A framework for conducting economic evaluations alongside natural experiments.
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ABSTRACT:
SUBMITTER: Deidda M
PROVIDER: S-EPMC6323352 | biostudies-literature | 2019 Jan
REPOSITORIES: biostudies-literature
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Project description:Trial-based economic evaluations are increasingly being conducted to support healthcare decision-making. When analysing trial-based economic evaluation data, different methodological challenges may be encountered, including (i) missing data, (ii) correlated costs and effects, (iii) baseline imbalances and (iv) skewness of costs and/or effects. Despite the broad range of methods available to account for these methodological challenges in effectiveness studies, they may not always be directly applicable in trial-based economic evaluations where costs and effects are analysed jointly, and more than one methodological challenge typically needs to be addressed simultaneously. The use of inappropriate methods can bias results and conclusions regarding the cost-effectiveness of healthcare interventions. Eventually, such low-quality evidence can hamper healthcare decision-making, which may in turn result in a waste of already scarce healthcare resources. Therefore, this tutorial aims to provide step-by-step guidance on how to combine appropriate statistical methods for handling the abovementioned methodological challenges using a ready-to-use R script. The theoretical background of the described methods is provided, and their application is illustrated using a simulated trial-based economic evaluation.
| S-EPMC10570221 | biostudies-literature
Project description:We demonstrate the possibility of conducting synchronous, repeated, multi-game economic decision-making experiments with hundreds of subjects in-person or remotely with live streaming using entirely mobile platforms. Our experiment provides important proof-of-concept that such experiments are not only possible, but yield recognizable results as well as new insights, blurring the line between laboratory and field experiments. Specifically, our findings from 8 different experimental economics games and tasks replicate existing results from traditional laboratory experiments despite the fact that subjects play those games/task in a specific order and regardless of whether the experiment was conducted in person or remotely. We further leverage our large subject population to study the effect of large (N = 100) versus small (N = 10) group sizes on behavior in three of the scalable games that we study. While our results are largely consistent with existing findings for small groups, increases in group size are shown to matter for the robustness of those findings.
| S-EPMC8084158 | biostudies-literature
Project description:The use of a spatial index is a common strategy to improve the performance of spatial queries in spatial database systems and Geographic Information Systems. Choosing the right spatial index to be employed in a given context requires a quantitative method to analyze the performance of spatial indices. This is done through extensive experimental evaluations. However, conducting these evaluations is an expensive, error-prone, and challenging task because (i) spatial objects are complex data to manage, (ii) spatial indices can apply different parameter values and thus assume distinct configurations, and (iii) there are indices specifically developed for different storage systems, such as disks and flash memories. In this article, we propose FESTIval, a versatile framework for conducting experimental evaluations of spatial indices. FESTIval has the following main advantages: •the support for different types of disk-based and flash-aware spatial indices;•the specification and execution of user-defined workloads;•the use of a data schema that stores index configurations and statistical data of executed workloads. Because of its characteristics, FESTIval allows users to reproduce executed experiments. Further, FESTIval provides an extensible environment, where any spatial dataset can be handled by spatial indices. FESTIval has been used to validate new proposals of flash-aware spatial indices, such as eFIND-based indices.
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Project description:Over a decade ago, the Society for Prevention Research endorsed the first standards of evidence for research in preventive interventions. The growing recognition of the need to use limited resources to make sound investments in prevention led the Board of Directors to charge a new task force to set standards for research in analysis of the economic impact of preventive interventions. This article reports the findings of this group's deliberations, proposes standards for economic analyses, and identifies opportunities for future prevention science. Through examples, policymakers' need and use of economic analysis are described. Standards are proposed for framing economic analysis, estimating costs of prevention programs, estimating benefits of prevention programs, implementing summary metrics, handling uncertainty in estimates, and reporting findings. Topics for research in economic analysis are identified. The SPR Board of Directors endorses the "Standards of Evidence for Conducting and Reporting Economic Evaluations in Prevention Science."
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Project description:BackgroundLarge observational datasets such as Clinical Practice Research Datalink (CPRD) provide opportunities to conduct clinical studies and economic evaluations with efficient designs.ObjectivesOur objectives were to report the economic evaluation methodology for a cluster randomised controlled trial (RCT) of a UK NHS-delivered public health intervention for children with asthma that was evaluated using CPRD and describe the impact of this methodology on results.MethodsCPRD identified eligible patients using predefined asthma diagnostic codes and captured 1-year pre- and post-intervention healthcare contacts (August 2012 to July 2014). Quality-adjusted life-years (QALYs) 4 months post-intervention were estimated by assigning utility values to exacerbation-related contacts; a systematic review identified these utility values because preference-based outcome measures were not collected. Bootstrapped costs were evaluated 12 months post-intervention, both with 1-year regression-based baseline adjustment (BA) and without BA (observed).ResultsOf 12,179 patients recruited, 8190 (intervention 3641; control 4549) were evaluated in the primary analysis, which included patients who received the protocol-defined intervention and for whom CPRD data were available. The intervention's per-patient incremental QALY loss was 0.00017 (bias-corrected and accelerated 95% confidence intervals [BCa 95% CI] -0.00051 to 0.00018) and cost savings were £14.74 (observed; BCa 95% CI -75.86 to 45.19) or £36.07 (BA; BCa 95% CI -77.11 to 9.67), respectively. The probability of cost savings was much higher when accounting for BA versus observed costs due to baseline cost differences between trial arms (96.3 vs. 67.3%, respectively).ConclusionEconomic evaluations using data from a large observational database without any primary data collection is feasible, informative and potentially efficient. Clinical Trials Registration Number: ISRCTN03000938.
| S-EPMC5385191 | biostudies-literature
Project description:AimsThe aim of this systematic review of economic evaluations alongside randomised controlled trials (RCTs) was to provide a comprehensive overview of the evidence concerning cost-effectiveness analyses of common treatment options for major depression.MethodsAn existing database was used to identify studies reporting cost-effectiveness results from RCTs. This database has been developed by a systematic literature search in the bibliographic databases of PubMed, PsychINFO, Embase and Cochrane library from database inception to December 2014. We evaluated the quality of economic evaluations using a 10-item short version of the Drummond checklist. Results were synthesised narratively. The risk of bias of the included RCTs was assessed, based on the Cochrane risk of bias assessment tool.ResultsFourteen RCTs were included from the 5580 articles screened on titles and abstracts. The methodological quality of the health economic evaluations was relatively high and the majority of the included RCTs had low risk of bias in most of Cochrane items except blinding of participants and personnel. Cognitive behavioural therapy was examined in seven trials as part of a variety of treatment protocols and seems cost-effective compared with pharmacotherapy in the long-term. However cost-effectiveness results for the combination of psychotherapy with pharmacotherapy are conflicting and should be interpreted with caution due to limited comparability between the examined trials. For several treatments, only a single economic evaluation was reported as part of a clinical trial. This was the case for comparisons between different classes of antidepressants, for several types of psychotherapy (behavioural activation, occupational therapy, interpersonal psychotherapy, short-term psychotherapy, psychodynamic psychotherapy, rational emotive behavioural therapy, solution focused therapy), and for transcranial magnetic stimulation v. electroconvulsive therapy. The limited evidence base for these interventions means generalisations, based on economic evaluation alongside clinical trials, cannot easily be made.ConclusionsThere is some economic evidence underpinning many of the common treatment options for major depression. Wide variability was observed in study outcomes, probably attributable to differences in population, interventions or follow-up periods. For many interventions, only a single economic evaluation alongside clinical trials was identified. Thus, significant economic evidence gaps remain in the area of major depressive disorder.
| S-EPMC6998890 | biostudies-literature
Project description:Online labor markets provide new opportunities for behavioral research, but conducting economic experiments online raises important methodological challenges. This particularly holds for interactive designs. In this paper, we provide a methodological discussion of the similarities and differences between interactive experiments conducted in the laboratory and online. To this end, we conduct a repeated public goods experiment with and without punishment using samples from the laboratory and the online platform Amazon Mechanical Turk. We chose to replicate this experiment because it is long and logistically complex. It therefore provides a good case study for discussing the methodological and practical challenges of online interactive experimentation. We find that basic behavioral patterns of cooperation and punishment in the laboratory are replicable online. The most important challenge of online interactive experiments is participant dropout. We discuss measures for reducing dropout and show that, for our case study, dropouts are exogenous to the experiment. We conclude that data quality for interactive experiments via the Internet is adequate and reliable, making online interactive experimentation a potentially valuable complement to laboratory studies.
| S-EPMC5807491 | biostudies-literature
Project description:BackgroundIn low- and middle-income countries, budget impact is an important criterion for funding new interventions, particularly for large public health investments such as new vaccines. However, budget impact analyses remain less frequently conducted and less well researched than cost-effectiveness analyses.ObjectiveThe objective of this study was to fill the gap in research on budget impact analyses by assessing (1) the quality of stand-alone budget impact analyses, and (2) the feasibility of extending cost-effectiveness analyses to capture budget impact.MethodsWe developed a budget impact analysis checklist and scoring system for budget impact analyses, which we then adapted for cost-effectiveness analyses, based on current International Society for Pharmacoeconomics and Outcomes Research Task Force recommendations. We applied both budget impact analysis and cost-effectiveness analysis checklists and scoring systems to examine the extent to which existing economic evaluations provide sufficient evidence about budget impact to enable decision making. We used rotavirus vaccination as an illustrative case in which low- and middle-income countries uptake has been limited despite demonstrated cost effectiveness. A systematic literature review was conducted to identify economic evaluations of rotavirus vaccine in low- and middle-income countries published between January 2000 and February 2017. We critically appraised the quality of budget impact analyses, and assessed the extension of cost-effectiveness analyses to provide useful budget impact information.ResultsSix budget impact analyses and 60 cost-effectiveness analyses were identified. Budget impact analyses adhered to most International Society for Pharmacoeconomics and Outcomes Research recommendations, with key exceptions being provision of undiscounted financial streams for each budget period and model validation. Most cost-effectiveness analyses could not be extended to provide useful budget impact information; cost-effectiveness analyses also rarely presented undiscounted annual costs, or estimated financial streams during the first years of programme scale-up.ConclusionsCost-effectiveness analyses vastly outnumber budget impact analyses of rotavirus vaccination, despite both being critical for policy decision making. Straightforward changes to the presentation of cost-effectiveness analyses results could facilitate their adaptation into budget impact analyses.
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Project description:Advanced health economic analysis techniques currently performed in Microsoft Excel, such as incorporating heterogeneity, time-dependent transitions and a value of information analysis, can be easily transferred to R. Often the outputs of survival analyses (such as Weibull regression models) will estimate the impacts of correlated patient characteristics on patient outcomes, and are utilised directly as inputs for health economic decision models. This tutorial provides a step-by-step guide of how to conduct such analyses with a Markov model developed in R, and offers a comparison with established analyses performed in Microsoft Excel. This is done through the conversion of a previously published Microsoft Excel case study of a hip replacement surgery cost-effectiveness model. We hope that this paper can act as a facilitator in switching decision models from Microsoft Excel to R for complex health economic analyses, providing open-access code and data, suitable for future adaptation.
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Project description:It is becoming increasingly popular and straightforward to collect data in cognitive psychology through web-based studies. In this paper, I review issues around web-based data collection for the purpose of numerical cognition research. Provided that the desired type of data can be collected through a web-browser, such online studies offer numerous advantages over traditional forms of physical lab-based data collection, such as gathering data from larger sample sizes in shorter time-windows and easier access to non-local populations. I then present results of two replication studies that employ classical paradigms in numerical cognition research: the number-size congruity paradigm and comparison to a given standard, which also included a masked priming manipulation. In both replications, reaction times and error rates were comparable to original, physical lab-based studies. Consistent with the results of original studies, a distance effect, a congruity effect, and a priming effect were observed. Data collected online thus offers a level of reliability comparable to data collected in a physical lab when it comes to questions in numerical cognition.
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