Browsing by Author "Hammermeister, Karl E."
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- ItemAssessment of predictive models for binary outcomes: an empirical approach using operative death from cardiac surgery(Wiley, 1994) Marshall Rivera, Guillermo; Grover, Frederick L.; Henderson, William G.; Hammermeister, Karl E.Predictive models in medical research have gained popularity among physicians as an important tool in medical decision making. Eight methodological strategies for creating predictive models are compared in a large, complex data base consisting of preoperative risk and operative outcome data on 12,712 patients undergoing coronary artery bypass grafting and entered into the Department of Veterans Affairs Cardiac Surgery Risk Assessment Program between April 1987 and March 1990. The models under consideration were developed to predict operative death (any death within 30 days following the surgical procedure or later if the result of a perioperative complication). The two strategies with the best predictive power among the eight examined were stepwise logistic regression alone and data reduction by cluster analysis combined with clinical judgement followed by a logistic regression model. The additive model based on unadjusted relative risks, the model based on Bayes' Theorem, and the logistic model using all candidate variables were good alternatives. Whether or not we imputed values did not have a significant impact on the predictive power of the models.
- ItemBayesian-logit model for risk assessment in coronary artery bypass grafting(1994) Marshall Rivera, Guillermo; Shroyer, A. Laurie; Grover, Frederick L.; Hammermeister, Karl E.Predictive models for the assessment of operative risk using patient risk factors have gained popularity in the medical community as an important tool for the adjustment of surgical outcome. The Bayes' theorem model is among the various models used to predict mortality among patients undergoing coronary artery bypass grafting procedures. Comparative studies of the various classic statistical techniques, such as logistic regression, cluster of variables followed by a logistic regression, a subjectively created sickness score, classification trees model, and the Bayes' theorem model, have shown that the Bayes' model is among those with the highest predictive power. In this study, the Bayes' theorem model is reformulated as a logistic equation and extended to include qualitative and quantitative risk factors. We show that the resulting model, the Bayesian-logit model, is a mixture of logistic regression and linear discriminant analysis. This new model can be created easily without complex computer programs. Using 12,712 patients undergoing coronary artery bypass grafting procedures at the Department of Veterans Affairs Continuous Improvement in Cardiac Surgery Study between April 1987 and March 1990, the predictive power of the Bayesian-logit model is compared with the Bayes' theorem model, logistic regression, and discriminant analysis. The ability of the Bayesian-logit model to discriminate between operative deaths and operative survivors is comparable with that of logistic regression and discriminant analysis
- ItemContinuous assessment and improvement in quality of care. A model from the Department of Veterans Affairs Cardiac Surgery(1994) Hammermeister, Karl E.; Johnson, Randall; Marshall Rivera, Guillermo; Grover, Frederick L.Objective: The authors organized the Department of Veterans Affairs (VA) Continuous Improvement in Cardiac Surgery Study (CICSS) to provide risk-adjusted outcome data for the continuous assessment and improvement of quality of care for all patients undergoing cardiac surgery in the VA. Background: The use of risk-adjusted outcomes to monitor quality of health care has the potential advantage over consensus-derived standards of being free of preconceived biases about how health care should be provided. Monitoring outcomes of all health care episodes, as opposed to review of selected cases (e.g., adverse outcomes), has the advantages of greater statistical power, the opportunity to compare processes of care between good and bad outcomes, and the positive psychology of treating all providers equally. These two concepts, together with a pre-existing peer committee (the VA Cardiac Surgery Consultants Committee) to review, interpret, and act on the risk-adjusted outcome data, form the primary design considerations for CICSS. Methods: Patient-level risk and outcome (operative mortality and morbidity) data are collected prospectively on each of the approximately 7000 patients undergoing cardiac surgery in the VA each year. These outcomes, adjusted for patient risk using logistic regression, are provided every 6 months to each cardiac surgery program and to a national peer review committee for internal and external quality assessment and improvement. Results: For the most recent 12-month period with complete data collection, observed-to-expected (O/E) ratios ranged from 0.2 to 2.2, with eight centers falling outside of the 90% confidence limits for an O/E ratio equaling 1.0. The O/E ratio for all centers has fallen by 14% over the 4.5-year period of this program (p = 0.06). Conclusions: A large-scale, low-cost program of continuous quality improvement using risk-adjusted outcome is feasible. This program has been associated with a decrease in risk-adjusted operative mortality.
- ItemImpact of mammary grafts on coronary bypass operative mortality and morbidity(1994) Grover, Frederick L.; Johnson, Randall; Marshall Rivera, Guillermo; Hammermeister, Karl E.The internal mammary artery is frequently used as a coronary artery bypass graft conduit because of superior long-term patency. The purpose of this study was to determine if there was also an advantage to the internal mammary artery in terms of operative mortality and morbidity. The Department of Veterans Affairs Cardiac Surgery Database was reviewed for two separate time periods, April 1987 through March 1989 and October 1990 through September 1991. During these periods, 14,172 patients underwent coronary artery bypass grafting. Univariate and multivariate logistic regression analyses were used to determine preoperative variables predictive of operative mortality and morbidity, with the independent variable of use of the internal mammary artery added to previously determined indicators. The total group was analyzed in risk quartiles according to expected mortality. Univariate analysis revealed an operative mortality of 6.8% in the early period and 6.5% in the latter period for the saphenous vein groups compared with 3.7% and 3.2%, respectively, for the internal mammary artery groups (p = 0.000). Multivariate analysis revealed an odds ratio of operative death with use of the internal mammary artery graft versus use of vein grafts of 0.78 during the first period and 0.72 during the second period, reductions of 22% and 28%, respectively. There were 29% and 37% reductions in the odds of operative mortality in the highest-risk quartile group of patients using the internal mammary artery graft. The odds ratio of developing mediastinitis with one internal mammary artery graft was 1.84 (p < 0.01) in the first time period and 1.11 in the second time period (p = not significant). However, with multiple mammary bypass grafts, the odds ratios were 3.70 (p < 0.01) and 2.96 (p < 0.01) in the respective time periods. On the basis of this study, it is concluded that internal mammary artery grafts in addition to providing superior long-term patency also decreased operative mortality after adjustment for patient risk factors. Use of the mammary artery does not consistently increase operative complications with the exception of mediastinitis when both internal mammary arteries are employed.
- ItemTime series monitors of outcomes - A new dimension for measuring quality of care(LIPPINCOTT WILLIAMS & WILKINS, 1998) Marshall Rivera, Guillermo; Shroyer, A. Laurie W.; Grover, Fred L.; Hammermeister, Karl E.