Does Geography Play a Role in the Receipt of End-of-Life Care for Advanced Cancer Patients? Evidence from an Australian Local Health District Population-Based Study.

Objectives: To assess the influence of geographic remoteness on health care utilization at end of life (EOL) by people with advanced cancer in a geographically diverse Australian local health district, using two objective measures of rurality and travel-time estimations to health care facilities. Methods: This retrospective cohort study examined the association between rurality (using the Modified Monash Model) and travel-time estimation, and demographic and clinical factors, with the receipt of >1 inpatient and outpatient health service in the last year of life in multivariate models. The study cohort comprised of 3546 patients with cancer, aged ≥18 years, who died in a public hospital between 2015 and 2019. Results: Compared with decedents from metropolitan areas, decedents from some rural areas had higher rates of emergency department visits (small rural towns: aRR 1.29, 95% CI: 1.07-1.57) and ICU admissions (large rural towns: aRR 1.32, 95% CI: 1.03-1.69), but lower rates of acute hospital admissions (large rural towns: aRR 0.83, 95% CI: 0.76-0.90), inpatient palliative care (PC) (regional centers: aRR 0.85, 95% CI: 0.75-0.97), and inpatient radiotherapy (lowest in small rural towns: aRR 0.07, 95% CI: 0.03-0.18). Decedents from rural and regional centers had lower rates of outpatient chemotherapy and radiotherapy use, yet higher rates of outpatient cancer service utilization (p < 0.05). Shorter travel times (10-<30 minutes) were associated with higher rates of inpatient specialist PC (aRR 1.48, 95% CI: 1.09-1.98). Conclusions: Reporting on a series of inpatient and outpatient services used in the last year of life, measures of rurality and travel-time estimates can be useful tools to estimate geographic variation in EOL cancer care provision, with significant gaps uncovered in inpatient PC and outpatient service utilization in rural areas. Policies aimed at redistributing EOL resources in rural and regional communities to reduce travel times to health care facilities could help to reduce regional disparities and ensure equitable access to EOL care services.

Application of mixture distributions for identifying thresholds of frequent and high inpatient mental health service use in longitudinal data.

BACKGROUND: There is a need for greater understanding about frequent and high use of inpatient mental health services, and those with ongoing increased needs. Most studies employ a threshold of frequent use (e.g. numbers of admissions) and high use (e.g. lengthy stays) without justification. AIMS: To identify model-driven thresholds for frequent/high inpatient mental health service use and contrast characteristics of patients identified using various models and thresholds. METHOD: Retrospective population-based study using 12 years of longitudinal data for 5631 patients admitted with a mental health diagnosis. Two-component negative binomial and poisson mixture (truncated/untruncated) models identified thresholds for frequent/high use in a 12-month period. RESULTS: The two-component negative binomial mixture model resulted in the best model fit. Using negative binomial-derived thresholds, 5.3% of patients had a period of frequent use (admitted six or more times), 15.8% of high use (hospitalised for 45 or more days) and 3.5% of heavy use (both frequent and high use). The prevalence of specific mental health disorders (e.g. mood disorder and schizophrenia) among frequent and high use cohorts varied across thresholds. CONCLUSIONS: This model-driven approach can be applied to identify thresholds in other cohorts. Threshold choice may depend on the magnitude and focus of potential interventions.

Patterns of morbidity and multimorbidity associated with early and late readmissions in an Australian regional health service.

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.

Who needs, receives and misses out on palliative and end-of-life care? A population-based study to identify needs and gaps in a regional health service.

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 <65 years (adjusted odds ratio (aOR) 0.44; 95% confidence interval (CI) 0.31-0.64) and those with heart failure (aOR 0.58; 95% CI 0.47-0.72). Conclusions Estimates of need and access provide a sound basis for planning local palliative and end-of-life care services. These methods can be used on an ongoing basis to monitor service delivery. What is known about this topic? There is a small but expanding literature on estimating the need for palliative care at a population level. There is a lack of data regarding access to palliative and other end-of-life care across multiple settings (e.g. home, specialist palliative care unit, hospital) and patient groups (e.g. defined by sociodemographics and diagnostics). What does this paper add? The study builds on previously used methods for estimating the need for palliative care, with some refinements, including the addition of 'other clinical indications' and the use of weights to derive more realistic estimates. The estimates of need are consistent with recent estimates from Australia and overseas, whereas the estimates of access are similar to a recent Australian estimate, but higher than estimates from overseas. The gaps in access are highest among those with the major types of chronic organ failure, particularly heart and respiratory. What are the implications for practitioners? The study demonstrates how routinely collected data at a regional level can be used to estimate need and access to palliative and end-of-life care, in the hospital and in the community. These methods of estimating need and unmet need can be used to inform the planning and development of services, as well as to monitor progress with implementation of changes in service provision.

Predisposing, enabling and need factors associated with increased use and ongoing increased use of inpatient mental health care: A population-based longitudinal study.

OBJECTIVE: The study investigated factors associated with frequent (admissions), high (total length of stay) or heavy (frequent and high) hospital use, and with ongoing increased hospital use, for mental health conditions in a regional health district. METHODS: A retrospective population-based study using longitudinal hospital, emergency department and community service use data for people admitted with a mental health condition between 1 January 2012 and 31 December 2016. Multivariate logistic regression models assessed the association of predisposing, enabling and need factors with increased, and ongoing increased, hospital use. RESULTS: A total of 5,631 people had at least one mental health admission. Frequent admission was associated with not being married (odds ratio = 2.3, 95% confidence interval = [1.5, 3.3]), no private hospital insurance (odds ratio = 2.2, 95% confidence interval = [1.2, 3.8]), previous mental health service use (community, emergency department, lengthy admissions) and a history of a substance use disorder, childhood trauma, self-harm or chronic obstructive pulmonary disease. High and heavy hospital use was associated with marital status, hospital insurance, admission for schizophrenia, previous mental health service use and a history of self-harm. Ongoing frequent use was less likely among those aged 65 and older (odds ratio = 0.2, 95% confidence interval = [0.1, 1.0]) but more likely among those with a history of depression (odds ratio = 2.2, 95% confidence interval = [1.1, 4.4]). Ongoing high use was also associated with admissions for schizophrenia and a history of self-harm. CONCLUSION: Interventions targeted at younger people hospitalised with schizophrenia, a history of depression or self-harm, particularly with evidence of social and or health disadvantage, should be considered to improve long-term consumer and health system outcomes. These data can support policymakers to better understand the context and need for improvements in stepped or staged care for people frequently using inpatient mental health care.

Trends in unplanned readmissions over 15 years: a regional Australian perspective.

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.

Here one year, gone the next? Investigating persistence of frequent emergency department attendance: a retrospective study in Australia.

OBJECTIVES: Patients are presenting to emergency departments (EDs) with increasing complexity at rates beyond population growth and ageing. Intervention studies target patients with 12 months or less of frequent attendance. However, these interventions are not well targeted since most patients do not remain frequent attenders. This paper quantifies temporary and ongoing frequent attendance and contrasts risk factors for each group. DESIGN: Retrospective population-based study using 10 years of longitudinal data. SETTING: An Australian geographic region that includes metropolitan and rural EDs. PARTICIPANTS: 332 100 residents visited any ED during the study period. MAIN OUTCOME MEASURE: Frequent attendance was defined as seven or more visits to any ED in the region within a 12-month period. Temporary frequent attendance was defined as meeting this threshold only once, and ongoing more than once. Risk factors for temporary and ongoing frequent attenders were identified using logistic regression models for adults and children. RESULTS: Of 8577 frequent attenders, 80.1% were temporary and 19.9% ongoing (12.9% repeat, 7.1% persistent). Among adults, ongoing were more likely than temporary frequent attenders to be young to middle aged (aged 25-64 years), and less likely to be from a high socioeconomic area or be admitted. Ongoing frequent attenders had higher rates of non-injury presentations, in particular substance-related (OR=2.5, 99% CI 1.1 to 5.6) and psychiatric illness (OR=2.9, 99% CI 1.8 to 4.6). In comparison, children who were ongoing were more likely than temporary frequent attenders to be aged 5-15 years, and were not more likely to be admitted (OR=2.7, 99% CI 0.7 to 10.9). CONCLUSIONS: Future intervention studies should distinguish between temporary and ongoing frequent attenders, develop specific interventions for each group and include rigorous evaluation.

Impact of body mass index on utilization of selected hospital resources for four common surgical procedures.

BACKGROUND: Evidence about the impact of obesity on surgical resource consumption in the Australian setting is equivocal. Our objectives were to quantify the prevalence of obesity in four frequently performed surgical procedures and explore the association between body mass index (BMI) and hospital resource utilization including procedural duration, length of stay (LOS) and costs. METHODS: A retrospective cohort study of patients undergoing four surgical procedures at a tertiary referral centre in New South Wales, between 1 January 2016 and 31 December 2016, was conducted. The four surgical procedures were total hip replacement, laparoscopic appendectomy, laparoscopic cholecystectomy and hysteroscopy with dilatation and curettage. Surgical groups were stratified according to BMI category. RESULTS: A total of 699 patients were included in the study. The prevalence of obesity was significantly higher than local and national population estimates for all procedures except appendectomy. BMI was not associated with increased hospital resource utilization (procedural, anaesthetic or intensive care stay duration) in any of the four surgical procedures examined after controlling for age, gender and complexity. For other outcomes of hospital resource utilization (LOS and cost), the relationship was inconsistent across the four procedures examined. A high BMI was positively associated with higher LOS, medical costs and allied health costs in those who underwent an appendectomy, and critical care costs in those who underwent laparoscopic cholecystectomy. CONCLUSION: Obesity was common in patients undergoing four frequently performed surgical procedures. The relationship between BMI and hospital resource utilization appears to be complex and varies across the four procedures examined.