STASH, Vol. 9(2) – Lag time: Barriers to treatment in a national sample of people with substance disorders



Wait time is one of the most commonly cited barriers to substance abuse treatment (Claus, 2002; Festinger, 1995). To date, no national study has collected data about factors that might influence wait time. This week we review a study that identified program and client characteristics associated with longer wait time for entry in a substance abuse treatment program (Andrews, 2013).


  • The researchers used data from the National Treatment Improvement Evaluation Study (Gerstein, 1995), a national longitudinal study of outpatient substance abuse treatment programs serving underserved clients such as minorities, youth, and those in the criminal justice system. The sample was made up of 2,920 clients, racially and ethnically diverse, attending 57 substance abuse treatment programs.
  • The researchers gathered client data (e.g., gender, race, treatment payment source, referral source, severity of substance abuse, HIV status) through computer-assisted, personal interviews. For wait time, respondents answered the question  “How long ago was your name put in for treatment this time?” using 6 categorical response options (i.e., 1 day, 2-6 days, 1-4 weeks, 1-3 months, 4-12 months, more than one year). Researchers collected program characteristics (e.g., financial resources, organizational structure, types of treatment provided) through interviews conducted with program administrators and clinical directors.
  • The researchers identified the proportion of clients who waited over one month to receive substance abuse treatment.
  • Using generalized linear modeling, they examined program characteristics and client characteristics associated with wait time of over one month before entering treatment.


  • 28% of clients reported waiting over one month to enter treatment
  • Odds ratios differed significantly for selected client-specific factors:
    • Clients of African-American ethnicity were 1.40 times more likely, 95% Confidence Interval (CI) [1.04, 1.88], compared to clients of white ethnicity, to report waiting for over a month before entering treatment, < .05
    • Clients who were referred through a criminal justice path were 1.70 times, 95% CI [1.18, 2.43], more likely than clients referred through social services or self-referred clients to report waiting for over a month before entering treatment, < .01
    • Clients with a diagnosis of HIV/AIDS were less likely than clients without a diagnosis of HIV/AIDS to report waiting over a month to enter treatment, (0.38%, 95% CI [ 0.19, 0.77]), < .01.
    • Those with relatively high severity of substance use were less likely than those with low severity to wait more than one month (0.99%, 95% CI [0.98, 1.0]), < .01 1
    • Methadone treatment programs were significantly more likely to admit clients to treatment within one month (3.90%, 95% CI [1.0, 15.17]), < .05. No other program-specific factors were significantly associated with wait time.
  Variable OR CI lower CI upper
Client characteristics African-American versus White 1.40 * 1.04 1.88
versus White
1.25 0.85 1.84
Referred through criminal justice versus self-referral
or social services
1.70 ** 1.18 2.43
through social services versus self-referral or criminal justice
0.94 0.58 1.52
  HIV/AIDS diagnosis versus no diagnosis 0.38 ** 0.19 0.77
health problems versus no physical health problems
1.25 0.98 1.60
  High severity of substance use versus low severity 0.99 ** 0.98 1.00
Program characteristics Methadone
program versus other type of program
3.90 * 1.00 15.17
  High program revenue versus low program revenue 0.93 0.33 2.81

Figure. Odds ratios (95% confidence intervals) for selected associations between client and program-specific factors and waiting more than one month before substance use treatment. Adapted from Andrews, 2013.


  • The data were collected in 1992-1994 and therefore do not reflect and more recent national trends in drug use behavior and the availability of outpatient treatment.
  • As with any measure based on retrospective self-report, the wait time data could be inaccurate.
  • The response option for treatment wait times might be problematic, particularly the options “1-4 weeks” and “1-3 months”, which appear to overlap. This might further limit the reliability of wait time data.
  • The results of the study only pertain to a limited sample—people who eventually enter treatment despite a longer waiting time—so it is impossible to account for selective attrition.


This study analyzed factors associated with long wait time before entering substance abuse treatment. The results indicate that some treatment-seekers involuntarily wait longer than others to enter treatment for substance abuse.

The researchers speculate that HIV positive status and high addiction severity might have given clients priority entry to treatment; it is also possible, however, that some people with these characteristics dropped off wait lists more quickly, so that the pool of those who stayed and entered treatment was made up of people who experienced shorter wait times. The researchers further speculate that people referred through criminal justice were more motivated to enter treatment despite longer wait times because they were under supervision. They note also, that prior research indicates that African-Americans are more likely than Whites to report long wait lists as barriers to alcohol and substance abuse treatment (Grant, 1997).  Although the reasons for this are unclear, this corroborates previous findings that disparities exist. It is likely that longer wait times are more common for populations considered to be socially or financially disadvantaged, and that this exists in a constellation of factors such as ability to pay and location of outpatient treatment.

For future research looking at wait time and program admission, it would be helpful to examine a wider sample of people—this means finding means of gathering data from people who did not enter programs as well as those who persevered. In light of the changes to access to treatment resulting from the Affordable Care Act (ACA), these investigations will be more important than ever.

-Kat Belkin

What do you think? Please use the comment link below to provide feedback on this article.


Andrews, C. M., Shin, H., Marsh, J.C., Cao, D. (2013). Client and program characteristics associated with wait time to substance abuse entry. American Journal of Drug and Alcohol Abuse, 39(1), 61-68.

Claus, R. E., Kindleberger, L.R. . (2002). Engaging substance abusers after centralized assessment: predictors of treatment entry and dropout. Journal of Psychoactive Drugs, 34(1), 25-31.

Festinger, D. S., Lamb, R.J., Kountz, M.R., Kirby, K.C., Marlowe, D. (1995). Pretreatment dropout as a function of treatment delay and client variables. Addictive Behaviors, 20(1), 111-115.

Gerstein, D. R., Atta, A.R., Ingels, J.S., Johnson, R.A., Rasinski, K.A., Schildlaus, S., Talley, K., Jordan, K., Phillips, D.B., Anderson, D.W., Condelli, W.G., Collins, J.S. (1995). NTIES: National Treatment Improvement Evaluation Study. Rockville, Maryland: Center for Substance Abuse Treatment.

Grant, B.F. (1997). Barriers to alcoholism treatment: reasons for not seeking treatment in a general population study. Journal of Studies on Alcohol and Drugs, 58, 365-371.


[1] The researchers operationalized severity of substance use as the number of days of use of one of the five most common drugs in the past month.


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