Constructing B─N─P Bonds in Ultrathin Holey g-C3N4 for Regulating the Local Chemical Environment in Photocatalytic CO2 Reduction to CO.

The lack of intrinsic active sites for photocatalytic CO2 reduction reaction (CO2RR) and fast recombination rate of charge carriers are the main obstacles to achieving high photocatalytic activity. In this work, a novel phosphorus and boron binary-doped graphitic carbon nitride, highly porous material that exhibits powerful photocatalytic CO2 reduction activity, specifically toward selective CO generation, is disclosed. The coexistence of Lewis-acidic and Lewis-basic sites plays a key role in tuning the electronic structure, promoting charge distribution, extending light-harvesting ability, and promoting dissociation of excitons into active carriers. Porosity and dual dopants create local chemical environments that activate the pyridinic nitrogen atom between the phosphorus and boron atoms on the exposed surface, enabling it to function as an active site for CO2RR. The P-N-B triad is found to lower the activation barrier for reduction of CO2 by stabilizing the COOH reaction intermediate and altering the rate-determining step. As a result, CO yield increased to 22.45 µmol g-1 h-1 under visible light irradiation, which is ≈12 times larger than that of pristine graphitic carbon nitride. This study provides insights into the mechanism of charge carrier dynamics and active site determination, contributing to the understanding of the photocatalytic CO2RR mechanism.

EQ-5D-5L Population Norms and Quality-Adjusted Life Expectancy by Sociodemographic Characteristics and Modifiable Risk Factors for Adults in Queensland, Australia.

OBJECTIVES: Over half of Australia's disease burden is due to morbidity, predominantly chronic conditions. Health-related quality of life instruments provide measures of morbidity and health status across different dimensions with EQ-5D being one of the most widely used. This study reports EQ-5D-5L general population norms for Queensland, Australia using the recently published Australian value set. METHODS: Population survey results from cross-sectional computer-assisted telephone interviews for Queensland adults in 2022 and 2023 were analyzed. EQ-5D-5L, as well as modifiable risk factors and sociodemographic data were collected. Using the recently published final Australian EQ-5D-5L value set, mean utility scores were calculated for Queensland, as well as by sociodemographic characteristics, including remoteness and socioeconomic area-based measures, and modifiable risk factors, such as smoking and body mass index. Results were combined with life tables to estimate quality-adjusted life expectancy (QALE) for subgroups with different lifestyles. RESULTS: The EQ-5D utility score for the Queensland adult population was 0.916. Smoking daily, being obese or older in age, or living in the most disadvantaged socioeconomic area were associated with lower mean scores. QALE was 6.1 and 7.9 years shorter than the life expectancy for Queensland males and females, respectively, but generally, those who reported having healthier lifestyles had higher mean utility scores and thus longer QALE. CONCLUSIONS: In addition to reporting Queensland EQ-5D-5L general population norms, these results demonstrate potential QALE gains in people following healthier lifestyles. The results support investment in prevention and may motivate further studies in this important area.

Impact of a prospective feedback loop aimed at reducing non-beneficial treatments in older people admitted to hospital and potentially nearing the end of life. A cluster stepped-wedge randomised controlled trial.

OBJECTIVES: To investigate if a prospective feedback loop that flags older patients at risk of death can reduce non-beneficial treatment at end of life. DESIGN: Prospective stepped-wedge cluster randomised trial with usual care and intervention phases. SETTING: Three large tertiary public hospitals in south-east Queensland, Australia. PARTICIPANTS: 14 clinical teams were recruited across the three hospitals. Teams were recruited based on a consistent history of admitting patients aged 75+ years, and needed a nominated lead specialist consultant. Under the care of these teams, there were 4,268 patients (median age 84 years) who were potentially near the end of life and flagged at risk of non-beneficial treatment. INTERVENTION: The intervention notified clinicians of patients under their care determined as at-risk of non-beneficial treatment. There were two notification flags: a real-time notification and an email sent to clinicians about the at-risk patients at the end of each screening day. The nudge intervention ran for 16-35 weeks across the three hospitals. MAIN OUTCOME MEASURES: The primary outcome was the proportion of patients with one or more intensive care unit (ICU) admissions. The secondary outcomes examined times from patients being flagged at-risk. RESULTS: There was no improvement in the primary outcome of reduced ICU admissions (mean probability difference [intervention minus usual care] = -0.01, 95% confidence interval -0.08 to 0.01). There were no differences for the times to death, discharge, or medical emergency call. There was a reduction in the probability of re-admission to hospital during the intervention phase (mean probability difference -0.08, 95% confidence interval -0.13 to -0.03). CONCLUSIONS: This nudge intervention was not sufficient to reduce the trial's non-beneficial treatment outcomes in older hospital patients. TRIAL REGISTRATION: Australia New Zealand Clinical Trial Registry, ACTRN12619000675123 (registered 6 May 2019).

The conveyor belt for older people nearing the end of life.

The current fallback position for the elderly frail nearing the end of life (less than 12 months to live) is hospitalisation. There is a reluctance to use the term 'terminally ill' for this population, resulting in overtreatment, overdiagnosis and management that is not consistent with the wishes of people. This is the major contributor to the so-called hospital crisis, including decreased capacity of hospitals, reduced ability to conduct elective surgery, increased attendances at emergency departments and ambulance ramping. The authors recently conducted the largest randomised study, to their knowledge, attempting to inform specialist hospital medical teams about the terminally ill status of their admitted patients. This information did not influence their clinical decisions in any way. The authors discuss the reasons why this may have occurred, such as the current avoidance of discussing death and dying by society and the concentration of healthcare workers on actively managing the acute presenting problem and ignoring the underlying prognosis in the elderly frail. The authors discuss ways of improving the management of the elderly nearing the end of life, such as more detailed goals of care discussions using the concept of shared decision-making rather than simply completing Advanced Care Decision documents. Empowering people in this way could become the most important driver of people's health care.

Process evaluation of a tailored nudge intervention to promote appropriate care and treatment of older patients at the end-of-life.

BACKGROUND: Non-beneficial treatment affects a considerable proportion of older people in hospital, and some will choose to decline invasive treatments when they are approaching the end of their life. The Intervention for Appropriate Care and Treatment (InterACT) intervention was a 12-month stepped wedge randomised controlled trial with an embedded process evaluation in three hospitals in Brisbane, Australia. The aim was to increase appropriate care and treatment decisions for older people at the end-of-life, through implementing a nudge intervention in the form of a prospective feedback loop. However, the trial results indicated that the expected practice change did not occur. The process evaluation aimed to assess implementation using the Consolidated Framework for Implementation Research, identify barriers and enablers to implementation and provide insights into the lack of effect of the InterACT intervention. METHODS: Qualitative data collection involved 38 semi-structured interviews with participating clinicians, members of the executive advisory groups overseeing the intervention at a site level, clinical auditors, and project leads. Online interviews were conducted at two times: implementation onset and completion. Data were coded to the Consolidated Framework for Implementation Research and deductively analysed. RESULTS: Overall, clinicians felt the premise and clinical reasoning behind InterACT were strong and could improve patient management. However, several prominent barriers affected implementation. These related to the potency of the nudge intervention and its integration into routine clinical practice, clinician beliefs and perceived self-efficacy, and wider contextual factors at the health system level. CONCLUSIONS: An intervention designed to change clinical practice for patients at or near to end-of-life did not have the intended effect. Future interventions targeting this area of care should consider using multi-component strategies that address the identified barriers to implementation and clinician change of practice. TRIAL REGISTRATION: Australia New Zealand Clinical Trial Registry (ANZCTR), ACTRN12619000675123p (approved 06/05/2019).

From pilot to a multi-site trial: refining the Early Detection of Deterioration in Elderly Residents (EDDIE +) intervention.

BACKGROUND: Early Detection of Deterioration in Elderly Residents (EDDIE +) is a multi-modal intervention focused on empowering nursing and personal care workers to identify and proactively manage deterioration of residents living in residential aged care (RAC) homes. Building on successful pilot trials conducted between 2014 and 2017, the intervention was refined for implementation in a stepped-wedge cluster randomised trial in 12 RAC homes from March 2021 to May 2022. We report the process used to transition from a small-scale pilot intervention to a multi-site intervention, detailing the intervention to enable future replication. METHODS: The EDDIE + intervention used the integrated Promoting Action on Research Implementation in Health Services (i-PARIHS) framework to guide the intervention development and refinement process. We conducted an environmental scan; multi-level context assessments; convened an intervention working group (IWG) to develop the program logic, conducted a sustainability assessment and deconstructed the intervention components into fixed and adaptable elements; and subsequently refined the intervention for trial. RESULTS: The original EDDIE pilot intervention included four components: nurse and personal care worker education; decision support tools; diagnostic equipment; and facilitation and clinical support. Deconstructing the intervention into core components and what could be flexibly tailored to context was essential for refining the intervention and informing future implementation across multiple sites. Intervention elements considered unsustainable were updated and refined to enable their scalability. Refinements included: an enhanced educational component with a greater focus on personal care workers and interactive learning; decision support tools that were based on updated evidence; equipment that aligned with recipient needs and available organisational support; and updated facilitation model with local and external facilitation. CONCLUSION: By using the i-PARIHS framework in the scale-up process, the EDDIE + intervention was tailored to fit the needs of intended recipients and contexts, enabling flexibility for local adaptation. The process of transitioning from a pilot to larger scale implementation in practice is vastly underreported yet vital for better development and implementation of multi-component interventions across multiple sites. We provide an example using an implementation framework and show it can be advantageous to researchers and health practitioners from pilot stage to refinement, through to larger scale implementation. TRIAL REGISTRATION: The trial was prospectively registered with the Australia New Zealand Clinical Trial Registry (ACTRN12620000507987, registered 23/04/2020).

Impact of a prospective feedback loop on care review activities in older patients at the end of life. A stepped-wedge randomised trial.

BACKGROUND: Hospitalisation rates for older people are increasing, with end-of-life care becoming a more medicalised experience. Innovative approaches are warranted to support early identification of the end-of-life phase, communicate prognosis, provide care consistent with people's preferences, and improve the use of healthcare resources. The Intervention for Appropriate Care and Treatment (InterACT) trial aimed to increase appropriate care and treatment decisions for older people at the end of life, through implementation of a prospective feedback loop. This paper reports on the care review outcomes. METHODS: A stepped-wedge randomised controlled trial was conducted in three large acute hospitals in Queensland, Australia between May 2020 and June 2021. The trial identified older people nearing the end of life using two validated tools for detecting deterioration and short-term death. Admitting clinical teams were provided with details of patients identified as at-risk with the goal of increasing awareness that end of life was approaching to facilitate appropriate patient centred care and avoid non-beneficial treatment. We examined the time between when the patient was identified as 'at-risk' and three outcomes: clinician-led care review discussions, review of care directive measures and palliative care referrals. These were considered useful indicators of appropriate care at the end of life. RESULTS: In two hospitals there was a reduction in the review of care directive measures during the intervention compared with usual care at 21 days (reduced probability of - 0.08; 95% CI: - 0.12 to - 0.04 and - 0.14; 95% CI: - 0.21 to - 0.06). In one hospital there was a large reduction in clinician-led care review discussions at 21 days during the intervention (reduced probability of - 0.20; 95% CI: - 0.28 to - 0.13). There was little change in palliative care referrals in any hospital, with average probability differences at 21 days of - 0.01, 0.02 and 0.04. DISCUSSION: The results are disappointing as an intervention designed to improve care of hospitalised older people appeared to have the opposite effect on care review outcomes. The reasons for this may be a combination of the intervention design and health system challenges due to the pandemic that highlight the complexity of providing more appropriate care at the end of life. TRIAL REGISTRATION: Australia New Zealand Clinical Trial Registry, ACTRN12619000675123 (registered 6 May 2019).

A stepped-wedge randomised controlled trial assessing the implementation, effectiveness and cost-consequences of the EDDIE+ hospital avoidance program in 12 residential aged care homes: study protocol.

BACKGROUND: Older people living in residential aged care homes experience frequent emergency transfers to hospital. These events are associated with risks of hospital acquired complications and invasive treatments or interventions. Evidence suggests that some hospital transfers may be unnecessary or avoidable. The Early Detection of Deterioration in Elderly residents (EDDIE) program is a multi-component intervention aimed at reducing unnecessary hospital admissions from residential aged care homes by empowering nursing and care staff to detect and manage early signs of resident deterioration. This study aims to implement and evaluate the program in a multi-site randomised study in Queensland, Australia. METHODS: A stepped-wedge randomised controlled trial will be conducted at 12 residential aged care homes over 58 weeks. The program has four components: education and training, decision support tools, diagnostic equipment, and implementation facilitation with clinical systems support. The integrated Promoting Action on Research Implementation in Health Services (i-PARIHS) framework will be used to guide the program implementation and process evaluation. The primary outcome measure will be the number of hospital bed days used by residents, with secondary outcomes assessing emergency department transfer rates, admission rates, length of stay, family awareness and experience, staff self-efficacy and costs of both implementation and health service use. A process evaluation will assess the extent and fidelity of program implementation, mechanisms of impact and the contextual barriers and enablers. DISCUSSION: The intervention is expected to improve outcomes by reducing unnecessary hospital transfers. Fewer hospital transfers and admissions will release resources for other patients with potentially greater needs. Residential aged care home staff might benefit from feelings of empowerment in their ability to proactively manage early signs of resident deterioration. The process evaluation will be useful for supporting wider implementation of this intervention and other similar initiatives. TRIAL REGISTRATION: The trial is prospectively registered with the Australia New Zealand Clinical Trial Registry ( ACTRN12620000507987 , registered 23/04/2020).

Effectiveness of clinical criteria in directing patient flow from the emergency department to a medical assessment unit in Queensland, Australia: a retrospective chart review of hospital administrative data.

BACKGROUND: Medical Assessment Units (MAUs) have become a popular model of acute medical care to improve patient flow through timely clinical assessment and patient management. The purpose of this study was to determine the effectiveness of a consensus-derived set of clinical criteria for patient streaming from the Emergency Department (ED) to a 15-bed MAU within the highly capacity-constrained environment of a large quaternary hospital in Queensland, Australia. METHODS: Clinically coded data routinely submitted for inter-hospital benchmarking purposes was used to identify the cohort of medical admission patients presenting to the ED in February 2016 (summer) and June 2016 (winter). A retrospective review of patient medical records for this cohort was then conducted to extract MAU admission data, de-identified patient demographic data, and clinical criteria. The primary outcome was the proportion of admissions that adhered to the MAU admission criteria. RESULTS: Of the total of 540 included patients, 386 (71 %) patients were deemed to meet the MAU eligibility admission criteria. Among patients with MAU indications, 66 % were correctly transferred (95 % CI: 61 to 71) to the MAU; this estimated sensitivity was statistically significant when compared with random allocation (p-value < 0.001). Transfer outcomes for patients with contraindications were subject to higher uncertainty, with a high proportion of these patients incorrectly transferred to the MAU (73 % transferred; 95 % CI: 50 to 89 %; p-value = 0.052). CONCLUSIONS: Based on clinical criteria, approximately two-thirds of patients were appropriately transferred to the MAU; however, a larger proportion of patients were inappropriately transferred to the MAU. While clinical criteria and judgement are generally established as the process in making decisions to transfer patients to a limited-capacity MAU, our findings suggest that other contextual factors such as bed availability, time of day, and staffing mix, including discipline profile of decision-making staff during ordinary hours and after hours, may influence decisions in directing patient flow. Further research is needed to better understand the interplay of other determinants of clinician decision making behaviour to inform strategies for improving more efficient use of MAUs, and the impact this has on clinical outcomes, length of stay, and patient flow measures in MAUs.

Clinical and Economic Outcomes of Genome Sequencing Availability on Containing a Hospital Outbreak of Resistant Escherichia coli in Australia.

OBJECTIVES: To evaluate the outbreak size and hospital cost effects of bacterial whole-genome sequencing availability in managing a large-scale hospital outbreak. METHODS: We built a hybrid discrete event/agent-based simulation model to replicate a serious bacterial outbreak of resistant Escherichia coli in a large metropolitan public hospital during 2017. We tested the 3 strategies of using whole-genome sequencing early, late (actual outbreak), or not using it and assessed their associated outbreak size and hospital cost. The model included ward dynamics, pathogen transmission, and associated hospital costs during a 5-month outbreak. Model parameters were determined using data from the Queensland Hospital Admitted Patient Data Collection (N = 4809 patient admissions) and local clinical knowledge. Sensitivity analyses were performed to address model and parameter uncertainty. RESULTS: An estimated 197 patients were colonized during the outbreak, with 75 patients detected. The total outbreak cost was A$460 137 (US$317 117), with 6.1% spent on sequencing. Without sequencing, the outbreak was estimated to result in 352 colonized patients, costing A$766 921 (US$528 547). With earlier detection from use of routine sequencing, the estimated outbreak size was 3 patients and cost A$65 374 (US$45 054). CONCLUSIONS: Using whole-genome sequencing in hospital outbreak management was associated with smaller outbreaks and cost savings, with sequencing costs as a small fraction of total hospital costs, supporting the further investigation of the use of routine whole-genome sequencing in hospitals.

A hybrid simulation model approach to examine bacterial genome sequencing during a hospital outbreak.

BACKGROUND: Hospital infection control requires timely detection and identification of organisms, and their antimicrobial susceptibility. We describe a hybrid modeling approach to evaluate whole genome sequencing of pathogens for improving clinical decisions during a 2017 hospital outbreak of OXA-181 carbapenemase-producing Escherichia coli and the associated economic effects. METHODS: Combining agent-based and discrete-event paradigms, we built a hybrid simulation model to assess hospital ward dynamics, pathogen transmission and colonizations. The model was calibrated to exactly replicate the real-life outcomes of the outbreak at the ward-level. Seven scenarios were assessed including genome sequencing (early or late) and no sequencing (usual care). Model inputs included extent of microbiology and sequencing tests, patient-level data on length of stay, hospital ward movement, cost data and local clinical knowledge. The main outcomes were outbreak size and hospital costs. Model validation and sensitivity analyses were performed to address uncertainty around data inputs and calibration. RESULTS: An estimated 197 patients were colonized during the outbreak with 75 patients detected. The total outbreak cost was US$318,654 with 6.1% of total costs spent on sequencing. Without sequencing, the outbreak was estimated to result in 352 colonized patients costing US$531,109. Microbiology tests were the largest cost component across all scenarios. CONCLUSION: A hybrid simulation approach using the advantages of both agent-based and discrete-event modeling successfully replicated a real-life bacterial hospital outbreak as a foundation for evaluating clinical outcomes and efficiency of outbreak management. Whole genome sequencing of a potentially serious pathogen appears effective in containing an outbreak and minimizing hospital costs.

A stepped-wedge randomised-controlled trial assessing the implementation, impact and costs of a prospective feedback loop to promote appropriate care and treatment for older patients in acute hospitals at the end of life: study protocol.

BACKGROUND: Hospitalisation rates for the older population have been increasing with end-of-life care becoming a more medicalised and costly experience. There is evidence that some of these patients received non-beneficial treatment during their final hospitalisation with a third of the non-beneficial treatment duration spent in intensive care units. This study aims to increase appropriate care and treatment decisions and pathways for older patients at the end of life in Australia. This study will implement and evaluate a prospective feedback loop and tailored clinical response intervention at three hospitals in Queensland, Australia. METHODS: A stepped-wedge cluster randomised trial will be conducted with up to 21 clinical teams in three acute hospitals over 70 weeks. The study involves clinical teams providing care to patients aged 75 years or older, who are prospectively identified to be at risk of non-beneficial treatment using two validated tools for detecting death and deterioration risks. The intervention's feedback loop will provide the teams with a summary of these patients' risk profiles as a stimulus for a tailored clinical response in the intervention phase. The Consolidated Framework for Implementation Research will be used to inform the intervention's implementation and process evaluation. The study will determine the impact of the intervention on patient outcomes related to appropriate care and treatment at the end of life in hospitals, as well as the associated healthcare resource use and costs. The primary outcome is the proportion of patients who are admitted to intensive care units. A process evaluation will be carried out to assess the implementation, mechanisms of impact, and contextual barriers and enablers of the intervention. DISCUSSION: This intervention is expected to have a positive impact on the care of older patients near the end of life, specifically to improve clinical decision-making about treatment pathways and what constitutes appropriate care for these patients. These will reduce the incidence of non-beneficial treatment, and improve the efficiency of hospital resources and quality of care. The process evaluation results will be useful to inform subsequent intervention implementation at other hospitals. TRIAL REGISTRATION: Australia New Zealand Clinical Trial Registry (ANZCTR), ACTRN12619000675123p (approved 6 May 2019).

The effectiveness and cost effectiveness of a hospital avoidance program in a residential aged care facility: a prospective cohort study and modelled decision analysis.

BACKGROUND: Residential aged care facility residents experience high rates of hospital admissions which are stressful, costly and often preventable. The EDDIE program is a hospital avoidance initiative designed to enable nursing and care staff to detect, refer and quickly respond to early signals of a deteriorating resident. The program was implemented in a 96-bed residential aged care facility in regional Australia. METHODS: A prospective pre-post cohort study design was used to collect data on costs of program delivery, hospital admission rates and length of stay for the 12 months prior to, and following, the intervention. A Markov decision model was developed to synthesize study data with published literature in order to estimate the cost-effectiveness of the program. Quality adjusted life years (QALYs) were adopted as the measure of effectiveness. RESULTS: The EDDIE program was associated with a 19% reduction in annual hospital admissions and a 31% reduction in the average length of stay. The cost-effectiveness analysis found the program to be both more effective and less costly than usual care, with 0.06 QALYs gained and $249,000 health system costs saved in a modelled cohort of 96 residents. A probabilistic sensitivity analysis estimated that there was an 86% probability that the program was cost-effective after taking the uncertainty of the model inputs into account. CONCLUSIONS: This study provides promising evidence for the effectiveness and cost-effectiveness of a nurse led, early intervention program in preventing unnecessary hospital admissions within a residential aged care facility. Further research in multi-site randomised studies is needed to confirm the generalisability of these results.

Estimating the costs of genomic sequencing in cancer control.

BACKGROUND: Despite the rapid uptake of genomic technologies within cancer care, few studies provide detailed information on the costs of sequencing across different applications. The objective of the study was to examine and categorise the complete costs involved in genomic sequencing for a range of applications within cancer settings. METHODS: We performed a cost-analysis using gross and micro-costing approaches for genomic sequencing performed during 2017/2018 across different settings in Brisbane, Australia. Sequencing was undertaken for patients with lung, breast, oesophageal cancers, melanoma or mesothelioma. Aggregated resource data were captured for a total of 1433 patients and point estimates of per patient costs were generated. Deterministic sensitivity analyses addressed the uncertainty in the estimates. Estimated costs to the public health system for resources were categorised into seven distinct activities in the sequencing process: sampling, extraction, library preparation, sequencing, analysis, data storage and clinical reporting. Costs were also aggregated according to labour, consumables, testing, equipment and 'other' categories. RESULTS: The per person costs were AU$347-429 (2018 US$240-297) for targeted panels, AU$871-$2788 (2018 US$604-1932) for exome sequencing, and AU$2895-4830 (2018 US$2006-3347) for whole genome sequencing. Cost proportions were highest for library preparation/sequencing materials (average 76.8% of total costs), sample extraction (8.1%), data analysis (9.2%) and data storage (2.6%). Capital costs for the sequencers were an additional AU$34-197 (2018 US$24-67) per person. CONCLUSIONS: Total costs were most sensitive to consumables and sequencing activities driven by commercial prices. Per person sequencing costs for cancer are high when tumour/blood pairs require testing. Using the natural steps involved in sequencing and categorising resources accordingly, future evaluations of costs or cost-effectiveness of clinical genomics across cancer projects could be more standardised and facilitate easier comparison of cost drivers.

Comparison of EQ-5D-5L and SPVU-5D for measuring quality of life in patients with venous leg ulcers in an Australian setting.

PURPOSE: Given the importance of measuring health-related quality of life (HRQoL) for cost-utility studies, this study aimed to determine the validity and responsiveness of two preference-based HRQoL instruments, the EuroQol-five dimensions-five levels questionnaire (EQ-5D-5L) and the Sheffield Preference-based Venous Ulcer questionnaire (SPVU-5D) in patients with venous leg ulcers (VLUs) in an Australian setting. METHODS: This study analysed de-identified data collected from 80 patients with VLUs recruited by a prospective study in Brisbane, Queensland, Australia. Patients were asked to complete EQ-5D-5L and SPVU-5D surveys at baseline, 1-month, 3-month and 6-month follow-up as part of the prospective study. Baseline data and follow-up data were pooled to test the construct validity and level of agreement of the two instruments. Follow-up data were used to test the responsiveness. RESULTS: The ceiling effects were negligible for EQ-5D-5L and SPVU-5D utility scores. Both instruments were able to discriminate between healed VLU and unhealed VLU and showed great responsiveness when healing status changed over time. Weak to strong correlations were found between dimensions of EQ-5D-5L and SPVU-5D. The utility scores produced from EQ-5D-5L were generally lower. CONCLUSIONS: This study found that both EQ-5D-5L and SPVU-5D were valid and responsive in detecting change of VLU healing status among a small Australian population. Both instruments may be used in economic evaluation studies that involve patients with healed or unhealed VLUs. However, given the limitations presented in this study, further research is necessary to make sound recommendations on the preferred instrument in economic evaluation of VLU-related interventions.

Health benefits of an innovative model of care for chronic wounds patients in Queensland.

Wound management in Australia suffers from a lack of adequate coordination and communication between sectors that impacts patient outcomes and costs. Wound Innovations is a specialist service comprising of a transdisciplinary team that aims to streamline and improve patient care and outcomes. We compared patient experiences and outcomes prior to accessing this specialist service, and the 3 months following their enrolment at the clinic. Information on patient experiences, wound history, and outcomes was collected through interviews and a review of medical records for the 12 months prior to enrolment at the clinic. Wound progress, quality of life (QoL) outcomes, and service use were tracked during the 3-month prospective phase. A sample of 29 participants was recruited. 40% healed completely by 3 months, with the average time to healing being 8 weeks. The average QoL score at baseline was 0.69 (from a score of 1, being best health imaginable). At 3 months, the average QoL score increased significantly to 0.84 (P ≤0.001). On average, participants attended the clinic 4.6 times. The average decrease in wound size was 85.4% (95% CI [75.7%, 95%]). Accessing wound care treatment at a specialist, multidisciplinary wound clinic leads to an increase in QoL and access to consistent evidence-based practices.

Measuring costs and quality of life for venous leg ulcers.

Venous leg ulcers (VLUs) result in substantial economic costs and reduced quality of life (QoL); however, there are few Australian cost estimates, especially using patient-level data. We measured community-setting VLU management costs and the impact on the QoL of affected individuals. VLU patients were recruited from a specialist wound clinic, an outpatient clinic, and two community care clinics in Queensland. Cost data were collected at the baseline visit. QoL (EQ-5D-5L) and wound status data were collected at baseline, 1, 3, and 6 months. Patients were classified into guideline-based/optimal care and usual care groups. Average weekly costs per patient were statistically significantly different between the usual care and optimal care groups-$214.61 and $294.72, respectively (P = 0.04). Baseline average QoL score for an unhealed ulcer was significantly higher in the optimal care group compared with usual care (P = 0.025). Time to healing differed between the usual care group and the optimal care group (P = 0.04), with averages of 3.9 and 2.7 months, respectively. These findings increase the understanding of the costs, QoL, and healing outcomes of VLU care. Higher optimal care costs may be offset by faster time to healing. This study provides data to inform an economic evaluation of guideline-based care for VLUs.

Model choice problems using approximate Bayesian computation with applications to pathogen transmission data sets.

Analytically or computationally intractable likelihood functions can arise in complex statistical inferential problems making them inaccessible to standard Bayesian inferential methods. Approximate Bayesian computation (ABC) methods address such inferential problems by replacing direct likelihood evaluations with repeated sampling from the model. ABC methods have been predominantly applied to parameter estimation problems and less to model choice problems due to the added difficulty of handling multiple model spaces. The ABC algorithm proposed here addresses model choice problems by extending Fearnhead and Prangle (2012, Journal of the Royal Statistical Society, Series B 74, 1-28) where the posterior mean of the model parameters estimated through regression formed the summary statistics used in the discrepancy measure. An additional stepwise multinomial logistic regression is performed on the model indicator variable in the regression step and the estimated model probabilities are incorporated into the set of summary statistics for model choice purposes. A reversible jump Markov chain Monte Carlo step is also included in the algorithm to increase model diversity for thorough exploration of the model space. This algorithm was applied to a validating example to demonstrate the robustness of the algorithm across a wide range of true model probabilities. Its subsequent use in three pathogen transmission examples of varying complexity illustrates the utility of the algorithm in inferring preference of particular transmission models for the pathogens.

Protocol for a process evaluation of a stepped wedge randomised controlled trial to reduce unnecessary hospitalisations of older people from residential aged care: the EDDIE+ study.

INTRODUCTION: The Early Detection of Deterioration in Elderly residents (EDDIE+) programme is a theory-informed, multi-component intervention aimed at upskilling and empowering nursing and personal care staff to identify and manage early signs of deterioration in residents of aged care facilities. The intervention aims to reduce unnecessary hospital admissions from residential aged care (RAC) homes. Alongside a stepped wedge randomised controlled trial, an embedded process evaluation will be conducted to assess the fidelity, acceptability, mechanisms of action and contextual barriers and enablers of the EDDIE+ intervention. METHODS AND ANALYSIS: Twelve RAC homes in Queensland, Australia are participating in the study. A comprehensive mixed-methods process evaluation, informed by the integrated Promoting Action on Research Implementation in Health Services (i-PARIHS) framework, will assess intervention fidelity, contextual barriers and enablers, mechanisms of action, and the acceptability of the programme from various stakeholder perspectives. Quantitative data will be collected prospectively from project documentation, including baseline context mapping of participating sites, activity tracking and regular check-in communication sheets. Qualitative data will be collected postintervention via semi-structured interviews with a range of stakeholder groups. The i-PARIHS constructs of innovation, recipients, context and facilitation will be applied to frame the analysis of quantitative and qualitative data. ETHICS AND DISSEMINATION: Ethical approval for this study has been granted by the Bolton Clarke Human Research Ethics Committee (approval number: 170031) with administrative ethical approval granted by the Queensland University of Technology University Human Research Ethics Committee (2000000618). Full ethical approval includes a waiver of consent for access to residents' demographic, clinical and health services de-identified data. A separate health services data linkage based on RAC home addresses will be sought through a Public Health Act application. Study findings will be disseminated through multiple channels, including journal publications, conference presentations and interactive webinars with a stakeholder network. TRIAL REGISTRATION NUMBER: Australia New Zealand Clinical Trial Registry (ACTRN12620000507987).

The Increased Length of Hospital Stay and Mortality Associated With Community-Associated Infections in Australia.

Background: An increasing proportion of antibiotic-resistant infections are community acquired. However, the burden of community-associated infections (CAIs) and the resulting impact due to resistance have not been well described. Methods: We conducted a multisite, retrospective case-cohort study of all acute care hospital admissions across 134 hospitals in Australia. Patients admitted with a positive culture of 1 of 5 organisms of interest, namely Escherichia coli, Klebsiella pneumoniae, Pseudomonas aeruginosa, Staphylococcus aureus, and Enterococcus faecium, from January 1, 2012, through December 30, 2016, were included. Data linkage was used to link hospital admissions and pathology data. Patients with a bloodstream infection (BSI), urinary tract infection (UTI), or respiratory tract infection (RTI) were included in the analysis. We compared patients with a resistant and drug-sensitive infection and used regression analyses to derive the difference in length of hospital stay (LOS) and mortality estimates associated with resistance. Results: No statistically significant impact on hospital LOS for patients with resistant CAIs compared with drug-sensitive CAIs was identified. CAI patients with drug-resistant Enterobacteriaceae (E. coli, K. pneumoniae) BSIs were more likely to die in the hospital than those with drug-sensitive Enterobacteriaceae BSIs (odds ratio [OR], 3.28; 95% CI, 1.40-6.92). CAI patients with drug-resistant P. aeruginosa UTIs were more likely to die in the hospital than those with the drug-sensitive counterpart (OR, 2.43; 95% CI, 1.12-4.85). Conclusions: The burden of CAI in the hospital is significant, and antibiotic resistance is adding to associated mortality.