Changing roles of population-based cancer registries in Australia

Abstract

Abstract.Registries have key roles in cancer incidence, mortality and survival monitoring and in showing disparities across the population. Incidence monitoring began in New South Wales in 1972 and other jurisdictions soon followed. Registry data are used to evaluate outcomes of preventive, screening, treatment and support services. They have shown decreases in cancer incidence following interventions and have been used for workforce and other infrastructure planning. Crude markers of optimal radiotherapy and chemotherapy exist and registry data are used to show shortfalls against these markers. The data are also used to investigate cancer clusters and environmental concerns. Survival data are used to assess service performance and interval cancer data are used in screening accreditation. Registries enable determination of risk of multiple primary cancers. Clinical quality registries are used for clinical quality improvement. Population-based cancer registries and linked administrative data complement clinical registries by providing high-level system-wide data. The USA Commission on Cancer has long used registries for quality assurance and service accreditation. Increasingly population-based registry data in Australia are linked with administrative data on service delivery to assess system performance. Addition of tumour stage and other prognostic indicators is important for these analyses and is facilitated by the roll-out of structured pathology reporting. Data linkage with administrative data, following checks on the quality of these data, enables assessment of patterns of care and other performance indicators for health-system monitoring. Australian cancer registries have evolved and increasingly are contributing to broader information networks for health system management. Traditional rolesCancer registries perform a fundamentally important role in monitoring incidence, mortality and survival by cancer type across the population and show sociodemographic disparities.

A national study of the unmet needs of support persons of haematological cancer survivors in rural and urban areas of Australia

“…Study participants were adult support persons nominated by each haematological cancer survivor and defined as ‘someone who has helped you the most during your cancer journey.’ Cancer survivors were adults aged between 18 and 80 years and diagnosed with an ICD-10 or ICD-0-3 (M) defined haematological cancer (including leukaemia, non-Hodgkin lymphoma, myeloma and other blood cancers) recruited from five Australian state population-based cancer registries. There are eight state and territory cancer registries across Australia that serve a vital role in monitoring cancer incidence, mortality and linkage with patterns of care [ 26 ].…”

Cancer staging at diagnosis data comparisons in South Australia

“…While rates of cancer diagnosis are declining, the number of diagnoses continues to rise and so there is an ongoing need to better understand the population dynamics of cancer over time for health systems. Cancer registries in Australia have been collecting data on the incidence and mortality of invasive cancer since as early as 1972, providing highly valuable data to inform health service planning, prevention policy, the evaluation of interventions and for research purposes 2 . Despite the value presented in population based cancer registries 3,4 , there is a clear need to expand them to include stage at diagnosis 5 .…”

Comparison of cause of death between Australian and New Zealand Dialysis and Transplant Registry and the Australian National Death Index

“…Registries provide a valuable source of data for epidemiologic research and help inform policy decisions on resource allocation and health service provision. [1][2][3] However, depending on how data are collected, from whom, for what purpose, and the coding and classification systems used, it is possible that the same variable, such as cause of death, from separate datasets may contain differing information for the same population. It is therefore possible that disparate or even contradictory conclusions may be drawn about the same population depending on the data source used in an analysis.…”