Skip to main content
Download PDF
Download ePub

Is use of opioid agonist treatment associated with broader primary healthcare use among men with recent injecting drug use histories following release from prison? A prospective cohort study

Harm Reduction Journal volume 20, Article number: 42 (2023) Cite this article

Abstract

Background

A precipitous decline in health status among people recently released from prison is common. In Victoria, Australia, opioid agonist treatment (OAT) in the community involves frequent contact with primary care, potentially facilitating broader use of primary healthcare services. Among a cohort of men who injected drugs regularly pre-imprisonment, we estimated differences in rates of primary healthcare use and medication dispensation between people who did and did not receive OAT post-release.

Methods

Data came from the Prison and Transition Health Cohort Study. Three-month post-release follow-up interviews were linked with primary care and medication dispensation records. Generalised linear models were fit with one exposure (OAT: none/partial/complete) for 13 outcomes relating to primary healthcare use, pathology testing, and medication dispensation, adjusted for other covariates. Coefficients were reported as adjusted incidence rate ratios (AIRR).

Results

Analyses included 255 participants. Compared to no OAT use, both partial and complete OAT use were associated with increased rates of standard (AIRR: 3.02, 95%CI: 1.88–4.86; AIRR: 3.66, 95%CI: 2.57–5.23), extended (AIRR: 2.56, 95%CI: 1.41–4.67; AIRR: 2.55, 95%CI: 1.60–4.07) and mental health-related (AIRR: 2.71, 95%CI: 1.42–5.20; AIRR: 2.27, 95%CI: 1.33–3.87) general practitioner (GP) consultations, total medication (AIRR: 1.88, 95%CI: 1.19–2.98; AIRR: 2.40, 95%CI: 1.71–3.37), benzodiazepine (AIRR: 4.99, 95%CI: 2.81–8.85; AIRR: 8.30, 95%CI: 5.28–13.04) and gabapentinoid (AIRR: 6.78, 95%CI: 3.34–13.77; AIRR: 4.34, 95%CI: 2.37–7.94) dispensations, respectively. Partial OAT use was also associated with increased after-hours GP consultations (AIRR: 4.61, 95%CI: 2.24–9.48) and complete OAT use? with increased pathology utilisation (e.g. haematological, chemical, microbiological or immunological tissue/sample testing; AIRR: 2.30, 95%CI: 1.52–3.48).

Conclusion

We observed higher rates of primary healthcare use and medication dispensation among people who reported partial and complete OAT use post-release. Findings suggest that access to OAT post-release may have a collateral benefit in supporting broader health service utilisation, underscoring the importance of retention in OAT after release from prison.

Background

People in prison experience poorer physical and mental health than people in the general population [1, 2]. Conditions such as cardiovascular disease, blood borne viruses, substance use disorders and mental illness are all more prevalent among people in prison than the general population [1, 3,4,5,6,7]. Difficulties with obtaining secure housing [5, 8], re-establishing social support networks [9], substance use [10,11,12] and unemployment [13,14,15] are common following community re-entry. These challenges often intersect and compound disadvantage [16, 17], contributing to declines in physical and mental health [1, 18] and increased risk of mortality [19,20,21].

Early and regular contact with primary care has the potential to support improved physical and mental health among people recently released from prison [22,23,24,25]. For people experiencing opioid dependence, one mechanism likely to promote early and regular primary healthcare contact after release from prison is use of primary healthcare-based opioid agonist treatment (OAT). In some Australian jurisdictions, programmes that include short-term subsidisation of OAT dispensing fees, to support continuity of prison-based OAT in the community, require people continuing OAT post-release to present to a primary healthcare-based general practitioner (GP) within one week of release [26]. Community prescribing guidelines then encourage at least monthly OAT reviews with their GP [27], thereby affording regular opportunities to identify and respond to other concurrent health issues.

International studies of cohorts of people receiving OAT have found that retention in OAT is associated with increased rates of primary healthcare contact [28,29,30,31], use of pathology services [30], and receipt of prescription medication [29, 30, 32, 33]. Further, receipt of buprenorphine-based OAT prescribed in primary healthcare settings has been found to be associated with higher rates of chronic disease screening than in people prescribed OAT by psychiatric specialists [34], and a global systematic review and meta-analysis found that recent use of OAT was associated with elevated odds of recent hepatitis C testing and treatment uptake [35]. However, other studies have found that compared to the general population, people receiving OAT were less likely to receive chronic disease and cancer screening and imaging, despite attending primary healthcare services at greater rates [28, 31]. Few Australian studies have explored the relationship between OAT and broader primary healthcare engagement, reporting conflicting results. A study of COVID-19 vaccine uptake among people who injected drugs found increased odds of vaccine uptake among people receiving OAT [36]. Another reported that people who accessed community OAT programmes used GP and pathology services at approximately three times the rate of the general population, but accessed other health services and procedures (e.g. therapeutic procedures) at reduced rates [37]. In contrast, others found no association between current OAT use and past-month non-OAT GP contact [38].

How accessing OAT after release from prison influences the use of primary healthcare by people released from prison is unknown. Previous Australian research examining use of primary healthcare after release from prison [e.g. 25, 39, 40]. has not considered its relationship with use of OAT. Similarly, Australian studies of use of OAT after release from prison [e.g. 41–43] have not examined primary healthcare use. In the United States, Howell et al. [44] compared individual rates of healthcare use before a period of imprisonment during which participants enrolled in a state-wide prison-based OAT programme, with rates of healthcare use after release. They found that rates of non-acute outpatient care, hepatitis C antiviral, and OAT medication dispensations were significantly greater following imprisonment and OAT enrolment than pre-imprisonment, but no differences in rates of dispensation of psychiatric, human immunodeficiency antivirals or chemotherapy medications, and reduced dispensation of non-OAT opioid and benzodiazepine medication [44]. However, this study did not explore use of OAT post-release as an exposure.

To address these knowledge gaps, we used data from a prospective cohort study of men who injected drugs regularly prior to a period of imprisonment in Victoria, Australia, to compare rates of (1) standard community primary healthcare; (2) a broader range of community primary healthcare services; and (3) medication dispensation, between those who did and did not use OAT post-release.

Methods

Setting

This research was conducted in Victoria, Australia. Victoria had a population of 6,649,200 people at 30 June 2021 [45], making it Australia’s second most populous state. Victoria’s adult imprisonment rate rose from 110 people per 100,000 adult population in 2011 to 139 people per 100,000 adult population in 2021 [46]. OAT is available in all Victorian prisons. People receiving community-based OAT when imprisoned can continue OAT during imprisonment, and others may commence OAT in prison following clinical assessment [26]. Methadone and sublingual buprenorphine-naloxone were available as OAT medicines in Victorian prisons during data collection, but methadone is the Department of Justice and Community Safety (DJCS) preferred medicine for people commencing OAT in prison due a lower potential for diversion [26].

Shortly before release from prison, people receiving OAT are referred to a private community-based pharmacist with a prescription for daily OAT dispensation for a maximum of seven days, and also to a GP based in comprehensive primary healthcare for ongoing OAT prescribing. Victoria does not operate any public OAT clinics (prescribing or dispensing) [47]. GP visits are fully subsidised under the Medicare Benefits Schedule (MBS), Australia’s universal primary healthcare financing scheme, although some GPs may charge gap fees to the consumer. Consumers are required to attend a private pharmacy for supervised daily dosing. Consumers may be approved for unsupervised (i.e. take-home) doses by their prescribing GP following clinical assessment [27]. Consumers are charged a daily OAT dispensing fee by pharmacies, typically AUD$5/day [27]. In Victoria the DJCS subsidises the first 28 days of post-release dispensing fees [26]. Victorian community-based OAT treatment guidelines recommend intensive (minimum monthly) monitoring and review of OAT for people recently released from prison [27]. Urine screening for detection of illicit drug use is not a routine part of Victorian OAT programmes, but is one of a number of strategies available to prescribers when assessing suitability for unsupervised dosing [27].

Participants and data sources

Data are from the Prison and Transition Health (PATH) Cohort Study, a prospective cohort study of 400 men recruited during a prison sentence and pending release in Victoria, Australia. Participants were recruited between September 2014 and May 2016 from one minimum-, one medium- and one maximum-security prison. PATH eligibility requirements included being sentenced (not pre-trial detention), aged 18 years or older, and self-reported at least monthly injecting drug use (IDU) in the 6 months preceding index imprisonment. Participants completed a baseline interview a median of 39 (IQR, 15–69) days prior to release. Follow-up interviews were conducted approximately three, 12 and 24 months after release from their index sentence. Detailed PATH methodology and cohort characteristics are published elsewhere [14, 48, 49].

In addition to interview participation, participants were asked if they wanted to consent to linkage of survey data to a range of health and social services databases. This analysis includes linked administrative data from the Medicare Benefits Schedule (MBS; Australia’s publicly-funded universal health financing scheme), Pharmaceutical Benefits Scheme (PBS; Australia’s publicly-funded universal medication financing scheme), National Death Index (NDI), and adult reimprisonment data from DJCS. Data linkage was conducted by the Australian Department of Human Services (MBS and PBS), DJCS (reimprisonment data), and the Australian Institute of Health and Welfare (NDI). Data custodians were supplied names (including known aliases), sex, dates of birth, last known addresses, corrections reference numbers (DJCS) and Medicare numbers, and used deterministic and probabilistic methods to link participant survey data with administrative data records [50]. Ethics approvals for PATH were obtained from the Alfred Hospital Ethics Committee (79/12) DJCS (CF/14/10169) and AIHW Ethics Committee (EO2014/1/77).

Outcomes

To understand the breadth of health services and medications used by the study population, this study had 13 outcomes: five health service utilisation outcomes, and eight prescription medication outcomes.

MBS data compile records of a federal-government subsidised health service used by a person, with use of multiple health services per person per day possible. Each type of MBS-listed health service is assigned an item code, used by medical practitioners when making claims to the Commonwealth Government for payment for services [51]. Health services outcomes were total counts of MBS-recorded health services used by participants on or between the dates of index release and three-month follow-up. Health services outcomes were grouped according to MBS item codes, and included: (1) standard GP consultations (less than 20 min), (2) extended GP consultations (at least 20 min), (3) mental health GP consultations, (4) after-hours GP consultations (between 6 pm and 8am, on public holidays, and after 12 pm on a Saturday or on a Sunday), and (5) any pathology services. Specific MBS item codes for each outcome are provided in Appendix 1.

PBS data contain dispensing records of over 900 subsidised prescription medications; with data including all Section 85-listed (dispensed via community pharmacies) medications and some Section 100 (highly specialised medications dispensed via special arrangements) medications [52, 53]. Each record represents one medication dispensation event, such that dispensation of seven day’s medication, one month’s medication, or two month’s medication in one event all represent one PBS record. PBS data do not include the condition for which the medication was dispensed, therefore, data were grouped into eight medications-type outcomes according to first-level headings of the Anatomical Therapeutic Chemical (ATC) classification system [54], which groups medications according to pharmacological action and body system impacted. Medication outcomes, which were aggregate counts of PBS recorded medications dispensed to participants, included: (6) total dispensations, (7) nervous system, (8) anti-infective, (9) alimentary and metabolic system, and (10) other (comprising of all remaining ATC body systems) medications dispensed. Additionally, given the elevated risk of drug-related mortality among people recently released from prison [20, 21, 55,56,57], dispensation of the following specific nervous system medications were also examined: (11) opioids (non-OAT), (12) benzodiazepines, and (13) gabapentinoids.

Primary exposure

The primary exposure for this study was the use of OAT after release from prison. As individual-level OAT dispensing data in Victoria were not collected in any administrative dataset during PATH observation, use of OAT was ascertained by self-report at the 3-month follow-up survey. At three-month follow-up, participants were asked: “Were you released from prison on [OAT]?”, “Have you been prescribed [OAT] since we last saw you?”, “Are you currently being prescribed [OAT]?”, and if currently on OAT at three-month interview “How long [days/weeks/months] have you been on [OAT] for?”. These answers were used to classify participants into one of three OAT use strata (none/partial/complete) as per Fig. 1 (below). Due to an insufficient number of participants prescribed sublingual buprenorphine-naloxone, analyses did not dissaggregate by OAT medicines.

Fig. 1
figure 1

PATH participant inclusion and OAT exposure classification

Full size image

Covariates

Model covariates were selected following a review of literature relating healthcare use among people who use drugs [38, 58, 59], people recently released from prison [25], and access to healthcare in rural and regional Australia [60]. Covariates derived from baseline survey data included: age (years, continuous); Aboriginal and/or Torres Strait Islander (no/yes); ever diagnosed with a mental illness (no/yes); and ever diagnosed with a chronic health condition (no/yes). Covariates derived from three-month survey included: reporting fair or poor health status (poor or fair/good or excellent); reporting current accommodation as unstable (no/yes); times moved accommodation since index release (0/1 − 2/3 +); area of residence at 3-month interview (metropolitan/regional or rural/prison); main drug injected in the preceding 30 days (heroin/methamphetamine/heroin and methamphetamine/neither heroin nor methamphetamine); having a current support worker (no/yes); and current psychiatric distress assessed via the 12-Item General Health Questionnaire (GHQ-12; integer), scored according to the C-GHQ-12 scoring method [62]. Further covariate descriptions are available in Appendix 2.

Data analysis

Among 400 PATH participants, five died prior to three-month follow-up (see Fig. 1). Among remaining participants, 277 (70%) completed a three-month follow-up interview. Of these, nine participants were excluded from analysis because DJCS linkage occurred between index release and three-month follow-up interview, resulting in incomplete reimprisonment data and preventing calculation of time in the community. Two participants who could not be linked with MBS or PBS data were also excluded. A complete case approach was used, resulting in the exclusion of a further 11 participants due to missing covariate data, resulting in a final analysis sample of 255 participants. Differences between excluded and included participants were examined for baseline sociodemographic variables using independent sample t-tests for continuous variables and chi-square tests for categorical variables.

Baseline descriptive statistics for sociodemographics were generated. Outcome data were skewed, so median and ranges are reported for each outcome. We considered the occurrence of zero outcomes in the data; we assumed that the probability of being able to access primary healthcare and prescription medication was greater than zero for all participants, such that all observed zeros were considered to occur by chance. Given these assumptions, and the over-dispersion of all outcomes, we used generalised linear models with a negative binomial distribution to estimate associations between the mean count of each outcome (that is, 13 models were estimated) and OAT use post-release, adjusted for other covariates. For interpretability we modelled the outcomes as rates, with days at risk in the community included in modelling as an exposure term (i.e. the count of each outcome during time at risk). As people are not eligible for MBS and PBS subsidies during imprisonment [65], time at risk (days) was calculated as time between release from index sentence and three-month follow-up interview, with any time spent reimprisoned deducted from this. Reimprisonment dates were determined via linkage to DJCS data; as DJCS data were unavailable beyond three-month follow-up interviews for the whole cohort to account for time in the community, all analyses examine the period between index release and three-month follow-up interview. Model estimates were reported as crude and adjusted incidence rate ratios (IRR and AIRR) with 95% confidence intervals (95%CI). Statistical significance was set at p < 0.05. All analyses were conducted using Stata 14.1 [66].

To assess whether relationships between use of OAT and primary healthcare use were impacted by the inclusion of participants who may not have used opioids in the observation period, and were therefore not indicated for OAT, we conducted additional sensitivity analyses. Each of the 13 models described above were refit with a restricted sample including only participants who reported at the 3-month follow-up survey any use of heroin or pharmaceutical opioids (e.g. methadone, buprenorphine, oxycodone; inclusive of prescribed and illicit/diverted) since last interview.

Results

Participant characteristics

The mean age of participants (N = 255) was 36 years (standard deviation: 8 years, see Table 1) and 15% identified as Aboriginal and/or Torres Strait Islander peoples. Most (91%) were born in Australia, 13% reported being employed prior to index imprisonment, and 20% had completed secondary school. Most (84%) reported ever having been diagnosed with a mental illness and 64% reported ever having been diagnosed with a chronic health condition. At three-month follow-up, 50% of participants were residing in a metropolitan area, and most reported their main drug injected in the past 30 days as methamphetamine (28%), heroin (12%) or a combination of the two (21%). Over half (58%) of participants reported no use of OAT since index release, 13% reported partial OAT use, and 29% reported complete OAT use. No statistically significant differences in baseline characteristics were found between participants included and excluded (n = 143) from analysis (see Appendix 3).

Table 1 Participant characteristics at baseline and three-month follow-up interview (N = 255)
Full size table

Primary healthcare utilisation and OAT

Aggregate counts, summary statistics, and crude and adjusted IRR for each health service outcome (outcomes 1–5) stratified by post-release OAT use are shown in Table 2, with extended summary statistics available in Appendix 4. A total of 1113 GP consultations was observed, with 201 participants accessing at least one consultation. Standard GP consultations (n = 697, 63%) were the most commonly accessed, followed by extended GP consultations (n = 194, 17%).

Table 2 Item totals, median and range, for each level of opioid agonist treatment (OAT) use (None: n = 148, Partial: n = 32, Complete: n = 75), unadjusted (IRR) and adjusted incidence rate ratios (AIRR) comparing use of primary healthcare services across different levels of post-release OAT use
Full size table

In each multivariable analysis, complete retention in OAT, compared to no OAT, was associated with an increased rate of standard GP consultations (outcome 1), extended GP consultations (outcome 2), and mental health GP consultations (outcome 3) and pathology services (outcome 5). Partial OAT, compared to no OAT, was associated with an increased rate of standard GP consultations (outcome 1), extended GP consultations (outcome 2), mental health GP consultations (outcome 3) and after-hours GP consultations (see Table 2).

Complete adjusted models for each healthcare utilisation outcome are available as (Appendix 5).

Medication dispensation and OAT

Aggregate counts, summary statistics, and crude and adjusted IRR for each prescription medication outcome (outcomes 6–13) stratified by post-release OAT use are shown in Table 3. A total of 1188 dispensations occurred during observation, with 159 participants being dispensed at least one medication. Nervous system medications accounted for 75% (n = 894) of dispensations. Benzodiazepines accounted for 39% (n = 353) of nervous system medication dispensations; of these, diazepam (n = 224, 63%) and oxazepam (n = 78, 22%) were the most common benzodiazepines dispensed.

Table 3 Item totals, median and range, median and range for each level of opioid agonist treatment (OAT) use (None: n = 148, Partial: n = 32, Complete: n = 75), unadjusted (IRR) and adjusted incidence rate ratios (AIRR) comparing primary healthcare-based medication dispensation across different levels of post-release OAT use
Full size table

In each multivariable analysis, complete retention in OAT was associated with increased rates of total medication, nervous system, benzodiazepine, and gabapentinoid dispensations (see Table 3). Partial OAT was also associated with an increased rate of total medication, nervous system, benzodiazepine, and gabapentinoid dispensations.

Complete adjusted models for each prescription medication outcome are available as (Appendix 6).

A total of 195 (76% of 255) participants reported at least one episode of opioid use between baseline and three-month follow-up interviews, and were included in sensitivity analyses. Associations between use of OAT and primary healthcare among participants reporting opioid use were consistent with those observed in the primary analysis (see Table 4).

Table 4 Sensitivity analysis of item totals, median and range, median and range for each level of OAT use (None: n = 88, Partial: n = 32, Complete: n = 75), unadjusted (IRR) and adjusted incidence rate ratios (AIRR) comparing primary healthcare-based medication dispensation across different levels of post-release OAT use among participants who reported any opioid use since baseline interview (N = 195)
Full size table

Discussion

Among a cohort of men recently released from prison who reported regular IDU prior to imprisonment, we found that use of OAT in the post-release observation period was associated with increased use of standard and extended GP consultations in primary healthcare settings compared to those reporting no OAT use, consistent with existing literature [28,29,30, 44]. These elevated rates of primary healthcare attendance among people using OAT provide opportunities to address concurrent health priorities and support improved health outcomes among people recently released from prison. We also observed increased use of mental health GP consultations among people reporting partial or complete post-release OAT use, although the proportion of participants accessing these services during follow-up (32%) was low given the very high prevalence of mental health problems in the cohort. While previous studies have found elevated use of pathology services among people using OAT [30, 37], this was only observed among people reporting complete OAT use in this study. We also found increased use of after-hours GP services among people reporting partial OAT use, but not complete OAT.

While overall rates of total medication dispensation were higher among both partial and complete OAT groups than in the no OAT group, only medication dispensations for the nervous system were elevated when dispensations were analysed according to ATC group. We also observed increased rates of benzodiazepine and gabapentinoid prescription among people who accessed OAT, compared to people who did not. These findings were unexpected, given prior evidence of reduced benzodiazepine prescription among people using OAT [44, 67] and Victorian community-based OAT prescribing guidelines repeatedly cautioning against concurrent prescription of central nervous system depressants due to the risk of multiple drug toxicity and drug-related mortality [27].

Implications

Studies have demonstrated the importance of integrated health and substance use treatment services in meeting the health needs of people who inject drugs [68, 69]. In our study, most GP consultations in the first three months after release from prison were standard consultations of less than 20 min duration. While MBS data do not include details of healthcare provided during GP consultations, short consultation durations may result in GPs prioritising initiation of OAT and/or stabilisation of OAT dose, potentiating other health issues being un- or under-treated. Diagnostic overshadowing is a well-recognised concern for people with complex health needs, after release from prison [70]. Routine use of extended consultations for people recently released from prison using OAT could support holistic individual health plans which concurrently address other health issues, including mental health, blood borne virus and chronic disease screening and treatment. However, the use of extended consultations may require increased OAT prescribing capacity. At June 2020, approximately eleven per cent of Victoria’s GPs were accredited to prescribe OAT [47, 71]. Currently in Victoria, GPs are required to undertake specialist training to prescribe methadone-OAT or buprenorphine-OAT to six or more patients, consisting of a short online module and a day-long module [72]. OAT accreditation requirements pose a barrier to recruiting new OAT prescribers and may cultivate a perception that OAT prescription is difficult [73]. The abolition of training requirements for buprenorphine-OAT, which carries a reduced risk of overdose [74], and the integration of methadone-OAT training into standard GP training and ongoing professional development, may increase the number of GPs prescribing OAT [73].

Our results add to the evidence supporting the health benefits of retention in OAT after release from prison. However, long-term retention in OAT after release from prison is rare [41, 43, 75,76,77,78]; indicating the need for reforms to OAT provision. Financial barriers such as dispensing fees [79,80,81] and indirect costs including transport [80] reduce OAT retention. Subsidising OAT in line with other PBS-listed prescription medications in Australia would improve health equity and affordability [80, 82], while increased access to unsupervised doses [80] may reduce indirect costs. Alternative OAT medications such as injectable diamorphine [83,84,85] are safe, effective and may support retention among people not retained in methadone- or buprenorphine-OAT. Routine clinical assessment supported by machine learning tools may support early identification of people at risk of premature OAT discontinuation, enabling early intervention [86], and online tools may also support retention [87,88,89]. Use of such programmes to support improved retention should be explored.

Improvements to the prison-to-community OAT referral process may provide additional opportunities to improve health among people receiving OAT after release from prison. In Victoria, prison discharge summaries, which are also used to support prison-to-community OAT referrals, contain fields for listing other concurrent physical and mental health issues which could be used to help GPs target care and assist in informing additional health screens. A randomised trial in Queensland, Australia, showed that active referral and provision of health summaries during the transition from prison to community increased primary care and mental healthcare contacts for at least 6 months post-release [39]. Currently, completion rates of non-OAT health information in OAT referrals in Victoria are unknown. However, research from New South Wales, Australia, found that women on OAT were no more likely to have prison health information transferred to community-based healthcare than women who were not using OAT [90].

Australian [e.g. 42, 55, 91] and international research [20, 21] has consistently shown an elevated risk of drug overdose among people recently released from prison. Both benzodiazepines [92, 93] and gabapentinoids [94, 95] are associated with an increased risk of drug-related morbidity and mortality. Although the majority of benzodiazepines dispensed to our cohort were lower potency medications, concurrent prescription of central nervous system depressants such as these may increase the risk of overdose among people using OAT post-release. This risk may be most pronounced among people who initiate or discontinue OAT in the immediate post-release period, as the weeks pre- and post-OAT are also associated with an elevated risk of opioid-related mortality [42, 96]. While previous research has found that retention in OAT after release from prison reduces the risk of opioid-related mortality [42, 97], it is unclear whether the high rates of benzodiazepine and gabapentinoid use may erode this protective effect. Future research should examine the reasons for benzodiazepine and gabapentinoid prescription during community re-entry, including whether they are prescribed and dispensed by the same healthcare providers, and any subsequent impact on the risk of drug overdose.

Limitations and strengths

Several limitations should be considered when interpreting these findings. First, as the sample included only men who were regularly injecting drugs prior to imprisonment, these results cannot be generalised to other groups such as women, young people, people released from pre-trial detention, or people who do not inject drugs. In particular, for women in prison, the increased burden of many physical health, mental health and substance-related conditions [1, 3, 4], reproductive health needs [1] and differing patterns of healthcare access compared to men [5] may impact associations between OAT use post-release and primary healthcare utilisation. Replication of our findings in other settings will be required. Second, the sample size limited the precision of model estimates, especially for less frequent outcomes. Third, 123 participants who did not complete a 3-month follow-up interview were excluded from analysis. No differences were observed between participants included and excluded; however we cannot exclude the potential of attrition bias influencing our findings. Fourth, the absence of administrative OAT data may have introduced measurement and recall bias. Fifth, the PATH study design prevented determination of opioid dependence. As such, the ‘none’ OAT exposure group likely includes people who were not experiencing opioid dependence, either because they had ceased or reduced use, or were primarily using drugs other than opioids, and therefore unsuitable for OAT. However, the results of sensitivity analyses which excluded people who did not report any opioid use since baseline interview were consistent with primary results. Additionally, the absence of administrative OAT data also prevented temporal analysis of OAT exposure relative to health services use for participants reporting partial OAT use, which may have offered additional insight into patterns of health service use. Sixth, these findings represent associations between use of OAT and primary healthcare in the immediate post-release period. Future research should examine whether and how these associations change over time. Seventh, MBS data do not contain details of health matters discussed or treatments provided within consultations, preventing more detailed analysis. Eighth, given the absence of daily prescribed dose and medication indication from PBS data, estimation of mean medication dispensation rates are a proxy for healthcare use and not medication consumption per se. We note that the mean number of total medication dispensations was 4.6 (standard deviation: 7.8; see Appendix 3) over an average of 3.7 months of observation per person. Therefore, it is reasonable to use these data as a proxy for healthcare use. Finally, this analysis focused primarily on personal factors associated with health service utilisation. Despite these limitations, a key strength of this analysis was the linkage of self-report and administrative data. Administrative data provided unbiased data on frequency of primary healthcare use and medication dispensation, while self-report data allowed inclusion of covariates relating to housing stability and injecting drug use which are typically unavailable to analyses using only administrative data.

Conclusion

People recently released from prison commonly experience significant declines in their physical and mental health. We observed higher rates of standard GP consultation in primary healthcare, and some evidence of broader primary healthcare use, including mental health consultations, among men with histories of IDU using OAT after release from prison. Retention in post-release OAT provides clear opportunities to address the concurrent health needs of people recently released from prison. Increased use of extended GP consultations among people recently released from prison who use OAT, and initiatives which support retention in OAT post-release, has the potential to support improved physical and mental health outcomes.

Availability of data and materials

The datasets analysed during this study are not publically available due to restrictions regarding the sharing of data for people involved with the criminal justice system in Victoria, Australia, but may be available upon request subject relevant ethics approvals.

References

  1. Fazel S, Baillargeon J. The health of prisoners. Lancet. 2011;377(9769):956–65.

    Article  PubMed  Google Scholar 

  2. Kinner SA, Young JT. Understanding and improving the health of people who experience incarceration: an overview and synthesis. Epidemiol Rev. 2018;40(1):4–11.

    Article  PubMed  PubMed Central  Google Scholar 

  3. Fazel S, Yoon IA, Hayes AJ. Substance use disorders in prisoners: an updated systematic review and meta-regression analysis in recently incarcerated men and women. Addiction. 2017;112(10):1725–39.

    Article  PubMed  PubMed Central  Google Scholar 

  4. Fazel S, et al. Mental health of prisoners: prevalence, adverse outcomes, and interventions. Lancet Psychiatry. 2016;3(9):871–81.

    Article  PubMed  PubMed Central  Google Scholar 

  5. Australian Institute of Health and Welfare, The health of Australia's prisoners 2018. 2019, Australian Institute of Health and Welfare: Canberra.

  6. Larney S, et al. Incidence and prevalence of hepatitis C in prisons and other closed settings: results of a systematic review and meta-analysis. Hepatology. 2013;58(4):1215–24.

    Article  PubMed  Google Scholar 

  7. Dolan K, et al. People who inject drugs in prison: HIV prevalence, transmission and prevention. Int J Drug Policy. 2015;26(Suppl 1):S12–5.

    Article  PubMed  Google Scholar 

  8. Baldry E, et al. Ex-prisoners, homelessness and the state in Australia. Aust N Z J Criminol. 2016;39(1):20–33.

    Article  Google Scholar 

  9. Wallace D, et al. Examining the role of familial support during prison and after release on post-incarceration mental health. Int J Offender Ther Comp Criminol. 2016;60(1):3–20.

    Article  PubMed  Google Scholar 

  10. Winter RJ, et al. Resumption of injecting drug use following release from prison in Australia. Drug Alcohol Depend. 2016;168:104–11.

    Article  CAS  PubMed  Google Scholar 

  11. Chamberlain A, et al. Illicit substance use after release from prison among formerly incarcerated primary care patients: a cross-sectional study. Addict Sci Clin Pract. 2019;14(1):7.

    Article  PubMed  PubMed Central  Google Scholar 

  12. Curtis M, et al. High rates of resumption of injecting drug use following release from prison among men who injected drugs before imprisonment. Addiction. 2022;117(11):2887–98.

    Article  PubMed  PubMed Central  Google Scholar 

  13. Western B, et al. Stress and hardship after prison. Am J Sociol. 2015;120(5):1512–47.

    Article  Google Scholar 

  14. Stewart AC, et al. The prison and transition health (PATH) cohort study: prevalence of health, social, and crime characteristics after release from prison for men reporting a history of injecting drug use in Victoria Australia. Drug Alcohol Depend. 2021;227: 108970.

    Article  PubMed  Google Scholar 

  15. Visher CA, Debus-Sherrill SA, Yahner J. Employment after prison: a longitudinal study of former prisoners. Justice Q. 2010;28(5):698–718.

    Article  Google Scholar 

  16. Schroeder SE, et al. “It’s a revolving door”: ego-depletion among prisoners with injecting drug use histories as a barrier to post-release success. Int J Drug Policy. 2022;101:103571.

    Article  PubMed  Google Scholar 

  17. Denton M, Foster M, Bland R. How the prison-to-community transition risk environment influences the experience of men with co-occurring mental health and substance use disorder. Aust N Z J Criminol. 2016;50(1):39–55.

    Article  Google Scholar 

  18. Brinkley-Rubinstein L. Incarceration as a catalyst for worsening health. Health Justice. 2013;1(1):3.

    Article  PubMed Central  Google Scholar 

  19. Spittal MJ, et al. Suicide in adults released from prison in Queensland, Australia: a cohort study. J Epidemiol Community Health. 2014;68(10):993–8.

    Article  PubMed  Google Scholar 

  20. Merrall EL, et al. Meta-analysis of drug-related deaths soon after release from prison. Addiction. 2010;105(9):1545–54.

    Article  PubMed  PubMed Central  Google Scholar 

  21. Bukten A, et al. High risk of overdose death following release from prison: variations in mortality during a 15-year observation period. Addiction. 2017;112(8):1432–9.

    Article  PubMed  Google Scholar 

  22. Kinner SA, Young JT, Carroll M. The pivotal role of primary care in meeting the health needs of people recently released from prison. Australas Psychiatry. 2015;23(6):650–3.

    Article  PubMed  Google Scholar 

  23. de Andrade DF, et al. Emergency health service contact and reincarceration after release from prison: a prospective cohort study. Crim Behav Ment Health. 2019;29(2):85–93.

    Article  PubMed  Google Scholar 

  24. Carroll M, et al. High rates of general practice attendance by former prisoners: a prospective cohort study. Med J Aust. 2017;207(2):75–80.

    Article  PubMed  Google Scholar 

  25. Young JT, et al. Early primary care physician contact and health service utilisation in a large sample of recently released ex-prisoners in Australia: prospective cohort study. BMJ Open. 2015;5(6):e008021.

    Article  PubMed  PubMed Central  Google Scholar 

  26. Justice Health, Victorian Prison Opioid Substitution Therapy Program Guidelines Department of Justice & Regulation, Editor. 2015, Victorian Government: Melbourne.

  27. Department of Health and Human Services, Policy for maintenance pharmacotherapy for opioid dependence, D.o.H.a.H. Services, Editor. 2016, Victorian Government: Melbourne.

  28. Mohlman MK, et al. Impact of medication-assisted treatment for opioid addiction on medicaid expenditures and health services utilization rates in vermont. J Subst Abuse Treat. 2016;67:9–14.

    Article  PubMed  Google Scholar 

  29. Ronquest NA, et al. Relationship between buprenorphine adherence and relapse, health care utilization and costs in privately and publicly insured patients with opioid use disorder. Subst Abuse Rehabil. 2018;9:59–78.

    Article  PubMed  PubMed Central  Google Scholar 

  30. Shah A, et al. Healthcare utilization and costs associated with treatment for opioid dependence. J Med Econ. 2018;21(4):406–15.

    Article  PubMed  Google Scholar 

  31. Spithoff S, et al. Quality of primary care among individuals receiving treatment for opioid use disorder. Can Fam Physician. 2019;65(5):343–51.

    PubMed  PubMed Central  Google Scholar 

  32. Tkacz J, et al. Relationship between buprenorphine adherence and health service utilization and costs among opioid dependent patients. J Subst Abuse Treat. 2014;46(4):456–62.

    Article  PubMed  Google Scholar 

  33. Baser O, et al. Cost and utilization outcomes of opioid-dependence treatments. Am J Manag Care. 2011;17(Suppl 8):S235–48.

    PubMed  Google Scholar 

  34. Haddad MS, Zelenev A, Altice FL. Buprenorphine maintenance treatment retention improves nationally recommended preventive primary care screenings when integrated into urban federally qualified health centers. J Urban Health. 2015;92(1):193–213.

    Article  PubMed  Google Scholar 

  35. Grebely J, et al. Association between opioid agonist therapy and testing, treatment uptake, and treatment outcomes for hepatitis C infection among people who inject drugs: a systematic review and meta-analysis. Clin Infect Dis. 2021;73(1):e107–18.

    Article  PubMed  Google Scholar 

  36. Iversen J, et al. Uptake of COVID-19 vaccination among people who inject drugs. Harm Reduct J. 2022;19(1):59.

    Article  PubMed  PubMed Central  Google Scholar 

  37. Ward P, Mattick R. Health care utilisation and costs under the Commonwealth Medicare Benefit Scheme by methadone maintenance patients in NSW. In: NDARC Technical Report No. 240. 2005. Sydney: National Drug and Alcohol Research Centre

  38. Nambiar D, Stoove M, Dietze P. A cross-sectional study describing factors associated with utilisation of GP services by a cohort of people who inject drugs. BMC Health Serv Res. 2014;14:308.

    Article  PubMed  PubMed Central  Google Scholar 

  39. Kinner SA, et al. Low-intensity case management increases contact with primary care in recently released prisoners: a single-blinded, multisite, randomised controlled trial. J Epidemiol Community Health. 2016;70(7):683–8.

    Article  PubMed  Google Scholar 

  40. Young JT, et al. Contact with mental health services after acute care for self-harm among adults released from prison: a prospective data linkage study. Suicide Life Threat Behav. 2020;50(5):990–1006.

    Article  PubMed  Google Scholar 

  41. Dolan KA, et al. Four-year follow-up of imprisoned male heroin users and methadone treatment: mortality, re-incarceration and hepatitis C infection. Addiction. 2005;100(6):820–8.

    Article  PubMed  Google Scholar 

  42. Degenhardt L, et al. The impact of opioid substitution therapy on mortality post-release from prison: retrospective data linkage study. Addiction. 2014;109(8):1306–17.

    Article  PubMed  Google Scholar 

  43. Larney S, et al. Effect of prison-based opioid substitution treatment and post-release retention in treatment on risk of re-incarceration. Addiction. 2012;107(2):372–80.

    Article  PubMed  Google Scholar 

  44. Howell BA, et al. Changes in health services use after receipt of medications for opioid use disorder in a statewide correctional system. Health Aff. 2021;40(8):1304–11.

    Article  Google Scholar 

  45. Australian Bureau of Statistics. National, state and territory population. 2021; Available from: https://www.abs.gov.au/statistics/people/population/national-state-and-territory-population/latest-release.

  46. Australian Bureau of Statistics, Prisoner numbers and prisoner rates by Indigenous Status and sex, States and territories, 2006–2021 (Tables 40 to 42). 2021. Canberra: Australian Bureau of Statistics

  47. Australian Institute of Health and Welfare, National Opioid Pharmacotherapy Statistics Annual Data Collection. 2022. Canberra: AIHW.

  48. Kirwan A, et al. The prison and transition health (PATH) cohort study: study protocol and baseline characteristics of a cohort of men with a history of injecting drug use leaving prison in Australia. J Urban Health. 2019;96(3):400–10.

    Article  PubMed  PubMed Central  Google Scholar 

  49. Stewart AC, et al. Strategies to maximise study retention and limit attrition bias in a prospective cohort study of men reporting a history of injecting drug use released from prison: the prison and transition health study. BMC Med Res Methodol. 2021;21(1):185.

    Article  PubMed  PubMed Central  Google Scholar 

  50. Tibble H, et al. The importance of including aliases in data linkage with vulnerable populations. BMC Med Res Methodol. 2018;18(1):76.

    Article  PubMed  PubMed Central  Google Scholar 

  51. Department of Health, Medicare Benefits Schedule Book. 2021. Canberra: Commonwealth of Australia

  52. Mellish L, et al. The Australian pharmaceutical benefits scheme data collection: a practical guide for researchers. BMC Res Notes. 2015;8(1):634.

    Article  PubMed  PubMed Central  Google Scholar 

  53. Department of Health, PBS Expenditure and prescriptions report 1 July 2020 to 30 June 2021. 2021. Canberra: Department of Health

  54. World Health Organization. Anatomical Therapeutic Chemical (ATC) Classification. 2021; Available from: https://www.who.int/tools/atc-ddd-toolkit/atc-classification.

  55. Forsyth SJ, et al. Incidence and risk factors for mortality after release from prison in Australia: a prospective cohort study. Addiction. 2018;113(5):937–45.

    Article  PubMed  Google Scholar 

  56. Gan WQ, et al. Risk of overdose-related death for people with a history of incarceration. Addiction. 2021;116(6):1460–71.

    Article  PubMed  Google Scholar 

  57. Groot E, et al. Drug toxicity deaths after release from incarceration in Ontario, 2006–2013: review of coroner’s cases. PLoS ONE. 2016;11(7):e0157512.

    Article  PubMed  PubMed Central  Google Scholar 

  58. Lewer D, et al. Frequency of health-care utilization by adults who use illicit drugs: a systematic review and meta-analysis. Addiction. 2020;115(6):1011–23.

    Article  PubMed  PubMed Central  Google Scholar 

  59. Darke S, et al. Health service utilization among heroin users. Addict Disord Treat. 2015;14(3):159–66.

    Article  Google Scholar 

  60. McGrail MR, Humphreys JS. Spatial access disparities to primary health care in rural and remote Australia. Geospat Health. 2015;10(2):358.

    Article  PubMed  Google Scholar 

  61. Australian Bureau of Statistics. ASGS Coding Indexes (2016). 2016; Available from: https://data.gov.au/data/dataset/asgs-coding-indexes-2016/resource/c6051960-6012-452c-ac68-dba55a1f837a.

  62. Donath S. The validity of the 12-item general health questionnaire in Australia: a comparison between three scoring methods. Aust N Z J Psychiatry. 2001;35(2):231–5.

    Article  CAS  PubMed  Google Scholar 

  63. Goldberg D. General health questionnaire (GHQ-12). 1992; Nfer-Nelson: Windsor

  64. Goldberg DP, et al. The validity of two versions of the GHQ in the WHO study of mental illness in general health care. Psychol Med. 1997;27(1):191–7.

    Article  CAS  PubMed  Google Scholar 

  65. Plueckhahn TM, et al. Are some more equal than others? Challenging the basis for prisoners’ exclusion from Medicare. Med J Aust. 2015;203(9):359–61.

    Article  PubMed  Google Scholar 

  66. StataCorp, Stata Statistical Software: Release 14. 2015. College Station: StataCorp LP

  67. Rieckmann TR, et al. Treating opioid dependence with buprenorphine in the safety net: critical learning from clinical data. J Behav Health Serv Res. 2017;44(3):351–63.

    Article  PubMed  Google Scholar 

  68. Islam MM, et al. The accessibility, acceptability, health impact and cost implications of primary healthcare outlets that target injecting drug users: a narrative synthesis of literature. Int J Drug Policy. 2012;23(2):94–102.

    Article  PubMed  Google Scholar 

  69. Socias ME, et al. Integrated models of care for people who inject drugs and live with hepatitis C virus: a systematic review. Int J Drug Policy. 2019;72:146–59.

    Article  PubMed  Google Scholar 

  70. Calais-Ferreira L, et al. Multimorbidity and quality of primary care after release from prison: a prospective data-linkage cohort study. BMC Health Serv Res. 2022;22(1):876.

    Article  PubMed  PubMed Central  Google Scholar 

  71. Medical Board of Australia, Registration Data Table—June 2021. 2021. Melbourne: Medical Board of Australia

  72. Department of Health, Pharmacotherapy training. 2015. Melbourne: Victoria State Government

  73. Prathivadi P, Sturgiss EA. When will opioid agonist therapy become a normal part of comprehensive health care? Med J Aust. 2021;214(11):504–5.

    Article  PubMed  Google Scholar 

  74. Whelan PJ, Remski K. Buprenorphine vs methadone treatment: a review of evidence in both developed and developing worlds. J Neurosci Rural Pract. 2012;3(1):45–50.

    Article  PubMed  PubMed Central  Google Scholar 

  75. Mattick RP, et al. Methadone maintenance therapy versus no opioid replacement therapy for opioid dependence. Cochrane Database Syst Rev. 2009;2009(3):CD002209.

    PubMed  PubMed Central  Google Scholar 

  76. Kinlock TW, et al. A randomized clinical trial of methadone maintenance for prisoners: results at 12 months postrelease. J Subst Abuse Treat. 2009;37(3):277–85.

    Article  PubMed  PubMed Central  Google Scholar 

  77. Brinkley-Rubinstein L, et al. A randomized, open label trial of methadone continuation versus forced withdrawal in a combined US prison and jail: findings at 12 months post-release. Drug Alcohol Depend. 2018;184:57–63.

    Article  CAS  PubMed  Google Scholar 

  78. Curtis M, et al. Discontinuation of opioid agonist treatment following release from prison in a cohort of men who injected drugs prior to imprisonment in Victoria, Australia: a discrete-time survival analysis. Drug Alcohol Depend. 2023;242:109730.

    Article  CAS  PubMed  Google Scholar 

  79. Shepherd A, Perrella B, Hattingh HL. The impact of dispensing fees on compliance with opioid substitution therapy: a mixed methods study. Subst Abuse Treat Prev Policy. 2014;9:32.

    Article  PubMed  PubMed Central  Google Scholar 

  80. Tran AD, et al. Economic analysis of out-of-pocket costs among people in opioid agonist treatment: a cross-sectional survey in three Australian jurisdictions. Int J Drug Policy. 2022;99:103472.

    Article  PubMed  Google Scholar 

  81. Zahra E, et al. Examining the cost and impact of dosing fees among clients in opioid agonist treatment: results from a cross-sectional survey of Australian treatment clients. Drug Alcohol Rev. 2022;41(4):841–50.

    Article  PubMed  PubMed Central  Google Scholar 

  82. Chalmers J, Ritter A. Subsidising patient dispensing fees: the cost of injecting equity into the opioid pharmacotherapy maintenance system. Drug Alcohol Rev. 2012;31(7):911–7.

    Article  PubMed  Google Scholar 

  83. Haasen C, et al. Heroin-assisted treatment for opioid dependence: randomised controlled trial. Br J Psychiatry. 2007;191(1):55–62.

    Article  PubMed  Google Scholar 

  84. Blanken P, et al. Heroin-assisted treatment in the Netherlands: history, findings, and international context. Eur Neuropsychopharmacol. 2010;20(Suppl 2):S105–58.

    Article  CAS  PubMed  Google Scholar 

  85. Fischer B, et al. Heroin-assisted treatment (HAT) a decade later: a brief update on science and politics. J Urban Health. 2007;84(4):552–62.

    Article  PubMed  PubMed Central  Google Scholar 

  86. Hasan MM, et al. A machine learning based two-stage clinical decision support system for predicting patients’ discontinuation from opioid use disorder treatment: retrospective observational study. BMC Med Inform Decis Mak. 2021;21(1):331.

    Article  PubMed  PubMed Central  Google Scholar 

  87. Schuman-Olivier Z, et al. MySafeRx: a mobile technology platform integrating motivational coaching, adherence monitoring, and electronic pill dispensing for enhancing buprenorphine/naloxone adherence during opioid use disorder treatment: a pilot study. Addict Sci Clin Pract. 2018;13(1):21.

    Article  PubMed  PubMed Central  Google Scholar 

  88. Maricich YA, et al. Safety and efficacy of a prescription digital therapeutic as an adjunct to buprenorphine for treatment of opioid use disorder. Curr Med Res Opin. 2021;37(2):167–73.

    Article  CAS  PubMed  Google Scholar 

  89. Christensen DR, et al. Adding an Internet-delivered treatment to an efficacious treatment package for opioid dependence. J Consult Clin Psychol. 2014;82(6):964–72.

    Article  PubMed  PubMed Central  Google Scholar 

  90. Abbott P, et al. Supporting continuity of care between prison and the community for women in prison: a medical record review. Aust Health Rev. 2017;41(3):268–76.

    Article  PubMed  Google Scholar 

  91. Curtis M, et al. Non-fatal opioid overdose after release from prison among men who injected drugs prior to their imprisonment: a prospective data linkage study. Med J Aust. 2022;218:94.

    Article  PubMed  Google Scholar 

  92. Votaw VR, et al. The epidemiology of benzodiazepine misuse: a systematic review. Drug Alcohol Depend. 2019;200:95–114.

    Article  PubMed  PubMed Central  Google Scholar 

  93. Keen C, et al. Periods of altered risk for non-fatal drug overdose: a self-controlled case series. Lancet Public Health. 2021;6(4):e249–59.

    Article  PubMed  Google Scholar 

  94. Evoy KE, et al. Abuse and misuse of pregabalin and gabapentin: a systematic review update. Drugs. 2021;81(1):125–56.

    Article  CAS  PubMed  Google Scholar 

  95. Gomes T, et al. Gabapentin, opioids, and the risk of opioid-related death: a population-based nested case-control study. PLoS Med. 2017;14(10):e1002396.

    Article  PubMed  PubMed Central  Google Scholar 

  96. Santo T Jr, et al. Association of opioid agonist treatment with all-cause mortality and specific causes of death among people with opioid dependence: a systematic review and meta-analysis. JAMA Psychiat. 2021;78(9):979–93.

    Article  Google Scholar 

  97. Bird SM, et al. Impact of opioid substitution therapy for Scotland’s prisoners on drug-related deaths soon after prisoner release. Addiction. 2015;110(10):1617–24.

    Article  PubMed  PubMed Central  Google Scholar 

Download references

Acknowledgements

We would like to acknowledge the participants involved in the Prison and Transition Health study for the time and knowledge they contributed to this study. Thanks to the Burnet Institute fieldwork team for their tireless efforts with data collection. We would also like to acknowledge the Victorian Department of Justice and Community Safety, the Australian Institute of Health and Welfare and the Centre for Victorian Data Linkage for the support they have provided.

Funding

The Prison and Transition Health Cohort Study was funded by a NHMRC Project Grant (APP1029915). MC is the recipient of a NHMRC post-graduate award (APP1168954) and a Monash Addiction Research Centre PhD top-up scholarship. PD and MS are the recipients of NHMRC Senior Research Fellowships. We gratefully acknowledge the support provided to the Burnet Institute by the Victorian Government Operational Infrastructure Support Program.

Author information

Authors and Affiliations

  1. Disease Elimination Program, Public Health Discipline, Burnet Institute, 85 Commercial Road, Melbourne, VIC, 3004, Australia

    Michael Curtis, Anna L. Wilkinson, Paul Dietze, Ashleigh C. Stewart, Rebecca J. Winter, Campbell Aitken, Shelley J. Walker, Reece D. Cossar & Mark Stoové

  2. School of Public Health and Preventive Medicine, Monash University, Melbourne, VIC, Australia

    Michael Curtis, Anna L. Wilkinson, Paul Dietze, Ashleigh C. Stewart, Rebecca J. Winter, Campbell Aitken & Mark Stoové

  3. Monash Addition Research Centre, Monash University, Melbourne, VIC, Australia

    Michael Curtis

  4. National Drug Research Institute, Curtin University, Melbourne, Australia

    Paul Dietze & Shelley J. Walker

  5. School of Population Health, Curtin University, Perth, WA, Australia

    Stuart A. Kinner

  6. Justice Health Unit, Melbourne School of Population and Global Health, University of Melbourne, Melbourne, VIC, Australia

    Stuart A. Kinner

  7. Centre for Adolescent Health, Murdoch Children’s Research Institute, Melbourne, VIC, Australia

    Stuart A. Kinner

  8. Griffith Criminology Institute, Griffith University, Brisbane, QLD, Australia

    Stuart A. Kinner

  9. Department of Gastroenterology, St Vincent’s Hospital, Melbourne, VIC, Australia

    Rebecca J. Winter

  10. School of Population Health, University of New South Wales, Sydney, NSW, Australia

    Tony Butler

  11. School of Psychology and Public Health, La Trobe University, Melbourne, Australia

    Mark Stoové

Authors
  1. Michael Curtis
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Anna L. Wilkinson
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Paul Dietze
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. Ashleigh C. Stewart
    View author publications

    You can also search for this author in PubMed Google Scholar

  5. Stuart A. Kinner
    View author publications

    You can also search for this author in PubMed Google Scholar

  6. Rebecca J. Winter
    View author publications

    You can also search for this author in PubMed Google Scholar

  7. Campbell Aitken
    View author publications

    You can also search for this author in PubMed Google Scholar

  8. Shelley J. Walker
    View author publications

    You can also search for this author in PubMed Google Scholar

  9. Reece D. Cossar
    View author publications

    You can also search for this author in PubMed Google Scholar

  10. Tony Butler
    View author publications

    You can also search for this author in PubMed Google Scholar

  11. Mark Stoové
    View author publications

    You can also search for this author in PubMed Google Scholar

Contributions

MC, with assistance from AW, PD and MS, developed the framework for the paper, undertook statistical analysis and produced the initial draft. ALW, PD, ACS, SAK, RJW, CA, SJW, RDC, TB and MS provided substantial editorial comment and review. MS is the chief investigator of the Prison and Transition Health study and guided paper development and gave editorial support throughout the duration of planning and writing. All authors read and approved the final manuscript.

Corresponding author

Correspondence to Michael Curtis.

Ethics declarations

Ethics approval and consent to participate

Ethics approvals for the Prison and Transition Health Cohort Study were obtained from the Alfred Hospital Ethics Committee (79/12) DJCS (CF/14/10169) and AIHW Ethics Committee (EO2014/1/77). All study participants provided consent.

Consent for publication

All study participants provided consent.

Competing interests

PD has received investigator-driven funding from Gilead Sciences for work related to hepatitis C treatment and an untied educational grant from Indivior for work related to the introduction of buprenorphine/naloxone into Australia. He has also served as an unpaid member of an Advisory Board for an intranasal naloxone product. The remaining authors declare that they have no conflicts of interest. MS has received investigator-initiated funding from Gilead Sciences, AbbVie and Bristol Myers Squibb, and consultant fees from Gilead Sciences for activities unrelated to this work.

Additional information

Publisher's Note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Appendices

Appendix 1

(See Table

Table 5 Primary healthcare service outcomes and corresponding MBS item codes [51]
Full size table

5).

Appendix 2

(See Table

Table 6 Covariate names, type, unit of measurement and additional description notes
Full size table

6).

Appendix 3

(See Table

Table 7 Summary statistics of participant sociodemographic characteristics, stratified by analysis inclusion
Full size table

7).

Appendix 4

(See Table

Table 8 Health services utilisation and medication dispensation item totals and extended summary statistics among PATH participants (N = 255)
Full size table

8).

Appendix 5

(See Table

Table 9 Participants (N = 255), total outcome counts (between date of index release and three-month follow-up), outcome counts stratified by model covariates and results of generalised linear models for health service outcomes, reported as adjusted incidence rate ratios (AIRR)
Full size table

9).

Appendix 6

(See Table

Table 10 Participants (N = 255), total outcome counts (between date of index release and three-month follow-up), outcome counts stratified by model covariates and results of generalised linear models for each prescription medication outcome, reported as adjusted incidence rate ratios (AIRR)
Full size table

10).

Rights and permissions

Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated in a credit line to the data.

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Curtis, M., Wilkinson, A.L., Dietze, P. et al. Is use of opioid agonist treatment associated with broader primary healthcare use among men with recent injecting drug use histories following release from prison? A prospective cohort study. Harm Reduct J 20, 42 (2023). https://doi.org/10.1186/s12954-023-00773-2

Download citation

  • Received:

  • Accepted:

  • Published:

  • DOI: https://doi.org/10.1186/s12954-023-00773-2

Keywords

Harm Reduction Journal

ISSN: 1477-7517