This tutorial presents practical guidance on transforming various types of information published in journals, or available online from government and other sources, into transition probabilities for ...use in state-transition models, including cost-effectiveness models. Much, but not all, of the guidance has been previously published in peer-reviewed journals. Our purpose is to collect it in one location to serve as a stand-alone resource for decision modelers who draw most or all of their information from the published literature. Our focus is on the technical aspects of manipulating data to derive transition probabilities. We explain how to derive model transition probabilities from the following types of statistics: relative risks, odds, odds ratios, and rates. We then review the well-known approach for converting probabilities to match the model’s cycle length when there are two health-state transitions and how to handle the case of three or more health-state transitions, for which the two-state approach is not appropriate. Other topics discussed include transition probabilities for population subgroups, issues to keep in mind when using data from different sources in the derivation process, and sensitivity analyses, including the use of sensitivity analysis to allocate analyst effort in refining transition probabilities and ways to handle sources of uncertainty that are not routinely formalized in models. The paper concludes with recommendations to help modelers make the best use of the published literature.
IMPORTANCE: Since publication of the report by the Panel on Cost-Effectiveness in Health and Medicine in 1996, researchers have advanced the methods of cost-effectiveness analysis, and policy makers ...have experimented with its application. The need to deliver health care efficiently and the importance of using analytic techniques to understand the clinical and economic consequences of strategies to improve health have increased in recent years. OBJECTIVE: To review the state of the field and provide recommendations to improve the quality of cost-effectiveness analyses. The intended audiences include researchers, government policy makers, public health officials, health care administrators, payers, businesses, clinicians, patients, and consumers. DESIGN: In 2012, the Second Panel on Cost-Effectiveness in Health and Medicine was formed and included 2 co-chairs, 13 members, and 3 additional members of a leadership group. These members were selected on the basis of their experience in the field to provide broad expertise in the design, conduct, and use of cost-effectiveness analyses. Over the next 3.5 years, the panel developed recommendations by consensus. These recommendations were then reviewed by invited external reviewers and through a public posting process. FINDINGS: The concept of a “reference case” and a set of standard methodological practices that all cost-effectiveness analyses should follow to improve quality and comparability are recommended. All cost-effectiveness analyses should report 2 reference case analyses: one based on a health care sector perspective and another based on a societal perspective. The use of an “impact inventory,” which is a structured table that contains consequences (both inside and outside the formal health care sector), intended to clarify the scope and boundaries of the 2 reference case analyses is also recommended. This special communication reviews these recommendations and others concerning the estimation of the consequences of interventions, the valuation of health outcomes, and the reporting of cost-effectiveness analyses. CONCLUSIONS AND RELEVANCE: The Second Panel reviewed the current status of the field of cost-effectiveness analysis and developed a new set of recommendations. Major changes include the recommendation to perform analyses from 2 reference case perspectives and to provide an impact inventory to clarify included consequences.
Conceptualizing a Model Roberts, Mark; Russell, Louise B.; Paltiel, A. David ...
Medical decision making,
09/2012, Letnik:
32, Številka:
5
Journal Article
Recenzirano
The appropriate development of a model begins with understanding the problem that is being represented. The aim of this article is to provide a series of consensus-based best practices regarding the ...process of model conceptualization. For the purpose of this series of papers, the authors consider the development of models whose purpose is to inform medical decisions and health-related resource allocation questions. They specifically divide the conceptualization process into two distinct components: the conceptualization of the problem, which converts knowledge of the health care process or decision into a representation of the problem, followed by the conceptualization of the model itself, which matches the attributes and characteristics of a particular modeling type to the needs of the problem being represented. Recommendations are made regarding the structure of the modeling team, agreement on the statement of the problem, the structure, perspective and target population of the model, and the interventions and outcomes represented. Best practices relating to the specific characteristics of model structure, and which characteristics of the problem might be most easily represented in a specific modeling method, are presented. Each section contains a number of recommendations that were iterated among the authors, as well as the wider modeling taskforce, jointly set up by the International Society for Pharmacoeconomics and Outcomes Research and the Society for Medical Decision Making.
Despite substantial evidence on the effectiveness of non-pharmaceutical interventions (NPIs), there is still limited evidence on the individual effects of different types of NPIs on social ...distancing, especially in low- and middle-income countries.
We used panel data analysis to evaluate the effects of mandatory social distancing rules on social distancing. We obtained data on six different categories of mandatory restrictions implemented in Brazil, by date and state, from state government gazettes (diários oficiais). We then defined a social distancing rules index (SDI) to measure the strictness of social distancing rules, assigning each a value of 2, 1, or 0 depending on whether restrictions were full, partial, or very limited/non-existent at every given time. A separate variable was defined for masking mandates. We tested whether the following variables were associated to social distancing: SDI, masking mandates, COVID-19 incidence, population socioeconomic status, and political orientation. Data is for each day between March 11th and November 10th, 2020 in the 27 Brazilian states (N = 6615).
Social distancing increased when social distancing rules were stricter, and decreased when the use of face masks became mandatory. The effects of different types of restrictions varied: suspending in-person classes and gatherings, religious/sport/cultural activities had a greater effect than other types of restrictions. Also, the effect of social distancing rules on people's behaviour decreased over time, especially when rules were stricter.
Mandatory social distancing rules must be adopted to increase social distancing. Stricter rules have a higher impact, but result in decreased compliance over time. Policymakers should prioritize more targeted policies.
Celotno besedilo
Dostopno za:
DOBA, IZUM, KILJ, NUK, PILJ, PNG, SAZU, SIK, UILJ, UKNU, UL, UM, UPUK
Optimizing sorption capacity and amine efficiency are among the major challenges in developing solid carbon dioxide sorbents. Such materials frequently feature polyamines impregnated onto supports ...adding weight to the sorbents. This work presents the cross-linking of polyethyleneimine (PEI) by the industrially available epoxy resin, bisphenol-A diglycidyl ether (DER) to form support-free sorbent materials. Prior to cross-linking, the polyamine chain is functionalized with hydrophobic additives; one material modified with the branched chain hydrocarbon 2-ethylhexyl glycidyl ether displays a CO2 uptake of 0.195 g/g, 4.43 mmol CO2/g (1 atm single component CO2, 90 °C). The additive loading affects the cross-linking, with the lesser cross-linked materials showing more favorable sorption capacities and higher amine efficiencies. The type of additive also influences sorption, with the larger, longer and bulkier additives better able to free the amines from their hydrogen bonding network, generally promoting better sorption. In addition to increasing CO2 uptake, the additives also reduce the optimum sorption temperature, offering a handle to tune sorbents for specific working conditions. The best performing material shows high selectivity for CO2 sorption, and under sorption cycles in a 10% CO2/90% N2 mixture, utilizing temperature swing desorption, demonstrates a good working capacity of 9.5% CO2 uptake over the course of 29 cycles. Furthermore, humidity has been found to promote CO2 sorption at lower temperatures with a CO2 uptake of 0.235 g/g, 5.34 mmol/g (1 atm single component CO2, 25 °C) using a prehydrated sample. Overall, these findings confirm the value of our approach where cross-linking emerges as a valid and practical alternative to loading polyamines onto solid supports. This work demonstrates the versatility of these types of materials and their potential for use in large-scale carbon capture systems.
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•Particulate matter (PM) levels on the CPH metro are measured with low-cost sensors.•Low-costs sensors perform well, due to stable conditions and a primary PM source.•Fine ...micro-environment classification using sensors and machine learning is tested.•PM concentrations in different micro-environments of the metro are characterised.•Measurements made whilst mobile on undergrounds trains gave the highest PM levels (edited).
In this study fine particulate matter (PM2.5) levels throughout the Copenhagen metro system are measured for the first time and found to be ∼10 times the roadside levels in Copenhagen. In this Part 2 article, low-cost sensor (LCS) nodes designed for personal-exposure monitoring are tested against a conventional mid-range device (TSI DustTrak), and gravimetric methods. The nodes were found to be effective for personal exposure measurements inside the metro system, with R2 values of > 0.8 at 1-min and > 0.9 at 5-min time-resolution, with an average slope of 1.01 in both cases, in comparison to the reference, which is impressive for this dynamic environment. Micro-environment (ME) classification techniques are also developed and tested, involving the use of auxiliary sensors, measuring light, carbon dioxide, humidity, temperature and motion. The output from these sensors is used to distinguish between specific MEs, namely, being aboard trains travelling above- or under- ground, with 83 % accuracy, and determining whether sensors were aboard a train or stationary at a platform with 92 % accuracy. This information was used to show a 143 % increase in mean PM2.5 concentration for underground sections relative to overground, and 22 % increase for train vs. platform measurements. The ME classification method can also be used to improve calibration models, assist in accurate exposure assessment based on detailed time-activity patterns, and facilitate field studies that do not require personnel to record time-activity diaries.
Abstract The appropriate development of a model begins with understanding the problem that is being represented. The aim of this article was to provide a series of consensus-based best practices ...regarding the process of model conceptualization. For the purpose of this series of articles, we consider the development of models whose purpose is to inform medical decisions and health-related resource allocation questions. We specifically divide the conceptualization process into two distinct components: the conceptualization of the problem, which converts knowledge of the health care process or decision into a representation of the problem, followed by the conceptualization of the model itself, which matches the attributes and characteristics of a particular modeling type with the needs of the problem being represented. Recommendations are made regarding the structure of the modeling team, agreement on the statement of the problem, the structure, perspective, and target population of the model, and the interventions and outcomes represented. Best practices relating to the specific characteristics of model structure and which characteristics of the problem might be most easily represented in a specific modeling method are presented. Each section contains a number of recommendations that were iterated among the authors, as well as among the wider modeling taskforce, jointly set up by the International Society for Pharmacoeconomics and Outcomes Research and the Society for Medical Decision Making.
Although the U.S. spends more on medical care than any country in the world, Americans live shorter lives than the citizens of other high-income countries. Many important opportunities to improve ...this record lie outside the health sector and involve improving the conditions in which Americans live and work: safe design and maintenance of roads, bridges, train tracks, and airports; control of environmental pollutants; occupational safety; healthy buildings; a safe and healthy food supply; safe manufacture of consumer products; a healthy social environment; and others. Faced with the overwhelming array of possibilities, U.S. decision makers need help identifying those that can contribute the most to health. Cost-effectiveness analysis is designed to serve that purpose, but has mainly been used to assess interventions within the health sector. This paper briefly reviews the objective of cost-effectiveness analysis and its methodologic evolution and discusses the issues that arise when it is used to evaluate interventions that fall outside the health sector under three headings: structuring the analysis, quantifying/measuring benefits and costs, and valuing benefits and costs.
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