Towards computerizing intensive care sedation guidelines: design of a rule-based architecture for automated execution of clinical guidelines

<p>Abstract</p> <p>Background</p> <p>Computerized ICUs rely on software services to convey the medical condition of their patients as well as assisting the staff in taking treatment decisions. Such services are useful for following clinical guidelines quickly and accurately. However, the development of services is often time-consuming and error-prone. Consequently, many care-related activities are still conducted based on manually constructed guidelines. These are often ambiguous, which leads to unnecessary variations in treatments and costs.</p> <p>The goal of this paper is to present a semi-automatic verification and translation framework capable of turning manually constructed diagrams into ready-to-use programs. This framework combines the strengths of the manual and service-oriented approaches while decreasing their disadvantages. The aim is to close the gap in communication between the IT and the medical domain. This leads to a less time-consuming and error-prone development phase and a shorter clinical evaluation phase.</p> <p>Methods</p> <p>A framework is proposed that semi-automatically translates a clinical guideline, expressed as an XML-based flow chart, into a Drools Rule Flow by employing semantic technologies such as ontologies and SWRL. An overview of the architecture is given and all the technology choices are thoroughly motivated. Finally, it is shown how this framework can be integrated into a service-oriented architecture (SOA).</p> <p>Results</p> <p>The applicability of the Drools Rule language to express clinical guidelines is evaluated by translating an example guideline, namely the sedation protocol used for the anaesthetization of patients, to a Drools Rule Flow and executing and deploying this Rule-based application as a part of a SOA. The results show that the performance of Drools is comparable to other technologies such as Web Services and increases with the number of decision nodes present in the Rule Flow. Most delays are introduced by loading the Rule Flows.</p> <p>Conclusions</p> <p>The framework is an effective solution for computerizing clinical guidelines as it allows for quick development, evaluation and human-readable visualization of the Rules and has a good performance. By monitoring the parameters of the patient to automatically detect exceptional situations and problems and by notifying the medical staff of tasks that need to be performed, the computerized sedation guideline improves the execution of the guideline.</p

Web and knowledge-based decision support system for measurement uncertainty evaluation

This thesis was submitted for the degree of Doctor of Philosophy and awarded by Brunel UniversityIn metrology, measurement uncertainty is understood as a range in which the true value of the measurement is likely to fall in. The recent years have seen a rapid development in evaluation of measurement uncertainty. ISO Guide to the Expression of Uncertainty in Measurement (GUM 1995) is the primary guiding document for measurement uncertainty. More recently, the Supplement 1 to the "Guide to the expression of uncertainty in measurement" – Propagation of distributions using a Monte Carlo method (GUM SP1) was published in November 2008. A number of software tools for measurement uncertainty have been developed and made available based on these two documents. The current software tools are mainly desktop applications utilising numeric computation with limited mathematical model handling capacity. A novel and generic web-based application, web-based Knowledge-Based Decision Support System (KB-DSS), has been proposed and developed in this research for measurement uncertainty evaluation. A Model-View-Controller architecture pattern is used for the proposed system. Under this general architecture, a web-based KB-DSS is developed based on an integration of the Expert System and Decision Support System approach. In the proposed uncertainty evaluation system, three knowledge bases as sub-systems are developed to implement the evaluation for measurement uncertainty. The first sub-system, the Measurement Modelling Knowledge Base (MMKB), assists the user in establishing the appropriate mathematical model for the measurand, a critical process for uncertainty evaluation. The second sub-system, GUM Framework Knowledge Base, carries out the uncertainty evaluation process based on the GUM Uncertainty Framework using symbolic computation, whilst the third sub-system, GUM SP1 MCM Framework Knowledge Base, conducts the uncertainty calculation according to the GUM SP1 Framework numerically based on Monte Carlo Method. The design and implementation of the proposed system and sub-systems are discussed in the thesis, supported by elaboration of the implementation steps and examples. Discussions and justifications on the technologies and approaches used for the sub-systems and their components are also presented. These include Drools, Oracle database, Java, JSP, Java Transfer Object, AJAX and Matlab. The proposed web-based KB-DSS has been evaluated through case studies and the performance of the system has been validated by the example results. As an established methodology and practical tool, the research will make valuable contributions to the field of measurement uncertainty evaluation.Brunel Universit

Monitoring Complex Processes to Verify System Conformance: A Declarative Rule-Based Framework

Over the last 60 years, computers and software have favoured incredible advancements in every field. Nowadays, however, these systems are so complicated that it is difficult – if not challenging – to understand whether they meet some requirement or are able to show some desired behaviour or property. This dissertation introduces a Just-In-Time (JIT) a posteriori approach to perform the conformance check to identify any deviation from the desired behaviour as soon as possible, and possibly apply some corrections. The declarative framework that implements our approach – entirely developed on the promising open source forward-chaining Production Rule System (PRS) named Drools – consists of three components: 1. a monitoring module based on a novel, efficient implementation of Event Calculus (EC), 2. a general purpose hybrid reasoning module (the first of its genre) merging temporal, semantic, fuzzy and rule-based reasoning, 3. a logic formalism based on the concept of expectations introducing Event-Condition-Expectation rules (ECE-rules) to assess the global conformance of a system. The framework is also accompanied by an optional module that provides Probabilistic Inductive Logic Programming (PILP). By shifting the conformance check from after execution to just in time, this approach combines the advantages of many a posteriori and a priori methods proposed in literature. Quite remarkably, if the corrective actions are explicitly given, the reactive nature of this methodology allows to reconcile any deviations from the desired behaviour as soon as it is detected. In conclusion, the proposed methodology brings some advancements to solve the problem of the conformance checking, helping to fill the gap between humans and the increasingly complex technology.Negli ultimi 60 anni, i computer e i programmi hanno favorito incredibili avanzamenti in ogni campo. Oggigiorno, purtroppo, questi sistemi sono così complicati che è difficile – se non impossibile – capire se soddisfano qualche requisito o mostrano un comportamento o una proprietà desiderati. Questa tesi introduce un approccio a posteriori Just-In-Time (JIT) per effettuare il controllo di conformità ed identificare appena possibile ogni deviazione dal comportamento desiderato, ed eventualmente applicare qualche correzione. Il framework dichiarativo che implementa il nostro approccio – interamente sviluppato su una promettente piattaforma open source di Production Rule System (PRS) chiamata Drools – si compone di tre elementi: 1. un modulo per il monitoraggio basato su una nuova implementazione efficiente di Event Calculus (EC), 2. un modulo generale per il ragionamento ibrido (il primo del suo genere) che supporta ragionamento temporale, semantico, fuzzy e a regole, 3. un formalismo logico basato sul concetto di aspettativa che introduce le Event-Condition-Expectation rules (ECE-rules) per valutare la conformità globale di un sistema. Il framework è anche accompagnato da un modulo opzionale che fornisce Probabilistic Inductive Logic Programming (PILP). Spostando il controllo di conformità da dopo l’esecuzione ad appena in tempo, questo approccio combina i vantaggi di molti metodi a posteriori e a priori proposti in letteratura. Si noti che, se le azioni correttive sono fornite esplicitamente, la natura reattiva di questo metodo consente di conciliare le deviazioni dal comportamento desiderato non appena questo viene rilevato. In conclusione, la metodologia proposta introduce alcuni avanzamenti per risolvere il problema del controllo di conformità, contribuendo a colmare il divario tra l’uomo e la tecnologia, sempre più complessa

Semantic web system for differential diagnosis recommendations

There is a growing realization that healthcare is a knowledge-intensive field. The ability to capture and leverage semantics via inference or query processing is crucial for supporting the various required processes in both primary (e.g. disease diagnosis) and long term care (e.g. predictive and preventive diagnosis). Given the wide canvas and the relatively frequent knowledge changes that occur in this area, we need to take advantage of the new trends in Semantic Web technologies. In particular, the power of ontologies allows us to share medical research and provide suitable support to physician's practices. There is also a need to integrate these technologies within the currently used healthcare practices. In particular the use of semantic web technologies is highly demanded within the clinicians' differential diagnosis process and the clinical pathways disease management procedures as well as to aid the predictive/preventative measures used by healthcare professionals

An Adaptable Long-term Condition Workload Prediction Model for Primary Health Care

The primary health care (PHC) system must manage the growing demand for care due to patients with long-term conditions (LTCs) such as diabetes, hypertension, and asthma. Population-based care can help address this workload management problem, specifically by enabling a shift from a reactive to a proactive patient management approach. However, current PHC systems lack the ability to provide population-based care. This thesis presents a tool to predict the future workload generated by a population of patients. We use a rule-based system, for its modularity, flexibility and the automated modifiability behaviour, to develop the care pathways as rules that, when given the patient data, would simulate the patient visits for the upcoming year (since some start date). It is assumed that the GPs follow best practice and their patients adhere to their plan-of-care, making visits to the medical practice on their scheduled LTC appointments. Then, these visits are aggregated to a population-level as a count of appointments per week from these LTC patients, referred to as the workload to be managed within the capacity of the practice. Knowing this predicted workload, the PHC organisation can then plan and deliver care accordingly. In this thesis, we also explore using seven what-if scenarios the impacts of alternatives in practices and evaluate the strategies to address them. We then propose the use of Bayesian inference in our workload prediction model, in order to incorporate the variation in patient visits due to the impact of renewal of their LTC prescriptions. This work is done in collaboration with BPAC, a non-profit organisation that promotes best practice for primary care within New Zealand. The collaborations on this work were in the form of 1. health data from a medical practice; 2. the knowledge base to understand the primary health care domain, and the practical issues at a medical practice. Approval for this research using the anonymised patient data provided by BPAC has been given by the University of Otago Human Ethics Committee (Health). We follow the design science research (DSR) methodology to develop our adaptable best practice based workload prediction model for a PHC due to its LTC patients. From a DSR perspective, we developed a construct called the three-layer LTC PHC construct, and a process called the encounter-based unfolding plan-of-care process, which are used to build our artefact: the adaptable best practice based workload prediction model. In DSR, much emphasis is on communicating the developed artefact or model to a wider community and the feedback guides further improvement of the model or the artefact developed. We followed seven iterative cycles to incrementally build the rule base, and the feedback served as a guide to improve the simulation capability of our ABP-WPM. Apart from the feedback from the collaborator on this work, feedback was also collected through informal meetings with the care providers of a medical practice at Mosgiel, the executive members of two different PHOs (one in the North Island and the other in the South Island of New Zealand) at various stages of development of this artefact. The artefact developed was also communicated to the research community through two publications. In the process of developing this population-level workload prediction model, we identified shortcomings (for example, the LTC status of a patient is not explicit) in the current health data models and in the PHC data shared with us, which is needed to support a population-level workload analysis. We, therefore, developed a patient information data model that makes this information explicit

Business rules based legacy system evolution towards service-oriented architecture.

Enterprises can be empowered to live up to the potential of becoming dynamic, agile and real-time. Service orientation is emerging from the amalgamation of a number of key business, technology and cultural developments. Three essential trends in particular are coming together to create a new revolutionary breed of enterprise, the service-oriented enterprise (SOE): (1) the continuous performance management of the enterprise; (2) the emergence of business process management; and (3) advances in the standards-based service-oriented infrastructures. This thesis focuses on this emerging three-layered architecture that builds on a service-oriented architecture framework, with a process layer that brings technology and business together, and a corporate performance layer that continually monitors and improves the performance indicators of global enterprises provides a novel framework for the business context in which to apply the important technical idea of service orientation and moves it from being an interesting tool for engineers to a vehicle for business managers to fundamentally improve their businesses

Runtime Adaptation of Scientific Service Workflows

Software landscapes are rather subject to change than being complete after having been built. Changes may be caused by a modified customer behavior, the shift to new hardware resources, or otherwise changed requirements. In such situations, several challenges arise. New architectural models have to be designed and implemented, existing software has to be integrated, and, finally, the new software has to be deployed, monitored, and, where appropriate, optimized during runtime under realistic usage scenarios. All of these situations often demand manual intervention, which causes them to be error-prone. This thesis addresses these types of runtime adaptation. Based on service-oriented architectures, an environment is developed that enables the integration of existing software (i.e., the wrapping of legacy software as web services). A workflow modeling tool that aims at an easy-to-use approach by separating the role of the workflow expert and the role of the domain expert. After the development of workflows, tools that observe the executing infrastructure and perform automatic scale-in and scale-out operations are presented. Infrastructure-as-a-Service providers are used to scale the infrastructure in a transparent and cost-efficient way. The deployment of necessary middleware tools is automatically done. The use of a distributed infrastructure can lead to communication problems. In order to keep workflows robust, these exceptional cases need to treated. But, in this way, the process logic of a workflow gets mixed up and bloated with infrastructural details, which yields an increase in its complexity. In this work, a module is presented that can deal automatically with infrastructural faults and that thereby allows to keep the separation of these two layers. When services or their components are hosted in a distributed environment, some requirements need to be addressed at each service separately. Although techniques as object-oriented programming or the usage of design patterns like the interceptor pattern ease the adaptation of service behavior or structures. Still, these methods require to modify the configuration or the implementation of each individual service. On the other side, aspect-oriented programming allows to weave functionality into existing code even without having its source. Since the functionality needs to be woven into the code, it depends on the specific implementation. In a service-oriented architecture, where the implementation of a service is unknown, this approach clearly has its limitations. The request/response aspects presented in this thesis overcome this obstacle and provide a SOA-compliant and new methods to weave functionality into the communication layer of web services. The main contributions of this thesis are the following: Shifting towards a service-oriented architecture: The generic and extensible Legacy Code Description Language and the corresponding framework allow to wrap existing software, e.g., as web services, which afterwards can be composed into a workflow by SimpleBPEL without overburdening the domain expert with technical details that are indeed handled by a workflow expert. Runtime adaption: Based on the standardized Business Process Execution Language an automatic scheduling approach is presented that monitors all used resources and is able to automatically provision new machines in case a scale-out becomes necessary. If the resource's load drops, e.g., because of less workflow executions, a scale-in is also automatically performed. The scheduling algorithm takes the data transfer between the services into account in order to prevent scheduling allocations that eventually increase the workflow's makespan due to unnecessary or disadvantageous data transfers. Furthermore, a multi-objective scheduling algorithm that is based on a genetic algorithm is able to additionally consider cost, in a way that a user can define her own preferences rising from optimized execution times of a workflow and minimized costs. Possible communication errors are automatically detected and, according to certain constraints, corrected. Adaptation of communication: The presented request/response aspects allow to weave functionality into the communication of web services. By defining a pointcut language that only relies on the exchanged documents, the implementation of services must neither be known nor be available. The weaving process itself is modeled using web services. In this way, the concept of request/response aspects is naturally embedded into a service-oriented architecture

Designing and Testing an Experimental Framework of Affective Intelligent Agents in Healthcare Training Simulations

A thesis submitted in partial fulfilment of the requirements of the University of Wolverhampton for the degree of Doctor of PhilosophyThe purpose of this study is to investigate how emotionally enabled virtual agents (VAs) in healthcare provision training simulations allow for a more effective level of understanding on how an emotionally enhanced scenario can affect different aspects of learning. This is achieved by developing virtual agents that respond to the user’s emotions and personality. The developed system also provides visual and auditory representations of the virtual agents’ state of mind. To enable the fulfilment of this purpose an experimental framework for incorporating emotional enhancements (concentrating on negative emotions such as stress, fear, and anxiety) into virtual agents in virtual training applications for healthcare provision is designed and implemented. The framework for incorporating emotional enhancements is designed based on previous research, on psychological theories (with input by experienced psychologists) and from input of experts in the area of healthcare provision. For testing the framework and answering the research question of this thesis the researcher conducted nine case studies. The participants were nursing students in the area of healthcare provision, and more specifically in the area of mental health, specialising in caring for patients with dementia. The results of the study showed that the framework and its implementation succeeded in providing a realistic learning experience, stimulated a better set of responses from the user, improved their level of understanding on how an emotionally enhanced scenario can affect the learning experience and helped them become more empathetic towards the person they cared for