Impact of disability services on mental health service utilization in adults with intellectual disability.

Background: Can disability support services (DS) facilitate access to mental health services (MHS) for people with intellectual disability? This study utilized 10 years of data from 6,260 persons in NSW who had received DS and specific MHS to quantify the relationship between DS utilization and MHS utilization in adults with intellectual disability and co‐existing mental illness. Results: Receipt of DS was associated with greater odds of accessing community mental health (CMH) services (36%, 95% CI 29%–43%) but not psychiatric admissions. Age, sex and social disadvantage did not affect the odds of psychiatric admission or CMH use. Individuals living in a remote area had greater odds of CMH use and lesser odds of psychiatric admission. Conclusions: Receipt of DS was associated with greater CMH but not psychiatric hospital utilization in people with intellectual disability and co‐existing mental illness.

Keywords: community mental health; data linkage; intellectual disability; mental health; psychiatric admissions

People with an intellectual disability are estimated to comprise around 1%–2% of the population (Maulik, Mascarenhas, Mathers, Dua, & Saxena, 2011; Wen, 1997) but have a higher mortality rate than the general population (Florio & Trollor, 2015) and higher rates of vision, hearing and musculoskeletal impairments, respiratory and congenital heart disease, epilepsy, diabetes, dysphagia, endocrine disorders, osteoporosis, mental health issues, and poorer oral health, injuries, accidents and falls (Emerson, Baines, Allerton & Welch, 2011). Emerson et al. (2011) categorized the determinants of these health inequalities into five main groups: genetic and biological causes (e.g., Down syndrome), social determinants (poverty, discrimination, unemployment), personal health behaviours (e.g., diet and exercise), communication and health literacy, and deficiencies in access to and quality of care.

Inadequate health care for people with intellectual disability has been documented worldwide. Deaths amenable to health care were found to be six times more likely in the population with intellectual disability than the general population in Canada (Hosking et al., 2016). In New South Wales (NSW), Australia, people with intellectual disability experience a higher proportion of deaths from potentially avoidable causes such as infections, cancer and circulatory system issues (Trollor, Srasuebkul, Xu, & Howlett, 2017) and were previously found to have more chronic diseases that were not recognized or appropriately treated (Beange, McElduff, & Baker, 1995). People with intellectual disability are rarely targeted for health prevention and promotion activities (Scheepers, Kerr, & O'hara D, 2005), and a US study found that people with intellectual disability had less usage of preventative dental services such as dental visits and teeth cleanings, and females attended fewer cancer (cervical and breast) screenings than people without disabilities (Havercamp, Scandlin, & Roth, 2004). Barriers may also occur due to impairments in mobility, vision and hearing (Carey et al., 2016) and problems with receptive and expressive communication (Flynn & Gravestock, 2010). Socioeconomic factors also contribute with low income and rurality linked to higher rates of hospitalization for preventable conditions (Balogh, Ouellette‐Kuntz, Brownell, & Colantonio, 2013).

People with intellectual disability also experience higher rates of mental illness than the general population, although estimates vary based on methodology (Cooper, Smiley, & Morrison, 2007). This is commonly not accompanied by increased usage of mental health services (MHS) (Einfeld & Tonge, 1996; Gustafsson, 1997; McCarthy & Boyd, 2002). Diagnosis and treatment are compromised by the same factors impeding access to physical health services: physical difficulties, socioeconomic barriers, sensory and communication impairments. In addition, barriers exist specific to the mental health diagnosis, such as a lack of specialized knowledge, lack of collaboration between disability services and MHS, or misattribution due to diagnostic overshadowing, a phenomenon in which behavioural symptoms indicative of mental illness in people with intellectual disability are likely to be attributed to the intellectual disability instead (Whittle, Fisher, Reppermund, Lenroot, & Trollor, 2018).

Historically in the state of NSW, Australia, mental health and intellectual disability services were typically co‐located within large psychiatric hospitals. Following the Richmond Report (New South Wales Department of Health, 1983) and deinstitutionalization, responsibility for mental health and disability services was provided by separate state government agencies. During the period covered by this study, people diagnosed with intellectual disability could access disability services through the government agency for Ageing, Disability and Home Care (ADHC). Throughout this document, the term disability services will refer generically to any provision of services aimed at assisting people with a disability and the term disability support service (DS) will refer specifically to disability services in NSW that are funded or provided through the ADHC. This centralized system supplied government or government‐contracted providers with funding to establish services that eligible individuals could access. In the 2012–13 financial year, people diagnosed with intellectual disability as their primary or secondary disability made up a third of the DS receiving population, and the intellectual/learning disability category (additionally incorporating autism, learning disabilities and developmental delay) comprised over half (Australian Institute of Health and Welfare, 2014). ADHC provided case management and information services as well as assistance in the domains of self‐care, mobility, communication, interpersonal relationships, learning, education, community life, domestic life and working (Australian Institute of Health and Welfare, 2016).

Mental health services were administered via the NSW Department of Health (NSW Health). NSW Health offered episodic services in hospitals, correctional facilities, in the community, or in people's homes. Community Mental Health Care (CMH) operated via Community Mental Health centres that allowed patients to contact (face to face or by phone/video) specialist mental health service providers (psychiatrists, psychologists, social workers, occupational therapists and nurses) without payment, and to access individual or group mental health treatment. The term Mental Health Service (MHS) will be used as an umbrella term for all state government‐provided services relating to mental health, including the CMH and hospital services that are examined in this study.

The historical separation of disability and MHS led to a siloing of services such that people were viewed as belonging primarily to one service or the other based on their primary presenting problem. This caused a decline in standard of care for people with both intellectual disability and mental illness together (Lennox & Chaplin, 1996) due to a loss of expertise, budget constraints and lack of coordination between the now completely separate services (Molony, 1993; Sullivan, Roberton, & Daffern, 2013). This lack of coordination between disability services and MHS for people with intellectual disability and a co‐existing mental illness has repeatedly been identified as a barrier to appropriate mental health care (NSW Council for Intellectual Disability, 2013; Einfeld, Ellis, & Emerson, 2011; Sullivan et al., 2013; Trollor, 2014). To address this, a number of joint initiatives were established between NSW Health and the ADHC aimed at improving collaboration between mental health and disability support services (NSW Health & ADHC, 2010).

In this context, disability support services have the potential to facilitate access to MHS in people with intellectual disability via practical assistance with mobility and communication, but also via case management and information functions that may allow users to learn about and access MHS available to them. Case management has been found to impact hospitalization under different conditions (Allen, 1998; Coelho, Kelley, & Deatsman‐Kelly, 1993; Dieterich, Irving, & Park, 2010; Hassiotis, Ukoumunne, & Byford, 2001; Mueser, Bond, Drake, & Resnick, 1998; Tricco et al., 2014). What is currently untested is whether disability service access has facilitated access to mental health care for people with intellectual disability in NSW.

Interest in this issue has been reinvigorated by the rapidly changing disability environment under the National Disability Insurance Scheme (NDIS), a national scheme which replaces state‐funded disability services and commenced national rollout in Australia from July 2016. The scheme aims to give more autonomy to people with disabilities by allocating funding to individuals to purchase required services. This moves service provision from state government to private providers, annulling previous joint collaborative initiatives between disability and MHS in NSW. Because the NDIS is federally funded and privately provided, state government is no longer directly involved in the provision of disability support services, reducing the opportunity for oversight and interaction with MHS which are still state based. There is a danger that this loss of interaction between disability and MHS will create a service gap and widen social inequality, particularly for people who require integrated care from both services, as the nature of their disability presents a barrier to navigation of an increasingly self‐driven system. Understanding the role that disability services have played thus far in facilitating access to MHS is therefore important at this transition, as it can be used to clarify the benefits of communication and collaboration between disability and MHS in order to inform policy and best practice in the new system.

This study aims to establish whether receipt of disability support services was associated with mental health service usage (specifically psychiatric admissions and community MHS) in people with intellectual disability and a co‐existing mental illness. We predict that disability support service provision will be associated with greater utilization of community MHS and fewer psychiatric admissions due to facilitating more timely and appropriate access to mental health resources. The impact of age, sex, remoteness and socioeconomic status on mental health service usage will also be assessed due to evidence suggesting that rurality and socioeconomic disadvantage tend to impact mental healthcare use (NSW Health, 2006; Hart, 1971; Saxena et al., 2007; Turrell et al., 1999; Carey et al., 2017).

Administrative datasets relating to disability support services, health services and mortality in NSW were linked as part of a National Health and Medical Research Council Australia funded Partnerships for Better Health grant (ID: APP1056128; Title: Improving the Mental Health Outcomes of People with Intellectual Disability). Detailed information on the linkage project and methods can be found in Reppermund et al. (2017). The project was approved by the NSW Population and Health Services Research Ethics Committee (AU RED Study Reference Number: HREC/13/CIPHS/7; CINSW Reference Number: 2013/02/446 sub study 2018/UMB0305) and conducted at the Department of Developmental Disability Neuropsychiatry at the University of NSW. The four datasets utilized for this study were as follows:

This is the NSW portion of the Disability Services National Minimum Dataset (Australian Institute of Health and Welfare, 2016) and contains records of each individual who received a state government‐funded disability support service in NSW during each financial year between 1 July 2005 and 30 June 2015. This record is limited to whether a service was provided or not during the year, and does not record commencement date. It includes coding for intellectual disability diagnosis as primary or secondary disability.

This contains information (including date of admission, date of separation and length of stay, statistical area code) on every patient episode of care, including psychiatric episodes, provided by NSW public and private hospitals and private day procedure centres from 1 July 2001 to 30 June 2016.

This is collected at the local health district level and comprises information about every occasion of service provided by public CMH services in NSW from 1 January 2001 to 30 June 2016.

This contains information on date of death for all people in NSW. The subset relevant to our cohort was used to determine the duration of follow‐up for each individual in this study.

Primary outcomes were CMH service use and psychiatric admissions (Admissions). For each subject for each financial year (from 2005–06 to 2014–15), data from MHAMB were used to code a CMH variable as 1 if a person received one or more services from CMH during the financial year and coded zero otherwise. Similarly, cleaned data from the APDC were used to code an Admissions variable as 1 if a person had at least one admission to a designated psychiatric inpatient facility during the financial year and 0 otherwise.

The study cohort was all individuals in NSW with an intellectual disability flag in DS‐MDS who received a NSW disability support service (DS) at any time between 1 July 2005 and 30 June 2015 as well as a mental health service (CMH or Admission) at any time between 1 July 2001 and 30 June 2016. For each person in the study cohort, observation began on 1 July 2005 or at the start of the financial year that a person turned 18, whichever occurred last. Observation ended on 30 June 2015, or at 30 June of the financial year in which they turned 65, or at 30 June of the financial year before their death, whichever occurred first. The observation period was determined by the availability of disability support service data (which was from 1 July 2005 to 30 June 2015); however, study cohort formation utilized all mental health data available (from 2001 to 2016). An intellectual disability flag in DS‐MDS indicated that the individual had been assessed as meeting DSM IV criteria (American Psychiatric Association, 1994) for intellectual disability as either their primary or secondary diagnosis.

The study data file contained one record per individual per financial year; however, not all individuals were represented in each financial year due to age or death exclusion criteria. As each participant could appear in the dataset up to 10 times, dependence among repeated observations was controlled in the regression model. Disability support service status was defined as a person actively receiving a state‐funded disability support service (DS) in a financial year (coded 1 for receiving and 0 for not receiving). Age was coded in years, as the person's age on the last day of the financial year. Australian Bureau of Statistics (ABS) statistical area codes were used to code socioeconomic area as a 5‐level categorization based on the ABS 10‐level Index of Relative Social Disadvantage (IRSD), which summarizes information about economic and social conditions within an area such as income, employment, qualifications and occupation (Australian Bureau of Statistics, 2016a). Statistical area was also used to code Remoteness, defined according to the Australian Bureau of Statistics coding of Remoteness Areas (Australian Bureau of Statistics, 2016b), with categories for Outer Regional, Remote, and Very Remote grouped due to low numbers. Financial year was from 1 July to 30 June and was coded as the year that the financial year ended in.

Records missing socioeconomic or remoteness data were excluded from analysis. See Figure 1 for cohort selection flowchart.

Two multivariable logistic regressions were conducted, one for each binary outcome measure (CMH and Admissions). Disability support service (DS) status, age, sex, remoteness, IRSD and financial year were entered into each regression as independent variables, and participant intellectual disability was entered as a repeated subject's covariate. All statistical analyses were completed with SAS version 9.41 using PROC Genmod. Adjusted odds ratios (aOR) with 95% confidence interval (CI) were reported. Familywise error rate was controlled using the Bonferroni correction, with p = .003 as threshold for significance.

At the start of the study period, 58% of participants meeting inclusion criteria were male, and mean and median ages were 36 years and 35, respectively. Most (62%) lived in major cities, while 13% lived in outer regional, remote or very remote areas. 20% fell into the least economically disadvantaged quintile and 14% into the most disadvantaged. See Table 1 for overall and first year demographic data.

1 TABLEDemographic characteristics in total and in first year of study

1 a Age at entry into the study.

DS receivers showed a moderate degree of continuity year on year. Overall, there was between 74% and 90% overlap in the DS receiving population from 1 year to the next (e.g., out of 2007–08 DS receiving population, 74% had also received DS in 2006–07). Longer term, there was sufficient discontinuity in DS receipt such that only 26% of the DS receiving population in the final year of the study had received it continuously since the first year of the study. Overall, 29% of the study population consistently received DS every year that they were in the study (100% continuity), and 13% of the study population showed no continuity (0%) in DS receipt, with all others falling in between. See Appendix for details on population continuity

During the study period, the number of people receiving DS increased steadily until 2013–14 after which numbers dropped. Similarly, the level of co‐servicing (proportion of the population accessing both disability support services and MHS within a year) increased year on year from 2005–06 to 2012–13 but then dropped from 2013 to 2014. Overall, 61% of CMH visits and 62% of psychiatric admissions were by current DS receivers (Table 2).

2 TABLEDisability support and MH service use in cohort by financial year

2 a Proportion of visits recorded in the study population that were by people also receiving DS in that year. Each receiver may make one or more visits.

Table 3 shows aOR, 95% CIs and p values for factors explored in relation to CMH use and psychiatric admissions. Using a Bonferroni correction for 20 significance tests, only p values <.003 are reported as significant.

3 TABLEFactors associated with CMH use and psychiatric admissions

3 * Significant at 0.003.

Individuals receiving DS in a given financial year were more likely to have utilized CMH in that year than those who had not received DS [OR = 1.36, 95% CI 1.29–1.43]. Individuals living in outer regional, remote or very remote areas were more likely to have used CMH compared to those living in major cities [OR = 1.27, 95% CI 1.12–1.43], but the odds did not differ between inner regional and major cities. Social disadvantage, sex, age and financial year were not found to be associated with CMH use.

Individuals receiving DS had similar odds of psychiatric admission to those not receiving DS. Individuals living in outer regional, remote or very remote areas were less likely to have had psychiatric admissions than those in major cities [OR = 0.75, 95% CI 0.62–0.90], and social disadvantage, sex and age showed no differences. Financial year was a factor in psychiatric admissions such that the odds of admission slightly reduced over the time [OR = 0.97, 95% CI 0.96–0.98].

The aim of this study was to determine whether receipt of disability support services was associated with different patterns of mental health service use in adults with intellectual disability and co‐existing mental illness. Our study showed that use of community MHS was higher when people were receiving disability support services, but that rates of psychiatric admissions were not related to receipt of disability support services. Results also showed that CMH was utilized more and psychiatric admissions less in remote areas compared to inner city areas. Social disadvantage was not associated with rates of either type of mental health usage, nor were sex and age. Year was a factor in psychiatric admissions, such that the odds of admission reduced over time.

Although a causal inference cannot be drawn, the increase in CMH servicing when disability support services were received suggests that either disability support services facilitated access to CMH in people with intellectual disability and co‐existing mental illness or that accessing MHS increased the uptake of disability support. This study does not examine the mechanisms by which either may have occurred, but it is plausible that disability support could facilitate access by providing mobility assistance, facilitating health education, or by providing disability case management that informed individuals of the availability of CMH services and/or assisted them to navigate access. Provision of assistance through disability support services could also help in overcoming communication barriers with CMH service providers as those in disability support roles could provide input about changes in functioning and behaviour, facilitating diagnosis and treatment. For the reverse causality, contact with CMH services may have led to informing attendees about the availability and existence of disability support services, although it is notable that contact with psychiatric inpatient services did not show the same association.

The lack of association with psychiatric admissions implies that disability support services did not materially affect access to inpatient psychiatric services, or vice versa. There is no directly comparable research between disability support services and hospital admission, but there are common features with studies on mental health case management models such as assertive community treatment and intensive case management that examine the impact of combining clinical care with social support services and practical supports in daily living. Reviews of these models generally found them effective in reducing time spent in hospitals for mental illness (Dieterich et al., 2010; Mueser et al., 1998), although other studies found hospital admissions to be reduced only for patients with chronic physical conditions but not for patients with mental illness (Tricco et al., 2014). Studies on the population with intellectual disability specifically have found that case management reduced length of stay but not number of psychiatric admissions (Allen, 1998), or shifted admissions from high care services such as state psychiatric wards to lower care respite services (Coelho et al., 1993). Only for patients with intellectual disability with psychosis specifically, case management reduced both admissions and days in hospital (Hassiotis et al., 2001).

The result showing lesser use of psychiatric inpatient facilities in rural compared to inner city areas is likely due to limited availability of psychiatric hospital beds in less populated areas (NSW Health, 2006). The greater use of CMH services in rural over inner city areas suggests a compensatory mechanism in the face of limited inpatient facilities.

The lack of association between socioeconomic disadvantage and measures of mental health care use was incongruent with general health research. The "Inverse Care Law" notes that "the availability of good medical care tends to vary inversely with the need for it in the population served" (Hart, 1971: p. 405), and this has been shown to occur with mental health care also (Saxena et al., 2007). In Australia however, people in low socioeconomic areas have been found to attend a higher number of medical consultations (albeit shorter) and were more likely to be high mental health users (Turrell et al., 1999), possibly reflecting the benefits of a universal healthcare system in which hospitalization in a public hospital is free for those who require it. It appears that people with intellectual disability were not experiencing socioeconomically based disadvantages in their access to MHS in NSW between 2005 and 2015.

Because this study was observational (participants were not randomly allocated to a condition), the associations found show correlation, not causation. Directionality cannot be assumed, and it is also possible that an unmeasured factor may be responsible for both results; for instance, disability support service use may have occurred during periods of greater mental illness and need that also resulted in sourcing more types of service.

A limit to generalizability is that our population selection captures only individuals who accessed disability support services and hospital/CMH treatment. It may exclude the most disadvantaged, those people who lacked the capacity or advocacy to seek services, as well as the most advantaged, people with well funded supports who accessed private outpatient MHS only. Our selection also excludes people with mild levels of mental illness that did not result in inpatient admission or meet severity criteria for access to community MHS. The sample is potentially a biased subset of the wider population of adults with intellectual disability and mental health issues.

There is also systematic error introduced because there was no way to detect participants who moved in or out of NSW during the study period. They would be included in the observation pool as disability support service non‐receivers and non‐mental health users. This could bias the findings in the direction of showing that disability support service non receivers had lower mental health utilization for both CMH and psychiatric admissions, particularly in the later years of the study. However, this occurrence is expected to be infrequent, as people with intellectual disability tend to move rarely, often living with their parents until late middle age and then moving to a community facility (Beer & Faulkner, 2008).

Having established a connection between MHS and disability support services, the next step would be to explore what facets of disability support were most closely related to mental health servicing. As noted, Australian disability services are in transition to the NDIS, a system which gives previously denied choice and decision making to people with a disability and their carers, but removes an opportunity for oversight and interactions between MHS and disability providers. It is important to know which previous elements were helpful in facilitating access to community MHS by people with intellectual disability, so that this benefit is not inadvertently lost in the changeover process. The present study implies that provision of disability services can facilitate the provision of community MHS; however, it is specific to a time (2005–2015), place (NSW) and context (a particular style of government‐provided disability support service) and does not automatically generalize to all disability services.

In the Australian context, the NDIS is a very different model of disability support to that investigated in the current study, and it is not known how it may act to facilitate or hinder access to MHS for people with intellectual disability. NDIS data systems are not currently able to contribute to research of the type conducted here, so there is no capacity to scrutinize whether the NDIS has any positive or negative impact upon MHS provision to people with a disability. In future, it would be valuable to examine how people with intellectual disability and a co‐existing mental illness are being serviced through the transition to NDIS. Carey et al. (2017) raise concerns about the potential for personalization schemes such as the NDIS to widen socioeconomic inequalities given that people with intellectual disability may lack the capability to exercise choice, planning and control over providers and may be reliant on their support networks for advocacy. They note that people with mental illness and intellectual disability are the population least likely to opt into the (voluntary) personalization scheme operating in the UK, and also indicate that free market models disadvantage people in sparsely populated areas where markets are thin. Recommendations have been made by the Council for Intellectual Disability (2018) on how to bridge the gap in the NDIS for people with complex needs, such as training specialist planners, funding disability advocacy and continuing funding of rural psychiatric health services funded by ADHC. The National Disability Insurance Agency (NDIA) that manages the NDIS has announced that a complex support needs pathway will be implemented to improve access to services from October 2018 (National Disability Insurance Agency, 2018) but it is not yet clear what this will involve. Our findings suggest that it is possible to design service systems so that people with intellectual disability and complex needs can receive an appropriate set of services (including MHS) that meet their needs.

The year‐on‐year changes found in psychiatric admissions data indicate another potentially useful future investigation. Allen (1998) found that community support altered length of psychiatric hospital stay but admissions did not fall until the introduction of specialist intervention services. Investigating the correlates of the reduction in admissions during our study period may provide information about whether and what initiatives may have contributed, and how any benefits of these can be maintained or replicated after the closure of state programmes.

In the broader picture, the role of disability services in facilitating healthcare access outside the mental health arena should be explored. Care coordination has been found to reduce emergency department attendance in chronic conditions other than mental illness (Tricco et al., 2014), suggesting that the interdependence between disability services and health services may extend beyond the intellectual disability and mental health arena.

The demarcation between mental health and disability support services was identified as one of the most prominent barriers to good quality mental health (NSW Council for Intellectual Disability, 2013). This is the first study to test the link between disability support servicing and mental health utilization and supports the importance of collaboration as an enabler of mental health care, demonstrating that practical support in the community may be leveraged to improve access to mental health care.

APPENDIX

DS Population Continuity

Two methods were used to gauge the degree of continuity in the population receiving DS over the study period. The first aimed to describe continuity on an individual person basis. For every 2‐year span, each person was allocated a score of 1 if they had maintained the same DS status over the period (of either receiving DS or not receiving DS) or 0 if they either started or stopped receiving DS during the period. A percentage was calculated of "1" records over the total number of records for that person (which was a maximum of 9 depending on when they entered the study). A person who maintained the same DS status throughout the study would receive 100%, and one who changed status every year would receive 0%. This score considers continuity in both receiving and not receiving.

The population varied in consistency, with 29% of the total study population scoring 100%, 32% scoring between 50% and 100%, 23% scoring between 1% and 49%, and 15% scoring zero continuity. A frequency histogram is shown in Table A1.

TABLE Study population consistency score histogram

A second measure of continuity was determined for the population as a whole. The "1‐year continuity" number is the count of people receiving DS in a given year who had also received it in the previous year. The "% overlap" is this number over the total number of DS receivers in the latter year. This was calculated for 1, 2, 3, 5 and 10 years, and is shown in Table A2.

There was between 74% and 90% overlap between any 2 years, falling to 49% −71% for 3‐year continuity (i.e., no change in DS status for 4 consecutive years). In the final year of the study, 26% of DS receivers had been receiving it continually since the first year of the study.

TABLE Year‐on‐year continuity in DS receiving population