# Ten-Year Trends and Predictors of Unplanned Hospitalisation in Community-Dwelling Older People Receiving Home-Based Care

Authors: Marissa Dickins; Angela Joe; Judy A. Lowthian
Journal: Health & Social Care in the Community
 (2023)

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## Abstract

Older people prefer to remain living in their own home for as long as possible; however, many require support to do so through health and other care services provided in the home. This study aimed to explore the trends in usage of a home-based care service by older people in metropolitan Melbourne and factors associated with unplanned hospitalisations. This longitudinal study analysed episodes of home-based care for people aged ≥65 years between 2006 and 2015. An episode of care was defined as the period of time during which the home care services were provided to the client. Care episodes culminated in a planned discharge from the service or an unplanned hospitalisation. Descriptive statistics and multivariable logistic regression were utilised to investigate the characteristics associated with unplanned hospitalisations. Utilisation of home-based care services over the 10-year period showed an increasing rate of use by people aged ≥85 years and a reduced usage rate by females aged 70–84 years and males 75–79 years old. Of 170,001 episodes of care, 43,608 (25.7%) resulted in an unplanned hospitalisation. Home-based care delivered to people aged ≥85 years showed an increasing rate of episodes ending in an unplanned transfer to the hospital. Between 2006 and 2015, individuals aged 85–89 years displayed a rate increase of 18.7% in episodes ending in an unplanned hospitalisation; for those aged ≥90 years, the rate rise was 43.6%. Factors associated with an unplanned hospitalisation included advancing age, male gender, living alone, cognitive dysfunction, and the complexity of medical issues. Health policy has focussed on providing services to enable older people to remain in their own home. The increasing rate of unplanned hospitalisations for community-dwellers aged ≥85 years suggests more support is required to enable ageing in place.


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## Body

## 1. Introduction

Older people aged ≥65 years are the fastest growing demographic in Australia [1]. Ageing is strongly associated with increasing dependence on care provided by others [2]. It is vital that a consumer-centred aged care system is in place to support the wellbeing of older persons. Most older Australians reside in a private household; in 2018, this was the case for 95% of all persons aged ≥65 years, including 75% of Australians aged 85 years and older [2]. The majority prefers to remain in their own home for as long as possible [3], with most not transitioning to institutionalised living unless it is unavoidable.Recent changes in the aged care system guided by Living Longer Living Better [4], a 10-year reform plan implemented in 2013, has focussed on home-based formal care for older people. Primary healthcare and community services are tasked with delivering the care needed to sustain older Australians in their home.Acute unplanned hospital admissions represent a distressing event for older people. Older hospitalised patients are at risk of adverse outcomes such as functional decline, loss of mobility [5], unplanned readmissions [6], and earlier death [7]. An unplanned hospitalisation jeopardises an older person’s ability to remain independent, with increased likelihood of needing higher level care upon discharge [8]. Emergency hospitalisations often precipitate an unplanned and urgent move to residential care, leaving an older person feeling displaced, confused, and depressed [8].Strategies to reduce unplanned hospitalisations would not only benefit older people but also help alleviate the demands on acute care hospitals and residential care. Data from community care providers are a rich source of information to monitor the impact of ongoing reforms on older Australians. The present study utilised home-based nursing and personal care data collected between 1 January 2006 and 31 December 2015. This period spans the years preceding implementation of Living Longer Living Better and includes the initial years of aged care reform. The aims of our analyses were to reveal the trends for home-based care across the pre-reform and early reform periods and to explore the risk factors associated with unplanned hospitalisations.


## 2. Methods

This study is reported in accordance with the REporting of studies Conducted using Observational Routinely collected health Data (RECORD) Statement [9].


### 2.1. Study Design and Setting

A retrospective cohort study was conducted utilising routinely collected data from a large not-for-profit provider of home nursing and personal care in Victoria, Australia. The predominant types of care activities conducted in home visits were assessments; nursing care; education, counselling, and support; monitoring and surveillance; and care coordination. Upon admission to the provider, opt-out consent was sought for use of clients’ data for research. Clients who did not opt out had their data de-identified and provided to the research team.Anepisode of care was defined as “a period of health care with a defined start and end” [10] and represented the period of time that a client received nursing or personal care services from the home care provider. Ethics approval was from the Bolton Clarke Human Research Ethics Committee, Approval Number 170003.


### 2.2. Participants and Data Source

Data comprised completed episodes of home-based nursing and personal care between 1 January 2006 and 31 December 2015 for clients aged ≥65 years living in metropolitan Melbourne. Episodes that culminated in a planned discharge from the service (hereafter, a planned discharge) or an unplanned discharge to the hospital (hereafter, an unplanned hospitalisation) were included in the analysis. In a planned discharge, home care ceased and the client continued residing in their own home without further nursing or personal care from the service. This could occur for a range of reasons, including an improvement in their condition or a change in the formal care arrangement (for example, a family member taking over care). In an unplanned hospitalisation, the client was transferred to hospital for acute care with the termination of home-based care. Other types of discharge (for example, to residential care or rehabilitation) were excluded from the analysis.Socioeconomic information included age, gender, living arrangement, primary language, and country of birth. As a socioeconomic status proxy, the Index of Relative Socioeconomic Disadvantage (IRSD) deciles for postal areas in 2016 [11] were linked to clients’ postcodes. Low IRSD values indicate areas of high disadvantage. Service information included contact time with the provider, the source of referral to home care, and the requirement and availability of informal carers. Diagnostic information was available as International Classification of Diseases 10th revision (ICD-10) codes [12]. The Charlson Comorbidity Index (CCI) was used as a proxy for disease burden [13]. A cognitive dysfunction variable was generated by grouping ICD-10 data for cognitive impairment (F06.7, R41.8, and R41.3), senility (R54), Alzheimer’s disease (F00 and G30), and dementia (F01, F02, F03, and G31).


### 2.3. Statistical Analysis

Descriptive statistics compared episodes culminating in an unplanned hospitalisation with episodes ending in a planned discharge. Associations between categorical variables were determined using the chi-squared test for independence. For continuous variables, an independent samplest-test was utilised. A Wilcoxon rank sum test was employed for non-normal distributions. Due to the large sample size, significance was set at p=0.001 [14]. Rates per 1,000 episodes per year and relative rates per year (with 2006 as the base year) were calculated.Multivariable logistic regression was used to identify factors associated with an unplanned hospitalisation. Candidate variables, selected based on the literature and the descriptive analyses, were tested for multicollinearity. Collinearity between two variables, defined asr ≥ 0.3, resulted in the removal of one variable from the analysis. Univariate analyses were conducted, with candidate variables retained if the unadjusted odds ratio wasp<0.1. Multivariable analyses were then undertaken, with the final model run with 1,000 bootstrapped samples drawn with replacement to ensure robust results. Analyses were conducted using Stata 15.1 [15].


## 2.1. Study Design and Setting

A retrospective cohort study was conducted utilising routinely collected data from a large not-for-profit provider of home nursing and personal care in Victoria, Australia. The predominant types of care activities conducted in home visits were assessments; nursing care; education, counselling, and support; monitoring and surveillance; and care coordination. Upon admission to the provider, opt-out consent was sought for use of clients’ data for research. Clients who did not opt out had their data de-identified and provided to the research team.Anepisode of care was defined as “a period of health care with a defined start and end” [10] and represented the period of time that a client received nursing or personal care services from the home care provider. Ethics approval was from the Bolton Clarke Human Research Ethics Committee, Approval Number 170003.


## 2.2. Participants and Data Source

Data comprised completed episodes of home-based nursing and personal care between 1 January 2006 and 31 December 2015 for clients aged ≥65 years living in metropolitan Melbourne. Episodes that culminated in a planned discharge from the service (hereafter, a planned discharge) or an unplanned discharge to the hospital (hereafter, an unplanned hospitalisation) were included in the analysis. In a planned discharge, home care ceased and the client continued residing in their own home without further nursing or personal care from the service. This could occur for a range of reasons, including an improvement in their condition or a change in the formal care arrangement (for example, a family member taking over care). In an unplanned hospitalisation, the client was transferred to hospital for acute care with the termination of home-based care. Other types of discharge (for example, to residential care or rehabilitation) were excluded from the analysis.Socioeconomic information included age, gender, living arrangement, primary language, and country of birth. As a socioeconomic status proxy, the Index of Relative Socioeconomic Disadvantage (IRSD) deciles for postal areas in 2016 [11] were linked to clients’ postcodes. Low IRSD values indicate areas of high disadvantage. Service information included contact time with the provider, the source of referral to home care, and the requirement and availability of informal carers. Diagnostic information was available as International Classification of Diseases 10th revision (ICD-10) codes [12]. The Charlson Comorbidity Index (CCI) was used as a proxy for disease burden [13]. A cognitive dysfunction variable was generated by grouping ICD-10 data for cognitive impairment (F06.7, R41.8, and R41.3), senility (R54), Alzheimer’s disease (F00 and G30), and dementia (F01, F02, F03, and G31).


## 2.3. Statistical Analysis

Descriptive statistics compared episodes culminating in an unplanned hospitalisation with episodes ending in a planned discharge. Associations between categorical variables were determined using the chi-squared test for independence. For continuous variables, an independent samplest-test was utilised. A Wilcoxon rank sum test was employed for non-normal distributions. Due to the large sample size, significance was set at p=0.001 [14]. Rates per 1,000 episodes per year and relative rates per year (with 2006 as the base year) were calculated.Multivariable logistic regression was used to identify factors associated with an unplanned hospitalisation. Candidate variables, selected based on the literature and the descriptive analyses, were tested for multicollinearity. Collinearity between two variables, defined asr ≥ 0.3, resulted in the removal of one variable from the analysis. Univariate analyses were conducted, with candidate variables retained if the unadjusted odds ratio wasp<0.1. Multivariable analyses were then undertaken, with the final model run with 1,000 bootstrapped samples drawn with replacement to ensure robust results. Analyses were conducted using Stata 15.1 [15].


## 3. Results

The number of care episodes analysed was 170,001. Across all episodes of care the average age of clients was 80.2 years (SD 7.8) and 55% of episodes were for a female (Tables1 and 2). Of the episodes of home-based care, 49% involved a client who lived with family members; 33% of care delivery was to a person who lived alone. Eighteen percent of episodes were associated with persons residing in an area of high socioeconomic disadvantage in metropolitan Melbourne.Table 1
Characteristics of the clients in 170,001 episodes of home-based care, by discharge type, 1 January 2006 to 31 December 2015.
Client attributesUnplanned hospitalisationPlanned dischargeTotaln%n%n%Number of episodes43,60826126,39374170,001100Number of unique clients27,98581,01694,200†Age (mean, standard deviation)∗81.5 (7.8)79.8 (7.8)80.2 (7.8)Age categories∗∗65–693,760915,2881219,0481170–745,2261219,2561524,4821475–797,5411725,1202032,6611980–8410,1992329,1302339,3292385–8910,1542323,7901933,9442090+6,7281513,8091120,53712Missing000000Gender∗∗Female23,0085371,3235694,33155Male20,5984755,0494475,64744Others/not stated20210230Missing000000Living arrangements∗∗Alone16,7413838,9613155,70233Special purpose accommodation1,61142,12023,7312With family21,0104862,8895083,89949With others who are not family98922,31923,3082Missing3,257720,1041623,36114Index of Socioeconomic Disadvantage (IRSD) quintiles∗∗1 (high disadvantage)7,2941723,8131931,1071825,2961215,7021220,9981236,8931620,5371627,43016410,0802330,4942440,574245 (low disadvantage)14,0313235,8222849,85329Missing140250390†Of the total number of unique clients, 56,120 (60%) had 1 episode only during the study period; 38,080 people (40%) had multiple episodes; ∗p<0.0001 (t-test for independent samples); ∗∗p<0.0001 (chi-square test for independent samples).Table 2
Detailed characteristics of the clients in 170,001 episodes of home-based care, by discharge type, 1 January 2006 to 31 December 2015.
Client attributesUnplanned hospitalisationPlanned discharge homeTotaln%n%n%Number of episodes43,60825.7126,39374.3170,001100Number of unique clients27,98581,01694,200§Age (mean, standard deviation)∗81.5 (7.8)79.8 (7.8)80.2 (7.8)Age categories∗∗65–693,7608.615,28812.119,04811.270–745,2261219,25615.224,48214.475–797,54117.325,12019.932,66119.280–8410,19923.429,13023.139,32923.185–8910,15423.323,79018.833,9442090+6,72815.413,80910.920,53712.1Missing000000Gender∗∗Female23,00852.871,32356.494,33155.5Male20,59847.255,04943.675,64744.5Other/not stated20210230Missing000000Living arrangements∗∗Alone16,74138.438,96130.955,70232.8Special purpose accommodation1,6113.72,1201.73,7312.2With family21,01048.262,88949.883,89949.2With others who are not family9892.32,3191.83,3081.9Missing3,2577.520,10415.923,36113.7Index of socioeconomic disadvantage (IRSD) quintiles∗∗1 (high disadvantage)7,29416.723,81318.831,10718.325,29612.115,70212.420,99812.436,89315.820,53716.327,43016.1410,08023.130,49424.140,57423.95 (low disadvantage)14,03132.235,82228.349,85329.3Missing140250390Language^∗∗English35,3218197,12676.8132,44777.9Eastern Asian languages2100.51,22011,4300.8Eastern European languages1,9334.45,6434.57,5764.5Northern European languages (excl. English)2300.56040.58340.5South-East Asian languages2000.51,3571.11,5570.9Southern Asian languages720.23090.23810.2Southern European languages4,74010.915,06411.919,80411.7Southwest and Central Asian languages4851.11,7431.42,2281.3Australian indigenous languages10160170Other660.22610.23270.2Supplementary codes300.11520.11820.1Missing3200.72,8982.33,2181.9Country of birth^∗∗Australia25,52958.563,92150.689,45052.6Southern and Eastern Europe9,45721.729,25123.138,70822.8North-West Europe4,80711.013,42510.618,23210.7North Africa and the Middle East8291.92,6182.13,4472.0South-East Asia3780.92,0461.62,4241.4Southern and Central Asia5351.22,0811.72,6161.5North-East Asia2170.51,0650.81,2820.8Oceania and Antarctica (excl. Australia)2650.69580.81,2230.7Sub-Saharan Africa2570.68970.71,1540.7Americas2140.57890.61,0030.6Other400.11110.11510.1Missing1,0802.59,2317.310,3116.1§Of the total number of unique clients, 56,120 (59.6%) had 1 episode only during the study period; 38,080 people (40.4%) had multiple episodes; ^Collapsed to binary variable (Language: English versus Other; Country of birth: Australia versus Other) for significance testing; ∗p<0.0001 (t-test for independent samples); ∗∗p<0.0001 (chi-square test for independent samples).


### 3.1. Trends and Characteristics Associated with Episodes of Care

Over the 10-year period, females aged 75–79 years and males aged ≥90 years exhibited the greatest change in demand for home care (Figures1(a) and 1(b)). Comparing 2006 to 2015, females aged 75–79 years showed a 26% decrease in the rate of home care usage (Figure 1(c)). Males in this age group also showed a steady decline in utilisation of home-based services, with a 17% reduction over the 10 year period (Figure 1(d)). In contrast, the rate of episodes of home care for males aged ≥90 years increased by 67% (Figure 1(d)).Figure 1
Rates of utilisation of home-based care services by gender and age group, metropolitan Melbourne, 1 January 2006 to 31 December 2015. (a) Female utilisation rate per 1000 episodes. (b) Male utilisation rate per 1000 episodes. (c) Females, relative rates of utilisation. (d) Males, relative rates of utilisation. Number of episodes per year: 2006,n = 11,832; 2007, n = 14,180; 2008, n = 14,535; 2009, n = 15,950; 2010, n = 16,401; 2011, n = 17,901; 2012, n = 19,630; 2013, n = 20,010; 2014, n = 20,557; 2015, n = 19,005.
(a)(b)(c)(d)Of the total number of care episodes, 26% (n = 43,608) resulted in an unplanned hospitalisation. An unplanned hospitalisation was more likely in episodes comprising individuals who were older, of the male gender, living alone or in special purpose accommodation, spoke English as their primary language, and who were born in Australia (Tables 1 and 2).Care episodes ending in an unplanned hospitalisation, rather than a planned discharge, were associated with 2.7 times more contact time with home care staff (median hours of care: 14.5 hours vs. 5.4 hours per episode;p<0.0001) (Tables 3 and 4). Episodes involving individuals who required a carer (regardless of carer status), who were referred to home-based care by a palliative care team, or who had a higher number of diagnoses were more likely to conclude with an unplanned hospitalisation. The median CCI score was identical for episodes culminating in unplanned hospitalisation or planned discharge; however, there was a statistically significant difference in the distribution of scores for these discharge groups, such that higher CCI scores had a greater likelihood of an unplanned hospitalisation. Episodes resulting in an unplanned hospitalisation were more likely for clients experiencing cognitive dysfunction.Table 3
Characteristics of the care needs and client diagnoses in 170,001 episodes of home-based care, by discharge type, 1 January 2006 to 31 December 2015.
Home care requirement or client diagnoses informationUnplanned hospitalisationPlanned dischargeTotaln%n%n%Number of episodes43,60826126,39374170,001100Number of unique clients27,98581,01694,200Total hours of home care contact time, median (IQR)∗14.5 (31.3)5.43 (8.53)6.74 (12.59)Source of referral for home-based care∗∗Hospital19,0394456,2764475,31544.3Individuals5,6171314,7511220,36812Subacute care7,4221720,2971627,71916.3Doctor4,8371113,3091018,14610.7Others6,6931521,7601728,45316.7Missing000000Carer requirement/availability∗∗Carer not required7,3021732,0262539,32823No carer (carer required)10,8032523,1181833,92120Has informal carer22,0825150,1124072,19442Missing3,4218211371724,55814Number of diagnoses, median (IQR)∗5 (3)4 (3)5 (3)Charlson Comorbidity Index, median (IQR)∗1 (2)1 (1)1 (1)Presence of cognitive dysfunction∗∗6,3331414,0361120,36912∗p<0.0001 (Wilcoxon rank sum test); ∗∗p<0.0001 (chi-square test for independent samples).Table 4
Detailed characteristics of the care needs and client diagnoses in 170,001 episodes of home-based care, by discharge type, 1 January 2006 to 31 December 2015.
Unplanned hospitalisationPlanned discharge homeTotaln%n%n%Number of episodes43,60825.7126,39374.3170,001100Number of unique clients27,98581,01694,200Total hours of home care contact time, median (IQR)§14.5 (31.3)5.43 (8.53)6.74 (12.59)Source of referral for home-based care∗∗Hospital19,03943.756,27644.575,31544.3Individuals5,61712.914,75111.720,36812Subacute care7,4221720,29716.127,71916.3Doctor4,83711.113,30910.518,14610.7Government and referral services1,0072.35,7654.66,7724Palliative care2,0434.73,9353.15,9783.5Residential aged care4861.11,4331.11,9191.1Other3,1577.210,6278.413,7848.1Missing000000Carer requirement/availability∗∗Carer not required7,30216.732,02625.339,32823.1No carer (carer required)10,80324.823,11818.333,92120Has informal carer22,08250.750,11239.772,19442.5Missing3,4217.82113716.724,55814.5Number of diagnoses, median (IQR)§5 (3)4 (3)5 (3)Charlson Comorbidity Index, median (IQR)§1 (2)1 (1)1 (1)Presence of cognitive dysfunction∗∗6,33314.5214,03611.1120,36911.98ICD-10 chapterChapter 1: Certain infectious and parasitic diseases∗∗1,2692.93,1082.54,3772.6Chapter 2: Neoplasms∗∗8,82320.220,48416.229,30717.2Chapter 3: Diseases of the blood and blood-forming organs and certain disorders involving the immune mechanism∗∗2,2385.14,2993.46,5373.9Chapter 4: Endocrine, nutritional, and metabolic diseases∗∗17,06539.143,74934.660,81435.8Chapter 5: Mental and behavioural disorders∗∗9,35621.521,99017.431,34618.4Chapter 6: Diseases of the nervous system∗∗5,67313.015,16712.020,84012.3Chapter 7: Diseases of the eye and adnexa∗∗4,1549.510,1998.114,3538.4Chapter 8: Diseases of the ear and mastoid process1,8644.35,3204.27,1844.2Chapter 9: Diseases of the circulatory system∗∗27,05662.069,02254.696,07856.5Chapter 10: Diseases of the respiratory system∗∗7,81017.918,43114.626,24115.4Chapter 11: Diseases of the digestive system∗∗7,09416.322,65917.929,75317.5Chapter 12: Diseases of the skin and subcutaneous tissue∗∗13,19130.328,43622.541,62724.5Chapter 13: Diseases of the musculoskeletal system and connective tissue11,48426.333,75626.745,24026.6Chapter 14: Diseases of the genitourinary system∗∗8,44619.418,13214.426,57815.6Chapter 15: Pregnancy, childbirth and the puerperium00.000.000.0Chapter 16: Certain conditions originating in the perinatal period50.0110.0160.0Chapter 17: Congenital malformations, deformations, and chromosomal abnormalities∗1250.32610.23860.2Chapter 18: Symptoms, signs, and abnormal clinical and laboratory findings, not elsewhere classified∗∗14,63133.640,97532.455,60632.7Chapter 19: Injury, poisoning, and certain other consequences of external causes∗∗11,11725.531,06724.642,18424.8Chapter 20: External causes of morbidity and mortality1780.46090.57870.5Chapter 21: Factors influencing health status and contact with health services∗∗9,86122.629,99423.739,85523.4Chapter 22: Codes for special purposes00.000.000.0§p<0.0001 (Wilcoxon rank sum test); ∗∗p<0.0001 (chi-square test for independent samples).


### 3.2. Rates of Discharge

Discharge rates per 1,000 episodes and relative rates across the 10-year period are presented in Figure2. Rates of planned discharge, for all ages, were 746 and 735 per 1,000 care episodes in 2006 and 2015, respectively. Unplanned hospitalisation rates, for all ages, were 254 and 265 per 1,000 episodes for 2006 and 2015, respectively (Figure 2(a)). Discharge rates relative to those in 2006, for both planned discharge and unplanned hospitalisation, appeared comparatively stable over 10 years (Figure 2(b)). However, further investigation disclosed these trends were nuanced by age.Figure 2
Rates of discharge from home-based care, metropolitan Melbourne, 1 January 2006 to 31 December 2015. (a) Discharge of persons aged ≥65 years, rates. (b) Discharge of persons aged ≥65 years, relative rates. (c) Planned discharge, relative rates by age group. (d) Unplanned hospitalisation, relative rates by age group.
(a)(b)(c)(d)Stratification of data by age revealed distinct patterns for different age groups (Figures2(c) and 2(d)). For both discharge types, relative rates remained comparatively stable for the youngest age groups (65–69; 70–74 years) and decreased for the middle age groups (75–79; 80–84 years). In contrast, from 2006 to 2015, home-based care for individuals aged 85–89 years showed a 25% increase in the rate of planned discharge and a 19% increase in the rate of unplanned hospitalisation. For people aged ≥90 years, there were rate increases of 27% and 44% in planned discharge and unplanned hospitalisation, respectively.


### 3.3. Factors Associated with Unplanned Hospitalisation

Adjusted Odds Ratios (ORad) showed episodes resulting in an unplanned hospitalisation differed to those ending in a planned discharge in several characteristics (χ2 (31, N = 142,121) = 17,048.19, and p<0.001) (Figure 3; Table 5).Figure 3
Multivariable logistic regression (1,000 bootstrapped samples) modelling the factors associated with an unplanned hospitalisation. OR, odds ratio; CI, confidence interval; IRSD, Index of Relative Socioeconomic Disadvantage.Table 5
Logistic regression modelling of factors associated with an unplanned hospitalisation. Abbreviations: OR = odds ratio, CI = confidence interval, IRSD = index of relative socioeconomic disadvantage.
UnivariateMultivariableMultivariable (bootstrapped 1,000 samples)OR95% CIOR95% CIOR95% CIUnique client identifier number0.990.990.990.990.990.990.990.990.99Charlson Comorbidity Index Score1.261.251.271.211.201.221.211.201.22Total hours of home care contact time2.072.052.091.971.952.001.971.952.00Age group65–691.001.001.0070–741.101.051.161.101.041.161.101.041.1675–791.221.171.281.151.091.211.151.091.2180–841.421.361.481.291.231.361.291.231.3685–891.741.661.811.511.441.591.511.441.5990+1.981.892.071.731.631.821.731.631.83GenderFemale1.001.001.00Male1.161.131.191.321.291.361.321.291.36Other/not stated0.30a0.071.260.28c0.042.260.28f0.080.98Referral sourceHospital1.001.001.00Individuals1.131.071.170.870.840.910.870.830.91Doctor1.071.041.110.720.690.750.720.690.75Palliative care1.531.451.621.211.131.291.211.131.30Subacute care1.081.051.120.930.890.960.930.890.96Government and referral services0.520.480.550.510.470.550.510.480.55Residential aged care1.00b0.901.110.790.700.890.790.700.89Other0.880.840.920.740.700.780.740.700.78Carer situationCarer not required1.001.001.00No carer (carer required)2.051.982.121.501.441.551.501.441.55Has informal carer1.931.881.991.731.671.791.731.671.79Living situationFamily1.001.001.00Alone1.291.261.321.221.181.261.221.191.26Special purpose accommodation2.272.132.431.911.772.061.911.772.05Others (non-family)1.281.181.381.211.121.321.211.111.32IRSD quintiles1 (low disadvantage)1.001.001.0021.101.061.151.02d0.981.071.02g0.971.0831.101.061.141.091.041.141.091.041.1441.081.041.121.02e0.981.061.02h0.981.065 (high disadvantage)1.281.241.321.101.061.141.101.051.14LanguageEnglish1.001.001.00Language other than English0.830.810.850.880.850.910.880.850.91Cognitive dysfunctionNot present1.001.001.00Present1.361.321.41.091.051.131.091.051.13p values all <0.001 unless specified; ap=0.099, bp=0.963, cp=0.234, dp=0.316, ep=0.329, fp=0.046, gp=0.345, hp=0.341.Total contact time with home care staff (ORad: 1.97, 95% CI: 1.95–2.00) was a significant predictor of an unplanned hospitalisation. The need for a carer (that is, has carer ORad: 1.73, 95% CI: 1.67–1.79; no carer although one was required ORad: 1.50, 95% CI: 1.44–1.55) and male gender (ORad: 1.32, 95% CI: 1.29–1.36) also raised the odds of this discharge type. Increased odds of an unplanned hospitalisation were associated with age (ranging from ORad: 1.10, 95% CI: 1.04–1.16 for clients aged 70–74, to ORad: 1.73, 95% CI: 1.63–1.83 for those aged ≥90) and if the client was not living with family (that is, in special purpose accommodation ORad: 1.91, 95% CI: 1.77–2.05; living alone ORad: 1.22, 95% CI: 1.19–1.26; living with others (non-family) ORad: 1.21, 95% CI: 1.11–1.32). Other risk factors for an unplanned hospitalisation were cognitive dysfunction (ORad: 1.09, 95% CI: 1.05–1.13), a high CCI score (ORad: 1.21, 95% CI: 1.20–1.22), or a referral to home-based care by a palliative care team (ORad: 1.21, 95% CI: 1.13–1.30). Primary language other than English (ORad: 0.88, 95% CI: 0.85–0.91) was associated with lower odds of an unplanned hospitalisation.


## 3.1. Trends and Characteristics Associated with Episodes of Care

Over the 10-year period, females aged 75–79 years and males aged ≥90 years exhibited the greatest change in demand for home care (Figures1(a) and 1(b)). Comparing 2006 to 2015, females aged 75–79 years showed a 26% decrease in the rate of home care usage (Figure 1(c)). Males in this age group also showed a steady decline in utilisation of home-based services, with a 17% reduction over the 10 year period (Figure 1(d)). In contrast, the rate of episodes of home care for males aged ≥90 years increased by 67% (Figure 1(d)).Figure 1
Rates of utilisation of home-based care services by gender and age group, metropolitan Melbourne, 1 January 2006 to 31 December 2015. (a) Female utilisation rate per 1000 episodes. (b) Male utilisation rate per 1000 episodes. (c) Females, relative rates of utilisation. (d) Males, relative rates of utilisation. Number of episodes per year: 2006,n = 11,832; 2007, n = 14,180; 2008, n = 14,535; 2009, n = 15,950; 2010, n = 16,401; 2011, n = 17,901; 2012, n = 19,630; 2013, n = 20,010; 2014, n = 20,557; 2015, n = 19,005.
(a)(b)(c)(d)Of the total number of care episodes, 26% (n = 43,608) resulted in an unplanned hospitalisation. An unplanned hospitalisation was more likely in episodes comprising individuals who were older, of the male gender, living alone or in special purpose accommodation, spoke English as their primary language, and who were born in Australia (Tables 1 and 2).Care episodes ending in an unplanned hospitalisation, rather than a planned discharge, were associated with 2.7 times more contact time with home care staff (median hours of care: 14.5 hours vs. 5.4 hours per episode;p<0.0001) (Tables 3 and 4). Episodes involving individuals who required a carer (regardless of carer status), who were referred to home-based care by a palliative care team, or who had a higher number of diagnoses were more likely to conclude with an unplanned hospitalisation. The median CCI score was identical for episodes culminating in unplanned hospitalisation or planned discharge; however, there was a statistically significant difference in the distribution of scores for these discharge groups, such that higher CCI scores had a greater likelihood of an unplanned hospitalisation. Episodes resulting in an unplanned hospitalisation were more likely for clients experiencing cognitive dysfunction.Table 3
Characteristics of the care needs and client diagnoses in 170,001 episodes of home-based care, by discharge type, 1 January 2006 to 31 December 2015.
Home care requirement or client diagnoses informationUnplanned hospitalisationPlanned dischargeTotaln%n%n%Number of episodes43,60826126,39374170,001100Number of unique clients27,98581,01694,200Total hours of home care contact time, median (IQR)∗14.5 (31.3)5.43 (8.53)6.74 (12.59)Source of referral for home-based care∗∗Hospital19,0394456,2764475,31544.3Individuals5,6171314,7511220,36812Subacute care7,4221720,2971627,71916.3Doctor4,8371113,3091018,14610.7Others6,6931521,7601728,45316.7Missing000000Carer requirement/availability∗∗Carer not required7,3021732,0262539,32823No carer (carer required)10,8032523,1181833,92120Has informal carer22,0825150,1124072,19442Missing3,4218211371724,55814Number of diagnoses, median (IQR)∗5 (3)4 (3)5 (3)Charlson Comorbidity Index, median (IQR)∗1 (2)1 (1)1 (1)Presence of cognitive dysfunction∗∗6,3331414,0361120,36912∗p<0.0001 (Wilcoxon rank sum test); ∗∗p<0.0001 (chi-square test for independent samples).Table 4
Detailed characteristics of the care needs and client diagnoses in 170,001 episodes of home-based care, by discharge type, 1 January 2006 to 31 December 2015.
Unplanned hospitalisationPlanned discharge homeTotaln%n%n%Number of episodes43,60825.7126,39374.3170,001100Number of unique clients27,98581,01694,200Total hours of home care contact time, median (IQR)§14.5 (31.3)5.43 (8.53)6.74 (12.59)Source of referral for home-based care∗∗Hospital19,03943.756,27644.575,31544.3Individuals5,61712.914,75111.720,36812Subacute care7,4221720,29716.127,71916.3Doctor4,83711.113,30910.518,14610.7Government and referral services1,0072.35,7654.66,7724Palliative care2,0434.73,9353.15,9783.5Residential aged care4861.11,4331.11,9191.1Other3,1577.210,6278.413,7848.1Missing000000Carer requirement/availability∗∗Carer not required7,30216.732,02625.339,32823.1No carer (carer required)10,80324.823,11818.333,92120Has informal carer22,08250.750,11239.772,19442.5Missing3,4217.82113716.724,55814.5Number of diagnoses, median (IQR)§5 (3)4 (3)5 (3)Charlson Comorbidity Index, median (IQR)§1 (2)1 (1)1 (1)Presence of cognitive dysfunction∗∗6,33314.5214,03611.1120,36911.98ICD-10 chapterChapter 1: Certain infectious and parasitic diseases∗∗1,2692.93,1082.54,3772.6Chapter 2: Neoplasms∗∗8,82320.220,48416.229,30717.2Chapter 3: Diseases of the blood and blood-forming organs and certain disorders involving the immune mechanism∗∗2,2385.14,2993.46,5373.9Chapter 4: Endocrine, nutritional, and metabolic diseases∗∗17,06539.143,74934.660,81435.8Chapter 5: Mental and behavioural disorders∗∗9,35621.521,99017.431,34618.4Chapter 6: Diseases of the nervous system∗∗5,67313.015,16712.020,84012.3Chapter 7: Diseases of the eye and adnexa∗∗4,1549.510,1998.114,3538.4Chapter 8: Diseases of the ear and mastoid process1,8644.35,3204.27,1844.2Chapter 9: Diseases of the circulatory system∗∗27,05662.069,02254.696,07856.5Chapter 10: Diseases of the respiratory system∗∗7,81017.918,43114.626,24115.4Chapter 11: Diseases of the digestive system∗∗7,09416.322,65917.929,75317.5Chapter 12: Diseases of the skin and subcutaneous tissue∗∗13,19130.328,43622.541,62724.5Chapter 13: Diseases of the musculoskeletal system and connective tissue11,48426.333,75626.745,24026.6Chapter 14: Diseases of the genitourinary system∗∗8,44619.418,13214.426,57815.6Chapter 15: Pregnancy, childbirth and the puerperium00.000.000.0Chapter 16: Certain conditions originating in the perinatal period50.0110.0160.0Chapter 17: Congenital malformations, deformations, and chromosomal abnormalities∗1250.32610.23860.2Chapter 18: Symptoms, signs, and abnormal clinical and laboratory findings, not elsewhere classified∗∗14,63133.640,97532.455,60632.7Chapter 19: Injury, poisoning, and certain other consequences of external causes∗∗11,11725.531,06724.642,18424.8Chapter 20: External causes of morbidity and mortality1780.46090.57870.5Chapter 21: Factors influencing health status and contact with health services∗∗9,86122.629,99423.739,85523.4Chapter 22: Codes for special purposes00.000.000.0§p<0.0001 (Wilcoxon rank sum test); ∗∗p<0.0001 (chi-square test for independent samples).


## 3.2. Rates of Discharge

Discharge rates per 1,000 episodes and relative rates across the 10-year period are presented in Figure2. Rates of planned discharge, for all ages, were 746 and 735 per 1,000 care episodes in 2006 and 2015, respectively. Unplanned hospitalisation rates, for all ages, were 254 and 265 per 1,000 episodes for 2006 and 2015, respectively (Figure 2(a)). Discharge rates relative to those in 2006, for both planned discharge and unplanned hospitalisation, appeared comparatively stable over 10 years (Figure 2(b)). However, further investigation disclosed these trends were nuanced by age.Figure 2
Rates of discharge from home-based care, metropolitan Melbourne, 1 January 2006 to 31 December 2015. (a) Discharge of persons aged ≥65 years, rates. (b) Discharge of persons aged ≥65 years, relative rates. (c) Planned discharge, relative rates by age group. (d) Unplanned hospitalisation, relative rates by age group.
(a)(b)(c)(d)Stratification of data by age revealed distinct patterns for different age groups (Figures2(c) and 2(d)). For both discharge types, relative rates remained comparatively stable for the youngest age groups (65–69; 70–74 years) and decreased for the middle age groups (75–79; 80–84 years). In contrast, from 2006 to 2015, home-based care for individuals aged 85–89 years showed a 25% increase in the rate of planned discharge and a 19% increase in the rate of unplanned hospitalisation. For people aged ≥90 years, there were rate increases of 27% and 44% in planned discharge and unplanned hospitalisation, respectively.


## 3.3. Factors Associated with Unplanned Hospitalisation

Adjusted Odds Ratios (ORad) showed episodes resulting in an unplanned hospitalisation differed to those ending in a planned discharge in several characteristics (χ2 (31, N = 142,121) = 17,048.19, and p<0.001) (Figure 3; Table 5).Figure 3
Multivariable logistic regression (1,000 bootstrapped samples) modelling the factors associated with an unplanned hospitalisation. OR, odds ratio; CI, confidence interval; IRSD, Index of Relative Socioeconomic Disadvantage.Table 5
Logistic regression modelling of factors associated with an unplanned hospitalisation. Abbreviations: OR = odds ratio, CI = confidence interval, IRSD = index of relative socioeconomic disadvantage.
UnivariateMultivariableMultivariable (bootstrapped 1,000 samples)OR95% CIOR95% CIOR95% CIUnique client identifier number0.990.990.990.990.990.990.990.990.99Charlson Comorbidity Index Score1.261.251.271.211.201.221.211.201.22Total hours of home care contact time2.072.052.091.971.952.001.971.952.00Age group65–691.001.001.0070–741.101.051.161.101.041.161.101.041.1675–791.221.171.281.151.091.211.151.091.2180–841.421.361.481.291.231.361.291.231.3685–891.741.661.811.511.441.591.511.441.5990+1.981.892.071.731.631.821.731.631.83GenderFemale1.001.001.00Male1.161.131.191.321.291.361.321.291.36Other/not stated0.30a0.071.260.28c0.042.260.28f0.080.98Referral sourceHospital1.001.001.00Individuals1.131.071.170.870.840.910.870.830.91Doctor1.071.041.110.720.690.750.720.690.75Palliative care1.531.451.621.211.131.291.211.131.30Subacute care1.081.051.120.930.890.960.930.890.96Government and referral services0.520.480.550.510.470.550.510.480.55Residential aged care1.00b0.901.110.790.700.890.790.700.89Other0.880.840.920.740.700.780.740.700.78Carer situationCarer not required1.001.001.00No carer (carer required)2.051.982.121.501.441.551.501.441.55Has informal carer1.931.881.991.731.671.791.731.671.79Living situationFamily1.001.001.00Alone1.291.261.321.221.181.261.221.191.26Special purpose accommodation2.272.132.431.911.772.061.911.772.05Others (non-family)1.281.181.381.211.121.321.211.111.32IRSD quintiles1 (low disadvantage)1.001.001.0021.101.061.151.02d0.981.071.02g0.971.0831.101.061.141.091.041.141.091.041.1441.081.041.121.02e0.981.061.02h0.981.065 (high disadvantage)1.281.241.321.101.061.141.101.051.14LanguageEnglish1.001.001.00Language other than English0.830.810.850.880.850.910.880.850.91Cognitive dysfunctionNot present1.001.001.00Present1.361.321.41.091.051.131.091.051.13p values all <0.001 unless specified; ap=0.099, bp=0.963, cp=0.234, dp=0.316, ep=0.329, fp=0.046, gp=0.345, hp=0.341.Total contact time with home care staff (ORad: 1.97, 95% CI: 1.95–2.00) was a significant predictor of an unplanned hospitalisation. The need for a carer (that is, has carer ORad: 1.73, 95% CI: 1.67–1.79; no carer although one was required ORad: 1.50, 95% CI: 1.44–1.55) and male gender (ORad: 1.32, 95% CI: 1.29–1.36) also raised the odds of this discharge type. Increased odds of an unplanned hospitalisation were associated with age (ranging from ORad: 1.10, 95% CI: 1.04–1.16 for clients aged 70–74, to ORad: 1.73, 95% CI: 1.63–1.83 for those aged ≥90) and if the client was not living with family (that is, in special purpose accommodation ORad: 1.91, 95% CI: 1.77–2.05; living alone ORad: 1.22, 95% CI: 1.19–1.26; living with others (non-family) ORad: 1.21, 95% CI: 1.11–1.32). Other risk factors for an unplanned hospitalisation were cognitive dysfunction (ORad: 1.09, 95% CI: 1.05–1.13), a high CCI score (ORad: 1.21, 95% CI: 1.20–1.22), or a referral to home-based care by a palliative care team (ORad: 1.21, 95% CI: 1.13–1.30). Primary language other than English (ORad: 0.88, 95% CI: 0.85–0.91) was associated with lower odds of an unplanned hospitalisation.


## 4. Discussion

Home care policy reforms implemented in 2013 have reoriented the primary healthcare system to support older people to live in their own home [4]. Monitoring the use of health services and patient outcomes is critical to assessing the impact of the reforms on older Australians. Our study of utilisation of home-based care services from 2006 to 2015 showed a rising rate of home care use by individuals aged ≥85 years; persons aged 75–79 showed the greatest decline in use of services. The factors contributing to the marked reduction in home care use for this age group are unclear and warrant further investigation. It could be that these individuals are moving in with family or transitioning to residential aged care. The rate of unplanned hospitalisations for individuals aged ≥85 years increased over the 10-year study period. To our knowledge, this is the first study to quantify rates of unplanned hospitalisation and associated risk factors in a community-dwelling cohort supported by home-based care amidst home care policy reform.Australian housing trends show a steadily decreasing proportion of people aged ≥80 years living in residential aged care (27% in 2000, declining to 22% in 2014) [3]. The growing number of oldest older Australians living in the community was reflected in our finding that home-based care to people aged ≥85 years increased over time. More care delivery to this cohort accounted for the upward trend in both the rate of planned discharge and the rate of unplanned hospitalisations for those aged ≥85 years.Advancing age increased the likelihood of an unplanned hospitalisation, corroborated by other studies [16, 17]. In 2008-09, 61% of people aged ≥85 years attending a public hospital emergency department in metropolitan Melbourne were admitted to hospital [16]. Men aged ≥85 years warrant attention as they exhibited the steepest increase in demand for home care. Furthermore, we identified male gender as a risk factor for unplanned hospitalisations, as have previous researchers [17, 18]. Men who lived alone, rather than with someone, were more likely to have an unplanned hospital admission [18].Older people living with family, compared to other living arrangements, had lower odds of an unplanned admission. This appears to contradict the finding of an increased likelihood of an unplanned hospitalisation if there is an informal carer. A possible explanation is that living with family does not imply an older person cannot manage their own activities. However, the requirement for a carer indicates assistance is needed. The requirement for a carer, taken as a measure of diminished capability, is consistent with increased odds of an unplanned hospitalisation.Episodes involving individuals with greater medical complexities, as evidenced by a high CCI score or the client requiring more contact time with home care staff, had greater odds of an unplanned admission. Akugizibwe and colleagues reported that multimorbidity increases the risk of unplanned hospitalisations [19]. Improved primary care monitoring of people with chronic conditions and/or multimorbidity, may reduce avoidable unplanned hospitalisations [19, 20].There is unmet demand for comprehensive home-based care provided by the Living Longer Living Better Home Care Packages program [21, 22]. Government-funded assistance is available for basic care needs (Level 1 package) to high care needs (Level 4 packages); however, the number of available packages is limited. Older people, having been approved for a funded package, may wait a considerable time before receiving the home care they need. In 2018–19, the median wait times were 7 and 34 months for Level 1 and Level 4 packages, respectively [21, 23]. Without timely access to the home-based care required, older people are at risk of deteriorating health, preventable hospitalisation, premature admission to residential care, and early death [21].In response to ongoing reforms in the aged care system, the health service continuum is calling for improved delivery of primary healthcare for older people [21, 24] alongside closer monitoring of the impact of reforms using data from across the health system [22]. Furthermore, surveillance of the outcomes of home-based care provides a reference point against which the introduction of new approaches to healthy ageing in community-dwelling older people can be compared. Still in its infancy is the development of drugs to kill senescent cells, thereby slowing ageing by treating age-related conditions and improving resiliency. It is envisaged that senotherapeutic drugs, many of which are approaching clinical trials, will in the future extend the healthspan and potentially the lifespan of humans [25, 26]. Advances in technological innovation have sparked a range of e-Health interventions which may currently be improving the lifestyles and health of older adults. Propelled by the COVID-19 pandemic, the delivery of health services through telemedicine, online networking, and virtual educational and physical activity sessions has enabled older people to receive care and support outside of clinics, hospitals, and other institutionalised settings [27, 28]. With the increasing use of mobile technology, such as smartphones, the development of mobile sensors that support older adults to stay healthy and active has rapidly grown. Mobile health devices include wearable technology to continually monitor biological or environmental data such as heart rate, glucose, and geographical location. These sensor systems may incorporate mobile phone text interventions to assist with the management of issues such as diabetes control or adherence to medication [29, 30]. Thus, changes in the delivery of healthcare and developments in medical technology may further promote the ability of older people to age in their own homes.The strength of this study was the large amount of routinely collected data available, enabling sufficient power for accurate statistical analyses. Several limitations should be considered. Data were collected for the purposes of service provision, not research, therefore incomplete or misreported information was not unexpected. However, given the comprehensiveness of the data set, we believe inaccuracies to be minimal. The data analysed in this study is historical; however, we believe it provides insight into trends and service demands, which can then be compared to the outcomes from the provision of home care services from 2016 to current day. We are cautious regarding the generalisability of our findings, as data were from one provider of home nursing and personal care services. Culturally and linguistically diverse people may be underrepresented in our data set.


## 5. Conclusion

In recent years, Australian health policy has focussed on providing services to enable older people to remain in their own homes. The increasing rate of unplanned hospitalisations for community-dwelling individuals aged ≥85 years highlights the need for more home care support to reduce the risk and potentially adverse effects of unplanned hospitalisations. This is particularly important as innovative technology and drug therapies driving changes in the delivery of healthcare and management of chronic conditions may result in greater numbers of older adults being able to live independently in the community, provided adequate support is available to meet their needs.



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