Clinical Pathway Enhanced by Knowledge Management Technology

Clinical pathways are complex processes based on knowledge and personal experience, which are essential for high quality patient treatment. However, the insufficient knowledge coverage and representation for detailed clinical pathways makes it difficult to provide accurate information to improve patient safety. The gap between the dynamic practical treatment process and the predefined clinical pathways knowledge becomes an important issue. This chapter discusses how knowledge management enhances the implementation of clinical pathway to achieve medical quality improvement. The relationship between patient safety and the effectiveness of clinical pathway knowledge is discussed. The clinical pathway knowledge management pattern is derived in the context of healthcare knowledge management. More specifically, a norm-based approach is proposed to represent and manage clinical pathway knowledge. Types of knowledge can be represented comprehensively with the taxonomy of norms as useful building blocks to construct the dynamic and accurate clinical pathway knowledge. The multi-agent system embedded with norms is developed to enhance clinical pathway management in the context of complicated healthcare environment. Finally, social-technical issues of implementing knowledge management technologies in practical treatment process are discussed.

G-NO-TECS

This chapter examines the concept of non-technical skills and how deficiencies in this arena can result in medical error.

The SHEEP Model

This chapter explains the development of a model, titled “SHEEP,” to identify quality and safety factors relating to near misses. The model allows frequency of risk factors and their impact to be analysed at departmental or institutional levels, which enables a structured focusing of resources at an organisational level.

The Internet of Things and Opportunities for Pervasive Safety Monitored Health Environments

This chapter discusses the opportunities for new ubiquitous computing technologies, with concentration on the Internet of Things (IoT), to improve patient safety and quality. The authors focus on elective or planned surgical interventions, although the technology is applicable to primary and trauma care. The chapter is divided into three main sections with section 1 covering medical error issues and mechanisms, section 2 introducing Internet of Things, and section 3 discussing how IoT capabilities may address and reduce medical errors. The authors explore the existing theory of errors expounded by Reason (Reason, 2000, 1998; Leape, 1994) to identify perception-, decision-, and knowledge-based medical errors and related processes, environments, and cultural drivers causing error. The authors then introduce the technology of the Internet of Things and identify a range of capabilities from sensing, tracking, control, cooperative, and semantic reasoning. They then show how these new capabilities might be applied to reduce the errors expounded by the discussed error theories. They identify that: IoT enables augmentation of objects, which provides a massive increase in information transfer, thus improving clinician perception and support for decision-making and problem solving; IoT provides a host of additional observers and opportunities, which can shift the focus of overworked clinicians from constant monitoring to undertaking complex actions, such as decision making and care; IoT networks of sensors and actuators, through the addition of semantic and contextual rules, support decision making and facilitate automated monitoring and control of pervasive safety-monitored health environments, thus reducing clinician workload.

A Pharmaco-Cybernetics Approach to Patient Safety

Pharmaco-cybernetics is an upcoming interdisciplinary field that supports our use of medicines and drugs through the combined use of computational technologies and techniques with human-computer-environment interactions to reduce or prevent drug-related problems. The advent of pharmaco-cybernetics has led to the development of various software, tools, and Internet applications that can be used by healthcare practitioners to deliver optimum pharmaceutical care and health-related outcomes. Patients are becoming more informed through health information on the Internet, which empowers them to better participate in the management of their own conditions. Focusing on patients with cancer, this chapter describes the use of a pharmaco-cybernetics approach to identify clinically relevant predictors of two debilitating adverse drug reactions, which are a cause of patient safety – chemotherapy-induced nausea and vomiting and febrile neutropenia. The early identification of such clinical predictors enables clinicians to prevent or reduce the occurrence of adverse drug reactions in cancer patients undergoing chemotherapy through appropriate management strategies. The computational methods used in this approach involve two unsupervised machine-learning techniques – principal component and multiple correspondence analyses. Using two case examples, this chapter shows the potential of machine-learning techniques for identifying patients who are at greater risks of these adverse drug reactions, thus enhancing patient safety. This chapter also aims to increase the awareness among healthcare professionals and clinician-scientists about the usefulness of such techniques in clinical patient populations, so that these can be considered as part of clinical care pathways to enhance patient safety and effectively manage cancer patients on chemotherapy.

Information Architecture for Pervasive Healthcare Information Provision with Technological Implementation

The Pervasive Healthcare Information Provision (PHIP) is a concept that ensures patients are covered with healthcare services with the appropriate information provision together with the technical infrastructure when needed. Clinicians can obtain the real-time information by accessing the electronic patient record that supports decision-making in providing health services. PHIP aims to provide comprehensive healthcare services to its stakeholders covering the social and technical aspect. Information architecture is a high-level map of information requirements of an organisation that possesses business processes and information flows. Organisational semiotics, a fundamental theory for information and communication, helps in understanding the nature of information. It deals with information and information systems in a balanced way, taking account of both the physical space (when physical actions take place) and the information space (which are mainly characterised by information and communication using signs, symbols, and data). Information sharing among multi-stakeholders in decision-making is essential for pervasive healthcare. The information architecture can be reflected in information systems implementation such as Electronic Patient Record (EPR) and other forms. The aim of this chapter is to derive a conceptual model of information architecture for PHIP, including technological implementation via wireless technology. The information architecture serves as requirement engine that covers social and technical needs from both patients and clinicians. The contribution of this research is two fold: 1) establishing the theoretical perspective of information architecture, which serves as backbone to support PHIP, and 2) implementing PHIP via wireless technology and agent-based system.

Workarounds

Patient safety and the quality of clinical interventions rely on the application of best practices in clinical processes to achieve clinical and service specifications for patients. However, outcomes vary due to variations in work activity performance in terms of efficiency and quality, and variations in what is done. This chapter explores the concept of deviations from formal work processes as workarounds in health interventions. It examines workaround evolution and development, the motivation for them, and types. It identifies their positive and negative impact on patient safety and quality. The chapter is based on primary research and workaround case studies of 14 staff in three hospitals. The approach supports the work to develop a generic conceptual normative analysis model of workarounds and adopts BPMN and organisational semiotics to qualitatively and quantitatively define and compare the original work process and workaround. This chapter extends definitions of workaround types and the relationship between actors in the formal work process and informal workaround process. The authors propose a conceptual model to identify the relative safety risk of workarounds and hence their likely patient impact. The discussion focuses on the initial findings of this model on patient safety and how different workaround types impact patient safety. The chapter highlights examples of the clinical work deviations and shows that they can have both positive and negative benefits for patient safety. It emphasises how, using an informatics approach, workarounds need to be considered in detail to understand the motivation and potential impact on health activities.

A New Era for Safety Measurement

This chapter presents current systems thinking concerning patient safety and explores what patient safety actually means, allowing a foundation for a critical review of tools used for safety measurement. Content considers a range of content from hard measures to softer cultural perspectives, thus ensuring that the patient view is not forgotten.

Health IT Policy in the UK

The challenge to provide a nation-wide integrated health service is part of a UK government policy to transform healthcare using information and communications technology. The National Programme for Information Technology launched in 2002 is the largest, non-military, non-scientific government-funded IT programme, with an estimated total cost exceeding £20 bn. This chapter is a longitudinal study of the National Care Record Service, which is the largest part of the programme, aimed to provide 50 million UK (English) citizens with an electronic health record. Using episodic interviewing techniques over ten years and secondary source material, the findings reveal a serious mismatch between health IT policy and the failure to rollout electronic health records on time and within budget. Key stakeholders, notably clinicians and patient groups, continuously question the policy and merits of the programme, not merely as a “technical challenge” but as a means of transforming working practices in healthcare. This study suggests that government agencies therefore need to extend their health technology assessment criteria to include cultural, social, and economic issues, as imposing centrist, top-down health IT policy needs to secure the “buy-in” from diverse and influential groups and individuals to ensure the successful adoption and implementation of health technologies.

Healthcare Resource Sustainability

Health care provision is significantly impacted by the ability of health providers to engineer a viable healthcare space to support care stakeholders needs. In this chapter, the authors discuss and propose use of organisational semiotics as a set of methods to link stakeholders to systems, which allows them to capture data about clinician activity, information transfer, and building use, which in turn allows them to define the value of specific systems in the care environment to specific stakeholders and the dependence between systems in a care space. The authors suggest use of a semantically enhanced Building Information Model (BIM) to support the linking of clinician activity to the physical resource objects and space and facilitate the capture of quantifiable data over time or in relation to key stakeholders. Finally, the authors argue for the inclusion of appropriate stakeholder feedback and persuasive mechanisms to incentivise building user behaviour to support organisational level sustainability policy.