Model and Integrate Medical Resource Available Times and Relationships in Verifiably Correct Executable Medical Best Practice Guideline Models (Extended Version)

Improving patient care safety is an ultimate objective for medical cyber-physical systems. A recent study shows that the patients' death rate is significantly reduced by computerizing medical best practice guidelines. Recent data also show that some morbidity and mortality in emergency care are directly caused by delayed or interrupted treatment due to lack of medical resources. However, medical guidelines usually do not provide guidance on medical resource demands and how to manage potential unexpected delays in resource availability. If medical resources are temporarily unavailable, safety properties in existing executable medical guideline models may fail which may cause increased risk to patients under care. The paper presents a separately model and jointly verify (SMJV) architecture to separately model medical resource available times and relationships and jointly verify safety properties of existing medical best practice guideline models with resource models being integrated in. The SMJV architecture allows medical staff to effectively manage medical resource demands and unexpected resource availability delays during emergency care. The separated modeling approach also allows different domain professionals to make independent model modifications, facilitates the management of frequent resource availability changes, and enables resource statechart reuse in multiple medical guideline models. A simplified stroke scenario is used as a case study to investigate the effectiveness and validity of the SMJV architecture. The case study indicates that the SMJV architecture is able to identify unsafe properties caused by unexpected resource delays.Comment: full version, 12 page

Modeling Clinical Pathways - Design and Application of a Domain-Specific Modeling Language

Networking and collaboration in clinical care are increasingly entailing new requirements on supporting medical processes. The information technology (IT) in public health accordingly earns strategic relevance and encounters new potentials as well as challenging demands. The application of conceptual models in health care domain is almost entirely restricted to documentation tasks. Approaches like Model-Driven-Architectures or Workflow Management Systems have shown that the application of models, e.g. transformation, execution and formal interpretation, has huge potential. This article presents a modeling language for modeling clinical pathways. Three scenarios show the potential of conceptual models in health care domain and provide foundations for language requirements. Presenting a state-of-the-art of modeling languages for clinical domain and evaluating existing approaches to the requirements provide the gap to develop a domain-specific language. The potentials of the language and the use of corresponding models in medical treatment are demonstrated exemplarily including a discussion on model-driven management

TAT-based Formal Representation of Medical Guidelines : Imatinib Case-study

Computer-based interpretation of medical guide- lines (GLs) has drawn lots of attention in the past three decades. It is essential to use a formalism for GLs representation that would enable the validation of GLs structural properties, be able to map medical actions into the time scale and support the automatic formal verification of GLs without additional translation paths. In this paper we preset a novel approach based on Timed Automata extended with Tasks (TAT) for the medical protocol formal representation using the TIMES toolbox. We discuss the verification issues with the help of the Imatinib case study

An Ontological Framework for Representing Clinical Knowledge in Decision Support Systems, Journal of Telecommunications and Information Technology, 2014, nr 1

In the last decades, clinical evidence and expert consensus have been encoded into advanced Decision Support Systems (DSSs) in order to promote a better integration into the clinical workflow and facilitate the automatic provision of patient specific advice at the time and place where decisions are made. However, clinical knowledge, typically expressed as unstructured and free text guidelines, requires to be encoded into a computer interpretable form suitable for being interpreted and processed by DSSs. For this reason, this paper proposes an ontological framework, which enables the encoding of clinical guidelines from text to a formal representation, in order to allow querying, advanced reasoning and management in a well defined and rigorous way. In particular, it jointly manages declarative and procedural aspects of a standards based verifiable guideline model, named GLM-CDS (GuideLine Model for Clinical Decision Support), and expresses reasoning tasks that exploit such a represented knowledge in order to formalize integrity constraints, business rules and complex inference rules

Information Systems and Healthcare XXI: A Dynamic, Client-Centric, Point-Of-Care System for the Novice Nurse

Nurse clinicians need to make complex decisions on a continual basis, while delivering cost-effective treatments. The rapid proliferation of medical and nursing knowledge complicates the decision-making process, particularly for novice nurses. We describe a Clinical Decision Support System (CDSS) for the novice nurse that combines evidence-based nursing knowledge with specific patient information to create a real-time guide through the nursing diagnostic care process. The goal of the paper is to describe how an appropriately designed and evidence-based CDSS can aid the nursing practice. An off-the-shelf handheld computer is utilized to deliver clinical knowledge to the nurse, via wireless link to a central server and a data repository. In describing the software architecture of the system, particular emphasis is paid to the issue of appropriate design by discussing the steps taken to address system extensibility, performance, reliability, and security, which are important factors in the design of a CDSS

Generación de interfaces gráficos automáticos a partir de ontologías, aplicación a guías clínicas

Pérez González, AM. (2011). Generación de interfaces gráficos automáticos a partir de ontologías, aplicación a guías clínicas. http://hdl.handle.net/10251/11582.Archivo delegad