116 research outputs found

    Automatic Generation of Personalized Recommendations in eCoaching

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    Denne avhandlingen omhandler eCoaching for personlig livsstilsstĆøtte i sanntid ved bruk av informasjons- og kommunikasjonsteknologi. Utfordringen er Ć„ designe, utvikle og teknisk evaluere en prototyp av en intelligent eCoach som automatisk genererer personlige og evidensbaserte anbefalinger til en bedre livsstil. Den utviklede lĆøsningen er fokusert pĆ„ forbedring av fysisk aktivitet. Prototypen bruker bƦrbare medisinske aktivitetssensorer. De innsamlede data blir semantisk representert og kunstig intelligente algoritmer genererer automatisk meningsfulle, personlige og kontekstbaserte anbefalinger for mindre stillesittende tid. Oppgaven bruker den veletablerte designvitenskapelige forskningsmetodikken for Ć„ utvikle teoretiske grunnlag og praktiske implementeringer. Samlet sett fokuserer denne forskningen pĆ„ teknologisk verifisering snarere enn klinisk evaluering.publishedVersio

    Distributed Dynamic Condition Response Structures

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    We present distributed dynamic condition response structures as a declarative process model in-spired by the workflow language employed by our industrial partner and conservatively generalizing labelled event structures. The model adds to event structures the possibility to 1) finitely specify re-peated, possibly infinite behavior, 2) finitely specify fine-grained acceptance conditions for (possibly infinite) runs based on the notion of responses and 3) distribute events via roles. We give a graph-ical notation inspired by related work by van der Aalst et al and formalize the execution semantics as a labelled transition system. Exploration of the relationship between dynamic condition response structures and traditional models for concurrency, application to more complex scenarios, and further extensions of the model is left to future work.

    Assuring Access to Care Under Health Reform: The Key Role of Workforce Policy

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    Examines policy and practical options for addressing the projected shortage of primary care physicians to ensure access to health care under expanded insurance coverage, including reorganizing practices to make productive use of nurses and other staff

    Flexible Support of Healthcare Processes

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    Traditionally, healthcare information systems have focused on the support of predictable and repetitive clinical processes. Even though the latter can be often prespecified in formal process models, process flexibility in terms of dynamic adaptability is indispensable to cope with exceptions and unforeseen situations. Flexibility is further required to accommodate the need for evolving healthcare processes and to properly support healthcare process variability. In addition, process-aware information systems are increasingly used to support less structured healthcare processes (i.e., patient treatment processes), which can be characterized as knowledge-intensive. Healthcare processes of this category are neither fully predictable nor repetitive and, therefore, they cannot be fully prespecified at design time. The partial unpredictability of these processes, in turn, demands a certain amount of looseness. This chapter deals with the characteristic flexibility needs of both prespecified and loosely specified healthcare processes. In addition, it presents fundamental flexibility features required to address these flexibility needs as well as to accommodate them in healthcare practice

    Personalized conciliation of clinical guidelines for comorbid patients through multi-agent planning

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    [EN] The conciliation of multiple single-disease guidelines for comorbid patients entails solving potential clinical interactions, discovering synergies in the diagnosis and the recommendations, and managing clinical equipoise situations. Personalized conciliation of multiple guidelines considering additionally patient preferences brings some further difficulties. Recently, several works have explored distinct techniques to come up with an automated process for the conciliation of clinical guidelines for comorbid patients but very little attention has been put in integrating the patient preferences into this process. In this work, a Multi-Agent Planning (MAP) framework that extends previous work on single-disease temporal Hierarchical Task Networks (HTN) is proposed for the automated conciliation of clinical guidelines with patient-centered preferences. Each agent encapsulates a single-disease Computer Interpretable Guideline (CIG) formalized as an HTN domain and conciliates the decision procedures that encode the clinical recommendations of its CIG with the decision procedures of the other agents' CIGs. During conciliation, drug-related interactions, scheduling constraints as well as redundant actions and multiple support interactions are solved by an automated planning process. Moreover, the simultaneous application of the patient preferences in multiple diseases may potentially bring about contradictory clinical decisions and more interactions. As a final step, the most adequate personalized treatment plan according to the patient preferences is selected by a Multi-Criteria Decision Making (MCDM) process. The MAP approach is tested on a case study that builds upon a simplified representation of two real clinical guidelines for Diabetes Mellitus and Arterial Hypertension.This work has been partially supported by Spanish Government Projects MINECO TIN2014-55637-C2-2-R and TIN2015-71618-R.FernĆ”ndez-Olivares, J.; Onaindia De La Rivaherrera, E.; Castillo Vidal, L.; JordĆ”n, J.; CĆ³zar, J. (2019). Personalized conciliation of clinical guidelines for comorbid patients through multi-agent planning. Artificial Intelligence in Medicine. 96:167-186. https://doi.org/10.1016/j.artmed.2018.11.003S1671869

    Together for change: investigating a socio-technical system approach for supporting miscarriage

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    Globally, miscarriage is affecting a substantial number of women: about 1 in 5 women who know they are pregnant miscarry. Importantly, miscarriage can be profoundly distressing, and lack of social support during and after a miscarriage can greatly affect womenā€™s wellbeing. Unfortunately, miscarriage is not a commonly discussed topic, despite the significant number of miscarriages occurring. As a result of the lack of discussion around the subject of miscarriage, it continues to be stigmatised and misunderstood. Consequently, there is inadequate communication between women who have experienced miscarriage and care networks when communicating their social support needs. This thesis investigates how technology can be meaningfully leveraged to enhance those communications. As a theoretical framework, the thesis author uses the Circles of Care Model, which has previously successfully been used to understand the complex context of caring for people with chronic illness. The research process was strongly participatory, inspired by principles of Community-Based Participatory Research. The main contributions of this thesis are: (a) an in-depth and rich holistic contextual understanding of the social support needs of women who have miscarried, describing in-depth their practices and use of technology (b) extending the Circles of Care Model approach to designing a socio-technical system for miscarriage care (c) proposing empirical design goals for socio-technical systems for miscarriage care that are grounded in mixed methods research with women from different cultures and different health care systems. In collaboration with ProHealth Lab, University of Indiana, Bloomington, United States, we began with an exploratory Asynchronous Remote Communities (ARC) study to investigate the breadth of miscarriage experiences, the support needs that arise, the people who can help, and the potential scope for technology to facilitate the support needed. The study involved 16 activities (discussions, creative tasks, and surveys) posted in two closed, secret Facebook groups over eight weeks. Women who have miscarried face barriers to receiving appropriate social support when communicating with their care network. Since miscarriage still carries a considerable stigma, women hear unwanted responses and belittlement of the loss, which made them more hesitant to reach out. They often felt unable to discuss their feelings and thoughts openly, as they feared a lack of empathy. Without having a guiding hand, women who have miscarried feel alone in this experience. They live experience that no one has prepared them to, very few people understand and sometimes is challenging to get support. This left many overwhelmed with complex social support needs while in a raw emotional state, and often with insufficient informational, emotional, esteem and network support at the time. While women experiencing a miscarriage utilise various technology channels for seeking support when other options fail them, each woman only focuses on a few online streams. We developed the Miscarriage Circle of Care Model (MCCM) to mapping the formal, informal care networks, and their respective roles in providing social support. Our findings highlight the importance of integrating the Peer Advisor support to provide holistic support for a woman experiencing a miscarriage. Next, the thesis author carried out five sets of 1:1 co-design workshops with women who have miscarried to investigate how technology might help address their unmet support needs, given the map of formal and informal care networks we developed. The workshops were structured around a journey mapping exercise. The thesis author also used card sorting to explore mental models of miscarriage support. The thesis author collected data both from women who had miscarried and those who had not experienced miscarriage themselves but felt a strong connection to the topic. We involve women who have not experience a miscarriage in the process to explore the different clustering behaviour between women with experience of miscarriage and those without experience, which in turn, help to understand how the experience of miscarriage changes the perception of support. The thesis author distilled the findings into actionable design goals, which were then instantiated in a wireframe prototype of the socio-technical system solution, which was designed to be able to fit into a pregnancy app. The thesis author evaluated the prototype in another five series of 1:1 workshops using techniques from usability testing, such as task analysis, and methods from service design, such as love letters / break up letters. Overall, women considered the prototype to be useful and acceptable, with suggestions for improvements. The thesis author concludes with a critical reflection of the process and findings and provides a conclusive description and suggestions for implementing them in practice. Through reflection on the experiences in conducting research for this thesis, including the difficulties we faced and decisions we made, we derive insights into the role of design, power relations in the community and research in a sensitive area. We conclude with a discussion of limitations and discuss how the MCCM developed in this thesis might be implemented within existing miscarriage care in the United States and United Kingdom healthcare systems

    Implementation of workflow engine technology to deliver basic clinical decision support functionality

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    BACKGROUND: Workflow engine technology represents a new class of software with the ability to graphically model step-based knowledge. We present application of this novel technology to the domain of clinical decision support. Successful implementation of decision support within an electronic health record (EHR) remains an unsolved research challenge. Previous research efforts were mostly based on healthcare-specific representation standards and execution engines and did not reach wide adoption. We focus on two challenges in decision support systems: the ability to test decision logic on retrospective data prior prospective deployment and the challenge of user-friendly representation of clinical logic. RESULTS: We present our implementation of a workflow engine technology that addresses the two above-described challenges in delivering clinical decision support. Our system is based on a cross-industry standard of XML (extensible markup language) process definition language (XPDL). The core components of the system are a workflow editor for modeling clinical scenarios and a workflow engine for execution of those scenarios. We demonstrate, with an open-source and publicly available workflow suite, that clinical decision support logic can be executed on retrospective data. The same flowchart-based representation can also function in a prospective mode where the system can be integrated with an EHR system and respond to real-time clinical events. We limit the scope of our implementation to decision support content generation (which can be EHR system vendor independent). We do not focus on supporting complex decision support content delivery mechanisms due to lack of standardization of EHR systems in this area. We present results of our evaluation of the flowchart-based graphical notation as well as architectural evaluation of our implementation using an established evaluation framework for clinical decision support architecture. CONCLUSIONS: We describe an implementation of a free workflow technology software suite (available at http://code.google.com/p/healthflow) and its application in the domain of clinical decision support. Our implementation seamlessly supports clinical logic testing on retrospective data and offers a user-friendly knowledge representation paradigm. With the presented software implementation, we demonstrate that workflow engine technology can provide a decision support platform which evaluates well against an established clinical decision support architecture evaluation framework. Due to cross-industry usage of workflow engine technology, we can expect significant future functionality enhancements that will further improve the technology's capacity to serve as a clinical decision support platform
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