While there is great concern about the impact of illicit drug use in New York City, particularly use of heroin and prescription opioids, since the 1970s there have been few rigorous efforts to estimate its prevalence [1]. In recent decades we have seen significant changes in the culture and patterns of drug use, including greater availability of potent prescription opioids and decreasing rates of intravenous drug use. What persists is the disproportionate burden of morbidity and mortality borne by opioid users, including chronic infectious diseases (hepatitis C, HIV/AIDS) and premature death due to overdose and accidents [2-7]. Service providers and government health authorities are challenged to provide appropriate drug services in the absence of basic knowledge about the size and characteristics of their target population.

Three notable developments in recent years make this an opportune time to revisit estimates of the prevalence of opioid use. First, increasing rates of prescription opioid misuse and related overdose deaths indicate a shift in drug use patterns, demographics, and potential harms of use [8-11]. Prescription opioid users may be poorly reached by traditional drug treatment services, although treatment admissions in New York State do display a steady increase from this group over the past 15 years. Historically, research on opioid use has largely focused on heroin-using populations, with much less known about the treatment needs and access to care issues experienced by prescription opioid users [12].

A second event is the approval in 2002 of buprenorphine for treatment of opioid dependence, which offers an exceptional opportunity for expansion of evidence-based treatment. Buprenorphine can be prescribed by physicians in general practice settings, and thus offers the possibility of dramatically expanding access to treatment, but is not currently being employed to its fullest potential [13,14]. A related third event is a newly increased emphasis on integrating addiction treatment into non-specialty medical settings such as primary care clinics. This is exemplified in the current strategic plan issued by the federal Office of National Drug Control Policy, which emphasizes early identification of substance use disorders and expansion of treatment through mainstream healthcare settings [15].

Population surveys, primarily the National Survey on Drug Use and Health (NSDUH), are relied upon to assess the prevalence of illicit drug use, but are believed to severely underestimate ‘hardcore’ drug use, including heroin and injection drug use [16,17]. The survey does not include individuals who are incarcerated, institutionalized, or street homeless; all populations with disproportionately high prevalence of drug use [18]. It may also underestimate drug use among those who do participate, due to underreporting of stigmatized and illicit behavior by respondents, despite efforts to counteract this with recent changes in survey methodology [19]. As a result of these constraints, the NSDUH is limited in its ability to inform intelligent program design for opioid users.

Other data collected for administrative purposes and public health surveillance contains information on the health, demographic, and geographic characteristics of opioid users, and captures populations excluded from the NSDUH sample. While no single data source provides a comprehensive picture of illicit opioid use, each provides information on a subset of users who have developed social, psychological or physical problems as a consequence of their use. Yet these data sources have not previously been systematically applied to characterize the prevalence of opioid use. We analyzed these data with a goal of informing potential changes in drug services that could accommodate those left out of the current treatment system.

This descriptive analysis of the prevalence of opioid use in New York City utilizes multiple data sources, including administrative datasets recording hospital inpatient and emergency room admissions, treatment and detoxification services utilization, prescription records, overdose deaths, and correctional health statistics, as well as survey data from the NSDUH. Using data from the most recent year (2006) for which complete data were available for all sources, we analyzed these datasets in combination to characterize the population of opioid users who would be candidates for drug services. We then compared them to the population entering drug treatment programs to estimate the extent of the untreated opioid user population.

These data sources identified 126,681 cases of opioid use among New York City residents in 2006 (Table 2). Based on our case definitions, all of these opioid users have attributes consistent with opioid abuse, dependence, or poisoning, and would thus qualify for services to address their substance use [20,21].

Opioid users were categorized into three subpopulations, of which the general population (G) was the largest, with a midpoint estimate of 69,463 individuals. The majority were identified from the NSDUH survey. The 607 unintentional opioid poisoning overdose decedents represented 0.9 % of this subpopulation. Entrants to drug services (D) were the second largest subpopulation, with an estimated 28,378 individuals. Ten percent (2,880) of this group received a prescription for buprenorphine. Medical service recipients (M) were the smallest of our three subpopulations, but still represented an estimated 17,618 opioid users.

Adding the midpoint estimations for our three subpopulations produced an expansive estimate of 115,459 opioid users (Figure 1). The restrictive estimate, which assumed that all opioid users were represented in the general population estimate, lowered the estimation to 69,463. An estimated 21,600 entered drug treatment, either by enrolling in a substance abuse treatment program or initiating treatment with buprenorphine.

Characteristics of opioid users identified in the drug services versus hospital-based medical services data are shown in Table 3. Opioid users had a mean age of 40 years or greater, with hospital inpatients being considerably older. The majority were male, though there was greater representation of females in the hospitalized population than in drug treatment programs. The Bronx was the county with both the greatest number and proportion of opioid users. Bronx residents were also well represented in the drug services population, with a rate of 814 admissions per 100,000 adults.

We found that opioid users had high rates of acute care hospital utilization. Overall, they represented 4.1 % of all individuals hospitalized and 0.7 % of all individuals admitted to the emergency room in 2006. In total, opioid users had 44,154 hospitalizations, 20,959 (47 %) of which were for medical reasons (i.e. not for detoxification or rehabilitation). They incurred an additional 10,053 emergency room visits that did not result in hospitalization (data not shown).

Our analysis sought to provide a rigorous estimation of the opioid user population by grounding prevalence estimates in a range of datasets that are not often applied to this question. Although even this diversified approach may not capture the full scope of opioid use, it does allow construction of a more comprehensive picture of opioid users in New York City, including prevalence, service utilization, and demographic characteristics.

There is clearly a need for expanded drug services for opioid users in New York City. Even using our most restrictive estimations, there were over 69,000 opioid users residing in New York City in 2006. While over 21,000 individual opioid users did initiate treatment, this represents a small fraction of the identified opioid user population. Moreover, because close to half of treatment admissions are mandated each year in New York City, including one-third by criminal justice authorities (i.e. courts, probation, parole), one can assume a considerable portion of this fraction did not initiate treatment voluntarily.

The current drug treatment system alone cannot be relied upon to accommodate the needs of this population. Though maintenance treatment with an opioid agonist medication, (methadone or buprenorphine), is the best evidence-based treatment strategy for opioid dependence [29], not all of the opioid users identified here would necessarily qualify for, or accept, medication assisted treatment. Furthermore, accommodating these individuals within the existing substance abuse treatment system would involve doubling the capacity of New York City opiate agonist treatment programs, which currently serve approximately 37,500 patients [14]. Buprenorphine treatment in general medical settings provides an alternative means of treatment expansion, but slow uptake among physicians has thus far limited its reach.

While many opioid users would undoubtedly benefit from traditional drug treatment services, the availability of treatment slots is not the only barrier to engaging them in effective evidence-based care. Although these data sources largely capture the negative sequelae of opioid use (health problems, incarceration) that are more prominent among those with active substance use disorders, even non-dependent and early-stage users are vulnerable to drug-related problems, and may also have been identified here. Similarly, these data may include opioid users that were already enrolled in drug treatment, but nonetheless experienced problems related to drug use. Some opioid users could be served by less intensive treatment interventions, such as brief interventions or pharmacotherapy, provided in healthcare or community settings that are not traditionally considered part of the drug treatment system [30,31]. Many would benefit from harm reduction approaches to prevent the negative consequences of opioid use. A greater diversity, as well as a greater number, of treatment providers would thus be needed to deliver care to the full range of opioid users identified here. Public health authorities could apply this data to assess and orient the structural configuration of existing treatment services, and to expand engagement, access points, service types and modalities, and venues to better reach the sizeable under-served opioid user population.

Our approach does have a number of limitations. Most notably, we were unable to match individual opioid users across data sources. Capture-recapture analysis, which relies on identifying unique individuals across multiple datasets, can potentially improve the accuracy of prevalence estimation, and has been applied in municipalities outside the US to estimate populations of illicit drug users [32-35]. We chose not to use this approach because accessing fully identified individual-level data from multiple data sources was not feasible at the time of this analysis. Similarly, although it would be desirable to perform a validity check of the final estimates using an alternate method, this was beyond the scope of the present study. However, our findings do have face validity in light of prior estimates of the New York City opioid user population [1,13].

Our estimation of the medical services population relied on hospital data from inpatient and emergency room presentations, and did not capture individuals who utilized only ambulatory care services. Analysis of insurance claims data could contribute that information, but was not accessible for this analysis. Our data also fail to capture services provided within the Veteran’s Administration (VA) system.

There are several limitations inherent to the datasets themselves. Substance use is often not identified in medical settings [36-39] and substance use and other mental health diagnoses are poorly captured by medical administrative data [40-44]. Additionally, none of the datasets that rely on service utilization (drug treatment, detoxification, or hospital inpatient services) capture those with less problematic opioid use, who have not experienced the health and social sequelae of addiction that often drive users to seek care. As a result, we relied on the NSDUH for the general population estimation of opioid use, despite its known limitations [16,17]. Finally, our analysis is restricted to a single year-long period (2006), and thus does not capture trends in opioid use over time. This may be a particularly significant limitation with respect to prescription opioid use, which has been rising rapidly nationwide [9-11].

Despite these limitations, our study contributes to the understanding of the prevalence of opioid use in New York City by rigorously defining the dimensions and characteristics of the opioid user population. More sophisticated epidemiologic analyses of these multiple datasets, including capture-recapture and multiplier methods, could provide a more accurate estimate of the hidden population of opioid users who do not appear in any existing data sources. Our goal here was to take a first step toward that end by defining the number and range of individuals who met our case definition of problematic opioid use in health-related datasets.

The health and social impact of opioid use is well recognized, but drug services have yet to adapt and expand to meet the needs of New York City’s sizeable out of treatment opioid user population. By providing a more comprehensive view of the opioid user population, our analysis could inform policy changes at the municipal and state level that would foster a broader spectrum of services for opioid users, and greater diversity of settings in which drug services are provided.

Efforts to reach this population could include provision of treatment and early intervention outside of specialized drug treatment programs, through greater involvement of the mainstream health care system. Though a minority of opioid users entered drug treatment in 2006, our analysis reveals that their contact with other aspects of the health system is routine. Many are utilizing hospital-based care, and many more are likely seen in ambulatory care settings, visits to which were not captured here. This presents an opportunity to expand both the scope and reach of drug services. Office-based treatment with buprenorphine, for example, offers the opportunity to reach individuals who do not typically seek care at substance abuse treatment programs. Greater adoption of screening and brief intervention (SBI) models is another potential avenue for expanding services to the large substance using population that is not actively seeking drug treatment.

These changes will occur only with strong public health leadership and targeted research that informs and supports changes within the complex systems of health care and drug treatment services. Buprenorphine’s potential has yet to be fully realized, in New York City and throughout the U.S., due to practitioner- and systems-level barriers [45-47]. There are important questions about how best to implement SBI, and its effectiveness for individuals with opioid abuse or dependence, but research can provide better models for identifying and engaging this population in health care settings [48]. Successful early intervention with these users could potentially prevent development of the severe sequelae of untreated opioid use disorders, including the health and social consequences that are starkly revealed here as statistics on hospitalizations, incarcerations, and overdose deaths.

Health surveys and datasets

CDS, Client Data System; DAWN, Drug Abuse Warning Network; ICD-9, International Classification of Infectious Diseases 9th revision; NSDUH, National Survey on Drug Use and Health; SPARCS, Statewide Planning and Research Cooperative System; NYC DOHMH, New York City Department of Health and Mental Hygiene; NYS DOH New, York State Department of Health; NYS OASAS, New York State Office of Alcoholism and Substance Abuse Services.

Agencies and Organizations

CDS, Client Data System; DAWN, Drug Abuse Warning Network; ICD-9, International Classification of Infectious Diseases 9th revision; NSDUH, National Survey on Drug Use and Health; SPARCS, Statewide Planning and Research Cooperative System; NYC DOHMH, New York City Department of Health and Mental Hygiene; NYS DOH New, York State Department of Health; NYS OASAS, New York State Office of Alcoholism and Substance Abuse Services.

The authors have no conflicts of interest to disclose.

JM, DH and MG conceived of the study. JM directed the study and led the writing and analysis. DP, SW and SS contributed to the analyses. All authors advised on the analysis and contributed to the writing.

This study represents a collaborative effort between the NYU School of Medicine and the New York City Department of Health and Mental Hygiene, Bureau of Alcohol and Drug Use Prevention, Care and Treatment. At the time of writing, Daliah Heller, PhD, MPH was Assistant Commissioner of the Bureau, which has primary responsibility to develop and implement programs and policies to prevent the adverse health consequences of alcohol and drug use in New York City. The Bureau achieves its mission through developing and promoting policies, conducting and disseminating the results of epidemiologic analyses, promoting best practices in primary care and substance use service settings, overseeing contracted syringe exchange and substance use treatment services, and coordinating services across a wide range of governmental and community stakeholders. Denise Paone, EdD, BSN is the Bureau’s Director of Research and Program Development and Sharmila Shah, MD, MPH is Research Scientist.

Dr. McNeely received support from NIH/NIDA (K23DA030395), NIH/NYU CTSI (KL2RR029891), and Cooperative Agreement Number T01 CD000146 from the Centers for Disease Control and Prevention (CDC). The contents of this paper are solely the responsibility of the authors and do not necessarily represent the official views of the New York City Department of Health and Mental Hygiene, the Centers for Disease Control, the National Institute on Drug Abuse or the National Institutes of Health.

The pre-publication history for this paper can be accessed here:

http://www.biomedcentral.com/1471-2458/12/443/prepub