Managing information and knowledge within maternity services: Privacy and consent issues.

OBJECTIVE: Electronic Patient Records have improved vastly the quality and efficiency of care delivered. However, the formation of single demographic database and the ease of electronic information sharing give rise to many concerns including issues of consent, by whom and how data are accessed and used. This paper examines the organizational and socio-technical issues related to privacy, confidentiality and security when employing electronic records within a maternity service hospital in England. METHODS: A preliminary questionnaire was administered (n = 52), in total, 24 responses were received. Sixteen responses were from personnel in the information technology department, 5 from health information department and 3 from midwifery managers. This was followed by a semi-structured interview with representatives from the clinical and technological side. RESULTS: A number of issues related to information governance (IG) have been identified, especially breaches on sharing personal information without consent from the patients have been identified as one immediate challenge that needs to be fixed. CONCLUSION: There is an immediate need for more robust, realistic, built-in accountability both locally and nationally on data sharing. A culture of ownership and strict adherence to IG principles is paramount. Focused training in the area of data, information and knowledge sharing will bring in a balance of legitimate usage against the individual's rights to confidentiality and privacy.

Predicting breast screening attendance using machine learning techniques.

Machine learning-based prediction has been effectively applied for many healthcare applications. Predicting breast screening attendance using machine learning (prior to the actual mammogram) is a new field. This paper presents new predictor attributes for such an algorithm. It describes a new hybrid algorithm that relies on back-propagation and radial basis function-based neural networks for prediction. The algorithm has been developed in an open source-based environment. The algorithm was tested on a 13-year dataset (1995-2008). This paper compares the algorithm and validates its accuracy and efficiency with different platforms. Nearly 80% accuracy and 88% positive predictive value and sensitivity were recorded for the algorithm. The results were encouraging; 40-50% of negative predictive value and specificity warrant further work. Preliminary results were promising and provided ample amount of reasons for testing the algorithm on a larger scale.

Exploring the link between populomics and knowledge management: patient-oriented case exemplars.

The challenge of population-level health problems, such as healthcare disparities, encompasses socio-behavioural, community and biologic factors and advances in information and communication technologies (ICTs). These elements are reflected in the key ethos of contemporary knowledge management (KM), as knowledge emerges from the confluence of people, process and technology. This paper illustrates how knowledge-based health case studies can be used as effective exemplars to illuminate understanding and explore possible connections between populomics and KM.

A systematic approach: optimization of healthcare operations with knowledge management.

Effective decision making is vital in all healthcare activities. While this decision making is typically complex and unstructured, it requires the decision maker to gather multispectral data and information in order to make an effective choice when faced with numerous options. Unstructured decision making in dynamic and complex environments is challenging and in almost every situation the decision maker is undoubtedly faced with information inferiority. The need for germane knowledge, pertinent information and relevant data are critical and hence the value of harnessing knowledge and embracing the tools, techniques, technologies and tactics of knowledge management are essential to ensuring efficiency and efficacy in the decision making process. The systematic approach and application of knowledge management (KM) principles and tools can provide the necessary foundation for improving the decision making processes in healthcare. A combination of Boyd's OODA Loop (Observe, Orient, Decide, Act) and the Intelligence Continuum provide an integrated, systematic and dynamic model for ensuring that the healthcare decision maker is always provided with the appropriate and necessary knowledge elements that will help to ensure that healthcare decision making process outcomes are optimized for maximal patient benefit. The example of orthopaedic operating room processes will illustrate the application of the integrated model to support effective decision making in the clinical environment.

Realising the knowledge spiral in healthcare: the role of data mining and knowledge management.

Knowledge Management (KM) is an emerging business approach aimed at solving current problems such as competitiveness and the need to innovate which are faced by businesses today. The premise for the need for KM is based on a paradigm shift in the business environment where knowledge is central to organizational performance . Organizations trying to embrace KM have many tools, techniques and strategies at their disposal. A vital technique in KM is data mining which enables critical knowledge to be gained from the analysis of large amounts of data and information. The healthcare industry is a very information rich industry. The collecting of data and information permeate most, if not all areas of this industry; however, the healthcare industry has yet to fully embrace KM, let alone the new evolving techniques of data mining. In this paper, we demonstrate the ubiquitous benefits of data mining and KM to healthcare by highlighting their potential to enable and facilitate superior clinical practice and administrative management to ensue. Specifically, we show how data mining can realize the knowledge spiral by effecting the four key transformations identified by Nonaka of turning: (1) existing explicit knowledge to new explicit knowledge, (2) existing explicit knowledge to new tacit knowledge, (3) existing tacit knowledge to new explicit knowledge and (4) existing tacit knowledge to new tacit knowledge. This is done through the establishment of theoretical models that respectively identify the function of the knowledge spiral and the powers of data mining, both exploratory and predictive, in the knowledge discovery process. Our models are then applied to a healthcare data set to demonstrate the potential of this approach as well as the implications of such an approach to the clinical and administrative aspects of healthcare. Further, we demonstrate how these techniques can facilitate hospitals to address the six healthcare quality dimensions identified by the Committee for Quality Healthcare.

Electronic health records approaches and challenges: a comparison between Malaysia and four East Asian countries.

An integrated Lifetime Health Record (LHR) is fundamental for achieving seamless and continuous access to patient medical information and for the continuum of care. However, the aim has not yet been fully realised. The efforts are actively progressing around the globe. Every stage of the development of the LHR initiatives had presented peculiar challenges. The best lessons in life are those of someone else's experiences. This paper presents an overview of the development approaches undertaken by four East Asian countries in implementing a national Electronic Health Record (EHR) in the public health system. The major challenges elicited from the review including integration efforts, process reengineering, funding, people, and law and regulation will be presented, compared, discussed and used as lessons learned for the further development of the Malaysian integrated LHR.

Providing secure mAccess to medical information.

This paper provides the description of a pilot system, HERMES, which allows secure mobile access in geographically distributed medical databases. The HERMES system builds an environment where mobile medical personnel perform secure registration and acquisition of medical information. The system can be used as an overall medical communication system on which diverse medical applications could inter-operate and securely exchange data.

Using actor network theory to understand network centric healthcare operations.

The adoption and diffusion of e-health and the application of ICT in healthcare is being heralded as the panacea with both European and US governments making e-health a priority on their agendas. In this context, a model of networkcentric healthcare operations has been proffered as the best way to maximise the benefits of ICT use in healthcare. We suggest that, before we can move forward and realise such a state, it is vital to examine the critical issues, likely barriers and facilitators and, most importantly, the critical success factors. To do this however, we need an appropriate cognitive lens through which we can capture all the complexities of healthcare dynamics. In this paper we suggest why Actor Network Theory (ANT) should be this lens.

The major barriers and facilitators for the adoption and implementation of knowledge management in healthcare operations.

The importance of Knowledge Management (KM) to organisations in today's competitive environment is being recognised as paramount and significant. This is particularly evident for healthcare both globally and in the USA. The US healthcare system is facing numerous challenges in trying to deliver cost effective, high quality treatments and is turning to KM techniques and technologies for solutions in an attempt to achieve this goal. We examine this by outlining the primary barriers encountered in the adoption and implementation of specific KM technologies in healthcare settings and then examine these in the context of an orthopaedic case vignette. In doing so, we show the benefit of KM tools and techniques for enhancing healthcare delivery.

Improving uptake of a breast screening programme: A knowledge management approach for opportunistic intervention.

Reducing mortality from breast cancer through screening has been accepted as a viable tool and breast screening has attracted a lot of attention from healthcare organisations worldwide. Government funded screening programmes in Europe, the Americas and Australia have made good progress in diagnosing and treating breast cancer through effective screening programmes. The UK's National Health Service (NHS) National Screening Programme manages one of the biggest publicly funded breast screening programmes. In the UK, only 75% of the intended population is screened and a diverse set of efforts has attempted to identify and initiate countermeasures to improve screening attendance. This paper identifies how innovative use of information and communication technologies (ICTs) can be the focus for strategising not only improved screening attendance but also better quality of care for women.

Knowledge management and electronic care records: Incorporating social, legal and ethical issues.

Many challenges face developers of secure computer-based clinical systems but the technical problems are overshadowed by many obstacles, key amongst them being social and ethical issues. A sound Knowledge Management (KM) structure within clinical environments can recognise the responsibility of healthcare professionals to keep patient clinical data (for example, electronic care record (ECR) systems) secure. An arrangement is proposed that gives the most senior clinician in a healthcare facility the ultimate responsibility for security of clinical data held in the organisation. Ideally, the senior clinician would possess training and experience in information systems and their security. Contracts should be developed between healthcare facilities and their patients, defining the limits to the use and disclosure of clinical health data. However, we are observing increasing confusion about the term 'Knowledge Management' which may be limited both its efficacy and effectiveness. Health organisations are referring to the term in various contexts and health informatics articles frequently use the term and interpret it in diverse ways. Given the divergence of views, this paper will attempt to establish KM's efficacy for the implementation of electronic care record systems.

Knowledge creation using artificial intelligence: a twin approach to improve breast screening attendance.

Knowledge management (KM) is rapidly becoming established as a core organizational element within the healthcare industry to assist in the delivery of better patient care. KM is a cyclical process which typically starts with knowledge creation (KC), progresses to knowledge sharing, knowledge accessibility and eventually results in new KC (in the same or a related domain). KC plays a significant role in KM as it creates the necessary "seeds" for propagating many more knowledge cycles. This paper addresses the potential of KC in the context of the UK's National Health Service (NHS) breast screening service. KC can be automated to a greater extent by embedding processes within an artificial intelligence (AI) based environment. The UK breast screening service is concerned about non-attendance and this paper discusses issues pertaining to increasing attendance.

Application of knowledge management and the intelligence continuum for medical emergencies and disaster scenarios.

The world has recently witnessed several large scale natural disasters. These include the Asian tsunami which devastated many of the countries around the rim of the Indian Ocean in December 2004, extensive flooding in many parts of Europe in August 2005, hurricane katrina (September 2005), the outbreak of severe acute respiratory syndrome (SARS) in many regions of Asia and Canada in 2003 and the Pakistan earthquake (towards the end of 2005). Such emergency and disaster situations (E&DS) serve to underscore the utter chaos that ensues in the aftermath of such events, the many casualties and lives lost not to mention the devastation and destruction that is left behind. One recurring theme that is apparent in all these situations is that, irrespective of the warnings of imminent threats, countries have not been prepared and ready to exhibit effective and efficient crisis management. This paper examines the application of the tools, techniques and processes of the knowledge economy to develop a prescriptive model that will support superior decision making in E&DS, thereby enabling effective and efficient crisis management.

The efficacy of knowledge management for personalised healthcare.

This chapter examines some of the key issues surrounding the incorporation of the Knowledge Management (KM) paradigm for personalised healthcare. We discuss the complex nature of KM, some essential concepts necessary to make personalised healthcare a reality and introduce a schematic which illustrates the efficacy of KM for personalised health.

Introduction to the special issue on advances in clinical and health-care knowledge management.

Clinical and health-care knowledge management (KM) as a discipline has attracted increasing worldwide attention in recent years. The approach encompasses a plethora of interrelated themes including aspects of clinical informatics, clinical governance, artificial intelligence, privacy and security, data mining, genomic mining, information management, and organizational behavior. This paper introduces key manuscripts which detail health-care and clinical KM cases and applications.

Clinical knowledge management: an overview of current understanding.

This chapter outlines contributions to a workshop for ICMCC 2005. We details some of the central issues surrounding the incorporation of the Knowledge Management (KM) paradigm for the healthcare and clinical sectors. The complex nature of KM is discussed, together with some essential theories and some contemporary applications of the tools and techniques are presented.