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BACKGROUND: In Australia, general practitioners (GPs) act as gatekeepers of the healthcare system, so consultation data are essential for policy and resource allocation. However, recent national evidence linking consultation frequency with sociodemographic factors, morbidity and medication use is limited. AIM: To quantify GP consultation frequencyamong 'regular' patients' attending Australian general practices, and explore associated sociodemographic and clinical factors. DESIGN & SETTING: Cross-sectional study with adult 'regular' patients (18+years; 3+visits in two consecutive years) who attended an Australian general practice in 2021 (MedicineInsight database). METHOD: We performed multilevel zero-truncated negative binominal models to explore the association between the number of consultations with patient's sociodemographic characteristics, morbidity and medications. RESULTS: In 2021, 1 302 932 (76%) people were 'regular' attenders to their practice, contributing 10 806 418 consultations. The median number of consultations was 6 (IQR:3,11), with variations by sex, age group and the presence of health conditions. The model showed that being female, older, living in more disadvantaged areas, having chronic, recurrent, or acute conditions, and being prescribed medications were all associated with higher consultation rates, after adjusting for other covariates. The highest relative consultation rates were observed among people aged 75+years (IRR 2.54, 95% CI 2.48;2.61) and those with a diagnosis of chronic pain (IRR 1.82, 95% CI 1.79;1.85) or depression/anxiety (IRR 1.67, 95% CI 1.65;1.69). CONCLUSION: GP consultation frequency was strongly influenced by age, sex, disadvantage and morbidity, with comparatively lower attendance among younger men despite recorded health conditions. These findings highlight potential missed opportunities for monitoring, prevention and early management.

More information Original publication

DOI

10.3399/BJGPO.2026.0052

Type

Journal article

Publication Date

2026-05-14T00:00:00+00:00

Keywords

Comorbidity, Family medicine, Large database research