Cardiac surgery "report card" modeling

Current Opinion in Critical Care

Volumn 3, Issue 3, 1997, Pages 169-174

  Higgins, Thomas L ^a  

^a BAYSTATE MEDICAL CENTER   (United States)

Author keywords

[No Author keywords available]

Indexed keywords

EID: 1842687969     PISSN: 10705295     EISSN: None     Source Type: Journal    
DOI: 10.1097/00075198-199706000-00002     Document Type: Article

References (39)

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3. Cleveland Health Quality Choice: Summary Report #4. Cleveland, Ohio: Quality Information Management Corporation; 1994.
4. Nugent WC, Schults WC: Playing by the numbers: how collecting outcomes data changed my life. Ann Thorac Surg 1994, 58:1866-1868.
5. Hattler BG, Madia C, Johnson C, Armitage JM, Hardesty RL, Kormos RL, Pham SM, Payne DN, Griffith BP: Risk stratification using the Society of Thoracic Surgeons Program. Ann Thorac Surg 1994, 58:1348-1352.
6. Rosenthal E: Heart bypasses safer, study shows. New York Times, June 7, 1995:B5.
7. Orr RK, Maini BS, Sottile FD, Dumas EM, O'Mara P: A comparison of four severity-adjusted models to predict mortality after coronary artery bypass surgery. Arch Surg 1995, 130:301-306. An independent evaluation and validation of four preoperative mortality models. Discrimination and calibration of the models were examined and found to differ from the original reports. All models performed adequately, but some overpredict whereas others underpredict mortality, making the applicability of these models for individual patients questionable.
8. Omoigui NA, Miller DP, Brown KJ, Annan K, Cosgrove D, Lytle B, Loop F, Topol E: Outmigration for coronary bypass surgery in an era of public dissemination of clinical outcomes. Circulation 1996, 93:27-33. This study concludes that the number of out-of-state referrals may have increased with public release of data in New York State. This conclusion has been challenged by Chassin et al. (N Engl J Med 1996, 331:394-398).
9. Omoigui NA, Miller DP, Brown KJ, Annan K, Cosgrove D, Lytle B, Loop F, Topol E: Outmigration for coronary bypass surgery in an era of public dissemination of clinical outcomes. Circulation 1996, 93:27-33. This study concludes that the number of out-of-state referrals may have increased with public release of data in New York State. This conclusion has been challenged by Chassin et al. (N Engl J Med 1996, 331:394-398).
10. Hannan EL, Siue AL, Kumar D, Kilburn H, Chassin MR: The decline in coronary artery bypass surgery mortality in New York State: the role of surgeon volume. JAMA 1995, 273:209-213.
11. Higgins TL, Estafanous FG, Loop FD, Beck GJ, Blum JM, Paranandi L: Stratification of morbidity and mortality outcome by preoperative risk factors in coronary artery bypass patients: a clinical severity score. JAMA 1992, 67:2344-2348.
12. Higgins TL, Estafanous FG, Starr NJ, Beck GJ, Lee JC, Knaus WA, Loop FD: Risk-stratification following coronary artery bypass surgery: an ICU admission score [abstract]. Anesthesiology 1995, 83:A215.
13. Knaus WA, Wagner DP, Draper EA, Zimmerman JE, Bergner M, Bastos PG, Sirio CA, Murphy DJ, Lotring T, Damiano A: The APACHE III prognostic system: risk prediction of hospital mortality for critically III hospitalized adults. Chest 1991, 100:1619-1636.
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15. Turner JS, Mudaliar YM, Change RWS, Morgan CJ: Acute Physiology and Chronic Health Evaluation (APACHE II) scoring in a cardiothoracic intensive care unit. Crit Care Med 1991, 19:1266-1270.
16. Becker RB, Zimmerman JE, Knaus WA, Wagner DP, Seneff NG, Draper EA, Higgins TL, Estafanous FG, Loop FD: The use of APACHE III to evaluate ICU length of stay, resource use and mortality after coronary artery surgery. J Cardiovasc Surg 1995, 36:1-11.
17. Turner JS, Morgan CJ, Thakrar B, Pepper JR: Difficulties in predicting outcome in cardiac surgery patients. Crit Care Med 1996, 23:1843-1850. Good review of factors that predict outcome; models are developed for mortality and ICU length-of-stay based on variables available at the time of ICU admission.
18. Blackstone EH: Outcome analysis using hazard function methodology. Ann Thorac Surg 1996, 61:S2-S7. This study provides a method for separately considering early (perioperative) deaths, late events, and the constant risk of an age-, race-, and sex-matched general population. Compartmental analyses, familiar from pharmacokinetic analysis, are used in place of mathematics to illuminate the hazard analysis methodology.
19. Cullen DJ, Civetta JM, Briggs BA: Therapeutic Intervention Scoring System: a method for quantitative comparison of patient care. Crit Care Med 1974, 2:57-60.
20. Miranda DR, deRijk A, Schaufeli W: Simplified Therapeutic Intervention Scoring System: the TISS-28 items-results from a multicenter study. Crit Care Med 1996, 24:64-73. Although not specific to the cardiac surgical population, this score does provide a streamlined assessment of nursing activity for ICU patients. Calculations are provided to determine nursing workload, which may be helpful in the management of nursing staffing levels in the postoperative ICU.
21. Nielsen D, Sellgren J, Ricksten SE: Quality of life after cardiac surgery complicated by multiple organ failure. Crit Care Med 1997, 25:52-57. This article applies the Nottingham Health Profile to 47 patients surviving multiple organ failure after cardiac surgery at 1 year after discharge. A high percentage of patients report problems in activities of daily living and a worse overall quality-of-life score than matched control subjects.
22. Zhu BP, Lemeshow S, Hosmer DW, Klar J, Teres D: Factors affecting the performance of the models in the Mortality Probability Model II system and strategies of customization: a simulation study. Crit Care Med 1996, 24:57-63. Different mortality rates and sample sizes were simulated from an existing data set, and effects on model performance evaluated. Goodness-of-fit tests and receiver operating characteristic curve areas showed that the models were sensitive to differences in hospital mortality, confirming the value of models as quality assurance tools. The further the hospital mortality rate diverged from the original rate, the worse the performance of the model. Sample size is also an important consideration.
23. Clark RE: Calculating risk and outcome: the Society of Thoracic Surgeons database. Ann Thorac Surg 1996, 62:S2-S5. Reviews various approaches to the calculation of risk and specific requirements for building risk-calculation models.
24. Paiement B, Pelletier C, Dryda I, Maillé JG, Boulanger M, Taillefer J, Sahab P, Delorme M, Dupont E: A simple classification of risk in cardiac surgery. Can Anaesth Soc J 1983, 30:61-66.
25. Tuman KJ, McCarthy RJ, March RJ, Najofi H, Ivankovach AD: Morbidity and duration of ICU stay after cardiac surgery: a model for preoperative risk assessment Chest 1992, 102:36-41.
26. Tu JV, Jaglal SB, Naylor CD, the Steering Committee of the Provincial Adult Cardiac Care Network of Ontario: Multicenter validation of a risk index for mortality, intensive care unit stay, and overall hospital length of stay after cardiac surgery. Circulation 1995, 91:677-681.
27. Personnet V, Dean D, Bernstein AD: A method of uniform stratification of risk for evaluating the results of surgery in acquired adult heart disease. Circulation 1989, 79(suppl 1)1:3-12.
28. Parsonnet V, Bernstein AD, Gera M: Clinical usefulness of risk-stratified outcome analysis in cardiac surgery in New Jersey. Ann Thorac Surg 1996, 61:S8-S11. This report discusses changes to the original model, but unfortunately does not give values to calculate risk using the revised model. This version demonstrates a significant decline in length of postoperative stay, consistent with the implementation of accelerated recovery protocols in the past few years.
29. Edwards FH, Clark RE, Schwartz M: Coronary artery bypass grafting: the Society of Thoracic Surgeons National Database experience. Ann Thorac Surg 1994, 57:12-19.
30. Hattler BR, Madia C, Johnson C, et al.: Risk stratification using the Society of Thoracic Surgeons Program. Ann Thorac Surg 1994, 58:1348-1352.
31. Estafanous FG, Higgins TL, Tekyi-Mensah S, Starr NJ: Changes in preoperative severity and ICU morbidity with coronary artery bypass [abstract]. Crit Care Med 1995, 23:A54.
32. Koch CG, Higgins TL, Capdeville M, Maryland P, Leventhal M, Starr NJ: The risk of coronary artery surgery in women: a matched comparison using preoperative severity of illness scoring. J Cardiothorac Vasc Anesth 1996, 10:839-843. The authors demonstrate the utility of severity scoring in comparing populations with different baseline characteristics.
33. O'Connor GT, Plume SK, Olmstead EM, Coffin LH, Morton JR, Maloney CT, Nowicki ER, Levy DG, Tryzelaar JF, Hernandez F: Multivariate prediction of in-hospital mortality associated with coronary artery bypass graft surgery. Circulation 1992, 85:2110-2116.
34. Chassin NM, Hannan EL, DeBuono BA: Benefits and hazards of reporting medical outcomes publicly. N Engl J Med 1996, 331:394-398. Excellent overview of the New York State Cardiac Surgery Reporting System, and the pluses and pitfalls of public data release.
35. Murphy-Filkins RL, Teres D, Lemeshow S, Hosmer DW: Effect of changing patient mix on the performance of an intensive care unit severity-of-illness model: how to distinguish a general from a specialty intensive care unit Crit Care Med 1996, 24:1968-1973. This paper develops the concept of "critical percentages" and demonstrates what happens when these critical percentages are exceeded in a patient population. Highly specialized ICU's (or, by extension, cardiac surgical programs) may find that general severity models are not accurate in estimating hospital mortality.
36. Loop FD, Higgins TL, Panda R, Pearce G, Estafanous FG: Myocardial protection during cardiac operations. J Thorac Cardiovasc Surg 1992, 104:608-614.
37. Green J, Wintfeld N: Report cards on cardiac surgeons: assessing New York State's approach. N Engl J Med 1996, 332:1229-1232. An important "Sounding Board" article that raises important questions about the New York State Cardiac Surgery Reporting System.
38. Crawford FA, Anderson RP, Clark RE, Grover FL, Kouchoukos NT, Waldhausen JA, Wilcox BR [for the Ad Hoc Committee on Cardiac Surgery Credentialing of the Society of Thoracic Surgeons]: Volume requirements for cardiac surgery credentialing: a critical examination. Ann Thorac Surg 1996, 61:12-16. A review of the literature and the Society of Thoracic Surgeons data on the impact of individual surgical volume on outcome. The authors conclude that case volume should not be used as a criterion for credentialing by hospitals or managed care groups.
39. Grover FL, Hammermeister KE, Shroyer ALW: Quality initiatives and the power of the database: What they are and how they run. Ann Thorac Surg 1995, 60:1514-1521.