Systemic sclerosis (SSc) is a disease characterised by significant skin fibrosis and internal organ involvement, leading to high morbidity and mortality. Dermatology involvement in all SSc patient care is gold standard, as outlined in the 2024 British Society of Rheumatology guidelines. Australia has higher rates of SSc than the global average, though exact figures are unknown, with a potential higher prevalence in non-metropolitan areas. Overseas studies show SSc hotspots in rural regions, possibly due to chemical exposures. There is limited knowledge on the care pathways for Australian SSc patients, though multidisciplinary care has been shown to improve patient outcomes and satisfaction overseas. Dermatology care is often under-resourced, particularly in non-metropolitan areas, yet its impact on patient care has not been well studied.

Large databases of routinely collected data can provide insights into population-level trends by linking information from multiple healthcare sources. The primary data source will be the National Health Data Hub (NHDH), a linked, anonymous dataset maintained by the AIHW. SSc cases will be identified using algorithms that link hospital, PBS, and MBS data (e.g., rheumatology/dermatology MBS codes, SSc-specific ICD-10 codes, and PBS authority numbers). These cases will be mapped to the Australian Standard Geographical Classification Remoteness Area Score, with socio-economic status linked via the Index of Relative Socio-Economic Disadvantage. Dermatologist density will be calculated using the AHPRA National Health Workforce Dataset and the ACD opt-in dermatologist database. These data will be used to assess dermatology involvement in SSc care and its frequency.

By leveraging big data, we will determine the prevalence and geographic distribution of Australian SSc patients, the proportion receiving dermatology care, and factors such as geography, socio-economic status, and workforce availability that influence care. This information will inform care planning, funding allocation, advocacy, and may help identify vulnerable populations.