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Prognostic Scoring Systems: Facing Difficult Decisions with Objective Data

Published online by Cambridge University Press:  29 July 2009

Kent Sasse
Kent Sasse
Affiliation:
University of California, San Francisco
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Extract

In the United States, at least 6% of all hospital beds are in the intensive care unit (ICU) or coronary care unit. The cost of treating a patient in an intensive care unit averages from $2,000 to $3,500 per day. At least 10–40% of intensive care patients will not survive to hospital discharge. Today, every major category of disease may be found in the modern ICU; common diagnoses are septicemia, postsurgical complications, cerebrovascular accidents, gastrointestinal bleeding, neoplasia, and respiratory failure. ICUs employ some of the most sophisticated medical technology, routinely monitoring the cardiopulmonary performance of patients and often providing assisted ventilation. ICUs are high intensity in terms of their staffing, involving 24-hour physician supervision and nurse:patient ratios from 1:3 to 1:1.

Type
Special Section: Medical Futility: Demands, Duties, and Dilemmas
Information
Cambridge Quarterly of Healthcare Ethics , Volume 2 , Issue 2 , Spring 1993 , pp. 185 - 191
Copyright
Copyright © Cambridge University Press 1993

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References

Notes

1. Berenson, RA. Intensive Care Units (ICUs): Clinical Outcomes, Costs, and Decisionmaking (OTA-HCS28). Washington, D.C.: Office of Technology Assessment, U.S. Congress, 11 1984.Google Scholar

2. Osborne, ML. Physician decisions regarding life support in the intensive care unit. Chest 1992;101:217–24.CrossRefGoogle ScholarPubMed

3. Snider, GH. Historical perspective on mechanical ventilation: from simple life support to ethical dilemma. American Review of Respiratory Disease 1989;140:52–7.CrossRefGoogle ScholarPubMed

4. Knas, WA, Draper, EA, Wagner, DP. An evaluation of outcome from intensive care in major medical centers. Annals of Internal Medicine 1986;104:410–8.CrossRefGoogle Scholar

5. Knas, WA, Draper, EA, Wagner, DP. Prognosis in acute organ system failure. Annals of Surgery 1985;202(6):685–93.CrossRefGoogle Scholar

6. Schuster, DP, Marion, JM. Precedents for meaningful recovery during treatment in a medical intensive care unit: outcome in patients with hematologic malignancy. American Journal of Medicine 1983;75:402–8.CrossRefGoogle Scholar

7. Cullen, DJ, Civetta, JM, Briggs, BA, et al. Therapeutic intervention scoring system. Critical Care Medicine 1974;2:57.CrossRefGoogle ScholarPubMed

8. Keene, AR, Cullen, DJ. Therapeutic intervention scoring system: update 1983. Critical Care Medicine 1983;11(1):1–3.CrossRefGoogle ScholarPubMed

9. Cullen, DJ, Keene, R, Waternax, C, et al. Objective, quantitative measurement of severity of illness in critically ill patients. Critical Care Medicine 1984;12(3):155–60.CrossRefGoogle ScholarPubMed

10. Lemeshow, S, Teres, D, Pastides, H, et al. A method for predicting survival and mortality of ICU patients using objectively derived weights. Critical Care Medicine 1985;13(7):519–25.CrossRefGoogle Scholar

11. Teres, D, Lemeshow, S, Avrunin, JS, et al. Validation of the mortality prediction model for ICU patients. Critical Care Medicine 1987;15(3):208.CrossRefGoogle ScholarPubMed

12. Shoemaker, WC, Chang, P, Czer, L, et al. Cardiorespiratory monitoring in postoperative patients: prediction of outcome and severity of illness. Critical Care Medicine 1979;7(5):237–42.CrossRefGoogle ScholarPubMed

13. Shoemaker, WC, Appel, PL, Bland, R, et al. Clinical trial of an algorithm for outcome prediction in acute circulatory failure. Critical Care Medicine 1982;10(6):390.CrossRefGoogle ScholarPubMed

14. Bland, RD, Shoemaker, WC. Probability of survival as a prognostic and severity of illness score in critically ill surgical patients. Critical Care Medicine 1985;13(2):91–5.CrossRefGoogle ScholarPubMed

15. Snyder, JV, McGuirk, M, Grenvik, A, et al. Outcome of intensive care: an application of a predictive model. Critical Care Medicine 1981;9(8):598–603.CrossRefGoogle ScholarPubMed

16. Knas, WA, Zimmerman, JE, Wagner, DP, et al. APACHE - acute physiology and chronic health evaluation: a physiologically based classification system. Critical Care Medicine 1981;9(8):591–7.CrossRefGoogle Scholar

17. Le Gall, Jr, Loirat, P, Alperovitch, A, et al. A simplified acute physiology score for ICU patients. Critical Care Medicine 1984;12(11)975–7.CrossRefGoogle ScholarPubMed

18. Knaus, WA, Draper, E, Wagner, DP, et al. APACHE II: a severity of disease classification system. Critical Care Medicine 1985;13(10):818–29.CrossRefGoogle ScholarPubMed

19. 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;100:1619–36.CrossRefGoogle ScholarPubMed

20. All of these categories have been proposed by others; specifically, Douglas Wagner in his April 1992 talk at the International Bioethics Institute Conference in San Francisco proposed three very similar primary applications.

21. Knaus, WA, Wagner, DP, Lynn, J. Short–term mortality predictions for critically ill hospitalized adults: science and ethics. Science 1991;254:389–94.CrossRefGoogle Scholar

22. Knaus, WA, Draper, EA, et al. Evaluating outcome from intensive care: a preliminary multihospital comparison. Critical Care Medicine 1982;10(8):491–6.CrossRefGoogle ScholarPubMed

23. Marshall, MF, Schwenzer, KJ, Orsina, M, et al. Influence of political power, medical provincialism, and economic incentives on the rationing of surgical intensive care unit beds. Critical Care Medicine 1992;20(3):387–94.CrossRefGoogle ScholarPubMed

24. See note 21. Knaus, et al. 1991;254:389–94.Google Scholar

25. Callahan, D. What Kind of Life. New York: Simon and Schuster, 1990.Google Scholar

26. Darman, Pear R. forecasts dire health costs. The New York Times. 1991 04 17.Google Scholar

27. Englehardt, HT, Rie, MA. Intensive care units, scarce resources, and conflicting principles of justice. Journal of the American Medical Association 1986;255:1159–64.CrossRefGoogle Scholar

28. Welch, G, Larson, E. Dealing with limited resources: the Oregon decision to curtail funding for organ transplantation. New England Journal of Medicine 1989;319:171–3.CrossRefGoogle Scholar

29. Alameda County Health Care Services Agency and Bioethics Consultation Group. Rationing Health Care: A Rational Approach. 06 1989.Google Scholar

30. Callahan, D. Setting Limits: Medical Goals in a Changing Society. New York: Simon and Schuster, 1987.Google Scholar

31. Hollib, AI, Fink, DJ, Murphy, GP. American Cancer Society Textbook of Clinical Oncology. Atlanta: The American Cancer Society, 1991:392.Google Scholar

32. Applebaum, FR, Sullivan, KM, Buckner, CD, et al. Treatment of malignant lymphoma in 100 patients with chemotherapy, total body irradiation, and marrow transplantation. Journal of Clinical Oncology 1987;5:1340–7.CrossRefGoogle Scholar

33. See note 5. Knaus, et al. 1985;202(6):685–93.Google Scholar

34. Chang, RW, Jacobs, S, Lee, B. Use of APACHE II severity of disease classification to identify intensive care unit patients who would not benefit from total parenteral nutrition. Lancet 1986 06 28:1483–6.CrossRefGoogle Scholar