Impact of adaptive functioning on readmission to alcohol detoxification among Alaska Native People

Abstract

Background: This study examined predictors associated with readmission to detoxification in a sample of adult Alaska Native patients admitted to inpatient alcohol detoxification. Even though Alaska Native people diagnosed with alcoholism have been identified as frequent utilizers of the health care system and at elevated risk of death, little is known about factors associated with readmission to detoxification for this group.

Methods: We sought to predict readmission using a retrospective cohort study. The sample included 383 adult Alaska Native patients admitted to an inpatient detoxification unit and diagnosed with alcohol withdrawal during 2006 and 2007. Cox proportional hazard modeling was used to estimate unadjusted and adjusted associations with time to readmission within one year.

Results: Forty-two percent of the patients were readmitted within one year. Global Assessment Functioning (GAF; Axis V in the multi-axial diagnostic system of the Diagnostic and Statistical Manual of Mental Disorders [DSM IV]) score measured at the time of intake was associated with readmission. A one point increase in the GAF score (HR=.96, 95% CL=.94, .99, P=.002) was associated with a four percent decrease in readmission. The results also indicated that the GAF mediated the relationship between readmission and: employment and housing status.

Conclusions: The GAF measures both illness severity and adaptive functioning, is part of standard behavioral health assessments, and is easy to score. Readmission rates potentially could be decreased by creating clinical protocols that account for differences in adaptive functioning and illness severity during detoxification treatment and aftercare.

Keywords: Alaska Native People; American Indian; Detoxification; Readmission; Substance abuse treatment.

Fig. 1

Conceptual model of readmission to detoxification. The conceptual model used to guide the study of readmission to detoxification has six distinct components. The Health Care System component within the dashed box was not studied as data were not available to measure these constructs. Similarly, those elements with an asterisk (*) were not studied due to unavailability of data. Insurance (+) was not studied as these services were funded by the Indian Health Service without regard to insurance status.

Fig. 2

GAF mediating the effect of unstable housing and employment on readmission to detoxification. Fig. 2 depicts the GAF score mediating the effect of unstable housing and employment on readmission. This figure graphically shows the relationship between unstable housing, employment, and the GAF score assigned by the clinician, which in turn is related to readmission. Unstable housing and employment (employed versus not employed) are bivariately associated with readmission (p-values ≤.01). These relationships become non-significant when the GAF score is included in the model. Unstable housing and employment are also associated with the GAF score (p-values ≤.001), which supports the GAF score as a mediator. Cox proportional hazard modeling was used to determine coefficients for the relationships between readmission with unstable housing and employment. Linear regression was used to determine the coefficients for the relationships between the GAF with unstable housing and employment.