RESIDENTIAL AGED CARE FACILITIES AND THEIR WORKERS How Staffing Patterns and Work Experience Vary with Facility Characteristics

RESIDENTIAL AGED CARE FACILITIES AND THEIR WORKERS How Staffing Patterns and Work Experience Vary with Facility Characteristics By Associate Professor Bill Martin August 2005 Phoenix:Phoenix:Projects:Aged Care Workforce:2005 Additional Work:Aug 05 Facilities Variation (Bill):Facilities Variation Report 26Aug.doc

Contents List of Tables...3 Executive Summary...5 1. Introduction...7 2. The Workforce and How it is Employed...8 2.1 Age and Education...8 2.2 Staffing Mix... 13 2.3 Full-time permanent and part-time or casual staff... 17 2.4 Extent of vacancies and use of agency staff... 19 2.5 Job tenure and turnover... 23 2.6 Additional labour capacity workers who would be prepared to work more... 25 3 Job experience... 27 3.1. Time spent in direct caring... 27 3.2. Do workers feel they spend enough time with residents?... 29 3.3. Workplace experience - use of skills, autonomy, work pressure... 31 3.4. Job satisfaction... 34 4. Conclusion... 37 References... 41 Appendix... 42 2

List of Tables Table 2.1: Average age of employees by employment classification, location of facility, State, type of facility and ownership of facility... 8 Table 2.2: Proportion of PCs with Certificate III in Aged Care by location of facility... 9 Table 2.3: Proportion of PCs with Certificate IV in Aged Care by location of facility...10 Table 2.4: Proportion of PCs with Certificate III in Aged Care by type of facility...10 Table 2.5: Proportion of PCs with Certificate III in Aged Care by State...11 Table 2.6: Proportion of PCs with Certificate IV in Aged Care by State...11 Table 2.7: Proportion of PCs with Certificate III in Aged Care by ownership of facility...12 Table 2.8: Proportion of PCs with Certificate IV in Aged Care by ownership of facility...12 Table 2.9: Average ratio of beds per employed equivalent full-time (EFT) staff...13 Table 2.10: Average ratio of beds per employed equivalent full-time (EFT) staff by location of facility...14 Table 2.11: Average ratio of beds per employed equivalent full-time (EFT) staff by State...15 Table 2.12: Average ratio of beds per employed equivalent full-time (EFT) staff by ownership type of facility...16 Table 2.13: Proportion of facilities with full-time employees by State...17 Table 2.14: Proportion of facilities with full-time employees by location of facility...18 Table 2.15: Proportion of facilities with full-time employees by type of facility...18 Table 2.16: Proportion of facilities with full-time employees by ownership of facility...19 Table 2.17: Average number of vacancies per employed equivalent full-time (EFT) staff by location of facility...20 Table 2.18: Average number of vacancies per employed equivalent full-time (EFT) staff by State...20 Table 2.19: Average number of vacancies per employed equivalent full-time (EFT) staff by type of facility...21 Table 2.20: Average proportion of shifts worked by agency staff per EFT staff... by location of facility...21 Table 2.21: Average proportion of shifts worked by agency staff per EFT staff by State.22 Table 2.22: Average proportion of shifts worked by agency staff per EFT staff by type of facility...22 Table 2.23: Average proportion of shifts worked by agency staff per EFT staff by type of facility...23 Table 2.24: Proportion of employees with tenure of less than one year by employment classification and location of facility...24 Table 2.25: Proportion of employees with tenure of less than one year by 3

employment classification and State...24 Table 2.26: Proportion of employees with tenure of less than one year by employment classification and type of facility...25 Table 2.27: Proportion of employees with tenure of less than one year by employment classification and ownership of facility...25 Table 2.28: Hours employees would like to work by State...26 Table 2.29: Hours employees would like to work by type of facility...26 Table 2.30: Hours employees would like to work by ownership of facility...27 Table 3.1: Time employees spend in direct caring work by location of facility...28 Table 3.2: Time employees spend in direct caring work by State...28 Table 3.3: Time employees spend in direct caring work by type of facility...29 Table 3.4: Time employees spend in direct caring work by ownership of facility...29 Table 3.5: I am able to spend enough time with each resident by location of facility...30 Table 3.6: I am able to spend enough time with each resident by State...30 Table 3.7: I am able to spend enough time with each resident by type of facility...31 Table 3.8: I am able to spend enough time with each resident by ownership of facility...31 Table 3.9: I have a lot of freedom to decide how I do my work by location of facility...32 Table 3.10: I have a lot of freedom to decide how I do my work by State/Territory...32 Table 3.11: I have a lot of freedom to decide how I do my work by type of facility...32 Table 3.12: I have a lot of freedom to decide how I do my work by ownership of facility...33 Table 3.13: Average job satisfaction of employees by location of facility...34 Table 3.14: Average job satisfaction of employees by State/Territory...35 Table 3.15: Average job satisfaction of employees by type of facility...36 Table 3.16: Average job satisfaction of employees by ownership of facility...36 Table A1.1: I use many of my skills in my current job by location of facility...42 Table A1.2: I use many of my skills in my current job by State/Territory...42 Table A1.3: I use many of my skills in my current job by type of facility...42 Table A1.4: I use many of my skills in my current job by ownership of facility...42 4

Executive Summary This report uses data from a census of Australian aged care facilities and a survey of their direct care workers, both undertaken in 2003. It investigates how staffing patterns and workers experience of work vary according to the characteristics of facilities. In particular, it examines variations associated with the geographic location of facilities (metropolitan, regional and rural, and State), the mix of high and low care beds in facilities, and their ownership (for-profit, not-for-profit or public). In general, the results indicate that there are some significant variations in staffing patterns amongst facilities in different locations and of different types. By contrast, workers experience of work and their work satisfaction tend to vary little with facility characteristics. Amongst the more significant variations in staffing patterns are: Unsurprisingly, staffing levels and mix are strongly associated with the mix of beds in facilities. High Care facilities employ more staff per bed, and use more Registered Nurses (RNs) and less Personal Carers (PCs), than others. They are also more likely to employ some staff on full-time permanent contracts. Beyond this, they have younger Enrolled Nurses (ENs) and PCs than other facilities, have fewer PCs with Aged Care qualifications, higher vacancy levels, and higher use of agency staff. Metropolitan facilities have higher RN and PC vacancies, greater use of agency staff, and slightly higher turnover than other facilities. Facilities in South Australia (SA) and Western Australia (WA) have significantly greater use of agency staff than those in other States. Compared to facilities in other States, those in New South Wales (NSW) have older RNs, younger PCs, more PCs on full-time permanent contracts and fewer with the Certificate IV in Aged Care. For-profit facilities have fewer staff per bed, younger PCs, higher vacancies (particularly for RNs), more use of agency staff, and higher staff turnover (particularly for PCs) compared to not-for-profit and publicly owned facilities. On the other hand, publicly owned facilities have more PCs with Aged Care qualifications, the highest staff per bed, and lowest RN turnover rates. Some, but not all, of these variations are due to for-profit facilities having a heavy predominance of high care beds. 5

Variations amongst facilities in staffing patterns may arise for several reasons. The conclusion to this report considers four important ones: Differing labour market conditions. Facilities faced with more limited supply of workers may change their staffing mix, reduce staffing or use agency staff. It appears that metropolitan facilities face generally tighter labour market conditions than others. RNs for high care facilities seem also to be relatively difficult to recruit, particularly in NSW. There may also be some general staff shortages in SA and WA, as reflected in their higher use of agency staff. Different industrial relations and/or regulatory traditions and histories. Differences between States in staffing mixes may result from differences in the State industrial awards that cover direct care workers and/or differences across States in the tasks that particular categories of workers are permitted to undertake. These factors probably explain the particularly low use of ENs in NSW, especially compared to Victoria. Different priorities in facility goals. Some facility characteristics are likely to emphasise different goals. Most obviously, for-profit facilities may place a priority on maximising return to investment, a goal that is not a concern of not-for-profit or public facilities, and this may affect decisions about how to staff facilities. Some staffing patterns in for-profit facilities are consistent with a distinctive concern with minimising their labour costs. However, the work experience and job satisfaction patterns of workers in for-profit facilities are the same as those in other facilities. It therefore remains unclear whether the distinctive staffing patterns of for-profit facilities are due to their distinctive goals, or to other unmeasured factors. Different solutions to resident needs. Some variations in staffing mix or levels may simply reflect differences in the way facilities have organised direct carers work to meet resident needs. There is no reason to suppose that there is a single optimum staffing mix or employment contract mix for aged care facilities. There may be many sets of arrangements that provide equal quality care. The results presented in this report are consistent with such a picture. Significant variation by facility characteristics in staffing patterns (notably staff and employment contract mix, and overall staffing levels) does not translate into systematic variation in workers experience of work, or their work satisfaction. 6

1. Introduction In The Care of Older Australians (Richardson and Martin 2004), the main features of the national residential aged care workforce were described. While that report provided a few hints about how the workforce varied across facilities, the issue was not its focus. Yet variation in the workforce across facilities is an important topic. For example, if some facilities face higher worker turnover than others, or employ much older workforces, then these facilities may face unique challenges in maintaining their workforces over the long term. Similarly, if workers in some kinds of facilities have higher job satisfaction than others, then this may have important effects on those facilities ability to retain staff and successfully fill vacancies. In this report, we explore issues like these. We use data from the census of aged care facilities and from the survey of direct care workers to investigate how the characteristics of the workforce vary across different types of facilities (for details of the census and survey, see Richardson and Martin 2004). We examine geographic location as one form of variation, focusing on differences between facilities located in each State and differences related to whether facilities are located in metropolitan, regional or rural areas. We also look at variation associated with the bed mix in facilities (high care, low care or mixed) and with their ownership type (public, not-for-profit, and for-profit). These are amongst the most important features on which facilities vary, and are readily measured in the data we use. This report begins by considering the main features of the workforce and its employment in facilities: the age and qualifications of employees, the staffing mix in facilities, the use of part-time and casual vs. full-time employees, tenure and turnover, vacancies and the use of agency staff, and spare capacity amongst currently employed workers. The second major section of the report examines variation in how workers experience their jobs, and how they feel about them, including job satisfaction. 7

2. The Workforce and How it is Employed 2.1 Age and Education Generally, the aged care workforce is older than the whole Australian workforce (Richardson and Martin, 2004: 24-25). Table 2.1 shows the mean age of Registered Nurses (RNs), Enrolled Nurses (ENs) and Personal Carers (PCs) in facilities of different types and in different locations. Table 2.1: Average age of employees by employment classification, location of facility, State, type of facility and ownership of facility RN EN PCs Total Location of Facility State Type of Facility Ownership of Facility Metropolitan 47.9 42.9 43.1 47.9 Regional 49.7 44.3 42.2 49.7 Rural 49.0 43.5 43.5 49.0 N 715 414 1348 715 NSW 49.1 44.6 41.5 49.1 VIC 47.2 42.2 43.4 47.2 QLD 49.6 45.5 44.8 49.6 SA 47.6 44.6 43.9 47.6 WA 48.2 41.3 42.6 48.2 TAS 51.4 45.1 44.1 51.4 N 713 412 1352 713 Low Care Only 48.1 45.1 45.0 48.1 High Care Only 48.8 41.9 40.8 48.8 Both High and Low Care 48.3 45.1 43.7 48.3 N 714 401 1343 714 Not for Profit 49.1 45.1 44.0 49.1 For Profit 47.9 42.4 39.8 47.9 Public 47.8 41.6 44.9 47.8 N 714 410 1348 714 In general, variations in average age are small. However, there are some noticeable differences. First, RNs in NSW and Queensland are an average of 1-2 years older than those in other mainland States. However, NSW has the youngest PCs, on average, and Queensland has the oldest. ENs and PCs in high care facilities are younger than those in other facilities, by an average of 3-4 years. However, there is no difference in the average age of RNs by the bed mix. Finally, PCs in for-profit 8

facilities are significantly younger than those in other facilities, by an average of 4-5 years. In examining the training of direct care workers, we focus on the proportion of PCs in facilities who have the Certificate III or Certificate IV in Aged Care. Table 2.2 shows that metropolitan facilities are much less likely than rural or regional ones to have three quarters or more of their PCs with the Certificate III (28% of metropolitan facilities fall into this category compared to about 40% of others). Table 2.2: Proportion of PCs with Certificate III Proportion of PCs with Certificate III in Aged Care by location of facility Metropolitan Regional Rural None 7.4% 6.6% 15.3% Less than 25% 14.5% 7.2% 7.1% Between 25% and 50% 23.5% 18.6% 14.8% Between 50% and 75% 26.3% 25.2% 22.8% Between 75% and 100% 28.3% 42.5% 40.0% Total N 816 318 465 Note: This table shows the proportion of facilities in each location with the designated proportion of PCs holding the Certificate III in Aged Care. For example, in 7.4% of metropolitan facilities no PCs hold this qualification, while in 23.5% between a quarter and a half of PCs hold the qualification. Tables 2.2-2.7 have equivalent interpretations. However, rural facilities are much more likely than others to fall into the small group of facilities with no PCs who have the Certificate III. The differences are less clear when we examine what proportion of PCs have the Certificate IV (Table 2.3), although rural facilities are more likely than others to be in the small group of facilities where more than a quarter of PCs have this qualification. In general, then, PCs in rural and regional facilities tend to be better qualified than those in metropolitan ones. 9

Table 2.3: Proportion of PCs with Certificate IV Proportion of PCs with Certificate IV in Aged Care by location of facility Metropolitan Regional Rural None 61.7% 59.3% 61.2% Less than 25% 32.6% 32.7% 25.8% Between 25% and 50% 3.7% 4.7% 7.6% Between 50% and 75% 1.0% 2.4% 3.8% Between 75% and 100% 0.9% 0.9% 1.6% Total N 861 339 497 Perhaps surprisingly, high care facilities are much more likely to have few PCs with Certificate III in Aged Care than low care ones (Table 2.4). Whereas 45% of low care facilities have three quarters or more of their PCs with the Certificate III, only 24% of high care ones do; and 15% of high care facilities have no PCs with this qualification, compared to 6% of low care ones. Facilities with a mix of high and low care fall in between these extremes. Table 2.4: Proportion of PCs with Certificate III Proportion of PCs with Certificate III in Aged Care by type of facility Low Care Only High Care Only Both High and Low Care None 5.8% 14.9% 7.1% Less than 25% 8.7% 12.5% 11.3% Between 25% and 50% 17.8% 22.3% 20.1% Between 50% and 75% 23.0% 26.1% 25.7% Between 75% and 100% 44.8% 24.1% 35.8% Total N 518 551 522 Variations by State in the proportion of PCs with the Certificate III or IV defy easy description. Victoria does stand out in having a relatively large number of facilities with no PCs having the Certificate III. However, Victorian facilities are also more likely than those in any other State to have three quarters or more of PCs with the 10

qualification. Overall, the variations between States are not large, though PCs in Tasmanian facilities may be least likely to have the Certificate III (Table 2.5). Table 2.5: Proportion of PCs with Certificate III Proportion of PCs with Certificate III in Aged Care by State NSW VIC QLD SA WA TAS None 7.6% 16.0% 4.7% 6.3% 4.4% 16.7% Less than 25% 12.0% 10.4% 8.5% 8.2% 9.6% 23.8% Between 25% and 50% 20.1% 14.1% 19.1% 27.0% 29.4% 11.9% Between 50% and 75% 25.0% 19.7% 33.2% 27.7% 28.7% 26.2% Between 75% and 100% 35.3% 39.8% 34.5% 30.8% 27.9% 21.4% Total N 527 482 235 159 136 42 With regard to the Certificate IV, there is very significant variation in that facilities in NSW are far more likely than those in other States to have no PCs with this qualification (81% of NSW facilities have no PCs with the Certificate IV compared to 45-55% in other States) (see Table 2.6). Table 2.6: Proportion of PCs with Certificate IV in Aged Care by State Proportion of PCs with Certificate IV NSW VIC QLD SA WA TAS None 80.8% 56.0% 44.3% 47.6% 51.4% 48.9% Less than 25% 16.0% 27.4% 50.8% 46.4% 45.2% 28.9% Between 25% and 50% 1.8% 9.7% 3.3% 4.8% 1.4% 17.8% Between 50% and 75% 0.7% 4.3% 1.2% 0.6% 2.1% 4.4% Between 75% and 100% 0.7% 2.6% 0.4% 0.6% 0.0% 0.0% Total N 567 507 244 166 146 45 Finally, 40% of publicly owned facilities have no PCs with the Certificate III in Aged Care, compared to 6-7% of private and not-for-profit ones. Since most publicly owned facilities are in Victoria, this helps explain the high proportion of Victorian facilities in this category. Publicly owned facilities are also distinctive in having few 11

facilities with intermediate proportions of PCs with the Certificate III they tend to have a high proportion with the qualification, or none at all (see Table 2.7). Table 2.7: Proportion of PCs with Certificate III Proportion of PCs with Certificate III in Aged Care by ownership of facility Not for Profit For Profit Public None 6.6% 5.7% 40.0% Less than 25% 10.4% 12.9% 9.3% Between 25% and 50% Between 50% and 75% Between 75% and 100% 20.6% 22.6% 7.3% 26.2% 26.5% 13.3% 36.3% 32.4% 30.0% Total N 1062 389 150 These patterns are continued with respect to the Certificate IV, where three quarters of public facilities have no PCs with this qualification compared to about 60% of other facilities; but publicly owned facilities are much more likely than others to fall into the very small group where more than half of PCs have the Certificate IV (see Table 2.8). Table 2.8: Proportion of PCs with Certificate IV Proportion of PCs with Certificate IV in Aged Care by ownership of facility Not for Profit For Profit Public None 59.0% 61.5% 75.3% Less than 25% 32.6% 31.4% 14.2% Between 25% and 50% Between 50% and 75% Between 75% and 100% 5.8% 4.2% 1.9% 1.9% 1.2% 5.6% 0.6% 1.7% 3.1% Total N 1129 408 162 12

2.2 Staffing Mix One important dimension of variation in aged care facilities lies in their staffing levels for each direct care occupation, and how staffing levels for occupations of different kinds are combined. To examine this issue, we present data on the number of beds per equivalent full-time (EFT) employee for each occupation. We examine facility characteristics separately for facilities with only high care beds, only low care beds and both low and high care beds, since staffing patterns are clearly affected by the bed mix in facilities. We begin by reviewing how patterns of staffing vary overall according to the bed mix in facilities (Table 2.9). Facilities with only low care beds use few RNs, and most staff are PCAs. The result is that, in these facilities, there is an average of just over 6 beds per EFT PC, whereas there are 46 beds per EFT RN and 41 beds per EFT EN. Facilities with only high care beds make much greater use of RNs, particularly RNs. The result is that, in these facilities, there are only slightly more beds per RN (8) than beds per PC (7). Overall, facilities with only low care beds have almost twice as many beds per direct care worker (6.3) as facilities with only high care beds (3.3). Facilities with both high and low care beds generally lie between the other two types, except that they have the smallest number of beds per EFT PC. Table 2.9: Average ratio of beds per employed equivalent full-time (EFT) staff Type of facility Low care places only RN EN PCs Total 46.3% 40.9% 6.4% 6.3% N 230 137 303 328 High care places only 8.3% 22.5% 7.1% 3.3% N 393 314 337 399 Obviously, these broad patterns are closely related to variation in the nature of the work in aged care facilities associated with high and low care beds. Residents in high care beds require both more intensive and more technically skilled care than those in low care beds. Hence, there are more staff per bed in high care facilities than low care ones, and more RNs in high care facilities because of the technical 13

requirements of caring for residents in these facilities. However, differences in staffing mix associated with factors other than bed mix indicates that purely technical work requirements are not the only determinants of staffing mix. To further examine the considerable variation in how facilities combine RNs, ENs and PCs in their staffing, we begin with variation according to the regional location of facilities. As Table 2.10 shows, in facilities with only low care beds, metropolitan facilities have most beds per EFT staff (7.7), rural ones the fewest (4.6) with regional facilities lying between these extremes (5.9). These differences are due to metropolitan facilities tendency to employ fewer PCs per bed than either regional or rural ones, and a gradient in the staffing ratios for ENs, so that rural facilities use the greatest number of these staff per bed. Table 2.10: Average ratio of beds per employed equivalent full-time (EFT) staff by location of facility Type of facility Location of Facility RN EN PCs Total Low care places only High care places only Metropolitan 45.6% 46.7% 7.3% 7.7% Regional 46.2% 39.0% 5.7% 5.9% Rural 47.7% 31.1% 5.6% 4.6% N 230 137 303 328 Metropolitan 9.0% 31.7% 4.2% 3.0% Regional 7.2% 14.6% 6.6% 3.0% Rural 7.5% 10.5% 16.8% 4.1% N 393 314 337 399 The pattern is quite different where facilities have only high care beds. Here, metropolitan and regional facilities have the same overall ratio of beds to direct care staff (3.0 beds per EFT staff), while rural facilities operate with lower overall staffing levels (4.1 beds per EFT staff). However, metropolitan facilities make much greater use of PCs and less use of RNs than either regional or rural facilities. In essence, rural high care facilities operate with fewer staff than metropolitan ones, but they use more highly trained staff (particularly ENs). There is also some variation in patterns of use of staff across States (Table 2.11). Amongst low care facilities, the number of direct care staff per bed is generally very similar. However, there is some variability in how this overall similarity is achieved. 14

Facilities in Victoria and South Australia make much greater use of ENs than do those in other States, and there are correspondingly fewer RNs and PCs. Queensland facilities use many more RNs than other States, with about half the number of beds per RN compared to other States. 1 Table 2.11: Average ratio of beds per employed equivalent full-time (EFT) staff by State Type of facility State RN EN PCs Total Low care places only High care places only NSW 49.4% 49.3% 6.0% 6.1% VIC 57.0% 30.7% 6.4% 5.7% QLD 23.3% 69.4% 5.2% 5.7% SA 45.0% 29.7% 7.5% 6.1% WA 54.3% 45.2% 8.4% 11.9% N 230 137 303 318 NSW 8.9% 37.7% 4.0% 3.3% VIC 7.3% 6.9% 17.4% 2.8% QLD 10.5% 31.9% 2.9% 5.3% SA 7.2% 24.4% 3.7% 1.8% WA 9.9% 20.7% 2.3% 3.9% N 393 314 337 400 There is also considerable variation between high care facilities in different States in the number of beds per EFT direct care staff. Queensland facilities have lower overall staffing levels per bed than those in other States, with almost three times the number of beds per staff member compared to South Australia. Queensland high care facilities are particularly distinctive in their heavy use of PCs, and lower reliance on RNs compared to other States. South Australian facilities have the highest staffing levels, relying primarily on RNs and PCs. ENs are used far more in Victorian facilities than in those in other States, with correspondingly little employment of PCs in Victoria. 1 The data suggest that facilities in WA have almost twice the number of beds per staff member compared to those in other States. They appear to have more beds per EFT staff member for each occupation than other States. However, the WA pattern is so extreme that it suggests significant sampling error in the data from that State, and would require careful checking from other sources. 15

Most low care facilities are run as not-for-profit enterprises, with only about 10% of low care facilities in our sample being for-profit and 6% being publicly owned. Thus, although there are differences in staffing patterns across low care facilities depending on ownership, the vast majority fall into the not-for-profit category. Nevertheless, Table 2.12 makes it clear that for-profit facilities have more beds per EFT staff than either of the other types. This results from the fact that they employ fewer RNs and PCs per bed than either not-for-profit or publicly owned facilities. Publicly owned low care facilities have the most staff per bed, primarily because they employ more ENs and PCs per bed than either of the other ownership types. Table 2.12: Average ratio of beds per employed equivalent full-time (EFT) staff by ownership type of facility Type of facility Ownership of facility RN EN PCs Total Low care places only High care places only Not for Profit 42.1% 42.4% 6.3% 6.1% For Profit 91.4% 34.0% 8.9% 12.1% Public 48.5% 27.2% 5.1% 3.4% N 230 137 303 329 Not for Profit 8.0% 25.1% 3.7% 2.6% For Profit 9.6% 29.0% 4.3% 4.2% Public 5.3% 4.2% 35.5% 2.3% N 393 314 337 401 Amongst high care facilities, for-profit and not-for-profit facilities are more evenly represented, with the former accounting for nearly half of the group and the latter about 37% in our sample. Again, for-profit facilities appear to operate with more beds per EFT staff member than either of the other facility types (Table 2.12). They are particularly distinctive in having higher bed:staff ratios for RNs and PCs. They have about 1.5 more beds per RN than not-for-profit ones, and about 0.6 more beds per PC. Public facilities, mostly located in Victoria, are distinctive in their heavy reliance on ENs and their very limited use of PCs. 16

2.3 Full-time permanent and part-time or casual staff An important characteristic of employment practices in facilities is whether staff work on a full-time or part-time basis, and whether they are employed permanently or casually. In general, direct care staff are most likely to be employed on a parttime permanent basis, with just over 60% of RNs and over 70% of other direct care workers being employed in this way (Richardson and Martin 2004: 20). PCs are least likely to be employed full-time. Here, we focus on full-time permanent staff compared to part-time or casual staff, examining the proportion of facilities with at least some staff in each occupation employed on full-time permanent contracts. This provides a useful indicator of variation in facilities propensity to employ staff on such contracts. Overall, facilities are much more likely to employ at least one RN on a full-time permanent basis compared to other occupations: 62% employ at least one full-time permanent RN, compared to 23% employing at least one full-time EN, 26% employing at least one full-time PC, and only 13% employing at least one full-time Allied Health worker. While facilities in most States conform to this picture, there are several sharp departures. As Table 2.13 shows, Western Australian facilities are far less likely to have a full-time RN than those in other States, with only about 35% of Western Australian facilities having such employees. At the same time, 44% of NSW facilities have at least one full-time PC, at least twice the proportion of any other State except Tasmania. Facilities in NSW, Victoria and, perhaps, Tasmania are also more likely to have at least one full-time EN, although even in these States only about a quarter of facilities do so. Table 2.13: Proportion of facilities with full-time employees by State Response NSW VIC QLD SA WA TAS % with F/T RNs 63.1% 64.0% 63.2% 65.4% 35.6% 85.7% % with F/T ENs 26.0% 28.4% 16.3% 10.9% 17.1% 22.2% % with F/T PCs 44.4% 14.9% 20.6% 12.2% 23.0% 31.0% % with F/T AHs 18.9% 10.8% 14.2% 6.5% 8.2% 8.8% 17

As Table 2.14 shows, there is relatively little variation in propensity to employ fulltime staff depending on the regional location of facilities. Metropolitan facilities are less likely to employ a full-time EN than those in regional or rural areas, but less than a third employ them in this way in any location. Table 2.14: Proportion of facilities with full-time employees by location of facility Response Metropolitan Regional Rural % with F/T RNs 61.6% 67.8% 59.6% % with F/T ENs 16.4% 25.2% 31.6% % with F/T PCs 24.3% 29.0% 26.8% % with F/T AHs 14.4% 14.5% 10.1% Much more significant is variation in employment patterns depending on bed mix. Table 2.15 shows that only about 40% of low care facilities employ at least one fulltime RN, compared to about 80% of high care facilities. Similarly, the high care facilities are almost twice as likely as low care ones to have staff in each other occupation employed on a full-time permanent basis. Rates of full-time permanent employment in mixed facilities fall between these two extremes, though they are mostly closer to the pattern for high care facilities. These patterns are highly significant, and indicate that high care facilities find it much more necessary to have a core of permanent, full-time staff than low care ones. Table 2.15: Proportion of facilities with full-time employees by type of facility Response % with F/T RNs % with F/T ENs % with F/T PCs % with F/T AHs Low care places only High care places only Mixture of high and low care places 39.4% 80.5% 64.0% 15.1% 27.2% 23.5% 18.8% 32.0% 26.5% 7.9% 16.1% 15.5% Finally, Table 2.16 shows the variation in propensity to employ full-time staff depending on ownership of the facility. Publicly owned facilities are generally more 18

likely to employ a full-time permanent person than others, with the difference being particularly striking for employment of ENs where publicly owned facilities have three times the rate of employment of some full-time ENs compared to other facility types. Table 2.16: Proportion of facilities with full-time employees by ownership of facility Response Not for Profit For Profit Public % with F/T RNs 57.4% 69.0% 79.2% % with F/T ENs 19.6% 14.9% 63.2% % with F/T PCs 25.5% 25.1% 34.0% % with F/T AHs 12.6% 15.7% 13.1% 2.4 Extent of vacancies and use of agency staff Two useful indicators of the state of the labour market in aged care facilities are the extent of vacancies and the use of agency staff. In this section, we examine how these features vary across different types of facilities and those in different locations. As a measure of vacancies we examine the average number of vacancies per employed equivalent full time (EFT) staff in facilities of different types and locations. Table 2.17 shows that there are more vacancies for RNs relative to the number employed than for other categories of staff vacancies for RNs run to an average of about 4.6% of employed EFT RNs, compared to about 2.0% for ENs and 2.7% for PCs. Regional facilities reported the lowest levels of vacancies for all categories of staff. Metropolitan facilities differ from rural ones mainly in reporting higher vacancies for RNs and PCs. 19

Table 2.17: Average number of vacancies per employed equivalent fulltime (EFT) staff by location of facility Location of Allied RN EN PCs Facility Health Metropolitan 5.1% 2.2% 3.4% 1.8% Regional 3.4% 1.3% 1.8% 1.2% Rural 4.5% 2.1% 2.2% 2.0% Total 4.6% 2.0% 2.7% 1.7% N 1591 1662 1597 1688 There are also some quite significant variations in vacancy patterns by State, as Table 2.18 indicates. NSW shows quite high levels of vacancies for both RNs and PCs, with South Australia showing similar vacancies patterns for RNs, but much lower ones for PCs. Overall, these figures suggest that vacancy rates are somewhat higher in NSW, particularly for RNs and PCs. 2 Table 2.18: Average number of vacancies per employed equivalent fulltime (EFT) staff by State State RN EN PCs Allied Health New South Wales 5.1% 1.6% 3.5% 2.4% Victoria 4.0% 2.4% 2.7% 1.4% Queensland 3.9% 1.3% 2.3% 1.5% South Australia 4.9% 2.1% 2.2% 0.9% Western Australia 3.7% 2.7% 1.3% 1.7% Tasmania 7.6% 1.2% 0.3% 0.9% Total 4.6% 2.0% 2.7% 1.7% N 1591 1662 1597 1688 Vacancy levels are significantly higher in high care facilities than in low care ones. For RNs and ENs, the average ratio of vacancies to EFT staff in high care facilities is about three times that in low care ones (Table 2.19). While the difference is smaller with respect to PCs, the vacancy rate in high care facilities for this group is still about one and a half times that in low care ones. Facilities with a mix of high and low care beds show vacancy patterns that lie between those of pure high care and pure low care facilities. 2 The apparently high vacancy rate for RNs in Tasmania is not reliable due to the small number of cases involved. 20

Table 2.19: Average number of vacancies per employed equivalent fulltime (EFT) staff by type of facility Type of Facility Low care places only High care places only Mixture of high and low care places RN EN PCs Allied Health 2.2% 0.8% 2.2% 1.3% 6.4% 3.1% 3.3% 1.9% 5.2% 2.1% 2.8% 2.0% Total 4.6% 2.0% 2.8% 1.7% N 1580 1652 1588 1678 Finally, for-profit facilities have average vacancy levels that are higher than those of not-for-profit or publicly owned facilities, particularly for RNs. At the same time, publicly owned facilities have strikingly low vacancy rates for PCs. Part of these differences is likely to be associated with the fact that for-profit facilities are predominantly high care or mixed, rather than low care. However, for-profit facilities show higher average vacancy levels for RNs than all high care ones, suggesting that there is an additional effect associated with ownership type. Use of agency staff is also an important issue. We examine how the proportion of all shifts that are worked by agency staff varies across different types of facilities. Use of agency staff is much greater in metropolitan facilities than in rural or regional ones, as Table 2.20 shows. Whereas about 3% of all shifts worked by metropolitan RNs and PCs were worked by agency staff, the figures for regional and rural RNs and PCs were about a third and a sixth of the metropolitan rates respectively. Table 2.20: Average proportion of shifts worked by agency staff per EFT staff by location of facility Location of Allied RN EN PCs Facility Health Metropolitan 3.0% 0.9% 3.3% 1.1% Regional 0.8% 0.2% 0.5% 0.7% Rural 1.1% 0.6% 0.5% 0.8% Total 2.0% 0.6% 1.8% 0.9% N 1598 1682 1541 1685 21

As Table 2.21 shows, there are also significant variations in the use of agency staff between States. South Australia and Western Australia stand out as having particularly high average proportions of shifts worked by agency staff. An average of nearly 5% of PC shifts and nearly 4% of RN shifts in South Australia are worked by agency staff, while the figures in Western Australia are close to 3% for both categories. This compares to around 1.5-2.0% for most other States. Table 2.21: Average proportion of shifts worked by agency staff per EFT staff by State State RN EN PCs Allied Health New South Wales 1.4% 0.1% 1.3% 0.5% Victoria 1.9% 0.8% 1.9% 1.0% Queensland 1.4% 0.1% 0.6% 0.4% South Australia 3.9% 2.5% 4.8% 1.8% Western Australia 2.9% 1.2% 2.7% 2.1% Tasmania 1.1% 0.0% 0.0% 0.6% Total 2.0% 0.6% 1.8% 0.9% N 1598 1682 1541 1685 The use of agency staff also varies considerably depending on the types of beds in a facility (Table 2.22). Those with only high care beds have at least twice the rate of use of agency staff as other facility types in almost every occupation. Facilities with only low care beds are also generally the lowest users of agency staff. Table 2.22: Average proportion of shifts worked by agency staff per EFT staff by type of facility Type of Facility Low care places only High care places only Mixture of high and low care places RN EN PCs Allied Health 0.7% 0.4% 1.2% 0.9% 3.0% 1.0% 2.9% 1.0% 2.3% 0.6% 1.3% 0.8% Total 2.0% 0.7% 1.8% 0.9% N 1588 1671 1531 1674 For-profit facilities, which also tend to have only high care beds, use agency staff at higher rates than not-for-profits, or public facilities (except for ENs where public 22

facilities are the greatest users of agency staff). Table 2.23 also shows that not-forprofit facilities are the lowest users of agency PCs, with publicly owned ones having usage rates between the other types. Table 2.23: Average proportion of shifts worked by agency staff per EFT staff by type of facility Type of Allied RN EN PCs Facility Health Not for Profit 1.6% 0.6% 1.4% 0.8% For Profit 3.3% 0.6% 2.8% 1.2% Public 1.3% 1.5% 2.0% 0.8% Total 2.0% 0.6% 1.8% 0.9% N 1601 1684 1545 1687 2.5 Job tenure and turnover An important indicator of the state of the labour market faced by facilities is the length of time staff have been employed at a facility. Short tenure is often an indicator of a tight labour market in which employees face attractive alternative employment. High turnover arising from short tenure produces increased costs and, sometimes, disruption for facilities because it increases the effort required to recruit replacement employees. The survey of facilities provided data on tenure for each of the main direct care occupations. Our initial analysis of the data indicated quite high levels of turnover, as indicated by the proportion of staff who had been employed for one year or less, particularly for PCs and RNs (Martin and Richardson 2004: 30-31). Here, we examine whether tenure patterns vary across different types of facilities. We measure turnover by the proportion of employees who have been in their jobs for less than a year. This proportion can be interpreted as the proportion of the workforce that facilities need to replace each year. Turnover appears to be somewhat higher for all direct care occupations in metropolitan facilities than in regional ones (Table 2.24). In turn, turnover in regional facilities is higher than in rural facilities. However, these differences are not large: an average of about 26% of RNs in metropolitan facilities have tenure of less than one year, compared to an average of 23% in rural facilities. The slightly higher turnover in metropolitan facilities also translates into a greater proportion of employees having quite long 23

experience in non-metropolitan facilities. For example, an average of 30% of PCs in rural facilities have been employed for 6 or more years, compared to an average of 24% in metropolitan ones. Table 2.24: Proportion of employees with tenure of less than one year by employment classification and location of facility Metropolitan Regional Rural Total N RNs 26.1% 24.9% 22.9% 1519 ENs 21.3% 18.6% 17.4% 1129 PCs 26.0% 24.3% 24.9% 1632 AH 26.3% 22.4% 25.4% 1149 Variations in tenure across States are also not very large, though some are notable (Table 2.25). Western Australia stands out in having particularly high turnover amongst RNs: an average of 33% of RNs in WA facilities have less than one year of tenure, compared to 23% in NSW, 25% in Victoria and 22% in South Australia. There is much less variation in PC turnover rates, with South Australia showing slightly lower turnover than the other States. Table 2.25: Proportion of employees with tenure of less than one year by employment classification and State NSW VIC QLD SA WA TAS Total N RNs 22.9% 24.8% 27.7% 22.0% 32.7% 23.6% 1525 ENs 17.7% 18.5% 19.4% 24.6% 26.1% 11.7% 1133 PCs 25.1% 26.6% 25.6% 22.8% 26.0% 17.7% 1639 AH 20.8% 29.6% 25.9% 22.1% 31.3% 11.3% 1154 Turnover varies quite significantly depending on the bed mix in facilities (Table 2.26). On average, about 31% of RNs in low care facilities have been employed for less than one year, whereas in high care facilities the average is about 20%. Thus, low care facilities appear to face a significantly greater problem in retaining RNs than high care ones, though they also employ far fewer RNs. On the other hand, low care facilities have slightly lower turnover than high care ones with respect to PCs: an average of 23% have been in their jobs for a year or less, compared to 28% in high care facilities. In both cases, facilities with a mix of high and low care beds have turnover that is between that of pure high care and pure low care ones. 24

Table 2.26: Proportion of employees with tenure of less than one year by employment classification and type of facility Low care places only High care places only Mixture of high and low care places Total N RNs 30.6% 20.0% 26.6% 1511 ENs 21.4% 19.0% 19.2% 1123 PCs 22.9% 28.1% 25.3% 1623 AH 29.3% 23.7% 24.2% 1145 As Table 2.27 shows, for-profit facilities have somewhat higher turnover than others, particularly in relation to ENs and PCs. On average, for-profit facilities have 31% of PCs who have been in their jobs less than one year, compared to 23% in publicly owned facilities and 24% in not-for-profits. In a similar vein, for-profit facilities have an average of 25% of ENs with less than a year s tenure, compared to 18% in private and not-for-profit ones. With regard to RNs, there is little difference between private and not-for-profit facilities in average turnover, but public facilities have significantly lower RN turnover. Table 2.27: Proportion of employees with tenure of less than one year by employment classification and ownership of facility Not for Profit For Profit Public Total N RNs 25.6% 26.6% 17.1% 1523 ENs 17.5% 25.0% 18.4% 1130 PCs 23.5% 31.0% 23.3% 1634 AH 22.3% 30.2% 30.7% 1151 2.6 Additional labour capacity workers who would be prepared to work more Workers were asked both how many hours they currently work, and how many hours they would prefer to work. We begin by examining what proportions of employees would prefer to work more, less and the same amount as they currently do. In general, the greater the proportion who would work more, the greater the additional labour capacity represented by the existing workforce. Table 2.28 shows this proportion by State. The differences between States are generally small, though NSW and Victoria clearly have somewhat lower proportions of employees willing to work more hours than other States, and Tasmania stands out as having the greatest proportion willing to work more. 25

Table 2.28: Hours employees would like to work by State Hours desired NSW VIC QLD SA WA TAS Want to work MORE hours 26.4% 27.0% 32.2% 30.1% 32.1% 35.8% Want to work SAME hours 59.3% 60.0% 53.4% 55.7% 53.6% 49.4% Want to work LESS hours 14.4% 13.0% 14.4% 14.2% 14.3% 14.8% Total N 869 623 369 332 196 81 Table 2.29 shows that employees in high care facilities are significantly less likely to wish to work more hours than those in other facilities. Indeed, about a third of those in low care and mixed facilities are willing to work more hours, compared to a quarter of those in high care facilities. This difference is probably due to the fact that Nurses, who generally work longer hours than PCs and are therefore less likely to want to work more hours, are employed more in high care facilities than in low care ones. Table 2.29: Hours employees would like to work by type of facility Hours desired Low care places only High care places only Mixture of high and low care places Want to work MORE hours 34.2% 24.1% 31.2% Want to work SAME hours 53.1% 60.7% 55.5% Want to work LESS hours 12.8% 15.2% 13.3% Total N 392 1122 984 Finally, Table 2.30 shows that employees in publicly owned facilities are somewhat less likely to wish to work more hours than those in for-profit or not-for-profit ones. However, the difference is not overwhelming. 26

Table 2.30: Hours employees would like to work by ownership of facility Hours desired Not for Profit For Profit Public Want to work MORE hours 30.4% 27.0% 20.3% Want to work SAME hours 55.3% 60.0% 63.8% Want to work LESS hours 14.3% 12.9% 15.9% Total N 1541 703 271 3 Job experience Our initial analysis of data from the survey of aged care workers (Richardson and Martin 2004), and our more recent analysis of open-ended responses (Moskos and Martin 2005), strongly suggested that workers positive workplace experience, particularly through actually caring for residents, was very important in retaining their commitment to their jobs. We argued that this was especially so in the context of workers considerable dissatisfaction with low pay. Whether the experience of work, and workers subjective response to it, varies systematically across facilities is therefore an important issue. If workers in some types of facilities tend to have less positive workplace experience and subjective response to that experience, then these facilities may be at risk of significant problems in retaining staff. Where any negative experience (or subjective response) is associated with other characteristics of facility staffing (staffing mix, vacancy levels, etc.), retention and/or recruitment problems could be exacerbated. 3.1. Time spent in direct caring Since the caring work itself seems to be a major source of work satisfaction for aged care workers, a key issue is how much time they actually spend in direct care work (as opposed to paper work, consultation with other staff, etc.). Workers were asked whether they spend less than a third of their time in direct caring work, one third to two thirds, or more than two thirds. Table 3.1 shows that there is no significant variation in the distribution across these categories between staff in metropolitan, regional and rural facilities. 27

Table 3.1: Time employees spend in direct caring work by location of facility Hours desired Metropolitan Regional Rural Less than one-third 27.6% 27.5% 23.3% Between one-third and 35.2% 35.2% 39.0% two-thirds More than two-thirds 37.2% 37.3% 37.7% Total N 1354 654 692 However, the pattern does vary somewhat across States (Table 3.2). In particular, workers in NSW and Victoria report spending less time in direct care work than those in other States. For example, about one third of NSW and Victorian workers spend more than two thirds of their time actively caring for residents, compared to about 45% in Queensland and South Australia. These differences are not overwhelming, but it will be worth examining whether they have any impact on subjective job experience. Table 3.2: Time employees spend in direct caring work by State Hours desired NSW VIC QLD SA WA TAS Less than one-third Between one-third and twothirds More than two-thirds 31.5% 27.2% 21.4% 21.6% 24.9% 19.1% 37.4% 38.5% 34.3% 32.0% 33.8% 40.4% 31.1% 34.3% 44.3% 46.4% 41.3% 40.4% Total N 927 665 397 347 213 94 There is also some small variation in proportion of time spent caring for residents depending on bed mix. Workers in low care facilities spend a little less time with residents than those in other facilities, though the difference is smaller than the variation by State (Table 3.3). Similarly, workers in publicly owned facilities seem to spend a little less time in direct caring work than those in other facilities. However, again, the difference is small (Table 3.4). 28

Table 3.3: Time employees spend in direct caring work by type of facility Hours desired Less than one-third Between one-third and two-thirds More than two-thirds Low care places only High care places only Mixture of high and low care places 28.5% 27.2% 25.1% 41.6% 35.7% 35.1% 29.9% 37.1% 39.8% Total N 421 1204 1055 Table 3.4: Time employees spend in direct caring work by ownership of facility Hours desired Not for Profit For Profit Public Less than one-third 27.5% 25.9% 21.9% Between one-third and 35.8% 33.3% 47.1% two-thirds More than two-thirds 36.7% 40.7% 30.9% Total N 1660 756 278 Overall, then, the variation amongst employees in different types of facilities in time spent with residents is quite small. The major difference appears to lie in a tendency for NSW and Victorian workers to spend more time on non-direct care activities than those in other States, especially Queensland and South Australia. 3.2. Do workers feel they spend enough time with residents? How do workers respond to the amount time they spend in direct care work? The effect of their experience on their job satisfaction is likely to be highly dependent on whether they feel they are able to spend enough time with residents. Overall, nearly 70% of employees felt they were not able to spend enough time with residents. In general, variations in this response across different kinds of facilities are small. As Table 3.5 indicates, workers in regional facilities are somewhat more likely than those in other types to feel that they are unable to spend sufficient time with 29