ABSTRACT
Chronic cough of unknown etiology is often difficult to diagnose, thus, there exists controversy regarding the management of such patients. Although the ACCP (American College of Chest Physicians) statement in 1998 recommended that treatment should follow testing, recent evidence suggests that empirical treatment of GERD is more cost-effective than testing followed by treatment, in both chronic cough and non-cardiac chest pain. In this paper, we evaluated the cost-effectiveness in managing patients with chronic unexplained cough by building a decision model, and compared the cost-effectiveness of six most common management strategies. The outcome of our analysis demonstrates that empirical treatment is the cheapest option, while testing followed by treatment is the most expensive option with the shortest time course.
Subject(s)
Cost-Benefit Analysis , Cough/therapy , Decision Support Techniques , Chronic Disease , Cough/etiology , Health Care Costs , Humans , SoftwareABSTRACT
OBJECTIVE: The prompt diagnosis of smear-negative pulmonary tuberculosis (PTB) is a clinical challenge. It may be achieved by a number of tests which have varying accuracies, costs and degrees of invasiveness. The objective of this study was to compare the cost-effectiveness of clinical judgement (empirical), the Roche Cobas amplicor assay for Mycobacterium tuberculosis (amplicor), acid-fast staining of bronchoalveolar lavage specimens (BAL), nucleic acid amplification tests of bronchoalveloar lavage specimens for M. tuberculosis (BAL + NAA), computed tomography (CT) and amplicor assay followed by BAL. METHODOLOGY: The range of predictive values of the various strategies were derived from published data and a new study of 441 consecutive adult patients with suspected smear-negative PTB prospectively stratified into three pretest risk groups: low, intermediate and high. The cost-effectiveness was evaluated with a decision tree model (DATA software). RESULTS: The incidence of PTB was 5.7% (4% culture positive) for the whole group, 95% in the high-risk group, 0.9% in the low-risk group and 3.4% in the intermediate-risk group. The sensitivity of the empirical approach was 49% and of the amplicor assay was 44%. Patient outcomes were expressed as life expectancy for the base case of a 58-year-old man with a pretest probability of 5.7%. At this low pretest risk the differences in life expectancies between tests was < 0.1 years and the empirical approach incurred the lowest cost. Sensitivity analysis at increasing pretest risks showed better life expectancies (approximately 1 years) for CT scan and test combinations than empirical and amplicor for additional costs of US$243-US$309. Bronchoalveolar lavage had the worst overall cost-effectiveness. CONCLUSIONS: We conclude that the pretest risk of active PTB was a key determinant of test utility; that the AMPLICOR assay was comparable to clinical judgement; that BAL was the least useful test; and that with increasing risks, CT scan and test combinations performed better. Further studies are needed to better define patients with intermediate risk for PTB and to directly compare the cost-effectiveness of more sensitive nucleic acid amplification tests such as the enhanced Gen Probe, CT scan and test combinations/sequences in these patients.
Subject(s)
Bacteriological Techniques/standards , Bronchoalveolar Lavage Fluid , Bronchoscopy/standards , Nucleic Acid Amplification Techniques/standards , Sputum/microbiology , Tomography, X-Ray Computed/standards , Tuberculosis, Pulmonary/diagnosis , Bacteriological Techniques/economics , Bronchoscopy/economics , Cost-Benefit Analysis , Decision Trees , Humans , Life Expectancy , Male , Middle Aged , Nucleic Acid Amplification Techniques/economics , Patient Selection , Risk Factors , Sensitivity and Specificity , Tomography, X-Ray Computed/economics , Tuberculosis, Pulmonary/microbiologyABSTRACT
Severe head injury management in the intensive care unit is extremely challenging due to the complex domain, the uncertain intervention efficacies, and the time-critical setting. We adopt a decision analytic approach to automate the management process. We document our experience in building a simplified influence diagram that involves about 3000 numerical parameters. We identify the inherent problems in structuring a model with unclear domain relationships, numerous interacting variables, and real-time multiple inputs. We analyze the effectiveness and limitations of the decision analytic approach and present a set of desiderata for effective knowledge acquisition in this setting. We also propose a semi-qualitative approach to parameter elicitation.
