Your browser doesn't support javascript.
COVID-19 Surveillance in a Primary Care Sentinel Network: In-Pandemic Development of an Application Ontology.
de Lusignan, Simon; Liyanage, Harshana; McGagh, Dylan; Jani, Bhautesh Dinesh; Bauwens, Jorgen; Byford, Rachel; Evans, Dai; Fahey, Tom; Greenhalgh, Trisha; Jones, Nicholas; Mair, Frances S; Okusi, Cecilia; Parimalanathan, Vaishnavi; Pell, Jill P; Sherlock, Julian; Tamburis, Oscar; Tripathy, Manasa; Ferreira, Filipa; Williams, John; Hobbs, F D Richard.
  • de Lusignan S; Nuffield Department of Primary Care Health Sciences, University of Oxford, Oxford, United Kingdom.
  • Liyanage H; Nuffield Department of Primary Care Health Sciences, University of Oxford, Oxford, United Kingdom.
  • McGagh D; Nuffield Department of Primary Care Health Sciences, University of Oxford, Oxford, United Kingdom.
  • Jani BD; General Practice and Primary Care, Institute of Health and Wellbeing, University of Glasgow, Glasgow, United Kingdom.
  • Bauwens J; University Children's Hospital Basel, University of Basel, Basel, Switzerland.
  • Byford R; Nuffield Department of Primary Care Health Sciences, University of Oxford, Oxford, United Kingdom.
  • Evans D; PRIMIS, University of Nottingham, Nottingham, United Kingdom.
  • Fahey T; Department of General Practice, Royal College of Surgeons, Ireland, Dublin, Ireland.
  • Greenhalgh T; Nuffield Department of Primary Care Health Sciences, University of Oxford, Oxford, United Kingdom.
  • Jones N; Nuffield Department of Primary Care Health Sciences, University of Oxford, Oxford, United Kingdom.
  • Mair FS; General Practice and Primary Care, Institute of Health and Wellbeing, University of Glasgow, Glasgow, United Kingdom.
  • Okusi C; Nuffield Department of Primary Care Health Sciences, University of Oxford, Oxford, United Kingdom.
  • Parimalanathan V; Nuffield Department of Primary Care Health Sciences, University of Oxford, Oxford, United Kingdom.
  • Pell JP; General Practice and Primary Care, Institute of Health and Wellbeing, University of Glasgow, Glasgow, United Kingdom.
  • Sherlock J; Nuffield Department of Primary Care Health Sciences, University of Oxford, Oxford, United Kingdom.
  • Tamburis O; Department of Veterinary Medicine and Animal Productions, University of Naples Federico II, Naples, Italy.
  • Tripathy M; Nuffield Department of Primary Care Health Sciences, University of Oxford, Oxford, United Kingdom.
  • Ferreira F; Nuffield Department of Primary Care Health Sciences, University of Oxford, Oxford, United Kingdom.
  • Williams J; Nuffield Department of Primary Care Health Sciences, University of Oxford, Oxford, United Kingdom.
  • Hobbs FDR; Nuffield Department of Primary Care Health Sciences, University of Oxford, Oxford, United Kingdom.
JMIR Public Health Surveill ; 6(4): e21434, 2020 11 17.
Article in English | MEDLINE | ID: covidwho-976102
ABSTRACT

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.
Subject(s)
Keywords

Full text: Available Collection: International databases Database: MEDLINE Main subject: Primary Health Care / Sentinel Surveillance / Biological Ontologies / COVID-19 Type of study: Observational study / Prognostic study / Randomized controlled trials Limits: Humans Language: English Journal: JMIR Public Health Surveill Year: 2020 Document Type: Article Affiliation country: 21434

Similar

MEDLINE

...
LILACS

LIS


Full text: Available Collection: International databases Database: MEDLINE Main subject: Primary Health Care / Sentinel Surveillance / Biological Ontologies / COVID-19 Type of study: Observational study / Prognostic study / Randomized controlled trials Limits: Humans Language: English Journal: JMIR Public Health Surveill Year: 2020 Document Type: Article Affiliation country: 21434