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Objectives: To assess whether adding clinical information and written discharge documentation variables improves prediction of paediatric 30-day same-hospital unplanned readmission compared with predictions based on administrative information alone. Methods: A retrospective matched case-control study audited the medical records of patients discharged from a tertiary paediatric hospital in Western Australia (WA) between January 2010 and December 2014. A random selection of 470 patients with unplanned readmissions (out of 3330) were matched to 470 patients without readmissions based on age, sex, and principal diagnosis at the index admission. Prediction utility of three groups of variables (administrative, administrative and clinical, and administrative, clinical and written discharge documentation) were assessed using standard logistic regression and machine learning. Results: Inclusion of written discharge documentation variables significantly improved prediction of readmission compared with models that used only administrative and/or clinical variables in standard logistic regression analysis (χ217 = 29.4, P = 0.03). Highest prediction accuracy was obtained using a gradient boosted tree model (C-statistic = 0.654), followed closely by random forest and elastic net modelling approaches. Variables highlighted as important for prediction included patients' social history (legal custody or patient was under the care of the Department for Child Protection), languages spoken other than English, completeness of nursing admission and discharge planning documentation, and timing of issuing discharge summary. Conclusions: The variables of significant social history, low English language proficiency, incomplete discharge documentation, and delay in issuing the discharge summary add value to prediction models. What is known about the topic?: Despite written discharge documentation playing a critical role in the continuity of care for paediatric patients, limited research has examined its association with, and ability to predict, unplanned hospital readmissions. Machine learning approaches have been applied to various health conditions and demonstrated improved predictive accuracy. However, few published studies have used machine learning to predict paediatric readmissions. What does this paper add?: This paper presents the findings of the first known study in Australia to assess and report that written discharge documentation and clinical information improves unplanned rehospitalisation prediction accuracy in a paediatric cohort compared with administrative data alone. It is also the first known published study to use machine learning for the prediction of paediatric same-hospital unplanned readmission in Australia. The results show improved predictive performance of the machine learning approach compared with standard logistic regression. What are the implications for practitioners?: The identified social and written discharge documentation predictors could be translated into clinical practice through improved discharge planning and processes, to prevent paediatric 30-day all-cause same-hospital unplanned readmission. The predictors identified in this study include significant social history, low English language proficiency, incomplete discharge documentation, and delay in issuing the discharge summary. [ABSTRACT FROM AUTHOR]

Objective: This study assessed the effect of the frequency of general practitioner (GP) visitation in the 12 months before a 21% consumer copayment increase in the Pharmaceutical Benefits Scheme (PBS; January 2005) on the reduction or discontinuation of statin dispensing for tertiary prevention. Methods: The study used routinely collected, whole-population linked PBS, Medicare, mortality and hospital data from Western Australia. From 2004 to 2005, individuals were classified as having discontinued, reduced or continued their use of statins in the first six months of 2005 following the 21% consumer copayment increase on 1 January 2005. The frequency of GP visits was calculated in 2004 from Medicare data. Multivariate logistic regression models were used to determine the association between GP visits and statin use following the copayment increase. Results: In December 2004, there were 22 495 stable statin users for tertiary prevention of prior coronary heart disease, prior stroke or prior coronary artery revascularisation procedure. Following the copayment increase, patients either discontinued (3%), reduced (12%) or continued (85%) their statins. Individuals who visited a GP three or more times in 2004 were 47% less likely to discontinue their statins in 2005 than people attending only once. Subgroup analysis showed the effect was apparent in men, and long-term or new statin users. The frequency of GP visits did not affect the proportion of patients reducing their statin therapy. Conclusions: Patients who visited their GP at least three times per year had a lower risk of ceasing their statins in the year following the copayment increase. GPs can help patients maintain treatment following rises in medicines costs. What is known about the topic?: Following the 21% increase in medication copayment in 2005, individuals discontinued or reduced their statin usage, including for tertiary prevention. What does this paper add?: Patients who visited their GP at least three times per year were less likely to discontinue their statin therapy for tertiary prevention following a large copayment increase. What are the implications for practitioners?: This paper identifies the important role that GPs have in maintaining the continued use of important medications following rises in medicines costs. [ABSTRACT FROM AUTHOR]

Objective: The aim of this study was to explore Western Australian cancer patients' experiences of out-of-pocket expenses (OOPE) during diagnosis and cancer treatment using a phenomenological approach. Methods: Semi-structured interviews were conducted with a purposive convenience sample of 40 Western Australian cancer patients diagnosed with breast, lung, prostate or colorectal cancer. Participants were asked about the impact of their diagnosis, the associated costs and their experience within the health system. Data were analysed using thematic content analysis. Results: Three key themes influencing participant OOPE experiences were identified: (1) personal circumstances; (2) communication with health providers; and (3) coping strategies. Despite Australia's public healthcare system, several participants found the costs affected their financial security and resorted to coping strategies including medication rationing and restrictive household budgeting. The key themes had a complex and interrelated effect on patient OOPE experiences and were used to adapt Carrera et al. 's model of economic consequences of cancer treatment on the patient and patient coping to describe these relationships in a mixed healthcare system. Conclusion: Organised efforts must be implemented to mitigate maladaptive coping strategies being used by cancer patients: (1) health providers should seek informed financial consent from patients before commencing treatment; and (2) financial aid and support schemes for cancer patients should be reviewed to ensure they are delivered equitably. What is known on this topic?: The financial cost of cancer can have significant adverse effects on cancer patients. Although financial transparency is desired by cancer patients, its implementation in practice is not clear. What does this paper add?: This study adapts a conceptual model for the economic consequences of a cancer diagnosis and repurposes it for a mixed public–private health system, providing a framework for understanding downstream consequences of cancer costs and highlighting opportunities for intervention. What are the implications for health practitioners?: Health practitioners need to initiate discussions concerning treatment costs earlier with cancer patients. There are several resources and guides available to assist and facilitate financial transparency. Without urgent attention to the financial consequences of cancer treatment and related expenses, we continue to leave patients at risk of resorting to maladaptive coping strategies, such as medication rationing and restrictive household budgeting. [ABSTRACT FROM AUTHOR]

Objective: The aim of this study was to examine the characteristics and prevalence of all-cause unplanned hospital readmissions at a tertiary paediatric hospital in Western Australia from 2010 to 2014. Methods: A retrospective cohort descriptive study was conducted. Unplanned hospital readmission was identified using both 28- and 30-day measurements from discharge date of an index hospital admission to the subsequent related unplanned admission date. This allowed international comparison. Results: In all, 73 132 patients with 134 314 discharges were identified. During the 5-year period, 4070 discharges (3.03%) and 3330 patients (4.55%) were identified as 30-day unplanned hospital readmissions. There were minimal differences in the rate of readmissions on Days 28, 29 and 30 (0.2%). More than 50% of readmissions were identified as a 5-day readmission. Nearly all readmissions for croup and epiglottitis occurred by Day 5; those for acute bronchiolitis and obstructive sleep apnoea requiring tonsillectomy and/or adenoidectomy occurred by Day 15 and those for acute appendicitis and abdominal and pelvic pain occurred by Day 30. Conclusion: This study highlights the variability in the distribution of time intervals from discharge to readmission among diagnoses, suggesting the commonly used 28- or 30-day readmission measurement requires review. It is crucial to establish an appropriate measurement for specific paediatric conditions related to readmissions for the accurate determination of the prevalence and actual costs associated with readmissions. What is known about this topic?: Unplanned hospital readmissions result in inefficient use of health resources. Australia has used 28 days to measure unplanned readmissions. However, the 30-day measurement is commonly used in the literature. Only five Australian studies were identified with a focus on readmissions associated with specific paediatric health conditions. What does this paper add?: This is the first known study examining paediatric all-cause unplanned same-hospital readmissions in Western Australia. The study used both 28- and 30-day measures from discharge to unplanned readmission to allow international comparison. More than half the unplanned hospital readmissions occurred between Day 0 and Day 5 following discharge from the index admission. Time intervals from discharge date to readmission date varied for diagnosis-specific readmissions of paediatric patients. What are the implications for practitioners?: Targeting the top principal index admission diagnoses identified for paediatric readmissions is critical for improvement in the continuity of discharge care delivery, health resource utilisation and associated costs. Because 52% of unplanned readmissions occurred in the first 5 days, urgent investigation and implementation of prevention strategies are required, especially when the readmission occurs on the date of discharge. [ABSTRACT FROM AUTHOR]

Objective. This study of equity and access characterises admissions for coronary, cerebrovascular and peripheral arterial disease by hospital type (rural, tertiary and non-tertiary metropolitan) in a representative Australian population. Methods. We conducted a descriptive analysis using data linkage of all residents aged 35-84 years hospitalised in Western Australia with a primary diagnosis for an atherothrombotic event in 2007. We compared sociodemographic and clinical features by atherothrombotic territory and hospital type. Results. There were 11 670 index admissions for atherothrombotic disease in 2007 of which 46% were in tertiary hospitals, 41% were in non-tertiary metropolitan hospitals and 13% were in rural hospitals. Coronary heart disease comprised 72% of admissions, followed by cerebrovascular disease (19%) and peripheral arterial disease (9%). Comparisons of socioeconomic disadvantage reveal that for those admitted to rural hospitals, more than one-third were in the most disadvantaged quintile, compared with one-fifth to any metropolitan hospital. Conclusions. Significant differences in demographic characteristics were evident between Western Australian tertiary and non-tertiary hospitals for patients hospitalised for atherothrombotic disease. Notably, the differences among tertiary, non-tertiary metropolitan and rural hospitals were related to socioeconomic disadvantage. This has implications for atherothrombotic healthcare provision and the generalisation of research findings from studies conducted exclusively in the tertiary metropolitan hospitals. What is known about the topic? Equity and access to hospital care for atherothrombotic disease in a geographically diverse population is poorly characterised. National data show that both fatal and non-fatal coronary heart disease and non-fatal stroke hospitalisations increase with remoteness. Fatal in-hospital stroke is greatest in major cities, whereas peripheral arterial disease hospitalisations are greatest in the inner and outer regional areas. What does this paper add? This study demonstrates that around 13% of atherothrombotic events were treated in rural hospitals with in-hospital case fatality higher than in tertiary and non-tertiary metropolitan hospitals. A greater proportion of atherothrombotic disease cases treated in rural hospitals were in the most disadvantaged Socioeconomic Indices For Area group. What are the implications for practitioners? It is important to consider differences in disadvantage when generalising results of studies generated from tertiary hospital data to non-tertiary metropolitan and rural patients. [ABSTRACT FROM AUTHOR]