this study—with its unique study participants—offers exciting new possibilities for literature growth.
Funding for this conference was made possible in part by P20MD001816 from the National Center on Minority Health and Health Disparities. The views expressed in written conference materials or publications and by speakers and moderators do not necessarily reflect the official policies of the Department of Health and Human Services; nor does mention by trade names, commercial practices, or organizations imply endorsement by the U.S. Government.