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Race, resource use, and survival in seriously III hospitalized adults

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Abstract

OBJECTIVE: To examine the association between patient race and hospital resource use.

DESIGN: Prospective cohort study.

SETTING: Five geographically diverse teaching hospitals.

PATIENTS: Patients were 9,105 hospitalized adults with one of nine illnesses associated with an average 6-month mortality of 50%.

MEASUREMENTS AND MAIN RESULTS: Measures of resource use included: a modified version of the Therapeutic Intervention Scoring System (TISS); performance of any of any of five procedures (operation, dialysis, pulmonary artery catheterization, endoscopy, and bronchoscopy); and hospital charges, adjusted by the Medicare cost-to-charge ratio per cost center at each participating hospital. The median patient age was 65; 79% were white, 16% African-American, 3% Hispanic, and 2% other races; 47% died within 6 months. After adjusting for other sociodemographic factors, severity of illness, functional status, and study site, African-Americans were less likely to receive any of five procedures on study day 1 and 3 (adjusted odds ratio [OR] 0.70; 95% confidence interval [CI] 0.60, 0.81). In addition, African-Americans had lower TISS scores on study day 1 and 3 (OR −1.8; 95% CI −1.3, −2.4) and lower estimated costs of hospitalization (OR −$2,805; 95% CI −$1,672, −$3,883). Results were similar after adjustment for patients’ preferences and physicians’ prognostic estimates. Differences in resource use were less marked after adjusting for the specialty of the attending physician but remained significant. In a subset analysis, cardiologists were less likely to care for African-Americans with congestive heart failure (p<.001), and cardiologists used more resources (p<.001). After adjustment for other sociodemographic factors, severity of illness, functional status, and study site, survival was slightly better for African-American patients (hazard ratio 0.91; 95% CI 0.84, 0.98) than for white or other race patients.

CONCLUSIONS: Seriously ill African-Americans received less resource-intensive care than other patients after adjustment for other sociodemographic factors and for severity of illness. Some of these differences may be due to differential use of subspecialists. The observed differences in resource use were not associated with a survival advantage for white or other race patients.

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References

  1. Weissman JS, Stern R, Fielding SL, Epstein AM. Delayed access to health care: risk factors, reasons, and consequences. Ann Intern Med. 1991;114:325–31.

    PubMed  CAS  Google Scholar 

  2. Blendon RJ, Aiken LH, Freeman HE, Corey CR. Access to medical care for black and white Americans. A matter of continuing concern. JAMA. 1989;261:278–81.

    Article  PubMed  CAS  Google Scholar 

  3. Ayanian JZ, Udvarhelyi IS, Gatsonis CA, Pashos CL, Epstein AM. Racial differences in the use of revascularization procedures after coronary angiography. JAMA. 1993;269:2642–6.

    Article  PubMed  CAS  Google Scholar 

  4. Wenneker MB, Epstein AM. Racial inequalities in the use of procedures for patients with ischemic heart disease in Massachusetts. JAMA. 1989;261:253–7.

    Article  PubMed  CAS  Google Scholar 

  5. Tunis SR, Bass EB, Klag MJ, Steinberg EP. Variation in utilization of procedures for treatment of peripheral arterial disease. A look at patient characteristics. Arch Intern Med. 1993;153:991–8.

    Article  PubMed  CAS  Google Scholar 

  6. Johnson PA, Lee TH, Cook EF, Rouan GW, Goldman L. Effect of race on the presentation and management of patients with acute chest pain. Ann Intern Med. 1993;118:593–601.

    PubMed  CAS  Google Scholar 

  7. Satariano ER, Swanson GM, Moll PP. Nonclinical factors associated with surgery received for treatment of early-stage breast cancer. Am J Public Health. 1992;82:195–8.

    Article  PubMed  CAS  Google Scholar 

  8. Buckle JM, Horn SD, Oates VM, Abbey H. Severity of illness and resource use differences among white and black hospitalized elderly. Arch Intern Med. 1992;152:1596–603.

    Article  PubMed  CAS  Google Scholar 

  9. Lynn J, Knaus WA. Background for SUPPORT. J Clin Epidemiol. 1990;43:1S-4S.

    Article  PubMed  Google Scholar 

  10. SUPPORT Principal Investigators. A controlled trial to improve care for seriously ill hospitalized patients: the study to understand prognosis and preferences for outcomes and risks of treatment support. JAMA. 1995;274:1591–8.

    Article  Google Scholar 

  11. Knaus WA, Wagner DP, Draper EA, et al. The APACHE III prognostic system. Risk prediction of hospital mortality for critically ill hospitalized adults. Chest. 1991;100:1018–38.

    Google Scholar 

  12. Knaus WA, Draper EA, Zimmerman JE. APACHE II: a severity of disease classification system. Crit Care Med. 1985;13:818–29.

    Article  PubMed  CAS  Google Scholar 

  13. Katz S, Ford AB, Moskowitz RW, Jackson BA, Jaffe MW. Studies of illness in the aged. The index of ADL: a standardized measure of biological and psychosocial function. JAMA. 1963;185:914–9.

    PubMed  CAS  Google Scholar 

  14. Landefeld CS, Phillips RS, Bergner M. Patient characteristics in SUPPORT: functional status. J Clin Epidemiol. 1990;43(suppl):37S-39S.

    Article  PubMed  Google Scholar 

  15. Hlatky M, Boirev RE, Higginbotham MB, et al. A brief self-administered questionnaire to determine functional capacity (The Duke Activity Status Index). Am J Cardiol. 1989;64:651–4.

    Article  PubMed  CAS  Google Scholar 

  16. Phillips RS, Goldman L, Bergner M. Patient characteristics in SUPPORT: activity status and cognitive function. J Clin Epidemiol. 1990;43(suppl):33S-36S.

    Article  PubMed  Google Scholar 

  17. Keene AR, Cullen DJ. Therapeutic intervention scoring system: update 1983. Crit Care Med. 1983;11:1–3.

    Article  PubMed  CAS  Google Scholar 

  18. Knaus WA, Harrell FE, Lynn J, et al. The SUPPORT prognostic model: prediction of survival for seriously ill hospitalized adults. Ann Intern Med. 1995;122:191–203.

    PubMed  CAS  Google Scholar 

  19. Covinsky KE, Goldman L, Cook EF, et al. The impact of serious illness on patients’ families. JAMA. 1994;272:1839–44.

    Article  PubMed  CAS  Google Scholar 

  20. Wu AW, Damiano AM, Lynn J, et al. Predicting future functional status for seriously ill hospitalized adults. The SUPPORT prognostic model. Ann Intern Med. 1995;122:343–50.

    Google Scholar 

  21. Walker SH, Duncan OB. Estimation of the probability of an event as a function of several independent variables. Biometrika. 1967;54:167–79.

    PubMed  CAS  Google Scholar 

  22. Cox DR. Regression models and life tables (with discussion). J R Stat Soc B. 1972;34:187–220.

    Google Scholar 

  23. Black-white disparities in health care. JAMA. 1990;263:2344–6.

  24. Haywood LJ. Coronary heart disease mortality/morbidity and risk in blacks, II: access to medical care. Am Heart J. 1984;108:794–6.

    Article  PubMed  CAS  Google Scholar 

  25. Haywood LJ. Hypertension in minority populations. Access to care. Am J Med. 1990;88:17S-20S.

    Article  PubMed  CAS  Google Scholar 

  26. Woolhandler S, Himmelstein DU, Silber R, Bader M, Harnly M, Jones AA. Medical care and mortality: racial differences in preventable deaths. Int J Health Serv. 1985;15:1–22.

    Article  PubMed  CAS  Google Scholar 

  27. Horner RD, Lawler FH, Hainer BL. Relationship between patient race and survival following admission to intensive care among patients of primary care physicians. Health Serv Res. 1991;26:531–42.

    PubMed  CAS  Google Scholar 

  28. Williams JF, Zimmerman JE, Wagner DP, Hawkings M, Knaus WA. African-American and white intensive care unit admissions: Is there a difference in therapy and outcome? Crit Care. 1995;23:626–36.

    Article  CAS  Google Scholar 

  29. 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. JAMA. 1994;271:1175–80.

    Article  PubMed  CAS  Google Scholar 

  30. Greenfield S, Nelson EC, Zubkoff M, et al. Variations in resource utilization among medical specialties and systems of care. Results from the Medical Outcomes Study. JAMA. 1992;267:1624–30.

    Article  PubMed  CAS  Google Scholar 

  31. Childs AW, Hunter ED. Non-medical factors influencing use of diagnostic x-ray by physicians. Med Care. 1972;10:323–35.

    Article  PubMed  CAS  Google Scholar 

  32. Elsenberg JM, Nicklin D. Use of diagnostic services by physicians in community practice. Med Care. 1981;10:297–309.

    Article  Google Scholar 

  33. Pineault R. The effect of medical training factors on physician utilization behavior. Med Care. 1977;15:51–67.

    Article  PubMed  CAS  Google Scholar 

  34. Noren J, Frazier T, Altman I, DeLozier J. Ambulatory medical care: a comparison of internists and family-general practitioners. N Engl J Med. 1990;302:11–6.

    Article  Google Scholar 

  35. Ward MM, Leigh JP, Fries JF. Progression of functional disability in patients with rheumatoid arthritis; associations with rheumatology subspecialty care. Arch Intern Med. 1993;153:2229–37.

    Article  PubMed  CAS  Google Scholar 

  36. Chouillet AM, Bell CMJ, Hiscox JG. Management of breast cancer in southeast England. BMJ. 1994;308:168–71.

    PubMed  CAS  Google Scholar 

  37. The GUSTO Investigators. An international randomized trial comparing four thrombolytic strategies for acute myocardial infarction. N Engl J Med. 1993;329:673–82.

    Article  Google Scholar 

  38. Mark DB, Naylor CD, Hlatky MA, et al. Use of medical resources and quality of life after acute myocardial infarction in Canada and the United States. N Engl J Med. 1994;331:1130–5.

    Article  PubMed  CAS  Google Scholar 

  39. Ayanian JZ, Hauptman PJ, Guadagnoli E, Antman EM, Pashos CL, McNeil BJ. Knowledge and practices of generalist and specialist physicians regarding drug therapy for acute myocardial infarction. N Engl J Med. 1994;331:1136–42.

    Article  PubMed  CAS  Google Scholar 

  40. Phillips RS, Wenger NS, Teno J, et al., for the SUPPORT Investigators. Seriously ill patients’ choices about cardiopulmonary resuscitation: correlates and outcomes. Am J Med. 1996;100:128–37.

    Article  PubMed  CAS  Google Scholar 

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The opinions and findings contained in this manuscript are those of the authors and do not necessarily represent the views of the Robert Wood Johnson Foundation or their Board of Trustees.

Financial support for this study was provided by the Robert Wood Johnson Foundation.

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Phillips, R.S., Hamel, M.B., Teno, J.M. et al. Race, resource use, and survival in seriously III hospitalized adults. J Gen Intern Med 11, 387–396 (1996). https://doi.org/10.1007/BF02600183

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