Decision support and disease management: a Logic Engineering approach John Fox and Richard Thomson




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Decision support and disease management:
a Logic Engineering approach

John Fox and Richard Thomson




Imperial Cancer Research Fund, PO Box 123, Lincoln’s Inn Fields, London WC2A 3PX

email for correspondence: jf@acl.icnet.uk




Abstract: This paper describes the development and application of PROforma, a unified technology for clinical decision support and disease management. Work leading to the implementation of PROforma has been carrried out in a series of projects funded by European agencies over the past thirteen years. The work has been based on logic engineering, a distinct design and development methodology which combines concepts from knowledge engineering, logic programming and software engineering. Several of the projects have used the approach to demonstrate a wide range of applications in primary and specialist care and in clinical research. Concurrent academic research projects have provided a sound theoretical basis for the safety-critical elements of the methodology. The principle technical results of the work are the PROforma logic language for defining clinical processes, and an associated suite of software tools for delivering applications such as decision support and disease management procedures. The language supports four standard objects (decisions, plans, actions and enquiries), each of which has an intuitive meaning with well-understood logical semantics. The development toolset includes a powerful visual programming environment for composing applications from these standard components, for verifying consistency and completeness of the resulting specification, and for delivering stand-alone or embeddable applications. Tools and applications that have resulted from the work are described and illustrated with examples from specialist cancer care and primary care. The results of a number of evaluation activities are reported to illustrate the utility of the technology.


1 Introduction



Quality and consistency in most healthcare systems are highly variable, and occasionally lamentable. Traditional clinical practices are proving unsustainable (e.g. overuse of drugs and investigations, waiting lists measured in years), and the costs of medical services continue to rise inexorably. In addition, high-profile media exposés of clinical errors, and increases in litigation following North American trends, are forcing many European governments and healthcare agencies to acknowledge that their services have structural problems.


It is not a sufficient response simply to blame doctors, as tends to happen in litigation. Most doctors are doing their best, but have too much to do and too little time to ensure that all their decisions attain an optimal balance between achieving the best care for their patients and the most efficient use of resources. Many organizations are therefore looking for new solutions, and many are asking whether information technology can help doctors carry out their job more effectively, without usurping their traditional professional roles and responsibilities.


This paper reviews a line of work that aims to show that advanced techniques for supporting clinical decision making and disease management at the point of care can make a significant contribution to the process of patient care 1. While the objectives of the work are common to many other projects worldwide, the solutions proposed exploit technological and other strengths that are particularly European.


The idea that computers can be used to provide various forms of assistance to clinicians, such as better clinical records, timely prompts and reminders, and assistance in following care pathways, is far from new. A number of well-known centres, particularly in North America, have pioneered such systems, in some cases over decades. We are now beginning to see that their faith was justified, as objective benefits of computer support on clinical effectiveness [1] and cost-effectiveness [2] are emerging.


Until quite recently, the funding available in Europe in this field was relatively modest, but about ten years ago the European Union (EU) established a series of research and development programs in medical informatics. Since then the level of activity and range of projects has expanded substantially.


Although the emphasis of European projects can be different from those in North America (e.g. a greater concentration on primary care) common themes are also apparent. For example, a renewed interest in established methods (e.g. Arden Syntax [3] ) and a desire to develop new methods for standardising medical knowledge and disseminating best clinical practice (e.g. clinical coding systems, guideline interchange formats [4] and technologies for delivering decision support [5, 6]).


In the field of decision support, European developments have paralleled North American trends. There has been a radical shift in emphasis away from providing support for diagnosis decisions (as described in de Dombal’s classic work on diagnosis of acute abdominal pain [7]) towards support for patient management (e.g. the UK health service’s experimental prescribing system, Prodigy [8], and the Dutch trial of the Bloedlink system for assisting GPs in ordering blood tests [9]. As elsewhere, current developments are profoundly influenced by the emergence of the Internet, as indicated by the explosion of clinical guidelines published on the World Wide Web.


Work on advanced clinical information technologies is now developing strongly in Europe. Mainstream R&D in new technologies (e.g. multimedia), communications (e.g. the Internet and intranet technologies), and object-oriented programming languages and tools (e.g. CORBA, JAVA) are strongly influenced by US developments. However, Europe is also showing distinctive strengths in certain areas. For example, formal methods for software engineering (e.g. Z [10], VDM [11]) have always been strong, and these are being transferred into knowledge engineering (e.g. ML2 [12], DESIRE [13]).


There is also a strong European tradition in the development of software technologies based on mathematical logic (e.g. logic programming languages like Prolog, deductive databases, constraint solving systems), and these are having considerable influence on new technologies for machine learning and software agents. There is a growing interest in safety-critical applications using both conventional methods [14] and logic-based and AI techniques [15, 16, 17]. Our own work on medical systems has been particularly influenced by formal software engineering [18], and the PROforma technology described below exploits a number of ideas from these areas.


The work described in this paper is characterised by an emphasis on rigorous design and systematic development methodologies for clinical applications, based on an integration of methods from logic programming and software engineering, or logic engineering [19].

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