Objectives To describe patterns of hospital readmission for asthma in South Australia from 1989 to 1996, in relation to implementation of the National Asthma Campaign. Design and setting A comparison of hospital admissions in South Australia of patients aged between one year and 49 years for three conditions: asthma (or respiratory failure with asthma as an underlying condition) and two control conditions — diabetes and epilepsy. Individuals were identified by Medicare number and date of birth. Outcome measures Hospital readmission within 28 days and within one year. Results Overall, by 1996, there was a statistically significant decline in the risk of readmission for asthma within 28 days of 18% and within one year of 17% compared with 1989 readmission rates. There were no reductions in the risk of readmission for diabetes or epilepsy, suggesting that the decline in risk of readmission for asthma was greater than the underlying effects of general changes in hospital casemix. Conclusions The decline in risk of readmission may reflect changes in asthma severity or improved management practices. However, hospital readmission rates still remain high, and to further reduce readmissions for asthma there is a need to identify factors related to presentation for asthma at accident and emergency departments.

Objective: To use linked NSW Cancer Registry and hospital lung cancer (LC) data for raising discussion points on how to improve outcomes. Design: Historical cohort – cases diagnosed in 2003-2007. Setting: New South Wales, Australia Outcome Measures: Relative odds (OR) of localised disease and resection of non-small cases (NSCLC) using multiple logistic regression. Comparisons of risk of NSCLC death using competing risk regression. Findings: (1) Older patients have fewer resections of localised NSCLC [adjusted OR 95% CLs; 80+Vs <60 years; 0.20 (0.14, 0.28)]. Cases with co-morbidity have fewer resections [adjusted OR, 0.74 (0.61, 0.90)] and have more conservative resections. Question: Is there the best balance between resection and avoiding surgery to accommodate frailty and co-morbidity? (2) Compared with public patients, the health insured: have higher odds of localised LC [adjusted OR, 1.23 (1.12, 1.35] and resection for localised NSCLC [adjusted OR, 2.08 (1.70, 2.54)]; are more likely to have lobectomies than wedge/segmental resections (p<0.001); and have a lower risk of LC death [adjusted SHR, 0.89 (0.85, 0.93)]. Question: Are there opportunities for improving publicpatient outcomes? (3) Patients born in non-English speaking countries have lower odds of localised disease [adjusted OR, 0.88 (0.79, 0.99)]. – Question: Could this difference be decreased by reducing cultural and language barriers? (4) Cancers of pulmonary lobes rather than the main bronchus pose lower risks of LC death. Question: Could outcomes for main bronchus cancers be improved by up-skilling or referral to higher-volume centres? (5) Greater extent of disease is strongly predictive of case fatality – Question: Could LC deaths be reduced by earlier treatment? (6) Use of lobectomies varies – Question: Could survival be increased through greater use of lobectomies for localised NSCLC? Conclusions: Linked cancer registry and hospital data can increase system-wide understanding of local health-service delivery and prompt discussion points on how to improve outcomes. Abbreviations: APDC – Australian Patient Data Collection; CHeReL – Centre for Health Record Linkage; EOD – Extent of Disease; LC – Lung Cancer; NSCLC – Non-Small Cell Cancers; NSWCR – New South Wales Cancer Registry; OR – Relative Odds; SEIFA – Socio-Economic Index for Areas; SES – Socio- Economic Status.