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Two national guidelines were used as standards to evaluate unit guidelines.
The main goal of this study was to evaluate unit operations in two plant-made biomanufacturing processes and estimate the cost of goods of the active ingredient (AI) and the impact of those costs on the cost of the final product.
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To examine changes in compliance over time, checklist-level data were analysed using generalised estimating equations that factored in confounding variables, and statistical process control charts were used to evaluate unit-level data.
Economic factors will also be evaluated; unit costs [ 15] will be estimated for each of the study arms and the cost for each patient calculated.
In June 2014, after a first evaluation phase, FCT announced that 22% of the 322 evaluated units would lose their funding because they had been rated poorly.
Two novel models are presented in this paper for evaluating units based on a profit-dominance criterion.
However, it should be noted that the evaluated units should be quite equal, i.e., with quite similar inputs and outputs.
Additionally, simple or composite indicators based on information from the evaluated units have been the focus of several studies, as described in the work of Archibugi et al. (2009) and Nardo et al. (2008).
Since decision makers are often interested in a complete ranking of the evaluated units according to their performance, procedures that effectively discriminate the units are of key importance for designing intelligent decision support systems to measure and evaluate different alternatives for a better allocation of resources.
Twenty-one subjective criteria were evaluated using a five-point Likert scale (from 1 = unsatisfying to 5 = excellent): five criteria concerned global packaging, nine evaluated unit-dose packaging and seven scored the ampoule itself.
QH reviewed literatures, conducted statistical analysis, and drafted the manuscript; JM and BG advised on and supervised statistical analysis and provided critical input in drafting and revising the manuscript; ND supervised NDNQI data collection, evaluated unit-specific nurse-sensitive data, and provided overall guidance for the manuscript.
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