Purpose: Radical cystectomy (RC), the gold standard treatment for invasive bladder cancer, is a morbid procedure associated with high costs. Numerous volume-outcomes studies focused on postoperative mortality suggest that centralization of care can reduce the economic burden of disease. This study evaluates the relationship between surgeon volume and RC morbidity outcomes as well as costs in the United States.
Methods: We captured all who underwent a RC (ICD-9 code 57.71) from 2003 to 2010, from a nationally representative discharge database. Patient (age, gender, race, marital status, insurance status, Charlson comorbidity), hospital (bed size, teaching status, location, region), and surgical characteristics (year of procedure, type of approach and urinary diversion, receipt of pelvic lymphandectomy) were evaluated. Annual volume, defined as the total number of cystectomies performed by a surgeon in the year the procedure was performed on a patient, was divided into quintiles. Multivariable logistic and linear regression analyses were performed with clustering by hospitals and survey weighting to ensure nationally representative estimates. Outcomes include 90-day major complications (Clavien 3-5) as defined by ICD-9 diagnosis codes, and direct patient costs.
Results: The weighted cohort included 49792 RC patients with an overall major complication rate of 16.2%. Compared to very low volume surgeons (1/year), very high surgeons (³7/year) had 44% decreased odds of major complications (OR: 0.56, 95% CI: 0.41-0.76, p<0.001). Compared to patients who did not have any complications, those who suffered a major or minor complication had significantly higher 90-day median direct hospital costs ($59283 and $54149 vs. $36550, both p<0.0001).
Conclusions: Our contemporary evaluation of radical cystectomy in the United States suggests an inverse relationship between surgeon volume and postoperative 90-day major complication rates as well as 90-day direct hospital costs. Preventing major complication via centralization of care may reduce the burden of disease. Primary mechanisms underlying this effect, such as peri-operative process of care variables, need to be investigated.
Method: A decision analytic model was developed to estimate the cost-effectiveness of diagnostic strategies for assessing patients with ischaemic cardiomyopathy. The different diagnostic pathways were applied to a hypothetical cohort of patients with ischaemic cardiomyopathy and the probability of successful identification of viable myocardium and non-viable myocardium was determined by the accuracy of the diagnostic pathway. It was assumed that patients diagnosed with viable myocardium would be managed promptly by revascularisation and that the patients diagnosed with non-viable myocardium would be on medical therapy. The model assigned each patient a risk of death and rehospitalisation depending upon whether they are truly viable and whether they had revascularisation or not. Each patient then accrued lifetime QALYs. Health care costs were also accrued through measuring diagnostic costs and treatment costs, depending on the pathway and their treatment status.
Result: All the diagnostic pathways are cost-effective when compared with no testing at current NICE threshold, this suggests that all the current services for diagnosing viable myocardium are a cost effective use of NHS resources irrespective of the diagnostic pathway used. For services that need to decide the most cost-effective strategy starting from scratch, then Stress CMR is the most cost-effective strategy.
Conclusion: There are a number of issues with abstracting the data for cost-effectiveness modelling of diagnostic tests. For example, the diagnostic accuracy depends upon the type of index test, gold standard test and threshold used. Furthermore, the benefits of treatments after diagnosis are not always clear and might be linked to the type of diagnostic test. Appropriate caution needs to be taken when evaluating diagnostic tests.
Method: A decision analytical model was used to estimate life year costs and outcomes represented as quality adjusted life years gained (QALY). The use of Markov model is needed to reflect long-term outcomes because some surviving SJS/TEN patients may suffer from long-term sequelae. The model was populated with relevant information of the association between gene and allopurinol-induced SJS/TEN, test characteristics, costs, and epidemiologic data for Thailand from a societal perspective. Input data were obtained from the literature and a retrospective database analysis. The results were expressed as incremental cost per quality-adjusted life years gained (QALY). A base-case analysis was performed for patients at age 30 from the societal perspective. A series of sensitivity analyses including threshold, scenario, one-way, and probabilistic sensitivity analyses were constructed to explore the robustness of the findings.
Result: Based on a hypothetical cohort of 1,000 patients, the incremental total cost was 923,919 THB and incremental QALY was 4.65 with an ICER of 198,486 THB (USD 6,403) per QALY. Genetic testing for HLA-B*5801 before allopurinol administration was not considered a cost-effective intervention, based on a standard cost-effectiveness threshold of 160,000 THB/QALY in Thailand. However, when the cost of genetic testing was less than 822 THB (USD 26.5), the test becomes cost-effective at the societal willingness-to-pay level of 160,000 THB (USD 5,161)/QALY.
Conclusion: The genetic testing for HLA-B*5801 before allopurinol administration might not be considered as a cost-effective intervention. However, consideration of other factors including ethical, legal, and social implications is needed in order to make an informed policy decision making.
Method: All admitted patients to Tan Tock Seng Hospital in 2012 were included. A risk prediction model was developed and validated to select high risk patients for screening, using logistic regression and Bayesian Information Criteria. Markov decision analysis was applied to identify the most cost-effective screening strategy. The five strategies were compared in terms of the cost per infection prevented: PCR screening for all; PCR screening for selected high risk patients; no screening. The modeling cycle (time length of transition) is 1 hour. The total modeled exposure time in hospital is about 120 hours (5 days). Costs to hospital will be used as the primary cost measure. We will also measure the cost from the perspectives of patients.
Result: In the risk stratification model, the important predictors identified were MRSA colonization history; elder age; infection or hospitalization in last 3 months; admitted from nursing homes; with kidney diseases, or stroke. The c-statistics of the ROC of the prediction model was 0.82 (95%CI: 0.81-0.83). The MRSA prevalence at admission was about 7.3% in 2012. Considering the cost of infection treatment, the incidence rate of hospital infection, the sensitivity and specificity of predicting the high risk patients, the most cost effective screening strategy was selective screening, which cost about $15.8K (95%CI: $7.8K - $ 21.9K) per infection prevented compared with no screening.
Conclusion: The study provides an evidence-based decision tool for policy makers to standardize care and set guidelines on cost effective infectious disease control in hospitals.
Method: We developed a stochastic agent-based model. An artificial population of 10,000 agents with demographic and behavioral characteristics was created to represent the population of Australia. Contacts between the agents were based on mixing groups according to an agent’s personal and behavioral characteristics. The probability of infection in a given period of time was determined by the number of contacts, transmission probability per contact established, susceptibility of the observed agent, and the infectivity of the contacted agent. The HCV model describes the progression of HCV stages: acute HCV; fibrosis stages 0-4, decompensated cirrhosis, hepatocellular carcinoma, liver transplantation and liver-related death. Treatment scenarios include: i) dual therapy (PEG-IFN/RBV); ii) response-guided dual therapy (RGT); iii) triple therapy with boceprevir and iv) triple therapy with telaprevir for persons with HCV genotype 1. Model calibration, uncertainty and sensitivity analyses were performed. An economic model was developed to conduct cost-utility analysis. Outcomes included numbers of HCV infections averted, lifetime health care costs, quality-adjusted life year (QALY), and incremental cost-effectiveness ratios.
Result: In 2010, approximately 4,000 persons with hepatitis C were treated with standard dual therapy. Our model estimated that there were approximately 10,000 new cases of hepatitis C, 560 new cases of decompensated cirrhosis, 143 new cases of hepatocellular carcinoma, 42 liver transplant cases, and 347 liver-related deaths. Over the lifetime with the same treatment rates, these new cases would relatively increase between 37-116% under standard dual therapy. Compared to standard dual therapy, there would be a significant decline in the number of new advanced cases and the number of persons receiving liver transplantation in triple therapies, QALY gains, and cost savings in both triple therapies and RGT.
Conclusion: Both triple therapies and response-guided therapy are cost saving. Strategies to improve new treatment uptake are critical to mitigate the future burden of hepatitis C.