Toward an Ontology of Collaborative Learning Healthcaresystems

Objective:To establish a basis for a domain ontology - a formal, explicit specificationof a shared conceptualization - of collaborative learning healthcare systems (CLHSs)in order to facilitate measurement, explanation, and improvement.Methods:We adapted the“Methontology”approach to begin building an ontologyof CLHSs. We specified the purpose of an ontology, acquired domain knowledge vialiterature review, conceptualized a common framework of CLHSs using a groundedapproach, refined these concepts based on expert panel input, and illustrated con-cept application via four cases.Results:The set of concepts identified as important to include in an ontologyincludes goals, values, structure, actors, environment, and products. To establish thisset of concepts, we gathered input from content experts in two ways. First, expertpanel methods were used to elicit feedback on these concepts and to test the elicita-tion of terms for the vocabulary of the Values concept. Second, from these discus-sions we developed a mapping exercise to test the intuitiveness of the concepts,requesting that network leaders from four CLHSs complete a mapping exercise toassociate characteristics of their networks with the high-level concepts, building thevocabulary for each concept in a grounded fashion. We also solicited feedback fromthese participants on the experience of completing the mapping exercise, finding thatthe exercise is acceptable and could aid in CLHS development and collaboration.Respondents identified opportunities to improve the operational definitions of eachconcept to ensure that corresponding vocabularies are distinct and non-overlapping.Discussion:Our results provide a foundation for developing a formal, explicit sharedconceptualization of CLHSs. Once developed, such a tool can be useful for measure-ment, explanation, and improvement. Further work, including alignment to a top-levelontology, expanding the vocabulary, and defining relations between vocabulary isrequired to formally build out an ontology for these uses

Seizure Forecasting from Idea to Reality. Outcomes of the My Seizure Gauge Epilepsy Innovation Institute Workshop

International audienc

Seizure Forecasting from Idea to Reality. Outcomes of the My Seizure Gauge Epilepsy Innovation Institute Workshop

International audienc

Reducing Placebo Exposure In Trials

The randomized controlled trial is the unequivocal gold standard for demonstrating clinical efficacy and safety of investigational therapies. Recently there have been concerns raised about prolonged exposure to placebo and ineffective therapy during the course of an add-on regulatory trial for new antiepileptic drug approval (typically ∼6 months in duration), due to the potential risks of continued uncontrolled epilepsy for that period. The first meeting of the Research Roundtable in Epilepsy on May 19-20, 2016, focused on Reducing placebo exposure in epilepsy clinical trials, with a goal of considering new designs for epilepsy regulatory trials that may be added to the overall development plan to make it, as a whole, safer for participants while still providing rigorous evidence of effect. This topic was motivated in part by data from a meta-analysis showing a 3-to 5-fold increased rate of sudden unexpected death in epilepsy in participants randomized to placebo or ineffective doses of new antiepileptic drugs. The meeting agenda included rationale and discussion of different trial designs, including active-control add-on trials, placebo add-on to background therapy with adjustment, time to event designs, adaptive designs, platform trials with pooled placebo control, a pharmacokinetic/pharmacodynamic approach to reducing placebo exposure, and shorter trials when drug tolerance has been ruled out. The merits and limitations of each design were discussed and are reviewed here

A feasibility assessment of functioning and quality-of-life patient-reported outcome measures in adult epilepsy clinics: A systematic review

© 2019 Elsevier Inc. Objective: The objective of the study was to identify functioning and quality-of-life (QOL) patient-reported outcome measurements (PROMs) feasible for use in the waiting room of adult epilepsy clinics. Material and methods: We searched PubMed and Web of Science for articles on in English, Spanish, Portuguese, Italian, and French published by the end of February 15th, 2019. We screened retrieved titles and abstracts looking for publications that reported the use of PROMs to measure functioning and QOL in epilepsy. The authors, clinical experts, and patient advocates from the Epilepsy Foundation of America conceptualized a set of desirable feasibility attributes for PROMs implementation in the waiting room of adult epilepsy clinics. These attributes included brief time for completion (i.e., ≤ 3 min), free cost, coverage of four minimum QOL domains and respective facets, and good evidence of psychometric properties. We defined QOL domains according to the World Health Organization\u27s classification and created psychometric appraisal criteria based on the Food and Drug Administration\u27s (FDA) Guidance. Results: Eighteen candidate instruments were identified and compared with respect to desirable attributes for use in adult epilepsy clinics. We found that the Quality-of-life in epilepsy (QOLIE)-10 and Patient-Reported Outcome Measurement Information System-10 (PROMIS-10) were the most feasible PROMs for implementation in adult epilepsy clinics based on our criteria. The QOLIE-10 and PROMIS-10 still lack ideal evidence of responsiveness in people with epilepsy. Conclusion: This is the first systematic review that aimed to assess feasibility properties of available functioning and QOL PROMs. The QOLIE-10 and PROMIS-10 are potentially feasible instruments for implementation in the waiting room of adult epilepsy clinics. Further studies assessing the responsiveness of these PROMs are needed and will contribute to the selection of the most appropriate instrument for longitudinal use in adult epilepsy clinical practice

Toward an Ontology of Collaborative Learning Healthcaresystems

Objective:To establish a basis for a domain ontology - a formal, explicit specificationof a shared conceptualization - of collaborative learning healthcare systems (CLHSs)in order to facilitate measurement, explanation, and improvement.Methods:We adapted the“Methontology”approach to begin building an ontologyof CLHSs. We specified the purpose of an ontology, acquired domain knowledge vialiterature review, conceptualized a common framework of CLHSs using a groundedapproach, refined these concepts based on expert panel input, and illustrated con-cept application via four cases.Results:The set of concepts identified as important to include in an ontologyincludes goals, values, structure, actors, environment, and products. To establish thisset of concepts, we gathered input from content experts in two ways. First, expertpanel methods were used to elicit feedback on these concepts and to test the elicita-tion of terms for the vocabulary of the Values concept. Second, from these discus-sions we developed a mapping exercise to test the intuitiveness of the concepts,requesting that network leaders from four CLHSs complete a mapping exercise toassociate characteristics of their networks with the high-level concepts, building thevocabulary for each concept in a grounded fashion. We also solicited feedback fromthese participants on the experience of completing the mapping exercise, finding thatthe exercise is acceptable and could aid in CLHS development and collaboration.Respondents identified opportunities to improve the operational definitions of eachconcept to ensure that corresponding vocabularies are distinct and non-overlapping.Discussion:Our results provide a foundation for developing a formal, explicit sharedconceptualization of CLHSs. Once developed, such a tool can be useful for measure-ment, explanation, and improvement. Further work, including alignment to a top-levelontology, expanding the vocabulary, and defining relations between vocabulary isrequired to formally build out an ontology for these uses

Toward an Ontology of Collaborative Learning Healthcaresystems

Objective:To establish a basis for a domain ontology - a formal, explicit specificationof a shared conceptualization - of collaborative learning healthcare systems (CLHSs)in order to facilitate measurement, explanation, and improvement.Methods:We adapted the“Methontology”approach to begin building an ontologyof CLHSs. We specified the purpose of an ontology, acquired domain knowledge vialiterature review, conceptualized a common framework of CLHSs using a groundedapproach, refined these concepts based on expert panel input, and illustrated con-cept application via four cases.Results:The set of concepts identified as important to include in an ontologyincludes goals, values, structure, actors, environment, and products. To establish thisset of concepts, we gathered input from content experts in two ways. First, expertpanel methods were used to elicit feedback on these concepts and to test the elicita-tion of terms for the vocabulary of the Values concept. Second, from these discus-sions we developed a mapping exercise to test the intuitiveness of the concepts,requesting that network leaders from four CLHSs complete a mapping exercise toassociate characteristics of their networks with the high-level concepts, building thevocabulary for each concept in a grounded fashion. We also solicited feedback fromthese participants on the experience of completing the mapping exercise, finding thatthe exercise is acceptable and could aid in CLHS development and collaboration.Respondents identified opportunities to improve the operational definitions of eachconcept to ensure that corresponding vocabularies are distinct and non-overlapping.Discussion:Our results provide a foundation for developing a formal, explicit sharedconceptualization of CLHSs. Once developed, such a tool can be useful for measure-ment, explanation, and improvement. Further work, including alignment to a top-levelontology, expanding the vocabulary, and defining relations between vocabulary isrequired to formally build out an ontology for these uses