Logo of jgimedspringer.comThis journalToc AlertsSubmit OnlineOpen Choice
J Gen Intern Med. Mar 2007; 22(3): 338–345.
Published online Jan 9, 2007. doi:  10.1007/s11606-006-0088-x
PMCID: PMC1824769

Influence of Race on Inpatient Treatment Intensity at the End of Life

Amber E. Barnato, MD, MPH, MS,corresponding author1 Chung-Chou H. Chang, PhD,1 Olga Saynina, MA, MBA,2 and Alan M. Garber, MD, PhD2,3,4

Abstract

OBJECTIVE

To examine inpatient intensive care unit (ICU) and intensive procedure use by race among Medicare decedents, using utilization among survivors for comparison.

DESIGN

Retrospective observational analysis of inpatient claims using multivariable hierarchical logistic regression.

SETTING

United States, 1989–1999.

PARTICIPANTS

Hospitalized Medicare fee-for-service decedents (n = 976,220) and survivors (n = 845,306) aged 65 years or older.

MEASUREMENTS AND MAIN RESULTS

Admission to the ICU and use of one or more intensive procedures over 12 months, and, for inpatient decedents, during the terminal admission. Black decedents with one or more hospitalization in the last 12 months of life were slightly more likely than nonblacks to be admitted to the ICU during the last 12 months (49.3% vs. 47.4%, p <.0001) and the terminal hospitalization (41.9% vs. 40.6%, p < 0.0001), but these differences disappeared or attenuated in multivariable hierarchical logistic regressions (last 12 months adjusted odds ratio (AOR) 1.0 [0.99–1.03], p = .36; terminal hospitalization AOR 1.03 [1.0–1.06], p = .01). Black decedents were more likely to undergo an intensive procedure during the last 12 months (49.6% vs. 42.8%, p < .0001) and the terminal hospitalization (37.7% vs, 31.1%, p < .0001), a difference that persisted with adjustment (last 12 months AOR 1.1 [1.08–1.14], p < .0001; terminal hospitalization AOR 1.23 [1.20–1.26], p < .0001). Patterns of differences in inpatient treatment intensity by race were reversed among survivors: blacks had lower rates of ICU admission (31.2% vs. 32.4%, p < .0001; AOR 0.93 [0.91–0.95], p < .0001) and intensive procedure use (36.6% vs. 44.2%; AOR 0.72 [0.70–0.73], p <.0001). These differences were driven by greater use by blacks of life-sustaining treatments that predominate among decedents but lesser use of cardiovascular and orthopedic procedures that predominate among survivors. A hospital’s black census was a strong predictor of inpatient end-of-life treatment intensity.

CONCLUSIONS

Black decedents were treated more intensively during hospitalization than nonblack decedents, whereas black survivors were treated less intensively. These differences are strongly associated with a hospital’s black census. The causes and consequences of these hospital-level differences in intensity deserve further study.

Key words: medicare, end of life care, race & ethnicity, intensive care, inpatient care

In contrast to general patterns of racial differences in health care utilization,1,2 including lower rates of invasive cardiac procedures,311 surgical treatment for lung cancer12 and renal transplantation13,14 among blacks, at the end of life, blacks appear to receive higher rates of intensive treatment. For example, blacks are more likely to die in the hospital15 and less likely to use hospice16 and have higher overall spending in their last 12 months than whites.1719 Some have tried to explain these phenomena by citing differences in patient preferences. Indeed, several studies report that blacks and Hispanics prefer more aggressive life-sustaining treatment than whites,2023 and that physicians’ preferences for end-of-life treatment follow the same pattern by race as patients’ preferences.24 However, treatment preferences for care at the end of life do not reliably predict actual treatment.15,25

Recent studies have explored the role of region,26 hospital,2729 and individual provider30 in observed racial differences in health care utilization. With respect to end-of-life care, an analysis of Medicare claims found that aggregate ICU admissions and hospital days in the last 6 months of life are driven more by region of residence than by race31 and an analysis of terminal hospital discharges from 6 states found that the majority of observed differences in ICU use among black and Hispanic decedents were attributable to their use of hospitals with higher ICU use rather than to racial differences in ICU use within the same hospital.32

Secular increases in ICU admission and intensive inpatient procedure use have occurred among both decedents and survivors33; little is known about the respective trends by race. Building upon our previous work, we sought to describe the effect of race on inpatient ICU and intensive procedure use among Medicare decedents over 10 years, adjusting for hospital-level effects in the analyses and using utilization among survivors for comparison. We hypothesized that hospitalized black decedents would be treated more intensively in their last 12 months of life, but less intensively otherwise, and that differences in end-of-life intensity would be largely attributable to greater use of life-sustaining procedures such as mechanical ventilation, feeding tube placement, and hemodialysis.

METHODS

Sample Selection

We initially drew a 20% sample of all decedents and a 5% sample of all survivors enrolled in Medicare in 1989, 1991, 1993, 1995, 1997, and 1999 from the Denominator file maintained by the Centers for Medicare and Medicaid Services. The data were initially assembled to study secular trends over time, so it was not felt that every year was necessary.33 For the current analyses, we removed 1985 and 1987 because these years were not comparable to the years after 1989, due to the introduction of DRGs 474 and 475 in October, 1987. After those DRGs were introduced, there was a marked jump in the coding of intubation and tracheostomy procedures, the most common inpatient intensive procedures among decedents. Regarding truncation at 1999, at the time of our initial forays into analysis (2001), 1999 was the most recent year of data available.

For each beneficiary, we assembled the acute care hospital claims from the Medicare Medical Provider Analysis and Review (MedPAR) files; for decedents, we included all claims in the 365 days preceding their death and for the survivors we included claims during the calendar year. This provided a full 12 months of enrollment and utilization experience for both survivors and decedents. We limited our analysis to patients aged 65 and older and excluded Medicare beneficiaries with discontinuous enrollment in Medicare Part A or Part B, residence outside the United States or a foreign hospital admission, enrollment in a health maintenance organization, or hospitalization in a Federal hospital during the year because these persons might have incomplete hospitalization records. For beneficiaries whose claims spanned multiple years (first as survivors and later as decedents), we randomly sampled one 12-month (survivor or decedent) claims period for the current analysis so that no beneficiary appears more than once.

We abstracted each patient’s age, sex, race, and ZIP code of residence from the Social Security Administration denominator file. We classified age into 5-year increments (65–69, 70–74, 75–79, 80–84, and >85), and analyzed race by grouping all beneficiaries into the categories “black” and “nonblack,” excluding all beneficiaries with “unknown” race.34 We used ZIP code level measures of income and education from the area resource file (ARF) as proxies for these socioeconomic indicators. Individual socioeconomic status will generally be associated with area measures of income, with people living in wealthy areas having more assets and socioeconomic status than people living in poorer areas.35,36 In exploratory multivariable regressions, Charlson diagnoses provided better model fit for expenditures than Elixhauser diagnoses,37,38 so we used the presence or absence of these 18 ICD-9 clinical diagnoses for comorbidity risk adjustment.

We attributed a beneficiary’s hospital care to the first hospital patronized in the 12-month sampling frame. Among survivors and decedents with at least one hospital admission in the year, over 60% and 40%, respectively, had only one claim; the remainder had two or more hospitalizations. Among all patients with at least one hospital admission, 87% of survivors and 78% of decedents in 1999 received all of their inpatient care at one hospital. We used files from the American Hospital Association (AHA) survey to identify hospitals’ membership in the Council of Teaching Hospitals (COTH), financial status (for profit or not for profit, including government hospitals), and bed size. A small number of hospitals care for the vast majority of elderly black Americans.39 We constructed a variable “percent black” (percent of all admissions among blacks) to capture unmeasured hospital differences that vary systematically with black census.

Inpatient ICU and Procedure Use

For each beneficiary with at least one hospital admission in the 12 months, we recorded total hospital admissions, ICU admissions, and major surgical procedures. We classified a patient as having an ICU admission if the hospitalization included one or more days in a coronary care unit (CCUs) or an intensive care unit (ICUs). We condensed the International Classification of Diseases, 9th Edition (ICD-9) procedure codes into 228 categories using an algorithm nearly identical to the Clinical Classification System (CCS) developed for the Agency for Healthcare Research and Quality (AHRQ). For this study, we report data on the 88 procedure categories that are performed primarily in the inpatient setting and which were likely the primary reason for admission (see Appendix). We made exceptions to this rule for a handful of technologies that were newly introduced during the time period of study and that grew rapidly in use (e.g., automated implantable cardioverter defibrillator (AICD) implantation).

Statistical Analyses

We performed all computations with SAS statistical software (version 6.12, SAS Corporation, Cary, NC, USA). We categorized patients with at least one hospital admission during the year into 4 subgroups: black decedents, nonblack decedents, black survivors, and nonblack survivors, and compared their demographics, comorbidities, hospital characteristics, inpatient expenditures, and ICU and intensive procedure use. We performed multivariable logistic regression on the categorical receipt of one or more ICU admission and the receipt of one or more intensive procedures using a hierarchical model to adjust for patients clustered within hospitals. We estimated this model with the restricted maximum likelihood method, assuming unstructured covariance and treating hospital as a random effect. We performed separate regressions for decedents and survivors and included calendar year of observation in all models. Due to the marked interaction between decedent status and all outcomes, this was the most appropriate modeling strategy. To calculate the 95% confidence intervals on odds ratios from our parameter estimates and standard errors, we used the Wald first-order approximation.40

The Institutional Review Board at Stanford University approved the study. We had complete independence from the National Institute on Aging (NIA) in the design, conduct, and reporting of the study.

RESULTS

Characteristics of the Study Sample

The sample included 887,787 nonblack and 88,433 black decedents and 781,980 nonblack and 63,326 black survivors with at least one admission between 1989 and 1999. There were significant differences in most measured covariables between nonblacks and blacks (Table 1).

Table 1
Characteristics of the Study Sample, by Race and Survivor Status, 1989–1999

Intensive Care and Procedure Use

We present crude rates of ICU admission and the use of one or more intensive procedures by race for all years combined in Table 2 and by year in Figure 1. Black decedents with one or more hospitalization in the last 12 months of life were slightly more likely than nonblacks to be admitted to the ICU during the last 12 months (49.3% vs. 47.4%, p < .0001) and the terminal hospitalization (41.9% vs. 40.6%, p < .0001), but these differences disappeared or attenuated in multivariable hierarchical logistic regressions (last 12 months adjusted odds ratio (AOR) 1.0 [0.99–1.03], p = .36; terminal hospitalization AOR 1.03 [1.0–1.06], p = .01). Black decedents were more likely to undergo an intensive procedure during the last 12 months (49.6% vs. 42.8%, p < .0001) and the terminal hospitalization (37.7% vs. 31.1%, p < .0001), a difference that persisted with adjustment (last 12 months AOR 1.1 [1.08–1.14], p < .0001; terminal hospitalization AOR 1.23 [1.20–1.26], p < .0001). Patterns of differences in inpatient treatment intensity by race were reversed among survivors: blacks had lower rates of ICU admission (31.2% vs. 32.4%, p < .0001; AOR 0.93 [0.91–0.95], p < .0001) and intensive procedure use (36.6% vs. 44.2%; AOR 0.72 [0.70–0.73], p < .0001). The black/nonblack difference in decedent, but not survivor, ICU and procedure use increased over time (Fig. 1).

Table 2
Inpatient Resource Use, by Race and Survivor Status, 1989–1999
Figure 1
Trends in inpatient treatment intensity differences by race between 1989 and 1999. The gap in ICU admission (panel A) and intensive procedure use (panel B) between blacks and nonblacks has widened among decedents (dashed lines) but remained parallel or ...

Additional predictors of inpatient treatment intensity included educational achievement in the patient’s ZIP code and hospital characteristics (Table 3). Notably, a 5% increase in the hospital’s black census increased the odds of ICU admission 17-fold ([14.1–20.8], p < .0001) for the last 12 months and 24-fold ([18.6–31.0], p < .0001) for the terminal admission. This effect was much more modest among survivors (AOR 1.55 [1.23–2.95], p = .0002). A 5% increase in the hospital’s black census increased the odds of an intensive procedure 8-fold ([6.2–10.4], p < .0001) for the last 12 months and 16-fold ([12.6–21.1], p < .0001) for the terminal admission, but decreased the odds for survivors more than 6-fold ([0.12–0.20], p < 0.0001).

Table 3
Adjusted Odds* of ICU Admission and Intensive Procedure Use, 1989–1999

The distinct patterns of racial differences in intensive procedure use were driven by the particular procedures that predominate among decedents compared to survivors. We list each of the procedures performed among 1.5% or more of each population in Table 4, indicating those that are more and less frequently performed among blacks compared to nonblacks. Specifically, such life-sustaining procedures as intubation/tracheostomy for mechanical ventilation and gastrostomy placement for enteral feeding predominated among decedents, and blacks were more likely than nonblacks to undergo these procedures, regardless of survivorship group. In contrast, cardiovascular and orthopedic procedures that have been classified by the Dartmouth Atlas of Health Care as preference- and supply-sensitive procedures, such as cardiac catheterization and revascularization and hip replacement, predominated among survivors and were less frequently performed among blacks than nonblacks.

Table 4
Common* Intensive Procedure Use by Race and Survivor Status, 1989–1999

DISCUSSION

In this retrospective observational study using fee-for-service Medicare claims, we confirmed that black decedents were treated more intensively during hospitalization than nonblack decedents, whereas black survivors were treated less intensively. The greater use by blacks of life-sustaining treatments that predominate among decedents but lesser use of cardiovascular and orthopedic procedures that predominate among survivors explained observed racial differences in procedure use by survivorship cohort. The relatively smaller differences in end-of-life ICU use were largely at]tributable to confounding factors, including hospital choice. Among the strongest predictors of ICU and intensive procedure use was a hospital’s black census. Because the addition of black census to the hierarchical model decreased the size of the parameter estimate on black race, our study suggests that blacks’ hospital choice/access in part mediates the observed relationship between treatment intensity and race.41 These systematic differences in hospital-level practice patterns may reflect local patient and community factors (e.g., preferences) or provider factors (e.g., hospital resources, staffing and organization, or process and outcomes of communication and decision making).

This is the first nationally representative study of fee-for-service Medicare beneficiaries to explore racial differences in ICU and intensive procedure use at the end of life. Most previous Medicare claims studies have focused on overall inpatient spending18,19 and none have used multilevel modeling to account for individual hospital effects. The study by Levinsky et al. that analyzed ICU and life-sustaining procedure use by age in California and Massachusetts only reported a demographic- and comorbidity-adjusted effect of black race on spending due to limited sample size of blacks.17 The multicenter Study to Understand Prognoses and Preferences for Outcomes and Risks of Treatment (SUPPORT) trial reported that black patients received less intervention than white patients among their sample of seriously ill adults that included younger patients and a mix of decedents and survivors.42

Both end-of-life health service use and racial differences in treatment receive a great deal of policy attention. End-of-life utilization attracts interest because per person expenditures for Medicare beneficiaries who die each year are 5 times higher than for survivors.43 Indeed, between 1985 and 1999 real spending on inpatient services for fee-for-service decedents increased 60%, to $23 billion in 1999.33 This increase in spending was neither driven by an increase in the population nor a significant increase in the age-adjusted likelihood of admission; instead, increases in per capita treatment intensity explained much of this expenditure growth. Racial differences in health service use attract interest because they may reflect differences in access or uptake that contribute to observed health disparities. Curiously, as reported by other authors, it is only at the end of life that blacks appear to have greater health services expenditures than nonblacks, particularly for inpatient services.17,19,44 In part, this is due to a higher likelihood of dying in the hospital.33 Findings from the present study additionally suggest that blacks’ greater use of intensive procedures, particularly highly remunerated (pre-2006) DRGs 475 and 483 associated with intubation/tracheostomy and mechanical ventilation >96 hours, help to explain this higher spending.

The lower rates of cardiovascular and orthopedic procedures among blacks have been previously documented, and may be due to differences in physician referral8,11,45 or to differences in patients’ perceptions of outcomes and their attendant willingness to undergo surgery.46,47 Higher rates of intubation and tracheostomy and feeding tube placement are consistent with previous studies of hypothetical and real end-of-life decisions suggesting that blacks are less likely to forego life-sustaining treatments.2024,48 Higher rates of vascular and hemodialysis access procedures and lower rates of surgical repair of hip fracture are likely attributable to the well-documented differences in burden of vascular disease, end-stage renal disease, and osteoporosis among blacks compared to nonblacks.

The secular trends demonstrating a widening of the difference in end-of-life impatient treatment intensity between blacks and nonblacks in the latter half of the 1990s could be explained by progressively higher rates of hospice enrollment16, 32 and attendant limitation of ICU admission, mechanical ventilation, and enteral feeding among nonblacks during this period. Furthermore, the minority of U.S. hospitals that care for most of America’s black patients are more likely to have medical ICUs39; other structures and processes related to treatment intensity also likely differ.

Our study is subject to several limitations. First, our study relies upon the frequently used “look back” approach to understand how dying patients are treated, though patients may not have been known to be “dying” at the time treatments were initiated.49,50 Additionally, we focused only on inpatient services and did not study trends in outpatient or postacute treatment intensity because the hospital remains the site of the most expensive and technologically intensive medical care. Our measures of utilization may have underestimated treatment intensity by calculating the receipt of one or more ICU admission or procedure over 12 months rather than the mean number of admissions and procedures. Our findings for the terminal hospitalization and for total expenditures which more closely track service volume (not reported) followed the same patterns by race and suggest that our measure of utilization does not confound the observations. Despite statistical adjustment for measured confounders, the large differences in characteristics of black and nonblack patients raise the possibility that differences are attributable to unmeasured confounders. Finally, the observations are based only upon fee-for-service Medicare and cannot be generalized to those in managed “risk plans.”

Our study does not offer any information about patient preferences or the appropriateness of end-of-life treatment intensity. It does, however, raise provocative questions about differences in practice patterns at hospitals caring for black patients that deserve further study.

Acknowledgements

We thank several anonymous reviewers for their suggestions to improve the report of our findings. An earlier version of this study, “Predictors of Intensive Inpatient Service Use Among the Elderly,” was presented in poster form at the AcademyHealth Annual Research Meeting in Nashville, TN, June, 2003.

Author contributions and data access and responsibility: Dr. Barnato was responsible for study concept and design, analysis and interpretation of data, and preparation of the manuscript. Dr. Garber obtained the data, and was responsible for study concept and design, analysis and interpretation of data, and providing feedback on drafted manuscripts. Ms. Saynina was responsible for data analytic concept and design and for programming and providing feedback on drafted manuscripts. Dr. Chang was responsible for statistical concept and design, in addition to interpretation of the data and providing feedback on drafted manuscripts. Dr. Barnato had full access to the data while at Stanford (until July 2001); thereafter, and for the version of the analysis reported here, Olga Saynina had full access to the data. Dr. Barnato takes full responsibility for the integrity of the data and the accuracy of the data analysis.

Potential Financial Conflicts of Interest: None of the authors has any affiliations with or financial involvement, within the past 5 years and foreseeable future (e.g., employment, consultancies, honoraria, stock ownership or options, expert testimony, grants or patents received, or pending royalties) with any organization or entity with a financial interest in or financial conflict with the subject matter or materials discussed in the manuscript. Disclosures: Dr. Barnato: NIH funding, no other disclosures. Dr. Chang: NIH funding, no other disclosures. Ms. Saynina: No disclosures. Dr. Garber: NIH-funding and paid and unpaid consultancies including: the Centers for Medicare and Medicaid Services’ Medicare Coverage Advisory Committee, the national Blue Cross and Blue Shield Association Medical Advisory Panel, the Institute of Medicine, the Congressional Office of Technology Assessment, and the Clinical Efficacy Assessment Project of the American College of Physicians.

Role of the sponsor: Funding was provided by National Institute on Aging (NIA) grants AG17253 and AG050842 to Stanford University and the National Bureau of Economic Research. Dr. Barnato was supported by NIA career-development grant AG021921. The NIA had no role in the design and conduct of the study; collection, management, analysis, and interpretation of the data; and preparation, review, or approval of the manuscript.

Appendix

Intensive procedures included in the study (in alphabetical order)

Amputation of lower extremity

Ankle/foot joint replacement

Aortic resection with replacement

Appendectomy

Arteriogram and venogram (not heart or head)

Automated implantable cardioverter defibrillator (AICD)

Biopsy of spinal cord

Bone marrow transplant

Cardiac assist device/ECMO/bypass

Cardiac catheterization, coronary arteriography

Carotid endarterectomy

Central vessel endarterectomy/thrombectomy

Cerebral arteriogram

Cholecystectomy and common duct exploration

Closed control of UGIB

Colon resection

Coronary artery bypass graft (CABG)

Creation of arteriovenous fistula

Cycstectomy

Electrophysiology study (EPS) +/- ablation

Enterostomy

Esophageal dilation

Esophageal reanastamosis/repair

Esophagectomy

Excision, lysis peritoneal tissue

Exploratory laparotomy

Feeding tube placement

Fundoplication

Genitourinary incontinence procedures

Hemodialysis

Hip replacement, total and partial

Hysterectomy

Ileostomy and colostomy

Injection or ligation of esophageal varices

Insert/repl/revise/remove permananent pacemaker

Insertion, temporary cardiac pacemaker

Intracoronary artery thrombolytic infusion

Intubation and Tracheostomy

Jaw fracture repair

Kidney transplant

Knee replacement

Laminectomy, diskectomy, arthrodesis

Laparoscopic cholecystectomy

Laryngectomy

Lobectomy

Local excision lung/bronchus

Mastectomy

Mastoidectomy

Mediastinoscopy

Nephrectomy

Oophorectomy, unilateral and bilateral

Open biopsy lung/bronchus

Open cholecystectomy

Open CNS biopsy

Open CNS diagnostic procedures

Open CNS therapeutic procedures

Open control of UGIB

Open heart repair of septal defects, etc.

Open or closed cardiac massage

Open Prostatectomy

Orchiectomy

Pancreatectomy/pancreaticoduodenectomy

Partial/total gastrectomy and gastric bypass

Pelvic exenteration

Percutaneous CNS biopsy (stereotactic/burr hole)

Percutaneous transluminal coronary angioplasty (PTCA)

Pericardial procedure

Peripheral vascular bypass

Peripheral vessel endarterectomy/thrombectomy

Pneumonectomy

Pyloroplasty

Radical Prostatectomy

Regional/radical lymph-node dissection

Revision/repair of vessel/vascular Procedure

Skin graft

Small bowel resection

Splenectomy

Surgical removal of urinary calculus

Thoracotomy

Thyroidectomy

Transurethral Prostatectomy (TURP)

Treatment, fracture of hip and femur

Treatment, fracture of lower extremity

Treatment, fracture of radius and ulna

Vagotomy

Valve procedures (including replacement)

Vena cava interruption

Ventricular shunt

References

1. Smedley B, Stith A, Nelson A, eds. Unequal Treatment: Confronting Racial and Ethnic Disparities in Health Care. Washington, DC: National Academy Press: 2002. [PMC free article] [PubMed]
2. McBean AM, Gornick M. Differences by race in the rates of procedures performed in hospitals for Medicare beneficiaries. Health Care Financ Rev. 1994;15(4):77–90. [PMC free article] [PubMed]
3. Udvarhelyi IS, Gatsonis C, Epstein AM, Pashos CL, Newhouse JP, McNeil BJ. Acute myocardial infarction in the Medicare population. Process of care and clinical outcomes. JAMA. 1992;268(18):2530–6. [PubMed]
4. Ayanian JZ, Udvarhelyi IS, Gatsonis CA, Pashos CL, Epstein AM. Racial differences in the use of revascularization procedures after coronary angiography. JAMA. 1993;269(20):2642–6. [PubMed]
5. Whittle J, Conigliaro J, Good CB, Lofgren RP. Racial differences in the use of invasive cardiovascular procedures in the Department of Veterans Affairs medical system. N Engl J Med. 1993;329(9):621–7. [PubMed]
6. Peterson ED, Wright SM, Daley J, Thibault GE. Racial variation in cardiac procedure use and survival following acute myocardial infarction in the Department of Veterans Affairs [see comments]. JAMA. 1994;271(15):1175–80. [PubMed]
7. Whittle J, Conigliaro J, Good CB, Joswiak M. Do patient preferences contribute to racial differences in cardiovascular procedure use? J Gen Intern Med. 1997;12(5):267–73. [PMC free article] [PubMed]
8. Schulman KA, Berlin JA, Harless W, et al. The effect of race and sex on physicians’ recommendations for cardiac catheterization [see comments]. [erratum appears in N Engl J Med 1999 Apr 8;340(14):1130]. N Engl J Med. 1999;340(8):618–26. [PubMed]
9. Chen J, Rathore SS, Radford MJ, Wang Y, Krumholz HM. Racial differences in the use of cardiac catheterization after acute myocardial infarction [see comments]. N Engl J Med. 2001;344(19):1443–9. [PubMed]
10. Einbinder LC, Schulman KA. The effect of race on the referral process for invasive cardiac procedures. Med Care Res Rev. 2000;57(Suppl 1):162–80. [PubMed]
11. LaVeist TA, Morgan A, Arthur M, Plantholt S, Rubinstein M. Physician referral patterns and race differences in receipt of coronary angiography. Health Serv Res. 2002;37(4):949–62. [PMC free article] [PubMed]
12. Bach PB, Cramer LD, Warren JL, Begg CB. Racial differences in the treatment of early-stage lung cancer [see comments]. N Engl J Med. 1999;341(16):1198–205. [PubMed]
13. Ayanian JZ, Cleary PD, Weissman JS, Epstein AM. The effect of patients’ preferences on racial differences in access to renal transplantation [see comments]. N Engl J Med. 1999;341(22):1661–9. [PubMed]
14. Epstein AM, Ayanian JZ, Keogh JH, et al. Racial disparities in access to renal transplantation-clinically appropriate or due to underuse or overuse? N Engl J Med. 2000;343(21):1537–44. [PubMed]
15. Pritchard RS, Fisher ES, Teno JM, et al. Influence of patient preferences and local health system characteristics on the place of death. SUPPORT Investigators. Study to understand prognoses and preferences for risks and outcomes of treatment [see comments]. J Am Geriatr Soc. 1998;46(10):1242–50. [PubMed]
16. Greiner KA, Perera S, Ahluwalia JS. Hospice usage by minorities in the last year of life: results from the National Mortality Followback Survey. J Am Geriatr Soc. 2003;51(7):970–8. [PubMed]
17. Levinsky NG, Yu W, Ash A, et al. Influence of age on Medicare expenditures and medical care in the last year of life. JAMA. 2001;286(11):1349–55. [PubMed]
18. Hogan C, Lunney J, Gabel J, Lynn J. Medicare beneficiaries’ costs of care in the last year of life. Health Aff. 2001;20(4):188–95. [PubMed]
19. Shugarman LR, Campbell DE, Bird CE, Gabel J, Louis TA, Lynn J. Differences in medicare expenditures during the last 3 years of life. J Gen Intern Med. 2004;19(2):127–35. [PMC free article] [PubMed]
20. Garrett JM, Harris RP, Norburn JK, Patrick DL, Danis M. Life-sustaining treatments during terminal illness: who wants what? J Gen Intern Med. 1993;8(7):361–8. [PubMed]
21. O’Brien LA, Grisso JA, Maislin G, et al. Nursing home residents’ preferences for life-sustaining treatments. JAMA. 1995;274(22):1775–9. [PubMed]
22. McKinley ED, Garrett JM, Evans AT, Danis M. Differences in end-of-life decision making among black and white ambulatory cancer patients. J Gen Intern Med. 1996;11(11):651–6. [PubMed]
23. Diringer MN, Edwards DF, Aiyagari V, Hollingsworth H. Factors associated with withdrawal of mechanical ventilation in a neurology/neurosurgery intensive care unit. Crit Care Med. 2001;29(9):1792–7. [PubMed]
24. Mebane EW, Oman RF, Kroonen LT, Goldstein MK. The influence of physician race, age, and gender on physician attitudes toward advance care directives and preferences for end-of-life decision-making. J Am Geriatr Soc. 1999;47(5):579–91. [PubMed]
25. Teno JM, Licks S, Lynn J, et al. Do advance directives provide instructions that direct care? SUPPORT Investigators. Study to understand prognoses and preferences for outcomes and risks of treatment [see comments]. J Am Geriatr Soc. 1997;45(4):508–12. [PubMed]
26. Skinner J, Weinstein JN, Sporer SM, Wennberg JE. Racial, ethnic, and geographic disparities in rates of knee arthroplasty among Medicare patients. N Engl J Med. 2003;349(14):1350–9. [PubMed]
27. Barnato AE, Lucas FL, Staiger D, Wennberg DE, Chandra A. Hospital-level racial disparities in acute myocardial infarction treatment and outcomes. Med Care. 2005;43(4):308–19. [PMC free article] [PubMed]
28. Bradley EH, Herrin J, Wang Y, et al. Racial and ethnic differences in time to acute reperfusion therapy for patients hospitalized with myocardial infarction. JAMA. 2004;292(13):1563–72. [PubMed]
29. Groeneveld PW, Laufer SB, Garber AM. Technology diffusion, hospital variation, and racial disparities among elderly Medicare beneficiaries: 1989–2000. Med Care. 2005;43(4):320–9. [PubMed]
30. Bach PB, Pham HH, Schrag D, Tate RC, Hargraves JL. Primary care physicians who treat blacks and whites. N Engl J Med. 2004;351(6):575–84. [PubMed]
31. Baicker K, Chandra A, Skinner JS, Wennberg JE. Who you are and where you live: how race and geography affect the treatment of Medicare beneficiaries. Health Aff (Millwood, VA). 2004. [PubMed]
32. Barnato AE, Berhane Z, Weissfeld LA, Chang CC, Linde-Zwirble WT, Angus DC. Racial variation in end-of-life intensive care use: a race or hospital effect? Health Serv Res. 2006;41(6):2219–37. [PMC free article] [PubMed]
33. Barnato AE, McClellan MB, Kagay CR, Garber AM. Trends in inpatient treatment intensity among Medicare beneficiaries at the end of life. Health Serv Res. 2004;39(2):363–75. [PMC free article] [PubMed]
34. Arday SL, Arday DR, Monroe S, Zhang J. HCFA’s racial and ethnic data: current accuracy and recent improvements. Health Care Financ Rev. 2000;21(4):107–16. [PMC free article] [PubMed]
35. Krieger N, Williams DR, Moss NE. Measuring social class in US public health research: concepts, methodologies, and guidelines. Annu Rev Public Health. 1997;18:341–78. [PubMed]
36. Geronimus AT, Bound J. Use of census-based aggregate variables to proxy for socioeconomic group: evidence from national samples. Am J Epidemiol. 1998;148(5):475–86. [PubMed]
37. Deyo RA, Cherkin DC, Ciol MA. Adapting a clinical comorbidity index for use with ICD-9-CM administrative databases. J Clin Epidemiol. 1992;45(6):613–9. [PubMed]
38. Elixhauser A, Steiner C, Harris R, Coffey R. Comorbidity measures for use with administrative data. Med Care. 1998;36(1):8–27. [PubMed]
39. Jha AK, Orav EJ, Li Z, Epstein AM. Where do elderly black Americans receive hospital care? Racial concentration in hospital care and the performance of hospitals that care for blacks [abstract]. J Gen Int Med. 2006;21(Suppl. 4):165.
40. Kleinbaum DG, Klein M. Logistic Regression, 2nd edn. New York: Springer.
41. Baron RM, Kenny DA. The moderator-mediator variable distinction in social psychological research: conceptual, strategic, and statistical considerations. J Pers Soc Psychol. 1986;51(6):1173–82. [PubMed]
42. Borum ML, Lynn J, Zhong Z. The effects of patient race on outcomes in seriously ill patients in SUPPORT: an overview of economic impact, medical intervention, and end-of-life decisions. Study to understand prognoses and preferences for outcomes and risks of treatments. J Am Geriatr Soc. 2000;48(5 Suppl):S194–8. [PubMed]
43. Lubitz JD, Riley GF. Trends in Medicare payments in the last year of life. N Engl J Med. 1993;328(15):1092–6. [PubMed]
44. Hogan C, Lynn J, Gabel J, Lunney J, O’Mara A, Wilkinson A. (Medicare Payment Advisory Commission). Medicare Beneficiaries’ Costs and Use of Care in the Last Year of Life (MedPAC Contract Research Series). 2000 May 1, 2000. Report No.: 00–1.
45. Ibrahim SA, Whittle J, Bean-Mayberry B, Kelley ME, Good C, Conigliaro J. Racial/ethnic variations in physician recommendations for cardiac revascularization. Am J Public Health. 2003;93(10):1689–93. [PMC free article] [PubMed]
46. Ibrahim SA, Siminoff LA, Burant CJ, Kwoh CK. Differences in expectations of outcome mediate African American/white patient differences in “willingness” to consider joint replacement. Arthritis Rheum. 2002;46(9):2429–35. [PubMed]
47. Ibrahim SA, Siminoff LA, Burant CJ, Kwoh CK. Understanding ethnic differences in the utilization of joint replacement for osteoarthritis: the role of patient-level factors. Med Care. 2002;40(1 Suppl):I44–51. [PubMed]
48. Shepardson LB, Gordon HS, Ibrahim SA, Harper DL, Rosenthal GE. Racial variation in the use of do-not-resuscitate orders. J Gen Intern Med. 1999;14(1):15–20. [PMC free article] [PubMed]
49. Bach PB, Schrag D, Begg CB. Resurrecting treatment histories of dead patients: a study design that should be laid to rest. JAMA. 2004;292(22):2765–70. [PubMed]
50. Barnato AE, Lynn J. Resurrecting treatment histories of dead patients. JAMA. 2005;293(13):1591–2 (author reply 1592). [PubMed]

Articles from Journal of General Internal Medicine are provided here courtesy of Society of General Internal Medicine
PubReader format: click here to try

Formats:

Related citations in PubMed

See reviews...See all...

Links

  • MedGen
    MedGen
    Related information in MedGen
  • PubMed
    PubMed
    PubMed citations for these articles

Recent Activity

Your browsing activity is empty.

Activity recording is turned off.

Turn recording back on

See more...