Predictors of contact with public service sectors among homeless adults with and without alcohol and other drug disorders.

OBJECTIVE: Homeless persons with alcohol and other drug (AOD) disorders face multiple problems that go beyond their AOD use. As a consequence, they commonly access services in multiple sectors in addition to the AOD treatment system. This study examined the predictors of contact with agencies in the health, mental health, social welfare and criminal justice sectors by AOD status among a probability sample of homeless adults in Houston, Texas. METHOD: Cross-sectional data were collected from a multistage random sample of 797 homeless adults (579 men), age 18 or older, who were living in shelters and on the streets of Houston in 1996. Structured face-to-face interviews provided screening diagnoses for AOD disorders, self-report data on AOD treatment use and candidate predictors of treatment use. Service use was tracked retrospectively through administrative data obtained from 10 federal, state, county and municipal agencies that provide finding for physical and mental health services and AOD treatment, as well as emergency income; we also tracked criminal justice contacts. Logistic regression analyses were stratified by AOD status. RESULTS: Adjusting for eligibility factors, key aspects of need were significant predictors of any utilization among those without an AOD problem, but not for those with an AOD problem. For those with AOD disorders, contact with one sector was not predictive of contact with other sectors. CONCLUSIONS: Our findings indicate that AOD disorders hinder utilization of public sector services by homeless persons. These disorders may be masking need or otherwise acting as a barrier to accessing treatment and support.

How mental health providers spend their time: a survey of 10 Veterans Health Administration mental health services.

BACKGROUND: Allocation of provider time across clinical, administrative, educational, and research activities may influence job satisfaction, productivity, and quality of care, yet we know little about what determines time allocation. AIMS: To investigate factors associated with time allocation, we surveyed all mental health providers in one Veterans Health Administration (VHA) network. We hypothesized that both facility characteristics (academic affiliation, type of organization of services, serving as a hub for treatment of severely mentally ill, facility size) and individual provider characteristics (discipline, length of time in job, having an academic appointment) would influence time allocation. METHODS: Eligible providers were psychiatrists, psychologists, social workers, physician assistants, registered or licensed practical nurses or other providers (psychology technicians, addiction therapists, nursing assistants, rehabilitation, recreational, occupational therapists) who were providing care in mental health services. A brief self-report survey was collected from all eligible providers at ten VHA facilities in late 1998 (N = 997). Data regarding facility characteristics were obtained by site visits and interviews with managers. Multilevel modeling was used to examine factors associated with three dependent variables: (i) total time allocation by activity (clinical, administrative, educational, research); (ii) clinical time allocation by treatment setting (inpatient vs. outpatient); and (iii) clinical time allocation by type of care (mental vs. physical). Licensed Practical Nurses (LPNs) were used as the reference group for all analyses because LPNs were expected to spend the majority of their time on clinical activities. RESULTS: Overall, providers spent most of their time on clinical activities (77%), followed by administrative (11%), and educational (10%). Surprisingly, research activities accounted for only 2% of their time. Multilevel analysis indicated none of the facility-level variables were significant in explaining facility variance in time allocation, but individual characteristics were associated with time allocation. The model for predicting time allocation by inpatient or outpatient settings explained 16-18% of the variance in the dependent variable. In all models, provider discipline and length of time in job played an important role. Having an academic appointment was important only in the model examining total time allocation by activity type. DISCUSSION: These simple models explained only a small amount of variance in the three dependent variables which were intended to capture issues related to time allocation; and the low number of facilities limited our power to examine effects of facility-level factors. Our models performed better in predicting allocation of clinical time to treatment setting and type of treatment than in predicting overall time allocation. Discipline and length of time in job were significant across all models. In contrast, having an academic appointment was associated with allocating significantly less time to clinical activities and more time to administrative activities but not to any significant difference in time spent in either research or education. IMPLICATIONS: While a gold standard of optimal time allocation does not exist, it is striking that research, a stated mission of the VHA, accounted for so little of providers' time. The lack of involvement of clinicians in research has implications for recruitment and retention of high-quality mental health providers in this network and for the education of future providers. Without involvement of clinicians, research conducted in the network by nonclinicians may be less relevant to "real-world" clinical issues. Reductions of funds available to mental health, coupled with increased clinical demands, may have prompted this pattern of time allocation, and these findings attest to the challenges faced by large institutions that are charged with balancing many often seemingly competing missions.