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Creating a Research-Ready Data Asset version of primary care data for Wales and investigating the impact of COVID-19 on utilisation of primary care services

Hoda Abbasizanjani Orcid Logo, Stuart Bedston, Ashley Akbari Orcid Logo

PLOS One, Volume: 20, Issue: 12, Start page: e0338652

Swansea University Authors: Hoda Abbasizanjani Orcid Logo, Stuart Bedston, Ashley Akbari Orcid Logo

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DOI (Published version): 10.1371/journal.pone.0338652

Abstract

Objectives: We developed an efficient Research-Ready Data Asset (RRDA) for the Welsh Longitudinal General Practice (WLGP) data within the Secure Anonymised Information Linkage Databank to standardise curation, enhance reproducibility, and facilitate research on primary care trends. Using this, we in...

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Published in: PLOS One
ISSN: 1932-6203
Published: Public Library of Science (PLoS) 2025
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spelling 2026-01-12T15:40:05.8534350 v2 71128 2025-12-11 Creating a Research-Ready Data Asset version of primary care data for Wales and investigating the impact of COVID-19 on utilisation of primary care services 93dd7e747f3118a99566c68592a3ddcc 0000-0002-9575-4758 Hoda Abbasizanjani Hoda Abbasizanjani true false c79d07eaba5c9515c0df82b372b76a41 Stuart Bedston Stuart Bedston true false aa1b025ec0243f708bb5eb0a93d6fb52 0000-0003-0814-0801 Ashley Akbari Ashley Akbari true false 2025-12-11 MEDS Objectives: We developed an efficient Research-Ready Data Asset (RRDA) for the Welsh Longitudinal General Practice (WLGP) data within the Secure Anonymised Information Linkage Databank to standardise curation, enhance reproducibility, and facilitate research on primary care trends. Using this, we investigated primary care activity trends during and after the COVID-19 pandemic. Methods: The RRDA involves cleaning, curation using GP-registration history, and transforming data into a structured, normalised format to support efficient large-scale queries. A comprehensive clinical code look-up was developed, incorporating official, local, and supplementary categories to enhance event classification. To enable patient-practice interaction analysis, a four-layer approach was developed to capture healthcare providers, access mode, interaction type, and event details. We assessed RRDA coverage, defined as the proportion of residents with shared primary care records, stratified by demographic and geographic factors, using longitudinal binomial Generalised Additive Mixed Models (GAMMs). We categorised GP events into key activity types and summarised averaged daily rates per month per 100,000 people (2000–2024), with trends analysed using negative binomial GAMMs. Results: Curating 4.6 billion records for 5.1 million people (1990–2024) revealed significant improvements in data quality and completeness over time, with data retention increased from 40% to 94%, and patient inclusion from 43% to 98%. Use of SNOMED-CT and local codes increased after Read-V2 discontinuation in 2018, while invalid codes declined—reflecting evolving coding practices and improved data quality. WLGP RRDA coverage rose from 35% in 1990 to 86% in 2024, with regional variation but modest demographic differences. From 2000 to 2024, consultation rates rose by 1.9 times, with post-COVID-19 pandemic levels 8% above 2019. Prescription-only activity doubled with little variation associated with the pandemic. Vaccination rates spiked during the pandemic, and remain 1.8 times above pre-pandemic levels. Other less frequent activities were significantly disrupted during the COVID-19 pandemic but recovered to 2019 levels. Conclusions: The WLGP RRDA improves the usability of primary care data, supporting timely, scalable analysis of healthcare delivery and system-level trends. Journal Article PLOS One 20 12 e0338652 Public Library of Science (PLoS) 1932-6203 10 12 2025 2025-12-10 10.1371/journal.pone.0338652 COLLEGE NANME Medical School COLLEGE CODE MEDS Swansea University SU Library paid the OA fee (TA Institutional Deal) This work was supported by the ADR Wales programme of work. ADR Wales, part of the ADR UK investment, unites research expertise from Swansea University Medical School and WISERD (Wales Institute of Social and Economic Research and Data) at Cardiff University with analysts from Welsh Government. ADR UK is funded by the Economic and Social Research Council (ESRC), part of UK Research and Innovation. This research was supported by ESRC funding, including Administrative Data Research Wales (ES/W012227/1). 2026-01-12T15:40:05.8534350 2025-12-11T08:51:39.3093380 Faculty of Medicine, Health and Life Sciences Swansea University Medical School - Health Data Science Hoda Abbasizanjani 0000-0002-9575-4758 1 Stuart Bedston 2 Ashley Akbari 0000-0003-0814-0801 3 71128__35964__08c29993531545afb192847bc8c6b208.pdf 71128.VOR.pdf 2026-01-12T15:38:15.0123631 Output 3084643 application/pdf Version of Record true © 2025 Abbasizanjani et al. This is an open access article distributed under the terms of the Creative Commons Attribution License. true eng http://creativecommons.org/licenses/by/4.0/
title Creating a Research-Ready Data Asset version of primary care data for Wales and investigating the impact of COVID-19 on utilisation of primary care services
spellingShingle Creating a Research-Ready Data Asset version of primary care data for Wales and investigating the impact of COVID-19 on utilisation of primary care services
Hoda Abbasizanjani
Stuart Bedston
Ashley Akbari
title_short Creating a Research-Ready Data Asset version of primary care data for Wales and investigating the impact of COVID-19 on utilisation of primary care services
title_full Creating a Research-Ready Data Asset version of primary care data for Wales and investigating the impact of COVID-19 on utilisation of primary care services
title_fullStr Creating a Research-Ready Data Asset version of primary care data for Wales and investigating the impact of COVID-19 on utilisation of primary care services
title_full_unstemmed Creating a Research-Ready Data Asset version of primary care data for Wales and investigating the impact of COVID-19 on utilisation of primary care services
title_sort Creating a Research-Ready Data Asset version of primary care data for Wales and investigating the impact of COVID-19 on utilisation of primary care services
author_id_str_mv 93dd7e747f3118a99566c68592a3ddcc
c79d07eaba5c9515c0df82b372b76a41
aa1b025ec0243f708bb5eb0a93d6fb52
author_id_fullname_str_mv 93dd7e747f3118a99566c68592a3ddcc_***_Hoda Abbasizanjani
c79d07eaba5c9515c0df82b372b76a41_***_Stuart Bedston
aa1b025ec0243f708bb5eb0a93d6fb52_***_Ashley Akbari
author Hoda Abbasizanjani
Stuart Bedston
Ashley Akbari
author2 Hoda Abbasizanjani
Stuart Bedston
Ashley Akbari
format Journal article
container_title PLOS One
container_volume 20
container_issue 12
container_start_page e0338652
publishDate 2025
institution Swansea University
issn 1932-6203
doi_str_mv 10.1371/journal.pone.0338652
publisher Public Library of Science (PLoS)
college_str Faculty of Medicine, Health and Life Sciences
hierarchytype
hierarchy_top_id facultyofmedicinehealthandlifesciences
hierarchy_top_title Faculty of Medicine, Health and Life Sciences
hierarchy_parent_id facultyofmedicinehealthandlifesciences
hierarchy_parent_title Faculty of Medicine, Health and Life Sciences
department_str Swansea University Medical School - Health Data Science{{{_:::_}}}Faculty of Medicine, Health and Life Sciences{{{_:::_}}}Swansea University Medical School - Health Data Science
document_store_str 1
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description Objectives: We developed an efficient Research-Ready Data Asset (RRDA) for the Welsh Longitudinal General Practice (WLGP) data within the Secure Anonymised Information Linkage Databank to standardise curation, enhance reproducibility, and facilitate research on primary care trends. Using this, we investigated primary care activity trends during and after the COVID-19 pandemic. Methods: The RRDA involves cleaning, curation using GP-registration history, and transforming data into a structured, normalised format to support efficient large-scale queries. A comprehensive clinical code look-up was developed, incorporating official, local, and supplementary categories to enhance event classification. To enable patient-practice interaction analysis, a four-layer approach was developed to capture healthcare providers, access mode, interaction type, and event details. We assessed RRDA coverage, defined as the proportion of residents with shared primary care records, stratified by demographic and geographic factors, using longitudinal binomial Generalised Additive Mixed Models (GAMMs). We categorised GP events into key activity types and summarised averaged daily rates per month per 100,000 people (2000–2024), with trends analysed using negative binomial GAMMs. Results: Curating 4.6 billion records for 5.1 million people (1990–2024) revealed significant improvements in data quality and completeness over time, with data retention increased from 40% to 94%, and patient inclusion from 43% to 98%. Use of SNOMED-CT and local codes increased after Read-V2 discontinuation in 2018, while invalid codes declined—reflecting evolving coding practices and improved data quality. WLGP RRDA coverage rose from 35% in 1990 to 86% in 2024, with regional variation but modest demographic differences. From 2000 to 2024, consultation rates rose by 1.9 times, with post-COVID-19 pandemic levels 8% above 2019. Prescription-only activity doubled with little variation associated with the pandemic. Vaccination rates spiked during the pandemic, and remain 1.8 times above pre-pandemic levels. Other less frequent activities were significantly disrupted during the COVID-19 pandemic but recovered to 2019 levels. Conclusions: The WLGP RRDA improves the usability of primary care data, supporting timely, scalable analysis of healthcare delivery and system-level trends.
published_date 2025-12-10T05:34:39Z
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