In recent years, clinical guidelines and protocols have become the main instruments for disseminating best practice in medical practice. They are designed to promote safe practices, reduce inter-clinician practice variations and support decision-making in patient care while containing the costs of care. So far, they have been proved useful in improving the quality and consistency of healthcare by supporting healthcare quality assessment and assurance, clinical decision making, workflow and resource management etc. The benefits of using clinical guidelines are widely recognized, yet the guideline development process is time- and resource-consuming, and the size and complexity of guidelines remains a major hurdle for effectively using them in clinical care.

Several methods have been or are being developed to support the development, deployment, maintenance and use of computerised evidence-based guidelines, using techniques from Artificial Intelligence, Software Engineering, Medical Informatics and Formal Methods. Various different representation formalisms and computational techniques are used e.g. rule-based, logic-based, knowledge-based and workflow-based. Computerised guideline-related research spans a wide range of the AI community as well as other research areas.