Retention in drug treatment is considered by the NTA to be the best available measure of treatment effectiveness [4]. To encourage a reduction in drop out rates, treatment retention measures were included in local partnership treatment plans and Primary Care Trust local delivery plans for the first time in 2004/05 [12], with 75% of drug users expected to be retained in treatment for at least 12 weeks during each annual reporting period [4]. Rates of retention can be improved by better understanding factors associated with premature drop out. The aims of the present study were to assess whether the retention target was achieved in the North West of England in 2005/06 and to identify factors associated with drop out. While a number of factors associated with drop out are identified, results also highlight the complexity of factors associated with treatment outcomes.
Results show that, overall in the North West, the treatment systems achieved the Government's retention target in 2005/06, with 75% of people retained for 12 weeks or more. Contextual information provides a more valuable assessment of how services should be improved, and the analyses presented here shows that current services are failing to retain Asian drug users. Furthermore, demographic data from the 2001 census [20] shows that Asian people are underrepresented in drug treatment services while those from white, mixed, black and 'other' ethnicities are adequately represented. While people of Asian ethnicity account for 3.4% of the population of the North West [20] they accounted for just 1.9% of the drug treatment population (Table 3). This finding may reflect the lower prevalence of drug use among Asian people although a growing body of evidence indicates that drug use exists among black and minority ethnic (BME) groups and that it is increasing [21]. Qualitative research into the extent and nature of drug use among young Asians suggests that they were increasingly likely to use illicit drugs and that knowledge and use of heroin, and perhaps crack cocaine, indicated similar use to the general population of the UK [22].
An alternative explanation is that Asian drug users are not attracted by current treatment provision. A recent review of literature on drug use and service provision for BME communities in England reported a number of potential reasons for differential treatment outcomes among drug users from different ethnicities, over and above the possibility of differing drug profiles [21]. Such reasons included the ethnicity of drugs workers, communication problems for those unable to speak English and a perception among drug users that drug workers lacked awareness of their culture. No literature which evaluated outcomes of culturally-sensitive initiatives in the clinical drug treatment field in the UK could be identified by reviewers although they pointed to two USA-based studies which showed that culturally competent and culturally responsive treatment was often associated with greater treatment retention and longer treatment durations [23, 24]. With respect to drug use among young Asians, healthcare professionals must be sensitive to the cultural context in which their behaviours occur and in particular the potential conflict of being affiliated to two different and at times incongruent cultural groups – British youth culture and that of their ethnic origin [22]. Further work is required to identify perceived barriers to treatment among Asian drug users and the reasons why they are more likely to drop out than their white counterparts, once contact has been initiated.
With respect to other individual characteristics, studies in the USA have reported longer durations of treatment for older drug users [8, 10, 25] and for male drug users [10]. Evidence from a UK-based retrospective cohort study showed no difference between men and women in rates of drop out compared to drug free discharge but that younger drug users (aged 10 to 19 years) were more likely to drop out than their older counterparts [18]. Here, bivariate analysis showed that the odds of drop out exhibited a significant inverse linear relationship with age. However, the multivariate analysis showed that age was not significantly associated with drop out once adjusted for deprivation and that a significant interaction between deprivation and age existed. The effect of deprivation was not included in the retrospective cohort study just detailed so no assessment of the relationship between age and deprivation is available.
A wealth of data exists which shows the relationship between socio-economic status and health. In the North West of England, standardised mortality rates by deprivation show that the all-age rate for those in the most deprived quintile of population is one and three quarter times the rate for the most affluent quintile of the population [26]. However, results presented here show a complex relationship between deprivation and age and their effects upon drug treatment outcomes (Figure 1). For those aged between 18 and 24 years, people living in least deprived areas were almost twice as likely to drop out of treatment than those living in the most deprived areas. A similar effect, of smaller magnitude, was observed for those aged 25 to 34 years. For those in the oldest age group, (55 to 74 years) the converse was true and those living in the most deprived areas were less likely to drop out than those living in the least deprived areas. A similar, though smaller, effect was observed for those aged 45 to 55 years.
Encouraging treatment participation among younger drug users is a well-recognised problem [14]. Younger drug users are less likely to view their drug use as problematic or view themselves as dependent upon drugs [27] and young drug users living in affluent areas may be somewhat protected from the negative consequences of drug use from their affluent families. It is not clear why older drug users living in the most deprived environmental conditions were the least likely to drop out and this finding warrants further consideration. It should be noted however, that an ecological, rather than individual, measure of deprivation was used and that affluent individuals live in deprived areas and visa versa. It is conceivable that affluent areas have a lower prevalence of problematic drug use and lower levels of service provision and that younger drug users with less motivation to change are deterred from using services to which they have to travel. Travelling more than one mile to treatment has been shown in one USA-based study to reduce the likelihood of a person completing treatment by a half after the effects of demographic differences and the type of drugs used were controlled [28] and the possible impact of travelling to services requires further consideration in the UK.
Controlling for the effect of deprivation and other explanatory factors, significant differences in the odds of drop out were observed for different areas of the North West of England with the odds greater among residents of Cumbria and Lancashire and Greater Manchester than Cheshire and Merseyside. Further work is needed to understand what is different about these regions and what factors differentially affect drop out. It is possible that there are differences between these areas in the manner in which treatment is delivered, or differences in client satisfaction with the treatment process and it is important to consider the potential influence of the quality of treatment on drop out rates rather than simply emphasising the role of client characteristics [10]. At the service rather than regional level, previous UK-based work has already demonstrated the effect the service can make on the number of clients retained successfully in treatment for six months [29]. The time people wait to access treatment will also influence retention. Here, a person was deemed to be in continuous treatment if they reappeared in treatment within three weeks of leaving the first agency they were in contact with. Individuals who dropped out of service and did not reappear until more than three weeks had elapsed were recorded as having dropped out so geographical areas whose waiting times were longer than three weeks would have a greater proportion of people reported as dropping out. Unfortunately, no assessment of the impact of waiting times on treatment outcomes can be made in this study.
The only substance significantly associated with outcomes was alcohol, with alcohol users less likely to drop out of treatment than non-alcohol users. Following adjustment for other variables, opiate use was found not be significantly associated with treatment outcomes. The only large-scale longitudinal, prospective cohort study of treatment outcomes in the UK reported that there was no long-term reduction in drinking among patients of drug treatment programmes and authors concluded that poor drinking outcomes required urgent attention [30]. That alcohol use is considered as part of the overall drug profile of people contacting drug treatment is therefore encouraging, particularly in light of the role of alcohol in drug-related deaths [31, 32] and its exacerbation of chronic hepatitis C, currently the most significant infection affecting drug users who inject in the UK [33]. It is possible, however, that this finding is a feature of reporting. The NDTMS records up to three drugs for each person, with those identified as most problematic (used most frequently, associated with greatest health and criminal consequences) reported preferentially. Alcohol is generally perceived to be less problematic than illicit drugs and individuals whose drug profile does not include alcohol may represent drug users who use a larger range of illicit drugs – those with the most severe drug problems. Alcohol use may therefore act as a proxy measure of less severe drug problems. A recent investigation into the characteristics of drug users in contact with structured drug treatment reported that those whose drug profiles included alcohol as a supplementary drug were younger, were less likely to use heroin and were more likely to be referred into treatment via the criminal justice system [34].
Previous research in the North West of England showed that those referred from the criminal justice system were significantly more likely to drop out and less likely to complete treatment drug free than those referred from non-criminal justice sources [18]. Here the route of referral was not significantly associated with treatment drop out in the bivariate analysis. Most community sentences last longer than 12 weeks; the now defunct Drug Treatment and Testing Orders for example (orders that required the offender to attend regularly both court and treatment and provide a urine sample for drug testing) became available nationally in October 2000 and could last between six months and three years [35]. It is therefore conceivable that those referred from the criminal justice system were retained in treatment for 12 weeks due to fear of breaking their order but had poorer long-term outcomes because they lacked the intrinsic motivation for behaviour change. However, the identification of poorer outcomes for criminal justice referrals [18] relates to outcomes recorded between 1998 and 2001/02, while the present study was undertaken after the introduction of retention targets. If drug use is considered a chronic condition defined by relapse and re-presentation [18, 36], the present finding that a high proportion of both criminal justice and non-criminal justice referrals adhere to treatment for at least 12 weeks reflects positively on current policy and practice.
While this study investigated the effects of a variety of variables, the goodness of fit test suggests that other important covariates were missing from the model. This finding hints at the complexity of factors associated with treatment outcomes and confirms suggestions that drop out and retention is an index that capture the impact of many interrelated individual and process measures [7]. In particular, it was not possible to evaluate the effect of treatment modality on treatment retention because an individual's entire treatment episode could be comprised of treatment within different modalities, yet treatment modality is likely to have considerable bearing on treatment outcomes. An examination of the covariate patterns of the goodness of fit test showed discrepancies between the observed and expected values for deprivation and further work looking at the interaction between deprivation and other explanatory variables is needed. However, the reliability of the findings presented here is enhanced by treatment outcome data being unavailable for only 272 (1.6%) individuals. Large-scale prospective cohort studies of drug treatment outcomes are costly and time consuming and the robustness of findings are often questionable due to follow-up losses occurring differentially across comparison groups. The use of well-established monitoring systems provides a cost-effective means by which treatment outcomes can be assessed [18] and while case control studies are also prone to selection bias (with controls not adequately reflecting the exposure history of cases), here controls would have been cases if they had dropped out of treatment before 12 weeks. Recall bias, an accepted weakness of case control studies, did not affect results of this study because data were collected prospectively; exposure data recorded before treatment outcomes were ascertained.
Problems associated with the use of routine data (for example, inconsistencies in the manner in which information is recorded) are somewhat mitigated in this study by using nationally agreed definitions and reporting protocols, standardised coding framework and data validation checks [12]. Furthermore, the large sample size reduces the impact of slight non-systematic variations, increases the study power and reduces the likelihood of a Type II error. However, the study relies totally on self-reported data and the accuracy of such reports cannot be ascertained. The standardisation of the drug treatment and data reporting across England mean that the results from the North West of England can be generalised to other areas although results also show that the effect of factors specific to each region would require further consideration.
