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Recording COVID-19 consultations: review of symptoms, risk factors, and proposed SNOMED CT terms
- Source :
- BJGP Open, Vol 4, Iss 4 (2020)
- Publication Year :
- 2020
- Publisher :
- Royal College of General Practitioners, 2020.
-
Abstract
- Background: There is an urgent need for epidemiological research in primary care to develop risk assessment processes for patients presenting with COVID-19, but lack of a standardised approach to data collection is a significant barrier to implementation. Aim: To collate a list of relevant symptoms, assessment items, demographics, and lifestyle and health conditions associated with COVID-19, and match these data items with corresponding SNOMED CT clinical terms to support the development and implementation of consultation templates. Design & setting: Published and preprint literature for systematic reviews, meta-analyses, and clinical guidelines describing the symptoms, assessment items, demographics, and/or lifestyle and health conditions associated with COVID-19 and its complications were reviewed. Corresponding clinical concepts from SNOMED CT, a widely used structured clinical vocabulary for electronic primary care health records, were identified. Method: Guidelines and published and unpublished reviews (N = 61) were utilised to collate a list of relevant data items for COVID-19 consultations. The NHS Digital SNOMED CT Browser was used to identify concept and descriptive identifiers. Key implementation challenges were conceptualised through a Normalisation Process Theory (NPT) lens. Results: In total, 32 symptoms, eight demographic and lifestyle features, 25 health conditions, and 20 assessment items relevant to COVID-19 were identified, with proposed corresponding SNOMED CT concepts. These data items can be adapted into a consultation template for COVID-19. Key implementation challenges include: 1) engaging with key stakeholders to achieve ’buy in’; and 2) ensuring any template is usable within practice settings. Conclusion: Consultation templates for COVID-19 are needed to standardise data collection, facilitate research and learning, and potentially improve quality of care for COVID-19.
Details
- Language :
- English
- ISSN :
- 23983795
- Volume :
- 4
- Issue :
- 4
- Database :
- Directory of Open Access Journals
- Journal :
- BJGP Open
- Publication Type :
- Academic Journal
- Accession number :
- edsdoj.5490768cbdf48c4b105fee76a8a7dab
- Document Type :
- article
- Full Text :
- https://doi.org/10.3399/bjgpopen20X101125