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BACKGROUND:Information about children treated in New South Wales (NSW), Australia following major injury has been limited to those treated at trauma centres using mortality as the main outcome measure, restricting assessment of the effectiveness of the Trauma System. This study sought to describe the detailed characteristics as well as functional and psychosocial health outcomes of all children suffering major injury in NSW. METHODS:A longitudinal study was conducted between July 2015 and November 2017 and included children < 16 years requiring intensive care or an injury severity score (ISS) ≥ 9 treated in NSW or who died following injury. Children were identified through the three NSW Paediatric Trauma Centres (PTC), the NSW Trauma Registry, NSW Aeromedical Retrieval Registry (AirMaestro) and the National Coronial Information System (NCIS). Health-related quality of life (HRQoL) outcomes for children treated at the three PTCs were collected at baseline, 6 and 12 months using the Paediatric Quality of Life inventory (PedsQL 4.0) and EuroQol five-dimensional EQ-5D-Y. RESULTS:There were 625 children, with a median (interquartile range) age of 7 (2-13) years and 71.7% were male. Around half were injured in major cities (51.2%). The median (IQR) injury severity score (ISS) was 10 (9-17). Twelve-month HRQoL measured by PedsQL remained below baseline for psychosocial health. Treatment costs increased with injury severity (p=

Aims This study aimed to quantify the health economic treatment costs of clinical deterioration of patients within 72 h of admission via the emergency department. Methods This study was conducted between March 2018 and February 2019 in two hospitals in regional New South Wales, Australia. All patients admitted via the emergency department were screened for clinical deterioration (defined as initiation of a medical emergency team call, cardiac arrest or unplanned admission to Intensive Care Unit) within 72 h through the site clinical deterioration databases. Patient characteristics, including pre-existing conditions, diagnosis and administrative data were collected. Results 1600 patients clinically deteriorated within 72 h of hospital admission. Linked treatment cost data were available for 929 (58%) of these patients across 352 Australian Refined Diagnosis Related Groups. The average (standard deviation) treatment costs for patients who deteriorated within 72 h was $26,778 ($34,007) compared to $7727 ($12,547). The average hospital length of stay of the deterioration group was nearly 8 days longer than patients without deterioration. When controlling for length of stay and Australian Refined Diagnosis Related Group codes, the incremental cost per episode of deterioration was $14,134. Conclusion Clinical deterioration within 72 h of admission is associated with increased treatment costs irrespective of diagnosis, hospital length of stay and age. Implementation of interventions known to prevent patient deterioration require evaluation.

Background Blunt chest injury leads to significant morbidity and mortality. The aim of this study was to evaluate the effect of a multidisciplinary chest injury care bundle (ChIP) on patient and health service outcomes. ChIP provides guidance in three key pillars of care for blunt chest injury—respiratory support, analgesia and complication prevention. ChIP was implemented using a multi-faceted implementation plan developed using the Behaviour Change Wheel. Methods This controlled pre-and post-test study (two intervention and two non-intervention sites) was conducted from July 2015 to June 2019. The primary outcome measures were unplanned Intensive Care Unit (ICU) admissions, non-invasive ventilation use and mortality. Results There were 1790 patients included. The intervention sites had a 58% decrease in non-invasive ventilation use in the post- period compared to the pre-period (95% CI 0.18–0.96). ChIP was associated with 90% decreased odds of unplanned ICU admissions (95% CI 0.04–0.29) at the intervention sites compared to the control groups in the post- period. There was no significant change in mortality. There were higher odds of health service team reviews (surgical OR 6.6 (95% CI 4.61–9.45), physiotherapy OR 2.17 (95% CI 1.52–3.11), ICU doctor OR 6.13 (95% CI 3.94–9.55), ICU liaison OR 55.75 (95% CI 17.48–177.75), pain team OR 8.15 (95% CI 5.52 –-12.03), analgesia (e.g. patient controlled analgesia OR 2.6 (95% CI 1.64–3.94) and regional analgesia OR 8.8 (95% CI 3.39–22.79), incentive spirometry OR 8.3 (95% CI 4.49–15.37) and, high flow nasal oxygen OR 22.1 (95% CI 12.43–39.2) in the intervention group compared to the control group in the post- period. Conclusion The implementation of a chest injury care bundle using behaviour change theory was associated with a sustained improvement in evidence-based practice resulting in reduced unplanned ICU admissions and non-invasive ventilation requirement. Trial registration ANZCTR: ACTRN12618001548224, approved 17/09/2018

Background: The present study aimed to ascertain the acceptability to at-risk young people of self-collected urine samples as a means of testing for Chlamydia trachomatis (chlamydia); to determine the effectiveness of drop-off and outreach collection methods as a means of detecting and treating chlamydia; and to determine the rate of positive chlamydia tests in a sample of the target group. Methods: Participants requested postal testing kits from the project website, the NSW Sexual Health Infoline or at an outreach event and either returned urine samples at selected drop-off locations or directly to the researchers during active outreach events. Results: A total of 413 kits were requested – 196 (47.5%) via email, 204 (49.4%) during outreach events and nine (2.2%) via the NSW Sexual Health Infoline. A total of 195 samples (47.2% of ordered kits) were returned. Participants were less likely to return samples if they had been requested by email (odds ratio = 9.6; 95% confidence interval: 6.0–15.0) or via telephone (odds ratio = 22.0; 95% confidence interval: 2.7–181.0) compared with directly obtaining a kit at an outreach event. The number of specimens positive for chlamydia in the targeted age range was 4, giving a 3.1% positive rate (95% confidence interval: 1.0–8.0). Conclusions: This study identified that free testing kits and online communication worked well as a means of engaging young people and raising awareness of sexual health. However, the requirement to drop-off urine samples at selected locations was not well accepted.

Background Clinical and non-clinical health leaders both seek to leverage data to drive innovative improvements in models of care and create sustainable and effective health systems. For the last three years, Activity-Based Funding (ABF) has been the main driver for funding public hospitals in New South Wales (NSW), Australia. The data generated by the implementation of ABF has been used for both policy and funding decisions. As quality improved, the data became more relevant to a wide range of stakeholders, and drove improved interactions and conversations between clinicians and administrators. These conversations and opportunities were particularly relevant for patient-level clinical costing. This process uses a large range of data sets to allocate costs, and is presented with patient activity data that are familiar to clinicians. Clinical analytics, which leverages on cost and activity data, are being used to shape the future of local health systems, improve service delivery, and enhance patient outcomes. This shift moves the system from ABF to Activity-Based Management (ABM), through which data can be used not only for funding the annual budgets of Local Health Districts (LHDs) but also to inform local policy decisions. For several years, LHDs have submitted annual patient costing data returns to the Ministry of Health. Until recently, however, they saw few benefits from the effort required to submit these data, since state-wide benchmarking and variance analysis were limited and/or provided with significant time delays. The ABM Portal was created and launched to address this issue. The Portal provides a rich data source that can support local decision-making about clinical care evaluations, reduce unwarranted clinical variations, improve care models, facilitate service planning, and effectively manage services within budget. The ABM Portal was developed with significant input from clinicians and is currently being expanded to incorporate additional data elements. The ABM Portal contains data aggregated to LHDs from patient-level data, enabling users to drill down to the lowest-level information and understand the causes of any identified variances (i.e., in cost or length of stay).