Abstract
Objectives. The movement to publicly report data on provider quality to inform consumer choices is predicated on assumptions of equal access and knowledge. We examine the validity of this assumption by testing whether minority/less educated Medicare patients are at greater risk of being discharged from a hospital to the lowest-quality nursing homes in a geographic area.
Methods. We used the 2002 national Minimum Data Set to identify 62601 new Medicare admissions to nursing homes in 95 hospital service areas with at least 4 freestanding nursing homes and at least 50 African Americans aged 65 years or older with Medicare admissions to nursing homes.
Results. The probability of African Americans’ being admitted to nursing homes in the lowest-quality quartile in the area was greater (relative risk [RR]=1.26; 95% confidence interval [CI]=1.0, 8.45) in comparison with Whites. Individuals without a high-school degree were also more likely to be admitted to a low-quality nursing home (RR=1.22; 95% CI=1.0, 1.46).
Conclusions. African American and poorly educated patients enter the worst-quality nursing facilities. This finding raises concerns about the usefulness of the current public reporting model for certain consumers.
The publication of nursing home quality data is intended to promote quality competition.1 Advocates of publicly reporting quality measures for nursing homes argue that efforts to give elders and their families more information will promote better care, ultimately reducing disparities through the mechanism of expanded consumer choice. However, actual choice when it comes to nursing home selection is limited by demand—side factors such as local geography (proximity to family and neighborhood), supply-side factors such as the availability of skilled nursing home beds, and the reality that the majority of initial nursing home placement decisions are mediated by hospital discharge planners and the options they present. In 1997, 61% of nursing home residents were admitted from a hospital.2 Because hospital discharge planners act as patients’ agents in guiding nursing home choice, it is important to ascertain whether referrals are made equitably or if race and education play a role in perpetuating disparities in the quality of nursing home care.
Ethnic/racial disparities persist across the health care spectrum, and nursing home care is no exception.3 Nursing homes have been shown to be more racially segregated than hospitals.4 Because African Americans are known to use nursing homes less5,6 and later,7 than non-Hispanic Whites, and because segregated access to nursing home care is thought to be a major contributor to differential nursing home use,8,9 the association between a nursing home’s quality and its ethnic/racial composition is an important consideration.
The relevance of the phenomenon of nursing home segregation is readily seen in the increasing evidence that ethnic/racial minority residents are less likely to receive appropriate care. Past research has found that ethnic/racial minority residents are less likely than non-Hispanic Whites to receive medically appropriate pharmacological treatments in nursing homes10 and are less likely to receive physical therapy when admitted to nursing homes after hospitalization.11 Other studies suggest that African American and Hispanic elders are more likely to receive care in facilities with documented problems related to cleanliness and maintenance,12 and ethnic/racial minority elders nationwide are more likely to be treated in nursing homes that have a higher number of health deficiencies as determined by state regulators.13 Non-White race is also associated with a greater use of feeding tubes in nursing home residents.14 Minority elders are more likely to have significantly longer delays in discharge from hospitals.15
The role of education in guiding nursing home decisionmaking has emerged as an important area of interest as the consumer choice model of long-term care continues to develop.16 The competitive marketplace of health insurers, managed care plans, and nursing home providers poses special challenges to the less educated current cohort of older persons.17 Thus, differences in both education and race may play a role in perpetuating existing disparities in the quality of nursing home care.
There has been a renewed call for hospital management to take a more active role in reducing disparities in health care settings.18 Developing a system of evidence-based discharge planning that includes information about the quality of nursing home care may help reduce disparities at discharge. However, because the majority of choices are made locally, understanding the effect of new public reporting efforts requires baseline documentation of ongoing disparities within geographic areas—in this case hospital service areas (HSAs). Thus, we tested the hypothesis that racial and ethnic minorities and less educated individuals are more likely than non-Hispanic Whites and more educated patients to enter freestanding nursing homes that are in the worst quartile (in a given HSA) in terms of publicly available quality-inspection information in 2002. Because all new admissions were Medicare reimbursed, the impact of differential payment levels between Medicaid and private pay, which reflects patient wealth, was quite limited in our analysis.
METHODS
Data Sources
We used individual-level data from the Minimum Data Set (MDS) to identify nursing home admissions nationwide in 2002. The MDS has been in use in all US Medicare/Medicaid-certified nursing homes since 1991 for the purpose of documenting residents’ care needs and contains over 300 data elements including demographic variables and clinical items such as functional dependence and cognitive functioning. Since the introduction of Medicare prospective payment for skilled nursing facilities in 1998, the MDS is completed for all “short stay” Medicare admissions and is updated periodically thereafter depending on whether the resident continues to be eligible for Medicare services.
Organizational data on nursing homes were drawn from the Online Survey, Certification and Reporting database.19 These data contain structural and staffing information about the facility on the day of the inspection, as well as information about survey deficiencies (described later). Data on nursing home market characteristics were computed by aggregating the On-Line Survey and Certification File data to the HSA level on the basis of an HSA–zip code crosswalk file.20 HSAs were chosen as the market unit of analysis rather than the considerably larger hospital referral regions, which are used extensively to denote general medical care related to hospitals.21 The more localized HSAs are a better approximation of the choice parameters for nursing home selection. Nursing homes located in urban areas have markets that are a fraction of the size of the county in which they are located.22
Additional contextual information was obtained from the area resource file, a compilation of multiple databases used to characterize the population residing in a county.23 The county-level information from the area resource file was disaggregated to the HSA level when necessary for this analysis (i.e., HSAs were assigned the value from the larger county in which the HSA city was located).
Sample Selection
We limited our analyses to only those individuals aged 65 and older who had not been admitted to any nursing home within the 120 days before an observed nursing home admission in 2002, including admissions that may have occurred in 2001. This is the “postacute” Medicare patient population (with Medicare payer status identified on the MDS). Individuals returning to the nursing home after a short-term hospitalization or those transferred from another nursing home were thereby excluded. Patients discharged from hospitals to hospital-based nursing homes were also excluded from the final analysis because the discharge planning process for hospitals with an affiliated facility is likely to differ substantially because of the adjacency of the postacute setting and because discharge planners are presumably predisposed to refer patients to their own facility. However, the inclusion of hospital-based homes in an unreported robustness check did not alter the primary findings.
Our final analytic sample was limited to HSAs with at least 4 freestanding nursing homes to allow for variability in patient nursing home selection. In 2002, there were 968 HSAs with at least 1 acute care hospital and 4 freestanding nursing homes (mean = 10, SD= 10). We further limited the analysis to HSAs with at least 50 African American Medicare patients aged 65 and older admitted into all freestanding nursing homes in the calendar year to validly test for a statistically significant effect of race on low-quality nursing home selection. Only 95 HSAs had 50 or more African American Medicare nursing home admissions in 2002. We observed 62 601 unique Medicare admissions to free-standing nursing homes in the 95 HSAs.
Measures
Our outcome measure is defined at the patient level and indicates whether an individual was admitted to a non–hospital-based nursing home in the bottom quartile of facilities in an HSA, that is, in relation to the number of deficiencies. Deficiencies are violations in care standards.24 Only health-related deficiencies were included in this study (e.g., nursing home failure to “have a program to keep infection from spreading,”19 or “keep the rate of medication errors—wrong drug, wrong dose, wrong time—to less than 5%”19). This information has been publicly reported by the Centers for Medicare and Medicaid Services on their Web site19 since 2000, and the information about the number and types of deficiencies has been available by request from nursing homes for decades.
The main independent variables of interest were ethnic/racial identity and education. We categorized the ethnic/racial variable into 3 groups: non-Hispanic White (referent), African American, and other. Education was measured as less than a high-school education, only a high-school education, some college, and college degree. Other variables at the patient level included age, gender, and marital status (currently married vs other). We controlled for patients’ health status with 4 different measures: nursing case mix at admission to the nursing home (derived from the MDS assessment and the basis for Medicare postacute payment by the Resource Utilization Groups classification system),25 the Cognitive Performance Scale,26 and activities-of-daily-living dependence (0–28).27
We also included the number of medications taken in the 7 days before the last MDS assessment. Covariates at the HSA level included the number of nursing homes, the number of acute hospitals, the percentage of the population that was African American, the average nursing home occupancy, the per capita income, and the Medicare managed care penetration rate. These measures helped to control for alternative choices in the market available to hospital patients at discharge. Specifically, we used the Medicare managed care penetration rate to control for differential referral rates related to Medicare managed care contracting.
Analytic Approach
We tested the propositions that African American, other minority, and less educated Medicare beneficiaries who enter nursing homes directly from the hospital are more likely to be admitted to a low-quality facility. A low-quality facility is defined as one in the top quartile within an HSA on the basis of the number of health-related deficiencies. We entered all the predictors simultaneously into a logistic regression model with a Huber-White adjustment of the standard errors to account for clustering of unique patients within HSAs. The Stata software statistical package was used for all statistical analyses.28
RESULTS
Table 1 ▶ summarizes the characteristics of the 95 HSAs in the study and the patient-level characteristics of the sample. Our sampling strategy yielded HSAs with a high percentage of African Americans (24%). The average HSA contained an average of 6 acute general hospitals (SD = 7, range = 1, 44), 20 freestanding nursing homes (SD = 16, range = 4, 75), and 3 hospital-based nursing homes (SD = 4, range = 0, 18). Patient-level characteristics are presented separately by race/ethnicity. A high proportion of African Americans (52%) and other minority elders (54%) did not complete high school. African Americans in our sample were generally younger (28% older than 85 years) than non-Hispanic Whites (37% older than 85 years).
TABLE 1—
Hospital Service Area (HSA) and Patient-Level Characteristics at Nursing Home Admission: United States, 2002
Mean (SD), Range (n = 95) | Non-Hispanic White (n = 48 984) | African American (n = 11 675) | Other (n = 1942) | |
HSAs | ||||
Hospital-based nursing homes, no. | 3 (4) 0–18 | . . . | . . . | . . . |
Freestanding nursing homes, no. | 20 (16) 4–75 | . . . | . . . | . . . |
Acute general hospitals, no. | 6 (7) 1–44 | . . . | . . . | . . . |
Nursing home occupancy rate, % | 87 (6) 69–96 | . . . | . . . | . . . |
African Americans in total population, % | 24 (13) 5–67 | . . . | . . . | . . . |
Per capita income, $ | 29 712 (7723) 0–81 665 | . . . | . . . | . . . |
Ratio of African American nursing home admissions to White nursing home admissions | 0.59 (0.65) 0.07–4.53 | . . . | . . . | . . . |
Patients | ||||
Female, % | . . . | 69 | 65 | 62 |
Married, % | . . . | 29 | 23 | 31 |
Education, % | . . . | |||
Not high-school graduate | . . . | 26 | 52 | 54 |
High-school graduate | . . . | 44 | 33 | 30 |
Some college or technical school | . . . | 17 | 10 | 9 |
College graduate | . . . | 13 | 5 | 7 |
Years of age, % | . . . | |||
65–74 | . . . | 18 | 30 | 30 |
75–84 | . . . | 45 | 42 | 46 |
≥ 85 | . . . | 37 | 28 | 24 |
Nursing Case Mix Index (SD) | . . . | 1.10 (0.23) | 1.10 (0.25) | 1.07 (0.24) |
Medications in last 7 days, no. (SD) | . . . | 9 (4) | 9 (4) | 9 (4) |
Cognitive Performance Scale (SD) | . . . | 1.6 (1.7) | 2.1 (1.9) | 2.0 (1.8) |
ADL score (0–28) (SD) | . . . | 11 (5) | 12 (5) | 12 (5) |
Discharged to worst quartile nursing home in HSA, % | . . . | 22 | 30 | 28 |
Note. ADL = activities of daily living.
In an effort to validate our quality measure, we compared the worst quartile of nursing homes in each HSA (n = 465) to other nursing homes with fewer deficiencies (n = 1439) across various proxies for facility resources and quality. Compared with nursing homes in the better quartiles of deficiencies, nursing homes in the worst quartile of deficiencies had significantly higher percentages (P < .05) of Medicaid residents (72% vs 63%), significantly lower occupancy rates (85% vs 87%), and significantly higher prevalence of pressure ulcers (11% vs 9%). The worst-quality nursing homes were more likely to be for-profit (78% vs 69%) and to have higher percentages of African American residents (33% vs 22%).
Table 2 ▶ presents the independent effect of being an ethnic/racial minority on the relative risk of admission into the worst quartile of freestanding nursing homes in the 95 HSAs. When we controlled for other factors, African Americans were more likely (relative risk [RR] = 1.26; 95% confidence interval [CI] = 1.0, 8.45) than non-Hispanic Whites to be admitted to a low-quality nursing home. Individuals without a high-school education were more likely (RR = 1.22; 95% CI = 1.0, 1.46) to be discharged to the lowest quartile of nursing homes in a given HSA. Women and older patients were significantly less likely to be discharged to low-quality nursing homes. In a set of unreported robustness checks, we tested for interaction effects between ethnic/racial minority status and other demographic characteristics such as marital status, female gender, and less than high-school diploma and found no significant interactions. We also ran the model with dummy variables for the 5 major regions in the United States and observed no changes in the effects for ethnic/racial minority status and education.
TABLE 2—
Factors Influencing Admission Into Nursing Homes in Lowest-Quality Quartile Within 95 Hospital Service Areas (HSAs)
Risk Ratio (95% CI) n=62601)a | |
Race | |
African American | 1.26 (1.08, 1.45) |
Other race | 1.09 (0.85, 1.35) |
Years of age | |
75–84 | 0.93 (0.89, 0.98) |
≥ 85 | 0.87 (0.81, 0.94) |
Female | 0.91 (0.85, 0.96) |
Married | 0.98 (0.92, 1.03) |
Education | |
Less than high-school diploma | 1.22 (1.01, 1.46) |
High-school diploma | 1.13 (0.96, 1.37) |
Some college | 1.02 (0.88, 1.21) |
Nursing case mix index | 1.21 (0.88, 1.60) |
Number of medications | 0.99 (0.98, 1.00) |
ADL dependence (0–28) | 0.99 (0.98, 1.01) |
Cognitive performance scale | 1.01 (0.98, 1.04) |
Percentage African Americans in HSA | 0.99 (0.98, 1.00) |
Number of nursing homes in HSA | 1.00 (1.00, 1.01) |
Average nursing home occupancy in HSA | 1.03 (1.00, 1.06) |
Per capita income in HSA | 1.00 (1.00, 1.00) |
Number of hospitals in HSA | 0.99 (0.97, 1.01) |
Medicare managed care penetration | 0.99 (0.96, 1.03) |
Note. ADL = activities of daily living.
aAll HSAs with at least 50 African American Medicare admissions to nursing homes in 2002.
DISCUSSION
Ecological analyses have shown residential racial segregation patterns to be independently associated with racially disparate mortality rates.29–31 Segregation clearly plays a role in perpetuating racial and ethnic disparities in quality of care, but identifying the mechanisms through which segregation persists has been difficult. Our findings offer evidence that existing ethnic/racial disparities in nursing home care are attributable in part to hospital discharge practices that refer minorities to lower-quality nursing homes. Focusing on the HSA level allowed us to narrow the range in which nursing home “choice” typically occurred, thereby characterizing quality differences in a highly localized manner. Moreover, by focusing on postacute Medicare patients, we were able to control for the role of insurance because all these individuals had Medicare-covered stays.
Not having completed high school was independently related to the likelihood of being discharged to poor-quality nursing homes. Because current policy assumes that elders and their advocates should be able to participate in making quality choices and avail themselves of the relevant information, we assumed that those with less education would have more difficulty finding, interpreting, and acting on this information.32
The Centers for Medicare and Medicaid Services rulings requiring providers to offer patients referred to postacute settings a choice of facilities may be counterproductive in guiding patients to those facilities with the highest quality (the goal of public reporting of quality information). If those discharged from hospitals are making choices solely on the basis of geography (proximity to their families), it may well be that African American and other minority patients “choose” facilities that are systematically of lower quality precisely because of their location in the community.33 Perhaps a more proactive approach will be required to give minority patients a choice based on quality information that could be known to the discharge planner. Indeed, discharge planners may be in the best position to translate publicly available information about nursing home quality to prospective nursing home admissions and their families, particularly because such decisions tend to be made in a crisis situation. This would involve expanding the role for discharge planners to include more than simply finding an empty bed as quickly as possible.34 One mechanism to expand the role for discharged planners could involve collaborative efforts initiated by Programs of All Inclusive Care for the Elderly, whereby the care of frail elders is proactively managed to reduce lengths of stay while facilitating high-quality transitions between settings.
Inspection data documenting nursing home health deficiencies were publicly available for several years before the Centers for Medicare and Medicaid Services online publication of new quality indicators in early 2003.35,36 The inspection results and new quality measures are now available to all hospital discharge planners to use in guiding nursing home placement decisions. Hospital discharge planners have been included as an audience in the national quality improvement organization efforts to promote higher-quality nursing home care.37 However, the extent to which hospital discharge planners are sharing the new information with patients and their families remains unknown.
Most interventions targeting discharge planners for education and awareness have focused on increasing discharges to home,38 reducing rates of readmissions,39,40 lowering total days rehospitalized,41 and improving patient satisfaction with and involvement in the discharge process.42 New initiatives to sensitize hospital discharge planners to the quality of nursing home care should build on these education and awareness efforts while recognizing that the choice of a nursing home can be influenced by the ethnic/racial makeup of nursing homes: racial/ethnic minorities may choose to reside with other ethnic/racial minorities.
Our study was limited by the lack of information about individuals’ preferences for specific nursing homes or the relative importance of nursing home geographic proximity to family. Also, we did not include information on the distribution of all hospital discharges receiving other forms of postacute care such as rehabilitation, hospital, or home care. Our findings may be biased if minorities are significantly more or less likely to use these other forms of postacute care. However, because recent research has shown that greater use of Medicare home health services among minorities is largely explained by differences in health needs, it is likely the same would be true in the case of nursing home care.43 We also lacked data on supplemental Medicare insurance for skilled nursing home care, which may influence placement into certain facilities. A final potential limitation is the omission of hospital quality information within our analyses. For example, minority patients may disproportionately be admitted to public hospitals with lower operating margins. Thus, policies that address broader disparities in hospital resources may ultimately lessen disparities in nursing home placements.
In spite of numerous commentaries on postacute care and the need for continuity of care for the frail Medicare population and the increasing recognition of the importance of chronic care systems of care, little attention has been devoted to the relations that hospitals have with the nursing homes to which they discharge their patients.44 This lack of attention has allowed racial disparities to persist in the quality of nursing homes to which hospitals’ minority patients are discharged. Hospital discharge planners’ referring of minority hospital patients to lower-quality nursing homes may contribute to racial and ethnic disparities in quality of care that exist within a geographical area. Educating hospital discharge planners about nursing home quality is a critical first step in leveling the playing field for vulnerable minority patients.
Acknowledgments
This research was funded in part by the National Institute on Aging (grants AG 20557, AG 13987, AG 024403), the Agency for Healthcare Research and Quality (grant HS 09552), and the Commonwealth Fund (grant 20050318).
Human Participant Protection No protocol approval was needed for this study.
Peer Reviewed
Contributors J. Angelelli originated the research question and directed all aspects of the analysis. D. C. Grabowski and V. Mor assisted with the analyses and interpretation. All authors helped to conceptualize ideas, interpret findings, and review drafts of the article.
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