Combining estimates of interest in prognostic modelling studies after multiple imputation: current practice and guidelines

Background: Multiple imputation (MI) provides an effective approach to handle missing covariate data within prognostic modelling studies, as it can properly account for the missing data uncertainty. The multiply imputed datasets are each analysed using standard prognostic modelling techniques to obtain the estimates of interest. The estimates from each imputed dataset are then combined into one overall estimate and variance, incorporating both the within and between imputation variability. Rubin's rules for combining these multiply imputed estimates are based on asymptotic theory. The resulting combined estimates may be more accurate if the posterior distribution of the population parameter of interest is better approximated by the normal distribution. However, the normality assumption may not be appropriate for all the parameters of interest when analysing prognostic modelling studies, such as predicted survival probabilities and model performance measures. Methods: Guidelines for combining the estimates of interest when analysing prognostic modelling studies are provided. A literature review is performed to identify current practice for combining such estimates in prognostic modelling studies. Results: Methods for combining all reported estimates after MI were not well reported in the current literature. Rubin's rules without applying any transformations were the standard approach used, when any method was stated. Conclusion: The proposed simple guidelines for combining estimates after MI may lead to a wider and more appropriate use of MI in future prognostic modelling studies

A service oriented approach for guidelines-based clinical decision support using BPMN

Evidence-based medical practice requires that clinical guidelines need to be documented in such a way that they represent a clinical workflow in its most accessible form. In order to optimize clinical processes to improve clinical outcomes, we propose a Service Oriented Architecture (SOA) based approach for implementing clinical guidelines that can be accessed from an Electronic Health Record (EHR) application with a Web Services enabled communication mechanism with the Enterprise Service Bus. We have used Business Process Modelling Notation (BPMN) for modelling and presenting the clinical pathway in the form of a workflow. The aim of this study is to produce spontaneous alerts in the healthcare workflow in the diagnosis of Chronic Obstructive Pulmonary Disease (COPD). The use of BPMN as a tool to automate clinical guidelines has not been previously employed for providing Clinical Decision Support (CDS)

Harmonised Principles for Public Participation in Quality Assurance of Integrated Water Resources Modelling

The main purpose of public participation in integrated water resources modelling is to improve decision-making by ensuring that decisions are soundly based on shared knowledge, experience and scientific evidence. The present paper describes stakeholder involvement in the modelling process. The point of departure is the guidelines for quality assurance for `scientific` water resources modelling developed under the EU research project HarmoniQuA, which has developed a computer based Modelling Support Tool (MoST) to provide a user-friendly guidance and a quality assurance framework that aim for enhancing the credibility of river basin modelling. MoST prescribes interaction, which is a form of participation above consultation but below engagement of stakeholders and the public in the early phases of the modelling cycle and under review tasks throughout the process. MoST is a flexible tool which supports different types of users and facilitates interaction between modeller, manager and stakeholders. The perspective of using MoST for engagement of stakeholders e.g. higher level participation throughout the modelling process as part of integrated water resource management is evaluate

Guidelines for assessing pedestrian evacuation software applications

This paper serves to clearly identify and explain criteria to consider when evaluating the suitability of a pedestrian evacuation software application to assess the evacuation process of a building. Guidelines in the form of nine topic areas identify different modelling approaches adopted, as well as features / functionality provided by applications designed specifically for simulating the egress of pedestrians from inside a building. The paper concludes with a synopsis of these guidelines, identifying key questions (by topic area) to found an evaluation

Introduction

The report provides a state-of-the-art of methodologies and guidelines related to quality assurance in water resources modelling. The conclusions from the present report will form the basis for the further HarmoniQuA work on establishment of a common glossary and a generic set of guidelines and methodologies. HarmoniQuA aims to be a component of a future infrastructure for model based water management at catchment and river basin scal

On Engineering Support for Business Process Modelling and Redesign

Currently, there is an enormous (research) interest in business process redesign (BPR). Several management-oriented approaches have been proposed showing how to make BPR work. However, detailed descriptions of empirical experience are few. Consistent engineering methodologies to aid and guide a BPR-practitioner are currently emerging. Often, these methodologies are claimed to be developed for business process modelling, but stem directly from information system design cultures. We consider an engineering methodology for BPR to consist of modelling concepts, their representation, computerized tools and methods, and pragmatic skills and guidelines for off-line modelling, communicating, analyzing, (re)designing\ud business processes. The modelling concepts form the architectural basis of such an engineering methodology. Therefore, the choice, understanding and precise definition of these concepts determine the productivity and effectiveness of modelling tasks within a BPR project. The\ud current paper contributes to engineering support for BPR. We work out general issues that play a role in the development of engineering support for BPR. Furthermore, we introduce an architectural framework for business process modelling and redesign. This framework consists of a coherent set of modelling concepts and techniques on how to use them. The framework enables the modelling of both the structural and dynamic characteristics of business processes. We illustrate its applicability by modelling a case from service industry. Moreover, the architectural framework supports abstraction and refinement techniques. The use of these techniques for a BPR trajectory are discussed

The challenges, uncertainties and opportunities of bioaerosol dispersion modelling from open composting facilities

Bioaerosols are ubiquitous organic particles that comprise viruses, bacteria and coarser fractions of organic matter. Known to adversely affect human health, the impact of bioaerosols on a population often manifests as outbreaks of illnesses such as Legionnaires Disease and Q fever, although the concentrations and environmental conditions in which these impacts occur are not well understood. Bioaerosol concentrations vary from source to source, but specific human activities such as water treatment, intensive agriculture and composting facilitate the generation of bioaerosol concentrations many times higher than natural background levels. Bioaerosols are not considered ‘traditional’ pollutants in the same way as PM10, PM2.5, and gases such as NO2, and consequently dispersion models do not include a bespoke method for their assessment. As identified in previous studies, priority areas for improving the robustness of these dispersion models include: 1) the development of bespoke monitoring studies designed to generate accurate modelling input data; 2) the publication of a robust emissions inventory; 3) a code of practice to provide guidelines for consistent bioaerosol modelling practices; and 4) a greater understanding of background bioaerosol emissions. The aim of this research project, funded by the Natural Environmental Research Council (NERC), is to address these key areas through a better understanding of the generation, concentration and potential dispersion of bioaerosols from intensive agricultural and biowaste facilities, using case studies developed at specific locations within the UK. The objective is to further refine existing bioaerosol monitoring and modelling guidelines to provide a more robust framework for regulating authorities and site operators. This contribution outlines the gaps that hinder robust dispersion modelling, and describes the on-site bioaerosol data collection methods used in the study, explaining how they might be used to close these gaps. Examples of bioaerosol dispersion modelled using ADMS 5 are presented and discussed

Model-building of multiple binary logit using model averaging

Many researchers had been carried out on the study of statistical modelling, making it easier for new researchers in many sectors (social sciences, economics, medical, and etc.) to obtain knowledge in order to ease their research study. Nevertheless, there is still no agreed guidelines in obtaining the best model for multiple binary logit (MBL) using model averaging (MA). This research will demonstrate the proper guidelines to obtain best MBL model by using MA. Upper Gastrointestinal Bleed (UGIB) data were studied to illustrate the process of model-building using the proposed guidelines. This study will pinpoint the factors with high possibility leading to mortality of UGIB patients using obtained best model. Corrected Akaike Information Criteria (AICc) and Bayesian Information Criteria (BIC) were used to compute the weights in model averaging method. The performance of the models was computed by using Root mean square error (RMSE) and mean absolute error (MAE). Model obtained by using BIC weights showed a better performance since the RMSE and MAE values are lower compared to model obtained using AICc weights. The factors that affects the survivability of UGIB patients are shock score, comorbidity and rebleed. In conclusion, model-building of multiple binary logit using model averaging showed a better performance when using BIC