A Process Modelling Framework Based on Point Interval Temporal Logic with an Application to Modelling Patient Flows

This thesis considers an application of a temporal theory to describe and model the patient journey in the hospital accident and emergency (A&E) department. The aim is to introduce a generic but dynamic method applied to any setting, including healthcare. Constructing a consistent process model can be instrumental in streamlining healthcare issues. Current process modelling techniques used in healthcare such as flowcharts, unified modelling language activity diagram (UML AD), and business process modelling notation (BPMN) are intuitive and imprecise. They cannot fully capture the complexities of the types of activities and the full extent of temporal constraints to an extent where one could reason about the flows. Formal approaches such as Petri have also been reviewed to investigate their applicability to the healthcare domain to model processes. Additionally, to schedule patient flows, current modelling standards do not offer any formal mechanism, so healthcare relies on critical path method (CPM) and program evaluation review technique (PERT), that also have limitations, i.e. finish-start barrier. It is imperative to specify the temporal constraints between the start and/or end of a process, e.g., the beginning of a process A precedes the start (or end) of a process B. However, these approaches failed to provide us with a mechanism for handling these temporal situations. If provided, a formal representation can assist in effective knowledge representation and quality enhancement concerning a process. Also, it would help in uncovering complexities of a system and assist in modelling it in a consistent way which is not possible with the existing modelling techniques. The above issues are addressed in this thesis by proposing a framework that would provide a knowledge base to model patient flows for accurate representation based on point interval temporal logic (PITL) that treats point and interval as primitives. These objects would constitute the knowledge base for the formal description of a system. With the aid of the inference mechanism of the temporal theory presented here, exhaustive temporal constraints derived from the proposed axiomatic system’ components serves as a knowledge base. The proposed methodological framework would adopt a model-theoretic approach in which a theory is developed and considered as a model while the corresponding instance is considered as its application. Using this approach would assist in identifying core components of the system and their precise operation representing a real-life domain deemed suitable to the process modelling issues specified in this thesis. Thus, I have evaluated the modelling standards for their most-used terminologies and constructs to identify their key components. It will also assist in the generalisation of the critical terms (of process modelling standards) based on their ontology. A set of generalised terms proposed would serve as an enumeration of the theory and subsume the core modelling elements of the process modelling standards. The catalogue presents a knowledge base for the business and healthcare domains, and its components are formally defined (semantics). Furthermore, a resolution theorem-proof is used to show the structural features of the theory (model) to establish it is sound and complete. After establishing that the theory is sound and complete, the next step is to provide the instantiation of the theory. This is achieved by mapping the core components of the theory to their corresponding instances. Additionally, a formal graphical tool termed as point graph (PG) is used to visualise the cases of the proposed axiomatic system. PG facilitates in modelling, and scheduling patient flows and enables analysing existing models for possible inaccuracies and inconsistencies supported by a reasoning mechanism based on PITL. Following that, a transformation is developed to map the core modelling components of the standards into the extended PG (PG*) based on the semantics presented by the axiomatic system. A real-life case (from the King’s College hospital accident and emergency (A&E) department’s trauma patient pathway) is considered to validate the framework. It is divided into three patient flows to depict the journey of a patient with significant trauma, arriving at A&E, undergoing a procedure and subsequently discharged. Their staff relied upon the UML-AD and BPMN to model the patient flows. An evaluation of their representation is presented to show the shortfalls of the modelling standards to model patient flows. The last step is to model these patient flows using the developed approach, which is supported by enhanced reasoning and scheduling

Information Systems as Representations: A Review of the Theory and Evidence

Representation theory proposes that the basic purpose of an information system (IS) is to faithfully represent certain real-world phenomena, allowing users to reason about these phenomena more cost- effectively than if they were observed directly. Over the past three decades, the theory has underpinned much research on conceptual modeling in IS analysis and design and, increasingly, research on other IS phenomena such as data quality, system alignment, IS security, and system use. The original theory has also inspired further development of its core premises and advances in methodological guidelines to improve its use and evaluation. Nonetheless, the theory has attracted repeated criticisms regarding its validity, relevance, usefulness, and robustness. Given the burgeoning literature on the theory over time, both positive and negative, the time is ripe for a narrative, developmental review. We review representation theory, examine how it has been used, and critically evaluate its contributions and limitations. Based on our findings, we articulate a set of recommendations for improving its application, development, testing, and evaluation

Computerization of workflows, guidelines and care pathways: a review of implementation challenges for process-oriented health information systems

There is a need to integrate the various theoretical frameworks and formalisms for modeling clinical guidelines, workflows, and pathways, in order to move beyond providing support for individual clinical decisions and toward the provision of process-oriented, patient-centered, health information systems (HIS). In this review, we analyze the challenges in developing process-oriented HIS that formally model guidelines, workflows, and care pathways. A qualitative meta-synthesis was performed on studies published in English between 1995 and 2010 that addressed the modeling process and reported the exposition of a new methodology, model, system implementation, or system architecture. Thematic analysis, principal component analysis (PCA) and data visualisation techniques were used to identify and cluster the underlying implementation ‘challenge’ themes. One hundred and eight relevant studies were selected for review. Twenty-five underlying ‘challenge’ themes were identified. These were clustered into 10 distinct groups, from which a conceptual model of the implementation process was developed. We found that the development of systems supporting individual clinical decisions is evolving toward the implementation of adaptable care pathways on the semantic web, incorporating formal, clinical, and organizational ontologies, and the use of workflow management systems. These architectures now need to be implemented and evaluated on a wider scale within clinical settings

Business Process Management for optimizing clinical processes: A systematic literature review

Business Process Management is a new strategy for process management that is having a major impact today. Mainly, its use is focused on the industrial, services, and business sector. However, in recent years, it has begun to apply for optimizing clinical processes. So far, no studies that evaluate its true impact on the healthcare sector have been found. This systematic review aims to assess the results of the application of Business Process Management methodology on clinical processes, analyzing whether it can become a useful tool to improve the effectiveness and quality of processes. We conducted a systematic literature review using ScienceDirect, Web of Science, Scopus, PubMed, and Springer databases. After the electronic search process in different databases, 18 articles met the pre-established requirements. The findings support the use of Business Process Management as an effective methodology to optimize clinical processes. Business Process Management has proven to be a feasible and useful methodology to design and optimize clinical processes, as well as to automate tasks. However, a more comprehensive follow-up of this methodology, better technological support, and greater involvement of all the clinical staff are factors that play a key role for the development of its true potential.This work was supported by the Ministerio de Economía y Competitividad of the Spanish Government (ref. TIN2014-53067-C3-1-R) and co-financed by FEDER

Contribution des services dirigés par l’ontologie pour l’interopérabilité de la gestion opérationnelle multi-acteurs des situations des crises

La gestion opérationnelle de situations de crise nécessite, selon l’importance et l’étendue de la crise, la mobilisation rapide et la coordination des différents services de secours. Malheureusement, cette coordination interservices est un exercice très délicat du fait de la diversité des acteurs intervenant sur le terrain et de l’hétérogénéité des différentes organisations. Aujourd’hui, il y a un manque de coordination, l’information n’est que très peu partagée entre les acteurs opérationnels et la communication n’est pas formalisée. Ces inconvénients conduisent au dysfonctionnement des réponses aux situations de crise. Afin de mieux répondre aux situations de crise, nous proposons POLARISC, une plateforme interopérable de coordination interservices pour la gestion opérationnelle de catastrophes visualisant en temps réel le théâtre des opérations. L’objectif de POLARISC est d’aider à la décision quel que soit le niveau de commandement. Pour atteindre ces objectifs, le premier enjeu de cette thèse est de garantir une interopérabilité sémantique entre les différents acteurs métiers pour assurer l’échange et le partage des informations. À cet égard, l’idée est de formaliser sémantiquement les connaissances des acteurs métiers de la gestion opérationnelle à l’aide des ontologies. En effet, nous proposons une approche fédérée qui représente les données, les services, les processus et les métiers de chaque acteur. Nous avons modélisé les connaissances des acteurs de secours en développant une ontologie modulaire (POLARISCO) comportant un module ontologique pour chaque acteur de secours et intégré ces derniers pour proposer un vocabulaire partagé. L’utilisation des ontologies de haut niveaux et des ontologies intermédiaires, respectivement « Basic Formel Ontology » et « Common Core Ontologies », facilitent l’intégration de ces modules et de leurs mappings. Le deuxième enjeu est d’exploiter ces ontologies afin de diminuer l’ambigüité et d’éviter la mal interprétation des informations échangées. Par conséquent, nous proposons un service de messagerie appelé PROMES transformant sémantiquement le message envoyé par un acteur émetteur selon le module ontologique de l’acteur destinataire. En effet, PROMES se base sur l’ontologie POLARISCO et sert à enrichir sémantiquement le message pour éviter tout type d’ambiguïté. Le fonctionnement de PROMES est basé principalement sur deux algorithmes ; un algorithme de transformation textuelle, et par la suite, un algorithme de transformation sémantique. Ainsi, nous avons instancié l’ontologie POLARISCO avec des données réelles de la réponse aux attaques terroristes de Paris en 2015 afin d’évaluer l’ontologie et le service de messagerie. Le troisième et dernier enjeu est de proposer un service d’aide à la décision multicritère qui permet de proposer des stratégies d’évacuation des victimes après le lancement du plan blanc. L’objectif est de trouver les structures hospitalières les plus adaptées à l’état de la victime. Le choix de l’hôpital le plus approprié dépend de la durée du transport, et surtout de la disponibilité des ressources matérielles et humaines, de façon à prendre en charge les victimes le plus rapide que possible. Notre étude comprend deux étapes : la première étape consiste à développer un module ontologique qui associe à chaque pathologie les ressources indispensables pour une meilleure prise en charge des victimes selon leurs états. La deuxième étape consiste à développer un algorithme qui permet de vérifier la disponibilité des ressources nécessaires, calculer le temps d’attente pour que la victime soit prise en charge dans chaque hôpital et par la suite choisir l’hôpital le plus appropri

Big data architecture for pervasive healthcare: a literature review

Pervasive healthcare aims to deliver deinstitutionalised healthcare services to patients anytime and anywhere. Pervasive healthcare involves remote data collection through mobile devices and sensor network which the data is usually in large volume, varied formats and high frequency. The nature of big data such as volume, variety, velocity and veracity, together with its analytical capabilities com-plements the delivery of pervasive healthcare. However, there is limited research in intertwining these two domains. Most research focus mainly on the technical context of big data application in the healthcare sector. Little attention has been paid to a strategic role of big data which impacts the quality of healthcare services provision at the organisational level. Therefore, this paper delivers a conceptual view of big data architecture for pervasive healthcare via an intensive literature review to address the aforementioned research problems. This paper provides three major contributions: 1) identifies the research themes of big data and pervasive healthcare, 2) establishes the relationship between research themes, which later composes the big data architecture for pervasive healthcare, and 3) sheds a light on future research, such as semiosis and sense-making, and enables practitioners to implement big data in the pervasive healthcare through the proposed architecture

Development HealthCare System of Smart Hospital Based on UML and XML

The convergence of information technology systems in health care system building is causing us to look at more effective integration of technologies. Facing increased competition, tighter spaces, staff retention and reduced reimbursement, today’s traditional hospitals are looking at strategic ways to use technology to manage their systems called smart hospital. The concept of the smart hospital is a useful system for any hospital; about adding intelligence to the traditional hospital system by covering all resources and locations with patient information. Patient’s information is an important component of the patient privacy in any health care system that is based on the overall quality of each patient in the health care system. The main commitment for any health care system is to improve the quality of the patient and privacy of patient’s information. Today, there is a need of such computer environment where treatment to patients can be given on the basis of his/her previous medical history at the time of emergency at any time, on any place and anywhere. Pervasive and ubiquitous environment and UML (unified modeling language) can bring the boon in this field. For this it's needed to develop the ubiquitous health care computing environment using the UML with traditional hospital environment. This paper is based on the ubiquitous and pervasive computing environment based on UML and XML(The Extensible Markup Language)  technology, in which these problems has been tried to improve traditional hospital system into smart hospital in the near future. The key solution of the smart hospital is online identification of all patients, doctors, nurses, staff, medical equipments, medications, blood bags, surgical tools, blankets, sheets, hospital rooms, etc. In this paper efforts is channeled into improving the knowledge-base ontological description for smart hospital system by using UML and XML technology, Our knowledge is represented in XML format from UML modeling(class diagram). Our smart hospital provides access to its system by using a smart card. Finally, the former try to improve health care delivery through development and management of acute care hospital designed; both physically and operationally, for more efficiency and increased patients safety. Keywords: UML; Smart Hospital (SH); Ontology; XML; health care system

Enhancing data and processes integration and interoperability in emergency situations: a SWS based emergency management system

In this paper we describe a powerful use case application in the area of emergency situations management in which to illustrate the benefits of a system based on Semantic Web Services (SWS), through the automation of the business processes involved. After creating Web services to provide spatial data to third parties through the Internet, semantics and domain ontologies were added to represent the business processes involved, allowing: ease of access and combination of heterogeneous data from different providers; and automatic discovery, access and composition to perform more complex tasks. In this way, our prototype contributes to better management of emergency situations by those responsible. The work described is supported by the DIP (Data, Information and Process Integration with Semantic Web Services) project. DIP (FP6 � 507483), an Integrated Project funded under the European Union�s IST programme