COVID-19 Surveillance in a Primary Care Sentinel Network: In-Pandemic Development of an Application Ontology (Preprint)

التفاصيل البيبلوغرافية
العنوان: COVID-19 Surveillance in a Primary Care Sentinel Network: In-Pandemic Development of an Application Ontology (Preprint)
المؤلفون: Cecilia Okusi, Harshana Liyanage, Filipa Ferreira, John H. H. Williams, Jill P. Pell, Frances S. Mair, Simon de Lusignan, Nick D. Jones, Oscar Tamburis, Vaishnavi Parimalanathan, Tom Fahey, Trisha Greenhalgh, Jorgen Bauwens, Rachel Byford, Dai Evans, Fd Richard Hobbs, Dylan McGagh, Julian Sherlock, Manasa Tripathy, Bhautesh Dinesh Jani
بيانات النشر: JMIR Publications Inc., 2020.
سنة النشر: 2020
مصطلحات موضوعية: medicine.medical_specialty, Knowledge management, 020205 medical informatics, Computer science, business.industry, Public health, Dashboard (business), MEDLINE, 02 engineering and technology, Ontology (information science), Health informatics, 03 medical and health sciences, 0302 clinical medicine, Informatics, 0202 electrical engineering, electronic engineering, information engineering, medicine, Use case, 030212 general & internal medicine, business, computer, Delphi, computer.programming_language
الوصف: BACKGROUND Creating an ontology for COVID-19 surveillance should help ensure transparency and consistency. Ontologies formalize conceptualizations at either the domain or application level. Application ontologies cross domains and are specified through testable use cases. Our use case was an extension of the role of the Oxford Royal College of General Practitioners (RCGP) Research and Surveillance Centre (RSC) to monitor the current pandemic and become an in-pandemic research platform. OBJECTIVE This study aimed to develop an application ontology for COVID-19 that can be deployed across the various use-case domains of the RCGP RSC research and surveillance activities. METHODS We described our domain-specific use case. The actor was the RCGP RSC sentinel network, the system was the course of the COVID-19 pandemic, and the outcomes were the spread and effect of mitigation measures. We used our established 3-step method to develop the ontology, separating ontological concept development from code mapping and data extract validation. We developed a coding system–independent COVID-19 case identification algorithm. As there were no gold-standard pandemic surveillance ontologies, we conducted a rapid Delphi consensus exercise through the International Medical Informatics Association Primary Health Care Informatics working group and extended networks. RESULTS Our use-case domains included primary care, public health, virology, clinical research, and clinical informatics. Our ontology supported (1) case identification, microbiological sampling, and health outcomes at an individual practice and at the national level; (2) feedback through a dashboard; (3) a national observatory; (4) regular updates for Public Health England; and (5) transformation of a sentinel network into a trial platform. We have identified a total of 19,115 people with a definite COVID-19 status, 5226 probable cases, and 74,293 people with possible COVID-19, within the RCGP RSC network (N=5,370,225). CONCLUSIONS The underpinning structure of our ontological approach has coped with multiple clinical coding challenges. At a time when there is uncertainty about international comparisons, clarity about the basis on which case definitions and outcomes are made from routine data is essential.
URL الوصول: https://explore.openaire.eu/search/publication?articleId=doi_________::eda79d65f37a4314b4780d1caad160d7
https://doi.org/10.2196/preprints.21434
حقوق: OPEN
رقم الأكسشن: edsair.doi...........eda79d65f37a4314b4780d1caad160d7
قاعدة البيانات: OpenAIRE