Multimorbidity and Health Care Service Utilization in the Australian Workforce: Findings From the National Health Survey

Impact of multimorbidity and complex multimorbidity on healthcare utilisation in older Australian adults aged 45 years or more: a large population-based cross-sectional data linkage study

OBJECTIVES

As life expectancy increases, older people are living longer with multimorbidity (MM, co-occurrence of ≥2 chronic health conditions) and complex multimorbidity (CMM, ≥3 chronic conditions affecting ≥3 different body systems). We assessed the impacts of MM and CMM on healthcare service use in Australia, as little was known about this.

DESIGN

Population-based cross-sectional data linkage study.

SETTING

New South Wales, Australia.

PARTICIPANTS

248 496 people aged ≥45 years who completed the Sax Institute's 45 and Up Study baseline questionnaire.

PRIMARY OUTCOME

High average annual healthcare service use (≥2 hospital admissions, ≥11 general practice visits and ≥2 emergency department (ED) visits) during the 3-year baseline period (year before, year of and year after recruitment).

METHODS

Baseline questionnaire data were linked with hospital, Medicare claims and ED datasets. Poisson regression models were used to estimate adjusted and unadjusted prevalence ratios for high service use with 95% CIs. Using a count of chronic conditions (disease count) as an alternative morbidity metric was requested during peer review.

RESULTS

Prevalence of MM and CMM was 43.8% and 15.5%, respectively, and prevalence increased with age. Across three healthcare settings, MM was associated with a 2.02-fold to 2.26-fold, and CMM was associated with a 1.83-fold to 2.08-fold, increased risk of high service use. The association was higher in the youngest group (45-59 years) versus the oldest group (≥75 years), which was confirmed when disease count was used as the morbidity metric in sensitivity analysis.When comparing impact using three categories with no overlap (no MM/CMM, MM with no CMM, and CMM), CMM had greater impact than MM across all settings.

CONCLUSION

Increased healthcare service use among older adults with MM and CMM impacts on the demand for primary care and hospital services. Which of MM or CMM has greater impact on risk of high healthcare service use depends on the analytic method used. Ageing populations living longer with increasing burdens of MM and CMM will require increased Medicare funding and provision of integrated care across the healthcare system to meet their complex needs.

Healthcare Costs Before and After Diagnosis of Cancer of Unknown Primary Versus Ovarian Cancer in Australia

BACKGROUND

Little is known about the healthcare resource usage and costs for patients with cancer of unknown primary (CUP).

OBJECTIVE

The aim of this study was to describe and quantify healthcare resource use and costs in Australia, 6 months prior to and after a diagnosis of CUP, and compare to those of women with ovarian cancer.

METHODS

Individual-level data combining baseline surveys, clinical records and Medicare Benefits Schedule (MBS) claim records were analysed for 149 patients with CUP and 480 patients with ovarian cancer from two prospective cohort studies. MBS data were aggregated for the period 6 months prior to diagnosis date and 6 months after diagnosis. Data included doctor consultations, pathology, diagnostics, therapeutic procedures, imaging, allied health and medicines. Generalised linear models were used to evaluate the cost differences between CUP and ovarian cancer using gamma family and log link functions. Models were adjusted for age, employment, marital status, surgery, chemotherapy and number of comorbidities.

RESULTS

The mean healthcare costs in the 6 months prior to diagnosis of CUP were Australian (AU) $3903 versus AU$1327 for ovarian cancer (adjusted cost ratio 2.94, 95% confidence interval [CI] 2.08-4.15). Mean healthcare costs 6 months post-diagnosis were higher for patients with CUP versus ovarian cancer (AU$20,339 vs AU$13,819, adjusted cost ratio 1.47, 95% CI 1.13-1.92). Higher costs for patients with CUP were driven by imaging (AU$1937 vs AU$1387), procedures (AU$5403 vs AU$2702) and prescribed medicines for all conditions (AU$10,111 vs AU$6717).

CONCLUSIONS

Pre-diagnosis costs for patients with CUP are nearly triple those for ovarian cancer. Six months after diagnosis, healthcare costs for CUP remained higher than for ovarian cancer due to imaging, procedures and medicines.

Epidemiology of physical-mental multimorbidity and its impact among Aboriginal and Torres Strait Islander in Australia: a cross-sectional analysis of a nationally representative sample

OBJECTIVES

This study aimed to examine the differences in multimorbidity between Aboriginal and Torres Strait Islander people and non-Indigenous Australians, and the effect of multimorbidity on health service use and work productivity.

SETTING

Cross-sectional sample of the Household, Income and Labour Dynamics in Australia wave 17.

PARTICIPANTS

A nationally representative sample of 16 749 respondents aged 18 years and above.

OUTCOME MEASURES

Multimorbidity prevalence and pattern, self-reported health, health service use and employment productivity by Indigenous status.

RESULTS

Aboriginal respondents reported a higher prevalence of multimorbidity (24.2%) compared with non-Indigenous Australians (20.7%), and the prevalence of mental-physical multimorbidity was almost twice as high (16.1% vs 8.1%). Multimorbidity pattern varies significantly among the Aboriginal and non-Indigenous Australians. Multimorbidity was associated with higher health service use (any overnight admission: adjusted OR=1.52, 95% CI=1.46 to 1.58), reduced employment productivity (days of sick leave: coefficient=0.25, 95% CI=0.19 to 0.31) and lower perceived health status (SF6D score: coefficient=-0.04, 95% CI=-0.05 to -0.04). These associations were found to be comparable in both Aboriginal and non-Indigenous populations.

CONCLUSIONS

Multimorbidity prevalence was significantly greater among Aboriginal and Torres Strait Islanders compared with the non-Indigenous population, especially mental-physical multimorbidity. Strategies are required for better prevention and management of multimorbidity for the aboriginal population to reduce health inequalities in Australia.

Non-adherence and sub-optimal treatment with asthma medications in young adults: a population-based cohort study

OBJECTIVE

Pharmacological treatment plays a key role in the management of asthma, but medication adherence is generally low. Our aim was to assess factors associated with dispensing patterns of, and adherence to, asthma medication in young adults with asthma.

METHODS

The study included young adults (age 22-24 years) from the Swedish population-based birth cohort BAMSE (n = 3,064) with linkage to register data on dispensed asthma medications and recorded diagnosis. Dispensing information was collected in January 2014-June 2019 (the study period) to cover the period of questionnaire data. Adherence to asthma medication was defined as refilling a prescription within 18 months.

RESULTS

In total, 234 individuals (7.6%) had asthma (doctor's diagnosis of asthma in combination with respiratory symptoms) and had been dispensed at least one prescription of asthma medication during the study period. Among them, 77% were dispensed a controller medication. The mean number of prescriptions dispensed per individual was higher in males than females (11.0 vs. 7.2; p < 0.01). The proportion of asthmatics with only a short-acting β₂-agonist (SABA) dispensed was 22%, of which 33% were classified as having uncontrolled asthma. Adherence to controller medication was 60% and higher among those with an asthma diagnosis from specialized care than those diagnosed in primary care (RR 1.32 95% CI 1.03-1.69). Sex, socioeconomic status, and non-allergic comorbidity did not affect adherence.

CONCLUSION

Young adults with asthma had few prescriptions of asthma medication dispensed, indicating sub-optimal treatment. A considerable proportion was dispensed only SABA. Furthermore, adherence to controller medication was relatively low.

The Joint Effect of Physical Multimorbidity and Mental Health Conditions Among Adults in Australia

Introduction

The prevalence of chronic physical and mental health conditions is rising globally. Little evidence exists on the joint effect of physical and mental health conditions on health care use, work productivity, and health-related quality of life in Australia.

Methods

We analyzed data from the Household, Income and Labour Dynamics in Australia (HILDA) Survey, waves 9 (2009), 13 (2013), and 17 (2017). Economic effects associated with multimorbidity were measured through health service use, work productivity loss, and health-related quality of life. We used generalized estimating equations to assess the effect of the association between physical multimorbidity and mental health conditions and economic outcomes.

Results

From 2009 through 2017 the prevalence of physical multimorbidity increased from 15.1% to 16.2%, and the prevalence of mental health conditions increased from 11.2% to 17.3%. The number of physical health conditions was associated with the number of health services used (general practitioner visits, incidence rate ratio = 1.41), work productivity loss (labor force participation, adjusted odds ratio = 0.71), and reduced health-related quality of life (SF-6D score: Coefficient = −0.03). These effects were exacerbated by the presence of mental health conditions and low socioeconomic status.

Conclusion

Having multiple physical health conditions (physical multimorbidity) creates substantial health and financial burdens on individuals, the health system, and society, including increased use of health services, loss of work productivity, and decreased health-related quality of life. The adverse effects of multimorbidity on health, quality of life, and economic well-being are exacerbated by the co-occurrence of mental health conditions and low socioeconomic status.

Implications of multimorbidity on healthcare utilisation and work productivity by socioeconomic groups: Cross-sectional analyses of Australia and Japan

BACKGROUND

Multimorbidity, the presence of 2 or more non-communicable diseases (NCDs), is a major contributor to inequalities of health in Australia and Japan. We use nationally representative data to examine (i) the relationships between multimorbidity with healthcare utilisation and productivity loss and (ii) whether these relationships differed by socioeconomic groups.

METHODS

Cross-sectional analyses using the Household, Income, and Labour Dynamics in Australia (HILDA) and the Japanese Study of Aging and Retirement (JSTAR) surveys. We examined 6,382 (HILDA) and 3,503 (JSTAR) adults aged ≥50 years. We applied multivariable regression, logistic and negative binomial models.

RESULTS

Prevalence of multimorbidity was overall 38.6% (46.0%, 36.1%, 28.9% amongst those in the lowest, middle and highest education group, respectively) in Australia, and 28.4% (33.9%, 24.6%, 16.6% amongst those in the lowest, middle and highest education group, respectively) in Japan. In Australia and Japan, more NCDs was associated with greater healthcare utilisation. In Australia and Japan, more NCDs was associated with higher mean number of sick leave days amongst the employed and lower odds of being employed despite being in the labour force. The association between multimorbidity and lower retirement age was found in Australia only.

CONCLUSION

Having more NCDs pose significant economic burden to the health system and wider society in Australia and Japan. Targeted policies are critical to improve financial protection, especially for lower income groups who are more likely to have multiple NCDs. These individuals incur both high direct and indirect costs, which lead to a greater risk of impoverishment.