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There are ongoing concerns regarding pharmaceutical opioid-related harms, including overdose and dependence, with an associated increase in treatment demand. People dependent on pharmaceutical opioids appear to differ in important ways from people who use heroin, yet most opioid agonist treatment research has been conducted in people who use heroin. OBJECTIVES: To assess the effects of maintenance opioid agonist pharmacotherapy for the treatment of pharmaceutical opioid dependence.We updated our searches of the following databases to January 2022: the Cochrane Drugs and Alcohol Group Specialised Register, CENTRAL, MEDLINE, four other databases, and two trial registers. We checked the reference lists of included studies for further references to relevant randomised controlled trials (RCTs).We included RCTs with adults and adolescents examining maintenance opioid agonist treatments that made the following two comparisons. 1. Full opioid agonists (methadone, morphine, oxycodone, levo-alpha-acetylmethadol (LAAM), or codeine) versus different full opioid agonists or partial opioid agonists (buprenorphine) for maintenance treatment. 2. Full or partial opioid agonist maintenance versus non-opioid agonist treatments (detoxification, opioid antagonist, or psychological treatment without opioid agonist treatment).We used standard Cochrane methods.We identified eight RCTs that met inclusion criteria (709 participants). We found four studies that compared methadone and buprenorphine maintenance treatment, and four studies that compared buprenorphine maintenance to either buprenorphine taper (in addition to psychological treatment) or a non-opioid maintenance treatment comparison. We found low-certainty evidence from three studies of a difference between methadone and buprenorphine in favour of methadone on self-reported opioid use at end of treatment (risk ratio (RR) 0.49, 95% confidence interval (CI) 0.28 to 0.86; 165 participants), and low-certainty evidence from four studies finding a difference in favour of methadone for retention in treatment (RR 1.21, 95% CI 1.02 to 1.43; 379 participants). We found low-certainty evidence from three studies showing no difference between methadone and buprenorphine on substance use measured with urine drug screens at end of treatment (RR 0.81, 95% CI 0.57 to 1.17; 206 participants), and moderate-certainty evidence from one study of no difference in days of self-reported opioid use (mean difference 1.41 days, 95% CI 3.37 lower to 0.55 days higher; 129 participants). There was low-certainty evidence from three studies of no difference between methadone and buprenorphine on adverse events (RR 1.13, 95% CI 0.66 to 1.93; 206 participants). We found low-certainty evidence from four studies favouring maintenance buprenorphine treatment over non-opioid treatments in terms of fewer opioid positive urine drug tests at end of treatment (RR 0.66, 95% CI 0.52 to 0.84; 270 participants), and very low-certainty evidence from four studies finding no difference on self-reported opioid use in the past 30 days at end of treatment (RR 0.63, 95% CI 0.39 to 1.01; 276 participants). There was low-certainty evidence from three studies of no difference in the number of days of unsanctioned opioid use (standardised mean difference (SMD) -0.19, 95% CI -0.47 to 0.09; 205 participants). There was moderate-certainty evidence from four studies favouring buprenorphine maintenance over non-opioid treatments on retention in treatment (RR 3.02, 95% CI 1.73 to 5.27; 333 participants). There was moderate-certainty evidence from three studies of no difference in adverse effects between buprenorphine maintenance and non-opioid treatments (RR 0.50, 95% CI 0.07 to 3.48; 252 participants). The main weaknesses in the quality of the data was the use of open-label study designs, and difference in follow-up rates between treatment arms.There is very low- to moderate-certainty evidence supporting the use of maintenance agonist pharmacotherapy for pharmaceutical opioid dependence. Methadone or buprenorphine did not differ on some outcomes, although on the outcomes of retention and self-reported substance use some results favoured methadone. Maintenance treatment with buprenorphine appears more effective than non-opioid treatments. Due to the overall very low- to moderate-certainty evidence and small sample sizes, there is the possibility that the further research may change these findings.

Prescription opioid use in Australia has increased over the last 3 decades. The majority of opioids are prescribed and dispensed in primary care, however, there are few studies that are specific to opioid prescribing in this setting. Evidence about the impact of key government policy strategies to optimize opioid prescribing in primary care is limited. The aim of this study is to examine the impact of recent policy changes and clinical guidelines on opioid prescribing in primary care.Longitudinal analysis of people prescribed opioid analgesics using Population Level Analysis and Reporting (POLAR) data. POLAR is a primary care dataset comprising 464 primary health care practices in Victoria, Australia. People prescribed opioid analgesics between 2015 and 2020 will be included. The impact of opioid policies and guideline recommendations will be evaluated using interrupted time series models. Group- based trajectory modelling and multivariate regression will be used to identify patterns of opioid cessation and the provision of corresponding non-opioid interventions.The study has received Monash University Human Research Ethics Committee approval (ID 24139). Permission to access, collate and use POLAR data is granted from Outcome Health as the data custodians. The results of this study will be disseminated through publication in international journals, presented at national and international scientific conferences, and disseminated to consumers, policy makers, primary care providers and primary health networks.EU PAS Register (EUPAS43218).

There are a range of models and structures that determine features of alcohol and other drug treatment. Despite some structures being long-established, less is known about how specific aspects of service delivery impact treatment-seeking for people who use alcohol and other drugs. This Australian qualitative study explored both people with lived experience of problematic alcohol and other drug use, and health care staff's experiences of service delivery.Thirty-nine semi-structured interviews with people with lived experience and staff from either alcohol and other drug specialist, or broader health-care services, explored experiences of service delivery processes and procedures. Transcripts were thematically analysed and guided by a broad interest in barriers to treatment-seeking.Within alcohol and other drug specialist services (i) time spent on wait lists; and (ii) poor implementation of assessment processes were identified barriers to treatment-seeking and engagement. Within broader health-care services (i) organisational expectations around behaviour and engagement; (ii) alcohol and other drugs viewed as separate to service role; and (iii) limited opportunities to informally engage were identified barriers to treatment-seeking.Results suggest opportunities to engage and undertake needs-based care planning are yet to be fully realised, particularly at the intake and assessment stages of alcohol and other drug service delivery; with frequent reassessment resulting in people repeatedly recounting traumatic experiences, often to different people, only to be placed back on wait lists with no support. Within broader health-care services aspects of service delivery may perpetuate stigma that places such people outside the purview of health care.

Persistent high rates of prescription opioid use and harms remain a concern in Australia, Europe and North America. Research priority setting can inform the research agenda, strategic responses and evidence-based interventions. The objective of this study was to establish research priorities related to the safe and effective use of prescription opioids in general practice.Consumers, clinicians and policy makers were invited to participate in a structured consensus workshop in May 2021. A modified nominal group technique was used to explore research priorities for the safe and effective use of opioids in Australian general practice. Research priorities were identified, consolidated and prioritised using a structured process.Seventeen consumer, medical, pharmacy, nursing, allied health and policy participants generated 26 consolidated priorities across three domains: (i) consumer-focused priorities; (ii) clinician and practice-focused priorities; and (iii) system and policy-focused priorities. The highest ranked research priorities in each of the domains were consumer characteristics that influence opioid prescribing and outcomes, opioid deprescribing strategies, and system-level barriers to prescribing alternatives to opioids, in the consumer, clinician and practice, and system and policy domains, respectively.The priorities reflect opportunities for research priority setting within Australian general practice. The priorities provide a map for future qualitative and quantitative research that will inform safe and effective opioid prescribing.

Background Medication Assisted Treatment for Opioid Dependence (MATOD) is clinically effective and cost effective, yet a lack of MATOD prescribers in the community limits access to this treatment in Australia. These shortages are often greatest in regional and rural areas. Objective(s) The Enhancing Pharmacists Involvement in Care (EPIC)-MATOD study will evaluate clinical and implementation outcomes among people with opioid dependence receiving MATOD through a collaborative pharmacist-prescriber model of care across multiple sites in a regional location (encompassing a mix of metropolitan and non-metropolitan areas) of Victoria, Australia. Methods and analysis The EPIC-MATOD study is a prospective, multisite, implementation trial of collaborative MATOD care. Pharmacists and prescribers will be recruited through the local network of opioid pharmacotherapy providers. Patients will be recruited through participating healthcare providers. After induction into the collaborative care model, patients and healthcare professionals will be followed up over 6- (patients) and 12-months (pharmacists and prescribers) in a hybrid implementation-efficacy study, with outcomes mapped to the RE-AIM framework. The primary clinical efficacy endpoint is patient retention in treatment at 26 weeks. The primary implementation outcome is treatment capacity, based on prescriber time required to provide treatment through collaborative care compared with traditional care. Secondary clinical endpoints include attendance for dosing and clinical reviews, substance use, mental and physical health and overall well-being. Implementation costs, acceptability, and provider engagement in collaborative care will be used as secondary implementation outcome indicators. Time and costs associated with collaborative care, and health service utilisation, will also be estimated. Project impact The study will provide important information on outcomes and acceptability of collaborative care for MATOD, as well as the cost and key considerations in delivering a collaborative model of care in Australia and other countries where similar treatment barriers exist.

Introduction Opioids prescribed in hospital are a key risk factor for harm in the community. This study aimed to gain an in-depth understanding of factors affecting post-operative opioid prescribing amongst clinicians using the capability, opportunity, motivation generate behaviour framework, more commonly known as COM-B. Methods Focus groups and semi-structured interviews were used to gain an in-depth understanding of factors affecting optimal practice when prescribing opioids for post-operative patients at discharge. A topic guide was written using the COM-B behaviour change model to ensure the full range of possible factors influencing prescribing behaviours were explored. Results We found barriers and facilitators of optimal opioid prescribing practice across all three domains of capability, opportunity and motivation. Capability among junior doctors could be increased in the areas of risk assessment and prescribing appropriate discharge analgesia, though education and training were not key barriers to improving practice. Findings indicated that opportunity to practice optimal prescribing was hindered by a lack of time at discharge and technology. Beliefs about one’s own and others’ responsibilities also impacted motivation to practice optimal prescribing behaviours. Pharmacists were identified as key supports for patient education and appropriate prescribing. Conclusions Educating prescribers about opioid risks and clinical practice guidelines are necessary interventions, however, our findings indicate that if implemented in isolation, they may not have the desired impact. Interventions also need to address discharge time pressures and presumptions that GPs are aware of whether opioids should be ceased or continued after surgical discharge.

Community pharmacists can play in addressing opioid-related harm. Community pharmacists are one of the most accessible health care professionals, with 90% of the US population within 3 km (2 miles) of a community pharmacy, and similarly, in regional areas of Australia, 72% of people are within 2.5 km of a pharmacy. This chapter will conduct a narrative review of the history of the delivery of harm reduction interventions in community pharmacy, and more recent innovations in pharmacy settings which can contribute to the identification and treatment of opioid use disorders. Models of delivering opioid agonist therapy within a pharmacy, strengths and challenges with pharmacy-delivered treatment, and evolving pharmacy-led and collaborative care models for the treatment of opioid use disorder (OUD) are reviewed. Additional considerations include other roles that pharmacists may play in the management of OUD, including brief screenings for prescription opioid-related problems, overdose education, naloxone provision, the delivery of injectable opioid agonist treatments, and infectious disease screening are also discussed.

Cannabinoid co-administration may enable reduced opioid doses for analgesia. This updated systematic review on the opioid-sparing effects of cannabinoids considered preclinical and clinical studies where the outcome was analgesia or opioid dose requirements. We searched Scopus, Cochrane Central Registry of Controlled Trials, Medline, and Embase (2016 onwards). Ninety-two studies met the search criteria including 15 ongoing trials. Meta-analysis of seven preclinical studies found the median effective dose (ED50) of morphine administered with delta-9-tetrahydrocannabinol was 3.5 times lower (95% CI 2.04, 6.03) than the ED50 of morphine alone. Six preclinical studies found no evidence of increased opioid abuse liability with cannabinoid administration. Of five healthy-volunteer experimental pain studies, two found increased pain, two found decreased pain and one found reduced pain bothersomeness with cannabinoid administration; three demonstrated that cannabinoid co-administration may increase opioid abuse liability. Three randomized controlled trials (RCTs) found no evidence of opioid-sparing effects of cannabinoids in acute pain. Meta-analysis of four RCTs in patients with cancer pain found no effect of cannabinoid administration on opioid dose (mean difference −3.8 mg, 95% CI −10.97, 3.37) or percentage change in pain scores (mean difference 1.84, 95% CI −2.05, 5.72); five studies found more adverse events with cannabinoids compared with placebo (risk ratio 1.13, 95% CI 1.03, 1.24). Of five controlled chronic non-cancer pain trials; one low-quality study with no control arm, and one single-dose study reported reduced pain scores with cannabinoids. Three RCTs found no treatment effect of dronabinol. Meta-analyses of observational studies found 39% reported opioid cessation (95% CI 0.15, 0.64, I2 95.5%, eight studies), and 85% reported reduction (95% CI 0.64, 0.99, I2 92.8%, seven studies). In summary, preclinical and observational studies demonstrate the potential opioid-sparing effects of cannabinoids in the context of analgesia, in contrast to higher-quality RCTs that did not provide evidence of opioid-sparing effects.

Opioid agonist treatment (OAT) clients frequently bear costs associated with their treatment, including dosing fees. This study aimed to explore the financial and social impact of dosing fees upon clients.Cross-sectional survey of people who use opioids regularly (N = 402) between December 2017 and March 2018, conducted in Australia. Dosing fees were calculated and expressed as percentage of income, by OAT type. Consequences and strategies for difficulties making payments were examined as proportions.A total of N = 360 participants had ever been in OAT and N = 245 participants currently engaged in OAT reported data on dosing fees, of them 53% (n = 129) reported paying dosing fees. Compared to clients with high levels of dosing supervision, those with moderate or low levels of supervision were more likely to pay dosing fees. The median 28-day dosing fee was AUD$110 (interquartile range AUD$80); median 28-day income was AUD$1520 (interquartile range AUD$700). For those who paid dosing fees, the fee comprised10% of total monthly income for 70% of participants; however, 23% of participants paid fees comprising 10% to 20%, and 7% of participants paid fees comprising 20% or more of monthly income. Among those that had ever been in OAT, 72% experienced difficulties in paying treatment costs; 36% left treatment earlier than intended and 25% had been excluded due to payment difficulties.Negative consequences of treatment costs to clients, particularly dosing fees, are evident. These costs impact treatment access and retention that may negatively impact clients' physical health, mental health and social wellbeing.

Illicit drug use disorders are the most stigmatised health conditions worldwide, and stigma acts as a meaningful barrier to treatment entry and treatment provision. In the context of dramatically rising opioid-related harms, it is critical that we understand the drivers of stigma and how it affects opioid use disorder treatment and policy. The aim of this narrative review is to discuss how opioid-related stigma impacts treatment provision and harm reduction, and provide potential strategies to reduce stigma at a social and structural level. We used the Framework for Integrating Normative Influences on Stigma (FINIS) to identify sources of opioid-related stigma at the macro (structural stigma), meso (public stigma) and micro (internalised stigma) levels. Reducing stigma requires strategies that target multiple levels, however addressing inequity in the laws, regulations, and rules that segregate people with opioid and other substance use disorders from mainstream society is essential.

The COVID-19 pandemic has disrupted seeking and delivery of healthcare. Different Australian jurisdictions implemented different COVID-19 restrictions. We used Australian national pharmacy dispensing data to conduct interrupted time series analyses to examine the incidence and prevalence of opioid dispensing in different jurisdictions. Following nationwide COVID-19 restrictions, the incidence dropped by -0.40 (95% confidence interval [CI]: -0.50, -0.31), -0.33 (95% CI: -0.46, -0.21) and -0.21 (95% CI: -0.37, -0.04) per 1000 people per week and the prevalence dropped by -0.85 (95% CI: -1.39, -0.31), -0.54 (95% CI: -1.01, -0.07) and -0.62 (95% CI: -0.99, -0.25) per 1000 people per week in Victoria, New South Wales and other jurisdictions, respectively. Incidence and prevalence increased by 0.29 (95% CI: 0.13, 0.44) and 0.72 (95% CI: 0.11, 1.33) per 1000 people per week, respectively in Victoria post-lockdown; no significant changes were observed in other jurisdictions. No significant changes were observed in the initiation of long-term opioid use in any jurisdictions. More stringent restrictions coincided with more pronounced reductions in overall opioid initiation, but initiation of long-term opioid use did not change.

Brief interventions (BIs) delivered in primary care can reduce harmful alcohol consumption. Yet, clinicians do not routinely offer BIs to reduce harmful alcohol use.We explored the perspectives of clinicians and patients about the use of alcohol BIs during consultations in Australian primary care.Semi-structured interviews and focus groups (face-to-face and virtual) were undertaken with 34 general practitioners, eight practice nurses and 17 patients. Field notes were made from audio-recordings and themes were identified using a descriptive qualitative approach with the field notes as the point of data analysis.Participants identified barriers within the consultation, practice setting and wider healthcare system plus across the community which reduce the delivery of BIs in primary care including: Australian drinking norms; inconsistent public health messaging around alcohol harm; primary care not recognized as a place to go for help; community stigma towards alcohol use; practice team culture towards preventive health, including systems for recording alcohol histories; limitations of clinical software and current patient resources.Multiple layers of the healthcare system influence the use of BIs in primary care. Identified facilitators for embedding BIs in primary care included: (i) raising community and clinician awareness of the health harms of alcohol, (ii) reinforcing a primary care culture that promotes prevention and, (iii) supportive resources to facilitate discussion about alcohol use and strategies to reduce intake. Alcohol BIs in primary care could be further supported by community public health messages about alcohol use.Alcohol is a major source of harm in the community and primary care (including family doctor and general practice settings) can play a role in reducing harmful alcohol use. When clinicians talk to their patients about alcohol use, research has shown they can reduce how much they drink each week. We spoke with general practitioners, nurses and patients in Australia to work out what is getting in the way of conversations about alcohol in primary care. We found that both clinicians and patients think we need to raise community awareness about the health harms of alcohol, that there are health system barriers, and there could be better resources to use in consultations. Low-income patients are particularly disadvantaged by financial costs associated with alcohol and counselling services when they seek help. To increase conversations about alcohol in primary care, it could be more helpful to target the broader community, the health system and primary care.

Prescription drug monitoring programs (PDMP) are databases which collect prescribing and dispensing information for high-risk medicines, and are one approach to mitigate prescription opioid-related risks.To examine correlates of PDMP use under voluntary and mandatory conditions, among a representative sample of community pharmacists in Victoria, Australia.An online anonymous survey was conducted and collected data in relation to pharmacist and pharmacy characteristics, comfort in performing certain tasks, PDMP training and the frequency of PDMP use under voluntary and mandatory conditions. Multivariate logistic regression models were performed to determine the effect of each covariate on voluntary and mandatory PDMP use.In total, 265 pharmacists participated (response rate 47%). Under voluntary conditions, a quarter of pharmacists (24.9%) used the PDMP all the time, while half (51.7%) used the PDMP all of the time, once mandated. Pharmacies that stocked naloxone (OR: 1.96; 95% CI 1.11-3.45) and pharmacists that had attended formal PDMP training (OR: 1.78; 95% CI 1.05-3.05), were significantly associated with regular PDMP use under voluntary conditions. Under mandatory conditions, increased odds of PDMP use were associated with pharmacies that stocked naloxone (OR: 1.88; 95% CI 1.06-3.34). Pharmacists working in regional and rural areas had significantly lower odds (OR: 0.35; 95% CI 0.20-0.63) of always using the PDMP, as did pharmacists with 15 years' experience (OR: 0.24; 95% CI 0.11-0.51) once use was mandated.Given that PDMP utilisation was slower or less regular amongst pharmacists located in regional and rural areas, pharmacists with more years of experience and those not already supplying naloxone, targeted training aimed at these sub-populations may be beneficial.

PurposeThe OPPICO cohort is a population-based cohort based on non-identifiable electronic health records routinely collected from 464 general practices in Victoria, Australia, created with the aim of understanding opioid prescribing, policy impacts and clinical outcomes. The aim of this paper is to provide a profile of the study cohort by summarising available demographic, clinical and prescribing characteristics.ParticipantsThe cohort described in this paper comprises people who were aged at least 14 years at cohort entry, and who were prescribed an opioid analgesic at least once at participating practices for a total of 1 137 728 person-years from 1 January 2015 to 31 December 2020. The cohort was formed using the data collected from electronic health records through the Population Level Analysis and Reporting (POLAR) system. The POLAR data primarily consist of patient demographics, clinical measurements, Australian Medicare Benefits Scheme item numbers, diagnoses, pathology testing and prescribed medications.Finding to dateIn total, the cohort consists of 676 970 participants with 4 389 185 opioid prescription records from 1 January 2015 to 31 December 2020. Approximately half (48.7%) received a single opioid prescription, and 0.9% received more than 100 opioid prescriptions. The mean number of opioid prescriptions per patient was 6.5 (SD=20.9); prescriptions for strong opioids accounted for 55.6% of all opioid prescriptions.Future plansThe OPPICO cohort data will be used for various types of pharmacoepidemiological research, including examining the impact of policy changes on coprescription of opioids with benzodiazepines and gabapentin, and monitoring trends and patterns of other medication utilisation. Through data-linkage between our OPPICO cohort and hospital outcome data, we will examine whether policy changes for opioid prescribing lead to changes in prescription opioid-related harms, and other drug and mental health-related outcomes.Trial registration numberEU PAS Register (EUPAS43218, prospectively registered).

IntroductionEach year, an estimated two million Australians commence opioids, with 50 000 developing longer-term (persistent) opioid use. An estimated 3%–10% of opioid-naïve patients prescribed opioids following surgery develop persistent opioid use. This study will compare rates of persistent opioid use between two commonly used postoperative opioids, oxycodone and tapentadol, to understand if initial postoperative opioid type is important in determining longer-term outcomes.Methods and analysisA retrospective data linkage study that analyses administrative data from hospital and community pharmacies. Data will be obtained from at least four pharmacies that service large hospitals with comparable supplies of oxycodone and tapentadol. The study will include at least 6000 patients who have been dispensed a supply of oxycodone or tapentadol to take home following their discharge from a surgical ward. The primary outcome measure will be persistent opioid use at 3 months postdischarge for opioid naïve people who receive either immediate release tapentadol or immediate release oxycodone. Hierarchical logistic regression models will be used to predict persistent opioid use, controlling for covariates including comorbidities.Ethics and disseminationEthics approval has been obtained through the Monash University Human Research Ethics Committee (29977). We will present project findings in a peer-reviewed journal article, in accordance with the REporting of studies Conducted using Observational Routinely-collected health Data statement.

Pregabalin has become widely used as an alternative to opioids in treating certain types of chronic non-cancer pain, but few studies have examined its clinical efficacy outside trials. We address this gap by examining the utilization, correlates and clinical outcomes of pregabalin use among an Australian community-based cohort of people prescribed opioids for chronic non-cancer pain. Through a five-year prospective cohort study (n = 1514) we examined associations between pregabalin use and pain severity and interference, mental health, opioid dose and past month use of ambulance and emergency department services. We used fixed-effects regression models to examine within-participant differences, and random-effects regression models to examine within and between participant differences in clinical outcomes. In an analysis of cases with complete data over five-years (n = 896), the prevalence of pregabalin use ranged from 16% at cohort entry to 29% at 36- and 48-months, and 46% reported pregabalin use at any time during the five years.. Pregabalin use was associated with greater pain severity and interference and greater use of high-risk opioid doses (>90 oral morphine equivalents/day). Pregabalin use was not associated with changes in mental health symptoms, ambulance, or emergency department attendance in the fixed or random effects models. Pregabalin use was common, but for most people use was not associated with clinically meaningful improvements in pain or functioning.

Background and aims Not all people experiencing opioid dependence benefit from oral opioid agonist treatment. The aim of this study was to examine perceptions of (supervised) injectable opioid agonist treatment (iOAT) (described as ‘an opioid similar to heroin self‐injected at a clinic several times a day’) among people who regularly use opioids and determine how common iOAT eligibility criteria accord with interest in iOAT. Design Cross‐sectional survey Setting Sydney, Melbourne and Hobart, Australia. Participants A total of 344 people (63% male) who use opioids regularly and had ever injected opioids, interviewed December 2017–March 2018. The mean age of participants was 41.5 years [standard deviation (SD) = 8.5]. Measurements Primary outcome measures were interest in iOAT, factors associated with interest and the proportion of participants who would be eligible using common criteria from trials and guidelines. We examined willingness to travel for iOAT, medication preferences and perspectives on whom should receive iOAT. Findings Overall, 53% of participants (n = 182) believed that iOAT would be a good treatment option for them. Participants who believed that iOAT was a good treatment option for them were more likely to be male [adjusted odds ratio (aOR) = 1.76, 95% confidence interval (CI) = 1.10–2.82], have used heroin in the past month (aOR = 6.03, 95% CI = 2.86–12.71), currently regularly inject opioids (aOR = 1.84, 95% CI = 1.16–2.91) and have met ICD‐10 criteria for opioid dependence (aOR = 3.46, 95% CI = 1.65–7.24). Those interested in iOAT had commenced more treatment episodes (aOR =1.06, 95% CI = 1.00–1.12). Among those interested in iOAT (n = 182), 26% (n = 48) met common eligibility criteria for iOAT. Conclusions Interest in injectable opioid agonist treatment does not appear to be universal among people who regularly use opioids. Among study participants who expressed interest in injectable opioid agonist treatment, most did not meet common eligibility criteria.

ObjectiveThe Routine Opioid Outcome Monitoring (ROOM) tool measures outcomes with opioids using an established framework which includes domains such as pain, mood, opioid use disorder, alcohol use, and constipation. This study aims to validate and establish the test-retest reliability of the computer-administered ROOM tool.Design and SettingCross-sectional analysis of an online sample.SubjectsParticipants comprised those with chronic noncancer pain who regularly used prescription opioids.MethodsParticipants self-completed the online ROOM tool along with other validated measures (validation questionnaire), and those who were agreeable also completed the online test-retest questionnaire approximately two weeks later. Subcomponents of the ROOM tool (i.e., pain, mood, alcohol use, opioid use disorder, and constipation) were validated against longer measures of the same construct using Pearson correlation coefficients. Intraclass correlation coefficients were used to assess the stability of the ROOM tool over time.ResultsA total of 324 participants completed the validation questionnaire, of whom 260 also completed the test-retest questionnaire. The opioid use disorder domain showed good sensitivity (73.6) and specificity (75.8) against the Diagnostic and Statistical Manual of Mental Disorders, 5th Edition, any opioid use disorder. All ROOM components showed moderate correlation (r = 0.55–0.73) with their longer counterparts. Test-retest reliability was fair (0.58–0.75), indicating that responses were relatively stable over time. Reliability did vary, however, based on the components being measured and how certain tools were scored.ConclusionThe computer-administered ROOM tool is a valid approach for brief monitoring of outcomes with prescribed opioids in primary care settings and appears to be acceptable to people who are using prescribed opioids for chronic pain.

Naloxone is a life-saving medication that reverses opioid overdose; naloxone can be provided on a 'take-home' basis so naloxone can be administered outside of the health-care setting. The Overdose Response and Take Home Naloxone (ORTHN) project established a model of care for take-home naloxone (THN) interventions across alcohol and other drug and harm reduction services in NSW, Australia. This paper evaluates the staff training and credentialing program, and examines staff attitudes and perspectives regarding the provision of THN interventions in these settings.Staff across seven services were trained through a 'train-the-trainer' credentialing model to deliver ORTHN, including naloxone supply. Staff were surveyed regarding their experience, attitudes and knowledge on THN prior to and after training, and after 6 months. At the 6 months follow up, staff were asked about the interventions they provided, barriers and enablers to uptake, and opinions regarding future rollout.A total of 204 staff were trained and credentialed to provide the ORTHN intervention. Most (60%) were nurses, followed by needle syringe program workers and allied health/counsellors (32%). Linear and logistic regression analyses indicated that the training program was associated with significant improvements in staff knowledge and attitudes towards overdose and THN; however, only attitudinal improvements were maintained over time. There were high rates of staff satisfaction with the ORTHN intervention and training.The ORTHN program is 'fit for purpose' for broad implementation in these settings. A number of potential barriers (e.g. time, medication and staffing costs) and enablers (e.g. peer engagement, regulatory framework for naloxone supply) in implementing THN interventions were identified.

Demand for medication assisted treatment for opioid dependence (MATOD) in Australia exceeds capacity, particularly in rural and regional areas. There is increasing recognition that community pharmacists are well-positioned to take on expanded roles in MATOD delivery, however there has been limited Australian research exploring attitudes of pharmacists, prescribers, and patients to collaborative models of care.This study aimed to better understand enablers and barriers to a collaborative model for MATOD, to inform implementation in regions where increases in treatment capacity are urgently needed.Semi-structured telephone interviews were conducted with pharmacists (n = 11), prescribers (n = 6), and patients (n = 8) recruited from the Frankston-Mornington Peninsula region in Victoria, Australia, where transport and access to services have impacts on health care utilisation. The COM-B model was used to explore perceptions of pharmacists' capability, opportunity, and motivations for delivering collaborative care.There was strong motivation among healthcare professionals to participate in a collaborative model of care, with the main perceived benefits including improvements in accessibility, convenience, and continuity of care, and leverage of pharmacists' high level of patient engagement. Key barriers identified by both pharmacists and prescribers included a perceived lack of pharmacist skills in some areas (capability) and resources (opportunity) to deliver collaborative care in a community pharmacy setting. Established relationships between all stakeholders (social opportunity) and communication between pharmacists and prescribers were identified as facilitators. Barriers and facilitators aligned with seven key areas: skills, confidence, relationships, patient selection, protocols, communication and resources.Findings informed the development of a collaborative model that was individualised, protocol based, and supported by training and clear processes.This study identifies specific barriers and facilitators to a pharmacist-prescriber collaborative model of care for MATOD. The resulting model will be tested in a hybrid implementation-effectiveness trial in the Frankston-Mornington Peninsula region.

ObjectiveThe OWLS is a screening tool for prescription opioid use disorder designed for use in primary care. This study aimed to confirm the optimal wording, scoring methods, and cutoff for the OWLS.Design and SettingCross-sectional analysis of an online sample.SubjectsParticipants comprised those with chronic noncancer pain who regularly used prescription opioids.MethodsEligible participants self-completed an online version of the OWLS prescription opioid use disorder screening tool and the Composite International Diagnostic Interview Substance Abuse module. Receiver operating characteristics were calculated for three scoring methods for the OWLS, and these were compared with DSM-5 classification of any use disorder and moderate to severe opioid use disorder.ResultsAmong the sample (N = 324), utilizing scoring method (i) (i.e., positive endorsement ≥ response option “a little bit”) and a cutoff of 3 increased the percentage of correctly classified participants, with concurrent increases in specificity and decreases in false discovery rate, and false positive rate.ConclusionOWLS utilizing scoring method (i) with a cutoff of 3 was shown to be the optimal version and scoring method of this tool. This represents a time-efficient, simple scoring method, allowing for quick and accurate screening for opioid use disorder to occur.