Patterns of patient interactions with primary care in Wales: the impact of the COVID-19 pandemic

ObjectivesWe aim to investigate changes in primary care activities and patient-practice interactions (e.g., face-to-face vs. remote consultations) in Wales during and after the COVID-19 pandemic, compared to pre-pandemic trends. Additionally, we will examine the impact on equity of access, utilisation, and potential health outcomes across different regions and sociodemographic groups. MethodsThe study utilises population-scale primary care records from the Welsh Longitudinal General Practice (WLGP) data within the SAIL Databank. We conduct a retrospective population study to analyse national trends in patient-practice interactions since 2000. Using the previously developed Research Ready Data Asset for WLGP, which includes mapped clinical codes and associated interaction types, we categorised daily GP events into key activity types. Time-series analysis techniques are applied to evaluate trends over time, assessing whether each activity type has returned to pre-pandemic levels. Seasonal and long-term trends are examined to identify periodic fluctuations and sustained shifts in consultation modes and key primary care activities. ResultsPreliminary findings reveal a sharp decline in all primary care activities except repeat prescriptions during 2020, followed by a gradual recovery toward pre-pandemic levels. However, vaccination rates continued to exceed pre-pandemic levels. We assessed consultation modes (face-to-face, remote, home visits) and key activities such as consultations, prescriptions, test requests and results, referrals, fit-notes, chronic disease monitoring, patient screening, and immunisation. We report baseline characteristics of these interactions stratified by ethnic group, deprivation, and rural/urban characteristics for both pre-pandemic and post-pandemic periods. Using a combination of time-series models, ARIMA and ETS, trained on pre-pandemic trends, we evaluate the difference between observed and forecasted post-pandemic activity to investigate recovery and change in primary care utilisation. ConclusionThe pandemic significantly disrupted healthcare services, altering patient interactions with primary care. Understanding these trends and their implications for healthcare access, utilisation, and outcomes is essential for informing future healthcare policies and ensuring equitable service delivery. These insights will help assess system resilience and guide strategies for preparedness and improvement.

Authors

Institutions

Publication Details

Journal
International Journal for Population Data Science
Published
2025-08-28
DOI
https://doi.org/10.23889/ijpds.v10i4.3065
Primary Topic
Primary Care and Health Outcomes
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Patterns of patient interactions with primary care in Wales: the impact of the COVID-19 pandemic

Ashley Akbari, Stuart Bedston, Hoda Abbasizanjani, Matthew Curds et al.
International Journal for Population Data Science
Primary Care and Health Outcomes
article

Patterns of patient interactions with primary care in Wales: the impact of the COVID-19 pandemic

Ashley Akbari, Stuart Bedston, Hoda Abbasizanjani, Matthew Curds, Lucy Robinson
article en

Abstract

ObjectivesWe aim to investigate changes in primary care activities and patient-practice interactions (e.g., face-to-face vs. remote consultations) in Wales during and after the COVID-19 pandemic, compared to pre-pandemic trends. Additionally, we will examine the impact on equity of access, utilisation, and potential health outcomes across different regions and sociodemographic groups. MethodsThe study utilises population-scale primary care records from the Welsh Longitudinal General Practice (WLGP) data within the SAIL Databank. We conduct a retrospective population study to analyse national trends in patient-practice interactions since 2000. Using the previously developed Research Ready Data Asset for WLGP, which includes mapped clinical codes and associated interaction types, we categorised daily GP events into key activity types. Time-series analysis techniques are applied to evaluate trends over time, assessing whether each activity type has returned to pre-pandemic levels. Seasonal and long-term trends are examined to identify periodic fluctuations and sustained shifts in consultation modes and key primary care activities. ResultsPreliminary findings reveal a sharp decline in all primary care activities except repeat prescriptions during 2020, followed by a gradual recovery toward pre-pandemic levels. However, vaccination rates continued to exceed pre-pandemic levels. We assessed consultation modes (face-to-face, remote, home visits) and key activities such as consultations, prescriptions, test requests and results, referrals, fit-notes, chronic disease monitoring, patient screening, and immunisation. We report baseline characteristics of these interactions stratified by ethnic group, deprivation, and rural/urban characteristics for both pre-pandemic and post-pandemic periods. Using a combination of time-series models, ARIMA and ETS, trained on pre-pandemic trends, we evaluate the difference between observed and forecasted post-pandemic activity to investigate recovery and change in primary care utilisation. ConclusionThe pandemic significantly disrupted healthcare services, altering patient interactions with primary care. Understanding these trends and their implications for healthcare access, utilisation, and outcomes is essential for informing future healthcare policies and ensuring equitable service delivery. These insights will help assess system resilience and guide strategies for preparedness and improvement.

International Journal for Population Data ScienceVol. 10(4)
Welsh Government (GB), Swansea University (GB)
Openalex Percentile: Top 64%
Primary Care and Health Outcomes
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.