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Background: In health care, clinical effectiveness involves evaluating the degree to which clinical interventions achieve beneficial patient and caregiver outcomes. Objective: To evaluate the clinical effectiveness of care in a specialist palliative care unit (SPCU) in Ireland, including an analysis of the temporal relationship among admission, Phase of Illness and patient and family distress. Design/Measurements: A consecutive case series with prospectively collected admission data (n = 400). Using a casemix tool (Phase of Illness), pain, other symptoms, psychological and family distress, and performance status were documented on admission and then daily by medical staff. Results: Three hundred forty-two (85%) patients had complete data recorded on day 1. After admission, there were linear correlations between days since admission and progressive improvements in pain (Cramer's V = 0.131, p

PurposeThe purpose of this paper is twofold: first, to present patient-level utilisation patterns of hospital-based mental health services funded by private health insurers; and second, to examine the implications of the findings for planning and delivering private mental health services in Australia.Design/methodology/approachAnalysing private health insurance claims data, this study compares differences in demographic and hospital utilisation characteristics of 3,209 patients from 13 private health insurance funds with claims for mental health-related hospitalisations and 233,701 patients with claims for other types of hospitalisations for the period May 2014 to April 2016. Average number of overnight admissions, length of stay and per patient insurer costs are presented for each group, along with overnight admissions vs same-day visits and repeat services within a 28-day period following hospitalisation. Challenges in analysing and interpreting insurance claims data to better understand private mental health service utilisation are discussed.FindingsPatients with claims for mental health-related hospitalisations are more likely to be female (62.0 per cent compared to 55.8 per cent), and are significantly younger than patients with claims for other types of hospitalisations (32.6 per cent of patients aged 55 years and over compared to 57.1 per cent). Patients with claims for mental health-related hospitalisations have significantly higher levels of service utilisation than the group with claims for other types of hospitalisations with a mean length of stay per overnight admission of 15.0 days (SD=14.1), a mean of 1.3 overnight admissions annually (SD=1.2) and mean hospital costs paid by the insurer of $13,192 per patient (SD=13,457) compared to 4.6 days (SD=7.3), 0.8 admissions (SD=0.6) and $2,065 per patient (SD=4,346), respectively, for patients with claims for other types of hospitalisations. More than half of patients with claims for mental health-related hospitalisations only claim for overnight admissions. However, the findings are difficult to interpret due to the limited information collected in insurance claims data.Practical implicationsThis study shows the challenges of understanding utilisation patterns with one data source. Analysing insurance claims reveals information on mental health-related hospitalisations but information on community-based care is lacking due to the regulated role of the private health insurance sector in Australia. For mental health conditions, and other chronic health conditions, multiple data sources need to be integrated to build a comprehensive picture of health service use as care tends to be provided in multiple settings by different medical and allied health professionals.Originality/valueThis study contributes in two areas: patient-level trends in hospital-based mental health service utilisation claimed on private health insurance in Australia have not been previously reported. Additionally, as the amount of data routinely collected in health care settings increases, the study findings demonstrate that it is important to assess the quality of these data sources for understanding service utilisation.

Objective This study explored the current activities of a sample of Australian private health insurance (PHI) funds to support the care of people living with chronic conditions, following changes to PHI legislation in 2007 permitting funds to cover a broader range of chronic disease management (CDM) services. Methods A qualitative research design was used to gather perspectives from PHI sector representatives via semistructured interviews with eight participants. The interview data were analysed systematically using the framework analysis method. Results Three main types of activities were most commonly identified: (1) healthcare navigation; (2) structured disease management and health coaching programs; and (3) care coordination services. These activities were primarily conducted via telephone by a combination of in-house and third-party health professionals. PHI funds seem to be taking a pragmatic approach to the type of CDM activities currently offered, guided by available data and identified member need. Activities are focused on people with diagnosed chronic conditions exiting hospital, rather than the broader population at-risk of developing a chronic condition. Conclusions Despite legislation permitting PHI funds to pay benefits for CDM services being in place for more than 10 years, insurers are still in an early stage of implementation and evaluation of CDM activities. Primarily due to the regulated scope of PHI coverage in Australia, participants reported several challenges in providing CDM services, including identifying target groups, evaluating service outcomes and collaborating with other healthcare providers. The effectiveness of the approach of PHI funds to CDM in terms of the groups targeted and outcomes of services provided still needs to be established because evidence suggests that population-level interventions that target a larger number of people with lower levels of risks are likely to have greater benefit than targeting a small number of high-risk cases. What is known about the topic? Since 2007, PHI funds in Australia have been able to pay benefits for a range of out-of-hospital services, focused on CDM. Although a small number of program evaluations has been published, there is little information on the scope of activities and the factors influencing the design and implementation of CDM programs. What does this paper add? This paper presents the findings of a qualitative study reporting on the CDM activities offered by a sample of PHI funds, their approach to delivery and the challenges and constraints in designing and implementing CDM activities, given the PHI sector’s role as a supplementary health insurer in the Australian health system. What are the implications for practitioners? Current CDM activities offered by insurers focus on health navigation advice, structured, time-limited CDM programs and care coordination services for people following a hospital admission. There is currently little integration of these programs with the care provided by other health professionals for a person accessing these services. Although the role of insurers is currently small, the movement of insurers into service provision raises considerations for managing potential conflicts in having a dual role as an insurer and provider, including the effectiveness and value of services offered, and how these programs complement other types of health care being received.

Chronic or persistent pain is a growing global health problem. Effective management of pain emerging in childhood may prevent long-term health and vocational consequences. Internationally, paediatric pain services are a limited resource and, as such, must strive to improve equity, outcomes, and value for money. The Paediatric electronic Persistent Pain Outcomes Collaboration (PaedePPOC) is a binational paediatric outcome measurement centre that aims to measure, benchmark, and improve children's specialist pain services in Australasia. This study documents the establishment of PaedePPOC and presents baseline and initial outcome data. Binational consensus meetings determined the measures. Governance structures, collection protocols, information technology, site-specific logistics, and onsite training were achieved within 18 months. Children and parents complete baseline and progress questionnaires. Seven of 10 Australasian services provided data to PaedePPOC, with 1432 patients enrolled until June 2018. At baseline, patients were 12.4 ± (3.0) years, 68% female, 93% Australian-born, and 5% Aboriginal and/or Torres Strait Islander people. Most had moderate-severe functional disability and impaired quality of life, with pain affecting school attendance and employment. Opioid-containing medicines were used often or daily by 16%. Patients completing outcome measures at treatment end reported clinically significant improvement in pain intensity (49% of patients), functional ability (59%), and quality of life (69%). The PaedePPOC initiative has been successfully integrated into children's pain services, yielding timely point-of-care information to support clinicians and families, and valuable binational and service data to inform quality improvement and future sector planning.

Choice and preference are fundamental to person-centered care and supporting personal choice at the end of life should be a priority. This study analyzed the relationship between a person’s preferred place of death and other individual variables that might influence their actual place of death by examining the activity of 2 specialist community palliative care services in Australia. This was a cross-sectional study of 2353 people who died between 01 August 2016-31 August 2018; 81% died in their preferred place. Sex, type of life-limiting illness, and length of time in care were the only variables significantly related to dying in one’s preferred place. Women were more likely to die in their preferred place than men (84% v 78%) and people with a non-cancer diagnosis were 7% more likely to die in their preferred place than those with cancer, particularly when that place was their private residence (74% v 60%) or Residential Aged Care Facility (98% v 89%). Someone in care for 0-7 days had 4.2 times greater odds of dying in their preferred place (OR = 4.18, 2.20-7.94), and after 21 days in care, people had 4.6 greater odds of having a preference to die in a hospital (OR = 4.63, 3.58-5.99). Both community palliative care services have capacity and a model of care that is responsive to choice. These findings align with known referral patterns and disease trajectories and demonstrate that it is possible to support the majority of people in the care of community palliative care services to die in their preferred place.

BackgroundImplementation of routinely collected patient-reported outcome measures (PROMs) ensures patients’ priorities are at the forefront of care planning and helps to standardize approaches to quality improvement. In palliative care, barriers to PROMs are widely known but what are not understood are the clinical and care settings in which patients are more likely to report and when proxy reporting is needed.ObjectiveTo examine the incidence of patient-reported symptom distress compared to the incidence of proxy reporting in palliative care and influencing factors.MethodsA national observational study using routinely collected PROMs data with influencing factors investigated by logistic regression modelling. Participants were patients with an advanced life-limiting illness receiving palliative care in an inpatient or a community healthcare setting in Australia.ResultsSixteen thousand one hundred and fifty-eight reports of symptom distress were collected from 1117 patients seen by 21 palliative care services. The majority of respondents were diagnosed with cancer (76%), were older (≥65 years, 72%) and had nominated English as their first language (88%). The majority of symptom distress reports were completed by patients (61%). The odds of a patient providing a self-report where grater when they were receiving community versus inpatient palliative care (odds ratio (OR): 3.0; 95% confidence interval (CI): 2.25–4.01), for patients diagnosed with malignant versus non-malignant disease (OR 1.7; 95% CI: 1.26–2.31), and for those who required an urgent change in their care plan versus those whose symptoms and problems were adequately managed (OR: 1.38; 95% CI: 1.04–1.83).ConclusionThree factors are associated with an increased likelihood of patient versus proxy reporting in palliative care: healthcare setting, diagnosis, and the acuity and urgency of the patient’s clinical needs. PROMs are feasible in most clinical scenarios in palliative care, including when an urgent clinical response is required.

Background There is wide inequity in specialist palliative care provision across settings. The absence of any standard way to group by case complexity is a barrier to addressing these inequities. Aim We therefore aimed to develop a casemix classification for UK specialist palliative care across settings, by identifying/grouping patient-level attributes at the start of an episode of care that predict costs of care provision within that episode. Design Cohort study with prospective collection of patient demographic and clinical variables, potential complexity and casemix criteria, and patient-level resource use. Results 2,469 participants were recruited (mean age 71.6, 51% male, 75% with cancer), receiving 2,968 episodes of care, from 14 specialist palliative organisations across England. Episodes of care lasted: median (range) 8 days (1–402) in hospital advisory palliative care, 12 days (1–140) in inpatient palliative units, 30 days (1–313) in community palliative care. Median cost per day (interquartile range) were: £56 (£31–100) in hospital advisory, £365 (£176-£698) within inpatient, and £21 (£6-£49) in community care. Seven hospital advisory, six inpatient, six community casemix classes for specialist palliative care, based on seven casemix variables (pain, other physical symptoms, psychological symptoms, functional status, palliative Phase of Illness, living alone, and family distress) predict per-diem costs. Conclusion The casemix classes show cost weight variations by up to 60% (in hospital advisory palliative care), up to 4.5-fold (in inpatient hospices), and approaching 3-fold (in community palliative care). The proposed casemix classification helps to understand these variations systematically and at scale; for practice, policy (including funding), and research, to help address inequities and provide fair, equitable and transparent palliative care to all who need it. Acknowledgements Funded by National Institute for Health Research (C-CHANGE project: RP-PG-1210-12015). The views and opinions expressed by authors do not necessarily reflect those of the NHS, NIHR, MRC, CCF, NETSCC, or DHSC

Objective The aim of this study was to assess the unmet need for palliative and other end-of-life care, as well as the sociodemographic and diagnostic factors associated with suboptimal access, among residents in an Australian region. Methods A cross-sectional descriptive and analytical study was performed using non-identifiable linked data from four administrative and two clinical datasets. The study population comprised 3175 patients aged ≥15 years who died in hospital in 2016 and 2017. The main outcome measures were the proportion of decedents potentially benefitting from end-of-life care and receiving end-of-life care. Results An estimated 74.8% of decedents needed palliative or other end-of-life care in the year before death. Approximately 13.3% did not receive any end-of-life care despite its potential benefit. The highest proportions with ‘unmet need’ were decedents with chronic obstructive pulmonary disease (31.0%) and heart failure (26.3%). Adjusting for sociodemographic and diagnostic factors, access was lowest among those aged

Background Access to primary care has an impact on health outcomes and is a significant public health issue. Limited access to primary care has seen non-urgent presentations to hospital emergency departments continue to rise globally. A lack of a universal workable definition of what a primary care presentation is has impeded national and international estimations of the true burden. Our aim was to develop a standardised code frame to identify potential primary care patients in the emergency department to allow accurate data estimations to be made, and help inform future interventions. Methods An audit of medical records was conducted in two major hospitals in Sydney, Australia. A code frame was developed, tested and applied retrospectively to five years of data. Results Of 601,168 presentations to the emergency department, 171,906 (29%) were deemed to be potential primary care presentations. The code frame had a sensitivity of 99.9% and a specificity of 49.0%. Conclusions This standardised code frame enables accurate retrospective local and national data estimations of the impact of primary care presentations in the emergency department, which was previously not available. The code frame could be used prospectively to evaluate interventions such as diverting patients to primary care settings, and to identify populations for specifically targeted interventions. The conservative nature of the code frame ensures that only those that can safely receive care in a primary care setting are identified as potential primary care. Key messages This robust tool will enable more accurate data estimations of primary care appropriate presentations in the emergency department, which can assist planning and policy efforts. It can be easily adapted to incorporate triage codes in international settings and provides a useful tool for comparing international trends.

Objectives To describe morbidity and multimorbidity patterns among adults readmitted to an Australian regional health service, in terms of occurrence of the same and different morbidities at index admission and readmission. Methods This cohort study used hospital admissions data for patients admitted between 1 July 2014 and 30 June 2016 to estimate proportions of unplanned readmissions (‘early’ within 30 days and ‘late’ within 1–6 months) with the same and different morbidities as the index admission. Readmission rates were estimated by selected sociodemographic, admission and diagnostic characteristics. Results The majority of early and late readmissions were in different diagnostic groups and for different primary morbidities to the index admission. Only 38.8% of readmissions were in the same major diagnostic group as the index admission and 18.4% in the same Adjacent Diagnosis-Related Group. Twenty one percent of admitted patients were readmitted within six months, with this increasing to 35.3% among multimorbid patients. Conclusion With increasing prevalence of multimorbidity, particularly among those at increased risk of readmission, it is essential to step away from a single disease focus in the design of both hospital avoidance and chronic disease management programmes. Holistic interventions and strategies that address multiple chronic conditions are required.

Objective To develop a casemix classification to underpin a new funding model for residential aged care in Australia. Design, setting Cross-sectional study of resident characteristics in thirty non-government residential aged care facilities in Melbourne, the Hunter region of New South Wales, and northern Queensland, March 2018 - June 2018. Participants 1877 aged care residents and 1600 residential aged care staff. Main outcome measures The Australian National Aged Care Classification (AN-ACC), a casemix classification for residential aged care based on the attributes of aged care residents that best predict their need for care: frailty, mobility, motor function, cognition, behaviour, and technical nursing needs. Results The AN-ACC comprises 13 aged care resident classes reflecting differences in resource use. Apart from the class that included palliative care patients, the primary branches were defined by the capacity for mobility; further classification is based on physical capacity, cognitive function, mental health problems, and behaviour. The statistical performance of the AN-ACC was good, as measured by the reduction in variation statistic (RIV; 0.52) and class-specific coefficients of variation. The statistical performance and clinical acceptability of AN-ACC compare favourably with overseas casemix models, and it is better than the current Australian aged care funding model, the Aged Care Funding Instrument (64 classes; RIV, 0.20). Conclusions The care burden associated with frailty, mobility, function, cognition, behaviour and technical nursing needs drives residential aged care resource use. The AN-ACC is sufficiently robust for estimating the funding and staffing requirements of residential aged care facilities in Australia.

ObjectivesTo explore differences in severe symptom outcomes for palliative care patients receiving hospital care compared with those receiving care at home.MethodsChange in symptom distress from the start of an episode of palliative care to just prior to death was measured for 25 679 patients who died under the care of a hospital or home-based palliative care team between January 2015 and December 2016. Logistic regression models controlled for differences between hospital and home and enabled a comparison of the number of severe symptoms just prior to death.ResultsAll symptoms improved and over 85% of all patients had no severe symptoms prior to death. Pain control illustrates this with 7.4% of patients reporting severe pain distress at episode start and 2.5% just prior to death. When comparing all symptom outcomes by place of death, hospital patients are 3.7 times more likely than home patients to have no severe symptoms.Conclusion Symptom outcomes are better for hospital patients. Patients at home have less improvement overall and some symptoms get worse. Reasons for the difference in outcomes by hospital and home are multifactorial and must be considered in relation to the patient’s right to choose their place of care.

Objective To identify diagnostic groups and the form of the trajectory of functional decline that has the potential to enhance advance care planning (ACP) in a nursing home (NH) population. Methods Retrospective, longitudinal study with dependent variable (function) derived from the Resident Classification Scale (RCS), 1997–2008. Trajectory modelling used linear and curvilinear terms. Results The organ failure or other residents have a linear average functional decline. The organ failure residents had an average decline of 6.5 points per year and average function score at death of 68.6, CI [62.4, 74.8]. The cancer and frailty residents had significant curvilinear terms. The frailty residents had a slower rate of decline at 9.54 points per year and were most care dependent at death, with an average function score of 77.1, CI [73.8, 80.9]. Conclusion Functional change is a measurable variable for a predictive tool to enhance ACP for NH residents based on their diagnosis.

© Copyright 2016, Mary Ann Liebert, Inc. 2016. Objective: The aim of this work was to analyze routine assessments recorded, when a patient was documented as likely to die in hours to days, to determine the prevalence, intensity, and associations of physical symptoms. Background: Although death inevitably occurs, very little prospective data describe at population level the physical symptoms confronting imminently dying people. Methods: Using prospectively collected data from participating palliative care services in the Australian Palliative Care Outcomes Collaboration between July 1, 2013, and December 31, 2014, factors associated with worse symptom experiences were explored using logistic regression modeling. Results: The experiences of 18,975 patients who died after being identified as imminently terminal were analyzed, with 75% (n = 14,238) of these being cancer deaths. Seventy percent (n = 13,051) occurred in a palliative care unit, 8.7% (n = 1657) in an acute hospital with palliative care support, and 22.5% (n = 4266) at home. More than half were assessed as experiencing acceptable symptom control especially those with nonmalignant disease. The notable exception was breathing problems, where compared to cancer patients, those with nonmalignant disease were 34% more likely to experience distressing breathlessness (odds ratio 1.34; 95% confidence interval 1.23-147). Regardless of the cause, deaths in a community setting were more likely to be complicated by more severe symptoms with the exception of breathlessness, where those dying in acute hospitals were most likely to be assessed as requiring further help. Discussion: The terminal phase is perceived as a time where the majority will experience distressing symptoms, but this work suggests a contrary view. However, there did seem to be a detrimental effect depending on place of care with more significant problems recorded when people were dying at home. More work is needed to clarify this given the current push for more home deaths.

Background: When capturing patient-level outcomes in palliative care, it is essential to identify which outcome domains are most important and focus efforts to capture these, in order to improve quality of care and minimise collection burden. Aim: To determine which domains of palliative care are most important for measurement of outcomes, and the optimal time period over which these should be measured. Design: An international expert consensus workshop using nominal group technique. Data were analysed descriptively, and weighted according to ranking (1–5, lowest to highest priority) of domains. Participants’ rationales for their choices were analysed thematically. Setting/participants: In all, 33 clinicians and researchers working globally in palliative care outcome measurement participated. Two groups (n = 16; n = 17) answered one question each (either on domains or optimal timing). This workshop was conducted at the 9th World Research Congress of the European Association for Palliative Care in 2016. Results: Participants’ years of experience in palliative care and in outcome measurement ranged from 10.9 to 14.7 years and 5.8 to 6.4 years, respectively. The mean scores (weighted by rank) for the top-ranked domains were ‘overall wellbeing/quality of life’ (2.75), ‘pain’ (2.06), and ‘information needs/preferences’ (2.06), respectively. The palliative measure ‘Phase of Illness’ was recommended as the preferred measure of time period over which the domains were measured. Conclusion: The domains of ‘overall wellbeing/quality of life’, ‘pain’, and ‘information needs/preferences’ are recommended for regular measurement, assessed using ‘Phase of Illness’. International adoption of these recommendations will help standardise approaches to improving the quality of palliative care.

Background Very few measures are used successfully as part of routine care within national palliative care outcome programs. Only a handful of studies examine these measures. The aim of this study is to evaluate the validity of a measure used in a national outcomes program: the Palliative Care Outcomes Collaboration Symptom Assessment Scale (PCOC SAS). Methods A retrospective multi-site cohort study with secondary analysis of routinely collected patient-level data to assess PCOC SAS’s internal consistency, construct validity, reliability, interpretability, acceptability and sensitivity. The analyses used two sets, with data collected by inpatient and community palliative care services registered with the Australian national PCOC. Results Dataset one included 1,117 patients receiving palliative care from 21 services. Dataset two included 5,294 patients receiving palliative care from 119 PCOC services. PCOC SAS demonstrated the ability to detect and discriminate distress by palliative care phase, functional status and diagnosis. Excellent and good convergent and discriminant validity were demonstrated. Fair through to substantial inter-rater and intra-rater reliability levels were evidenced. Sufficient interpretability resulted along with necessary levels of acceptability and sensitivity. Conclusion PCOC SAS is a valid and reliable patient-reported outcome measure suitable for use in routine clinical care with patients requiring palliative and or end-of-life care, including in national outcomes programs.

ObjectiveTo examine hospital use characteristics of a privately insured cohort including hospital setting (public or private), declared insurance status and category of services received during hospital admission. MethodsThe study population consisted of 14276 people with membership of a private health insurance (PHI) fund in New South Wales, Australia. The final study cohort included 9004 people with at least one hospital admission over a 6-year period from 1 January 2010 to 31 December 2015. PHI claims data were linked with public hospital records from a Local Health District. Hospital utilisation measures include number of admissions and length of stay. Measures were categorised by hospital user group (public only, private only or both), declared insurance status (PHI or public patient), type of service and admission case weight. ResultsThe study finds that despite having PHI, 40% of people receive services exclusively in a public hospital in the 6-year study period. Additionally, only 62% of overnight hospital admissions for the study population are claimed on PHI. There are differences in hospital utilisation for medical- and surgical-related admissions. Seventy percent of people with a medical admission receive services only in public hospitals, but a similar proportion of people (66%) receive services only in private hospitals for surgical admissions. ConclusionsPeople with PHI make considerable use of public hospitals both as a public and a private patient. For this privately insured cohort, public hospitals are more frequently used for medical-related admissions and also for more resource-intensive admissions compared with private hospitals. What is known about the topic?There are multiple government incentives to encourage people to take out PHI policies in Australia. Although PHI is closely associated with private hospital utilisation, people with PHI can still use public hospitals as either a public patient, in which the service is fully government-funded, or as a private patient in which PHI contributes funding towards the cost of hospital admissions. What does this paper add?This study provides the first analysis of hospital utilisation of a privately insured cohort in Australia that reports on the interaction between public and private hospital use and declared insurance status, including utilisation differences based on service type. What are the implications for practitioners?Although there are financial incentives offered by the Australian Government to encourage uptake of PHI, the study findings show that people with PHI still make considerable use of public hospitals both as a public and private patient. Future policy reforms relating to the regulation of PHI in Australia should consider the nuanced differences in the way people with PHI use public and private hospitals to optimise resource allocation.

With an ageing population and growing burden of chronic disease, the number of people requiring palliative or end-of-life care (P&EOLC) is set to rise. It is imperative to develop a comprehensive understanding of the quality and equity of P&EOLC provision to promote sustainable health systems. The aim of this presentation is to report an observational study of N=3,171 decedents across a Local Health Network to: 1) estimate the proportion who need, access and miss out on P&EOLC in the last 12 months of life, and 2) identify differences by clinical and sociodemographic characteristics. Analysis was performed on multiple integrated datasets containing routinely collected health and mortality data. Estimation methods based on underlying cause of death were applied to determine those decedents who could potentially benefit from P&EOLC. Results identified potential benefit to 75% of decedents, of which 62% received P&EOLC and 13% missed out. Decedents aged 85 years or more and from a residential aged care facility showed the lowest proportion of access. Decedents with diagnosis of liver or kidney failure and dementia received more P&EOLC than were expected to benefit. Multivariate logistic regression identified that diagnosis and no other clinical or sociodemographic factor was significantly associated with likelihood of accessing specialist palliative care, with cancer showing highest likelihood and heart failure lowest likelihood. This research highlights the value of population-based estimates to provide a ‘whole of system view’ of quality and equity of P&EOLC, with ready translation for service planners around resource allocation for need and likely benefit.

Context Breathlessness is a major cause of suffering and distress, and little is known about the trajectory of breathlessness near death. Objectives To determine the trajectory and clinical-demographic factors associated with breathlessness in the last week of life in patients receiving specialist palliative care. Methods This was a prospective, longitudinal cohort study using national data on specialist palliative care from the Australian Palliative Care Outcomes Collaboration. We included patients in the Australian Palliative Care Outcomes Collaboration who died between July 1, 2013 and June 30, 2014 with at least one measurement of breathlessness on a 0–10 numerical rating scale in the week before death. The trajectory and factors associated with breathlessness were analyzed using multivariate random-effects linear regression. Results A total 12,778 patients from 87 services (33,404 data points) were analyzed. The average observed breathlessness was 2.1 points and remained constant over time. Thirty-five percent reported moderate to severe distress (numerical rating scale ≥4) at some time in their last week. Factors associated with higher breathlessness were younger age, male gender, cardiopulmonary involvement, concurrent fatigue, nausea, pain, sleeping problems, higher Australia-modified Karnofsky Performance Status, and clinical instability in the multivariate analysis. Respiratory failure showed the largest association (mean adjusted difference 3.1 points; 95% confidence interval, 2.8–3.4). Conclusion Although breathlessness has been reported to worsen in the last months, the mean severity remained stable in the final week of life. In specialized palliative care, one in three people experienced significant breathlessness especially in respiratory disease.

Objectives In the increasingly competitive environment of aged care in Australasia, how can providers and consumers be sure that the care support delivered is efficient and makes a positive difference? Monitoring outcomes has long been emphasised for ensuring quality service delivery, yet there is currently no consistently applied approach available. Methods This paper considers the importance of measuring outcomes in community care and reports on the development and field trial of the Australian Community Care Outcomes Measure (ACCOM). The ACCOM combines data already collected by services on the capabilities and care needs of individual consumers and their demographic characteristics with a short questionnaire on quality of life based on the Adult Social Care Outcomes Toolkit (ASCOT). It is completed by consumers and staff. Results In the first round of a field test of the ACCOM (2016), baseline data were successfully collected for over 200 individual aged care clients, each receiving consumer-directed care (CDC) packages at home. Results show the measure to be practical and easy to use. A second round to measure change and enable the calculation of outcomes for each consumer was successfully completed 6 months later. Conclusion Field testing of the ACCOM shows promising results. More extensive trials of the measure are planned across Australia.

Australia has managed the crisis well so far but we should now also plan for future waves and the recovery phase. Coronavirus disease 2019 (COVID-19) pandemic management is focused on prevention, case finding and survival. Australia and New Zealand have done well and the numbers in our intensive care units (ICUs) are currently manageable.

Objective The aim of this study was to assess 15-year trends in unplanned readmissions in an Australian regional health service. Methods Drawing on data held in the Illawarra Health Information Platform (IHIP), this longitudinal retrospective study of adults admitted to hospital between 2001–02 and 2015–16 assessed rates of unplanned all-cause readmissions within 30 days (‘early’) and 1–6 months (‘late’) following discharge. Rates were compared over time and between patient groups. Results Age-adjusted early readmission rates declined over the 15 years by an average of 1.3% per annum, whereas late readmission rates increased by an average of 0.6% per annum. Together, there was an overall decline in readmission rates. The entire decline in early readmission rates and a reversal of the increasing trend in late readmission rates occurred since 2010–11. Similar trends occurred across age groups, but were most pronounced among those aged ≥75 years. Conclusions The decline in readmissions since 2010–11 suggests that the region has achieved improvements in discharge planning and in continuity between hospitals and community-based care. These improvements have occurred across broad patient groups. The longitudinal and linked data held in the IHIP provides a unique opportunity to examine patterns of service utilisation at a regional level. What is known about the topic? Published reports of longitudinal trends in readmissions are typically limited by short study periods and narrow criteria used to define study populations and readmissions. Australian longitudinal data suggest rates of early readmission have remained relatively unchanged in recent years, despite the focus on readmission rates as a metric to assess the quality and continuity of care. What does this paper add? This unique longitudinal study reports on long-term readmission trends over 15 years to hospitals within a single geographic area, with trends reported for both early (30-day) and late (1- to 6-month) readmissions by age group and major diagnostic categories. The findings reflect more complex patterns than are typically reported in cross-sectional and more limited longitudinal studies. What are the implications for practitioners? The results suggest improvements at a regional level that may be associated with care during the initial hospitalisation and discharge (reflected particularly in early readmissions) and in the community (reflected particularly in late readmissions). Future investigations will explore specific patient groups and the effects of specific initiatives, services and models of care to better predict those at risk of readmission and to inform translation locally and further afield. The relationship between readmissions and the use of ambulatory services (primary care, emergency department and out-patient) also warrants further investigation.

IntroductionProvision of palliative care is inequitable with wide variations across conditions and settings in the UK. Lack of a standard way to classify by case complexity is one of the principle obstacles to addressing this. We aim to develop and validate a casemix classification to support the prediction of costs of specialist palliative care provision.Methods and analysisPhase I: A cohort study to determine the variables and potential classes to be included in a casemix classification. Data are collected from clinicians in palliative care services across inpatient hospice, hospital and community settings on: patient demographics, potential complexity/casemix criteria and patient-level resource use. Cost predictors are derived using multivariate regression and then incorporated into a classification using classification and regression trees. Internal validation will be conducted by bootstrapping to quantify any optimism in the predictive performance (calibration and discrimination) of the developed classification. Phase II: A mixed-methods cohort study across settings for external validation of the classification developed in phase I. Patient and family caregiver data will be collected longitudinally on demographics, potential complexity/casemix criteria and patient-level resource use. This will be triangulated with data collected from clinicians on potential complexity/casemix criteria and patient-level resource use, and with qualitative interviews with patients and caregivers about care provision across difference settings. The classification will be refined on the basis of its performance in the validation data set.Ethics and disseminationThe study has been approved by the National Health Service Health Research Authority Research Ethics Committee. The results are expected to be disseminated in 2018 through papers for publication in major palliative care journals; policy briefs for clinicians, commissioning leads and policy makers; and lay summaries for patients and public.Trial registration numberISRCTN90752212.

Background:Caregiver satisfaction and experience surveys help health professionals to understand, measure, and improve the quality of care provided for patients and their families.Objective:Our aim was to explore caregiver perceptions of the care received from Australian specialist palliative care services.Method:Caregivers of patients receiving palliative care in services registered with Australia's Palliative Care Outcomes Collaboration were invited to participate in a caregiver survey. The survey included the FAMCARE–2 and four items from the Ongoing Needs Identification: Caregiver Profile questionnaire.Results:Surveys were completed by 1,592 caregivers from 49 services. Most respondents reported high satisfaction and positive experiences. Caregivers receiving care from community-based palliative care teams were less satisfied with the management of physical symptoms and comfort (odds ratio [OR] = 0.29; 95% confidence interval [CI95%] = 0.14, 0.59), with patient psychological care (OR = 0.56; CI95% = 0.32, 0.98), and with family support (OR = 0.52; CI95% = 0.35, 0.77) than caregivers of patients in an inpatient setting. If aged over 60 years, caregivers were less likely to have their information needs met regarding available support services (OR = 0.98; CI95% = 0.97, 0.98) and carer payments (OR = 0.99; CI95% = 0.98, 1.00). Also, caregivers were less likely to receive adequate information about carer payments if located in an outer regional area (OR = 0.41; CI95% = 0.25, 0.64). With practical training, caregivers receiving care from community services reported inadequate information provision to support them in caring for patients (OR = 0.60; CI95% = 0.45, 0.81).Significance of Results:While our study identified caregivers as having positive and satisfactory experiences across all domains of care, there is room for improvement in the delivery of palliative care across symptom management, as well as patient and caregiver support, especially in community settings. Caregiver surveys can facilitate the identification and evaluation of both patients' and caregivers' experiences, satisfaction, distress, and unmet needs.

Objective To develop and examine a profile of the demographic, hospital admission and clinical characteristics of high users of hospital resources within a cohort of privately insured Australians. Methods Hospital admissions claims data from a group of private health insurance funds were analysed. The top 1% of hospital users were selected based on three measures of resource utilisation: number of admissions, total bed days and total insurance benefits paid. The demographic, hospital admission and clinical characteristics data were compared for these three measures of resource utilisation. Results Compared with the general insured population, the three high-use cohorts are older, have more public hospital admissions and have more same-day admissions. The three high-use cohorts have the same top five principal diagnosis categories. These five categories account for more than two-thirds of admissions. The top 1% of users is responsible for a large proportion of total resource utilisation, accounting for 13% of total costs and 21% of total bed days. Conclusions The highest users of hospital resources have a distinct profile, accounting for a large proportion of total resource utilisation for a narrow range of health conditions. The age and hospital admission profile of this group suggest both policy and service considerations for the targeting of interventions to support this high-needs group. What is known about this topic? Statistics are regularly published on the uptake and use of private health insurance in Australia but there is little detailed information on resource utilisation in specific subgroups, particularly those with the highest levels of hospitalisation. What does this paper add? This paper provides a profile of high resource utilisation among a privately insured cohort, describing demographic, hospital admission and clinical characteristics across three measures of resource utilisation. Patterns of use are detailed in this profile, for example the top 1% of users have a higher proportion of public hospital admissions as a private patient. The clinical profile of admissions was similar for the three measures of resource utilisation and there was considerable overlap in the individuals categorised in each high-use group. What are the implications for practitioners? The narrow demographic and clinical profile of the high resource utilisation groups shows a chronic disease burden that is different to the focus of current chronic disease policy measures. The high-use conditions identified in this study are less amenable to preventive measures and new strategies may be required to target this high-needs group.