ArticleAMIA ... Annual Symposium proceedings. AMIA Symposium2012
OPIC: Ontology-driven Patient Information Capturing system for epilepsy.
Article in AMIA ... Annual Symposium proceedings. AMIA Symposium, 2012. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 15 papers.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
15 citing papers in PubMed.
- Whole-cycle management of women with epilepsy of child-bearing age: ontology construction and application.BMC medical informatics and decision making · 2024Article
- Ontology-based feature engineering in machine learning workflows for heterogeneous epilepsy patient records.Scientific reports · 2022Article
- A multimodal clinical data resource for personalized risk assessment of sudden unexpected death in epilepsy.Frontiers in big data · 2022Article
- A Bespoke Electronic Health Record for Epilepsy Care (EpiToMe): Development and Qualitative Evaluation.Journal of medical Internet research · 2021Article
- Big data in status epilepticus.Epilepsy & behavior : E&B · 2019Review
- Facilitating Cohort Discovery by Enhancing Ontology Exploration, Query Management and Query Sharing for Large Clinical Data Repositories.AMIA ... Annual Symposium proceedings. AMIA Symposium · 2017Article
- ODaCCI: Ontology-guided Data Curation for Multisite Clinical Research Data Integration in the NINDS Center for SUDEP Research.AMIA ... Annual Symposium proceedings. AMIA Symposium · 2016Article
- NHash: Randomized N-Gram Hashing for Distributed Generation of Validatable Unique Study Identifiers in Multicenter Research.JMIR medical informatics · 2015Article
- Article
- An integrated, ontology-driven approach to constructing observational databases for research.Journal of biomedical informatics · 2015Article
- A scalable neuroinformatics data flow for electrophysiological signals using MapReduce.Frontiers in neuroinformatics · 2015Article
- MEDCIS: Multi-Modality Epilepsy Data Capture and Integration System.AMIA ... Annual Symposium proceedings. AMIA Symposium · 2014Article
- Epilepsy informatics and an ontology-driven infrastructure for large database research and patient care in epilepsy.Epilepsia · 2013Review
- Electrophysiological signal analysis and visualization using Cloudwave for epilepsy clinical research.Studies in health technology and informatics · 2013Article
- Epilepsy and seizure ontology: towards an epilepsy informatics infrastructure for clinical research and patient care.Journal of the American Medical Informatics Association : JAMIAArticle
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
7 authors.
Funding
Abstract
The widespread use of paper or document-based forms for capturing patient information in various clinical settings, for example in epilepsy centers, is a critical barrier for large-scale, multi-center research studies that require interoperable, consistent, and error-free data collection. This challenge can be addressed by a web-accessible and flexible patient data capture system that is supported by a common terminological system to facilitate data re-usability, sharing, and integration. We present OPIC, an Ontology-driven Patient Information Capture (OPIC) system that uses a domain-specific epilepsy and seizure ontology (EpSO) to (1) support structured entry of multi-modal epilepsy data, (2) proactively ensure quality of data through use of ontology terms in drop-down menus, and (3) identify and index clinically relevant ontology terms in free-text fields to improve accuracy of subsequent analytical queries (e.g. cohort identification). EpSO, modeled using the Web Ontology Language (OWL), conforms to the recommendations of the International League Against Epilepsy (ILAE) classification and terminological commission. OPIC has been developed using agile software engineering methodology for rapid development cycles in close collaboration with domain expert and end users. We report the result from the initial deployment of OPIC at the University Hospitals Case Medical Center (UH CMC) epilepsy monitoring unit (EMU) as part of the NIH-funded project on Sudden Unexpected Death in Epilepsy (SUDEP). Preliminary user evaluation shows that OPIC has achieved its design objectives to be an intuitive patient information capturing system that also reduces the potential for data entry errors and variability in use of epilepsy terms.
Indexed as
Identifiers
23304354PMC3540561What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.