Development of the new lung allocation system in the United States.

This article reviews the development of the new U.S. lung allocation system that took effect in spring 2005. In 1998, the Health Resources and Services Administration of the U.S. Department of Health and Human Services published the Organ Procurement and Transplantation Network (OPTN) Final Rule. Under the rule, which became effective in 2000, the OPTN had to demonstrate that existing allocation policies met certain conditions or change the policies to meet a range of criteria, including broader geographic sharing of organs, reducing the use of waiting time as an allocation criterion and creating equitable organ allocation systems using objective medical criteria and medical urgency to allocate donor organs for transplant. This mandate resulted in reviews of all organ allocation policies, and led to the creation of the Lung Allocation Subcommittee of the OPTN Thoracic Organ Transplantation Committee. This paper reviews the deliberations of the Subcommittee in identifying priorities for a new lung allocation system, the analyses undertaken by the OPTN and the Scientific Registry for Transplant Recipients and the evolution of a new lung allocation system that ranks candidates for lungs based on a Lung Allocation Score, incorporating waiting list and posttransplant survival probabilities.

Identification of risk factors for increased cost, charges, and length of stay for cardiac patients.

BACKGROUND: In this study we explored different risk model options to provide clinicians with predictions for resource utilization. The hypotheses were that predictors of mortality are not predictive of resource consumption, and that there is a correlation between cost estimates derived using a cost-to-charge ratio or a product-line costing approach. METHODS: From March 1992 to June 1995, 2,481 University of Colorado Hospital patients admitted for ischemic heart disease were classified by diagnosis-related group code as having undergone or experienced coronary bypass procedures (CBP), percutaneous cardiovascular procedures (PCVP), acute myocardial infarction (AMI), and other cardiac-related discharges (Other). For each diagnosis-related group, Cox proportional hazards models were developed to determine predictors of cost, charges, and length of stay. RESULTS: The diagnosis groups differed in the clinical factors that predicted resource use. As the two costing methods were highly correlated, either approach may be used to assess relative resource consumption provided costs are reconciled to audited financial statements. CONCLUSIONS: To develop valid prediction models for costs of care, the clinical risk factors that are traditionally used to predict risk-adjusted mortality may need to be expanded.

The STS National Database: current changes and challenges for the new millennium. Committee to Establish a National Database in Cardiothoracic Surgery, The Society of Thoracic Surgeons.

BACKGROUND: The Society of Thoracic Surgeons (STS) established the National Database (NDB) for Cardiac Surgery in 1989. Since then it has grown to be the largest database of its kind in medicine. The NDB has been one of the pioneers in the analysis and reporting of risk-adjusted outcomes in cardiothoracic surgery. METHODS AND RESULTS: This report explains the numerous changes in the NDB and its structure that have occurred over the past 2 years. It highlights the benefits of these changes, both to the individual member participants and to the STS overall. Additionally, the vision changes to the NDB and reporting structure are identified. The individuals who have participated in this effort since 1989 are acknowledged, and the STS owes an enormous debt of gratitude to each of them. CONCLUSIONS: Because of their collective efforts, the goal to establish the STS NDB as a "gold standard" worldwide for process and outcomes analysis related to cardiothoracic surgery is becoming a reality.

Clinical science research.

Clinical science research incorporates the fields of clinical investigation and health services research. With a focus on the use of either human specimens or subjects, clinical investigation research projects translate knowledge gained from basic science research based on animal models for disease. The goal of clinical investigation is to develop new prevention, intervention, and therapeutic approaches to improve patient clinical outcomes. In contrast, health services research focuses on the improvement of the efficacy, cost-effectiveness, and outcomes of care. Health services research projects examine options to improve the health care delivery system, organization, financing, and reimbursement mechanisms in place today. The purpose of this article is to review common terminology and methodologic approaches that are used in clinical science research. The process of designing a research project is reviewed. Beginning with the development of a research question and hypothesis, the steps for successful completion of the project are discussed. Different study design approaches are presented with their respective strengths and weaknesses. The challenges associated with conducting a clinical research study are discussed, including the development of an appropriate sampling strategy, the designing of data collection, instruments, and the assurance of study data integrity. Possible threats to study validity and generalizability are assessed.One the major advantages of clinical research is that it offers an opportunity to study clinical questions in the clinical setting without the expenses of a basic research laboratory and basic science technology. Thus important clinical questions related to patient care, new technology assessment, clinical practice management, health care administration, or health policy may be addressed.

The Society of Thoracic Surgeons National Database: current status and future directions.

The Society of Thoracic Surgeons National Database, established seven years ago by thoracic surgeons for self improvement and quality assurance, now has 1,181,464 patients registered, including 897,914 coronary artery bypass operations. Risk-adjusted 30 day mortality for coronary bypass procedures, unadjusted mortality for other cardiothoracic procedures, unadjusted morbidity and length of stay as well as several processes of care are measured. There has been a progressive decrease in operative mortality and length of stay over the past seven years. Deaths, complications, and lengths of stay are stratified according to estimated risk of death. Definitions have been refined in conjunction with the American College of Cardiology. The database is being increasingly utilized for state analyses and is in demand by other organizations and third party carriers. Logistic regression analysis is now utilized for development of the risk models. The database has been useful for health care policy decisions and can be useful for our Professional Affairs Committee in their dealings with government. Other uses include measuring access to care and cost. Data quality improvement measures have been put in place, as well as data manager education. The General Thoracic and Congenital data acquisition packages are being modified and improved, and a goal is to begin collecting longitudinal data to demonstrate the long term efficacy of thoracic procedures. The data elements have been decreased from 500 to 200+ core variables for simplification. With the changing healthcare environment and emphasis on cost cutting, collecting valid data by a national specialty group enhances the monitoring of quality of care, thus protecting our patients from overzealous cutbacks. Data is essential to document the efficacy, quality and cost-effectiveness of the procedures we perform and is a necessary tool for each of us to have to assure the quality and continued success of our practices.

Early extubation following cardiac surgery in a veterans population.

BACKGROUND: Early tracheal extubation is an important component of the "fast track" cardiac surgery pathway. Factors associated with time to extubation in the Department of Veterans Affairs (DVA) population are unknown. The authors determined associations of preoperative risk and intraoperative clinical process variables with time to extubation in this population. METHODS: Three hundred four consecutive patients undergoing coronary artery bypass graft, valve surgery, or both on a fast track clinical pathway between October 1, 1993 and September 30, 1995 at a university-affiliated DVA medical center were studied retrospectively. After univariate screening of a battery of preoperative risk and intraoperative clinical process variables, stepwise logistic regression was used to determine associations with tracheal extubation < or = 10 h (early) or > 10 h (late) after surgery. Postoperative lengths of stay, complications, and 30-day and 6-month mortality rates were compared between the two groups. RESULTS: One hundred forty-six patients (48.3%) were extubated early; one patient required emergent reintubation (0.7%). Of the preoperative risk variables considered, only age (odds ratio, 1.80 per 10-yr increment) and preoperative intraaortic balloon pump (odds ratio, 7.88) were multivariately associated with time to extubation (model R) ("late" association is indicated by an odds ratio >1.00; "early" association is indicated by an odds ratio <1.00). Entry of these risk variables into a second regression model, followed by univariately significant intraoperative clinical process variables, yielded the following associations (model R-P): age (odds ratio, 1.86 per 10-yr increment), sufentanil dose (odds ratio, 1.54 per 1-microg/kg increment), major inotrope use (odds ratio, 5.73), platelet transfusion (odds ratio, 10.03), use of an arterial graft (odds ratio, 0.32), and fentanyl dose (odds ratio, 1.45 per 10-microg/kg increment). Time of arrival in the intensive care unit after surgery was also significant (odds ratio, 1.42 per 1-h increment). Intraoperative clinical process variables added significantly to model performance (P < 0.001 by the likelihood ratio test). CONCLUSIONS: In this population, early tracheal extubation was accomplished in 48% of patients. Intraoperative clinical process variables are important factors to be considered in the timing of postoperative extubation after fast track cardiac surgery.

The Society of Thoracic Surgeons National Cardiac Surgery Database: current risk assessment.

BACKGROUND: The Society of Thoracic Surgeons National Cardiac Surgery Database has recently completed gathering patient data from 1990 through 1994. Using information from more than 300,000 patients undergoing isolated coronary artery bypass grafting in this period, new risk models of operative mortality were developed. METHODS: Logistic regression analysis was used to develop a risk model for each calendar year. A standard "training set/test set" approach was used for each model. RESULTS: Five validation techniques were used to evaluate the reliability of the risk models. All models were found to predict operative mortality with good accuracy in this population. CONCLUSIONS: The new risk models for isolated coronary artery bypass operations serve as reliable predictors of operative mortality for the most recent harvest of patient data from The Society of Thoracic Surgeons National Cardiac Surgery Database.

The bright future of cardiothoracic surgery in the era of changing healthcare delivery.

We are currently at a crossroads in our specialty and in the American healthcare delivery system. The manner in which we approach the next 5 to 10 years will deeply affect the future of our specialty. Thoracic surgery has had many accomplishments during my 35-year career that have improved the healthcare for the American public and others. As cardiothoracic surgeons, we have a legacy to be proud of, and the future promises to be every bit as exciting. In spite of these tremendous advances and the potential for future scientific achievements, there has been considerable uncertainty and pessimism because of the changing structure of healthcare in the United States. This has largely been stimulated by increasing health-care expenditures leading to the development of health maintenance organizations in the hopes of curtailing expenses by competition and capitation. In addition to cost containment, managed care is likely to have an impact on the future workforce of cardiothoracic surgeons. Much of our future will be determined by how well we adapt to the changing environment and take charge of our destiny. The demand for performance information for managed care plans will be much greater than it has been in the past. It is, therefore, imperative that we collect data to reflect the quality and value of our work to ensure that significant quality is not being sacrificed for cost containment. We cardiothoracic surgeons must develop our own information management strategies so that we can be in control of our future. If we do this, I am confident that the future of cardiothoracic surgery will be a bright one indeed.

Quality initiatives and the power of the database: what they are and how they run.

The criteria by which healthcare is judged or measured are quality, accessibility, and cost effectiveness. To evaluate these criteria it is important to have a database. There are many strengths and weakness to large databases. They can be used as an indicator of the level of performance or quality, for clinical decision making, and as a measurement of cost effectiveness. They can also be useful in the evaluation and development of treatment algorithms and critical pathways for patients with entry level disease. In addition, they can measure patient access to healthcare and the appropriateness of care. It is important for these databases to appropriately adjust for preoperative risk factors that may influence outcome. Outcome in most of the databases is measured by mortality, but morbidity, functional status, quality of life, cost of care, length of stay, return to work, and patient satisfaction are also important outcomes. Factors that can influence the quality of the outcome data are the methods by which the data are collected, standardization of definitions, the currentness of the database, adequate numbers of patients and outcomes, and appropriate analytic techniques. It is important to feed back the data to the healthcare providers in a timely enough fashion so that processes and structures of care can be modified to improve treatment and results. The reliability of the databases and the validity must be substantiated for the healthcare provider to have confidence in the database.(ABSTRACT TRUNCATED AT 250 WORDS)

Assessment of predictive models for binary outcomes: an empirical approach using operative death from cardiac surgery.

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.

Bayesian-logit model for risk assessment in coronary artery bypass grafting.

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.

Continuous assessment and improvement in quality of care. A model from the Department of Veterans Affairs Cardiac Surgery.

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.

Factors predictive of operative mortality among coronary artery bypass subsets.

As risk-adjusted outcome is increasingly being used to make clinical decisions and to assess and improve quality of care, it is important to develop simple, stable models for predicting outcome. Here we address the hypothesis that a risk factor for increased operative mortality at coronary artery bypass grafting may have differential effects in subgroups of patients defined by the presence or absence of other risk variables. We used a series of univariate and multivariate analyses to identify a group of ten patient-related preoperative characteristics independently predictive of operative death in the total population of 12,712 patients undergoing coronary artery bypass grafting at 43 Department of Veterans Affairs medical centers participating in the Department of Veterans Affairs Continuous Improvement in Cardiac Surgery Study. Separate logistic regression models were then developed for each of 14 clinically important subgroups defined by the presence or absence of seven risk variables. Odds ratios for operative death and estimated operative mortality were calculated from these subgroup regression models. Of 65 comparisons of pairs odds ratios of preoperative risk variables between the subgroups with and without a second risk variable, only five were found to be significant (p < 0.05 without adjustment for multiple comparisons); this is only slightly more than would be expected by chance alone. Risk factors for increased operative death appear to have similar odds ratios for subgroups of patients defined by a second risk variable. This finding greatly simplifies the use of predicted operative mortality in clinical decision making and quality assessment and improvement in coronary artery bypass grafting.

Initial report of the Veterans Administration Preoperative Risk Assessment Study for Cardiac Surgery.

This study was authorized by the Department of Veterans Affairs to improve the quality assurance of cardiac surgery by assessing preoperative risk factors and relating them to operative mortality. Data were received on 10,480 patients over a 2-year period. Preoperative risk variables were subjected to univariate and multivariate logistic regression analyses. Significant variables for coronary artery bypass grafting after logistic regression analysis in order of importance are previous cardiac operation, priority of operation, New York Heart Association functional class, peripheral vascular disease, age, pulmonary rales, current diuretic use, and chronic obstructive pulmonary disease. For patients undergoing valve or other cardiac operations with or without coronary artery bypass grafting, those variables found to be significant after multivariate logistic regression analysis are priority of operation; age; peripheral vascular disease; great vessel repair; all other except aortic valve replacement, mitral valve replacement, and great vessel repair; mitral valve replacement; and cardiomegaly. By identifying these current risk factors and the coefficients from the multivariate stepwise logistic regression analysis, expected mortality can be calculated. We propose that the ratio of observed to expected mortality is a better measure of quality of care than unadjusted mortality.