An investigation into inductive parameter learning in complex hierarchical knowledge structures representing clinical expertise

This dissertation investigates the very important and current problem of modelling human expertise. This is an apparent issue in any computer system emulating human decision making. It is prominent in Clinical Decision Support Systems (CDSS) due to the complexity of the induction process and the vast number of parameters in most cases. Other issues such as human error and missing or incomplete data present further challenges. In this thesis, the Galatean Risk Screening Tool (GRiST) is used as an example of modelling clinical expertise and parameter elicitation. The tool is a mental health clinical record management system with a top layer of decision support capabilities. It is currently being deployed by several NHS mental health trusts across the UK. The aim of the research is to investigate the problem of parameter elicitation by inducing them from real clinical data rather than from the human experts who provided the decision model. The induced parameters provide an insight into both the data relationships and how experts make decisions themselves. The outcomes help further understand human decision making and, in particular, help GRiST provide more accurate emulations of risk judgements. Although the algorithms and methods presented in this dissertation are applied to GRiST, they can be adopted for other human knowledge engineering domains.

Ambulatory electroencephalogram in children:a prospective clinical audit of 100 cases

Ambulatory electroencephalogram has been used for differentiating epileptic from nonepileptic events, recording seizure frequency and classification of seizure type. We studied 100 consecutive children prospectively aged 11 days to 16 years that were referred for an ambulatory electroencephalogram to a regional children's hospital. Ambulatory electroencephalogram was clinically useful in contributing to a clinical diagnosis in 71% of children who were referred with a range of clinical questions. A diagnosis of epileptic disorder was confirmed by obtaining an ictal record in 26% and this included 11 children that had previously normal awake and or sleep electroencephalogram. We recommend making a telephone check of the current target event frequency and prioritising those with typical events on most days in order to improve the frequency of recording a typical attack.

Technological enhancements to optometric clinical tests

A sizeable amount of the testing in eye care, requires either the identification of targets such as letters to assess functional vision, or the subjective evaluation of imagery by an examiner. Computers can render a variety of different targets on their monitors and can be used to store and analyse ophthalmic images. However, existing computing hardware tends to be large, screen resolutions are often too low, and objective assessments of ophthalmic images unreliable. Recent advances in mobile computing hardware and computer-vision systems can be used to enhance clinical testing in optometry. High resolution touch screens embedded in mobile devices, can render targets at a wide variety of distances and can be used to record and respond to patient responses, automating testing methods. This has opened up new opportunities in computerised near vision testing. Equally, new image processing techniques can be used to increase the validity and reliability of objective computer vision systems. Three novel apps for assessing reading speed, contrast sensitivity and amplitude of accommodation were created by the author to demonstrate the potential of mobile computing to enhance clinical measurement. The reading speed app could present sentences effectively, control illumination and automate the testing procedure for reading speed assessment. Meanwhile the contrast sensitivity app made use of a bit stealing technique and swept frequency target, to rapidly assess a patient’s full contrast sensitivity function at both near and far distances. Finally, customised electronic hardware was created and interfaced to an app on a smartphone device to allow free space amplitude of accommodation measurement. A new geometrical model of the tear film and a ray tracing simulation of a Placido disc topographer were produced to provide insights on the effect of tear film breakdown on ophthalmic images. Furthermore, a new computer vision system, that used a novel eye-lash segmentation technique, was created to demonstrate the potential of computer vision systems for the clinical assessment of tear stability. Studies undertaken by the author to assess the validity and repeatability of the novel apps, found that their repeatability was comparable to, or better, than existing clinical methods for reading speed and contrast sensitivity assessment. Furthermore, the apps offered reduced examination times in comparison to their paper based equivalents. The reading speed and amplitude of accommodation apps correlated highly with existing methods of assessment supporting their validity. Their still remains questions over the validity of using a swept frequency sine-wave target to assess patient’s contrast sensitivity functions as no clinical test provides the range of spatial frequencies and contrasts, nor equivalent assessment at distance and near. A validation study of the new computer vision system found that the authors tear metric correlated better with existing subjective measures of tear film stability than those of a competing computer-vision system. However, repeatability was poor in comparison to the subjective measures due to eye lash interference. The new mobile apps, computer vision system, and studies outlined in this thesis provide further insight into the potential of applying mobile and image processing technology to enhance clinical testing by eye care professionals.

A KM perspective on implementing an electronic patient record within an NHS hospital

The Electronic Patient Record (EPR) is being developed by many hospitals in the UK and across the globe. We class an EPR system as a type of Knowledge Management System (KMS), in that it is a technological tool developed to support the process of knowledge management (KM). Healthcare organisations aim to use these systems to provide a vehicle for more informed and improved clinical decision making thereby delivering reduced errors and risks, enhanced quality and consequently offering enhanced patient safety. Finding an effective way for a healthcare organisation to practically implement these systems is essential. In this study we use the concept of the business process approach to KM as a theoretical lens to analyse and explore how a large NHS teaching hospital developed, executed and practically implemented an EPR system. This theory advocates the importance of taking into account all organizational activities - the business processes - in considering any KM initiatives. Approaching KM through business processes allows for a more holistic view of the requirements across a process: emphasis is placed on how particular activities are performed, how they are structured and what knowledge demanded and not just supplied across each process. This falls in line with the increased emphasis in healthcare on patient-centred approaches to care delivery. We have found in previous research that hospitals are happy with the delivery of patient care being referred to as their 'business'. A qualitative study was conducted over a two and half year period with data collected from semi-structured interviews with eight members of the strategic management team, 12 clinical users and 20 patients in addition to non- participant observation of meetings and documentary data. We believe that the inclusion of patients within the study may well be the first time this has been done in examining the implementation of a KMS. The theoretical propositions strategy was used as the overarching approach for data analysis. Here Initial theoretical research themes and propositions were used to help shape and organise the case study analysis. This paper will present preliminary findings about the hospital's business strategy and its links to the KMS strategy and process.

Implementing a knowledge management system within an NHS hospital:a case study exploring the roll-out of an Electronic Patient Record (EPR)

This research aims to contribute to understanding the implementation of knowledge management systems (KMS) in the field of health through a case study, leading to theory building and theory extension. We use the concept of the business process approach to knowledge management as a theoretical lens to analyse and explore how a large teaching hospital developed, executed and practically implemented a KMS. A qualitative study was conducted over a 2.5 year period with data collected from semi-structured interviews with eight members of the strategic management team, 12 clinical users and 20 patients in addition to non-participant observation of meetings and documents. The theoretical propositions strategy was used as the overarching approach for data analysis. Our case study provides evidence that true patient centred approaches to supporting care delivery with a KMS benefit from process thinking at both the planning and implementation stages, and an emphasis on the knowledge demands resulting from: the activities along the care pathways; where cross-overs in care occur; and knowledge sharing for the integration of care. The findings also suggest that despite the theoretical awareness of KMS implementation methodologies, the actual execution of such systems requires practice and learning. Flexible, fluid approaches through rehearsal are important and communications strategies should focus heavily on transparency incorporating both structured and unstructured communication methods.