Fatemeh Hoda Moghimi

Using ANT to uncover the full potential of an intelligent operational planning and support tool (IOPST) for acute healthcare contexts

Based on initial pre-clinical data and results from focus group studies, proof of concept for an intelligent operational planning and support tool (IOPST) for nursing in acute healthcare contexts has been demonstrated. However, moving from a simulated context to a large scale clinical trial brings potential challenges associated with the many complexities and multiple people-technology interactions. To enable an in depth and rich analysis of such a context, it is the contention of this paper that incorporating an Actor-Network Theory (ANT) lens to facilitate analysis will be a prudent option as discussed below.

Using Technology Solutions to Streamline Healthcare Processes for Nursing: The Case of an Intelligent Operational Planning Support Tool (IOPST) Solution

Identifying the value stream relating to healthcare processes primarily focuses around diagnosing and treating patients coupled with removing waste. This is now becoming a key priority for many healthcare organisations globally, yet remains an area that is significantly under researched especially with regard to nursing. Lean thinking, as a method to redesign processes in order to improve outcomes has been used with success especially in the manufacturing sector, and now, given the importance of identifying and creating value in healthcare processes, is becoming of increasing interest within various healthcare contexts. In this chapter, we discuss how lean thinking as a management approach, with focuses on operational aspects, can be used to facilitate effective and efficient nursing care. We illustrate with the example of an Intelligent Operational Planning Support Tool (IOPST) solution.

Improving e-Performance Management in Healthcare Using Intelligent IT Solutions

Leading healthcare organizations are discovering the power of a performance management approach, driven by intelligent solutions (Hurst and Jee-Hughes 2001). Moreover, IT solution providers are nowadays developing and providing internet based electronic services (e-services) featuring various intelligent functions. This then necessitates the development of an e-performance management application to improve performance management efficiency in the healthcare area by using such intelligent e-services. Specifically, this chapter examines how a web based performance management application, will transform healthcare as hospitals strive to become more efficient in the way they manage their resources and deliver quality service. Through our proposed application, some services are being put into electronic form at an exponential rate with the result that information can be managed as never before. Such applications provide the possibility to engage clinical staff and patients and their families in decision-making, giving them greater responsibility for their own health. Thus, this chapter explores such technologies as business intelligence (BI) led realtime performance management, both as a concept and as a technology, and defines some of the associated knowledge driven health solutions followed by an e-performance management application.

A Decision-making Model to Choose Business Intelligence Platforms for Organizations

In recent time, technology applications in different fields, especially Business Intelligence (BI) have been developed rapidly and considered to be one of the most significant uses of information technology with special position reserved. The application of BI systems provides organizations with a sense of superiority in the competitive environment. Despite many advantages, the companies applying such systems may also encounter problems in decision-making process because of the highly diversified interactions within the systems. Hence, the choice of a suitable BI platform is important to take the great advantage of using information technology in all organizational fields. The current research aims at addressing the problems existed in the organizational decision-making process, proposing and implementing a suitable BI platform using Iranian companies as case study. The paper attempts to present a solitary model based on studying different methods in BI platform choice and applying the chosen BI platform for different decisionmaking processes. The results from evaluating the effectiveness of subsequently implementing the model for Iranian Industrial companies are discussed.

Artificial Neural Network Excellence to Facilitate Lean Thinking Adoption in Healthcare Contexts

Over the years, healthcare organisations have improved their processes, services, and outcomes significantly. However, with the increasing importance placed on value making, healthcare organisations too often are struggling to demonstrate best performance and/or appropriate and sustained quality of care. Hence, in this chapter we explore the benefits of using artificial neural network (ANN) techniques to identify lost value for the healthcare organisations and to facilitate Lean thinking adoption.

An Intelligence Risk Detection Framework to Improve Decision Efficiency in Healthcare Contexts: The Example of Pediatric Congenital Heart Disease

Superior decision making in healthcare can literally mean the difference between life and death. Given the time pressures faced by healthcare professionals coupled with the need to process large amounts of disparate data and information to make appropriate treatment decisions, these professionals are faced with an increasingly challenging work context. We contend that such a context is appropriate for the application of real time intelligent risk detection decision support systems and try to develop a suitable model. To illustrate the benefits of risk detection to improve decision efficacy in healthcare contexts we focus on the case of Congenital Heart Disease (CHD), an area which requires complex high risk decisions to facilitate identification of appropriate treatment strategies.

Initiatives of Service-Oriented Architecture Towards Performance Improvement in Healthcare

In healthcare contexts, performance improvement is always one of the top priorities for stakeholders. The performance improvement history demonstrates outcomes of applying lots of techniques and approaches to enhance performance in different healthcare dimensions. However, due to the increasing use of computer-based solutions in healthcare, performance of technology solutions has been also a critical dimension which should be improved. Therefore, considering the importance of healthcare technology solutions performance, this chapter outlines how service-oriented architecture can facilitate performance improvement using well-known methods of Lean Thinking. In addition, this study tries to identify key architectural requirements in order to propose a conceptual model based on key concepts of these methods.

Applying predictive analytics to develop an intelligent risk detection application for healthcare contexts.

Healthcare is an information rich industry where successful outcomes require the processing of multi-spectral data and sound decision making. The exponential growth of data and big data issues coupled with a rapid increase of service demands in healthcare contexts today, requires a robust framework enabled by IT (information technology) solutions as well as real-time service handling in order to ensure superior decision making and successful healthcare outcomes. Such a context is appropriate for the application of real time intelligent risk detection decision support systems using predictive analytic techniques such as data mining. To illustrate the power and potential of data science technologies in healthcare decision making scenarios, the use of an intelligent risk detection (IRD) model is proffered for the context of Congenital Heart Disease (CHD) in children, an area which requires complex high risk decisions that need to be made expeditiously and accurately in order to ensure successful healthcare outcomes.

Applying the IPM Framework to Improve Remote Performance Management in the Contexts of Chronic Disease Care

The exponential growth of data coupled with a rapid increase of service demands in healthcare contexts requires a robust framework, which can support IT intelligent solutions as well as web-based service handling. We proffer the Intelligent Performance Management (IPM) framework as such an Internet based model that can enable greater access to clinical components by providing collaborative layers for service offerings on the web using Business Intelligence techniques. Thus, this chapter examines the technical and conceptual layers of the IPM framework and also defines some of the associated knowledge driven healthcare services by the IPM model in order to enhance healthcare performance management. To illustrate the benefits of the IPM framework to improve web-based performance management in healthcare contexts, we focus on chronic disease care in the case of improving a new wireless monitoring solution, an area, which requires high-quality performance management to facilitate development of appropriate remote care and management.