Abstract
Objectives: To identify and compare respiratory illness presentation rates and service utilisation to primary care in Aotearoa, New Zealand (NZ) before, through and after the COVID-19 pandemic.
Design: A natural language processing (NLP) software interference algorithm was used to interrogate quantitative and qualitative cross-sectional and retrospective cohort data from clinical consultation notes.
Setting: Primary care presentations across Aotearoa, NZ, encompassing both urban and rural areas.
Participants: Electronic records were obtained from general practice interactions from 2018 to end of 2023. Participants consisted of 37 consenting practices from eight districts.
Results: A total of 10 421 399 unique medical interactions were processed by the NLP software, of which 15.1% (1 573 631) were related to a respiratory issue. This ranged from 14.2% and 13.7% in 2018 and 2019 to a peak of 25.2% in 2022. Expected patterns of seasonal variation were observed prepandemic with small variance in mean rates. Due to the COVID-19 pandemic, border closures and then SARS-CoV-2 arrival, there was significant disruption to previous seasonal patterns across all respiratory illness presentations in primary care. Patterns vary markedly across different respiratory groups. While the degree of variance has reduced, there continues to be marked disruption of pre-COVID patterns.
Conclusions: Primary care respiratory presentations in NZ continue to experience persistent variation from the pre-COVID typical seasonal presentation patterns. There is significant change in presentations, likely due to changing disease prevalence, but also to changing patient and provider behaviour. These results have implications for primary care workload management and public health policy.