Development of modelling method selection tool for health services management: From problem structuring methods to modelling and simulation methods

Background: There is an increasing recognition that modelling and simulation can assist in the process of designing health care policies, strategies and operations. However, the current use is limited and answers to questions such as what methods to use and when remain somewhat underdeveloped. Aim. The aim of this study is to provide a mechanism for decision makers in health services planning and management to compare a broad range of modelling and simulation methods so that they can better select and use them or better commission relevant modelling and simulation work. Methods. This paper proposes a modelling and simulation method comparison and selection tool developed from a comprehensive literature review, the research team's extensive expertise and inputs from potential users. Twenty-eight different methods were identified, characterised by their relevance to different application areas, project life cycle stages, types of output and levels of insight, and four input resources required (time, money, knowledge and data). Results: The characterisation is presented in matrix forms to allow quick comparison and selection. This paper also highlights significant knowledge gaps in the existing literature when assessing the applicability of particular approaches to health services management, where modelling and simulation skills are scarce let alone money and time. Conclusions: A modelling and simulation method comparison and selection tool is developed to assist with the selection of methods appropriate to supporting specific decision making processes. In particular it addresses the issue of which method is most appropriate to which specific health services management problem, what the user might expect to be obtained from the method, and what is required to use the method. In summary, we believe the tool adds value to the scarce existing literature on methods comparison and selection. © 2011 Jun et al.

Parameter estimation for agenda-based user simulation

This paper presents an agenda-based user simulator which has been extended to be trainable on real data with the aim of more closely modelling the complex rational behaviour exhibited by real users. The train-able part is formed by a set of random decision points that may be encountered during the process of receiving a system act and responding with a user act. A sample-based method is presented for using real user data to estimate the parameters that control these decisions. Evaluation results are given both in terms of statistics of generated user behaviour and the quality of policies trained with different simulators. Compared to a handcrafted simulator, the trained system provides a much better fit to corpus data and evaluations suggest that this better fit should result in improved dialogue performance. © 2010 Association for Computational Linguistics.

A global model for effective use and evaluation of e-learning in health.

Healthcare systems worldwide face a wide range of challenges, including demographic change, rising drug and medical technology costs, and persistent and widening health inequalities both within and between countries. Simultaneously, issues such as professional silos, static medical curricula, and perceptions of "information overload" have made it difficult for medical training and continued professional development (CPD) to adapt to the changing needs of healthcare professionals in increasingly patient-centered, collaborative, and/or remote delivery contexts. In response to these challenges, increasing numbers of medical education and CPD programs have adopted e-learning approaches, which have been shown to provide flexible, low-cost, user-centered, and easily updated learning. The effectiveness of e-learning varies from context to context, however, and has also been shown to make considerable demands on users' motivation and "digital literacy" and on providing institutions. Consequently, there is a need to evaluate the effectiveness of e-learning in healthcare as part of ongoing quality improvement efforts. This article outlines the key issues for developing successful models for analyzing e-health learning.

Policy as a struggle for meaning: disentangling knowledge translation across international health contexts

Over the last decade, research in medical science has focused on knowledge translation and diffusion of best practices to enable improved health outcomes. However, there has been less attention given to the role of policy in influencing the translation of best practice across different national contexts. This paper argues that the underlying set of public discourses of healthcare policy significantly influences its development with implications for the dissemination of best practices. Our research uses Critical Discourse Analysis to examine the policy discourses surrounding the treatment of stroke across Canada and the U.K. It focuses in specific on how concepts of knowledge translation, user empowerment, and service innovation construct different accounts of the health service in the two countries. These findings provide an important yet overlooked starting point for understanding the role of policy development in knowledge transfer and the translation of science into health practice. © 2011 Operational Research Society. All rights reserved.

Articulating current service development practices: a qualitative analysis of eleven mental health projects.

BACKGROUND: The utilisation of good design practices in the development of complex health services is essential to improving quality. Healthcare organisations, however, are often seriously out of step with modern design thinking and practice. As a starting point to encourage the uptake of good design practices, it is important to understand the context of their intended use. This study aims to do that by articulating current health service development practices. METHODS: Eleven service development projects carried out in a large mental health service were investigated through in-depth interviews with six operation managers. The critical decision method in conjunction with diagrammatic elicitation was used to capture descriptions of these projects. Stage-gate design models were then formed to visually articulate, classify and characterise different service development practices. RESULTS: Projects were grouped into three categories according to design process patterns: new service introduction and service integration; service improvement; service closure. Three common design stages: problem exploration, idea generation and solution evaluation - were then compared across the design process patterns. Consistent across projects were a top-down, policy-driven approach to exploration, underexploited idea generation and implementation-based evaluation. CONCLUSIONS: This study provides insight into where and how good design practices can contribute to the improvement of current service development practices. Specifically, the following suggestions for future service development practices are made: genuine user needs analysis for exploration; divergent thinking and innovative culture for idea generation; and fail-safe evaluation prior to implementation. Better training for managers through partnership working with design experts and researchers could be beneficial.

A global model for effective use and evaluation of e-learning in health.

Healthcare systems worldwide face a wide range of challenges, including demographic change, rising drug and medical technology costs, and persistent and widening health inequalities both within and between countries. Simultaneously, issues such as professional silos, static medical curricula, and perceptions of "information overload" have made it difficult for medical training and continued professional development (CPD) to adapt to the changing needs of healthcare professionals in increasingly patient-centered, collaborative, and/or remote delivery contexts. In response to these challenges, increasing numbers of medical education and CPD programs have adopted e-learning approaches, which have been shown to provide flexible, low-cost, user-centered, and easily updated learning. The effectiveness of e-learning varies from context to context, however, and has also been shown to make considerable demands on users' motivation and "digital literacy" and on providing institutions. Consequently, there is a need to evaluate the effectiveness of e-learning in healthcare as part of ongoing quality improvement efforts. This article outlines the key issues for developing successful models for analyzing e-health learning.