Poisonings account for 0.8% of emergency room visits each year. Our review of current toxicological resources revealed a gap in their ability to provide expedient calculations and recommendations, as they are broad in scope and time-consuming to read. Time is crucial in a toxicologic emergency. Delay in first dose can lead to life-threatening sequelae. To bridge the gap, we developed the Antidote Application (AA), a computational system that automatically provides patient-specific antidote treatment recommendation(s) and individualized dose calculation(s). We implemented 27 algorithms that describe FDA approved use and evidence-based practices found in primary literature for the treatment of common toxin exposure. The AA covers 29 antidotes recommended by Poison Control and toxicology experts, 31 toxins from 19 toxin classes, and over 200 toxic entities. We implemented the AA in two formats: a standalone downloadable application for offline use and an online web application. The AA represents a unique educational resource for the study of toxicology with the potential of being adopted for point of care decision support. The system also provides guidance for reporting toxic exposures regionally and nationally as required by accrediting bodies and some states. The AA system has the potential for reducing initial dose delays and medication errors. To the best of our knowledge, the AA is the first educational and decision support system in toxicology that provides patient-specific treatment recommendations and drug dose calculations. The downloadable and online Antidote Applications are publically available at http://www.met-hilab.org/files/antidote/antidote_application.jar and http://projects.met-hilab.org/antidote/ respectively.

No description available.

This thesis presents the framework of a complex business process driven event stream processing system to produce meaningful output with direct implications to the business objectives of an organization. This framework is demonstrated using a case study instantiating the management of a newborn infant with hypoglycaemia. Business processes defined within guidelines, are defined at build-time while critical knowledge found in the definition of business processes are used to support their enactment for stream analysis. Four major research contributions are delivered. The first contribution enables the definition and enactment of complex business processes in real-time. The second contribution supports the extraction of business process using knowledge found within the initial expression of the business process. The third contribution allows for the explicit use of temporal abstraction and stream analysis knowledge to support enactment in real-time. Finally, the last contribution is the real-time integration of heterogeneous streams based on Service-Oriented Architecture principles. / UOIT

Clinical decision support systems (CDSS) and the Picture Archiving and Communication System (PACS) have been adopted by large healthcare organization to support stroke diagnosis to reduce the level of misdiagnosis occurrence. This research presents a methodology for constructing a stroke decision support system (Stroke DSS) which integrates basic information, physical and image stroke assessment criterions, constructs ischemic, hemorrhage and subarachnoid hemorrhage of stroke diagnosis flow. A prototype embedded methodology was built to support stroke diagnosis in healthcare organization. Using a design science approach, we embed the constructs of our methodology in a prototype and perform a usability evaluation to demonstrate the utility of our approach. The usability evaluation demonstrates the effectiveness of our approach in terms of efficiency, effectiveness and satisfaction. The resulting system allowed flexible knowledge model and representation that are useful for stroke diagnosis.

<p>Diss. (sammanfattning) Umeå : Umeå universitet, 2003</p> / digitalisering@umu

Semantic web based decision support systems represent domain knowledge using ontologies that capture the domain concepts, their relationships and instances. Typically, decision support systems use a single knowledge model—i.e. a single ontology—which at times restricts the knowledge coverage to only select aspects of the domain knowledge. The integration of multiple knowledge models—i.e. multiple ontologies—provides a holistic knowledge model that encompasses multiple perspectives, orientations and instances. The challenge is the execution-time merging of multiple ontologies whilst maintaining knowledge consistency and procedural validity. Knowledge morphing aims at the intelligent merging of multiple computerized knowledge artifacts—represented as distinct ontological models—in order to create a holistic and networked knowledge model. In our research, we have investigated and developed a knowledge morphing framework—termed as OntoMorph—that supports ontology merging through: (1) Ontology Reconciliation whereby we harmonize multiple ontologies in terms of their vocabularies, knowledge coverage, and description granularities; (2) Ontology Merging where multiple reconciled ontologies are merged into a single merged ontology. To achieve ontology merging, we have formalized a set of semantically-defined merging criteria that determine ontology merge points, and describe the associated process-specific and knowledge consistency constraints that need to be satisfied to ensure consistent ontology merging; and (3) Ontology Execution whereby we have developed logic-based execution engines for both execution-time ontology merging and the execution of the merged ontology to infer knowledge-based recommendations. We have utilized OWL reasoning services, for efficient and decidable reasoning, to execute an OWL ontology. We have applied the OntoMorph framework for clinical decision support, more specifically to achieve the dynamic merging of multiple clinical practice guidelines in order to handle comorbid situations where a patient may have multiple diseases and hence multiple clinical guidelines are to be simultaneously operationalized. We have demonstrated the execution time merging of ontologically-modelled clinical guidelines, such that the decision support recommendations are derived from multiple, yet merged, clinical guidelines such that the inferred recommendations are clinically consistent. The thesis contributes new methods for ontology reconciliation, merging and execution, and presents a solution for execution-time merging of multiple clinical guidelines.

Around ten percent of patients admitted to National Health Service (NHS) hospitals have experienced a patient safety incident, and an important reason for the high rate of patient safety incidents is medical errors. Research shows that appropriate increase in the use of clinical decision support systems (CDSSs) could help to reduce medical errors and result in substantial improvement in patient safety. However several barriers continue to impede the effective implementation of CDSSs in clinical settings, among which representation of and reasoning about medical knowledge particularly under uncertainty are areas that require refined methodologies and techniques. Particularly, the knowledge base in a CDSS needs to be updated automatically based on accumulated clinical cases to provide evidence-based clinical decision support. In the research, we employed the recently developed belief Rule-base Inference Methodology using the Evidential Reasoning approach (RIMER) for design and development of an online belief rule-based group CDSS prototype. In the system, belief rule base (BRB) was used to model uncertain clinical domain knowledge, the evidential reasoning (ER) approach was employed to build inference engine, a BRB training module was developed for learning the BRB through accumulated clinical cases, and an online discussion forum together with an ER-based group preferences aggregation tool were developed for providing online clinical group decision support.We used a set of simulated patients in cardiac chest pain provided by our research collaborators in Manchester Royal Infirmary to validate the developed online belief rule-based CDSS prototype. The results show that the prototype can provide reliable diagnosis recommendations and the diagnostic performance of the system can be improved significantly after training BRB using accumulated clinical cases.

Medication is an essential part of health care and enables the prevention andtreatment of many conditions. However, medication errors and drug-relatedproblems (DRP) are frequent and cause suffering for patients and substantial costsfor society. eMedication, defined as information technology (IT) in themedication management process, has the potential to increase quality, efficiencyand safety but can also cause new problems and risks.In this thesis, we have studied the employment of IT in different steps of themedication management process with a focus on the user's perspective. Sweden isone of the leading countries when it comes to ePrescribing, i.e. prescriptionstransferred and stored electronically. We found that ePrescribing is well acceptedand appreciated by pharmacists (Study I) and patients (Study II), but that therewas a need for improvement in several aspects. When the pharmacy market inSweden was re-regulated, four new dispensing systems were developed andimplemented. Soon after the implementation, we found weaknesses related toreliability, functionality, and usability, which could affect patient safety (StudyIII). In the last decade, several county councils in Sweden have implementedshared medication lists within the respective region. We found that physiciansperceived that a regionally shared medication list generally was more complete butoften not accurate (Study IV). Electronic expert support (EES) is a decisionsupport system which analyses patients´ electronically-stored prescriptions in orderto detect potential DRP, i.e. drug-drug interactions, therapy duplication, highdose, and inappropriate drugs for geriatric or pediatric patients. We found thatEES detected potential DRP in most patients with multi-dose drug dispensing inSweden (Study V), and that the majority of alerts were regarded as clinicallyrelevant (Study VI).For an improved eMedication, we need a holistic approach that combinestechnology, users, and organization in implementation and evaluation. The thesissuggests a need for improved sharing of information and support for decisionmaking, coordination, and education, as well as clarification of responsibilitiesamong involved actors in order to employ appropriate IT. We suggestcollaborative strategic work and that the relevant authorities establish guidelinesand requirements for IT in the medication management process. / Läkemedel förbättrar och förlänger livet för många och utgör en väsentlig del av dagens hälso- och sjukvård men om läkemedel tas i fel dos eller kombineras felaktigt med varandra kan behandlingen leda till en försämrad livskvalitet, sjukhusinläggningar och dödsfall. En del av dessa problem skulle kunna förebyggas med rätt information till rätt person vid rätt tidpunkt och i rätt form. Informationsteknik i läkemedelsprocessen har potentialen att öka kvalitet, effektivitet och säkerhet genom att göra information tillgänglig och användbar men kan också innebära problem och risker. Det är dock en stor utmaning att i läkemedelsprocessen föra in effektiva och användbara IT-system som stödjer och inte stör personalen inom sjukvård och på apotek, skyddar den känsliga informationen för obehöriga och dessutom fungerar tillsammans med andra system. Dagens IT-stöd i läkemedelsprocessen är otillräckliga. Till exempel saknar läkare, farmaceuter och patienter ofta tillgång på fullständig och korrekt information om en patients aktuella läkemedel; det händer att fel läkemedel blir utskrivet eller expedierat på apotek; och bristande eller långsamma system skapar frustration hos användarna. Dessutom är det flera delar av läkemedelsprocessen som fortfarande är pappersbaserade. Därför är det viktigt att utvärdera IT-system i läkemedelsprocessen. Vi har studerat IT i olika delar av läkemedelsprocessen, före eller efter införandet, framför allt utifrån användarnas perspektiv. Sverige har lång erfarenhet och tillhör de ledande länderna i världen när det gäller eRecept, det vill säga recept som skickas och lagras elektroniskt. I två studier fann vi att eRecept är väl accepterat och uppskattat av farmaceuter (Studie I) och patienter (Studie II), men att det finns behov av förbättringar. När apoteksmarknaden omreglerades 2009 infördes fyra nya receptexpeditionssystem på apoteken. Vi fann att det efter införandet uppstod problem med användbarhet, tillförlitlighet och funktionalitet som kan ha inneburit en risk för patientsäkerheten (Studie III). I Sverige har man inom flera sjukvårdsregioner infört gemensamma elektroniska läkemedelslistor. I en av studierna kunde vi visa att detta har inneburit en ökad tillgänglighet av information, men att en gemensam lista inte alltid blir mer korrekt och kan innebära en ökad risk att känslig information nås av obehöriga (Studie IV). I två av studierna undersöktes beslutsstödssystemet elektroniskt expertstöd (EES):s potential som stöd för läkare att upptäcka läkemedelsrelaterade problem till exempel om en patient har två olika läkemedel som inte passar ihop, eller ett läkemedel som kanske är olämpligt för en äldre person. Studierna visade att EES gav signaler för potentiella problem hos de flesta patienter med dosdispenserade läkemedel i Sverige (Studie V), och läkarna ansåg att majoriteten av signalerna är kliniskt relevanta och att några av signalerna kan leda till förändringar i läkemedelsbehandlingen (Studie VI). Sammantaget visar avhandlingen att IT-stöd har blivit en naturlig och nödvändig del i läkemedelsprocessen i Sverige men att flera problem är olösta. Vi fann svagheter med användbarhet, tillförlitlighet och funktionalitet i de använda IT-systemen. Patienterna är inte tillräckligt informerade och delaktiga i sin läkemedelsbehandling. Läkare och farmaceuter saknar fullständig och korrekt information om patienters läkemedel, och de har i dagsläget inte tillräckliga beslutsstöd för att förebygga läkemedelsrelaterade problem. Eftersom läkemedelsprocessen är komplex med många aspekter som påverkar utfall behöver vi ett helhetstänkande när vi planerar, utvecklar, implementerar och utvärderar IT-lösningar där vi väger in både tekniska, sociala och organisatoriska aspekter. Avhandlingens resultat visar på ett behov av ökad koordination och utbildning samt förtydligande av ansvaret för inblandade aktörer. Vi föreslår gemensamt strategiskt arbete och att inblandade myndigheter tar fram vägledning och krav för IT i läkemedelsprocessen.

With the help of appropriate IT support, health care services can be executed in a more effective and secure way. In Sweden, the NPÖ (National Patients’ Översikt) stands for National Patients’ Overview. It is a platform where authorized health care providers can access comprehensive and continuous information about health care and patients’ situation, based on which care providers can offer safe and qualified services. The NPÖ project is focusing on the information sharing phase. In order to improve the efficiency and correctness of care services, the next step is that health care systems can offer clinical suggestions and warnings with the existing patients’ data and medication information. Clinical Decision Support Systems (CDSSs) are aimed to offer such assistance and are necessary to be integrated. But by now, there is no explicit architecture to guide Swedish government to implement the integration. Although some architectures have been proposed for integrating CDSSs in health information systems, those architectures are developed for certain use cases and cannot be adopted directly in NPÖ. An integration architecture which takes full consideration of NPÖ-adopting data types, message structures and interface types is needed. This thesis adopts constructive research method, which contains three main phases. First, related backgrounds about national electronic health care system, clinical decision supports system and integration techniques are introduced. Second, the integration architecture is constructed following service-oriented principles. Third, theoretical valuation work is finished by assessing system features and making interviews. This thesis takes advantage of service-oriented architecture to design an architecture with Clinical Decision Support (CDS) middleware for health care information system integration. With this structure, national electronic health care systems, such as NPÖ, can have interaction with various types of CDSSs to provide more efficient and secure health care. It offers united interfaces which enable different CDSSs with different developing platforms to communicate without obstacles. Unlike the existing CDSS integration architectures, the new one with CDS Middleware can provide maximized scalability. Evaluation work has been done from two aspects. Feature criteria and interviews with national health care system developers indicate that the architecture can contribute to the development of NPÖ, and future works such as involving security agents can be continued to optimize the results.

Treatment decision-making in head and neck oncology is gaining complexity by the increasing evidence pointing towards more individualized and selective treatment options. Therefore, decision making in multidisciplinary teams is becoming the key point in the clinical pathways. Clinical decision-support systems based on Bayesian networks can support complex decision-making processes by providing mathematically correct and transparent advises. In the last three decades, different clinical applications of Bayesian networks have been proposed. Because appropriate data for model learning and testing is often unobtainable, expert modeling is required. To decrease the modeling and validation effort, networks usually represent small or highly simplified decision structures. However, especially systems for supporting multidisciplinary treatment decisions may only gain a user’s confidence if the systems’ results are comprehensive and comprehensible. Challenges in developing such systems relate to knowledge engineering, model validation, system interaction, clinical implementation and standardization. These challenges are well-known, however, they are not or only partially addressed by the developers. The thesis presented a methodology for the development of Bayesian network-based clinical treatment decision support systems. For this purpose, a concept introduced interactions between actors and systems. The proposed concept emphasizes model development with an exemplary use case of model interaction. A graph model design was presented that allows integrating all relevant variables of multidisciplinary treatment decisions. At the current stage, we developed TreLynCa: A graph model representing the treatment decisions of laryngeal cancer. From TreLynCa, a subnetwork that represents the TNM staging is completed by the required probabilistic parameters, and finally validated. The model validation required the development of a validation cycle in combination with existing data- and expert-based validation methods. Furthermore, modeling methods were developed that enable domain experts to model autonomously without Bayesian network expertise. Specifically, a novel graph modeling method was developed, and an existing method for modeling probabilistic parameters was extended. Both methods transform Bayesian network modeling tasks into a natural language form and provide a regulated modeling environment. A method for graph modeling is based on the presented graph model design with a regulated and restricted modeling procedure. This modeling procedure is supposed to enable collaborative modeling of compatible models. The method is currently under development. A method for probabilistic modeling is extended to reduce the modeling effort to a linear time. The method has been implemented as a web tool and was tested and evaluated in two studies. Finally, for clinical application of the TNM model, requirements were collected and constructed in a visual framework. In collaboration with visual scientists, the framework has been implemented and evaluated.