The summative evaluation was not able to assess this question for all groups who are traditionally disadvantaged in their access to mental health care, because no data were available for some (e.g., people from culturally and linguistically diverse backgrounds, Aboriginal and Torres Strait Islander people). It was, however, able to consider access for young people and older people, people in rural and remote areas, and people in areas of high socio-economic disadvantage.
Component B explored the uptake of Better Access items according to the socio-demographic characteristics available in the Medicare Benefits Schedule data, namely, age, gender, geographical location and socio-economic disadvantage. Table 8 summarises the rates of Better Access uptake by socio-demographic characteristics in each of 2007, 2008 and 2009, and the percentage change in rates between years.
Lower rates of uptake were found among young people aged less than 15 years and older people aged 65 or more compared to the middle age groups. However, the relative growth in uptake between 2007 and 2009 was considerably greater for young people under 15 years (96.1%) than for all other age groups, followed by those aged 65 years and over (61.6%).
Additional analyses showed that young people also had the lowest uptake of the GP and Consultant Psychiatry items and the second lowest uptake of Psychological Therapy Services and Focussed Psychological Strategies items (older people having the lowest uptake of the two latter item groups). However, rates of growth between 2007 and 2009 were strongest among young people for the GP Mental Health Treatment (96.3%), Psychological Therapy (121.4%) and Focussed Psychological Strategies (104.9%) items. Growth was more modest (but similar to all other age groups) for the Consultant Psychiatrist (10.8%) items.
Table 8 also shows that uptake rates varied according to geographic region. They were somewhat lower for people residing in capital cities (53.7 per 1,000 population in 2009) than for those in other metropolitan centres and rural centres (59.0 and 57.6 persons per 1,000 in 2009, respectively). Compared to people living in capital cities, uptake rates were approximately 12% lower for people in other rural areas (47.3 per 1,000 in 2009) and approximately 60% lower for people in remote areas (21.5 per 1,000 in 2009). Additional analyses showed that this pattern of lower uptake for people in remote areas was consistent, regardless of item group. However, relative growth in uptake between 2007 and 2009 was greatest for people in remote areas.
With respect to socio-economic disadvantage, uptake rates were approximately 10% lower for people living in the most disadvantaged areas (48.5 persons per 1,000 population in 2009) than for people living in relatively more advantaged areas (between 52.4 and 53.6 persons per 1,000 population in 2009). However, relative growth in uptake between 2007 and 2009 was highest for people in the most disadvantaged areas. Additional analyses showed that these patterns were generally consistent across all item groups.
These findings are corroborated by analyses of service-level Medicare data conducted for the Post-Implementation Review of Better Access18 and the Australian Institute of Health and Welfare's annual reports on mental health services,19 20 and by independent analyses conducted by Russell.21-23
A major limitation of the above analyses is that they did not control for the clinical characteristics of Better Access consumers, usually because they relied solely on Medicare data. They therefore cannot tell us whether services are being used by those who have a clinical need for them. Component B attempted to overcome this limitation by undertaking an ecological analysis that drew together Medicare Benefits Schedule data and data from the 2007 National Survey of Mental Health and Wellbeing. Data from both sources were aggregated at the level of Divisions of General Practice. Levels of mental health treatment needd in areas defined by the boundaries of Divisions of General Practice were modelled using the survey data. Analyses assessed whether Better Access services (total services and allied health services used per 1,000 population in 2007) were distributed across Divisions according to need. These analyses indicated that there were higher levels of Better Access service use in Divisions with higher levels of mental health need. Higher levels of Better Access use were also found in Divisions with higher levels of GP supply and Divisions in Victorian Divisions. Lower levels of Better Access use were found in Divisions with relatively more people in the most socioeconomically disadvantaged areas and Divisions with more people living in remote locations. Models including these factors accounted for over half the variation in total use of Better Access services (54.7%) and use of allied health Better Access services (51.0%).
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An independent study by Harris et al used data from the 2007 National Survey of Mental Health and Wellbeing to explore the use of Medicare-subsidised allied health services among people with a need for mental health treatment.14 Survey respondents who reported using allied health services subsidised by Medicare in the past year (regardless of other mental health service use) were deemed to be Better Access allied health consumerse. Respondents who reported symptoms consistent with a 12-month ICD-10 diagnosis of affective or anxiety disorder were divided into three mutually exclusive groups based on their reported use of services for mental health problems in the past year: Better Access allied health service consumers; people who had used other services; and people who had not used any services. Among people with a 12-month affective or anxiety disorder, Better Access service use, as compared to other service use or no service use, was predicted by clinical factors (i.e., more severe disorder, having an affective disorder) but not by urbanicity (i.e., living in a major urban area versus a rural or remote area), level of socio-economic disadvantage (i.e. living in areas of less disadvantage), or other sociodemographic factors (such as age, gender, education or employment status).
The latter two modelling exercises provide complementary information on equity of access to Better Access. They both show that mental health need is a key determinant of Better Access service use. The ecological study undertaken in Component B (which used aggregated data and examined Better Access use in the total population) suggested there were some geographical inequities. These probably reflect the lower availability of health care professionals in remote and socio-economically disadvantaged areas. The Harris et al study (which used individual-level data on the use of Better Access services within a population defined as having current need) suggested that the use of Better Access services is primarily driven by having more severe and complex needs, rather than by demographic or socio-economic factors.
Data from the BEACH program also suggest that when mental health need is taken into account differences on other variables diminish.27 28 Restricting the analysis to encounters where the patient presented with a mental health problem, Britt and colleagues showed that Better Access GP item numbers were equally as likely to be used for in GP encounters in major cities and outside major cities, and in areas of socio-economic advantage and disadvantage. People from outside major cities were just as likely as their counterparts from major cities to be referred to a psychologist (both before and after the introduction of Better Access). People in socio-economically disadvantaged areas were less likely than those in advantaged areas to be referred to a psychologist, although the differential was reduced after the introduction of Better Access.
A study of uptake of Better Access item numbers by women29 showed somewhat different results with respect to socioeconomic factors. Byles et al compared the characteristics of four groups: women who used a Better Access MBS item; women who did not use a Better Access MBS item but had a recent mental health condition; women who did not use a Better Access MBS item but had a past mental health condition; and women who did not use a Better Access MBS item and did not have a mental health condition. They found that women who did not use a Better Access MBS item but had a recent mental health condition included more women who reported difficulty managing on their income and fewer women with post-school qualifications. However they did not find any differences between the groups in terms of area of residence.
As well as considering the relative level of access to Better Access by particular sociodemographic groups, Component B also profiled the costs of Better Access services according to consumers' socio-demographic characteristics. Table 9 summarises these data for 2009; patterns were similar for 2007 and 2008. The table shows that there were some variations in average copayments according to socio-demographic characteristics. Notably, average co-payments in 2009 were: lower for people aged 65 years or more ($33) than for all younger age groups; higher among people in remote areas ($37) and people in capital cities ($37) than those in other regions ($31-$33). The average co-payment decreased as level of relative socio-economic disadvantage increased (from $38 to $33).
Additional analyses showed that there were also some variations in average co-payments according to socio-demographic characteristics and provider type. Most notably, average copayments in 2009 were: lowest among people aged 65 years and over for GP, Psychological Therapy Services and Focussed Psychological Strategies items and lowest for young people aged less than 15 years for Consultant Psychiatrist items; highest among people in remote locations for GP, Psychological Therapy Services and Consultant Psychiatrist items but in the middle of the range for Focussed Psychological Strategies; and lowest among people in areas of greatest socioeconomic disadvantage regardless of item group.
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Table 8: Rates and percentage change in rates of use of any Medicare Benefits Schedule-subsidised Better Access services by age, gender, geographical region and socio-economic disadvantage for 2007, 2008 and 2009, Component B
Rate (per 1,000)3 20071 | Rate (per 1,000)3 20081 | Rate (per 1,000)3 20091 | Percentage change 2007-20081 | Percentage change 2008-20091 | Percentage change 2007-20091 | |||
---|---|---|---|---|---|---|---|---|
Age 0-14 years | 10.1 | 14.8 | 19.7 | 47.7 | 32.8 | 96.1 | ||
Age 15-24 years | 35.9 | 47.3 | 57.3 | 31.7 | 21.2 | 59.5 | ||
Age 25-34 years | 50.6 | 65.2 | 75.2 | 28.7 | 15.5 | 48.6 | ||
Age 35-44 years | 52.3 | 68.5 | 80.0 | 30.9 | 16.8 | 52.9 | ||
Age 45-54 years | 44.1 | 57.5 | 67.4 | 30.6 | 17.1 | 52.9 | ||
Age 55-64 years | 33.2 | 43.6 | 51.8 | 31.2 | 18.9 | 56.0 | ||
Age 65+ years | 17.3 | 23.0 | 27.9 | 33.3 | 21.3 | 61.6 | ||
Male | 24.8 | 32.7 | 39.4 | 31.7 | 20.6 | 58.9 | ||
Female | 42.7 | 56.3 | 66.2 | 31.6 | 17.7 | 54.9 | ||
Region2,4 Capital cities | 35.2 | 45.8 | 53.7 | 30.2 | 17.3 | 52.7 | ||
Region2,4 Other metropolitan centres | 36.7 | 48.3 | 59.0 | 31.6 | 22.1 | 60.7 | ||
Region2,4 Rural centres | 35.0 | 47.5 | 57.6 | 35.6 | 21.4 | 64.6 | ||
Region2,4 Other rural areas | 28.2 | 38.9 | 47.3 | 36.4 | 21.5 | 65.8 | ||
Region2,4 Remote areas | 12.7 | 16.6 | 21.5 | 30.6 | 29.6 | 69.2 | ||
Socio-economic disadvantage2,5 Quintile 5 (Least) | 36.1 | 46.1 | 53.4 | 27.7 | 15.8 | 47.9 | ||
Socio-economic disadvantage2,5 Quintile 4 | 33.6 | 44.1 | 52.7 | 31.0 | 19.7 | 56.8 | ||
Socio-economic disadvantage2,5 Quintile 3 | 33.4 | 44.1 | 52.4 | 31.9 | 18.7 | 56.6 | ||
Socio-economic disadvantage2,5 Quintile 2 | 33.2 | 44.6 | 53.6 | 34.2 | 20.1 | 61.2 | ||
Socio-economic disadvantage2,5 Quintile 1 (Most) | 29.4 | 40.0 | 48.5 | 36.0 | 21.2 | 64.8 | ||
All Better Access items | 33.8 | 44.5 | 52.8 | 33.6 | 18.7 | 58.6 |
1. 2007 and 2008 figures have regard to all claims processed up to and including 30 April 2009; 2009 figures have regard to all claims processed up to and including 30 April 2010.
2. Region based on Rural, Remote and Metropolitan Areas (RRMA) classification. Socio-economic disadvantage based on Index of Relative Socioeconomic Disadvantage (IRSD) classification.
3. Rates for gender, region and socio-economic disadvantage are age-standardised; Rates for age group are crude.
4. 2007, 1 case excluded due to missing data on RRMA.
5. Approximately 1% of cases excluded due to missing IRSD quintile data.
Table 9: MBS-subsidised Better Access services received, bulk-billing rate, fees charges, benefits paid and average co-payment, by gender, age, geographical region and socioeconomic disadvantage, 20091
Total services N | Bulk-billed services N | Bulk-billed services % | Services with co-payments 2 N | |||||||
---|---|---|---|---|---|---|---|---|---|---|
Age group 0-14 years | 355,901 | 164,877 | 46.3 | 44,834,383 | 38,091,086 | 191,024 | 53.7 | 35.30 | 81,336 | |
Age group 15-24 years | 655,158 | 389,660 | 59.5 | 79,077,952 | 69,325,461 | 265,498 | 40.5 | 36.73 | 171,876 | |
Age group 25-34 years | 936,374 | 523,683 | 55.9 | 111,830,884 | 96,094,075 | 412,691 | 44.1 | 38.13 | 224,648 | |
Age group 35-44 years | 1,085,370 | 615,694 | 56.7 | 127,170,126 | 110,739,412 | 469,676 | 43.3 | 34.98 | 249,183 | |
Age group 45-54 years | 862,464 | 518,922 | 60.2 | 98,623,205 | 86,768,281 | 343,542 | 39.8 | 34.51 | 199,434 | |
Age group 55-64 years | 518,294 | 330,161 | 63.7 | 58,285,606 | 51,790,992 | 188,133 | 36.3 | 34.52 | 124,944 | |
Age group 65+ years | 250,420 | 188,149 | 75.1 | 27,395,417 | 25,326,405 | 62,271 | 24.9 | 33.23 | 78,963 | |
Gender Male | 1,643,579 | 992,585 | 60.4 | 195,046,140 | 170,876,697 | 650,994 | 39.6 | 37.13 | 419,561 | |
Gender Female | 3,020,402 | 1,738,561 | 57.6 | 352,171,432 | 307,259,015 | 1,281,841 | 42.4 | 35.04 | 710,823 | |
Region Capital cities | 3,220,794 | 1,746,665 | 54.2 | 387,705,576 | 333,310,309 | 1,474,129 | 45.8 | 36.90 | 740,953 | |
Region Other metro | 406,611 | 268,669 | 66.1 | 45,903,547 | 41,348,924 | 137,942 | 33.9 | 33.02 | 101,922 | |
Region Rural centres | 577,181 | 392,727 | 68.0 | 63,045,538 | 57,295,844 | 184,454 | 32.0 | 31.17 | 155,054 | |
Region Other rural areas | 427,534 | 300,178 | 70.2 | 46,983,183 | 42,935,883 | 127,356 | 29.8 | 31.78 | 120,434 | |
Region Remote areas | 31,828 | 22,891 | 71.9 | 3,575,450 | 3,241,381 | 8,937 | 28.1 | 37.38 | 12,012 | |
Socio-economic disadvantage Quintile 5 (Least) | 1,385,364 | 598,025 | 43.2 | 176,843,753 | 146,864,097 | 787,339 | 56.8 | 38.08 | 298,207 | |
Socio-economic disadvantage Quintile 4 | 1,040,198 | 586,625 | 56.4 | 122,380,008 | 106,271,473 | 453,573 | 43.6 | 35.51 | 245,822 | |
Socio-economic disadvantage Quintile 3 | 905,743 | 578,173 | 63.8 | 102,605,607 | 91,598,973 | 327,570 | 36.2 | 33.60 | 228,413 | |
Socio-economic disadvantage Quintile 2 | 732,988 | 512,346 | 69.9 | 80,322,694 | 73,198,042 | 220,642 | 30.1 | 32.29 | 195,517 | |
Socio-economic disadvantage Quintile 1(Most) | 547,063 | 428,338 | 78.3 | 58,516,903 | 54,639,090 | 118,725 | 21.7 | 32.66 | 149,683 |
1. 2009 figures have regard to all claims processed up to and including 30 April 2010.
2. Fees charged, benefits paid, and average copayments are expressed in 2009 dollars.
3. Only services for which the consumer contributed a co-payment are included in the calculation of the average copayment.
Footnotes
d Mental health need was indicated by the presence of any one of the following: an ICD-10 12-month affective, anxiety or substance use disorder; 12-month symptoms (but no ICD-10 lifetime disorder); any psychiatric hospitalisation in the past 12 months; high or very high level of psychological distress on the K10 measure; 7 or more days out of role; or any suicidality in the past 12 months.
e This assumption was justified on the basis that Medicare subsidised services claimed by psychologists, social workers and occupational therapists for non-Better Access mental health and other services constituted only 2% of all Medicare-subsidised mental health services provided by these providers in 2007.