Early cost-utility analysis of tissue-engineered heart valves compared to bioprostheses in the aortic position in elderly patients.

OBJECTIVES: Aortic valve disease is the most frequent indication for heart valve replacement with the highest prevalence in elderly. Tissue-engineered heart valves (TEHV) are foreseen to have important advantages over currently used bioprosthetic heart valve substitutes, most importantly reducing valve degeneration with subsequent reduction of re-intervention. We performed early Health Technology Assessment of hypothetical TEHV in elderly patients (≥ 70 years) requiring surgical (SAVR) or transcatheter aortic valve implantation (TAVI) to assess the potential of TEHV and to inform future development decisions. METHODS: Using a patient-level simulation model, the potential cost-effectiveness of TEHV compared with bioprostheses was predicted from a societal perspective. Anticipated, but currently hypothetical improvements in performance of TEHV, divided in durability, thrombogenicity, and infection resistance, were explored in scenario analyses to estimate quality-adjusted life-year (QALY) gain, cost reduction, headroom, and budget impact. RESULTS: Durability of TEHV had the highest impact on QALY gain and costs, followed by infection resistance. Improved TEHV performance (- 50% prosthetic valve-related events) resulted in lifetime QALY gains of 0.131 and 0.043, lifetime cost reductions of €639 and €368, translating to headrooms of €3255 and €2498 per hypothetical TEHV compared to SAVR and TAVI, respectively. National savings in the first decade after implementation varied between €2.8 and €11.2 million (SAVR) and €3.2-€12.8 million (TAVI) for TEHV substitution rates of 25-100%. CONCLUSIONS: Despite the relatively short life expectancy of elderly patients undergoing SAVR/TAVI, hypothetical TEHV are predicted to be cost-effective compared to bioprostheses, commercially viable and result in national cost savings when biomedical engineers succeed in realising improved durability and/or infection resistance of TEHV.

The economic impact of minimally invasive total hip arthroplasty.

We compared hospital length of stay (LOS) and costs between (1) minimally invasive total hip surgery (MIS) combined with an active hip pathway (AHP) and (2) long incision total hip surgery (LIS) with a passive hip pathway (PHP). A prospective consecutive cohort of 214 MIS/AHP patients was compared to a concurrent cohort of 265 LIS/PHP patients. The MIS/AHP cohort had significantly decreased LOS (1.5 days vs. 3.8 days, P < .001) and hospital costs ($12.8 thousand vs. $16.7 thousand, P < .001). The complication rates were similar for MIS/AHP and LIS/PHP. We conclude that, compared to LIS/PHP, MIS/AHP significantly shortened LOS by an average of 2.3 days, and significantly reduced hospital costs by an average of $3.9 thousand per patient.

What is the inpatient cost of hospital complications or death after lobectomy or pneumonectomy?

BACKGROUND: No information exists evaluating the costs of complications or death after lobectomy or pneumonectomy. METHODS: We analyzed hospital costs for 294 patients who underwent lobectomy (n=268) or pneumonectomy (n=26) from January 2005 through September 2007. The patients were categorized into two groups on the basis of clinical outcomes: uncomplicated versus complications or death. A cost prediction model was constructed with linear regression using uncomplicated patients only. The model was applied to the complications or death group to predict the expected cost as if they had no complication. The risk-adjusted cost of complications or death was quantified by the difference between the observed cost and the expected cost. RESULTS: There were 241 patients in the uncomplicated group (19 pneumonectomy), and 53 patients had complications or death (7 pneumonectomy). Length of stay was shorter for uncomplicated versus complications or death for both lobectomy and pneumonectomy. Pneumonectomy was costlier than lobectomy. Experiencing complications or death was costlier than costs associated with uncomplicated cases. The actual cost for uncomplicated cases was $18,380. The expected cost for complications or death was similar to that for uncomplicated cases regardless of the number of complications or death. The mean risk-adjusted cost of complications (95% confidence interval) increased by the number of complications: $11,693 ($4,430 to $18,957), $26,673 ($12,320 to $41,025) and $128,450 ($93,971 to $162,930) for 1, 2, and 3 complications, respectively. It was $49,823 ($23,187 to $76,459) for death. CONCLUSIONS: Patients experiencing complications or death have a similar perioperative risk profile as patients without complications. Hospital death or postoperative complications after lobectomy or pneumonectomy are economically costly. Decreasing inpatient death or complications would result in substantial cost-of-care savings.

Blood transfusion reduction in cardiac surgery: multidisciplinary approach at a community hospital.

BACKGROUND: Mounting evidence exists for more restrictive blood transfusion practices in patients undergoing cardiac surgery. Few studies, however, have recognized or agree upon a method by which this decrease in allogeneic red blood cell transfusion can be achieved. We will review our methods and experience in a blood conservation initiative from 2003 to 2007. METHODS: A data driven, multidisciplinary effort to decrease allogeneic red blood cell transfusion was instituted in a community hospital. Numerous innovations in treatment protocols were implemented and evaluated. Clinical data from 2003 to 2007 will be presented. Yearly review of outcomes led to an evolving clinical practice and lowered transfusion rates. RESULTS: A total of 2,531 consecutive cardiac surgical procedures were performed during a five-year period. Using a multidisciplinary approach to quality improvement, and with the goal of using fewer blood products, our incidence of allogeneic red blood cell transfusion was decreased, from 43% in 2003 to 18% in 2007. Patient outcomes were not significantly changed. CONCLUSIONS: Cardiac surgery in a community hospital can be performed safely with low utilization of allogeneic red blood cell transfusions. A multidisciplinary approach to blood conservation can result in lower transfusion rates and equivalent patient outcomes.

The value of aortic valve replacement in elderly patients: an economic analysis.

OBJECTIVE: Economists have designed frameworks to measure the economic value of improvements in health and longevity. Heart valve replacement surgery has significantly prolonged life expectancy and quality of life. For the example of aortic valve replacement, what is its economic value according to this framework? METHODS: From 1961 through 2003, a total of 4617 adult patients underwent aortic valve replacement by one team of cardiac surgeons. These patients were provided with a prospective lifetime follow-up service. As of 2005, observed follow-up was 31,671 patient-years, with a maximum of 41 years. A statistical model was used to generate the future life-years of patients currently alive. The value of life-years proposed by economists was applied to determine the economic value of the additional life given to these patients by aortic valve replacement. RESULTS: The total life-years after aortic valve replacement were 53,323, with a gross value of 14.6 billion dollars. The total expected life-years without surgery were 10,157, with an estimated value of 3.0 billion dollars. Thus the net life-years gained by AVR were 43,166, worth 11.6 billion dollars. Subtracting the 451 million dollars total lifetime cost of surgery, the net value of the life-years gained by AVR was 11.2 billion dollars. The mean net value decreases according to age at surgery but is still worth 600,000 dollars for octogenarians and 200,000 dollars for nonagenarians. CONCLUSION: According to the economic concept of the value of a statistical life, the return on the investment for aortic valve replacement is enormous for patients of all ages, even very elderly patients.

Cost-effectiveness of aortic valve replacement in the elderly: an introductory study.

OBJECTIVE: With increased life expectancy and improved technology, valve replacement is being offered to increasing numbers of elderly patients with satisfactory clinical results. By using standard econometric techniques, we estimated the relative cost-effectiveness of aortic valve replacement by drawing on a large prospective database at our institution. By using aortic valve replacement as an example, this introductory report paves the way to more definitive studies of these issues in the future. METHODS: From 1961 to 2003, 4617 adult patients underwent aortic valve replacement at our service. These patients were provided with a prospective lifetime follow-up. As of 2005, these patients had accumulated 31,671 patient-years of follow-up (maximum 41 years) and had returned 22,396 yearly questionnaires. A statistical model was used to estimate the future life years of patients who are currently alive. In the absence of direct estimates of utility, quality-adjusted life years were estimated from New York Heart Association class. The cost-effectiveness ratio was calculated by the patient's age at surgery. RESULTS: The overall cost-effectiveness ratio was approximately 13,528 dollars per quality-adjusted life year gained. The cost-effectiveness ratio increased according to age at surgery, up to 19,826 dollars per quality-adjusted life year for octogenarians and 27,182 dollars per quality-adjusted life year for nonagenarians. CONCLUSIONS: Given the limited scope of this introductory study, aortic valve replacement is cost-effective for all age groups and is very cost-effective for all but the most elderly according to standard econometric rules of thumb.

Validating the Clinical Outcomes Assessment Program risk model for percutaneous coronary intervention.

BACKGROUND: The Clinical Outcomes Assessment Program (COAP) from the state of Washington recently published a risk model for hospital mortality after percutaneous coronary intervention (PCI), which was validated by a consortium of hospitals in 4 northeastern states. The Providence Health System (PHS) Cardiovascular Study Group data was used to further validate this COAP model using data from PHS hospitals in 3 western states. METHODS: All 13124 consecutive PCI procedures performed in 6 PHS hospitals from July 2001 through June 2004 were included. The c index was used to test model discrimination. The Hosmer-Lemeshow test, the le Cessie-van Houwelingen-Copas test, and the cumulative sum method were used to test model calibration. RESULTS: The patient profiles of the COAP data and the PHS data were similar. The overall mortality was 1.6% for COAP and 1.4% for PHS. The subgroup mortalities were also similar. When applying the COAP model to the PHS data, the c index (95% CI) was 0.893 (0.859-0.928), indicating excellent discrimination, and the le Cessie-van Houwelingen-Copas test and the cumulative sum method showed good global goodness of fit. CONCLUSION: The COAP model for hospital mortality was successfully validated using PHS data. With the advance of technology and changing patient profile, PCI models must be periodically checked for possible updating to reflect contemporary practice. Predictors in a PCI risk model should be objective, have standard definitions, and be easy to obtain to facilitate the transportability of the model.

Additive vs. logistic risk models for cardiac surgery mortality.

OBJECTIVE: Logistic regression is most often used to produce a cardiac operative risk model. But the logistic equation requires a computer to solve. Thus, simple additive models have been derived from logistic models by adding the odds ratios or modified coefficients. However, this simplification has no statistical justification, and the additive scores do not equal the original logistic probabilities. METHODS: The EuroSCORE risk model is a very successful and widely used cardiac surgery risk model and it comes in both an additive and a full logistic version. We applied the EuroSCORE model to the 28,337 cardiac surgeries in the Providence Health System Cardiovascular Study Group database. The discrimination of the models was assessed by the c index. The comparison of the mortality predictions of the logistic and the additive model are mostly descriptive and graphical. RESULTS: Theoretical considerations would predict that the additive model greatly underestimates the risk for the higher risk patients, and clinical data confirm this fact. For the 23,463 (83%) cases with complete data, the predicted mortality was 8.3% by the logistic model and 5.4% by the additive model. The discrimination (c index) of the additive (0.794) and logistic (0.791) models was equally good. A modified additive score is proposed (the mean of the logistic predicted mortality for each original additive score) which could be provided as a look-up table along with the scoring sheet. CONCLUSIONS: The additive EuroSCORE gives excellent discrimination, as good as the logistic risk model, but it greatly underestimates the risk of high-risk patients, compared to the logistic. The logistic equation should be used to predicate the mortality when possible. If this is not feasible, a modified additive score could be employed at the bedside. But the logistic should always be used for comparison of providers and for research publications.

Cardiac surgery risk models: a position article.

Differences in medical outcomes may result from disease severity, treatment effectiveness, or chance. Because most outcome studies are observational rather than randomized, risk adjustment is necessary to account for case mix. This has usually been accomplished through the use of standard logistic regression models, although Bayesian models, hierarchical linear models, and machine-learning techniques such as neural networks have also been used. Many factors are essential to insuring the accuracy and usefulness of such models, including selection of an appropriate clinical database, inclusion of critical core variables, precise definitions for predictor variables and endpoints, proper model development, validation, and audit. Risk models may be used to assess the impact of specific predictors on outcome, to aid in patient counseling and treatment selection, to profile provider quality, and to serve as the basis of continuous quality improvement activities.