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Psychosomatic Medicine 65:931-937 (2003)
© 2003 American Psychosomatic Society

ORIGINAL ARTICLES

Disease Management for Depression and At-Risk Drinking Via Telephone in an Older Population of Veterans

David W. Oslin, MD, Steven Sayers, PhD, Jennifer Ross, BA, Vince Kane, MSW, Thomas Ten Have, PhD, Joseph Conigliaro, MD, MPH and Jack Cornelius, MD

From Section of Geriatric Psychiatry (D.W.O., J.R.), Department of Psychiatry, University of Pennsylvania, Philadelphia, PA; Center for the Study of Addictions (D.W.O., S.S.), Department of Psychiatry, University of Pennsylvania, Philadelphia, PA; Philadelphia VA Medical Center and VISN 4 MIRECC (D.W.O., S.S., V.K.); Department of Epidemiology and Biostatistics (T.T.H.), University of Pennsylvania, Philadelphia, Pennsylvania; and University of Pittsburgh School of Medicine (J.C., J.C.), the Pittsburgh VAMC, and VISN 4 MIRECC.

Address correspondence and reprint requests to David Oslin, MD, University of Pennsylvania, 3535 Market Street, Room 3002, Philadelphia, PA 19104. E-mail: oslin{at}mail.med.upenn.edu


   ABSTRACT
TOP
 ABSTRACT
INTRODUCTION
 MATERIALS AND METHODS
 RESULTS
 DISCUSSION
 ACKNOWLEDGMENTS
 REFERENCES
 
OBJECTIVES: The purpose of this study was to explore the efficacy in a primary care setting of a telephone-based disease management program for the acute management of depression and/or at-risk drinking.

MATERIALS AND METHODS: Veterans (N= 97) with depression and/or at-risk drinking were identified by systematic screening and assessment. Eligible subjects received either telephone disease management (TDM) program or usual care based on random assignment of their clinician. The TDM program consisted of regular contacts with each subject by a behavioral health specialist (BHS) to assist in assessment, education, support, and treatment planning. Symptomatic outcomes were assessed at 4 months.

RESULTS: Overall response rates favored those assigned to TDM compared with those assigned to usual care (39.1% responded vs. 17.6%, p= 0.022). Response rates within the separate diagnostic groups also favored TDM, but this was only significant for depressive disorders.

CONCLUSIONS: Although the sample size was modest and the sample was limited to veterans, findings strongly suggest that a telephone-based disease management program can improve outcomes for patients with a behavioral health problem. Findings also suggest that a health specialist can focus and manage patients with different diagnoses, thus expanding the role beyond just depression care. TDM may be a viable, low-cost, model for primary care clinicians to deliver manual guideline-adherent behavioral health care, especially in a VA clinical setting.

Key Words: telephone, • depression, • at-risk drinking, • primary care.

Abbreviations: TDM = telephone disease management;; PCP = primary care physician;; CESD = Center for Epidemiological Studies depression scale;; BOMC = Brief Orientation Memory Concentration test;; AHRQ = Agency for Healthcare Research and Quality;; VA = Department of Veterans Affairs;; BHS = behavioral health specialist;; HDRS = Hamilton Depression Rating scale;; ADS = Alcohol Dependence Scale;; SSRI = serotonin selective reuptake inhibitor.


   INTRODUCTION
TOP
 ABSTRACT
 INTRODUCTION
MATERIALS AND METHODS
 RESULTS
 DISCUSSION
 ACKNOWLEDGMENTS
 REFERENCES
 
Untreated or undertreated depression and alcoholism continue to be major public health concerns that lead to significant personal morbidity and significant societal burden in lost days of employment, increased utilization of medical services, and increased mortality (1–5). Despite advances in the treatment of depression and alcoholism, there remains a gap between the efficacy of treatments demonstrated in randomized clinical trials and outcomes in primary care clinics. Specifically, depression or alcohol abuse/dependence are often not diagnosed or treated in primary patients (6). Because both of these disorders are highly prevalent and disabling, it has been recommended that screening becomes a part of routine clinical practice. However, screening and identification, while necessary, are not sufficient in increasing access to treatment. Even when an intervention is initiated in primary care, few patients receive an adequate course of treatment and only one-quarter to one-third achieve full resolution of their symptoms, less than the usual placebo response rate observed in typical clinical trials conducted in the psychiatric sector (7–10). Moreover, several studies have demonstrated that while screening or clinical reminders facilitate identification of depression, there is limited impact on improving care (11,12). It is also becoming increasingly apparent that educating primary care physicians is not the sole answer to improving treatment outcomes. Gallo and colleagues have demonstrated that family practice physicians and internists have interest in treating depression and are knowledgeable about the diagnosis and treatment strategies (13,14). However, physicians report limited resources for conducting frequent monitoring or to overcome patient barriers to successful treatment (eg, lack of acceptance of treatment, low adherence).

To address the problem of undertreatment, a number of initiatives have attempted to increase the detection of depression and alcohol abuse and to increase rates of guideline-adherent care. Recently, clinical trials have focused on delivering guideline-adherent care through the development of collaborative care models. In these models, positive effects have been observed in interventions that included frequent patient contact with ongoing monitoring of treatment adherence and assessment of symptomatic outcomes with feedback and modification of treatment as needed (15–17). The value of disease management strategies appears to lie in engaging patients who did not seek out treatment on their own and facilitating guideline adherence. While this model seems to bring significant benefits relative to usual care, the model is practical only for larger group practices that generate a sufficient caseload to employ a health specialist, and not for smaller practices. Moreover, it is not clear that this face-to-face model will overcome existing logistical issues that patients face in getting to their primary care clinic, including transportation, work schedules, and finances. The logistic issues are particularly relevant in behavioral health care in which frequent clinical visits for monitoring and therapeutic contact are likely to have significant benefits in treating patients.

To address the limited access to behavioral health care for smaller clinics, practitioners in rural settings, or when logistic issues prevent frequent clinical visits, attention has turned to delivering specialized care by way of telephone assessments and management. The use of telephone disease management (TDM) increases the flexibility of scheduling visits and allows for cost sharing between several clinics for a health specialist. A small number of studies have examined the use of this method for the treatment of depression but not within the Department of Veterans Affairs (VA) care system. The largest trial by Tutty and colleagues demonstrated that those patients identified by a primary care physician and then randomly assigned to TDM had twice the chance of receiving a moderate dose of an antidepressant and twice the chance of having a 50% reduction in depressive symptoms compared with usual care (18). Several other smaller studies also demonstrate the efficacy of TDM for depression in primary care settings (19–24). Distance medicine is not unique to behavioral health and indeed has been demonstrated to be effective in preventive care, cardiac care, diabetes care, and with increasing adherence to medications and appointments (25).

The purpose of this study was to demonstrate the efficacy of TDM for depression and/or at-risk drinking for veterans and to explore the use of this model in medical subspecialty care as well as primary care. We choose to focus on the delivery of both alcohol and depression disease management as demonstrating efficacy from having a single health specialist capable of addressing multiple problems may improve the sustainability of the model rather than needing a different health specialist trained each problem. To our knowledge, this is the first study to explore the use of a single health specialist in delivering multiple disease-management algorithms. This study was conducted solely in an urban VA medical center which may affect the generalizability of the findings. Previous research has demonstrated higher than expected psychiatric illness in VA primary care settings which may enhance the feasibility of implementing TDM (26, 27).


   MATERIALS AND METHODS
TOP
 ABSTRACT
 INTRODUCTION
 MATERIALS AND METHODS
RESULTS
 DISCUSSION
 ACKNOWLEDGMENTS
 REFERENCES
 
Screening Procedures
During the time between September 2000 and October 2002, all patients age 18 and older who had an appointment with one of two primary care group practices and two subspecialty care practices (cardiology and rheumatology) at the Philadelphia Veteran Affairs Medical Center (PVAMC) were eligible for participation. In total, 37 clinicians (10 from primary care, 23 from cardiology, and 4 from rheumatology) were represented in the practices. Each week during the study, a random subset of patients was selected from each practice’s appointment list (a total of approximately 30 patients/wk with greater sampling of primary care patients). Patients were sent a letter from their physician informing them about the study and the screening procedures. Subjects were then contacted by the research staff, via telephone, to screen for depression, suicide risk, and at-risk alcohol use. Consent for participation was obtained at each stage of the study in accordance with the PVAMC Institutional Review Board regulations. Written informed consent was obtained before initiation of treatment.

Screening was then conducted using the following instruments: the Center for Epidemiological Studies depression scale (CESD) (28), the Brief Orientation Memory Concentration (BOMC) test (29) in those older than age 49, two screening questions for suicidal ideation modified from the PRIMEMD that identified passive suicidal ideation or death ideation and suicidal ideation (30), quantity and frequency of alcohol use, and demographics. Those who screened positive on the CESD (total score >15), indicated suicidal/death ideation or who reported consumption of eight or more drinks in the previous week were invited to receive a further baseline evaluation for potential inclusion in the randomized trial. Those patients already in mental health or substance abuse care for the condition that they screened positively for and those with a BOMC more than 16 were excluded from further assessment.

Baseline Assessment, Eligibility, and Follow-up Assessments
The baseline assessment instruments completed included the MINI modules for depression and anxiety disorders (31), the CAGE questionnaire modified to ask about problems in the past year (32), a scripted version of the Hamilton Rating scale for Depression—24 items (HDRS) (33), a medication list, the Cornell Services Index (34), the Alcohol Dependence Scale (ADS) (35), and the 7-day timeline follow-back for alcohol use (36). Follow-up assessments were conducted at 4 months using the same assessment battery using raters not involved in the subjects’ clinical care.

The following inclusion/exclusion criteria were intended to allow entry of most patients with behavioral health problems and to ensure that the study sample was representative of the overall primary and medical care population. Subjects had to be age 18 years or older, either male or female, and demonstrate signs and symptoms of a depressive disorder (major depression, dysthymia, or persistent minor depression). Major depression and dysthymia were determined using DSM-IV diagnostic criteria with "inclusive strategies" for the evaluation of symptoms in patients with medical illness using the MINI psychiatric interview. Persistent minor depression is defined as having DSM provisional criteria for minor depression for a minimum of 4 weeks. Inclusive strategies involve counting symptoms regardless of etiology. Subjects had to meet criteria for at-risk drinking as defined by drinking more than 21 standard drinks per week (14 for women or those older than age 65), or binge drinking (>3 binges in 3 mo), or positive CAGE responses combined with any drinking. Exclusion criteria included active suicidal ideation, regular use of illicit substances, current hallucinations and delusions or a history of a primary psychotic disorder, a history of mania or hypomania, and having a high potential for alcohol withdrawal symptoms as indicated by a score more than 14 on the Alcohol Dependence Scale (ADS).

Randomization
For all patients completing the baseline assessment, a written summary, similar to a laboratory report, was sent to the primary clinician to assist in the delivery of care. Before the initiation of the project, we provided information and education to the clinicians about the symptoms and morbidity associated with depression and at-risk drinking, their recognition, and treatment after VA and Agency for Healthcare Research and Quality (AHRQ) guidelines. Participating clinicians were randomly assigned either to the usual care arm or to the TDM arm. Randomization by physician was chosen to reduce possible contamination by crossover effects in which the co-localization of the two interventions could lead to changes in usual care. This could be achieved because subjects were randomly selected and screened rather than relying on referrals that could bias patient selection. For those patients receiving the usual care intervention, the physicians administered further evaluations and treatment as they saw fit.

TDM Treatment
For those assigned to TDM, a BHS maintained regularly scheduled telephone contact to develop a treatment plan, to monitor treatment effectiveness and adverse effects, assess and encourage treatment adherence, and offer support and education. The calls were scheduled at 1, 3, 6, 9, 12, 18, and 24 weeks after the initial clinical assessment. The content and focus of the contacts were manualized for both depression and at-risk drinking. The depression manual followed closely the disease management approach developed by Mulsant and colleagues (37) and the at-risk drinking manual was a telephone adaptation of brief alcohol intervention developed by Barry, Oslin, and Blow (38). As the brief alcohol intervention requires completion of a workbook, this was performed by the BHS and then mailed to patients. In patients with co-occurring problems, both interventions were delivered simultaneously. The initial focus of the interaction between the patients and BHS was to address issues of stigma and focused on engaging the patient in treatment. As such, each treatment manual devotes a significant proportion of time on engagement as well as assessment. In cases in which an antidepressant was clinically indicated, patients were typically started on a serotonin selective reuptake inhibitor (SSRI). Those intolerant to an SSRI or who did not respond were treated with second-line agents such as bupropion or venlafaxine, depending on past treatment exposure and adverse effects. It is important to note that the BHS did not simply take over the care of the patient but acted as a physician extender. The primary clinician maintained final decision-making authority for each patient. In addition to behavioral health-specific recommendations, the BHS assessed for medical complications of depression and alcohol use and may make recommendations for further medical management to assist in differential diagnosis or management. For instance, the BHS completed chart reviews to assure that those with depression had a thyroid screen in the past year and those with identified liver damage had been evaluated for hepatitis C infection.

Each clinical contact lasted approximately 45 minutes, with the first 30 minutes focused on evaluation of symptoms and adherence to the treatment plan. The remaining time was used to motivate patients to adhere to the treatment plan and to provide education about the illness or treatments. In addition to the training and the manuals, the BHSs met weekly with a psychiatrist to review each treatment plan. For this study, the BHSs were all registered nurses (N= 4) with at least 1 year of previous experience in clinical settings serving patients with behavioral health problems. None of the nursing staff had previous work experience in a primary care setting. Training and supervision focused on the clinical skills and pharmacological knowledge needed by the BHS to work and function effectively in a "medication-clinic" model.

Depression-Specific Care
The treatment plan included both pharmacological management of depression and psychosocial support. Following the VA and AHRQ treatment guidelines, particular attention was placed on assessments at 6 weeks, with recommendations to reevaluate the treatment plan for those who are unchanged or worse, to intensify or enhance treatment for those with partial responses (defined as more than a 30% decrease in depressive symptoms without meeting remission criteria [HDRS score <10]), and to continue treatment for those with significant improvements. Attention also focused on assessments at 12 weeks with recommendations for reevaluating treatment for those with residual symptoms and to continue treatment for those in remission. In addition to the training and the manuals, the BHSs met weekly with a psychiatrist to review each treatment plan.

At-Risk Drinking Algorithm
The BHS monitored outcomes by questioning the patient about quantity and frequency of use. The BHS used motivational skills in a nonjudgmental way to review the individual goals of the patient and the risks and benefits of drinking using a workbook that was mailed to the patient after each visit. A psychiatrist was available to the BHS for consultation and supervision. For patients who had unfavorable outcomes at the end of 4 months, a recommendation for referral to the Addiction Recovery Unit was made to the patient and physician.

Usual Care
Before initiation of this project, the usual procedures for behavioral health care in the participating clinics were to provide yearly screening for depression and/or alcohol problems. Those patients in need of care would be referred to an outpatient behavioral health clinic within the same building, formulate a treatment plan to be performed in primary care, or seek consultation from behavioral health. The majority of milder cases of depression are assumed to be treated by the primary care staff with more severe cases being referred to behavioral health. Baseline rates of referral and acceptance are unknown. Rather than rely solely on usual care practice, we chose to educate providers on existing treatment guidelines, screening patients attending clinic, provide diagnostic information to the clinician, and make general suggestions for treatment including encouraging clinicians to refer patients to the behavioral health clinic.

Statistical Analysis
Statistical analyses were performed with SPSS Version 11.0 for Windows. Descriptive analyses included means and standard deviations for continuous variables and frequencies for categorical variables. Unadjusted between-group comparisons of continuous and categorical baseline and follow-up outcome variables were performed using Student’s t tests and Chi square tests, respectively.

Response to treatment was defined as a dichotomous outcome based on remission of depression (HDRS score <=10) or at least a 50% reduction in depressive symptoms and/or reduction in drinking below study-entry criteria (more than 21 standard drinks per week [14 for women or those older than age 65] or binge drinking >3 binges in 3 mo). Subjects who withdrew from the study were considered in the primary outcome analysis as having a poor treatment outcome. A more complete analysis demonstrated similar findings but is not presented to simplify the presentation. In addition to examining an overall effect of TDM care, subjects in each of the diagnostic groups were analyzed separately. Subjects meeting more than one diagnostic criterion (eg, those with depression and alcohol abuse) were included in both the analyses relating to depression and the analyses relating to alcohol abuse; however, they were counted only once in the overall analyses.

Alternative outcomes included reductions in symptoms using the continuous HDRS and CESD scales. Regression analyses included race in each model and baseline depression severity in models examining depression severity as an outcome. Examination of continuous measures of drinking were not attempted because of the limited number of subjects enrolled for binge drinking versus heavy drinking and the lack of an overall continuous measure of drinking that did not have a significantly skewed distribution. The means and standard deviations are presented but not analyzed. Treatment access was defined as completing at least one specialty mental health/substance abuse contact. For those assigned to TDM, this included at least one telephone session with the BHS. The telephone session had to include elements of treatment and not just scheduling a visit.


   RESULTS
TOP
 ABSTRACT
 INTRODUCTION
 MATERIALS AND METHODS
 RESULTS
DISCUSSION
 ACKNOWLEDGMENTS
 REFERENCES
 
During the study period, 2489 patients were randomly selected for screening. Of those selected, 838 (33.7%) consented and were able to complete the screening process. The remaining patients refused participation (N= 749; 30.1%), were unable to be contacted during the screening period (N= 739; 29.7%), were too medically ill to answer questions (N= 51; 2.0%), were severely cognitively impaired (N= 38; 1.6%), were hearing-impaired (N= 9; 0.4%), or were ineligible for other reasons (N= 65; 2.6%). While there were no overall differences in the rates of being screened between older and younger veterans ({chi}2 = 1.83; 1 df; p= 0.176), there were differences in reasons for nonparticipation between older (65 years or older) and younger participants. Younger participants were more likely to be unavailable by telephone (55.7% vs. 33.0%) and older participants more likely to refuse participation (53.1% vs. 38.1%) or to be ineligible for screening (13.8% vs. 6.2%) ({chi}2 = 91.90; 1 df; p< 0.001).

Of the 838 subjects screened, 45.3% were positive for depression, 12.1% for drinking, and 16.3% for suicidal/death ideation. Death ideation (feeling that life would be better if dead) was reported in 15.6% of the patients, while suicidal ideation (feeling like hurting oneself) was reported in 4.8% of the patients. There were statistically significant differences in the screen positive rates for depression ({chi}2 = 61.61; 1 df; p< 0.001) and suicidal/death ideation ({chi}2 = 28.94; 1 df; p< 0.001) among younger and older veterans but not for the presence of excessive drinking ({chi}2 = 2.48; 1 df; p= 0.115). Among younger veterans, 57.6% screened positive for depression, 22.6% for suicidal/death ideation, and 13.7% for drinking. Among older veterans, 30.5% screened positive for depression, 8.7% for suicidal/death ideation, and 10.1% for drinking. Screen positive rates for each of the three clinic types also varied significantly. Among veterans seen in rheumatology, 61.7% screened positive for depression compared with 47.5% for cardiology and 40.5% for primary care ({chi}2 = 17.793; 2 df; p< 0.001). Similarly, 30.7% of veterans seen in rheumatology screened positive for suicidal/death ideation ({chi}2 = 37.161; 2 df; p< 0.001) and 19.5% for drinking ({chi}2 = 9.033; 2 df; p= 0.011). Comparable rates for cardiology were 23.1% and 8.0%, and 10.4% and 12.0% for primary care.

Of the 428 subjects who screened positively and were offered a baseline assessment, 88 (20.6%) refused participation, 177 (41.4%) were excluded from participation, 66 (15.4%) were found not to meet diagnostic criteria for a target disorder, and 97(22.7%) met all inclusion and exclusion criteria and represent the randomized sample. There were statistically significant differences in the baseline assessment outcomes (met a target, refused, ineligible, no diagnosis) between younger and older veterans but not related to race ({chi}2 = 2.54; 3 df; p= 0.468). Younger adults were more likely to be excluded (52.5% vs. 18.0%) while older adults were more likely to not meet inclusion criteria (29.5% vs. 19.7%). Reasons for being excluded included current participation in mental health care (N= 5; 1.2%), suicidal risk (N= 14; 3.3%), mania (N= 11, 2.6%); psychosis (N= 5; 1.2%), alcohol withdrawal (N= 15; 3.6%), currently undergoing substance abuse care (N= 17; 4.1%), and use of illicit drugs (N= 113; 27.0%).

The randomized sample of 97 patients was predominately white (49.5%), male (95.9%), and currently not married (55.7%). The mean age of participants was 61.6 ± 10.5. Because sampling focused more on primary care clinics, most patients were identified in the primary care clinics 61 (59.8%), with 24 (24.7%) from cardiology and 15 (15.5%) from rheumatology. As shown in Table 1, there were no baseline differences between those patients in the usual care arm and patients in the TDM arm, except in the distribution of racial groups. There were 11 subjects with concurrent depression and at-risk drinking (8 from usual care). Among those with a depressive disorder, 53 (68.8%) had major depression. There were no differences in the distribution of types of depression (major, minor, or dysthymia) between usual care and TDM ({chi}2 = 0.74; 2 df; p= 0.964).


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  		TABLE 1. Pretreatment Clinical Characteristics and Demographics of Study Participantsa
 
Follow-up assessments were completed for 76.3% of the subjects with no overall differences in the rate of incomplete data across the two study groups ({chi}2 = 0.002; 1 df; p= 0.965). Within the diagnostic categories, there were no differences in the follow-up rates between the two study arms. The principal reasons for lack of a follow-up assessment were withdrawal of consent (8.2%) and inability to contact the subject (15.5%).

Overall, a greater proportion of subjects randomized to TDM experienced a response to treatment compared with those randomized to usual care (39.1% vs. 17.6%) (Wald = 5.27; 1 df; OR = 0.33) (95% CI: 0.13–0.85) (p= 0.022) (Table 2 and Figure 1). Examination of subjects by diagnostic group demonstrated similar effects on response. For those with a depressive disorder, 44.1% achieved remission in the TDM arm compared with 20.5% in the usual care arm (Wald = 4.54; 1 df; OR =0 .34) (95% CI: 0.12–0.92) (p= 0.033). For those with at-risk drinking, 43.8% achieved a response to treatment in the TDM arm compared with 20.0% in the usual care arm (Wald = 2.16; 1 df; OR = 0.28) (95% CI: 0.05–1.54) (p= 0.142). Comparing depression severity using the HDRS, the patients treated using TDM had significantly greater improvement in symptoms compared with those randomized to usual care (ß = 3.78) (CI: 0.32, 7.52) (p= 0.048) (Table 2). Similar but nonsignificant findings were demonstrated with the CESD scale (ß = 3.33) (CI: -0.51, 7.18) (p= 0.088). Among those assigned to TDM, there were no differences in response rates for subjects from medical subspecialty clinics (40.7% overall response) compared with primary care clinics (36.8% response) ({chi}2 = 0.071; 1 df; p= 0.790).


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  		TABLE 2. Clinical Outcomes for Subjects With Depression and/or At-Risk Drinking Randomly Assigned to TDM or Usual Care
 


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  		Figure 1. Response rates to treatment between subjects assigned to TDM versus usual care for each diagnostic group and the overall response rate.

 
Treatment access was defined as completing at least one mental health/substance abuse appointment (by telephone for TDM or face-to-face for those referred from primary care). Treatment access was measured by self-report. Overall, 41.3% of patients assigned to TDM accessed behavioral health care compared with 9.8% of usual care patients ({chi}2 = 12.89; 1 df; p< 0.001). There was no evidence that access was a key factor in response to treatment. Of note, the BHSs reported that more than 90% of subjects were contacted at least one time raising concern that the self-report measure of attendance may underestimate actual participation in treatment. The self-report measure may also underestimate attendance because of subjects not completing the 4-month assessment. Guideline adherence was not measured by the research staff.


   DISCUSSION
TOP
 ABSTRACT
 INTRODUCTION
 MATERIALS AND METHODS
 RESULTS
 DISCUSSION
ACKNOWLEDGMENTS
 REFERENCES
 
There is growing recognition that studies are needed to examine the usefulness and effectiveness of interventions for the type of patients that most typically present for treatment.

The results of this study provide evidence that one form of collaborative care, TDM in the context of primary and subspecialty care can be used successfully to improve outcomes of patients with depression and/or at-risk drinking. Inclusion of both problems is important because many patients present with more than one behavioral health problem and demonstrating that the model is capable of delivering efficacious care for multiple problems may improve the sustainability of the model.

We adopted a relatively conservative measure of outcome in this study by examining the percentages of patients who both stayed in the intervention, as well as improved to the point of remission of depression or significant improvement or significant reductions in alcohol use, depending on the focus of the treatment. For depression, all but two cases were defined by remission of depression rather than significant reductions in symptoms. This was based on the need to have a common standard of improvement across the two types of behavioral health problems we examined. The strength of this approach was the reference to meaningful standards of severity, namely, the inclusion cut-off point for at-risk drinking of 21 standard drinks per week (or 14 for women or those older than age 65) or binge drinking, and a HDRS score of 10 or less. We do note that the continuous outcomes of depression, HDRS, and CESD, also support the efficacy of the TDM model. The change in HDRS scores (an interview based assessment) was significantly different between the two arms and though the magnitude of change in CESD scores (a self-report measure) was similar to the change in HDRS this change was not significantly different in the two arms.

The findings of this study are generally consistent with other studies in non-VA settings that have shown improvement in depression outcomes using a collaborative care approach (18,19,38). In the present study, twice as many veterans in the TDM group benefited from treatment for depression or at-risk drinking relative to patients in usual care. This compares favorably to Tutty et al. who found that telephone intervention patients were twice as likely to have a 50% reduction in depressive symptoms (18). Existing studies of collaborative care models have demonstrated substantial treatment effectiveness with moderate increases in costs (39). The cost-effectiveness of the collaborative care strategy in the current study should also be examined but is likely to be substantially less costly than similar programs that rely solely on in-person contact.

Of particular note in this study are the high rates of depression and suicidal/death ideation among those screened, especially in the specialty medical clinics. The rates of death or suicidal ideation are consistent with older primary care veterans reported by Oslin and colleagues (40). However, these rates are higher than reported in community practices of all age groups (41,42) or among veterans of all age groups (43). Our results do indicate that death ideation (thoughts about death or dying) was much more common than suicidal ideation (thoughts of ending one’s life). Given that the sample for this study was mostly older veterans, a possible explanation of the higher than expected rates is a reflection of high medical burden or frailty often seen in older adults, or related to the high rates of depression or alcohol use in the same, or alternatively related to greater exposure of military personnel to death while in the service or among aging peers. Rates of depression are consistent with previously reported prevalence rates of veterans in primary care (26,27). The higher-than-expected rates of depression among veterans has been hypothesized to relate to better access to behavioral health care, selection for more disabled and disadvantaged veterans, and veteran preference. The high rates of depression and suicide among medical subspecialty clinics would be consistent with literature on an association between arthritis and depression and cardiovascular disease and depression (44–46). However, there is a general lack of epidemiological data from these settings, especially among veteran populations. We caution that the rates in this study should not be used as true prevalence rates given the high rates of refusal for screening. It is also not clear if the prevalence of disorders will dramatically change the efficacy of an intervention such as TDM although higher prevalence and therefore greater need for services may positively affect the feasibility of implementing such a clinical model.

Limitations of this study include that the insufficient power to examine differential treatment response within medical subspecialty clinics or differential response of treatment of at-risk drinking. However, the high rates of positive screens suggest that more research is needed in the care of veterans in medical subspecialty clinics. In addition, we were also unable to examine other factors that might explain the response to treatment, such as medication adherence, or the patient’s perception of their relationship to their care providers. Replication of these findings might well examine these issues. We also note the relatively low rates of completed screens. While this should not effect the interpretation of the randomized component of the study, this does raise questions regarding research procedures (anecdotally some patients objected to the screening because of the implications of being identified with behavioral health problems) and the use of the telephone (some patients do not have access to telephones or are at their home only a limited amount of time). These completion rates are comparable with other primary care-based studies and reflect the difficulty of engaging patients not seeking care (47–49). Finally, as both depression and drinking problems are often chronic disorders, further study is needed of the sustainability or brittleness of response and the value of a maintenance program for monitoring patients for relapse or ongoing needs.

Despite the overall low rates of treatment response, it is also plausible that the success of TDM is not only in providing direct treatment but also in facilitating entry into specialty behavioral health care. Nevertheless, the initial evidence suggests that telephone-based collaborative care is a useful and efficacious model of treatment for behavioral health problems within the context of primary or medical subspecialty care practice at a VA facility. While costs associated with TDM were not directly measured, it is noted that the subjects enrolled in this program were managed using less than 25% of the time of a master’s prepared nurse with 1 hour of supervision per week from a psychiatrist. This minimal cost should be affordable in the context of primary care and given the use of telephone rather than face-to-face visits, a nurse could be shared between primary care practices without a decrement in service.


   ACKNOWLEDGMENTS
TOP
 ABSTRACT
 INTRODUCTION
 MATERIALS AND METHODS
 RESULTS
 DISCUSSION
 ACKNOWLEDGMENTS
REFERENCES
 
Supported in part by grants from the National Institute of Mental Health (1K08 MH01599-01) and the Mental Illness Research, Education and Clinical Center (MIRECC) at the Philadelphia VAMC.

Without the dedication of the primary care clinicians, this work would not be possible. We are grateful for their devotion to their patients and their belief that the treatment of behavioral health problems is a vital component to the care of patients. We also acknowledge the work of the health specialists who were equally devoted to the care of the participants.

Received for publication March 17, 2003.


   REFERENCES
TOP
 ABSTRACT
 INTRODUCTION
 MATERIALS AND METHODS
 RESULTS
 DISCUSSION
 ACKNOWLEDGMENTS
 REFERENCES
 

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