Unmet treatment need: The size of the gap for alcohol and other drugs in Australia
Drug Policy Modelling Program, Social Policy Research Centre, UNSW Sydney, Sydney, Australia
Abstract
Introduction
Assessing unmet demand for alcohol and other drug (AOD) treatment requires accurately counting those in treatment and determining those in need of treatment. Using updated epidemiological and treatment data, this study sought to provide an updated estimate of the unmet demand for AOD treatment in Australia.
Methods
Australian prevalence rates for alcohol, cannabis, methamphetamine and opioid use disorders were obtained from the Global Burden of Disease and research studies. The estimated proportion of people who would likely not seek or need treatment were subtracted from the diagnosed population. The number of people receiving treatment was estimated using AOD treatment databases and previous research.
Results
An estimated 752,812 to 1,291,119 people met criteria for a substance use disorder in Australia in 2023. Removing the proportion of people who would not need or seek treatment resulted in between 406,697 and 668,497 people as the potential treatment population. The number of people who received treatment in Australia was estimated at 198,731 people. The unmet demand for AOD treatment was estimated to be between 207,966 and 469,767 in 2023.
Discussion and Conclusions
In Australia, we only treat between 30% and 48% of the population who would seek and benefit from AOD treatment. This is a conservative analysis that assumes only 40% of the alcohol and cannabis use disorder population would seek treatment. The findings from this analysis highlight the continued significant unmet treatment needs of people with substance use disorders. Treatment resources need to be doubled in order to address this unmet treatment population.
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Keywords: alcohol, drugs, healthcare planning, treatment demand, treatment need
Article notes
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Revised 2025 Jan 5; Received 2024 Aug 15; Accepted 2025 Jan 15; Issue date 2025 Mar.
Boxed Text
- Previous analyses of the size of the alcohol and other drug (AOD) treatment gap in Australia are outdated, given epidemiological changes and better treatment data. This study sought to provide an up‐to‐date estimate of the size of unmet demand for AOD treatment in Australia.
- With 198,731 people receiving AOD treatment in Australia in 2023, this represents between 30% and 48% of the population who would seek treatment.
- Between 207,966 and 469,767 people missed out on AOD treatment in Australia in 2023.
- The findings from this analysis highlight the continued significant unmet demand for treatment of people with substance use disorders.
- Treatment resources need to be doubled in order to address this unmet treatment population.
1.INTRODUCTION
People who receive alcohol or other drug (AOD) treatment represent a very small proportion of all people diagnosed with a substance use disorder (SUD) [1, 2, 3, 4, 5]. This ‘unmet need’ population has been estimated for many countries and, while the findings vary by country, they are consistently and staggeringly high, with the proportion who do receive treatment rarely exceeding 15% [3, 6, 7]. For example, there was a reported 12% treatment access rate in Singapore [8], 8–13% in the United States [1, 9, 10], 4% in Lesotho [11] and about 16% in Germany [12]. One systematic review found an average of 17% of people with alcohol use disorder accessed treatment in the past year across 25 different countries [13]. Australia has a reportedly similar low rate of treatment access; the 2020–2022 National Study of Mental Health and Wellbeing [14] shows that 9.5% of people with any SUD reported accessing professional treatment for AOD in the past year, mirroring international findings.
These figures, suggesting that around 80% to 90% of people with a diagnosed SUD do not receive treatment, are very confronting for governments seeking to plan and fund AOD treatments. The overwhelming size of the unmet need population has the potential to impede effective treatment scale‐up. At the same time, these figures may not be the best representation of the size of the treatment gap. Importantly, many people with SUD recover without any formal treatment [15, 16, 17, 18]. While this varies by drug type and study design, it may be as high as 63% of the remitted population for alcohol [19] and 56% for cannabis [15]. In addition, if the above unmet need estimates only count those who receive AOD treatment within a specialist AOD setting, they are likely to under‐count treatment delivered. For example, many people receive help with their AOD problems from mental health services, primary care services and other non‐AOD treatment services and settings [20, 21].
A more careful approach to counting the number of people who do receive treatment, alongside adjustments to the population in need of treatment to reflect recovery without formal treatment and treatment seeking intentions, will result in more robust estimates of the size of the population who miss out on AOD treatment. We previously conducted such analyses for Australia [4, 22], finding that rather than a gap of 80% to 90%, it was in the order of 44% to 74%. This suggested that we were treating around half the number of people suitable for treatment in Australia. Those analyses used SUD rates from 1997 for alcohol and cannabis, 2005 for amphetamines, and 2009 for opioids. Over the last 20‐years, there have been significant changes in the nature and patterns of substance use across Australia. For example, there has been a reduction in alcohol consumption amongst young people in Australia between 2001 and 2022/2023 [23], methamphetamine use and harms have steadily increased over the past 10‐years [24], and amphetamines have overtaken cannabis as the second most common principal drug of concern at AOD treatment services [25].
In addition, the AOD treatment environment has changed considerably since that time. Estimates suggest spending on treatment has increased, including as a proportion of total spending on illicit drug policy [26]. Finally, to date the work on unmet need and demand for treatment has not taken into consideration the important role that brief interventions can play in preventing future treatment‐seeking. Screening and brief interventions have been shown to be efficacious and cost‐effective for alcohol [27, 28, 29] though there are mixed findings for the efficacy for other drugs [30].
In this paper, we report new estimates for the size of the gap between the population of people meeting diagnostic criteria for an SUD who would be suitable for and likely to seek treatment, compared to the number of people who currently receive AOD treatment in Australia. We conduct separate analyses for alcohol, cannabis, methamphetamine and opioid use disorders, and include an estimate for brief interventions delivered to those with an SUD who do not receive comprehensive treatment.
2.METHODS
Australian diagnostic prevalence rates for alcohol and cannabis use disorders were drawn from the 2021 Global Burden of Disease (GBD) study [31] in 5‐year age increments, which we matched to 2023 Australian population estimates for people aged over 10 years from the Australian Bureau of Statistics [32]. Methamphetamine use disorder prevalence rates, for those 15 years and older, were also sourced from the Australian GBD data and matched to 5‐year age increments. For opioids, and in light of the low population prevalence we used a more specific data source [33], which provided the prevalence of opioid use disorders in Sydney, Australia for 15 to 64 year olds. The rates from Downing et al. [33] are 1.7 to 2.1 times higher than those provided by GBD. As the authors acknowledge, their estimates are higher than previously published in both household surveys and indirect estimations due to more advanced and comprehensive epidemiological methods [33]. The prevalence rates are provided in Table A1.
Both the GBD [31] and Downing et al. [33] provide a main estimate and an upper and lower confidence interval estimate for the prevalence of SUD. In the analysis, we therefore report three estimates (main, lower and upper) for the number of people who should receive treatment, paralleling these differing prevalence estimates.
In order to take into account recovery in the absence of treatment, and the proportion of people who would not seek treatment for their SUD, we triangulated two different data sources: published research on rates of ‘natural recovery’ or ‘spontaneous remission’, and data on intentions to seek help. In relation to the former, for alcohol, an average of 50% of people in remission are likely to resolve their alcohol use disorder in the absence of treatment [19]. 1 For cannabis, research suggests average remission rates are about 55–65% [15, 34], of which about half resolve their cannabis issues without treatment [17, 35]. Methamphetamine use disorder appears to have much lower rates of natural remission compared to alcohol or cannabis [16, 35, 36]. One Australian study found 18% of people who were methamphetamine dependent remitted without any professional treatment at 12‐month follow up [16].
For opioids, there was limited research on natural recovery or spontaneous remission. One US study found about 70% of people who remitted from an opioid use disorder utilised some form of treatment, but did not measure what proportion of people remit [35]. Previous research has found low rates of remission for opioid use disorder in a 3‐year period at approximately 40% [37]. These findings suggest most people with an opioid use disorder will require some form of treatment, notably opioid agonist therapy.
Turning to data on intentions to seek help, the National Study of Mental Health and Wellbeing (NSMHWB) asked people whether they perceived a need for mental health services (“Whether perceived need for information on mental health was met”). While not a perfect match for treatment seeking intentions because it is not specific to AOD treatment, it is a reasonable proxy. For those people meeting criteria for alcohol use disorder, 51.8% did not perceive a need for treatment [14]. For the more generic category of SUD, it was 50.4%. These data are provided in Tables A2, A3, A4.
Triangulating the above two sources of information, it suggests that an appropriate treatment rate to apply to the population prevalence for alcohol use disorder is 40%. The same proportion (40%) is applied to the cannabis use disorder population. For methamphetamines, a lower number is likely to recover without treatment compared to alcohol and cannabis, and the NSMHWB does not provide a directly comparable figure for intentions to seek help. In the absence of further data, we assume that 75% of people with methamphetamine use disorder are likely to seek treatment. Finally for opioid use disorder, there are very limited data to suggest an appropriate treatment rate. For this work, we assume we should treat 90% of the diagnosed population.
This method to determine the percentages of the diagnosed population who would seek treatment has been used in previously published work [4, 38, 39]. Furthermore, the above percentages accord with expert consensus around Australia. The final rates of people who should receive treatment and the associated sources are provided in Table A5.
That many people who meet diagnostic criteria for SUD (60% for alcohol and for cannabis) are not presumed to seek treatment in this analysis raises public health concerns. The opportunity to provide a single session brief intervention (most likely in a non‐specialist setting) is an opportunity to provide information about seeking treatment, harm reduction advice and any other health or social supports. This recognises that while not everyone who meets diagnostic criteria will want or seek formal, professional AOD treatment, they likely still have other unmet health and wellbeing needs. We refer to this as a brief intervention but recognise there is insufficient evidence on whether brief interventions are effective for people with a SUD (as opposed to those at‐risk) [30]. In addition, this modelling work aims to inform governments and the pragmatic context of government funding is such that treatment availability will never match full demand (like any other health service). The inclusion of brief interventions for those with SUD recognises this reality. To that end, we model the number of people meeting SUD criteria who could be suitable for a brief intervention in the absence of formal treatment.
Turning to the methods for estimating the number of people who did receive AOD treatment, in 2023, we accessed the two main existing databases on AOD treatment in Australia: the Alcohol and Other Drug Treatment Services National Minimum Dataset (AODTS‐NMDS) and the National Opioid Pharmacotherapy Statistics Annual Dataset (NOPSAD). The AODTS‐NMDS, published annually, counts all specialist AOD treatment provided through services that receive government funding [25]. This includes government run services, non‐government organisations (that receive government funding) and some outpatient hospital services.
The NOPSAD is a census‐based data collection, that counts the number of people who received opioid agonist therapy in Australia in different settings (e.g., public clinics, specialist AOD services, prisons). The data are collected on a snapshot day in June and the numbers are adjusted to reflect those that receive weekly or monthly medications.
These two datasets provide comprehensive data for the bulk of AOD treatment provided in Australia. However, there are other providers of AOD treatment not necessarily included within these two datasets, including general practitioners, allied health practitioners, Aboriginal Community Controlled Organisations, and private psychologists and psychiatrists. There are no routine administrative datasets that count AOD treatment in these settings. We relied on a previous research study [20] which counted all AOD treatment across these settings, in addition to the AODTS‐NMDS and NOPSAD at that time. We calculated the ratio that these other settings comprised of the total treated population in that study (as detailed in Tables A6, A7). The total number of clients receiving treatment across all settings was 1.6 times that provided in the two main datasets alone (see Tables A6, A7). We applied this multiplier to the current 2023 data, to derive an estimated number of people receiving treatment across all settings for 2023. We tested the reliability of the treatment utilisation numbers against the estimates from the NSMHWB (as reported in the Results). This method includes the allied health and general practice providers outlined above but excludes non‐professional or informal types of care such as mutual aid or 12‐steps support groups.
3.RESULTS
The number of people estimated to have an SUD for the modelled substances (low, mid and high estimate) in Australia for 2022/2023 is shown in Table 1.
There are an estimated 752,812 to 1,291,119 people aged 10 and over who meet criteria for a SUD in Australia, for 2022/2023.
Removing the proportion of people who would remit without treatment and/or will not seek treatment (60% for alcohol and cannabis; 25% for methamphetamines, and 10% for opioids), results in between 406,697 and 668,497 people who should receive treatment in 2022/2023 (see Table 2).
| Drug type | Low prevalence treatment number | Mid prevalence treatment number | High prevalence treatment number | Proportion of the diagnosed population |
|---|---|---|---|---|
| Alcohol a | 159,298 | 217,276 | 287,936 | 40.0% |
| Cannabis a | 46,734 | 63,331 | 84,001 | 40.0% |
| Amphetamines b | 66,470 | 100,416 | 142,942 | 75.0% |
| Opioids c | 134,195 | 143,128 | 153,618 | 90.0% |
| Total | 406,697 | 524,151 | 668,497 | ‐ |
For the remaining individuals, those who meet diagnostic criteria but are outside the proportion of people modelled to receive treatment, a brief intervention is a sensible public health measure. The number of people modelled to receive brief intervention is provided in Table 3.
| Drug type | Low prevalence treatment number | Mid prevalence treatment number | High prevalence treatment number | Proportion of the diagnosed population |
|---|---|---|---|---|
| Alcohol | 238,947 | 325,914 | 431,904 | 60.0% |
| Cannabis | 70,101 | 94,997 | 126,001 | 60.0% |
| Amphetamines | 22,157 | 33,472 | 47,647 | 25.0% |
| Opioids | 14,911 | 15,903 | 17,069 | 10.0% |
| Total | 346,115 | 470,285 | 622,622 | ‐ |
An estimated 346,115 to 622,5622 people should receive a brief intervention for a substance use disorder in 2022/2023.
The primary estimate of the number of people actually receiving AOD treatment in Australia in 2022/2023 is 198,731. This is shown in Table 4.
| Drug type | Clients in NOPSAD and AODTS | Clients in other settings | Total |
|---|---|---|---|
| Alcohol | 40,083 | 23,248 | 63,330 |
| Cannabis | 24,017 | 13,930 | 37,947 |
| Amphetamines | 22,870 | 13,264 | 36,134 |
| Opioids | 61,320 | ‐ | 61,320 |
| Total | 148,289 | 50,442 | 198,731 |
We tested the reliability of this figure (198,731) against NSMWHB data. The NSMHWB provided the proportion of the sample self‐reporting accessing AOD treatment in the past year who met diagnostic criteria for an SUD [14]. Converting our estimate of treatment utilisation into a proportion of the diagnosed population, Table 5 shows that the results we obtained on treatment utilisation are very similar to those reported in the NSMHWB providing confidence in our estimates.
| Drug type | Proportion of diagnosed population who received treatment | |
|---|---|---|
| Our estimate (mid estimate) | NSMHWB estimate | |
| Alcohol | 11.7% | 13.7% |
| Other drugs | 29.8% | 20.0% |
| Total (all substances) | 19.9% | 17.5% |
Comparing the number of people who met diagnostic criteria and were suitable for treatment, with the number of people who received treatment in Australia provides a gap analysis. Table 6 shows the number of people who miss out on treatment; between 207,966 and 469,767 people missed out on AOD treatment in Australia for 2022/2023.
| Drug type | Low prevalence | Mid prevalence | High prevalence |
|---|---|---|---|
| Alcohol | 95,967 | 153,945 | 224,606 |
| Cannabis | 8788 | 25,384 | 46,054 |
| Methamphetamine | 30,336 | 64,282 | 106,808 |
| Opioids | 72,876 | 81,808 | 92,299 |
| Total | 207,966 | 325,420 | 469,767 |
Expressed differently, out of the potential treatment population, between 30% and 49% of people received AOD treatment in Australia in 2022/2023 (see Table 7).
| Drug type | Low prevalence | Mid prevalence | High prevalence |
|---|---|---|---|
| Alcohol | 39.8% | 29.1% | 22.0% |
| Cannabis | 81.2% | 59.9% | 45.2% |
| Methamphetamine | 54.4% | 36.0% | 25.3% |
| Opioids | 45.7% | 42.8% | 39.9% |
| Total | 48.9% | 37.9% | 29.7% |
We did not analyse the number of people missing out on brief interventions, as we do not have adequate data on receipt of brief interventions to undertake this analysis.
Two previously published estimates (2014 and 2019) of the population proportion who did receive treatment, reveals little change over time, as shown in Table 8.
4.DISCUSSION
The findings from this analysis highlight the continued significant unmet treatment needs of people with SUDs. Less than a third to half of those who should receive treatment accessed treatment in 2022/2023. This is not dissimilar to previous estimates, which ranged from a quarter to half of those in need of treatment receiving treatment [4, 22]. In the NSMHWB, 35–40% of people with a substance dependence disorder reported accessing a mental health service in the past year [14]. While it is not clear whether this was for their AOD use or another mental health issue, it fits within our estimations, providing further confidence in our methods.
The consistent findings of significant unmet demand for AOD treatment suggests there has been little change in the proportion of people in need of treatment who receive it per year. This aligns with the data published by the Australian Institute of Health and Welfare [25], which shows only a small increase in AOD treatment access per 100,000 people (564 and 568 in 2013/2014 and 2022/2023 respectively). In addition, the recent Australian ‘Drug Budgets’ found despite an increase in spending on illicit drug policy (including treatment), spending as a proportion of all government expenditure had decreased between 2009/2010 and 2021/2022 [26].
While many studies report unmet treatment need rates of up to 80–90% of the diagnosed population [1, 9, 11, 12], this approach assumes that everyone who meets diagnostic criteria for SUD should receive treatment. In our work, we reduce the potential in‐need population substantially because we take into account both untreated remission and recognise that some people have no desire to receive treatment. This produces a much more realistic ‘treatment gap’. At the same time it is subject to greater uncertainty. However, other methods for assessing the size of treatment gap, for example the use of wait list data, or surveys of key populations who miss out on treatment can bias results. Assuming that only 40% of all people with an alcohol or cannabis use disorder are likely to seek and benefit from treatment shows how conservative the analyses are—the treatment gap reported here is likely to be the minimum gap.
The population who meet diagnostic criteria but are not included in the treatment estimates are likely to still benefit from some form of intervention. As others have highlighted [40], a less intensive intervention, possibly provided in a primary care setting may be adequate. Our work provides an estimate of the number of people who could receive a brief intervention. Another population to be considered are those people who do not meet diagnostic criteria but are consuming in ‘risky’ quantities or experiencing harms. This is sometimes called the ‘at‐risk’ population. Some of these people may seek or perceive a need for treatment, and would likely benefit from some form of intervention. Investing in interventions at the earlier stages of someone's substance use can prevent the need for more intensive interventions later on. Similarly, investing in prevention interventions, such as education and social supports, as well as pricing and other regulatory policies for legal drugs such as alcohol [41], would reduce the need for AOD treatment in the long‐term.
4.1. Limitations
There are several key assumptions made in deriving these estimates. One assumption is the proportion of the population meeting diagnostic criteria who intend to seek treatment, and do not resolve their AOD problems without intervention. Estimating this proportion of the diagnosed population (40–90% depending on the drug type) is subjective. While based on the best available evidence and expert advice, there is considerable uncertainty in these parameters which can impact the resulting estimates.
In addition to the proportion of the diagnosed population who we assume should receive treatment, there have been many changes made to the diagnostic criteria over time [21]. The number of people who meet diagnostic criteria over time will therefore inevitably change, even if the number of people experiencing difficulties or harms remains stable.
We also have considerable uncertainty in the number of people who do receive treatment. While we have comprehensive data from the two main databases in Australia, the number of people accessing treatment outside these two databases is less clear. We employed a multiplier from an earlier analysis, however we do not know whether the proportion of treatment delivered in these settings has changed since that analysis.
Our analysis is focused on Australia nationally. We know that some geographic regions and populations have higher treatment need than others. These findings are therefore only applicable to Australia as a whole, but cannot be used to determine treatment needs in a particular region/area. In addition, this work does not provide estimation of treatment gaps for specific service types (e.g., withdrawal or residential rehabilitation). It also does not include one substance associated with high health costs, tobacco [42]. Analysis of unmet demand for tobacco/nicotine dependence treatment would be a valuable area for future research.
4.2. Implications
AOD treatment is significantly underfunded and under‐resourced. In 2022/2023, less than half of the people suitable for AOD treatment received it. Understanding the population in need, and those not receiving treatment can help to better plan for treatment services. In this paper we have provided an updated analysis of the number and proportion of people ‘missing out’ on AOD treatment, which may be used to better plan for service needs.
CONFLICT OF INTEREST STATEMENT
None.
ACKNOWLEDGEMENTS
Alison Ritter receives a National Health and Medical Research Council Investigator Fellowship, GNT2016695. This work has been informed by projects updating the Drug and Alcohol Services Planning Model. The authors thank the Queensland Department of Health and the Victorian Department of Health for their funding of these projects, as well as the many Expert Reference Group members who guided the development of the Drug and Alcohol Services Planning Model. Open access publishing facilitated by University of New South Wales, as part of the Wiley ‐ University of New South Wales agreement via the Council of Australian University Librarians.
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PREVALENCE RATES FOR THE FOUR DRUG TYPES USED IN THE ANALYSIS
| Age group, years | |||||||||||||||
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 10–14 (%) | 15–19 (%) | 20–24 (%) | 25–29 (%) | 30–34 (%) | 35–39 (%) | 40–44 (%) | 45–49 (%) | 50–54 (%) | 55–59 (%) | 60–64 (%) | 65–69 (%) | 70–74 (%) | 75–79 (%) | 80+ (%) | |
| Low | |||||||||||||||
| Alcohol a | 0.07 | 0.80 | 1.95 | 2.53 | 2.48 | 2.70 | 2.53 | 2.25 | 1.73 | 1.59 | 1.30 | 1.17 | 0.96 | 0.83 | 0.98 |
| Cannabis a | 0.11 | 1.58 | 1.84 | 1.06 | 0.63 | 0.43 | 0.31 | 0.23 | 0.17 | 0.12 | 0.08 | 0.05 | 0.03 | 0.02 | 0.01 |
| Amphet a | 0.00 | 0.27 | 1.26 | 1.40 | 0.81 | 0.46 | 0.28 | 0.15 | 0.07 | 0.04 | 0.03 | 0.02 | 0.02 | 0.01 | 0.02 |
| Opioids b | 0.89 | 0.89 | 0.89 | 0.89 | 0.89 | 0.89 | 0.82 | 0.82 | 0.82 | 0.82 | |||||
| Main | |||||||||||||||
| Alcohol a | 0.13 | 1.23 | 3.05 | 3.51 | 3.50 | 3.49 | 3.34 | 2.85 | 2.37 | 2.04 | 1.75 | 1.50 | 1.30 | 1.21 | 1.25 |
| Cannabis a | 0.19 | 2.13 | 2.33 | 1.41 | 0.88 | 0.61 | 0.45 | 0.34 | 0.25 | 0.17 | 0.11 | 0.07 | 0.05 | 0.04 | 0.02 |
| Amphet a | 0.00 | 0.43 | 1.93 | 2.03 | 1.20 | 0.72 | 0.43 | 0.23 | 0.12 | 0.07 | 0.05 | 0.04 | 0.03 | 0.02 | 0.03 |
| Opioids b | 0.94 | 0.94 | 0.94 | 0.94 | 0.94 | 0.94 | 0.89 | 0.89 | 0.89 | 0.89 | |||||
| High | |||||||||||||||
| Alcohol a | 0.22 | 1.83 | 4.56 | 4.78 | 4.77 | 4.34 | 4.16 | 3.50 | 3.20 | 2.66 | 2.33 | 1.91 | 1.65 | 1.50 | 1.57 |
| Cannabis a | 0.28 | 2.76 | 2.99 | 1.84 | 1.20 | 0.81 | 0.62 | 0.49 | 0.36 | 0.24 | 0.16 | 0.11 | 0.07 | 0.05 | 0.03 |
| Amphet a | 0.00 | 0.63 | 2.78 | 2.81 | 1.69 | 1.02 | 0.64 | 0.34 | 0.18 | 0.11 | 0.08 | 0.06 | 0.04 | 0.03 | 0.04 |
| Opioids b | 1.00 | 1.00 | 1.00 | 1.00 | 1.00 | 1.00 | 0.97 | 0.97 | 0.97 | 0.97 | |||||
NATIONAL STUDY OF MENTAL HEALTH AND WELLBEING 2020–2022 DATA, DRAWN FROM THE AUSTRALIAN BUREAU OF STATISTICS TABLE BUILDER
| Response | Alcohol use disorder (%) | Alcohol dependence (%) | Drug dependence a (%) | Substance use disorder (%) | Substance dependence (%) |
|---|---|---|---|---|---|
| Need fully met | 16.4 | 17.9 | 12.7 c | 15.2 | 18.3 |
| Need partially met | 21.3 | 29.8 | 47.7 | 24.8 | 37.2 |
| Need not met | 9.9 | 11.0 | 8.8 b | 10.0 | 9.7 |
| No need | 51.8 | 43.0 | 31.4 b | 50.4 | 35.8 |
| Not known | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 |
| Refused | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 |
| Total | 100.0 | 100.0 | 100.0 | 100.0 | 100.0 |
| Diagnosis | Accessed a professional treatment for alcohand other drugs? | |||
|---|---|---|---|---|
| Yes (%) | No (%) | NA/unknown (%) | Total (%) | |
| Alcohol dependence | 13.7 | 33.4 | 54.4 | 100 |
| Alcohol abuse | 2.0 | 19.7 | 78.8 | 100 |
| Alcohol use disorder | 7.1 | 23.9 | 68.0 | 100 |
| Drug dependence a | 20.0 | 45.0 | 32.6 | 100 |
| Drug abuse a | 7.8 | 22.2 | 62.8 | 100 |
| Substance dependence | 17.5 | 32.9 | 48.8 | 100 |
| Substance abuse | 3.5 | 19.8 | 76.3 | 100 |
| Any substance use disorder | 9.5 | 26.0 | 65.2 | 100 |
| Type of health professional | Alcohol dependence (%) | Any alcohol use disorder (%) | Drug dependence (%) | Substance dependence (%) | Any substance use disorder (%) |
|---|---|---|---|---|---|
| Health professionals (GP, specialist doctor, surgeon, other) | 42.1 | 31.0 | 47.1* | 44.2 | 34.3 |
| Mental health professionals (psychiatrist, psychologist, mental health nurse, other) | 35.9 | 30.2 | 44.9 | 41.1 | 31.7 |
| None | 52.2 | 61.2 | 37.6 | 42.9 | 58.0 |
| Total | 100.0 | 100.0 | 100.0 | 100.0 | 100.0 |
DATA USED TO INFORM THE ESTIMATED NUMBER OF PEOPLE WHO SHOULD RECEIVE TREATMENT
| Drug type | Proportion to treat (%) | Sources |
|---|---|---|
| Alcohol | 40 | Mellor et al., 2019; NSMHWB; previous expert reference groups for DASPM |
| Cannabis | 40 | Feingold et al., 2015; van der Pol et al., 2015; Kelly et al., 2017; Stea et al., 2015; NSMHWB; previous expert reference groups for DASPM |
| Methamphetamine | 75 | Quinn et al. (2016); previous expert reference groups for DASPM |
| Opioids | 90 | Kelly et al., 2017; Fleury et al., 2016; Previous expert reference groups for DASPM |
DATA USED TO INFORM ESTIMATED NUMBER OF PEOPLE RECEIVING ALCOHOL AND OTHER DRUG TREATMENT IN AUSTRALIA
| Drug type | AODTS‐NMDS | NOPSAD | Total |
|---|---|---|---|
| Alcohol | 40,083 | ‐ | 40,083 |
| Cannabis | 24,017 | ‐ | 24,017 |
| Methamphetamine | 22,870 | ‐ | 22,870 |
| Opioids | 5579 | 55,741 | 61,320 |
| Total | 92,548 | ‐ | 148,289 |
| Treatment provider | Number of people a | Low estimate (running total) | High estimate (running total) b |
|---|---|---|---|
| Government funded specialist AOD treatment services | 97,467 | 97,467 | 97,467 |
| Opioid agonist treatment | +50,071 | 130,032 | 130,032 |
| Total from two main datasets | ‐ | 130,032 | 130,032 |
| Aboriginal Community Controlled Organisations | +32,564 | 138,445 | 168,696 |
| General practitioners | +8413–38,664 | 138,445 | 168,696 |
| Inpatient hospitals | +0 | 188,516 | 218,767 |
| Mental health services and allied health | +13,652 | 202,168 | 232,419 |
| Total from all settings | ‐ | 202,168 | 232,419 |
| Multiplier (total from all datasets/total from main datasets) | ‐ | 1.56 | 1.79 b |
Untitled section
Ritter A, O'Reilly K. Unmet treatment need: The size of the gap for alcohol and other drugs in Australia. Drug Alcohol Rev. 2025;44(3):772–782. 10.1111/dar.14008
Endnote
Footnote Group
DATA AVAILABILITY STATEMENT
These data were derived from the following resources available in the public domain: GBD Results 2021, https://vizhub.healthdata.org/gbd-results/; Alcohol and other drug treatment services in Australia, https://www.aihw.gov.au/reports/alcohol‐other‐drug‐treatment‐services/alcohol‐other‐drug‐treatment‐services‐australia/data; National Opioid Pharmacotherapy Statistics Annual Data, https://www.aihw.gov.au/reports/alcohol‐other‐drug‐treatment‐services/national‐opioid‐pharmacotherapy‐statistics/contents/about.
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Associated Data
Data Availability Statement
These data were derived from the following resources available in the public domain: GBD Results 2021, https://vizhub.healthdata.org/gbd-results/; Alcohol and other drug treatment services in Australia, https://www.aihw.gov.au/reports/alcohol‐other‐drug‐treatment‐services/alcohol‐other‐drug‐treatment‐services‐australia/data; National Opioid Pharmacotherapy Statistics Annual Data, https://www.aihw.gov.au/reports/alcohol‐other‐drug‐treatment‐services/national‐opioid‐pharmacotherapy‐statistics/contents/about.