Decision support and the criminal justice system:an assessment of the potential for utilising technological decision support in undertaking the prosecutorial decision

DUE TO COPYRIGHT RESTRICTIONS ONLY AVAILABLE FOR CONSULTATION AT ASTON UNIVERSITY LIBRARY AND INFORMATION SERVICES WITH PRIOR ARRANGEMENT

Development of a total system simulation modelling approach for management decision support

DUE TO COPYRIGHT RESTRICTIONS ONLY AVAILABLE FOR CONSULTATION AT ASTON UNIVERSITY LIBRARY AND INFORMATION SERVICES WITH PRIOR ARRANGEMENT

Psychological cue use and implications for a clinical decision support system

Effective clinical decision making depends upon identifying possible outcomes for a patient, selecting relevant cues, and processing the cues to arrive at accurate judgements of each outcome's probability of occurrence. These activities can be considered as classification tasks. This paper describes a new model of psychological classification that explains how people use cues to determine class or outcome likelihoods. It proposes that clinicians respond to conditional probabilities of outcomes given cues and that these probabilities compete with each other for influence on classification. The model explains why people appear to respond to base rates inappropriately, thereby overestimating the occurrence of rare categories, and a clinical example is provided for predicting suicide risk. The model makes an effective representation for expert clinical judgements and its psychological validity enables it to generate explanations in a form that is comprehensible to clinicians. It is a strong candidate for incorporation within a decision support system for mental-health risk assessment, where it can link with statistical and pattern recognition tools applied to a database of patients. The symbiotic combination of empirical evidence and clinical expertise can provide an important web-based resource for risk assessment, including multi-disciplinary education and training. © 2002 Informa UK Ltd All rights reserved.

Decision support system for pipeline route selection

Presents information on a study which proposed a decision support system (DSS) for a petroleum pipeline route selection with the application of analytical hierarchy process. Factors governing route-selection for cross-country petroleum pipelines; Application of the DSS from an Indian perspective; Cost benefit comparison of the shortest route and the optimal route; Results and findings.

Investigating mental health risk assessment in primary care and the potential role of a structured decision support tool, GRiST

Aim: To explore current risk assessment processes in general practice and Improving Access to Psychological Therapies (IAPT) services, and to consider whether the Galatean Risk and Safety Tool (GRiST) can help support improved patient care. Background: Much has been written about risk assessment practice in secondary mental health care, but little is known about how it is undertaken at the beginning of patients' care pathways, within general practice and IAPT services. Methods: Interviews with eight general practice and eight IAPT clinicians from two primary care trusts in the West Midlands, UK, and eight service users from the same region. Interviews explored current practice and participants' views and experiences of mental health risk assessment. Two focus groups were also carried out, one with general practice and one with IAPT clinicians, to review interview findings and to elicit views about GRiST from a demonstration of its functionality. Data were analysed using thematic analysis. Findings Variable approaches to mental health risk assessment were observed. Clinicians were anxious that important risk information was being missed, and risk communication was undermined. Patients felt uninvolved in the process, and both clinicians and patients expressed anxiety about risk assessment skills. Clinicians were positive about the potential for GRiST to provide solutions to these problems. Conclusions: A more structured and systematic approach to risk assessment in general practice and IAPT services is needed, to ensure important risk information is captured and communicated across the care pathway. GRiST has the functionality to support this aspect of practice.

Understanding data collection behaviour of mental health practitioners

Failure to detect patients at risk of attempting suicide can result in tragic consequences. Identifying risks earlier and more accurately helps prevent serious incidents occurring and is the objective of the GRiST clinical decision support system (CDSS). One of the problems it faces is high variability in the type and quantity of data submitted for patients, who are assessed in multiple contexts along the care pathway. Although GRiST identifies up to 138 patient cues to collect, only about half of them are relevant for any one patient and their roles may not be for risk evaluation but more for risk management. This paper explores the data collection behaviour of clinicians using GRiST to see whether it can elucidate which variables are important for risk evaluations and when. The GRiST CDSS is based on a cognitive model of human expertise manifested by a sophisticated hierarchical knowledge structure or tree. This structure is used by the GRiST interface to provide top-down controlled access to the patient data. Our research explores relationships between the answers given to these higher-level 'branch' questions to see whether they can help direct assessors to the most important data, depending on the patient profile and assessment context. The outcome is a model for dynamic data collection driven by the knowledge hierarchy. It has potential for improving other clinical decision support systems operating in domains with high dimensional data that are only partially collected and in a variety of combinations.

Support tools for paediatric inpatient prescribers:a review

Prescribing support for paediatrics is diverse and includes both standard texts and electronic tools. Evidence concerning who should be supported and by what method is limited. This review aims to collate the current information available on prescribing support in paediatrics. Many tools designed to support prescribers are technology based. For example, electronic prescribing and smart phone applications. There is a focus on prescriber education both at undergraduate and postgraduate level. In the UK, the majority of inpatient prescribing is done by junior medical staff. It is important to ensure they are competent on qualification and supported in this role. A UK national prescribing assessment is being trialled to test for competence on graduation and there are also tools available to test paediatric prescribing after qualification. No information is available on the tools and resources UK prescribers currently use to support their decision making. One US study reported a decrease in the availability of paediatric prescribing information in a popular reference text. There is limited evidence to show that decisionsupport tools improve patient outcomes, however, there is growing confirmation that electronic prescribing reduces medication errors. There have been reports of new error types, such as selection errors, occurring with the use of electronic prescribing. Another concern with computerised decision-support systems is deciding what alerts should be presented to the prescriber and when/how often in order to avoid alert fatigue. There is little published concerning paediatric alerts perhaps as a consequence of commercial systems often not including paediatric specific support.

A decision support system for waste collection management and its potential improvement with Radio-Frequency Identification Technology (RFID)

Due to vigorous globalisation and product proliferation in recent years, more waste has been produced by the soaring manufacturing activities. This has contributed to the significant need for an efficient waste management system to ensure, with all efforts, the waste is properly treated for recycling or disposed. This paper presents a Decision Support System (DSS) framework, based on Constraint Logic Programming (CLP), for the collection management of industrial waste (of all kinds) and discusses the potential employment of Radio-Frequency Identification Technology (RFID) to improve several critical procedures involved in managing waste collection. This paper also demonstrates a widely distributed and semi-structured network of waste producing enterprises (e.g. manufacturers) and waste processing enterprises (i.e. waste recycling/treatment stations) improving their operations planning by means of using the proposed DSS. The potential RFID applications to update and validate information in a continuous manner to bring value-added benefits to the waste collection business are also presented. © 2012 Inderscience Enterprises Ltd.

Sources of support and expatriation:a multiple stakeholder perspective of expatriate adjustment and performance in Malaysia

This research tests the role of perceived support from multinational corporations and host-country nationals for the adjustment of expatriates and their spouses while on international assignments. The investigation is carried out with matched data from 134 expatriates and their spouses based in foreign multinationals in Malaysia. The results highlight the different reliance on support providers that expatriates and their accompanying spouses found beneficial for acclimatizing to the host-country environment. Improved adjustment in turn was found to have positive effects on expatriates' performance. The research findings have implications for both international human resource management researchers and practitioners. © 2014 © 2014 Taylor & Francis.

Decision support system for vendor managed inventory supply chain:a case study

Vendor-managed inventory (VMI) is a widely used collaborative inventory management policy in which manufacturers manages the inventory of retailers and takes responsibility for making decisions related to the timing and extent of inventory replenishment. VMI partnerships help organisations to reduce demand variability, inventory holding and distribution costs. This study provides empirical evidence that significant economic benefits can be achieved with the use of a genetic algorithm (GA)-based decision support system (DSS) in a VMI supply chain. A two-stage serial supply chain in which retailers and their supplier are operating VMI in an uncertain demand environment is studied. Performance was measured in terms of cost, profit, stockouts and service levels. The results generated from GA-based model were compared to traditional alternatives. The study found that the GA-based approach outperformed traditional methods and its use can be economically justified in small- and medium-sized enterprises (SMEs).

Support for paediatric prescribers:what is discussed at hospital board level?

Prescribing support tools range from traditional printed texts to state-of-the-art computerised decision support systems. Comparison between available literature is difficult due to country-specific resources often being the focus of the research. In the UK, it is widely accepted that hospitals take their own individualised approaches to reducing prescribing errors. Objective - This study focused on specialist paediatric hospitals. It aimed to identify the localised approaches taken by paediatric hospitals to reduce prescribing errors. Method - Applied thematic analysis was used to explore the publically published board meeting minutes from the four specialist stand-alone paediatric hospitals in England. Three years of data was collected from each hospital. Codes were collected into groups to identify themes from the data. Results - The main themes identified were clinician involvement in prescribing support is important; credit card-sized reminder tools are used to provide prescribing guidance; electronic prescribing is considered important for reducing prescribing errors; feedback from clinical pharmacists on prescribing errors is widely used; junior doctors require extra support when prescribing; medical records may be incomplete and specific prescribing support (eg, antibiotic prescribing support) is widely in use. Conclusions - There is no single collaborative approach taken to paediatric prescribing support in English paediatric hospitals. Success of electronic prescribing in English paediatric hospitals is considerably behind leaders such as the USA. Use of clinical pharmacists to support prescribers is important as supported by previous studies in Spain and the USA.

Green manufacturing supply chain design and operations decision support

This special issue of International Journal of Production Research provides a platform for sharing the knowledge base, recent research outputs and a review of recent developments highlighting the critical aspects of green manufacturing supply chain design and operations decision support. The special issue includes 15 contributions presenting new and significant research in the relevant area. Contributions mainly present either a novel green/sustainable manufacturing supply chain design and operations decision support approach applied to a problem, or a state-of-the-art method on green/sustainable factors in supply chain design and operations. The article delineates an overview of the contributions and their significance, and an introspection on the ‘green’ factors involved.

Advanced predictive-analysis-based decision support for collaborative logistics networks

Purpose – The purpose of this paper is to examine challenges and potential of big data in heterogeneous business networks and relate these to an implemented logistics solution. Design/methodology/approach – The paper establishes an overview of challenges and opportunities of current significance in the area of big data, specifically in the context of transparency and processes in heterogeneous enterprise networks. Within this context, the paper presents how existing components and purpose-driven research were combined for a solution implemented in a nationwide network for less-than-truckload consignments. Findings – Aside from providing an extended overview of today’s big data situation, the findings have shown that technical means and methods available today can comprise a feasible process transparency solution in a large heterogeneous network where legacy practices, reporting lags and incomplete data exist, yet processes are sensitive to inadequate policy changes. Practical implications – The means introduced in the paper were found to be of utility value in improving process efficiency, transparency and planning in logistics networks. The particular system design choices in the presented solution allow an incremental introduction or evolution of resource handling practices, incorporating existing fragmentary, unstructured or tacit knowledge of experienced personnel into the theoretically founded overall concept. Originality/value – The paper extends previous high-level view on the potential of big data, and presents new applied research and development results in a logistics application.