181404 Length of stay as a performance measure in substance abuse treatment

Tuesday, October 28, 2008

Mary Fry, ND , Department of Psychiatry, Oregon Health & Science University, Portland, OR
Bentson McFarland, MD , Department of Psychiatry, Oregon Health and Science University, Portland, OR
There is growing need for quality of care measures in substance abuse treatment. In particular, the National Institute on Drug Abuse recommends at least 90 days of service. Therefore, treatment duration (length of stay) is considered a performance measure. However, length of stay has generally not been included in routinely collected data such as the National Survey on Substance Abuse Treatment Services (NSSATS). On the other hand, the steady state equation “prevalence equals incidence times duration” suggests that length of stay can be estimated from the current client counts and annual admissions data collected by NSSATS. We devised a length of stay estimator using construction data (Alcohol and Drug Services Study) and tested it with validation data (National Treatment Improvement Evaluation Study and Drug Services Research Study). The estimator was: ln (percent lengths of stay greater than 90 days)= 1.046 + (0.620*ln (current client count)) - (0.839*ln (annual admissions)). The estimator was then used to examine NSSATS facilities that reported delivering only non-hospital, non-detoxification long-term (> 30 days) residential treatment in the 2003 through 2006 surveys. We identified approximately 700 facilities that met these criteria each year. There was minimal variation over time with mean percent length of stay greater than 90 days ranging from 59.5% in 2003 to 62.0% in 2005. Although not necessarily unbiased, this preliminary data suggests most long-term residential treatment programs may have lengths of stay that usually exceed the recommended 90 days. State by state analyses adjusting for client severity will be presented.

Learning Objectives:
Step 1: Learn how to work with available national data sets to answer research questions. Step 2: Review secondary data analysis on existing data sets. Step 3: Construct and validate new variables and/or performance measures from pre-existing data sets.

Keywords: Chemical Dependence, Quality of Care

Presenting author's disclosure statement:

Qualified on the content I am responsible for because: I have academic and mentored training in the field of substance abuse assessment and secondary data analysis.
Any relevant financial relationships? No

I agree to comply with the American Public Health Association Conflict of Interest and Commercial Support Guidelines, and to disclose to the participants any off-label or experimental uses of a commercial product or service discussed in my presentation.