A proposed semantic framework for diabetes education content management, customisation and delivery within the M2DM project

M2DM (multi access services for telematic management of diabetes mellitus, ) is an EU-funded telemedicine project that aims at increasing the quality of diabetes care by improving communication between patients and caregivers. As part of this project, we have undertaken the initial work of describing the necessary requirements (framework) of an advanced educational component for M2DM in accordance with the latest Semantic Web concepts. This paper describes our proposed semantic framework for educational content management, customisation and delivery. A big internet challenge today is to find and push situation and user-specific quality knowledge to users based on their actual individual needs, circumstances and profiles at any given time. We believe that the semantic framework presented in this paper could be a good step towards meeting this challenge. Benefits for users, both developers and end users, of adopting such framework are also discussed. The ideas discussed in this paper could be easily adapted to other similar services besides M2DM and to different health topics besides diabetes mellitus.

A dynamic problem to knowledge linking Semantic Web service based on clinical codes

Many information needs arise during everyday clinical practice. Problem to knowledge linking aims to answer these needs by providing contextually appropriate medical knowledge in the right place and at the right time. Empirical evidence shows that well-informed physicians and patients are able to make better clinical decisions that positively affect healthcare outcomes. This paper reports on the design and development of a re-usable and flexible Semantic Web problem to knowledge linking service. The service makes use of metadata and clinical codes contextually to link disparate Electronic Patient Record clients to resources in an online medical knowledge service (HealthCyberMap). Clinical codes act as crisp knowledge hooks, providing a reliable common backbone language for communication between Electronic Patient Records and HealthCyberMap. Ideas to improve the service are also discussed. By minimizing irrelevant leads (noise) and reducing the time needed to find relevant information (the right contextually relevant knowledge is linked to real patient data in the Electronic Patient Record), the system is potentially beneficial. The actual success of the system will depend on the quality and granularity of metadata it uses and the topical coverage and quality of resources to which it points.

Health geomatics: an enabling suite of technologies in health and healthcare

This Methodolical Review describes how health geomatics can improve our understanding of the important relationship between location and health, and thus assist us in Public Health tasks like disease prevention, and also in better healthcare service planning. The reader is first introduced to health geography and its two main divisions, disease ecology and healthcare delivery, followed by an overview of the basic concepts and principles of health geomatics. Topics covered include geographical information systems (GIS), GIS modeling, and GIS-related technologies (remote sensing and the global positioning system). We also present a number of real-life health geomatics applications and projects, with pointers to further studies and resources. Finally, we discuss the barriers facing the adoption of GIS technology in the health sector, including data availability/quality issues. The authors believe that we still need to combat many cultural and organizational barriers, including "spatial illiteracy" among healthcare workers, while making the tools cheaper and easier to learn and use, before health geomatics can become a mainstream technology in the health sector like today's spreadsheets and databases.

The use of quality benchmarking in assessing web resources for the dermatology virtual branch library of the National electronic Library for Health (NeLH)

BACKGROUND

In 1998, the U.K. National Health Service Information for Health Strategy proposed the implementation of a National electronic Library for Health to provide clinicians, healthcare managers and planners, patients and the public with easy, round the clock access to high quality, up-to-date electronic information on health and healthcare. The Virtual Branch Libraries are among the most important components of the National electronic Library for Health. They aim at creating online knowledge based communities, each concerned with some specific clinical and other health-related topics.

OBJECTIVES

This study is about the envisaged Dermatology Virtual Branch Libraries of the National electronic Library for Health. It aims at selecting suitable dermatology Web resources for inclusion in the forthcoming Virtual Branch Libraries after establishing preliminary quality benchmarking rules for this task. Psoriasis, being a common dermatological condition, has been chosen as a starting point.

METHODS

Because quality is a principal concern of the National electronic Library for Health, the study includes a review of the major quality benchmarking systems available today for assessing health-related Web sites. The methodology of developing a quality benchmarking system has been also reviewed. Aided by metasearch Web tools, candidate resources were hand-selected in light of the reviewed benchmarking systems and specific criteria set by the authors.

RESULTS

Over 90 professional and patient-oriented Web resources on psoriasis and dermatology in general are suggested for inclusion in the forthcoming Dermatology Virtual Branch Libraries. The idea of an all-in knowledge-hallmarking instrument for the National electronic Library for Health is also proposed based on the reviewed quality benchmarking systems.

CONCLUSIONS

Skilled, methodical, organized human reviewing, selection and filtering based on well-defined quality appraisal criteria seems likely to be the key ingredient in the envisaged National electronic Library for Health service. Furthermore, by promoting the application of agreed quality guidelines and codes of ethics by all health information providers and not just within the National electronic Library for Health, the overall quality of the Web will improve with time and the Web will ultimately become a reliable and integral part of the care space.

Estimating protein turnover with a [15N,13C]leucine tracer: a study using simulated data

We explore the use of [15N,13C]leucine tracer to estimate whole-body fractional rates of a fast-turning-over protein pool employing synthetic data. The kinetics of [15N,13C]leucine tracer are simplified compared with those of traditional leucine tracers and benefit from irreversible transamination to [13C]alpha-ketoisocaproaic acid (KIC) resulting in a simplified model structure. A three-compartment model of [15N,13C]leucine kinetics was proposed and evaluated using data generated by a Reference Model (based on a model by Cobelli et al.). The results suggest that fractional turnover rates of a fast-turning-over protein pool can be estimated with a low but acceptable precision during a six-hour constant intravenous infusion of [15N,13C]leucine with frequent sampling of plasma tracer-to-tracee ratio (TTR) of [15N,13C]leucine. We conclude that [15N,13C]leucine may be useful for the measurement of protein kinetics and its full potential should be explored in clinical studies with compartmental data analysis.

Clinical decision support, systems methodology, and telemedicine: their role in the management of chronic disease

In this paper, the design and evaluation of decision support systems, including those incorporating a telematic component, are considered. It is argued that effective design and evaluation are dependent upon the adoption of appropriate methodology set firmly within a systemic framework. Systems modeling is proposed as an approach to system design, with evaluation adopting an approach incorporating evaluability analysis and formative and summative evaluation, including the use of stakeholder matrix analysis. The relevance of such systemic methodology is demonstrated in the context of diabetes and end-stage renal disease as examples of the generic clinical problem of the management of chronic disease.

UTOPIA: a consultation system for visit-by-visit diabetes management

UTOPIA (UTilities for OPtimizing Insulin Adjustment) is a prototype computer system proposed to support home data analysis and therapy recommendations for the individual patient. The paper describes methods of analysis and their incorporation into an overall system design that matches the iterative practices at the physician-patient consultation from visit to visit. Four modules support home data display and comparison with clinical measurements; extraction of blood glucose trends and daily cycles using time series analysis, learning relationships between insulin adjustments and changes in time series patterns via a parametric, linear systems model; and advice generation by solving the linear equation for candidate insulin adjustments. Concepts and methods are placed in context, with a discussion of comparable and related research.

Methodological issues in validating decision-support systems for insulin dosage adjustment

Safety and reliability of advice from new computer systems should be confirmed before embarking on prospective hospital trials. This process of preliminary testing is termed 'validation'. Though it forms a fundamental stage in system development, few standards exist for choosing and implementing tests. In the present paper, a validation methodology is developed in the domain of diabetes and intended for general use in chronic health management. It is based on a peer review protocol and incorporates empirical measures indicating: applicability of results to the real environment; variation among doctors; comparisons between doctors' and computer advice; and relative merits of different computer algorithms.

Time series analysis and control of blood glucose levels in diabetic patients

This paper describes features of a computer-based decision support system which is being developed to assist in the management of insulin-dependent diabetic patients. The clinical context is the provision of advice on the adjustment of the basic insulin regimen such as occurs at regular visits to the clinician. The integrated system combines data processing and interpretation, generation of qualitative advice and testing the implications of that advice using a glucose/insulin dynamic simulator. The two major features described in this paper are time series analysis of blood glucose data, and their interpretation in relation to the provision of advice for controlling the patient's blood glucose level. It is demonstrated that two approaches may be adopted in such time series analysis: an intuitive approach, manipulating symbolic representations of the data, and formal time series methods which decompose the series into clinically related components.

Validation of a metabolic prototype to assist in the treatment of insulin-dependent diabetes mellitus

This paper describes the principles and prototyping of a computer system to assist in the treatment of patients with insulin-dependent (type 1) diabetes mellitus. The system adopts a mixed approach involving rule-based qualitative algebra and a dynamic mathematical model to define the relationships between insulin dosage, diet and glycaemic response. The rule-based system (KBS), implemented in PROLOG, can be used to generate qualitative therapeutic advice. These suggestions are quantified and rank-ordered by the use of a mathematical model of glucose-insulin interaction in type 1 diabetes mellitus, with parameters adjusted for individual patients. In this paper an overview of the integrated prototype, linking the KBS and model, is provided and a case study used to demonstrate the principles of the system in operation. The results of verification and validation work performed on the KBS are described.

An integrated approach for the computer-assisted treatment of diabetic patients on insulin

A prototype computer system has been developed to provide advice on the day-to-day adjustment of carbohydrate intake and insulin regimen in the insulin-dependent diabetic patient. The system also produces a 24-h simulation of the patient's blood glucose profile based on these adjustments. Advice is generated by a qualitative knowledge-based system which suggests what the next step in improving glycaemic control might be for a given patient, e.g. 'decrease morning short-acting insulin by 2 units'. The quantitative simulator module contains two different mathematical models. The first is a non-linear model in differential equation form which consists of a one-compartment glucose model linked to a model with free and bound insulin compartments. This physiological model is solved by a general-purpose simulation engine. The second is a linear systems model which uses a transfer function to describe the insulin input/blood glucose response relationship for individual diabetic patients. Results of a preliminary medical validation are presented.