Cost-effectiveness analysis of a two-stage screening intervention for hepatocellular carcinoma in Taiwan

Background/Purpose

Hepatocellular carcinoma (HCC) has been the leading cause of cancer death in Taiwan since the 1980s. A two-stage screening intervention was introduced in 1996 and has been implemented in a limited number of hospitals. The present study assessed the costs and health outcomes associated with the introduction of screening intervention, from the perspective of the Taiwanese government. The cost-effectiveness analysis aimed to assist informed decision making by the health authority in Taiwan.
Methods

A two-phase economic model, 1-year decision analysis and a 60-year Markov simulation, was developed to conceptualize the screening intervention within current practice, and was compared with opportunistic screening alone. Incremental analyses were conducted to compare the incremental costs and outcomes associated with the introduction of the intervention. Sensitivity analyses were performed to investigate the uncertainties that surrounded the model.
Results

The Markov model simulation demonstrated an incremental cost-effectiveness ratio (ICER) of NT$498,000 (US$15,600) per life-year saved, with a 5% discount rate. An ICER of NT$402,000 (US$12,600) per quality-adjusted life-year was achieved by applying utility weights. Sensitivity analysis showed that excess mortality reduction of HCC by screening and HCC incidence rates were the most influential factors on the ICERs. Scenario analysis also indicated that expansion of the HCC screening intervention by focusing on regular monitoring of the high-risk individuals could achieve a more favorable result.
Conclusion

Screening the population of high-risk individuals for HCC with the two-stage screening intervention in Taiwan is considered potentially cost-effective compared with opportunistic screening in the target population of an HCC endemic area.

A preliminary analysis of the cost-effectiveness of the National Bowel Cancer Screening Program – demonstrating the potential value of comprehensive real world data

Background The complexity and cost of treating cancer patients is escalating rapidly and increasingly difficult decisions are being made regarding which interventions provide value for money. BioGrid Australia supports collection and analysis of comprehensive treatment and outcome data across multiple sites. Here we use preliminary data regarding the National Bowel Cancer Screening Program (NBCSP) and stage-specific treatment costs for colorectal cancer (CRC) to demonstrate the potential value of real world data for cost-effectiveness analyses (CEA).

Methods Data regarding the impact of NBCSP on stage at diagnosis was combined with stage-specific CRC treatment costs and existing literature. An incremental CEA was undertaken from a government healthcare perspective, comparing NBCSP to no-screening. The 2008 invited population (n=681,915) was modelled in both scenarios. Effectiveness was expressed as CRC-related life years saved (LYS). Costs and benefits were discounted at 3% per annum.

Results Over the lifetime and relative to no-screening, NBCSP was predicted to save 1,265 life-years, prevent 225 CRC cases and cost an additional $48.3 million, equivalent to a cost-effectiveness ratio of $38,217 per LYS. A scenario analysis assuming full participation improved this to $23,395.

Conclusions This preliminary CEA based largely on contemporary real world data suggests population-based FOBT screening for CRC is attractive. Planned ongoing data collection will enable repeated analyses over time, using the same methodology in the same patient populations, permitting an accurate analysis of the impact of new therapies and changing practice. Similar CEA using real world data related to other disease types and interventions appears desirable.

Service guarantees and customer satisfaction: an empirical study of guarantee type and service experience

Scenario analysis was used to examine empirically the relationships between guarantee type and service experience, and consumer satisfaction, for the service of an Internet Service Provider (ISP). The scenarios involved hypothetical situations in which several factors were varied: the existence of a problem; the invocation of a guarantee, the identity of the invoker; and the manner of resolution of any problem. Alternative service guarantees were associated with each hypothetical experience: a specific guarantee, and an unconditional guarantee. Overall, consumer satisfaction related to the nature of the service experience much more strongly than it did to the difference in guarantee type.

Modelling the public health consequences of cannabis use in Australia

Aims: To detail and validate a simulation model that describes the dynamics of cannabis use, including its probable causal relationships with schizophrenia, road traffic accidents (RTA) and heroin/poly-drug use (HPU).

Methods: A Markov model with 17 health-states was constructed. Annual cycles were used to simulate the initiation of cannabis use, progression in use, reduction and complete remission. The probabilities of transition between health-states were derived from observational data. Following 10-year-old Australian children for 90 years, the model estimated age-specific prevalence for cannabis use. By applying the relative risks according to the extent of cannabis use, the age-specific prevalence of schizophrenia and HPU, and the annual RTA incidence and fatality rate were also estimated. Predictive validity of the model was tested by comparing modelled outputs with data from other credible sources. Sensitivity and scenario analyses were conducted to evaluate technical validity and face validity.

Results: The estimated cannabis use prevalence in individuals aged 10-65 years was 12.2% which comprised 27.4% weekly and 18.0% daily users. The modelled prevalence and age profile were comparable to the reported cross-sectional data. The model also provided good approximations to the prevalence of schizophrenia (Modelled: 4.75/1,000 persons vs Observed: 4.6/1,000 persons), HPU (3.2/1,000 vs 3.1/1,000) and the RTA fatality rate (8.1 per 100,000 vs 8.2 per 100,000). Sensitivity analyses and scenario analysis provided expected and explainable trends.

Conclusions: The validated model provides a valuable tool to assess the likely effectiveness and cost-effectiveness of interventions designed to affect patterns of cannabis use. It can be updated as new data becomes available and/or applied to other countries.

Ustekinumab for the treatment of moderate to severe psoriasis

This paper presents a summary of the evidence review group (ERG) report into the clinical effectiveness and cost-effectiveness of ustekinumab for the treatment of moderate to severe psoriasis based upon a review of the manufacturer's submission to the National Institute for Health and Clinical Excellence (NICE) as part of the single technology appraisal (STA) process. The submission's main evidence came from three randomised controlled trials (RCTs), of reasonable methodological quality and measuring a range of clinically relevant outcomes. Higher proportions of participants treated with ustekinumab (45 mg and 90 mg) than with placebo or etanercept achieved an improvement on the Psoriasis Area and Severity Index (PASI) of at least 75% (PASI 75) after 12 weeks. There were also statistically significant differences in favour of ustekinumab over placebo for PASI 50 and PASI 90 results, and for ustekinumab over etanercept for PASI 90 results. A weight-based subgroup dosing analysis for each trial was presented, but the methodology was poorly described and no statistical analysis to support the chosen weight threshold was presented. The manufacturer carried out a mixed treatment comparison (MTC); however, the appropriateness of some of the methodological aspects of the MTC is uncertain. The incidence of adverse events was similar between groups at 12 weeks and withdrawals due to adverse events were low and less frequent in the ustekinumab than in the placebo or etanercept groups; however, statistical comparisons were not reported. The manufacturer's economic model of treatments for psoriasis compared ustekinumab with other biological therapies. The model used a reasonable approach; however, it is not clear whether the clinical effectiveness estimates from the subgroup analysis, used in the base-case analysis, were methodologically appropriate. The base-case incremental cost-effectiveness ratio for ustekinumab versus supportive care was 29,587 pounds per quality-adjusted life-year (QALY). In one-way sensitivity analysis the model was most sensitive to the number of hospital days associated with supportive care, the cost estimate for intermittent etanercept 25 mg and the utility scores used. In the ERG's scenario analysis the model was most sensitive to the price of ustekinumab 90 mg, the proportion of patients with baseline weight > 100 kg and the relative risk of intermittent versus continuous etanercept 25 mg. In the ERG's probabilistic sensitivity analysis ustekinumab had the highest probability of being cost-effective at conventional NICE thresholds, assuming the same price for the 45-mg and 90-mg doses; however, doubling the price of ustekinumab 90 mg resulted in ustekinumab no longer dominating the comparators. In conclusion, the clinical effectiveness and cost-effectiveness of ustekinumab in relation to other drugs in this class is uncertain. Provisional NICE guidance issued as a result of the STA states that ustekinumab is recommended as a treatment option for adults with plaque psoriasis when a number of criteria are met. Final guidance is anticipated in September 2009.

Cost-effectiveness analysis of screening for lung cancer with low dose spiral CT (computed tomography) in the Australian setting

Introduction:
Low dose spiral computed tomography (CT) is a sensitive screening tool for lung cancer that is currently being evaluated in both non-randomised studies and randomised controlled trials.
Methods:
We conducted a quantitative decision analysis using a Markov model to determine whether, in the Australian setting, offering spiral CT screening for lung cancer to high risk individuals would be cost-effective compared with current practice. This exploratory analysis was undertaken predominantly from the perspective of the government as third-party funder. In the base-case analysis, the costs and health outcomes (life-years saved and quality-adjusted life years) were calculated in a hypothetical cohort of 10,000 male current smokers for two alternatives: (1) screen for lung cancer with annual CT for 5 years starting at age 60 year and treat those diagnosed with cancer or (2) no screening and treat only those who present with symptomatic cancer.
Results:
For male smokers aged 60–64 years, with an annual incidence of lung cancer of 552 per 100,000, the incremental cost-effectiveness ratio was $57,325 per life-year saved and $105,090 per QALY saved. For females aged 60–64 years with the same annual incidence of lung cancer, the cost-effectiveness ratio was $51,001 per life-year saved and $88,583 per QALY saved. The model was used to examine the relationship between efficacy in terms of the expected reduction in lung cancer mortality at 7 years and cost-effectiveness. In the base-case analysis lung cancer mortality was reduced by 27% and all cause mortality by 2.1%. Changes in the estimated proportion of stage I cancers detected by screening had the greatest impact on the efficacy of the intervention and the cost-effectiveness. The results were also sensitive to assumptions about the test performance characteristics of CT scanning, the proportion of lung cancer cases overdiagnosed by screening, intervention rates for benign disease, the discount rate, the cost of CT, the quality of life in individuals with early stage screen-detected cancer and disutility associated with false positive diagnoses. Given current knowledge and practice, even under favourable assumptions, reductions in lung cancer mortality of less than 20% are unlikely to be cost-effective, using a value of $50,000 per life-year saved as the threshold to define a “cost-effective” intervention.
Conclusion:
The most feasible scenario under which CT screening for lung cancer could be cost-effective would be if very high-risk individuals are targeted and screening is either highly effective or CT screening costs fall substantially.

What do they think when we stack them in? A comparative analysis of student perceptions relating to large and small marketing subjects

University education is in a period of flux with emphasis being focused on quality education, competition for students both local and international as well as changes in governmental financial support and direction. It is with this scenario as a backdrop, that universities in an endeavour to obtain economies of scale offer subjects with large student enrolments. This study investigates marketing students’ perception of and participation in marketing subjects relating to teaching quality, staff availability and support, and individual student involvement in marketing education with large enrolments compared to subjects with small enrolments. This research builds on the investigations of effects of class size by Cuseo (2004) and Binney et al (2004). The study used a multi-method approach. Data from a sample of 621 students was analysed using Factor analysis, MANOVA and ANOVA. Students indicated that there was little difference in the quality of learning obtained in small or large classes. Of interest from a marketing perspective, however, is the perception by students that they are more likely to obtain practical assistance and support from tutors in smaller classes. Student perceptions generally show no major differences between large and small classes in relation to subject selection, ability to learn and lecture  attendance. Students expressed a preference for the opportunity to choose from a number of lecture streams available in subjects with large enrolments. Of interest, however is the student belief that they are less likely to actively participate in large lectures than in small lecture environments.

Role assessment of GIS analysis and its reliability while ranking urban sustainability using scenarios specific to regional climate, community and culture

Urban Sustainability expresses the level of conservation of a city while living a town or consuming its urban resources, but the measurement of urban sustainability depends on what are considered important indicators of conservation besides the permitted levels of consumption in accordance with adopted criteria. This criterion should have common factors that are shared for all the members tested or cities to be evaluated as in this particular case for Abu Dhabi, but also have specific factors that are related to the geographic place, community and culture, that is the measures of urban sustainability specific to a middle east climate, community and culture where GIS Vector and Raster analysis have a role or add a value in urban sustainability measurements or grading are considered herein. Scenarios were tested using various GIS data types to replicate urban history (ten years period), current status and expected future of Abu Dhabi City setting factors to climate, community needs and culture. The useful Vector or Raster GIS data sets that are related to every scenario where selected and analysed in the sense of how and how much it can benefit the urban sustainability ranking in quantity and quality tests, this besides assessing the suitable data nature, type and format, the important topology rules to be considered, the useful attributes to be added, the relationships which should be maintained between data types of a geo- database, and specify its usage in a specific scenario test, then setting weights to each and every data type representing some elements of a phenomenon related to urban suitability factor. The results of assessing the role of GIS analysis provided data collection specifications such as the measures of accuracy reliable to a certain type of GIS functional analysis used in an urban sustainability ranking scenario tests. This paper reflects the prior results of the research that is conducted to test the multidiscipline evaluation of urban sustainability using different indicator metrics, that implement vector GIS Analysis and Raster GIS analysis as basic tools to assist the evaluation and increase of its reliability besides assessing and decomposing it, after which a hypothetical implementation of the chosen evaluation model represented by various scenarios was implemented on the planned urban sustainability factors for a certain period of time to appraise the expected future grade of urban sustainability and come out with advises associated with scenarios for assuring gap filling and relative high urban future sustainability. The results this paper is reflecting are concentrating on the elements of vector and raster GIS analysis that assists the proper urban sustainability grading within the chosen model, the reliability of spatial data collected; analysis selected and resulted spatial information. Starting from selecting some important indicators to comprise the model which include regional culture, climate and community needs an example of what was used is Energy Demand & Consumption (Cooling systems). Thus, this factor is related to the climate and it‟s regional specific as the temperature varies around 30-45 degrees centigrade in city areas, GIS 3D Polygons of building data used to analyse the volume of buildings, attributes „building heights‟, estimate the number of floors from the equation, following energy demand was calculated and consumption for the unit volume, and compared it in scenario with possible sustainable energy supply or using different environmental friendly cooling systems this is followed by calculating the cooling system effects on an area unit selected to be 1 sq. km, combined with the level of greenery area, and open space, as represented by parks polygons, trees polygons, empty areas, pedestrian polygons and road surface area polygons. (initial measures showed that cooling system consumption can be reduced by around 15 -20 % with a well-planned building distributions, proper spaces and with using environmental friendly products and building material, temperature levels were also combined in the scenario extracted from satellite images as interpreted from thermal bands 3 times during the period of assessment. Other examples of the assessment of GIS analysis to urban sustainability took place included Waste Productivity, some effects of greenhouse gases measured by the intensity of road polygons and closeness to dwelling areas, industry areas as defined from land use land cover thematic maps produced from classified satellite images then vectors were created to take part in defining their role within the scenarios. City Noise and light intensity assessment was also investigated, as the region experiences rapid development and noise is magnified due to construction activities, closeness of the airports, and highways. The assessment investigated the measures taken by urban planners to reduce degradation or properly manage it. Finally as a conclusion tables were presented to reflect the scenario results in combination with GIS data types, analysis types, and the level of GIS data reliability to measure the sustainability level of a city related to cultural and regional demands.

Dynamic load variation and stability analysis in distribution networks with distributed generators

In this paper, the modeling of the distribution network is done in a different way where the distributed generator and dynamic loads are considered. Based on this modeling, this paper presents an analysis to investigate the dynamic and static load variation effect on the distribution network. Graphical interface industry software is used to conduct all the aspects of model implementation and carry out the extensive simulation studies. Here also focuses on the worst case scenario and the different fault effect on the generator. Finally, this paper presents the voltage profile for different penetration with different network configurations.

Multichannel biomedical time series clustering via hierarchical probabilistic latent semantic analysis

Biomedical time series clustering that automatically groups a collection of time series according to their internal similarity is of importance for medical record management and inspection such as bio-signals archiving and retrieval. In this paper, a novel framework that automatically groups a set of unlabelled multichannel biomedical time series according to their internal structural similarity is proposed. Specifically, we treat a multichannel biomedical time series as a document and extract local segments from the time series as words. We extend a topic model, i.e., the Hierarchical probabilistic Latent Semantic Analysis (H-pLSA), which was originally developed for visual motion analysis to cluster a set of unlabelled multichannel time series. The H-pLSA models each channel of the multichannel time series using a local pLSA in the first layer. The topics learned in the local pLSA are then fed to a global pLSA in the second layer to discover the categories of multichannel time series. Experiments on a dataset extracted from multichannel Electrocardiography (ECG) signals demonstrate that the proposed method performs better than previous state-of-the-art approaches and is relatively robust to the variations of parameters including length of local segments and dictionary size. Although the experimental evaluation used the multichannel ECG signals in a biometric scenario, the proposed algorithm is a universal framework for multichannel biomedical time series clustering according to their structural similarity, which has many applications in biomedical time series management.

Actor-Network Theory (ANT) based visualisation of socio-technical facets of RFID technology translation: an Australian hospital scenario

In the early 2000s, Information Systems researchers in Australia had begun to emphasise socio-technical approaches in innovation adoption of technologies. The ‘essentialist' approaches to adoption (for example, Innovation Diffusion or TAM), suggest an essence is largely responsible for rate of adoption (Tatnall, 2011) or a new technology introduced may spark innovation. The socio-technical factors in implementing an innovation are largely flouted by researchers and hospitals. Innovation Translation is an approach that purports that any innovation needs to be customised and translated in to context before it can be adopted. Equally, Actor-Network Theory (ANT) is an approach that embraces the differences in technical and human factors and socio-professional aspects in a non-deterministic manner. The research reported in this paper is an attempt to combined the two approaches in an effective manner, to visualise the socio-technical factors in RFID technology adoption in an Australian hospital. This research investigation demonstrates RFID technology translation in an Australian hospital using a case approach (Yin, 2009). Data was collected using a process of focus groups and interviews, analysed with document analysis and concept mapping techniques. The data was then reconstructed in a ‘movie script' format, with Acts and Scenes funnelled to ANT informed abstraction at the end of each Act. The information visualisation at the end of each Act using ANT informed Lens reveal the re-negotiation and improvement of network relationships between the people (factors) involved including nurses, patient care orderlies, management staff and non-human participants such as equipment and technology. The paper augments the current gaps in literature regarding socio-technical approaches in technology adoption within Australian healthcare context, which is transitioning from non-integrated nearly technophobic hospitals in the last decade to a tech-savvy integrated era. More importantly, the ANT visualisation addresses one of the criticisms of ANT i.e. its insufficiency to explain relationship formations between participants and over changes of events in relationship networks (Greenhalgh & Stones, 2010).

Evaluation of a filmed clinical scenario as a teaching resource for an introductory pharmacology unit for undergraduate health students: A pilot study.

BACKGROUND: Simulation is frequently being used as a learning and teaching resource for both undergraduate and postgraduate students, however reporting of the effectiveness of simulation particularly within the pharmacology context is scant. OBJECTIVES: The aim of this pilot study was to evaluate a filmed simulated pharmacological clinical scenario as a teaching resource in an undergraduate pharmacological unit. DESIGN: Pilot cross-sectional quantitative survey. SETTING: An Australian university. PARTICIPANTS: 32 undergraduate students completing a healthcare degree including nursing, midwifery, clinical science, health science, naturopathy, and osteopathy. METHODS: As a part of an undergraduate online pharmacology unit, students were required to watch a filmed simulated pharmacological clinical scenario. To evaluate student learning, a measurement instrument developed from Bloom's cognitive domains (knowledge, comprehension, application, analysis, synthesis and evaluation) was employed to assess pharmacological knowledge conceptualisation and knowledge application within the following fields: medication errors; medication adverse effects; medication interactions; and, general pharmacology. RESULTS: The majority of participants were enrolled in an undergraduate nursing or midwifery programme (72%). Results demonstrated that the majority of nursing and midwifery students (56.52%) found the teaching resource complementary or more useful compared to a lecture although less so compared to a tutorial. Students' self-assessment of learning according to Bloom's cognitive domains indicated that the filmed scenario was a valuable learning tool. Analysis of variance indicated that health science students reported higher levels of learning compared to midwifery and nursing. CONCLUSION: Students' self-report of the learning benefits of a filmed simulated clinical scenario as a teaching resource suggest enhanced critical thinking skills and knowledge conceptualisation regarding pharmacology, in addition to being useful and complementary to other teaching and learning methods.

Computational inverse analysis of static recrystallization kinetics

© 2015 Published by Elsevier Ltd. All rights reserved. Accurate static recrystallization (SRX) models are necessary to improve the properties of austenitic steels by thermo-mechanical operations. This relies heavily on a careful and accurate analysis of "the interrupted test data" and conversion of the heterogeneous deformation data to the flow stress. A "computational-experimental inverse method" was presented and implemented here to analyze the SRX test data, which takes into account the heterogeneous softening of the post-interruption test sample. Conventional and "inverse" methods were used to identify the SRX kinetics for a model austenitic steel deformed at 1273 K (with a strain rate of 1 s-1) using the hot torsion test assess the merits of each method. Typical "static recrystallization distribution maps" in the test sample indicated that, at the onset of the second pass deformation with less than a critical holding time and a given pre-strain, a "partially-recrystallized zone" existed in the cylindrical core of the specimen near its center line. For the investigated scenario, the core was confined in the first half of the gauge radius when the holding time and the maximum pre strain were below 29 s and 0.5, respectively. For maximum pre strains smaller than 0.2, the specimen did not fully recrystallize, even at the gauge surface after holding for 50 s. Under such conditions, the conventional methods produced significant error.

Evaluation of deterministic and complex analytical hierarchy process methods for agricultural land suitability analysis in a changing climate

Land suitability analysis is employed to evaluate the appropriateness of land for a particular purpose whilst integrating both qualitative and quantitative inputs, which can be continuous in nature. However, in agricultural modelling there is often a disregard of this contiguous aspect. Therefore, some parametric procedures for suitability analysis compartmentalise units into defined membership classes. This imposition of crisp boundaries neglects the continuous formations found throughout nature and overlooks differences and inherent uncertainties found in the modelling. This research will compare two approaches to suitability analysis over three differing methods. The primary approach will use an Analytical Hierarchy Process (AHP), while the other approach will use a Fuzzy AHP over two methods; Fitted Fuzzy AHP and Nested Fuzzy AHP. Secondary to this, each method will be assessed into how it behaves in a climate change scenario to understand and highlight the role of uncertainties in model conceptualisation and structure. Outputs and comparisons between each method, in relation to area, proportion of membership classes and spatial representation, showed that fuzzy modelling techniques detailed a more robust and continuous output. In particular the Nested Fuzzy AHP was concluded to be more pertinent, as it incorporated complex modelling techniques, as well as the initial AHP framework. Through this comparison and assessment of model behaviour, an evaluation of each methods predictive capacity and relevance for decision-making purposes in agricultural applications is gained.