Non-fatal overdose risk associated with prescribing opioid agonists concurrently with other medication: Cohort study conducted using linked primary care, secondary care and mortality records.

BACKGROUND AND AIMS: An apparently protective effect of opioid agonist treatment (OAT) on all-cause and cause-specific mortality risk has been widely reported. Non-fatal overdose (NFO) often precedes subsequent drug-poisoning deaths. We hypothesized that benzodiazepines, gabapentinoids, antipsychotics, antidepressants, Z-drugs or opioids increase the NFO risk when co-prescribed with OAT. DESIGN: We conducted a cohort study using the Clinical Practice Research Datalink GOLD and Aurum databases. The cohort was linked to Hospital Episode Statistics admitted patient care data (HES-APC), neighbourhood- and practice-level Index of Multiple Deprivation quintiles and mortality records from the Office for National Statistics. SETTING: Primary care in England. PARTICIPANTS: We studied patients with opioid use disorder, aged 18-64 years, who were prescribed OAT (15155 methadone and 5743 buprenorphine recipients) between Jan 1, 1998, and Dec 31, 2017. MEASUREMENTS: The main outcome examined was NFO risk during co-prescription of OAT with benzodiazepines, antipsychotics, gabapentinoids, antidepressants, Z-drugs or opioids. Overdose was defined according to International Classification of Diseases codes from the HES-APC data set. Negative binomial regression models were used to estimate weighted rate ratios (wRR) for NFO during co-prescription of OAT and benzodiazepines, antipsychotics, gabapentinoids, antidepressants, Z-drugs or opioids with periods of exclusive OAT usage. FINDINGS: Among 20 898 patients observed over 83 856 person-years, we found an elevated overdose risk that resulted in hospital admission during co-prescription of OAT with benzodiazepines [wRR: 1.45; 95% confidence interval (CI) = 1.26-1.67], gabapentinoids (wRR = 2.22; 95% CI = 1.77-2.79), Z-drugs (wRR = 1.60; 95% CI = 1.31-1.96), antipsychotics (wRR = 1.85; 95% CI = 1.53-2.25) and opioids (wRR = 1.28; 95% CI = 1.02-1.60). The risk ratio for antidepressant co-prescriptions was below unity (wRR = 0.90; 95% CI = 0.79-1.02) but this result was not statistically significant. CONCLUSION: Elevated risk of non-fatal overdose among opioid agonist treatment recipients is associated with concurrent use of medication prescribed for other reasons.

Non-fatal overdose risk during and after opioid agonist treatment: A primary care cohort study with linked hospitalisation and mortality records.

Background: The initiation and cessation of opioid agonist treatment (OAT) have both been associated with elevated risk of fatal overdose. We examined risk of non-fatal overdose during OAT initiation and cessation and specifically between methadone versus buprenorphine recipients. Methods: We utilised primary care electronic health records from the Clinical Practice Research Datalink to delineate a study cohort of adults aged 18-64 who were prescribed OAT between Jan 1, 1998 and Dec 31, 2017. These records were linked to hospitalisation, mortality records and patient neighbourhood and practice-level Index of Multiple Deprivation quintiles. With inverse probability treatment weights applied and negative binomial regression models we estimated incidence rate ratios for hospital admissions among patients who experienced multiple overdoses. Findings: A total of 20898 patients were prescribed methadone or buprenorphine over 83856 person-years of follow-up. Compared with periods in treatment, patients not in treatment were 51% more likely to experience a non-fatal overdose that required hospitalisation (weighted rate ratio, wRR 1·51; 95% CI 1·42, 1·60), especially during the four weeks of OAT initiation (5·59; 5·31, 5·89) and following cessation (13·39; 12·78, 14·03). The wRR of overdose during (0·37; 0·34, 0·39) and after treatment (0·36; 0·34, 0·38) favoured buprenorphine compared to methadone. Interpretation: OAT is associated with decreased non-fatal overdose risk. Buprenorphine may act more protectively than methadone, especially during the first four weeks of treatment. Funding: National Institute for Health and Care Research (NIHR) Greater Manchester Patient Safety Translational Research Centre (PSTRC-2016-003).

Tobacco Smoking Rates in a National Cohort of People with Substance Use Disorder Receiving Treatment.

BACKGROUND AND AIM: The prevalence of tobacco smoking among individuals receiving treatment for substance use disorder (SUD) remains high. Respiratory disease and other harms are of prime concern to health policy-makers, given the contributory role played by tobacco smoking in the excess rates of premature mortality seen in individuals with SUD. The aim was to use SUD treatment data to investigate tobacco smoking prevalence among subgroups of adults over the course of treatment. METHODS: We used the English National Drug Treatment Monitoring System (NDTMS) to examine number of days tobacco had been smoked in the previous month in adults receiving SUD treatment (N = 106,472, median length of treatment 157 days). RESULTS: At baseline (treatment start), 48.7% reported smoking tobacco; the highest rate was observed in opiate users (61%). Overall, the level of smoking at the latest assessment was 48.5%. Reductions (of between 5 and 7%) were observed among those who finished treatment but only within the final stages of treatment. A 5% increase in smoking was observed in those still in treatment within the study timeframe. CONCLUSIONS: This study identifies the potential for a greater emphasis on reducing tobacco consumption within SUD treatment, for example, by offering all smokers within SUD treatment smoking cessation support as part of their SUD treatment programme.

Estimates of the Incidence of Crack Cocaine Use in Those Likely to Attend Treatment in the English Population, 2005-2018.

BACKGROUND: Public health bodies in the UK, and elsewhere, have expressed concern over the wider social and economic impact of crack cocaine use on society. OBJECTIVE: The aim of the study was to use English substance misuse treatment data to estimate the incidence of crack cocaine use in the population who are expected to present to treatment with crack cocaine as the primary substance. METHOD: Known year of first crack-related treatment demand and age of first use of crack were combined to provide the distribution of lag to treatment for each year of onset. The resulting combined lag distribution was used to estimate the proportion of incident crack cocaine users who will have presented in a given year and, from that, the total number who will have started in that year. RESULTS: Our estimates identified an approximate doubling in incidence between 2012 and 2016, following a decrease up to 2012. CONCLUSION: This represents an increase in treatment demand that is likely to continue for a number of years.

Estimating the prevalence of problem drug use from drug-related mortality data.

BACKGROUND AND AIMS: Indirect estimation methods are required for estimating the size of populations where only a proportion of individuals are observed directly, such as problem drug users (PDUs). Capture-recapture and multiplier methods are widely used, but have been criticized as subject to bias. We propose a new approach to estimating prevalence of PDU from numbers of fatal drug-related poisonings (fDRPs) using linked databases, addressing the key limitations of simplistic 'mortality multipliers'. METHODS: Our approach requires linkage of data on a large cohort of known PDUs to mortality registers and summary information concerning additional fDRPs observed outside this cohort. We model fDRP rates among the cohort and assume that rates in unobserved PDUs are equal to rates in the cohort during periods out of treatment. Prevalence is estimated in a Bayesian statistical framework, in which we simultaneously fit regression models to fDRP rates and prevalence, allowing both to vary by demographic factors and the former also by treatment status. RESULTS: We report a case study analysis, estimating the prevalence of opioid dependence in England in 2008/09, by gender, age group and geographical region. Overall prevalence was estimated as 0.82% (95% credible interval = 0.74-0.94%) of 15-64-year-olds, which is similar to a published estimate based on capture-recapture analysis. CONCLUSIONS: Our modelling approach estimates prevalence from drug-related mortality data, while addressing the main limitations of simplistic multipliers. This offers an alternative approach for the common situation where available data sources do not meet the strong assumptions required for valid capture-recapture estimation. In a case study analysis, prevalence estimates based on our approach were surprisingly similar to existing capture-recapture estimates but, we argue, are based on a much more objective and justifiable modelling approach.

The role of neuropsychological mechanisms in implementation intentions to reduce alcohol consumption among heavy drinkers: a randomized trial.

Implementation intention formation, which involves identifying triggers and linking them with coping strategies, has proven effective at reducing alcohol consumption in general populations. For the first time, the present study tested the ability of implementation intentions to reduce alcohol consumption among heavy drinkers and to explore potential neuropsychological mechanisms. At baseline, participants were randomized to form implementation intentions or to an active control group. There was a 5.7 unit (1 unit = 10 ml or 8 g ethanol) per week reduction ([95%CI 0.15, 11.19], p = 0.048) in alcohol consumption at 1 month follow-up among participants who formed implementation intentions, which was significantly more than controls F(1, 91) = 3.95, p = 0.048, a medium effect size (d = 0.47, Cohen, 1992). No significant differences in performance on the neuropsychological tasks were found between groups. The present study demonstrates for the first time that implementation intentions reduce alcohol consumption among heavy drinkers.

Evidence That Implementation Intentions Enhance Cognitive Training and Reduce Alcohol Consumption in Heavy Drinkers: A Randomized Trial.

BACKGROUND: Current training tasks to improve the cognitive deficits thought to be involved in sustained heavy drinking need further investigation to optimize their effectiveness. PURPOSE: The present study investigated whether combining implementation intention provision with a cognitive training task had a measurable effect on alcohol consumption in heavy drinkers and explored the neural mechanisms underpinning any reductions in subsequent alcohol consumption. METHODS: Thirty-two heavy-drinking participants completed approach-avoidance and visual probe training tasks preintervention and postintervention during functional Magnetic Resonance Imaging. Participants in the intervention group were randomized to form implementation intentions and participants in the control condition read a goal intention. Alcohol consumption was recorded preintervention and at 1 month follow-up. RESULTS: Compared to the control group, implementation intention provision significantly improved performance on alcohol-avoidance tasks postintervention, t(30) = -2.315, p = .028, d = .85, and reduced alcohol consumption by 6.9 units/week (1 unit = 10 mL or 8 g ethanol), F(1,30) = 4.263, p = .048 (d = .74), at follow-up. However, the analysis of functional Magnetic Resonance Imaging data revealed no significant differences between groups. CONCLUSIONS: These findings show for the first time that implementation intentions targeting cognitive processes can significantly reduce alcohol consumption among heavy drinkers. However, there was no evidence that the effects were mediated by changes in neural activity. Further work is required to explore the neural mechanisms underpinning the operation of implementation intentions. TRIAL REGISTRATION: This trial was registered (ISRCTN:35503634) and is available at https://www.isrctn.com/ISRCTN35503634.

Frequency of health-care utilization by adults who use illicit drugs: a systematic review and meta-analysis.

AIMS: To summarize evidence on the frequency and predictors of health-care utilization among people who use illicit drugs. DESIGN: Systematic search of MEDLINE, EMBASE and PsychINFO for observational studies reporting health-care utilization published between 1 January 2000 and 3 December 2018. We conducted narrative synthesis and meta-analysis following a registered protocol (identifier: CRD42017076525). SETTING AND PARTICIPANTS: People who use heroin, powder cocaine, crack cocaine, methamphetamine, amphetamine, ecstasy/3,4-methyl​enedioxy​methamphetamine (MDMA), cannabis, hallucinogens or novel psychoactive substances; have a diagnosis of 'substance use disorder'; or use drug treatment services. MEASUREMENTS: Primary outcomes were the cumulative incidence (risk) and rate of care episodes in three settings: primary care, hospital admissions (in-patient) and emergency department (ED). FINDINGS: Ninety-two studies were included, 84% from North America and Australia. Most studies focused on people using heroin, methamphetamine or crack cocaine, or who had a diagnosis of drug dependence. We were able to conduct a meta-analysis of rates across 25 studies reporting ED episodes and 25 reporting hospital admissions, finding pooled rates of 151 [95% confidence interval (CI) = 114-201] and 41 (95% CI = 30-57) per 100 person-years, respectively; on average 4.8 and 7.1 times more often than the general population. Heterogeneity was very high and was not explained by drugs used, country of study, recruitment setting or demographic characteristics. Predictors of health-care utilization were consistent across studies and included unstable housing, drug injection and mental health problems. Opioid substitution therapy was consistently associated with reduced ED presentation and hospital admission. There was minimal research on health-care utilization by people using ecstasy/MDMA, powder cocaine, hallucinogens or novel psychoactive substances. CONCLUSIONS: People who use illicit drugs are admitted to emergency department or hospital several times more often than the general population.

Prescription of benzodiazepines, z-drugs, and gabapentinoids and mortality risk in people receiving opioid agonist treatment: Observational study based on the UK Clinical Practice Research Datalink and Office for National Statistics death records.

BACKGROUND: Patients with opioid dependency prescribed opioid agonist treatment (OAT) may also be prescribed sedative drugs. This may increase mortality risk but may also increase treatment duration, with overall benefit. We hypothesised that prescription of benzodiazepines in patients receiving OAT would increase risk of mortality overall, irrespective of any increased treatment duration. METHODS AND FINDINGS: Data on 12,118 patients aged 15-64 years prescribed OAT between 1998 and 2014 were extracted from the Clinical Practice Research Datalink. Data from the Office for National Statistics on whether patients had died and, if so, their cause of death were available for 7,016 of these patients. We identified episodes of prescription of benzodiazepines, z-drugs, and gabapentinoids and used linear regression and Cox proportional hazards models to assess the associations of co-prescription (prescribed during OAT and up to 12 months post-treatment) and concurrent prescription (prescribed during OAT) with treatment duration and mortality. We examined all-cause mortality (ACM), drug-related poisoning (DRP) mortality, and mortality not attributable to DRP (non-DRP). Models included potential confounding factors. In 36,126 person-years of follow-up there were 657 deaths and 29,540 OAT episodes, of which 42% involved benzodiazepine co-prescription and 29% concurrent prescription (for z-drugs these respective proportions were 20% and 11%, and for gabapentinoids 8% and 5%). Concurrent prescription of benzodiazepines was associated with increased duration of methadone treatment (adjusted mean duration of treatment episode 466 days [95% CI 450 to 483] compared to 286 days [95% CI 275 to 297]). Benzodiazepine co-prescription was associated with increased risk of DRP (adjusted HR 2.96 [95% CI 1.97 to 4.43], p < 0.001), with evidence of a dose-response effect, but showed little evidence of an association with non-DRP (adjusted HR 0.91 [95% CI 0.66 to 1.25], p = 0.549). Co-prescription of z-drugs showed evidence of an association with increased risk of DRP (adjusted HR 2.75 [95% CI 1.57 to 4.83], p < 0.001) but little evidence of an association with non-DRP (adjusted HR 0.79 [95% CI 0.49 to 1.28], p = 0.342). There was no evidence of an association of gabapentinoid co-prescription with DRP (HR 1.54 [95% CI 0.60 to 3.98], p = 0.373) but evidence of an association with increased non-DRP (HR 1.83 [95% CI 1.28 to 2.62], p = 0.001). Concurrent benzodiazepine prescription also increased mortality risk after consideration of duration of OAT (adjusted HR for DRP with benzodiazepine concurrent prescription 3.34 [95% CI 2.14 to 5.20], p < 0.001). The main limitation of this study is the possibility that unmeasured confounding factors led to an association between benzodiazepine prescription and DRP that is not causal. CONCLUSIONS: In this study, co-prescription of benzodiazepine was specifically associated with increased risk of DRP in opioid-dependent individuals. Co-prescription of z-drugs and gabapentinoids was also associated with increased mortality risk; however, for z-drugs there was no evidence for a dose-response effect on DRP, and for gabapentinoids the increased mortality risk was not specific to DRP. Concurrent prescription of benzodiazepine was associated with longer treatment but still increased risk of death overall. Clinicians should be cautious about prescribing benzodiazepines to opioid-dependent individuals.

Modeling the Potential Impact of Changing Access Rates to Specialist Treatment for Alcohol Dependence for Local Authorities in England: The Specialist Treatment for Alcohol Model (STreAM).

OBJECTIVE: We modeled the impact of changing Specialist Treatment Access Rates to different treatment pathways on the future prevalence of alcohol dependence, treatment outcomes, service capacity, costs, and mortality. METHOD: Local Authority numbers and the prevalence of people "potentially in need of assessment for and treatment in specialist services for alcohol dependence" (PINASTFAD) are estimated by mild, moderate, severe, and complex needs. Administrative data were used to estimate the Specialist Treatment Access Rate per PINASTFAD person and classify 22 different treatment pathways. Other model inputs include natural remission, relapse after treatment, service costs, and mortality rates. "What-if" analyses assess changes to Specialist Treatment Access Rates and treatment pathways. Model outputs include the numbers and prevalence of people who are PINASTFAD, numbers treated by 22 pathways, outcomes (successful completion with abstinence, successfully moderated nonproblematic drinking, re-treatment within 6 months, dropout, transfer, custody), mortality rates, capacity requirements (numbers in contact with community services or staying in residential or inpatient places), total treatment costs, and general health care savings. Five scenarios illustrate functionality: (a) no change, (b) achieve access rates at the 70th percentile nationally, (c) increase access by 25%, (d) increase access to Scotland rate, and (e) reduce access by 25%. RESULTS: At baseline, 14,581 people are PINASTFAD (2.43% of adults) and the Specialist Treatment Access Rate is 10.84%. The 5-year impact of scenarios on PINASTFAD numbers (vs. no change) are (B) reduced by 191 (-1.3%), (C) reduced by 477 (-3.3%), (D) reduced by almost 2,800 (-19.2%), and (E) increased by 533 (+3.6%). The relative impact is similar for other outputs. CONCLUSIONS: Decision makers can estimate the potential impact of changing Specialist Treatment Access Rates for alcohol dependence.

Prevalence of recent fentanyl use among treated users of illicit opioids in England: based on piloted urine drug screens.

OBJECTIVE: To use a pilot of national fentanyl screening to establish the current prevalence of recent fentanyl use among treated users of illicit opioids in the English treatment system and inform the design of a full study. DESIGN: Cross-sectional fentanyl metabolite urine screening in randomly-selected study sites, stratified to cover all nine geographical regions of England, supplemented with self-report subsequent to a positive fentanyl test. PATIENTS: 468 adult (18 years of age and above) patients receiving treatment for opioid use disorder, screened December 2017 to May 2018. RESULTS: The fentanyl-positive rate in patients receiving treatment for opioid use disorder in the English treatment system was 3% (15/468, 95% CI 1.8% to 5.2%) with a per-site range (for the 10 sites in 9 regions where fentanyl was detected) of between 2% (1/57) and 15% (4/27). Self-report data indicated that the majority of fentanyl-positives (12/15, 80%) was unaware of having purchased fentanyl. CONCLUSIONS: Despite alerts already in place, patients receiving treatment for opioid use disorder, who were fentanyl-positive, were unwittingly purchasing and consuming fentanyl.

The impact of buprenorphine and methadone on mortality: a primary care cohort study in the United Kingdom.

AIMS: To estimate whether opioid substitution treatment (OST) with buprenorphine or methadone is associated with a greater reduction in the risk of all-cause mortality (ACM) and opioid drug-related poisoning (DRP) mortality. DESIGN: Cohort study with linkage between clinical records from Clinical Practice Research Datalink and mortality register. SETTING: UK primary care. PARTICIPANTS: A total of 11 033 opioid-dependent patients who received OST from 1998 to 2014, followed-up for 30 410 person-years. MEASUREMENTS: Exposure to methadone (17 373, 61%) OST episodes or buprenorphine (9173, 39%) OST episodes. ACM was available for all patients; information on cause of death and DRP was available for 5935 patients (54%) followed-up for 16 363 person-years. Poisson regression modelled mortality by treatment period with an interaction between OST type and treatment period (first 4 weeks on OST, rest of time off OST, first 4 weeks off OST, rest of time out of OST censored at 12 months) to test whether ACM or DRP differed between methadone and buprenorphine. Inverse probability weights were included to adjust for confounding and balance characteristics of patients prescribed methadone or buprenorphine. FINDINGS: ACM and DRP rates were 1.93 and 0.53 per 100 person-years, respectively. DRP was elevated during the first 4 weeks of OST [incidence rate ratio (IRR) = 1.93 95% confidence interval (CI) = 0.97-3.82], the first 4 weeks off OST (IRR = 8.15, 95% CI = 5.45-12.19) and the rest of time out of OST (IRR = 2.13, 95% CI = 1.47-3.09) compared with mortality risk from 4 weeks to end of treatment. Patients on buprenorphine compared with methadone had lower ACM rates in each treatment period. After adjustment, there was evidence of a lower DRP risk for patients on buprenorphine compared with methadone at treatment initiation (IRR = 0.08, 95% CI = 0.01-0.48) and rest of time on treatment (IRR = 0.37, 95% CI = 0.17-0.79). Treatment duration (mean and median) was shorter on buprenorphine than methadone (173 and 40 versus 363 and 111, respectively). Model estimates suggest that there was a low probability that methadone or buprenorphine reduced the number of DRP in the population: 28 and 21%, respectively. CONCLUSIONS: In UK general medical practice, opioid substitution treatment with buprenorphine is associated with a lower risk of all-cause and drug-related poisoning mortality than methadone. In the population, buprenorphine is unlikely to give greater overall protection because of the relatively shorter duration of treatment.

Effectiveness of inpatient withdrawal and residential rehabilitation interventions for alcohol use disorder: A national observational, cohort study in England.

BACKGROUND: This was a national English observational cohort study to estimate the effectiveness of inpatient withdrawal (IW) and residential rehabilitation (RR) interventions for alcohol use disorder (AUD) using administrative data. METHODS: All adults commencing IW and/or RR intervention for AUD between April 1, 2014 and March 31, 2015 reported to the National Drug Treatment Monitoring System (n=3812). The primary outcome was successful completion of treatment within 12months of commencement, with no re-presentation (SCNR) in the subsequent six months, analysed by multi-level, mixed effects, multivariable logistic regression. RESULTS: The majority (70%, n=2682) received IW in their index treatment journey; one-quarter (24%, n=915) received RR; 6% (n=215) received both. Of treatment leavers, 59% achieved the SCNR outcome (IW: 57%; RR: 64%; IW/RR: 57%). Positive outcome for IW was associated with older age, being employed, and receiving community-based treatment prior to and subsequent to IW. Patients with housing problems were less likely to achieving the outcome. Positive outcome for RR was associated with paid employment, self/family/peer referral, longer duration of RR treatment, and community-based treatment following discharge. Community-based treatment prior to entering RR, and receiving IW during the same treatment journey as RR, were associated with lower likelihood of SCNR. CONCLUSIONS: In this first national effectiveness study of AUD in the English public treatment system for alcohol-use disorders, 59% of patients successfully completed treatment within 12months and did not represent for more treatment within six months. Longer duration of treatment and provision of structured continuing care is associated with better treatment outcomes.

Effectiveness of community psychosocial and pharmacological treatments for alcohol use disorder: A national observational cohort study in England.

BACKGROUND: This was a national English observational cohort study using administrative data to estimate the effectiveness of community pharmacological and psychosocial treatment for alcohol use disorder (AUD). METHODS: All adults commencing AUD treatment in the community reported to the National Drug Treatment Monitoring System (April 1 2014-March 31 2015; N = 52,499). Past 28-day admission drinking pattern included drinks per drinking day (DDD): 0 ('Abstinent'), 1-15 ('Low-High'), 16-30 ('High-Extreme') and over 30 DDD ('Extreme'). The primary outcome was successful completion of treatment within 12 months of commencement with no re-presentation (SCNR) in the subsequent six months, analysed by multi-level, mixed effects, multivariable logistic regression. RESULTS: The majority reported DDD in the 'Low-High' (n = 17,698, 34%) and 'High-Extreme' (n = 21,383, 41%) range. Smaller proportions were categorised 'Extreme' (n = 7759, 15%) and 'Abstinent' (n = 5661, 11%). Three-fifths (58%) achieved SCNR. Predictors of SCNR were older age, black/minority ethnic group, employment, criminal justice system referral, and longer treatment exposure. Predictors of negative outcome were AUD treatment history, lower socio-economic status, housing problems, and 'Extreme' drinking at admission. In addition to psychosocial interventions, pharmacological interventions and recovery support increased the likelihood of SCNR. Pharmacological treatment was only beneficial for the 'Low-High' groups with recovery support. CONCLUSIONS: Over half of all patients admitted for community AUD treatment in England are reported to successfully complete treatment within 12 months and are not re-admitted for further treatment in the following 6 months. Study findings underscore efforts to tailor AUD treatment to the severity of alcohol consumption and using recovery support.

Ageing opioid users' increased risk of methadone-specific death in the UK.

BACKGROUND: The first evidence that the hazard ratio (HR) for methadone-specific death rises more steeply with age-group than for all drug-related deaths (DRDs) came from Scotland's cohort of 33,000 methadone-prescription clients. We aim to examine, for England, whether illicit opioid users' risk of methadone-specific death increases with age; and to pool age-related HRs for methadone-specific deaths with those for Scotland's methadone-prescription clients. METHODS: The setting is all services in England that provide publicly-funded, structured treatment for illicit opioid users, the methodology linkage of the English National Drug Treatment Monitoring System and mortality database, and key measurements are DRDs, methadone-specific DRDs, or heroin-specific DRDs, by age-group and gender, with proportional hazards adjustment for substances used, injecting status and periods in/out of treatment. RESULTS: Linkage was achieved for 129,979 adults receiving prescribing treatment modalities for opioid dependence during April 2005 to March 2009 and followed-up for 378,009 person-years (pys). There were 1,266 DRDs: 271 methadone-specific (7 per 10,000 pys: irrespective of gender) and 473 heroin-specific (15 per 10,000 pys for males, 7 for females). Methadone-specific DRD-rate per 10,000 person-years was 3.5 (95% CI: 2.7-4.4) at 18-34 years, 8.9 (CI: 7.3-10.5) at 35-44 years and 18 (CI: 13.8-21.2) at 45+ years; heroin-specific DRD-rate was unchanged with age. Relative to 25-34 years, pooled HRs for UK clients' methadone-specific deaths were: 0.87 at <25 years (95% CI: 0.56-1.35); 2.14 at 35-44 years (95% CI: 1.76-2.60); 3.75 at 45+ years (95% CI: 2.99-4.70). CONCLUSION: International testing and explanation are needed of UK's sharp age-related increase in the risk of methadone-specific death. Clients should be alerted that their risk of methadone-specific death increases as they age.

Does paying service providers by results improve recovery outcomes for drug misusers in treatment in England?

AIM: To compare drug recovery outcomes in commissioning areas included in a 'payment by results' scheme with all other areas. DESIGN: Observational and data linkage study of the National Drug Treatment Monitoring System, Office for National Statistics mortality database and Police National Computer criminal records, for 2 years before and after introduction of the scheme. Pre-post controlled comparison compared outcomes in participating versus non-participating areas following adjustment for drug use, functioning and drug treatment status. SETTING: Drug services in England providing publicly funded, structured treatment. PARTICIPANTS: Adults in treatment (between 2010 and 2014): 154 175 (10 716 in participating areas, 143 459 non-participating) treatment journeys in the 2 years before and 148 941 (10 012 participating, 138 929 non-participating) after the introduction of the scheme. INTERVENTION: Scheme participation, with payment to treatment providers based on patient outcomes versus all other areas. MEASUREMENTS: Rate of treatment initiation; waiting time (> or < 3 weeks); treatment completion; and re-presentation; substance use; injecting; housing status; fatal overdose; and acquisitive crime. FINDINGS: In participating areas, there were relative decreases in rates of: treatment initiation [difference-in-differences odds ratio (DID OR) = 0.17, 95% confidence interval (CI) = 0.14, 0.21]; treatment completion (DID OR = 0.60, 95% CI = 0.53, 0.67); and treatment completion without re-presentation (DID OR = 0.63, 95% CI = 0.52, 0.77) compared with non-participating areas. Within treatment, relative abstinence (DID OR = 1.50, 95% CI = 1.30, 1.72) and non-injecting (DID OR = 1.32, 95% CI = 1.10, 1.59) rates were improved in participating areas. No significant changes in mortality, recorded crime or housing status were associated with the scheme. CONCLUSION: Drug addiction recovery services in England that are commissioned on a payment-by-results basis tend to have lower rates of treatment initiation and completion but higher rates of in-treatment abstinence and non-injecting than other services.

Effect of initiating drug treatment on the risk of drug-related poisoning death and acquisitive crime among offending heroin users.

BACKGROUND: A recent Cochrane review of randomised trials identified a lack of evidence for interventions provided to drug-using offenders. We use routine data to address whether contact with treatment services reduces heroin users' likelihood of a future acquisitive offence or drug-related poisoning (DRP) death. METHODS: Heroin-users were identified from probation assessments and linked to drug-treatment, mortality and offending records. The study cohort was selected to ensure that the subject was not: in prison, in treatment or had recently left treatment. Subjects were classed as initiators if they attended a triage appointment within two weeks of their assessment; non-initiators otherwise. Initiator and non-initiators were compared over a maximum of one year, with respect to their risk of recorded acquisitive offence or DRP-death. Balance was sought using propensity score matching and missing data were accounted for using multiple imputation. RESULTS: Nine percent of assessments identified for analysis were classed as initiators. Accounting for observed confounding and missing data, there was a reduction in DRPs associated with initiator assessments, however there was uncertainty around this estimate such that a null-effect could not be ruled out (HR: 0.42, 95% CI 0.17-1.04). There was no evidence of a decrease in the recidivism risk, in fact the analysis showed a small increase (HR: 1.10, 95% CI 1.02-1.18). CONCLUSION: For heroin-using offenders, initial contact with treatment services does not appear to reduce the likelihood of a future acquisitive offence.

Levels of Motivation and Readiness for Treatment Aligned With Criminal Justice Referral and Coercion Among Substance Users in England.

OBJECTIVE: Motivation and readiness for substance misuse treatment predict treatment retention and successful treatment outcomes but may be lower among substance users coerced into treatment. We tested for differences associated with legal involvement and with client perceptions of coercion among individuals entering drug misuse treatment in England. METHOD: Data collection involved 342 treatment agencies. Measures of motivation and readiness for treatment were taken from the Circumstances, Motivation, and Readiness (CMR) scale. Referral source was ordered to represent level of legal involvement and conditions. Perceived coercion was defined by a CMR item. Linear regression models, adjusting for client complexity, tested for differences in motivation and readiness by these measures. RESULTS: Levels of motivation and readiness did not differ according to level of legal conditions (coefficient = -0.38, 95% CI [-1.65, 0.88]). Motivation was inversely associated with perceived coercion (coefficient = -0.28, 95% CI [-0.05, -0.50], p = .014). CONCLUSIONS: At the point of treatment entry, criminal justice referral and aligned conditions have no impact on levels of motivation to achieve positive treatment outcomes. Concerns around lower levels of motivation are better focused on those who perceive themselves as coerced rather than on those whose referral carries a level of legal condition.