Trial application of a model of resource utiliztion, costs, and outcomes for stroke (MORUCOS) to assist priority setting in stroke.

Background and Purpose— Cost-effectiveness data for stroke interventions are limited, and comparisons between studies are confounded by methodological inconsistencies. The aim of this study was to trial the use of the intervention module of the economic model, a Model of Resource Utilization, Costs, and Outcomes for Stroke (MORUCOS) to facilitate evaluation and ranking of the options.

Methods— The approach involves using an economic model together with added secondary considerations. A consistent approach was taken using standard economic evaluation methods. Data from the North East Melbourne Stroke Incidence Study (NEMESIS) were used to model "current practice" (base case), against which 2 interventions were compared. A 2-stage process was used to measure benefit: health gains (expressed in disability-adjusted life years [DALYs]) and filter analysis. Incremental cost-effectiveness ratios (ICERs) were calculated, and probabilistic uncertainty analysis was undertaken.

Results— Aspirin, a low-cost intervention applicable to a large number of stroke patients (9153 first-ever cases), resulted in modest health benefits (946 DALYs saved) and a mean ICER (based on incidence costs) of US $1421 per DALY saved. Although the health gains from recombinant tissue-type plasminogen activator (rtPA) were less (155 DALYs saved), these results were impressive given the small number of persons (256) eligible for treatment. rtPA dominates current practice because it is more effective and cost-saving.

Conclusions— If used to assess interventions across the stroke care continuum, MORUCOS offers enormous capacity to support decision-making in the prioritising of stroke services.

Using the Big Mac index for comparing construction costs internationally

This paper explores the use of purchasing power parity (PPP) in the comparison of construction costs between different countries, and whether the development of construction-specific indices will improve reliability.

The approach adopted is to compare the construction cost of a typical five star international hotel per square metre in each of ten major cities using a range of PPP methods and to comment on their variability. In particular, this paper looks at whether an index based on the price of a McDonalds Big Mac3 hamburger is a viable alternative when compared against the mainstream methods. The recent publication of construction-specific indices as part of the Eurostat-OECD joint PPP program is also compared against generic indices and the discrepancy is calculated.

The paper concludes with reflections about which approach is preferable when attempting to assess global construction relativities and what further research is needed.

Preliminary investigation of the costs of incubation in the Australasian Gannet (Morus serrator) breeding in Port Phillip Bay, Victoria

To optimise lifetime reproductive success, individuals must balance current reproductive effort against future reproductive prospects. In birds, incubation and chick-rearing must involve costs, and manipulation of the length of incubation offers an insight into some costs affecting adults. An experiment was conducted at a colony of Australasian Gannets in Port Phillip Bay, Victoria, in which length of incubation was manipulated so that some adults experienced short (10–20 days duration), long (70–80 days) or normal (~45 days) incubation periods. Adults with a manipulated incubation period did not show significant differences in weight change (taken here to reflect cost) during incubation or chick-rearing compared with controls. Manipulation of length of incubation did not significantly affect the hatching success or the growth rate of chicks involved and is not, therefore considered to impose an increased reproductive cost. This suggests that the Australasian Gannet has the capacity to maintain body condition and successfully rear young despite modified duration of incubation.

The cost of seasonal respiratory illnesses in Australian children: the dominance of patient and family costs and implications for vaccine use

Respiratory viral infections are one of the next group of diseases likely to be targeted for prevention in childhood by the use of vaccines. To begin collecting necessary epidemiology and cost information about the illnesses caused by these viruses, we conducted a prospective cohort study in 118 Melbourne children between 12 and 71 months of age during winter and spring 2001. We were interested in calculating an average cost per episode of community-managed acute respiratory disease, in identifying the key cost drivers of such illness, and to identify the proportion of costs borne by the patient and family. There were 202 community-managed influenza-like illnesses identified between July and December 2001, generating 89 general practitioner visits, and 42 antibiotic prescriptions. The average cost of community-managed episodes (without hospitalisation) was $241 (95% CI $191 to $291), with the key cost drivers being carer time away from usual activities caring for the ill child (70% of costs), use of non-prescription medications (5.4%), and general practice visits (5.0%). The patient and family met 87per cent of total costs. The lowest average cost occurred in households from the highest income bracket. Acute respiratory illness managed in the community is common, with the responsibility for meeting the cost of episodes predominantly borne by the patient and family in the form of lost productivity. These findings have implications for preventive strategies in children, such as the individual use of, or implementation of public programs using, currently available vaccines against influenza and vaccines under development against other viral respiratory pathogens.

Probabilistic models over ordered partitions with applications in document ranking and collaborative filtering

Ranking is an important task for handling a large amount of content. Ideally, training data for supervised ranking would include a complete rank of documents (or other objects such as images or videos) for a particular query. However, this is only possible for small sets of documents. In practice, one often resorts to document rating, in that a subset of documents is assigned with a small number indicating the degree of relevance. This poses a general problem of modelling and learning rank data with ties. In this paper, we propose a probabilistic generative model, that models the process as permutations over partitions. This results in super-exponential combinatorial state space with unknown numbers of partitions and unknown ordering among them. We approach the problem from the discrete choice theory, where subsets are chosen in a stagewise manner, reducing the state space per each stage significantly. Further, we show that with suitable parameterisation, we can still learn the models in linear time. We evaluate the proposed models on two application areas: (i) document ranking with the data from the recently held Yahoo! challenge, and (ii) collaborative filtering with movie data. The results demonstrate that the models are competitive against well-known rivals.

Learning from ordered sets and applications in collaborative ranking

Ranking over sets arise when users choose between groups of items. For example, a group may be of those movies deemed 5 stars to them, or a customized tour package. It turns out, to model this data type properly, we need to investigate the general combinatorics problem of partitioning a set and ordering the subsets. Here we construct a probabilistic log-linear model over a set of ordered subsets. Inference in this combinatorial space is highly challenging: The space size approaches (N!/2)6.93145N+1 as N approaches infinity. We propose a split-and-merge Metropolis-Hastings procedure that can explore the state-space efficiently. For discovering hidden aspects in the data, we enrich the model with latent binary variables so that the posteriors can be efficiently evaluated. Finally, we evaluate the proposed model on large-scale collaborative filtering tasks and demonstrate that it is competitive against state-of-the-art methods.

Patient costs during tuberculosis treatment in Bangladesh and Tanzania: the potential of shorter regimens

OBJECTIVE: To estimate the costs incurred by patients during the intensive and continuation phases of the current 6-month tuberculosis (TB) regimen in Bangladesh and Tanzania, and thus identify potential benefits to patients of a shorter, 4-month treatment regimen. DESIGN: The validated Stop TB patient cost questionnaire was adapted and used in interviews with 190 patients in the continuation phase of treatment with current regimens. RESULTS: In both countries, overall patient costs were lower during 2 months of the continuation phase (US$74 in Tanzania and US$56 in Bangladesh) than during the 2 months of the intensive phase of treatment (US$150 and US$111, respectively). However, continuation phase patient costs still represented 89% and 77% of the 2-month average national income in the respective countries. Direct travel costs in some settings were kept low by local delivery system features such as community treatment observation. Lost productivity and costs for supplementary foods remained significant. CONCLUSIONS: Although it is not a straightforward exercise to determine the exact magnitude of likely savings, a shorter regimen would reduce out-of-pocket expenses incurred by patients in the most recent 2 months of the continuation phase and allow an earlier return to productive activities. © 2014 The Union.

How does the cookie crumble? legal costs under a uniform interpretation of the United Nations Convention on Contracts for the International Sale of Goods

A family owned Mexican company, Zapata Hermanos Sucesores, S.A. ("Zapata"), sold approximately US$950,000 worth of cookie tins over a period of four years to the Maurice Lenell Cooky Company ("Lenell"), an American company that produced baked goods. Lenell failed to pay Zapata for the cookie tins so Zapata sought legal advice and instituted legal proceedings against Lenell for breach of contract in the Federal District Court of Illinios. The cookie tin sale contracts were governed by the United Nations Convention on Contracts for the International Sale of Goods ("CISG"). Zapata succeeded in its Federal District Court claim and, as part of the Court's order, was awarded US$550,000 as foreseeable loss under Article 74 of the CISG, being the amount of legal fees incurred by Zapata in bringing proceedings against Lenell. On appeal to the Federal Appellate Court, however, the award of legal fees was overturned. The parties now find themselves contesting a leave application to appeal to the Supreme Court of the United States of America in a much anticipated debate over who should pay the lawyers.

Comparing bargaining solutions in the shadow of conflict: how norms against threats can have real effects

In many economic environments agents make costly and irreversible investments (in ``guns'') that may enhance their respective threat payoffs but also shrink the utility possibilities set. In such settings, with variable threats and a variable utility possibilities set, it becomes possible to rank different bargaining solutions in terms of efficiency. We compare bargaining solutions within a class in which the influence of the threat point on the bargaining outcome varies across solutions. Under symmetry, we find that the solution in which the threat point is least influential the equal sacrifice solution Pareto-dominates the other solutions. Since the equal sacrifice solution puts the least weight on the threat point, norms against threats (that can be seen in many seemingly rhetorical pronouncements in adversarial relations) can mitigate some of the costs of conflict and therefore have efficiency- enhancing effects.

Modelling human preferences for ranking and collaborative filtering: a probabilistic ordered partition approach

Learning preference models from human generated data is an important task in modern information processing systems. Its popular setting consists of simple input ratings, assigned with numerical values to indicate their relevancy with respect to a specific query. Since ratings are often specified within a small range, several objects may have the same ratings, thus creating ties among objects for a given query. Dealing with this phenomena presents a general problem of modelling preferences in the presence of ties and being query-specific. To this end, we present in this paper a novel approach by constructing probabilistic models directly on the collection of objects exploiting the combinatorial structure induced by the ties among them. The proposed probabilistic setting allows exploration of a super-exponential combinatorial state-space with unknown numbers of partitions and unknown order among them. Learning and inference in such a large state-space are challenging, and yet we present in this paper efficient algorithms to perform these tasks. Our approach exploits discrete choice theory, imposing generative process such that the finite set of objects is partitioned into subsets in a stagewise procedure, and thus reducing the state-space at each stage significantly. Efficient Markov chain Monte Carlo algorithms are then presented for the proposed models. We demonstrate that the model can potentially be trained in a large-scale setting of hundreds of thousands objects using an ordinary computer. In fact, in some special cases with appropriate model specification, our models can be learned in linear time. We evaluate the models on two application areas: (i) document ranking with the data from the Yahoo! challenge and (ii) collaborative filtering with movie data. We demonstrate that the models are competitive against state-of-the-arts.

Economic evaluation plan (EEP) for a very early rehabilitation trial (AVERT): an international trial to compare the costs and cost-effectiveness of commencing out of bed standing and walking training (very early mobilization) within 24 h of stroke onset

RATIONALE: A key objective of A Very Early Rehabilitation Trial is to determine if the intervention, very early mobilisation following stroke, is cost-effective. Resource use data were collected to enable an economic evaluation to be undertaken and a plan for the main economic analyses was written prior to the completion of follow up data collection. AIM AND HYPOTHESIS: To report methods used to collect resource use data, pre-specify the main economic evaluation analyses and report other intended exploratory analyses of resource use data. SAMPLE SIZE ESTIMATES: Recruitment to the trial has been completed. A total of 2,104 participants from 56 stroke units across three geographic regions participated in the trial. METHODS AND DESIGN: Resource use data were collected prospectively alongside the trial using standardised tools. The primary economic evaluation method is a cost-effectiveness analysis to compare resource use over 12 months with health outcomes of the intervention measured against a usual care comparator. A cost-utility analysis is also intended. STUDY OUTCOME: The primary outcome in the cost-effectiveness analysis will be favourable outcome (modified Rankin Scale score 0-2) at 12 months. Cost-utility analysis will use health-related quality of life, reported as quality-adjusted life years gained over a 12 month period, as measured by the modified Rankin Scale and the Assessment of Quality of Life. DISCUSSION: Outcomes of the economic evaluation analysis will inform the cost-effectiveness of very early mobilisation following stroke when compared to usual care. The exploratory analysis will report patterns of resource use in the first year following stroke.