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How can we reward you? A compliance and reward ontology (CaRO) for eliciting quantitative reward rules for engagement in mHealth app and healthy behaviors. J Biomed Inform 2024; 154:104655. [PMID: 38754531 DOI: 10.1016/j.jbi.2024.104655] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/11/2024] [Revised: 05/02/2024] [Accepted: 05/11/2024] [Indexed: 05/18/2024]
Abstract
OBJECTIVE When developing mHealth apps with point reward systems, knowledge engineers and domain experts should define app requirements capturing quantitative reward patterns that reflect patient compliance with health behaviors. This is a difficult task, and they could be aided by an ontology that defines systematically quantitative behavior goals that address more than merely the recommended behavior but also rewards for partial compliance or practicing the behavior more than recommended. No ontology and algorithm exist for defining point rewards systematically. METHODS We developed an OWL ontology for point rewards that leverages the Basic Formal Ontology, the Behaviour Change Intervention Ontology and the Gamification Domain Ontology. This Compliance and Reward Ontology (CaRO) allows defining temporal elementary reward patterns for single and multiple sessions of practicing a behavior. These could be assembled to define more complex temporal patterns for persistence behavior over longer time intervals as well as logical combinations of simpler reward patterns. We also developed an algorithm for calculating the points that should be rewarded to users, given data regarding their actual performance. A natural language generation algorithm generates from ontology instances app requirements in the form of user stories. To assess the usefulness of the ontology and algorithms, information system students who are trained to be system analysts/knowledge engineers evaluated whether the ontology and algorithms can improve the requirement elicitation of point rewards for compliance patterns more completely and correctly. RESULTS For single-session rewards, the ontology improved formulation of two of the six requirements as well as the total time for specifying them. For multi-session rewards, the ontology improved formulation of five of the 11 requirements. CONCLUSION CaRO is a first attempt of its kind, and it covers all of the cases of compliance and reward pattern definitions that were needed for a full-scale system that was developed as part of a large European project. The ontology and algorithm are available at https://github.com/capable-project/rewards.
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Personalization in mHealth: Innovative informatics methods to improve patient experience and health outcome. J Biomed Inform 2023; 147:104523. [PMID: 37838289 DOI: 10.1016/j.jbi.2023.104523] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/08/2023] [Accepted: 10/10/2023] [Indexed: 10/16/2023]
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An eHealth App (CAPABLE) Providing Symptom Monitoring, Well-Being Interventions, and Educational Material for Patients With Melanoma Treated With Immune Checkpoint Inhibitors: Protocol for an Exploratory Intervention Trial. JMIR Res Protoc 2023; 12:e49252. [PMID: 37819691 PMCID: PMC10600650 DOI: 10.2196/49252] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/24/2023] [Revised: 07/12/2023] [Accepted: 08/03/2023] [Indexed: 10/13/2023] Open
Abstract
BACKGROUND Since treatment with immune checkpoint inhibitors (ICIs) is becoming standard therapy for patients with high-risk and advanced melanoma, an increasing number of patients experience treatment-related adverse events such as fatigue. Until now, studies have demonstrated the benefits of using eHealth tools to provide either symptom monitoring or interventions to reduce treatment-related symptoms such as fatigue. However, an eHealth tool that facilitates the combination of both symptom monitoring and symptom management in patients with melanoma treated with ICIs is still needed. OBJECTIVE In this pilot study, we will explore the use of the CAPABLE (Cancer Patients Better Life Experience) app in providing symptom monitoring, education, and well-being interventions on health-related quality of life (HRQoL) outcomes such as fatigue and physical functioning, as well as patients' acceptance and usability of using CAPABLE. METHODS This prospective, exploratory pilot study will examine changes in fatigue over time in 36 patients with stage III or IV melanoma during treatment with ICI using CAPABLE (a smartphone app and multisensory smartwatch). This cohort will be compared to a prospectively collected cohort of patients with melanoma treated with standard ICI therapy. CAPABLE will be used for a minimum of 3 and a maximum of 6 months. The primary endpoint in this study is the change in fatigue between baseline and 3 and 6 months after the start of treatment. Secondary end points include HRQoL outcomes, usability, and feasibility parameters. RESULTS Study inclusion started in April 2023 and is currently ongoing. CONCLUSIONS This pilot study will explore the effect, usability, and feasibility of CAPABLE in patients with melanoma during treatment with ICI. Adding the CAPABLE system to active treatment is hypothesized to decrease fatigue in patients with high-risk and advanced melanoma during treatment with ICIs compared to a control group receiving standard care. The Medical Ethics Committee NedMec (Amsterdam, The Netherlands) granted ethical approval for this study (reference number 22-981/NL81970.000.22). TRIAL REGISTRATION ClinicalTrials.gov NCT05827289; https://clinicaltrials.gov/study/NCT05827289. INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID) DERR1-10.2196/49252.
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The Case Manager: An Agent Controlling the Activation of Knowledge Sources in a FHIR-Based Distributed Reasoning Environment. Appl Clin Inform 2023; 14:725-734. [PMID: 37339683 PMCID: PMC10499504 DOI: 10.1055/a-2113-4443] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/15/2022] [Accepted: 05/12/2023] [Indexed: 06/22/2023] Open
Abstract
BACKGROUND Within the CAPABLE project the authors developed a multi-agent system that relies on a distributed architecture. The system provides cancer patients with coaching advice and supports their clinicians with suitable decisions based on clinical guidelines. OBJECTIVES As in many multi-agent systems we needed to coordinate the activities of all agents involved. Moreover, since the agents share a common blackboard where all patients' data are stored, we also needed to implement a mechanism for the prompt notification of each agent upon addition of new information potentially triggering its activation. METHODS The communication needs have been investigated and modeled using the HL7-FHIR (Health Level 7-Fast Healthcare Interoperability Resources) standard to ensure proper semantic interoperability among agents. Then a syntax rooted in the FHIR search framework has been defined for representing the conditions to be monitored on the system blackboard for activating each agent. RESULTS The Case Manager (CM) has been implemented as a dedicated component playing the role of an orchestrator directing the behavior of all agents involved. Agents dynamically inform the CM about the conditions to be monitored on the blackboard, using the syntax we developed. The CM then notifies each agent whenever any condition of interest occurs. The functionalities of the CM and other actors have been validated using simulated scenarios mimicking the ones that will be faced during pilot studies and in production. CONCLUSION The CM proved to be a key facilitator for properly achieving the required behavior of our multi-agent system. The proposed architecture may also be leveraged in many clinical contexts for integrating separate legacy services, turning them into a consistent telemedicine framework and enabling application reusability.
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Using graph rewriting to operationalize medical knowledge for the revision of concurrently applied clinical practice guidelines. Artif Intell Med 2023; 140:102550. [PMID: 37210156 DOI: 10.1016/j.artmed.2023.102550] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/19/2022] [Revised: 04/03/2023] [Accepted: 04/05/2023] [Indexed: 05/22/2023]
Abstract
Clinical practice guidelines (CPGs) are patient management tools that synthesize medical knowledge into an actionable format. CPGs are disease specific with limited applicability to the management of complex patients suffering from multimorbidity. For the management of these patients, CPGs need to be augmented with secondary medical knowledge coming from a variety of knowledge repositories. The operationalization of this knowledge is key to increasing CPGs' uptake in clinical practice. In this work, we propose an approach to operationalizing secondary medical knowledge inspired by graph rewriting. We assume that the CPGs can be represented as task network models, and provide an approach for representing and applying codified medical knowledge to a specific patient encounter. We formally define revisions that model and mitigate adverse interactions between CPGs and we use a vocabulary of terms to instantiate these revisions. We demonstrate the application of our approach using synthetic and clinical examples. We conclude by identifying areas for future work with the vision of developing a theory of mitigation that will facilitate the development of comprehensive decision support for the management of multimorbid patients.
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A Community-of-Practice-based Evaluation Methodology for Knowledge Intensive Computational Methods and its Application to Multimorbidity Decision Support. J Biomed Inform 2023; 142:104395. [PMID: 37201618 DOI: 10.1016/j.jbi.2023.104395] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/24/2022] [Revised: 04/25/2023] [Accepted: 05/15/2023] [Indexed: 05/20/2023]
Abstract
OBJECTIVE The study has dual objectives. Our first objective (1) is to develop a community-of-practice-based evaluation methodology for knowledge-intensive computational methods. We target a whitebox analysis of the computational methods to gain insight on their functional features and inner workings. In more detail, we aim to answer evaluation questions on (i) support offered by computational methods for functional features within the application domain; and (ii) in-depth characterizations of the underlying computational processes, models, data and knowledge of the computational methods. Our second objective (2) involves applying the evaluation methodology to answer questions (i) and (ii) for knowledge-intensive clinical decision support (CDS) methods, which operationalize clinical knowledge as computer interpretable guidelines (CIG); we focus on multimorbidity CIG-based clinical decision support (MGCDS) methods that target multimorbidity treatment plans. MATERIALS AND METHODS Our methodology directly involves the research community of practice in (a) identifying functional features within the application domain; (b) defining exemplar case studies covering these features; and (c) solving the case studies using their developed computational methods-research groups detail their solutions and functional feature support in solution reports. Next, the study authors (d) perform a qualitative analysis of the solution reports, identifying and characterizing common themes (or dimensions) among the computational methods. This methodology is well suited to perform whitebox analysis, as it directly involves the respective developers in studying inner workings and feature support of computational methods. Moreover, the established evaluation parameters (e.g., features, case studies, themes) constitute a re-usable benchmark framework, which can be used to evaluate new computational methods as they are developed. We applied our community-of-practice-based evaluation methodology on MGCDS methods. RESULTS Six research groups submitted comprehensive solution reports for the exemplar case studies. Solutions for two of these case studies were reported by all groups. We identified four evaluation dimensions: detection of adverse interactions, management strategy representation, implementation paradigms, and human-in-the-loop support.Based on our whitebox analysis, we present answers to the evaluation questions (i) and (ii) for MGCDS methods. DISCUSSION The proposed evaluation methodology includes features of illuminative and comparison-based approaches; focusing on understanding rather than judging/scoring or identifying gaps in current methods. It involves answering evaluation questions with direct involvement of the research community of practice, who participate in setting up evaluation parameters and solving exemplar case studies. Our methodology was successfully applied to evaluate six MGCDS knowledge-intensive computational methods. We established that, while the evaluated methods provide a multifaceted set of solutions with different benefits and drawbacks, no single MGCDS method currently provides a comprehensive solution for MGCDS. CONCLUSION We posit that our evaluation methodology, applied here to gain new insights into MGCDS, can be used to assess other types of knowledge-intensive computational methods and answer other types of evaluation questions. Our case studies can be accessed at our GitHub repository (https://github.com/william-vw/MGCDS).
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SATO (IDEAS expAnded wiTh BCIO): Workflow for designers of patient-centered mobile health behaviour change intervention applications. J Biomed Inform 2023; 138:104276. [PMID: 36586499 PMCID: PMC9975785 DOI: 10.1016/j.jbi.2022.104276] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/05/2022] [Revised: 11/17/2022] [Accepted: 12/19/2022] [Indexed: 12/29/2022]
Abstract
Designing effective theory-driven digital behaviour change interventions (DBCI) is a challenging task. To ease the design process, and assist with knowledge sharing and evaluation of the DBCI, we propose the SATO (IDEAS expAnded wiTh BCIO) design workflow based on the IDEAS (Integrate, Design, Assess, and Share) framework and aligned with the Behaviour Change Intervention Ontology (BCIO). BCIO is a structural representation of the knowledge in behaviour change domain supporting evaluation of behaviour change interventions (BCIs) but it is not straightforward to utilise it during DBCI design. IDEAS (Integrate, Design, Assess, and Share) framework guides multi-disciplinary teams through the mobile health (mHealth) application development life-cycle but it is not aligned with BCIO entities. SATO couples BCIO entities with workflow steps and extends IDEAS Integrate stage with consideration of customisation and personalisation. We provide a checklist of the activities that should be performed during intervention planning with concrete examples and a tutorial accompanied with case studies from the Cancer Better Life Experience (CAPABLE) European project. In the process of creating this workflow, we found the necessity to extend the BCIO to support the scenarios of multiple clinical goals in the same application. To ensure the SATO steps are easy to follow for the incomers to the field, we performed a preliminary evaluation of the workflow with two knowledge engineers, working on novel mHealth app design tasks.
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Why did AI get this one wrong? - Tree-based explanations of machine learning model predictions. Artif Intell Med 2023; 135:102471. [PMID: 36628785 DOI: 10.1016/j.artmed.2022.102471] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/26/2022] [Revised: 11/25/2022] [Accepted: 11/28/2022] [Indexed: 12/02/2022]
Abstract
Increasingly complex learning methods such as boosting, bagging and deep learning have made ML models more accurate, but harder to interpret and explain, culminating in black-box machine learning models. Model developers and users alike are often presented with a trade-off between performance and intelligibility, especially in high-stakes applications like medicine. In the present article we propose a novel methodological approach for generating explanations for the predictions of a generic machine learning model, given a specific instance for which the prediction has been made. The method, named AraucanaXAI, is based on surrogate, locally-fitted classification and regression trees that are used to provide post-hoc explanations of the prediction of a generic machine learning model. Advantages of the proposed XAI approach include superior fidelity to the original model, ability to deal with non-linear decision boundaries, and native support to both classification and regression problems. We provide a packaged, open-source implementation of the AraucanaXAI method and evaluate its behaviour in a number of different settings that are commonly encountered in medical applications of AI. These include potential disagreement between the model prediction and physician's expert opinion and low reliability of the prediction due to data scarcity.
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On the joint-effect of class imbalance and overlap: a critical review. Artif Intell Rev 2022. [DOI: 10.1007/s10462-022-10150-3] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/30/2022]
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Towards a framework for comparing functionalities of multimorbidity clinical decision support: A literature-based feature set and benchmark cases. AMIA ... ANNUAL SYMPOSIUM PROCEEDINGS. AMIA SYMPOSIUM 2022; 2021:920-929. [PMID: 35308994 PMCID: PMC8861752] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Subscribe] [Scholar Register] [Indexed: 06/14/2023]
Abstract
Multimorbidity, the coexistence of two or more health conditions, has become more prevalent as mortality rates in many countries have declined and their populations have aged. Multimorbidity presents significant difficulties for Clinical Decision Support Systems (CDSS), particularly in cases where recommendations from relevant clinical guidelines offer conflicting advice. A number of research groups are developing computer-interpretable guideline (CIG) modeling formalisms that integrate recommendations from multiple Clinical Practice Guidelines (CPGs) for knowledge-based multimorbidity decision support. In this paper we describe work towards the development of a framework for comparing the different approaches to multimorbidity CIG-based clinical decision support (MGCDS). We present (1) a set of features for MGCDS, which were derived using a literature review and evaluated by physicians using a survey, and (2) a set of benchmarking case studies, which illustrate the clinical application of these features. This work represents the first necessary step in a broader research program aimed at the development of a benchmark framework that allows for standardized and comparable MGCDS evaluations, which will facilitate the assessment of functionalities of MGCDS, as well as highlight important gaps in the state-of-the-art. We also outline our future work on developing the framework, specifically, (3) a standard for reporting MGCDS solutions for the benchmark case studies, and (4) criteria for evaluating these MGCDS solutions. We plan to conduct a large-scale comparison study of existing MGCDS based on the comparative framework.
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Towards an AI Planning-Based Pipeline for the Management of Multimorbid Patients. Artif Intell Med 2022. [DOI: 10.1007/978-3-031-09342-5_2] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/28/2022]
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A Health eLearning Ontology and Procedural Reasoning Approach for Developing Personalized Courses to Teach Patients about Their Medical Condition and Treatment. INTERNATIONAL JOURNAL OF ENVIRONMENTAL RESEARCH AND PUBLIC HEALTH 2021; 18:7355. [PMID: 34299806 PMCID: PMC8307382 DOI: 10.3390/ijerph18147355] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 05/17/2021] [Revised: 07/01/2021] [Accepted: 07/03/2021] [Indexed: 11/16/2022]
Abstract
We propose a methodological framework to support the development of personalized courses that improve patients' understanding of their condition and prescribed treatment. Inspired by Intelligent Tutoring Systems (ITSs), the framework uses an eLearning ontology to express domain and learner models and to create a course. We combine the ontology with a procedural reasoning approach and precompiled plans to operationalize a design across disease conditions. The resulting courses generated by the framework are personalized across four patient axes-condition and treatment, comprehension level, learning style based on the VARK (Visual, Aural, Read/write, Kinesthetic) presentation model, and the level of understanding of specific course content according to Bloom's taxonomy. Customizing educational materials along these learning axes stimulates and sustains patients' attention when learning about their conditions or treatment options. Our proposed framework creates a personalized course that prepares patients for their meetings with specialists and educates them about their prescribed treatment. We posit that the improvement in patients' understanding of prescribed care will result in better outcomes and we validate that the constructs of our framework are appropriate for representing content and deriving personalized courses for two use cases: anticoagulation treatment of an atrial fibrillation patient and lower back pain management to treat a lumbar degenerative disc condition. We conduct a mostly qualitative study supported by a quantitative questionnaire to investigate the acceptability of the framework among the target patient population and medical practitioners.
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A review of AI and Data Science support for cancer management. Artif Intell Med 2021; 117:102111. [PMID: 34127240 DOI: 10.1016/j.artmed.2021.102111] [Citation(s) in RCA: 10] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/07/2020] [Revised: 12/23/2020] [Accepted: 05/11/2021] [Indexed: 02/09/2023]
Abstract
INTRODUCTION Thanks to improvement of care, cancer has become a chronic condition. But due to the toxicity of treatment, the importance of supporting the quality of life (QoL) of cancer patients increases. Monitoring and managing QoL relies on data collected by the patient in his/her home environment, its integration, and its analysis, which supports personalization of cancer management recommendations. We review the state-of-the-art of computerized systems that employ AI and Data Science methods to monitor the health status and provide support to cancer patients managed at home. OBJECTIVE Our main objective is to analyze the literature to identify open research challenges that a novel decision support system for cancer patients and clinicians will need to address, point to potential solutions, and provide a list of established best-practices to adopt. METHODS We designed a review study, in compliance with the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines, analyzing studies retrieved from PubMed related to monitoring cancer patients in their home environments via sensors and self-reporting: what data is collected, what are the techniques used to collect data, semantically integrate it, infer the patient's state from it and deliver coaching/behavior change interventions. RESULTS Starting from an initial corpus of 819 unique articles, a total of 180 papers were considered in the full-text analysis and 109 were finally included in the review. Our findings are organized and presented in four main sub-topics consisting of data collection, data integration, predictive modeling and patient coaching. CONCLUSION Development of modern decision support systems for cancer needs to utilize best practices like the use of validated electronic questionnaires for quality-of-life assessment, adoption of appropriate information modeling standards supplemented by terminologies/ontologies, adherence to FAIR data principles, external validation, stratification of patients in subgroups for better predictive modeling, and adoption of formal behavior change theories. Open research challenges include supporting emotional and social dimensions of well-being, including PROs in predictive modeling, and providing better customization of behavioral interventions for the specific population of cancer patients.
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Preface: AIME 2019. Artif Intell Med 2021; 115:102058. [PMID: 34001318 DOI: 10.1016/j.artmed.2021.102058] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/22/2021] [Accepted: 03/22/2021] [Indexed: 10/21/2022]
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MitPlan 2.0: Enhanced Support for Multi-morbid Patient Management Using Planning. Artif Intell Med 2021. [DOI: 10.1007/978-3-030-77211-6_31] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/21/2022]
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MitPlan: A planning approach to mitigating concurrently applied clinical practice guidelines. Artif Intell Med 2020; 112:102002. [PMID: 33581823 DOI: 10.1016/j.artmed.2020.102002] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/22/2020] [Revised: 11/01/2020] [Accepted: 12/06/2020] [Indexed: 10/22/2022]
Abstract
As the population ages, patients' complexity and the scope of their care is increasing. Over 60% of the population is 65 years of age or older and suffers from multi-morbidity, which is associated with two times as many patient-physician encounters. Yet clinical practice guidelines (CPGs) are developed to treat a single disease. To reconcile these two competing issues, previously we developed a framework for mitigation, i.e., identifying and addressing adverse interactions in multi-morbid patients managed according to multiple CPGs. That framework relies on first-order logic (FOL) to represent CPGs and secondary medical knowledge and FOL theorem proving to establish valid patient management plans. In the work presented here, we leverage our earlier research and simplify the mitigation process by representing it as a planning problem using the Planning Domain Definition Language (PDDL). This new framework, called MitPlan, identifies and addresses adverse interactions using durative planning actions that embody clinical actions (including medication administration and patient testing), supports a physician-defined length of planning horizons, and optimizes plans based on patient preferences and action costs. It supports a variety of criteria when developing management plans, including the total cost of prescribed treatment and the cost of the revisions to be introduced. The solution to MitPlan's planning problem is a sequence of timed actions that are easy to interpret when creating a management plan. We demonstrate MitPlan's capabilities using illustrative and clinical case studies.
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Canadian Spine SocietyPresentation CPSS1: Spinal insufficiency fracture in the geriatric pediatric spinePresentation CPSS2: The clinical significance of tether breakages in anterior vertebral body growth modulation: a 2-year postoperative analysisPresentation CPSS3: Anterior vertebral body growth modulation for idiopathic scoliosis: early, mid-term and late complicationsPresentation CPSS4: Ovine model of congenital chest wall and spine deformity with alterations of respiratory mechanics: follow-up from birth to 3 monthsPresentation CPSS5: Test–retest reliability and minimum detectable change of the English translation of the Italian Spine Youth Quality of Life questionnaire in adolescents with idiopathic scoliosisPresentation B1. Abstract 31: Incidence of delayed spinal cord injury in pediatric spine deformity surgery seems to be higher than previously assumedPresentation B2. Abstract 155: What is the optimal surgical method for achieving successful symptom relief in pediatric high-grade spondylolisthesis?Presentation B3. Abstract 47: Vertebral body tethering: Truly motion preserving or rather limiting?Presentation B4. Abstract 180: Fusion rates in pediatric patients after posterior cervical spine instrumentationPresentation B5. Abstract 102: Effects of 8 years of growth hormone treatment on the onset and progression of scoliosis in children with Prader–Willi syndromePresentation B6. Abstract 144: Klippel–Feil syndrome: clinical phenotypes associated with surgical treatmentPresentation B7. Abstract 123: Anterior release for idiopathic scoliosis: Is it necessary for curve correction?Presentation B8. Abstract 62: Severe scoliosis: Do we know a better way? A retrospective comparative studyPresentation B9. Abstract 21: Intraoperative skull femoral traction in adolescent idiopathic scoliosis: the correlation of traction with side-bending radiographsPresentation B10. Abstract 147: What is the effect of intraoperative halo-femoral traction on correction of adolescent idiopathic scoliosis?Presentation B11. Abstract 174: Extreme long-term outcome of surgically versus non-surgically treated patients with adolescent idiopathic scoliosisPresentation B12. Abstract 172: The influence of multilevel spinal deformity surgery on the clinical outcome in the elderly: a prospective, observational, multicentre studyPresentation B13. Abstract 49: Demographics of a prospective evaluation of elderly deformity surgery: a prospective international observational multicentre studyPresentation B14. Abstract 119: Timing of conversion to cervical malalignment and proximal junctional kyphosis following surgical correction of adult spinal deformityPresentation B15. Abstract 44: Prioritization of realignment associated with superior clinical outcomes for surgical cervical deformity patientsPresentation B16. Abstract 50: Outcome of multilevel spinal deformity surgery in patients over 60 years of age: a multicentre international prospective studyPresentation B17. Abstract 122: A simpler, modified frailty index weighted by complication occurrence correlates to pain and disability for adult spinal deformity patientsPresentation B18. Abstract 75: Change in Oswestry Disability Index at 24 months following multilevel spinal deformity surgery in patients over 60 years of age: a multicentre international prospective studyPresentation C19. Abstract 19: A prospective cohort study evaluating trends in the surgical treatment of degenerative spondylolisthesis in Canada and the utility of a novel surgical decision aidPresentation C20. Abstract 154: Decompression compared with decompression and fusion for degenerative lumbar spondylolisthesis: a Canadian Spine Outcomes and Research Network (CSORN) studyPresentation C21. Abstract ID 77: Lumbar degenerative spondylolisthesis: factors impacting decision to fusePresentation C22. Abstract 27: Patient-reported outcomes following surgery for lumbar disc herniation: comparison of a universal and multitier health care systemPresentation C23. Abstract 151: Do patients with recurrent lumbar disc herniations fair worse with discectomy than primary operations? A retrospective analysis from the Canadian Spine Outcomes and Research NetworkPresentation C24. Abstract 136: A province-wide assessment of the appropriateness of lumbar spine MRIPresentation D25. Abstract 32: Surgical site infection reduction — a 10-year quality improvement journeyPresentation D26. Abstract 34: The impact of frailty on patient-reported outcome measures following elective thoraco-lumbar spine surgeryPresentation D27. Abstract 8: Moving toward better health: exercise practice is associated with improved outcomes after spine surgeryPresentation D28. Abstract 33: Preoperative decolonization does not adversely affect the microbiologic spectrum of spine surgical site infectionPresentation D29. Abstract 61: Feedback: reducing after-hours spine cases using an encrypted messaging systemPresentation D30. Abstract 177: Complex spine surgery is safe and effective in the extremely elderly age group: results from an ambispective study of 722 patients over 75 years old from a single institutionPresentation E31. Abstract 38: Clinical predictors of achieving minimal clinically important difference after surgery for cervical spondylotic myelopathy: an external validation study from the Canadian Spine Outcomes and Research NetworkPresentation E32. Abstract 66: The natural history of degenerative cervical myelopathy: an ambispective longitudinal cohort studyPresentation E33. Abstract 159: Quantitative assessment of gait characteristics in degenerative cervical myelopathy (DCM): a prospective studyPresentation E34. Abstract 130: Prognostic factors in degenerative cervical myelopathy (DCM) for patients managed operatively and nonoperativelyPresentation E35. Abstract 175: Efficacy of surgical decompression in patients with cervical spondylotic myelopathy: results of a Canadian prospective multicentre studyPresentation E36. Abstract 67: Interobserver reliability of the modified Japanese Orthopedic Association (mJOA) score in degenerative cervical myelopathyPresentation F37. Abstract 128: Continuous optical monitoring of spinal cord hemodynamics during the first 7 days after injury in a porcine model of acute spinal cord injuryPresentation F38. Abstract 106: Development of a prediction model for central cord syndrome: an evaluation of motor recovery and the effectiveness of early surgery in a prospective, multicentre cohortPresentation F39. Abstract 135: Spinal cord dynamics under different clinical configurations of thoracolumbar burst fractures through numerical simulationsPresentation F40. Abstract 60: Predicting the heterogeneity of outcome following sensorimotor complete cervical spinal cord injury: trajectory-based analysis of 655 prospectively enrolled patientsPresentation F41. Abstract 167: Mortality in the year following discharge to the community from inpatient care for acute traumatic spinal cord injury: When and why?Presentation F42. Abstract 104: A novel method to classify patients with cervical incomplete spinal cord injury based on potential for recovery: a group-based trajectory analysis using prospective, multicentre data from over 800 patientsPresentation G43. Abstract 7: Responsiveness of standard spine outcome tools: Do they measure up?Presentation G44. Abstract 142: Patient outcomes: important psychological measuresPresentation G45. Abstract 84: Accuracy of surveillance for surgical site infections after spine surgery: a Bayesian latent class analysis using 4 independent data sourcesPresentation G46. Abstract 169: Econometric modelling: development of a surgical cost calculator for degenerative conditions of the lumbar spinePresentation G47. Abstract 124: The economic impact of nonreimbursable events in open, minimally invasive and robot-assisted lumbar fusion surgeryPresentation G48. Abstract 164: Are there sex differences in preoperative health status and health care delivery for patients undergoing scheduled lumbar surgery? An analysis from the Canadian Spine Outcomes and Research NetworkPresentation H49. Abstract 41: Patient phenotypes associated with functional outcomes after spinal cord injury: a principal component analysis in 1119 patientsPresentation H50. Abstract 103: Early versus late surgical decompression for acute traumatic spinal cord injury: a pooled analysis of prospective, multicentre data in 1548 patientsPresentation H51. Abstract 79: Clinical outcome correlation of diffusion tensor imaging and magnetic resonance imaging values: a systematic reviewPresentation H52. Abstract 137: A numerical study on the pathogenesis of central cord syndromePresentation H53. Abstract 42: Feasibility and utility of machine learning in prediction of bladder outcomes after spinal cord injury: analysis of 1250 patients from the European Multicenter Study about Spinal Cord Injury (EMSCI) registryPresentation H54. Abstract 18: Interventions to optimize spinal cord perfusion in patients with acute traumatic spinal cord injuries: a systematic reviewPresentation i55. Abstract 55: The effect of posterior lumbar spinal surgery on passive stiffness of rat paraspinal muscles 13 weeks post-surgeryPresentation i56. Abstract 43: A computed tomographic based morphometric analysis of the axis in adult populationPresentation i57. Abstract 92: Is there value to flexion–extension x-rays for degenerative spondylolisthesis? A multicentre retrospective studyPresentation i58. Abstract 98: The novel “7/20 EMG protocol” in combination with O-arm image-guided navigation for accurate lumbar pedicle placement while minimizing diagnostic radiation exposurePresentation i59. Abstract 148: Comparative biomechanical study of 2 types of transdiscal fixation implants for high-grade L5/S1 spine spondylolisthesis in a porcine modelPresentation i60. Abstract 85: The effects of fibre bundle size and vertebral level on passive stiffness of the lumbar paraspinal muscles in a rat modelPresentation J61. Abstract 157: A self-assembling peptide biomaterial to enhance human neural stem cell-based regeneration of the injured spinal cordPresentation J62. Abstract 162: Measuring demyelination, axonal loss and inflammation after human spinal cord injury with quantitative magnetic resonance imaging and histopathologyPresentation J63. Abstract 179: Characterization of ubiquitin C-terminal hydrolase L1 (UCH-L1) as a fluid biomarker of human traumatic spinal cord injuryPresentation J64. Abstract 13: Utility and role of virtual reality based simulation models in spinal decompression trainingPresentation J65. Abstract 160: Investigating the determinants for predicting surgical patient outcomes through the application of machine learning methodsPresentation J66. Abstract 143: Comparison of screw design and technique on cervical lateral mass screw fixationPresentation K67. Abstract 57: Development of clinical prognostic models for postoperative survival and quality of life in patients with surgically treated metastatic epidural spinal cord compressionPresentation K68. Abstract 170: Sarcomas of the spine: a 20-year survey of disease and treatment strategy in Ontario, CanadaPresentation K69. Abstract 15: Metastatic spine disease: Should patients with short life expectancy be denied surgical care? An international retrospective cohort studyPresentation K70. Abstract 29: Nanoparticle-functionalized polymethyl methacrylate bone cement for sustained chemotherapeutic drug deliveryPresentation K71. Abstract 90: Development of the Spine Oncology Study Group Outcomes Questionnaire – 8 Domain (SOSGOQ-8D)Presentation K72. Abstract 6: Treatment expectations of patients with spinal metastases: What do we tell our patients?Presentation L73. Abstract 48: Factors related to risk of opioid abuse in primary care patients with low back painPresentation L74. Abstract 65: QI/QA of a transitional outpatient pain program for spinePresentation L75. Abstract 168: The effect of preoperative opioid use on hospital length of stay in patients undergoing elective spine surgeryPresentation L76. Abstract 163: Disability or pain: Which best predicts patient satisfaction with surgical outcome? A Canadian Spine Outcomes and Research Network (CSORN) studyPresentation L77. Abstract 58: Rapid access to interventional pain management for lumbar nerve root pain through collaborative interprofessional provider networksPresentation L78. Abstract 63: Chronic preoperative opioid use associated with higher perioperative resource utilization and complications in adult spinal deformity patientsPresentation M79. Abstract 108: Cervical disc arthroplasty versus anterior cervical discectomy and fusion: a longitudinal analysis of reoperationsPresentation M80. Abstract 46: Preliminary results of randomized controlled trial investigating the role of psychological distress on cervical spine surgery outcomes: a baseline analysisPresentation M81. Abstract 110: Operative versus nonoperative treatment of geriatric odontoid fractures: a study of North American trauma centresPresentation M82. Abstract 74: Clinical outcome of posterior cervical foraminotomy versus anterior cervical discectomy and fusionPresentation M83. Abstract 45: “Reverse Roussouly”: ratios of cervical to thoracic shape curvature in an adult cervical deformity populationPresentation M84. Abstract 109: Treatment of acute traumatic central cord syndrome: a study of North American trauma centresPresentation N85. Abstract 118: Comparing minimally invasive versus traditional open lumbar decompression and fusion surgery: a Canadian Spine Outcomes and Research Network (CSORN) studyPresentation N86. Abstract 54: Time to return to work after lumbar spine surgeryPresentation N87. Abstract 28: Patient-reported outcomes following surgery for lumbar spinal stenosis: comparison of a universal and multitier health care systemPresentation N88. Abstract 93: Outcomes of surgery in older adults with lumbar spinal stenosisPresentation N89. Abstract 162: Functional objective assessment using the TUG test is a useful tool to evaluate outcome in lumbar spinal stenosisPresentation N90. Abstract 36: A Canadian Spine Outcomes and Research Network (CSORN) matched-cohort study comparing lumbar fusion and disk arthroplastyPresentation o91. Abstract 171: Development of clinical practice guidelines for the management of traumatic spinal column and cord injuries in British Columbia: an approach to standardizing care of spine trauma patientsPresentation o92. Abstract 22: Notes from a small island: stemming the tide of a spinal deluge. The use of encrypted software applications to ensure accountability, quality control and surgical consensus in a national acute adult spinal surgery centrePresentation o93. Abstract 129: Traumatic spinal cord injuries among Aboriginal and non-Aboriginal populations in Canada: an ambispective outcomes studyPresentation o94. Abstract 132: Traumatic spinal cord injury in New Zealand and Canada: a comparative analysisPresentation o95. Abstract 150: Exploring the reasons for readmission following traumatic spinal cord injuryPresentation o96. Abstract 59: Exploring the epidemiology and impact of spinal cord injury in the elderly: a 15-year Canadian population-based cohort studyPresentation P1. Abstract 139: Incidence and management of spinal metastasis in Ontario: a population-based studyPresentation P2. Abstract 91: A general population utility valuation study for the Spine Oncology Study Group Outcomes Questionnaire – 8DPresentation P3. Abstract 158: Metastatic vertebrae segmentation by augmented 3D convolutional neural networkPresentation P4. Abstract 73: Risk factors for failure of radiation therapy for spinal metastasesPresentation P5. Abstract 68: Significance of extracanalicular cement extravasation in thoracolumbar kyphoplastyPresentation P6. Abstract 120: Modelling fracture in osteoblastic vertebraePresentation P7. Abstract 97: The development of novel 2-in-1 patient-specific, 3D-printed laminar osteotomy guides with integrated pedicle screw guidesPresentation P8. Abstract 56: Effect of pelvic retroversion on pelvic geometry and muscle morphometry from upright magnetic resonance imagingPresentation P9. Abstract 161: Anatomic relationship between the accessory process of the lumbar spine and the pedicle screw entry pointPresentation P10. Abstract 20: Novel chair to measure lumbar spine extensors strength in adultsPresentation P11. Abstract 95: Error measurement between human spine, 3D scans, CT-based models, and 3D-printed modelsPresentation P12. Abstract 52: The diagnostic precision of computed tomography for traumatic cervical spine injury: an in vitro investigationPresentation P13. Abstract 94: Epidural abscess causing spinal cord infarctionPresentation P14. Abstract 83: The nerve root sedimentation sign on magnetic resonance imaging is not only correlated with neurogenic claudication: association with all types of leg-dominant mechanical painPresentation P15. Abstract 3: Accuracy of robot-assisted compared with freehand pedicle screw placement in spine surgery: a meta-analysis of randomized controlled trialsPresentation P16. Abstract 82: A positive nerve root sedimentation sign on magnetic resonance imaging is associated with improved surgical outcomes in patients with back dominant painPresentation P17. Abstract 16: Thoracolumbar burst fracture: McCormack load-sharing classification —systematic review and single-arm meta-analysisPresentation P18. Abstract 86: Morphological features of thoracolumbar burst fractures associated with neurologic recovery after thoracolumbar traumatic spinal cord injuryPresentation P19. Abstract 89: Radiographic parameters of listhesis and instability are not associated with health status or clinical outcomes in grade 1 degenerative spondylolisthesisPresentation P20. Abstract 37: Predictive socioeconomic factors following lumbar disk arthroplasty: a Canadian Spine Outcomes and Research Network (CSORN) studyPresentation P21. Abstract 25: Effect of in situ fusion in lumbar spondylolisthesis on clinical outcomes and spino-pelvic sagittal balancingPresentation P22. Abstract 10: Sex differences in the surgical management of lumbar degenerative disease: a systematic reviewPresentation P23. Abstract 35: Two-year results of lumbar disk arthroplasty: a Canadian Spine Outcomes and Research Network (CSORN) studyPresentation P24. Abstract 78: Does disc morphology affect the success of nonoperative treatment of chronic sciatica from a lumbar disc herniation?Presentation P25. Abstract 141: Opioid prescribing patterns: preliminary investigationPresentation P26. Abstract 133: Frailty is a better predictor of complications than age alone after surgical treatment of degenerative cervical myelopathy: an ambispective study of 5107 elderly patients from the National Surgical Quality Improvement Program databasePresentation P27. Abstract 26: Pathway analysis in spine surgery: a model for evaluating length of stayPresentation P29. Abstract 156: Patients with adolescent idiopathic scoliosis (AIS) have different cervical lordosis than the normal populationPresentation P31. Abstract 64: Investigation of thoracic spinal muscle morphology with upright magnetic resonance imagingPresentation P32. Abstract 80: Postoperative complication prediction between spinal surgeons and a machine learning model: a comparative studyPresentation P33. Abstract 81: Is using a simplified procedural classification as accurate as using current procedural terminology codes to predict future complications in spinal surgery?Presentation P34. Abstract 88: Preoperative patient performance status and frailty phenotype as predictive factors of outcome in surgically treated patients with metastatic spinal disease: a systematic literature reviewPresentation P35. Abstract 101: The measurements of frailty and their application to spine surgeryPresentation P36. Abstract 131: The effect of prolonged sitting on muscle reflexes of the low backPresentation P37. Abstract 87: Implementing a rapid discharge pathway for adolescent idiopathic scoliosis in Canada. Can J Surg 2020. [DOI: 10.1503/cjs.014720] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/01/2022] Open
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An ontology-driven framework to support the dynamic formation of an interdisciplinary healthcare team. Int J Med Inform 2020; 136:104075. [PMID: 31958670 DOI: 10.1016/j.ijmedinf.2020.104075] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/07/2019] [Revised: 12/14/2019] [Accepted: 01/03/2020] [Indexed: 10/25/2022]
Abstract
BACKGROUND AND PURPOSE Teamwork has become a modus operandi in healthcare and delivery of patient care by an interdisciplinary healthcare team (IHT) is now a prevailing modality of care. We argue that a formal and automated support framework is needed for an IHT to properly leverage information technology resources. Such a framework should allow for patient preferences and expand a representation of a clinical workflow with a formal model of dynamic formation of a team, especially with regards to team leader- and membership, and the assignment of tasks to team members. Our goal was to develop such a support framework, present its prototype software implementation and verify the implementation using a proof-of-concept use case. Specifically, we focused on clinical workflows for in-patient tertiary care and on patient preferences with regards to selecting team members and team leaders. MATERIALS AND METHODS Drawing on the research on clinical teamwork we defined the conceptual foundations for the proposed framework. Then, we designed its architecture and used ontology-driven design and first-order logic with associated reasoning methods to create and operationalize architectural elements. Finally, we incorporated existing solutions for business workflow modeling and execution as a backend for implementing the proposed framework. RESULTS We developed a Team and Workflow Management Framework (TWMF) with semantic components that allow for formalizing and operationalizing team formation in in-patient tertiary care setting and support provider-related patient preferences. We also created a prototype software implementation of TWMF using the IBM Business Process Manager platform. This implementation was evaluated in several simulated patient scenarios. CONCLUSIONS TWMF integrates existing workflow technologies and extends them with the capabilities to support dynamic formation of an IHT. Results of this research can be used to support real-time execution of clinical workflows, or to simulate their execution in order to assess the impact of various conditions (e.g., patterns of work shifts, staffing) on IHT operations.
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Assessing the Impact of Distance Functions on K-Nearest Neighbours Imputation of Biomedical Datasets. Artif Intell Med 2020. [DOI: 10.1007/978-3-030-59137-3_43] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/23/2022]
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Shared Decision-Making Ontology for a Healthcare Team Executing a Workflow, an Instantiation for Metastatic Spinal Cord Compression Management. AMIA ... ANNUAL SYMPOSIUM PROCEEDINGS. AMIA SYMPOSIUM 2018; 2018:877-886. [PMID: 30815130 PMCID: PMC6371285] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Subscribe] [Scholar Register] [Indexed: 06/09/2023]
Abstract
Regardless of potential benefits and better outcomes, adoption of shared decision-making between a patient and providers involved in his/her care is still in its infancy. This paper intends to fill this gap by formalizing shared decision-making, situating it as part of team-based care delivery, and incorporating workflow concepts allowing for identification of shared decision-making tasks. We accomplish that by creating novel shared decision-making ontology which constitutes the first step required in the development of a decision support system for shared decision-making. The proposed ontology formally defines and describes the key concepts and relations in the shared decision-making domain and lays the foundation for the formalization and support of the patient management process. We illustrate the applicability of the proposed ontology by creating its instantiation for the complex patient management scenario involving shared decision-making about the treatment of metastatic spinal cord compression.
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Abstract
Summary
Objectives:
Our objective was to design and develop a mobile clinical decision support system for emergency triage of different acute pain presentations. The system should interact with existing hospital information systems, run on mobile computing devices (handheld computers) and be suitable for operation in weak-connectivity conditions (with unstable connections between mobile clients and a server).
Methods:
The MET (Mobile Emergency Triage) system was designed following an extended client-server architecture. The client component, responsible for triage decision support, is built as a knowledge-based system, with domain ontology separated from generic problem solving methods and used for the automatic creation of a user interface.
Results:
The MET system is well suited for operation in the Emergency Department of a hospital. The system’s external interactions are managed by the server, while the MET clients, running on handheld computers are used by clinicians for collecting clinical data and supporting triage at the bedside. The functionality of the MET client is distributed into specialized modules, responsible for triaging specific types of acute pain presentations. The modules are stored on the server, and on request they can be transferred and executed on the mobile clients. The modular design provides for easy extension of the system’s functionality. A clinical trial of the MET system validated the appropriateness of the system’s design, and proved the usefulness and acceptance of the system in clinical practice.
Conclusions:
The MET system captures the necessary hospital data, allows for entry of patient information, and provides triage support. By operating on handheld computers, it fits into the regular emergency department workflow without introducing any hindrances or disruptions. It supports triage anytime and anywhere, directly at the point of care, and also can be used as an electronic patient chart, facilitating structured data collection.
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[Miscommunication as a risk focus in patient safety : Work process analysis in prehospital emergency care]. Anaesthesist 2018; 67:255-263. [PMID: 29404658 DOI: 10.1007/s00101-018-0413-x] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/18/2017] [Revised: 12/31/2017] [Accepted: 01/15/2018] [Indexed: 11/29/2022]
Abstract
BACKGROUND In an analysis of a critical incident reporting system (CIRS) in out-of-hospital emergency medicine, it was demonstrated that in 30% of cases deficient communication led to a threat to patients; however, the analysis did not show what exactly the most dangerous work processes are. Current research shows the impact of poor communication on patient safety. OBJECTIVES An out-of-hospital workflow analysis collects data about key work processes and risk areas. The analysis points out confounding factors for a sufficient communication. Almost 70% of critical incidents are based on human factors. Factors, such as communication and teamwork have an impact but fatigue, noise levels and illness also have a major influence. MATERIAL AND METHODS (I) CIRS database analysis The workflow analysis was based on 247 CIRS cases. This was completed by participant observation and interviews with emergency doctors and paramedics. The 247 CIRS cases displayed 282 communication incidents, which are categorized into 6 subcategories of miscommunication. One CIRS case can be classified into different categories if more communication incidents were validated by the reviewers and four experienced emergency physicians sorted these cases into six subcategories. (II) Workflow analysis The workflow analysis was carried out between 2015 and 2016 in Jena and Berlin, Germany. The focal point of research was to find accumulation of communication risks in different parts of prehospital patient care. During 30 h driving with emergency ambulances, the author interviewed 12 members of the emergency medical service of which 5 were emergency physicians and 7 paramedics. A total of 11 internal medicine cases and one automobile accident were monitored. After patient care the author asked in a 15-min interview if miscommunication or communication incidents occurred. RESULTS (I) CIRS analysis Between 2005 and 2015, 845 reports were reported to the database. The experts identified 247 incident reports with communication failure. All communication aspects were analyzed and classified. We identified 282 communication incidents. (II) Workflow analysis The analysis showed three phases of prehospital patient care: 1. incoming emergency call and dispatch of ambulance service, 2. prehospital treatment, 3. transportation to a hospital. Overall, the number of incidences is increasing as a consequence of parallel workflows. Category 1 was particularly significant and predominantly, paramedics criticized that emergency physicians did not acknowledge their advice (n = 73 vs. n = 9). Category 3 with n = 63, category 4 with n = 20 and category 2 with n = 13 were the major reasons for incidents. CONCLUSION A better interface communication helps to coordinate patient transfer and is an option for optimizing resources. Frequent training in communication is an option to avoid incidents.
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Learning the Preferences of Physicians for the Organization of Result Lists of Medical Evidence Articles. Methods Inf Med 2018; 53:344-56. [DOI: 10.3414/me13-01-0085] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.2] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/24/2013] [Accepted: 02/24/2014] [Indexed: 11/09/2022]
Abstract
SummaryBackground: Online medical knowledge repositories such as MEDLINE and The Cochrane Library are increasingly used by physicians to retrieve articles to aid with clinical decision making. The prevailing approach for organizing retrieved articles is in the form of a rank-ordered list, with the assumption that the higher an article is presented on a list, the more relevant it is.Objectives: Despite this common list-based organization, it is seldom studied how physicians perceive the association between the relevance of articles and the order in which articles are presented. In this paper we describe a case study that captured physician preferences for 3-element lists of medical articles in order to learn how to organize medical knowledge for decision-making.Methods: Comprehensive relevance evaluations were developed to represent 3-element lists of hypothetical articles that may be retrieved from an online medical knowledge source such as MEDLINE or The Cochrane Library. Comprehensive relevance evalua tions asses not only an article’s relevance for a query, but also whether it has been placed on the correct list position. In other words an article may be relevant and correctly placed on a result list (e.g. the most relevant article appears first in the result list), an article may be relevant for a query but placed on an incorrect list position (e.g. the most relevant article appears second in a result list), or an article may be irrelevant for a query yet still appear in the result list. The relevance evaluations were presented to six senior physi cians who were asked to express their preferences for an article’s relevance and its position on a list by pairwise comparisons representing different combinations of 3-element lists. The elicited preferences were assessed using a novel GRIP (Generalized Regression with Intensities of Preference) method and represented as an additive value function. Value functions were derived for individual physicians as well as the group of physicians.Results: The results show that physicians assign significant value to the 1st position on a list and they expect that the most relevant article is presented first. Whilst physicians still prefer obtaining a correctly placed article on position 2, they are also quite satisfied with misplaced relevant article. Low consideration of the 3rd position was uniformly confirmed.Conclusions: Our findings confirm the importance of placing the most relevant article on the 1st position on a list and the importance paid to position on a list significantly diminishes after the 2nd position. The derived value functions may be used by developers of clinical decision support applications to decide how best to organize medical knowledge for decision making and to create personalized evaluation measures that can augment typical measures used to evaluate information retrieval systems.
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Clinical Decision Support System for Point of Care Use. Methods Inf Med 2018; 48:381-90. [DOI: 10.3414/me0574] [Citation(s) in RCA: 23] [Impact Index Per Article: 3.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/20/2008] [Accepted: 01/12/2009] [Indexed: 11/09/2022]
Abstract
Summary
Objectives: The objective of this research was to design a clinical decision support system (CDSS) that supports heterogeneous clinical decision problems and runs on multiple computing platforms. Meeting this objective required a novel design to create an extendable and easy to maintain clinical CDSS for point of care support. The proposed solution was evaluated in a proof of concept implementation.
Methods: Based on our earlier research with the design of a mobile CDSS for emergency triage we used ontology-driven design to represent essential components of a CDSS. Models of clinical decision problems were derived from the ontology and they were processed into executable applications during runtime. This allowed scaling applications’ functionality to the capabilities of computing platforms. A prototype of the system was implemented using the extended client-server architecture and Web services to distribute the functions of the system and to make it operational in limited connectivity conditions.
Results: The proposed design provided a common framework that facilitated development of diversified clinical applications running seamlessly on a variety of computing platforms. It was prototyped for two clinical decision problems and settings (triage of acute pain in the emergency department and postoperative management of radical pros-tatectomy on the hospital ward) and implemented on two computing platforms – desktop and handheld computers.
Conclusions: The requirement of the CDSS heterogeneity was satisfied with ontology-driven design. Processing of application models described with the help of ontological models allowed having a complex system running on multiple computing platforms with different capabilities. Finally, separation of models and runtime components contributed to improved extensibility and maintainability of the system.
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Abstract
The AAAI-17 workshop program included 17 workshops covering a wide range of topics in AI. Workshops were held Sunday and Monday, February 4-5, 2017 at the Hilton San Francisco Union Square in San Francisco, California, USA. This report contains summaries of 12 of the workshops, and brief abstracts of the remaining 5
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BK Polyomavirus-Specific 9mer CD8 T Cell Responses Correlate With Clearance of BK Viremia in Kidney Transplant Recipients: First Report From the Swiss Transplant Cohort Study. Am J Transplant 2017; 17:2591-2600. [PMID: 28326672 DOI: 10.1111/ajt.14282] [Citation(s) in RCA: 48] [Impact Index Per Article: 6.9] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/24/2017] [Revised: 02/22/2017] [Accepted: 03/12/2017] [Indexed: 01/25/2023]
Abstract
BK polyomavirus (BKPyV) causes premature kidney transplant (KT) failure in 1-15% of patients. Because antivirals are lacking, most programs screen for BKPyV-viremia and, if positive, reduce immunosuppression. To evaluate the relationship of viremia and BKPyV-specific immunity, we examined prospectively cryopreserved plasma and peripheral blood mononuclear cells at the time of transplantation (T0) and at 6 mo (T6) and 12 mo (T12) after transplant from 28 viremic KT patients and 68 nonviremic controls matched for the transplantation period. BKPyV IgG seroprevalence was comparable between cases (89.3%) and controls (91.2%; p = 0.8635), but cases had lower antibody levels (p = 0.022) at T0. Antibody levels increased at T6 and T12 but were not correlated with viremia clearance. BKPyV-specific T cell responses to pools of overlapping 15mers (15mer peptide pool [15mP]) or immunodominant CD8 9mers (9mer peptide pool [9mP]) from the early viral gene region were not different between cases and controls at T0; however, clearance of viremia was associated with stronger 9mP responses at T6 (p = 0.042) and T12 (p = 0.048), whereas 15mP responses were not informative (T6 p = 0.359; T12 p = 0.856). BKPyV-specific T cells could be expanded in vitro from all patients after transplant, permitting identification of 78 immunodominant 9mer epitopes including 50 new ones across different HLA class I. Thus, 9mP-responses may be a novel marker of reconstituting CD8 T cell function that warrants further study as a complement of plasma BKPyV loads for guiding immunosuppression reduction.
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Difficulty Factors and Preprocessing in Imbalanced Data Sets: An Experimental Study on Artificial Data. FOUNDATIONS OF COMPUTING AND DECISION SCIENCES 2017. [DOI: 10.1515/fcds-2017-0007] [Citation(s) in RCA: 12] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/15/2022] Open
Abstract
Abstract
In this paper we describe results of an experimental study where we checked the impact of various difficulty factors in imbalanced data sets on the performance of selected classifiers applied alone or combined with several preprocessing methods. In the study we used artificial data sets in order to systematically check factors such as dimensionality, class imbalance ratio or distribution of specific types of examples (safe, borderline, rare and outliers) in the minority class. The results revealed that the latter factor was the most critical one and it exacerbated other factors (in particular class imbalance). The best classification performance was demonstrated by non-symbolic classifiers, particular by k-NN classifiers (with 1 or 3 neighbors - 1NN and 3NN, respectively) and by SVM. Moreover, they benefited from different preprocessing methods - SVM and 1NN worked best with undersampling, while oversampling was more beneficial for 3NN.
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Comprehensive mitigation framework for concurrent application of multiple clinical practice guidelines. J Biomed Inform 2016; 66:52-71. [PMID: 27939413 DOI: 10.1016/j.jbi.2016.12.002] [Citation(s) in RCA: 21] [Impact Index Per Article: 2.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/07/2016] [Revised: 12/03/2016] [Accepted: 12/05/2016] [Indexed: 12/18/2022]
Abstract
In this work we propose a comprehensive framework based on first-order logic (FOL) for mitigating (identifying and addressing) interactions between multiple clinical practice guidelines (CPGs) applied to a multi-morbid patient while also considering patient preferences related to the prescribed treatment. With this framework we respond to two fundamental challenges associated with clinical decision support: (1) concurrent application of multiple CPGs and (2) incorporation of patient preferences into the decision making process. We significantly expand our earlier research by (1) proposing a revised and improved mitigation-oriented representation of CPGs and secondary medical knowledge for addressing adverse interactions and incorporating patient preferences and (2) introducing a new mitigation algorithm. Specifically, actionable graphs representing CPGs allow for parallel and temporal activities (decisions and actions). Revision operators representing secondary medical knowledge support temporal interactions and complex revisions across multiple actionable graphs. The mitigation algorithm uses the actionable graphs, revision operators and available (and possibly incomplete) patient information represented in FOL. It relies on a depth-first search strategy to find a valid sequence of revisions and uses theorem proving and model finding techniques to identify applicable revision operators and to establish a management scenario for a given patient if one exists. The management scenario defines a safe (interaction-free) and preferred set of activities together with possible patient states. We illustrate the use of our framework with a clinical case study describing two patients who suffer from chronic kidney disease, hypertension, and atrial fibrillation, and who are managed according to CPGs for these diseases. While in this paper we are primarily concerned with the methodological aspects of mitigation, we also briefly discuss a high-level proof of concept implementation of the proposed framework in the form of a clinical decision support system (CDSS). The proposed mitigation CDSS "insulates" clinicians from the complexities of the FOL representations and provides semantically meaningful summaries of mitigation results. Ultimately we plan to implement the mitigation CDSS within our MET (Mobile Emergency Triage) decision support environment.
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Is There a Consensus when Physicians Evaluate the Relevance of Retrieved Systematic Reviews? Methods Inf Med 2016; 55:292-8. [PMID: 26940845 DOI: 10.3414/me15-01-0131] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/09/2015] [Accepted: 02/07/2016] [Indexed: 11/09/2022]
Abstract
BACKGROUND A significant challenge associated with practicing evidence-based medicine is to provide physicians with relevant clinical information when it is needed. At the same time it appears that the notion of relevance is subjective and its perception is affected by a number of contextual factors. OBJECTIVES To assess to what extent physicians agree on the relevance of evidence in the form of systematic reviews for a common set of patient cases, and to identify possible contextual factors that influence their perception of relevance. METHODS A web-based survey was used where pediatric emergency physicians from multiple academic centers across Canada were asked to evaluate the relevance of systematic reviews retrieved automatically for 14 written case vignettes (paper patients). The vignettes were derived from prospective data describing pediatric patients with asthma exacerbations presenting at the emergency department. To limit the cognitive burden on respondents, the number of reviews associated with each vignette was limited to three. RESULTS Twenty-two academic emergency physicians with varying years of clinical practice completed the survey. There was no consensus in their evaluation of relevance of the retrieved reviews and physicians' assessments ranged from very relevant to irrelevant evidence, with the majority of evaluations being somewhere in the middle. This indicates that the study participants did not share a notion of relevance uniformly. Further analysis of commentaries provided by the physicians allowed identifying three possible contextual factors: expected specificity of evidence (acute vs chronic condition), the terminology used in the systematic reviews, and the micro environment of clinical setting. CONCLUSIONS There is no consensus among physicians with regards to what constitutes relevant clinical evidence for a given patient case. Subsequently, this finding suggests that evidence retrieval systems should allow for deep customization with regards to physician's preferences and contextual factors, including differences in the micro environment of each clinical setting.
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Expanding a First-Order Logic Mitigation Framework to Handle Multimorbid Patient Preferences. AMIA ... ANNUAL SYMPOSIUM PROCEEDINGS. AMIA SYMPOSIUM 2015; 2015:895-904. [PMID: 26958226 PMCID: PMC4765594] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Subscribe] [Scholar Register] [Indexed: 06/05/2023]
Abstract
The increasing prevalence of multimorbidity is a challenge for physicians who have to manage a constantly growing number of patients with simultaneous diseases. Adding to this challenge is the need to incorporate patient preferences as key components of the care process, thanks in part to the emergence of personalized and participatory medicine. In our previous work we proposed a framework employing first order logic to represent clinical practice guidelines (CPGs) and to mitigate possible adverse interactions when concurrently applying multiple CPGs to a multimorbid patient. In this paper, we describe extensions to our methodological framework that (1) broaden our definition of revision operators to support required and desired types of revisions defined in secondary knowledge sources, and (2) expand the mitigation algorithm to apply revisions based on their type. We illustrate the capabilities of the expanded framework using a clinical case study of a multimorbid patient with stable cardiac artery disease who suffers a sudden onset of deep vein thrombosis.
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A Framework for Modeling Workflow Execution by an Interdisciplinary Healthcare Team. Stud Health Technol Inform 2015; 216:1100. [PMID: 26262399] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 06/04/2023]
Abstract
The use of business workflow models in healthcare is limited because of insufficient capture of complexities associated with behavior of interdisciplinary healthcare teams that execute healthcare workflows. In this paper we present a novel framework that builds on the well-founded business workflow model formalism and related infrastructures and introduces a formal semantic layer that describes selected aspects of team dynamics and supports their real-time operationalization.
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MET4: Supporting Workflow Execution for Interdisciplinary Healthcare Teams. BUSINESS PROCESS MANAGEMENT WORKSHOPS 2015. [DOI: 10.1007/978-3-319-15895-2_4] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 01/15/2023]
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Using First-Order Logic to Represent Clinical Practice Guidelines and to Mitigate Adverse Interactions. ACTA ACUST UNITED AC 2014. [DOI: 10.1007/978-3-319-13281-5_4] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.1] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/16/2023]
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First-order logic theory for manipulating clinical practice guidelines applied to comorbid patients: a case study. AMIA ... ANNUAL SYMPOSIUM PROCEEDINGS. AMIA SYMPOSIUM 2014; 2014:892-898. [PMID: 25954396 PMCID: PMC4419977] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Subscribe] [Scholar Register] [Indexed: 06/04/2023]
Abstract
Clinical practice guidelines (CPGs) implement evidence-based medicine designed to help generate a therapy for a patient suffering from a single disease. When applied to a comorbid patient, the concurrent combination of treatment steps from multiple CPGs is susceptible to adverse interactions in the resulting combined therapy (i.e., a therapy established according to all considered CPGs). This inability to concurrently apply CPGs has been shown to be one of the key shortcomings of CPG uptake in a clinical setting1. Several research efforts are underway to address this issue such as the K4CARE2 and GuideLine INteraction Detection Assistant (GLINDA)3 projects and our previous research on applying constraint logic programming to developing a consistent combined therapy for a comorbid patient4. However, there is no generalized framework for mitigation that effectively captures general characteristics of the problem while handling nuances such as time and ordering requirements imposed by specific CPGs. In this paper we propose a first-order logic-based (FOL) approach for developing a generalized framework of mitigation. This approach uses a meta-algorithm and entailment properties to mitigate (i.e., identify and address) adverse interactions introduced by concurrently applied CPGs. We use an illustrative case study of a patient suffering from type 2 diabetes being treated for an onset of severe rheumatoid arthritis to show the expressiveness and robustness of our proposed FOL-based approach, and we discuss its appropriateness as the basis for the generalized theory.
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A Framework for Incorporating Patient Preferences to Deliver Participatory Medicine via Interdisciplinary Healthcare Teams. AMIA ... ANNUAL SYMPOSIUM PROCEEDINGS. AMIA SYMPOSIUM 2014; 2014:835-844. [PMID: 25954390 PMCID: PMC4419939] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Subscribe] [Scholar Register] [Indexed: 06/04/2023]
Abstract
Participatory medicine refers to the equal participation of patients and interdisciplinary healthcare team (IHT) members as part of care delivery. Facilitating workflow execution is a significant challenge for participatory medicine because of the need to integrate IHT members into a common workflow. A further challenge is that patient preferences should be considered when executing a workflow. To date there is limited research on supporting patient workflow as part of participatory medicine practices. To address that shortcoming we used a two-phase approach to develop a framework for participatory medicine that integrates different IHT members and workflows including the incorporation of patient preferences about care delivery options. Our framework uses a domain ontology to define the patient, IHT concepts and relations, as well as a workflow for operationalizing participatory medicine via an IHT. Proof of concept of the proposed framework is illustrated with a palliative care pain management case study.
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Expanding usability analysis with intrinsic motivation concepts to learn about CDSS adoption: a case study. HEALTH POLICY AND TECHNOLOGY 2014. [DOI: 10.1016/j.hlpt.2014.02.001] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.2] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/25/2022]
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Adiponectin promotes coxsackievirus B3 myocarditis by suppression of acute anti-viral immune responses. Basic Res Cardiol 2014; 109:408. [DOI: 10.1007/s00395-014-0408-y] [Citation(s) in RCA: 15] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 07/09/2013] [Accepted: 03/14/2014] [Indexed: 10/25/2022]
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Comparing predictions made by a prediction model, clinical score, and physicians: pediatric asthma exacerbations in the emergency department. Appl Clin Inform 2013; 4:376-91. [PMID: 24155790 DOI: 10.4338/aci-2013-04-ra-0029] [Citation(s) in RCA: 28] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/27/2013] [Accepted: 07/19/2013] [Indexed: 12/12/2022] Open
Abstract
BACKGROUND Asthma exacerbations are one of the most common medical reasons for children to be brought to the hospital emergency department (ED). Various prediction models have been proposed to support diagnosis of exacerbations and evaluation of their severity. OBJECTIVES First, to evaluate prediction models constructed from data using machine learning techniques and to select the best performing model. Second, to compare predictions from the selected model with predictions from the Pediatric Respiratory Assessment Measure (PRAM) score, and predictions made by ED physicians. DESIGN A two-phase study conducted in the ED of an academic pediatric hospital. In phase 1 data collected prospectively using paper forms was used to construct and evaluate five prediction models, and the best performing model was selected. In phase 2 data collected prospectively using a mobile system was used to compare the predictions of the selected prediction model with those from PRAM and ED physicians. MEASUREMENTS Area under the receiver operating characteristic curve and accuracy in phase 1; accuracy, sensitivity, specificity, positive and negative predictive values in phase 2. RESULTS In phase 1 prediction models were derived from a data set of 240 patients and evaluated using 10-fold cross validation. A naive Bayes (NB) model demonstrated the best performance and it was selected for phase 2. Evaluation in phase 2 was conducted on data from 82 patients. Predictions made by the NB model were less accurate than the PRAM score and physicians (accuracy of 70.7%, 73.2% and 78.0% respectively), however, according to McNemar's test it is not possible to conclude that the differences between predictions are statistically significant. CONCLUSION Both the PRAM score and the NB model were less accurate than physicians. The NB model can handle incomplete patient data and as such may complement the PRAM score. However, it requires further research to improve its accuracy.
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Mitigation of adverse interactions in pairs of clinical practice guidelines using constraint logic programming. J Biomed Inform 2013; 46:341-53. [DOI: 10.1016/j.jbi.2013.01.002] [Citation(s) in RCA: 24] [Impact Index Per Article: 2.2] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/09/2012] [Revised: 01/06/2013] [Accepted: 01/10/2013] [Indexed: 10/27/2022]
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Clinical practice guidelines and comorbid diseases: a MiniZinc representation of guideline models for mitigating adverse interactions. Stud Health Technol Inform 2013; 192:352-356. [PMID: 23920575] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 06/02/2023]
Abstract
Managing a patient with comorbid diseases according to multiple clinical practice guidelines (CPGs) may result in adverse interactions that need to be mitigated (identified and addressed) so a safe therapy can be devised. However, mitigation poses both clinical and methodological challenges. It requires extensive domain knowledge and calls for advanced CPG models and efficient algorithms to process them. We respond to the above challenges by describing our algorithm that mitigates interactions between pairs of CPGs. The algorithm creates logical models of analyzed CPGs and uses constraint logic programming (CLP) together with domain knowledge, codified as interaction and revision operators, to process them. Logical CPG models are transformed into CLP-CPG models that are solved to find a safe therapy. We represent these CLP-CPG models using MiniZinc, a standard language for CLP models. As motivation and illustration of our mitigation algorithm we use a clinical case study describing a patient managed for hypertension and deep vein thrombosis according to two individual CPGs. We apply the algorithm to this scenario and present MiniZinc representations of the constructed CLP-CPG models.
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Using Constraint Logic Programming to Implement Iterative Actions and Numerical Measures during Mitigation of Concurrently Applied Clinical Practice Guidelines. Artif Intell Med 2013. [DOI: 10.1007/978-3-642-38326-7_3] [Citation(s) in RCA: 12] [Impact Index Per Article: 1.1] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/12/2022]
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Using PICO to align medical evidence with MDs decision making models. Stud Health Technol Inform 2013; 192:1057. [PMID: 23920831] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 06/02/2023]
Abstract
Modern medicine is characterized by an "explosion" in clinical research information making practical application of Evidence-Based Medicine (EBM), problematic for many clinicians. We have developed a PICO-(evidence based search strategy focusing on Patient/Population, Intervention, Comparison and Outcome)-based framework for (indexing and retrieving medical evidence and we posit that the use of PICO allows for organizing evidence that is aligned with an MD's decision making model. We describe a study where medical students evaluated our PICO-based approach and results show that students are eager to apply EBM but are hindered by a lack of specialist skills. Students reported that the PICO-based framework for organizing evidence provided an intuitive way of accessing and evaluating evidence and would be useful for their clinical tasks.
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A task-based support architecture for developing point-of-care clinical decision support systems for the emergency department. Methods Inf Med 2012; 52:18-32. [PMID: 23232759 DOI: 10.3414/me11-01-0099] [Citation(s) in RCA: 21] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Abstract] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/12/2011] [Accepted: 09/01/2012] [Indexed: 11/09/2022]
Abstract
OBJECTIVES The purpose of this study was to create a task-based support architecture for developing clinical decision support systems (CDSSs) that assist physicians in making decisions at the point-of-care in the emergency department (ED). The backbone of the proposed architecture was established by a task-based emergency workflow model for a patient-physician encounter. METHODS The architecture was designed according to an agent-oriented paradigm. Specifically, we used the O-MaSE (Organization-based Multi-agent System Engineering) method that allows for iterative translation of functional requirements into architectural components (e.g., agents). The agent-oriented paradigm was extended with ontology-driven design to implement ontological models representing knowledge required by specific agents to operate. RESULTS The task-based architecture allows for the creation of a CDSS that is aligned with the task-based emergency workflow model. It facilitates decoupling of executable components (agents) from embedded domain knowledge (ontological models), thus supporting their interoperability, sharing, and reuse. The generic architecture was implemented as a pilot system, MET3-AE--a CDSS to help with the management of pediatric asthma exacerbation in the ED. The system was evaluated in a hospital ED. CONCLUSIONS The architecture allows for the creation of a CDSS that integrates support for all tasks from the task-based emergency workflow model, and interacts with hospital information systems. Proposed architecture also allows for reusing and sharing system components and knowledge across disease-specific CDSSs.
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Predicting the need for CT imaging in children with minor head injury using an ensemble of Naive Bayes classifiers. Artif Intell Med 2012; 54:163-70. [DOI: 10.1016/j.artmed.2011.11.005] [Citation(s) in RCA: 16] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/01/2011] [Revised: 10/18/2011] [Accepted: 11/24/2011] [Indexed: 10/14/2022]
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Reconciling pairs of concurrently used clinical practice guidelines using Constraint Logic Programming. AMIA ... ANNUAL SYMPOSIUM PROCEEDINGS. AMIA SYMPOSIUM 2011; 2011:944-953. [PMID: 22195153 PMCID: PMC3243171] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Subscribe] [Scholar Register] [Indexed: 05/31/2023]
Abstract
This paper describes a new methodological approach to reconciling adverse and contradictory activities (called points of contention) occurring when a patient is managed according to two or more concurrently used clinical practice guidelines (CPGs). The need to address these inconsistencies occurs when a patient with more than one disease, each of which is a comorbid condition, has to be managed according to different treatment regimens. We propose an automatic procedure that constructs a mathematical guideline model using the Constraint Logic Programming (CLP) methodology, uses this model to identify and mitigate encountered points of contention, and revises the considered CPGs accordingly. The proposed procedure is used as an alerting mechanism and coupled with a guideline execution engine warns the physician about potential problems with the concurrent application of two or more guidelines. We illustrate the operation of our procedure in a clinical scenario describing simultaneous use of CPGs for duodenal ulcer and transient ischemic attack.
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Triage of the child with abdominal pain: A clinical algorithm for emergency patient management. Paediatr Child Health 2011; 6:23-8. [PMID: 20084204 DOI: 10.1093/pch/6.1.23] [Citation(s) in RCA: 12] [Impact Index Per Article: 0.9] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/14/2022] Open
Abstract
OBJECTIVE To create a simplified clinical algorithm for the triage of children with abdominal pain. DESIGN Retrospective analysis. SETTING Emergency room at the Children's Hospital of Eastern Ontario, Ottawa, Ontario. METHODS A data mining methodology (rough sets analysis) was applied to a randomized data set obtained from 175 emergency room admission charts of patients. Patients were placed into two diagnostic decision classes: appendicitis confirmed by a pathological report, and resolution (this classification implied the resolution of all clinical complaints and physical findings, with no pathological diagnosis and no operative procedure). RESULTS Nine clinical symptoms and signs were identified as being important in the management of children with abdominal pain. A clinically based algorithm for the triage of such children was developed. CONCLUSIONS It is possible to develop a clinical algorithm for the triage of children with abdominal pain that can also be used by nonmedical professionals. A template for such an algorithm can be used as the basis for diagnosing other paediatric emergencies, such as chest pain, headaches and joint pain.
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MET3-AE system to support management of pediatric asthma exacerbation in the emergency department. Stud Health Technol Inform 2010; 160:841-845. [PMID: 20841804] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 05/29/2023]
Abstract
A decision making process behind the management of pediatric patients with asthma exacerbations in the Emergency Department includes three stages: data collection, diagnosis formulation and treatment planning. These stages are associated with activities involving different types of clinical knowledge: factual, conceptual and procedural. Effective decision support should span over the entire decision making process and facilitate the use of diversified clinical knowledge. In this paper we present MET3-AE - a point of care decision support system that satisfies this requirement. The system helps emergency physician collect data, evaluate exacerbation severity, plan corresponding treatment and retrieve clinical evidence associated with a given treatment plan. It was developed using ontology-driven and multi-agent methodologies and implemented with open source software. The system is accessible on tablet and desktop computers and smartphones, and it interacts with other hospital information systems. It was successfully verified in a simulated clinical setting and now it is undergoing testing in a teaching hospital.
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