Cost-effectiveness of the implantable cardioverter-defibrillator: Effect of improved battery life and comparison with amiodarone therapy

AbstractThe implantable cardioverter-defibrillator (ICD) greatly reduces the incidence of sudden cardiac death among patients with recurrent sustained ventricular tachycardia and fibrillation who do not respond to conventional antiarrhythmic therapy. A cost-effectiveness analysis was performed, comparing the ICD, amiodarone and conventional agents. Actual variable costs of hospitalization and follow-up care were used for 21 ICD- and 43 amiodarone-treated patients. Life expectancy and total variable costs were predicted with use of a Markov decision analytic model. Clinical event rates and probabilities were based on published reports or expert opinion.Life expectancy with an ICD (6.1 years) was 50% greater than that associated with treatment with amiodarone (3.9 years) and 2.5 times that associated with conventional treatment (2.5 years). Assuming replacement every 24 months, ICD lifetime treatment costs (in 1989 dollars) for a 55-year old patient are expected to be $89,600 compared with$24,800 for amiodarone and $16,100 for conventional therapy, yielding a marginal cost/effectiveness ratio for ICD versus amiodarone therapy of$29,200/year of life saved, which is comparable to that of other accepted medical treatments. If technologic improvements extend average battery life to 36 months, the marginal cost/effectiveness ratio would be $21,880/ year of life saved, and at 96 months it would be$13,800/year of life saved. Patient age at implantation did not significantly affect these results.If quality of life on amiodarone therapy is 30% lower than that with the ICD, the marginal cost/effectiveness ratio decreases by 35%. If the quality of life for patients receiving drugs is 40% lower than that of patients treated with an ICD, use of the defibrillator becomes the dominant strategy

Lessons Learned from Implementing Service-Oriented Clinical Decision Support at Four Sites: A Qualitative Study

Objective To identify challenges, lessons learned and best practices for service-oriented clinical decision support, based on the results of the Clinical Decision Support Consortium, a multi-site study which developed, implemented and evaluated clinical decision support services in a diverse range of electronic health records. Methods Ethnographic investigation using the rapid assessment process, a procedure for agile qualitative data collection and analysis, including clinical observation, system demonstrations and analysis and 91 interviews. Results We identified challenges and lessons learned in eight dimensions: (1) hardware and software computing infrastructure, (2) clinical content, (3) human-computer interface, (4) people, (5) workflow and communication, (6) internal organizational policies, procedures, environment and culture, (7) external rules, regulations, and pressures and (8) system measurement and monitoring. Key challenges included performance issues (particularly related to data retrieval), differences in terminologies used across sites, workflow variability and the need for a legal framework. Discussion Based on the challenges and lessons learned, we identified eight best practices for developers and implementers of service-oriented clinical decision support: (1) optimize performance, or make asynchronous calls, (2) be liberal in what you accept (particularly for terminology), (3) foster clinical transparency, (4) develop a legal framework, (5) support a flexible front-end, (6) dedicate human resources, (7) support peer-to-peer communication, (8) improve standards. Conclusion The Clinical Decision Support Consortium successfully developed a clinical decision support service and implemented it in four different electronic health records and four diverse clinical sites; however, the process was arduous. The lessons identified by the Consortium may be useful for other developers and implementers of clinical decision support services

N-Glycosylation of ß4 Integrin Controls the Adhesion and Motility of Keratinocytes

α6ß4 integrin is an essential component of hemidesmosomes and modulates cell migration in wound healing and cancer invasion. To elucidate the role of N-glycosylation on ß4 integrin, we investigated keratinocyte adhesion and migration through the re-expression of wild-type or N-glycosylation-defective ß4 integrin (ΔNß4) in ß4 integrin null keratinocytes. N-glycosylation of ß4 integrin was not essential for the heterodimer formation of ß4 integrin with α6 integrin and its expression on a cell surface, but N-glycosylation was required for integrin-mediated cell adhesion and migration. Concomitantly with the reduction of ß4 integrin in the membrane microdomain, the intracellular signals of Akt and ERK activation were decreased in cells expressing ΔNß4 integrin. Forced cross-linking of ß4 integrin rescued the decreased ERK activation in ΔNß4 integrin-expressing cells to a similar extent in wild-type ß4 integrin-expressing cells. Surprisingly, compared with cells expressing wild-type ß4 integrin, an alternation in N-glycan structures expressed on epidermal growth factor receptor (EGFR), and the induction of a stronger association between EGFR and ß4 integrin were observed in ΔNß4 integrin-expressing cells. These results clearly demonstrated that N-glycosylation on ß4 integrin plays an essential role in keratinocyte cellular function by allowing the appropriate complex formation on cell surfaces

Meta Modeling for Business Process Improvement

Conducting business process improvement (BPI) initiatives is a topic of high priority for today’s companies. However, performing BPI projects has become challenging. This is due to rapidly changing customer requirements and an increase of inter-organizational business processes, which need to be considered from an end-to-end perspective. In addition, traditional BPI approaches are more and more perceived as overly complex and too resource-consuming in practice. Against this background, the paper proposes a BPI roadmap, which is an approach for systematically performing BPI projects and serves practitioners’ needs for manageable BPI methods. Based on this BPI roadmap, a domain-specific conceptual modeling method (DSMM) has been developed. The DSMM supports the efficient documentation and communication of the results that emerge during the application of the roadmap. Thus, conceptual modeling acts as a means for purposefully codifying the outcomes of a BPI project. Furthermore, a corresponding software prototype has been implemented using a meta modeling platform to assess the technical feasibility of the approach. Finally, the usability of the prototype has been empirically evaluated

Testing a Short Nuclear Marker for Inferring Staphylinid Beetle Diversity in an African Tropical Rain Forest

The use of DNA based methods for assessing biodiversity has become increasingly common during the last years. Especially in speciose biomes as tropical rain forests and/or in hyperdiverse or understudied taxa they may efficiently complement morphological approaches. The most successful molecular approach in this field is DNA barcoding based on cytochrome c oxidase I (COI) marker, but other markers are used as well. Whereas most studies aim at identifying or describing species, there are only few attempts to use DNA markers for inventorying all animal species found in environmental samples to describe variations of biodiversity patterns.In this study, an analysis of the nuclear D3 region of the 28S rRNA gene to delimit species-like units is compared to results based on distinction of morphospecies. Data derived from both approaches are used to assess diversity and composition of staphylinid beetle communities of a Guineo-Congolian rain forest in Kenya. Beetles were collected with a standardized sampling design across six transects in primary and secondary forests using pitfall traps. Sequences could be obtained of 99% of all individuals. In total, 76 molecular operational taxonomic units (MOTUs) were found in contrast to 70 discernible morphospecies. Despite this difference both approaches revealed highly similar biodiversity patterns, with species richness being equal in primary and secondary forests, but with divergent species communities in different habitats. The D3-MOTU approach proved to be an efficient tool for biodiversity analyses.Our data illustrate that the use of MOTUs as a proxy for species can provide an alternative to morphospecies identification for the analysis of changes in community structure of hyperdiverse insect taxa. The efficient amplification of the D3-marker and the ability of the D3-MOTUs to reveal similar biodiversity patterns as analyses of morphospecies recommend its use in future molecular studies on biodiversity

An economic model of long-term use of celecoxib in patients with osteoarthritis

<p>Abstract</p> <p>Background</p> <p>Previous evaluations of the cost-effectiveness of the cyclooxygenase-2 selective inhibitor celecoxib (Celebrex, Pfizer Inc, USA) have produced conflicting results. The recent controversy over the cardiovascular (CV) risks of rofecoxib and other coxibs has renewed interest in the economic profile of celecoxib, the only coxib now available in the United States. The objective of our study was to evaluate the long-term cost-effectiveness of celecoxib compared with nonselective nonsteroidal anti-inflammatory drugs (nsNSAIDs) in a population of 60-year-old osteoarthritis (OA) patients with average risks of upper gastrointestinal (UGI) complications who require chronic daily NSAID therapy.</p> <p>Methods</p> <p>We used decision analysis based on data from the literature to evaluate cost-effectiveness from a modified societal perspective over patients' lifetimes, with outcomes expressed as incremental costs per quality-adjusted life-year (QALY) gained. Sensitivity tests were performed to evaluate the impacts of advancing age, CV thromboembolic event risk, different analytic horizons and alternate treatment strategies after UGI adverse events.</p> <p>Results</p> <p>Our main findings were: 1) the base model incremental cost-effectiveness ratio (ICER) for celecoxib versus nsNSAIDs was $31,097 per QALY; 2) the ICER per QALY was$19,309 for a model in which UGI ulcer and ulcer complication event risks increased with advancing age; 3) the ICER per QALY was $17,120 in sensitivity analyses combining serious CV thromboembolic event (myocardial infarction, stroke, CV death) risks with base model assumptions.</p> <p>Conclusion</p> <p>Our model suggests that chronic celecoxib is cost-effective versus nsNSAIDs in a population of 60-year-old OA patients with average risks of UGI events.</p

Decision analysis: A basic overview for the pediatric surgeon

Decision making in medicine requires choosing the option that best maximizes benefit while minimizing risk and cost. Even though uncertainty is an inherent feature of any clinical issue, clinicians and policy makers frequently are required to evaluate the best evidence and make therapeutic or policy decisions based on that evidence. Decision analysis is a quantitative approach to decision making under conditions of uncertainty that can be applied to specific types of clinical problems. This method disaggregates a complex clinical problem into its most important components that then can be understood more easily and analyzed quantitatively. Decision analysis has many potential applications in medicine and can be applied to solve specific clinical problems, analyze health care costs, or develop health care policies. In this review, the basic methods for constructing and analyzing decision analyses will be presented, and specific applications of this method to pediatric surgery will be discussed. Copyright © 2002 by W.B. Saunders Company

Decision analysis: A basic overview for the pediatric surgeon

Decision making in medicine requires choosing the option that best maximizes benefit while minimizing risk and cost. Even though uncertainty is an inherent feature of any clinical issue, clinicians and policy makers frequently are required to evaluate the best evidence and make therapeutic or policy decisions based on that evidence. Decision analysis is a quantitative approach to decision making under conditions of uncertainty that can be applied to specific types of clinical problems. This method disaggregates a complex clinical problem into its most important components that then can be understood more easily and analyzed quantitatively. Decision analysis has many potential applications in medicine and can be applied to solve specific clinical problems, analyze health care costs, or develop health care policies. In this review, the basic methods for constructing and analyzing decision analyses will be presented, and specific applications of this method to pediatric surgery will be discussed. Copyright © 2002 by W.B. Saunders Company

Transportation Energy and Carbon Footprints

In this paper we present estimates of the automobile and truck travel based energy and carbon footprints of the largest 100 U.S. metropolitan areas. The footprints are based on the estimated vehicle miles traveled and the transportation fuels consumed. Results are presented on an annual basis and represent end use emissions only. Total carbon emissions, emissions per capita, and emissions per dollar of gross metropolitan product are reported. Two years of annual data were examined, 2000 and 2005, with most of the in-depth analysis focused on the 2005 results. In section 2 we provide background data on the national picture and derive some carbon and energy consumption figures for the nation as a whole. In section 3 of the paper we examine the metropolitan area-wide results based on the sums and averages across all 100 metro areas, and compare these with the national totals and averages. In section 4 we present metropolitan area specific footprints and examine the considerable variation that is found to exist across individual metro areas. In doing so we pay particular attention to the effects that urban form might have on these differences. Finally, section 5 provides a summary of major findings, and a list of caveats that need to be borne in mind when using the results due to known limitations in the data sources used.The authors are grateful to the Brookings Institution for sponsoring this research as part of its Metropolitan Policy Progra