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Basics of Stratifying for Severity of Illness

Published online by Cambridge University Press:  02 January 2015

Peter A. Gross
Peter A. Gross*
Affiliation:
Hackensack University Medical Center, New Jersey Medical School, Newark, New Jersey
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Abstract

Conventional wisdom suggests that those who assess healthcare processes and outcomes always should stratify cases by severity of illness; however, infection control personnel should analyze each quality assessment tool with and without severity adjustment and determine whether such adjustment is necessary. This article briefly reviews severity adjustments for diseases or procedures involving specific organ systems, as well as those applicable to all diseases, including the commercially available systems. Also discussed is whether and how these various systems for severity adjustment can be compared. Finally, the article will provide selected references for individuals who will use these scoring systems and need more information.

Type
Practical Healthcare Epidemiology
Information
Infection Control & Hospital Epidemiology , Volume 17 , Issue 10 , October 1996 , pp. 675 - 686
Copyright
Copyright © The Society for Healthcare Epidemiology of America 1996 

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References

1. Shakespeare, W. Hamlet. Act III; scene 1; line 59.Google Scholar
2. Localio, AR, Hamory, BH, Sharp, TJ, Weaver, SL, TenHave, TR, Landis, JR. Comparing hospital mortality in adult patients with pneumonia: a case study of statistical methods in a managed care program. Ann Intern Med 1995;122:125–132.CrossRefGoogle Scholar
3. Iezzoni, LI. Risk and outcomes and dimensions of risk. In: Iezzoni, LI, ed. Risk Adjustment for Measuring Health Care Outcome. Ann Arbor, MI: Health Administration Press; 1994:1–118.Google Scholar
4. Iezzoni, LI, Ash, AS, Shwartz, M, Daley, J, Hughes, JS, Mackiernan, YD. Predicting who dies depends on how severity is measured: implications for evaluating patient outcomes. Ann Intern Med 1995;123:763–770.CrossRefGoogle ScholarPubMed
5. The Criteria Committee of the New York Heart Association, Inc. Diseases of the Heart and Blood Vessels; Nomenclature and Criteria for Diagnosis. 6th ed. Boston, MA: Little, Brown and Co; 1964.Google Scholar
6. Lemmedu, DK, Kepm, JW, Judkins, HG, Gosselin, AJ, Killp, T. Complications of coronary arteriography from the Collaborative Study of Coronary Artery Surgery (CASS). Circulation 1979;59:11–15.Google Scholar
7. Goldman, L, Hashimoto, B, Cook, FD, Loscalzo, A. Comparative reproducibility and validity of systems for assessing cardiovascular functional class: advantages of a new specific activity scale. Circulation 1981;64:1227–1234.CrossRefGoogle ScholarPubMed
8. Bergelson, BA, Jacobs, AK, Cupples, LA, et al. Prediction of risk for hemodynamic compromise during percutaneous transluminal coronary angioplasty. Am J Cardiol 1992;70:1540–1545.CrossRefGoogle ScholarPubMed
9. Ryan, TJ, Baumn, WB, Kennedy, JW. ACC/AHA Task Force Report: guidelines for percutaneous transluminal coronary angioplasty—a report of the American College of Cardiology/American Heart Association Task Force on Assessment of Diagnostic and Therapeutic Cardiovascular Procedures (Committee on Percutaneous Transluminal Coronary Angioplasty). J Am Coll Cardiol 1993;22:2033–2052.CrossRefGoogle Scholar
10. O'Connor, GT, Plume, SK, Olmstead, EM, et al. Multivariate prediction of in-hospital mortality associated with coronary artery bypass graft surgery: in-hospital mortality and CABG. Circulation 1992;85:2110–2118.CrossRefGoogle Scholar
11. Hannan, EL, Kilburn, H, Racz, M, Shields, E, Chassin, MR. Improving the outcomes of coronary artery bypass surgery in New York state. JAMA 1994;271:761–766.CrossRefGoogle ScholarPubMed
12. Altemeier, WA, Burke, JF, Pruitt, BA, Sandusky, WE, eds. Manual on Control of Infection in Surgical Patients. Philadelphia, PA: JB Lippincott; 1976.Google Scholar
13. Haley, RW, Culver, DH, Morgan, WM, et al. Identifying patients at high risk of surgical wound infection. A simple multivariate index of patient susceptibility and wound contamination. Am J Epidemiol 1985;121:206–215.CrossRefGoogle ScholarPubMed
14. Culver, DH, Horan, TC, Gaynes, RP, et al. Surgical wound infection rates by wound class, operative procedure, and patient risk index. Am J Med 1991;91(suppl 3B):152S–157S.CrossRefGoogle ScholarPubMed
15. Kollef, MH. Ventilator-associated pneumonia. A multivariate analysis. JAMA 1993;270:1965–1970.CrossRefGoogle ScholarPubMed
16. Marie, TJ. Community-acquired pneumonia. Clin Infect Dis 1994;18:501–515.CrossRefGoogle Scholar
17. Fine, MJ, Smith, DN, Singer, DE. Hospitalization decision in patients with community-acquired pneumonia: a prospective cohort study. Am J Med 1990;89:713–721.CrossRefGoogle ScholarPubMed
18. Chassin, MR, Park, RE, Lohr, KN, et al. Differences among hospitals in Medicare patient mortality. Health Serv Res 1989;24:1.Google ScholarPubMed
19. Fine, MJ, Singer, DE, Phelps, AL, Hanusa, BH, Kapoor, WN. Differences in length of hospital stay in patients with community-acquired pneumonia: a prospective four-hospital study. Med Care 1993;31:371–380.CrossRefGoogle ScholarPubMed
20. McCabe, WR, Jackson, GG. Gram-negative bacteremia, II: clinical, laboratory, and therapeutic observations. Arch Intern Med 1962;110:847–855.CrossRefGoogle Scholar
21. Setia, U, Gross, PA. Bacteremia in a community hospital. Spectrum and mortality. Arch Intern Med 1977;137:1698–1701.CrossRefGoogle Scholar
22. Rabeneck, L, Wray, NP. Predicting the outcomes of human immunodeficiency virus infection. Arch Intern Med 1993;153:2749–2755.CrossRefGoogle ScholarPubMed
23. Centers for Disease Control and Prevention. 1993 revised classification system for HIV infection and expanded surveillance case definition for AIDS among adolescents and adults. MMWR 1992;41(No. RR-17):1–19.Google Scholar
24. MacDonell, KB, Chimel, JS, Goldsmith, J, et al. Prognostic usefulness of the Walter Reed staging classification for HIV infection. J Acquir Immune Defic Syndr 1988;1:367–374.Google ScholarPubMed
25. Mayer, RJ. Gastrointestinal Cancer, VIII. In: Rubenstein, E, Federman, DD, eds. Scientific American Medicine. New York, NY: Scientific American Medicine Inc; 1986:1–18.Google Scholar
26. Feinstein, AR, Wells, CK. A clinical-severity staging system for patients with lung cancer. Medicine 1990;69:1–33.CrossRefGoogle ScholarPubMed
27. Steinberg, W, Tenner, S. Acute pancreatitis. N Engl J Med 1994;330:1198–1210.CrossRefGoogle ScholarPubMed
28. Ranson, JHC, Rifkind, KM, Roses, DF, Fink, SD, Eng, K, Spencer, FC. Prognostic signs and the role of operative management in acute pancreatitis. Surg Gynecol Obstet 1974;139:69–81.Google ScholarPubMed
29. Satariano, WA, Ragland, DR. The effect of comorbidity on 3-year survival of women with primary breast cancer. Ann Intern Med 1994;120:104–110.CrossRefGoogle ScholarPubMed
30. Roher, JE. Developing risk-adjusted monitoring systems: illustration of an approach. Clin Perform Qual Health Care 1994;2:84–91.Google Scholar
31. Tobacman, JK. Assessment of comorbidity: a review. Clin Perform Qual Health Care 1994;2:23–32.Google ScholarPubMed
32. LeGall, JR, Lemeshow, S, Saulnier, F. A new simplified acute physiology score (SAPS II) based on a European/North American multicenter study. JAMA 1993;270:2957–2964.CrossRefGoogle Scholar
33. Gross, PA. Use of severity of illness indices. In: Mayhall, G, ed. Hospital Epidemiology and Infection Control. Baltimore, MD: Williams & Wilkins; 1996:90–103.Google Scholar
34. Knaus, WA, Draper, EA, Wagner, DP, Zimmermn, JE. APACHE II: a severity of disease classification system. Crit Care Med 1985;9:591–597.CrossRefGoogle Scholar
35. Moreau, R, Soupison, T, Vauquelin, P, Derrida, S, Beaucur, H, Sicto, C. Comparison of two simplified severity scores SAPS and APACHE (II) for patients with acute myocardial infarction. Crit Care Med 1989;17:409–413.CrossRefGoogle ScholarPubMed
36. McMahon, LF, Hayward, RA, Bernard, AM, Rosevear, JS, Weissfeld, LA. Apache-L: a new severity of illness adjuster for inpatient medical care. Med Care 1992;30:445–452.CrossRefGoogle ScholarPubMed
37. Kruse, JA, Thil-Baharozian, MC, Carlson, RW. Comparison of clinical assessment with APACHE II for predicting mortality risk in patients admitted to a medical intensive care unit. JAMA 1988;260:1739–1742.CrossRefGoogle ScholarPubMed
38. Zimmerman, JE, ed. APACHE III study design: analytic plan for evaluation of severity and outcome in intensive care units. Crit Care Med 1988;17(12 pate 2):169S–221S.Google Scholar
39. Knaus, WA, Douglas, PW, Draper, EA, et al. Clinical investigations in critical care: the APACHE III prognostic system. Risk prediction of hospital mortality for critically ill hospitalized adults. Chest 1991;100:1619–1636.CrossRefGoogle Scholar
40. Knaus, WA, Wagner, DP, Lynn, J. Short-term mortality predictions for critically ill hospitalized adults: science and ethics. Science 1991;254:345–488.CrossRefGoogle ScholarPubMed
41. Brewster, AC, Karlin, BG, Hyde, LA, et al. MedisGroups: a clinically based approach to classifying hospital patients at admission. Inquiry 1985;12:377–387.Google Scholar
42. Iezzoni, LI, Ash, AS, Cobb, JL, Moskowitz, MA. Admission MedisGroups score and the cost of hospitalizations. Med Care 1988;26:1068–1080.CrossRefGoogle ScholarPubMed
43. Iezzoni, LI, Hotchkin, EK, Ash, AS, Schwartz, M, Mackiernan, Y. MedisGroups data bases: the impact of data collection guidelines on predicting in-hospital mortality. Med Care 1993;31:277–283.CrossRefGoogle ScholarPubMed
44. Horn, SD, Sharkey, PD, Buckle, JM, Backofen, JE, Averill, RF, Horn, RA. The relationship between severity of illness and hospital length of stay and mortality. Med Care 1991;29:305–317.CrossRefGoogle ScholarPubMed
45. Averill, RF, McGuire, TE, Manning, BE, Fowler, DA, Horn, SD, Dickson, PS. A study of the relationship between severity of illness and hospital cost in New Jersey hospitals. Health Serv Res 1992;27:587–606.Google ScholarPubMed
46. Coffee, RM, Goldfarb, MKG. DRGs and disease staging for reimbursing Medicare patients. Med Care 1986;24:814–829.CrossRefGoogle Scholar
47. Gonnella, JS, Hornbrook, MC, Louis, DZ. Staging of disease. A case-mix measurement. JAMA 1984;251:637–646.CrossRefGoogle ScholarPubMed
48. The Guide to Hospital Performance. Baltimore, MD: HCIA Inc;1993.Google Scholar
49. Young, WW, Macioce, DP. Product line analyses using PMCs versus DRGs. Public Budgeting and Finance Management 1992;4:83–106.Google Scholar
50. Kenkel, PJ. Projects serving up a data smorgasbord. Mod Healthc 1993.Google Scholar
51. Gross, PA. Severity of illness and other cofounders of quality measurement. In Wenzel, R, ed. Assessing Quality Health Care: A Perspective for Clinicians. Baltimore, MD: Williams & Wilkins; 1992:101–123.Google Scholar
52. Thomas, JW, Ashcraft, MLF. Measuring severity of illness: six severity systems and their ability to explain cost variations. Inquiry 1991;28:39–55.Google ScholarPubMed
53. Patient classification systems: an evaluation of the state of the art. Vol 1. Case Mix Research. Kingston, Ontario, Canada: Queen's University; 1991.Google Scholar
54. Iezzoni, LI, Hotchkin, EK, Ash, AS, Schwartz, M, Mackiernan, Y. MedisGroups databases: the impact of data collection guidelines on predicting in-hospital mortality. Med Care 1993;31:277–283.CrossRefGoogle ScholarPubMed
55. Hayward, RA, McMahon, LF, Bernard, AM. Evaluating the care of general medicine inpatients: how good is implicit review? Ann Intern Med 1993;118:550–556.CrossRefGoogle ScholarPubMed
56. Wennberg, JE. Future directions for small area variations. Med Care 1993;31:YS75–YS80.CrossRefGoogle ScholarPubMed
57. McMahon, LF, Newbold, R. Variation in resource use within diagnosis-related groups: the effect of severity of illness and physician practice. Med Care 1986;24:388–397.CrossRefGoogle ScholarPubMed