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Published Online: 1 April 2013

Practice-Based Versus Telemedicine-Based Collaborative Care for Depression in Rural Federally Qualified Health Centers: A Pragmatic Randomized Comparative Effectiveness Trial

Abstract

Using telemedicine technologies, off-site mental health specialists collaborating with on-site primary care physicians yielded better depression outcomes than practice-based care with staff available on-site. In this study of mostly rural, unemployed, and uninsured patients with treatment-resistant depression and numerous comorbidities, those patients assigned to a telemedicine-based group had significantly and substantially greater treatment response rates, remission rates, reductions in depression severity, and increases in mental health status and quality of life than patients assigned to the practice-based care group.

Abstract

Objective

Practice-based collaborative care is a complex evidence-based practice that is difficult to implement in smaller primary care practices that lack on-site mental health staff. Telemedicine-based collaborative care virtually co-locates and integrates mental health providers into primary care settings. The objective of this multisite randomized pragmatic comparative effectiveness trial was to compare the outcomes of patients assigned to practice-based and telemedicine-based collaborative care.

Method

From 2007 to 2009, patients at federally qualified health centers serving medically underserved populations were screened for depression, and 364 patients who screened positive were enrolled and followed for 18 months. Those assigned to practice-based collaborative care received evidence-based care from an on-site primary care provider and a nurse care manager. Those assigned to telemedicine-based collaborative care received evidence-based care from an on-site primary care provider and an off-site team: a nurse care manager and a pharmacist by telephone, and a psychologist and a psychiatrist via videoconferencing. The primary clinical outcome measures were treatment response, remission, and change in depression severity.

Results

Significant group main effects were observed for both response (odds ratio=7.74, 95% CI=3.94–15.20) and remission (odds ratio=12.69, 95% CI=4.81–33.46), and a significant overall group-by-time interaction effect was observed for depression severity on the Hopkins Symptom Checklist, with greater reductions in severity over time for patients in the telemedicine-based group. Improvements in outcomes appeared to be attributable to higher fidelity to the collaborative care evidence base in the telemedicine-based group.

Conclusions

Contracting with an off-site telemedicine-based collaborative care team can yield better outcomes than implementing practice-based collaborative care with locally available staff.
Complex evidence-based practices are difficult to implement with fidelity in routine care. One such evidence-based practice, practice-based collaborative care, involves co-located primary care providers, mental health specialists, and care managers working together on-site in a primary care setting. Practice-based collaborative care has been shown to improve depression outcomes in numerous randomized effectiveness trials (17). However, implementation in smaller primary care practices presents challenges where it is typically not feasible to employ on-site mental health specialists or full-time care managers. Only 25% of U.S. primary care practices have on-site mental health specialists (8). Two studies (3, 9) have demonstrated that depression outcomes can be improved in small primary care clinics lacking on-site mental health specialists by training on-site nurses to be depression care managers; however, the effect sizes have been small to medium. Moreover, based on the results of a meta-analysis of randomized trials of practice-based collaborative care, Gilbody et al. (10) concluded that collaborative care interventions with more mental health specialist involvement have larger effect sizes.
Telemedicine technologies now make possible the virtual co-location of mental health specialists and primary care providers. Telemedicine-based collaborative care involves an off-site team of mental health specialists collaborating with on-site primary care providers, from a centralized location, using telephones, videoconferencing, and electronic health records. A multisite randomized trial conducted in the Department of Veterans Affairs (VA) (11, 12) demonstrated that telemedicine-based collaborative care is more effective than usual care in small satellite primary care clinics. Telemedicine-based collaborative care has also been adopted and sustained as part of routine care in small satellite primary care clinics within the VA (13). Compared with practice-based collaborative care, telemedicine-based collaborative care has the potential to be implemented with higher fidelity in smaller primary care clinics because the off-site team can include an array of mental health specialists, and full-time care managers can practice under more intensive clinical supervision and dedicate their time to care coordination activities, resulting in higher fidelity to care manager protocols. However, there are also potential disadvantages to telemedicine-based collaborative care. Off-site care managers cannot build on established relationships with patients and may have difficulty establishing therapeutic alliances from a distance. Likewise, if off-site care managers lack access to on-site medical records, they may have difficulty integrating behavioral and physical aspects of care and face barriers communicating with on-site primary care providers. In addition, the stepped care elements of the collaborative care model (e.g., psychiatric consultation) may be less effective when delivered via telemedicine. However, patients and providers uniformly report high levels of satisfaction with videoconferencing (1417), and there is good evidence for the clinical equivalency of psychiatric (1821) and psychological (2226) treatments delivered via videoconferencing compared with face-to-face.
Given that 1) practice-based collaborative care without the involvement of on-site mental health specialists improves outcomes, 2) practice-based collaborative care with involvement from on-site mental health specialists improves outcomes more, and 3) the potential disadvantages of telemedicine-based collaborative care, an important policy-relevant question is whether it is more effective for small, remote primary care clinics to implement practice-based collaborative care without the involvement of on-site mental health specialists or to implement telemedicine-based collaborative care in partnership with an off-site team of mental health specialists.
Our objective in this pragmatic (27) comparative effectiveness trial (28) was to compare the process outcomes and clinical outcomes of patients randomly assigned to telemedicine-based collaborative care or practice-based collaborative care in small, remote primary care clinics that lacked on-site mental health specialists, thereby comparing two organizational approaches (with clinical equipoise) to delivering collaborative care for depression (29). We chose to conduct a pragmatic trial design in order to compare two viable competing strategies to delivering an evidence-based practice rather than an explanatory trial designed to determine why one approach was superior to the other. We hypothesized that compared with patients assigned to practice-based collaborative care, those assigned to telemedicine-based collaborative care would receive higher-fidelity care management, more specialty mental health services (e.g., telepsychiatry and telepsychology), and higher-quality pharmacotherapy and therefore would experience greater symptom improvement. Secondary outcomes examined included health status, quality of life, and satisfaction with care.
We partnered with five federally qualified health centers serving medically underserved populations in Arkansas’ Mississippi Delta region and the Ozark Highlands. With federal oversight from the Health Resources and Services Administration (HRSA), federally qualified health centers make up the nation’s largest and fastest growing network of primary care providers, with 8,000 clinics providing services to 20 million Americans. Three-quarters of federally qualified health center patients live in poverty, half live in rural areas, one-third are uninsured, and one-third are from minority populations. Mental health problems are the most commonly reported reasons for visits to federally qualified health centers (30), yet only 5.5% of encounters are with on-site mental health specialists (31). Research conducted in partnership with federally qualified health centers has direct applicability to a large segment of the U.S. population at risk for experiencing health disparities.

Method

Design Overview

This multisite randomized trial employed a comparative effectiveness research design (28). Patients were randomly assigned to one of two active treatment arms, both of which represent potentially feasible approaches to adapting the evidence-based collaborative care model for routine delivery in medically underserved areas. The study design also contained many elements of pragmatic trials (27), including the use of relatively few exclusion criteria, enrollment of a diverse sample of patients, monitoring of but not controlling intervention fidelity, a primary outcome measure defined in terms of changes in patient-reported symptoms, and use of intent-to-treat analyses to examine group differences.

Setting and Participants

We approached six federally qualified health centers, and five agreed to participate. Participating centers employed between 1.3 and 9.7 primary care physician full-time equivalents, served between 5,362 and 13,050 unique primary care patients, and operated one to six clinics across multiple locations. None of the participating clinic locations had an on-site mental health specialist. Between November 2007 and June 2009, 19,285 patients were screened for depression by health center staff using the nine-item Patient Health Questionnaire (see the CONSORT diagram in the data supplement that accompanies the online edition of this article). Fifteen percent of patients (N=2,863) screened positive (a score ≥10 on the Patient Health Questionnaire); health center staff obtained informed consent from 62% of potentially eligible patients (N=829), and 55% (N=364) were found to be eligible and completed the baseline telephone interview. We excluded patients that primary care providers would not be comfortable treating; exclusion criteria included pregnancy, schizophrenia, acute suicidal ideation, substance dependence, bipolar disorder, recent bereavement, and current specialty mental health treatment. We also excluded patients who were unable to participate in research because of cognitive impairment, having a court-appointed guardian, not speaking English, having no telephone, or having a life event preventing participation. Screening and eligibility results were entered into the medical record.

Randomization and Interventions

Randomization.

Eligible patients were assigned by computer randomization using a 2×2 Latin square design (stratified by clinic) to either telemedicine-based collaborative care or practice-based collaborative care. It was not feasible to blind patients or providers to randomization status.

Practice-based collaborative care.

The practice-based collaborative care intervention was designed to be the same as the model of care supported by HRSA, known as the Depression Health Disparities Collaborative (32, 33), which represents more intensive treatment than usual care. Practice-based collaborative care involved two types of providers: on-site primary care providers and on-site nurse depression care managers. Each clinic location employed a half-time depression care manager funded by the study. Depression care managers were nurses (R.N. or L.P.N.) who had no prior mental health experience. They received a care manager training manual, 1 day of training in depression care management, and access to a web-based patient registry and depression care manager decision support system (34). Patients could choose either watchful waiting or antidepressant treatment. Depression care manager encounters were conducted either face-to-face or by telephone, depending on the patient’s preference. The initial depression care manager encounter included 1) symptom monitoring with the Patient Health Questionnaire, 2) education/activation, 3) barrier assessment/resolution, and 4) establishing self-management goals, including planning physical, rewarding, and social activities. Follow-up encounters, scheduled every 2 weeks during acute treatment and every 4 weeks during continuation treatment, included the monitoring of symptoms, medication adherence, side effects, and engagement in planned self-management activities. Depression care managers received no clinical supervision from a mental health specialist. Progress notes were entered into the patients’ paper medical record. A trial was considered to have failed in the acute phase if the patient did not respond to treatment (response was defined as a decrease of ≥50% in Patient Health Questionnaire score) after 8 weeks of treatment. No additional on-site mental health support was available for patients who did not respond to treatment, although patients could be referred to off-site mental health providers (e.g., community mental health centers). Patients received the intervention for up to 12 months.

Telemedicine-based collaborative care.

Telemedicine-based collaborative care involved five types of providers: on-site primary care providers and off-site depression care managers (at the R.N. level), pharmacists (at the Pharm.D. level), psychologists (at the Ph.D. level), and psychiatrists. The off-site team, located at the University of Arkansas for Medical Sciences, was funded by the study. The full-time depression care manager was a nurse who had no prior mental health experience and received the same training and tools as the on-site depression care managers. All depression care manager encounters were conducted by telephone and followed the protocol described above. Progress notes were faxed to the clinic. During weekly meetings, the depression care manager received clinical supervision and the off-site team discussed new patients and patients who were not responding to treatment, and they offered treatment recommendations to primary care providers via the depression care manager progress notes. Patients received stepped care, whereby treatment intensity was increased for patients who were not responding to treatment. If the patient did not respond to the initial antidepressant, the pharmacist conducted a medication history and provided medication management by telephone as needed. If the patient did not respond to two antidepressant trials, a psychiatry consultation via videoconferencing was scheduled. At any time, patients had access to cognitive-behavioral therapy (CBT) delivered via videoconferencing. Patients who did not respond to an antidepressant trial were specifically encouraged to initiate and complete CBT.

Outcomes and Follow-Up

Fidelity assessment.

Fidelity to the depression care manager protocol was measured through chart review. Five of the charts (1.4%) could not be located during the site visits. The following fidelity measures were abstracted: number of depression care manager encounters with documented Patient Health Questionnaire scores; self-management activities; antidepressant adherence assessments and side effect assessments for those treated with antidepressants; and counseling adherence assessments for those referred to psychotherapy. Depression care manager fidelity was also measured from patient self-report during the 6- and 12-month telephone interviews using items that addressed education, self-management, symptom monitoring, adherence monitoring, and collaboration among providers. To measure fidelity to the stepped care protocol, we examined what proportion of patients in the telemedicine group who failed to respond to at least one medication trial had a telephone pharmacist encounter and what proportion of those who failed to respond to two trials had a telepsychiatry consultation. We also examined what proportion of patients in the telemedicine-based group attended at least one telepsychotherapy session and completed at least eight sessions.

Baseline interviews.

Data were collected at baseline in a blinded telephone interview. At baseline, sociodemographic and clinical case-mix data were collected using the Depression Outcomes Module (35, 36), the Mini International Neuropsychiatric Interview (37, 38), the Duke Social Support and Stress Scale (39, 40), the Quality Improvement for Depression Treatment Acceptability scale (3, 4), and the Depression Health Beliefs Inventory (41). Zip codes were used to categorize patients’ residence as rural or urban according to Rural Urban Commuting Area classification scheme C.

Follow-up interviews.

Blinded follow-up telephone interviews were completed for 87% of participants (N=318) at 6 months, 79% (N=287) at 12 months, and 78% (N=283) at 18 months. In addition to the fidelity measures described above, the other primary process measures included self-reported mental health service utilization, antidepressant prescriptions, antidepressant dosage (categorized as starting, usual, or high [42]), and antidepressant adherence (taking the full prescribed dosage at least 80% of days in the previous month). The primary clinical outcome measures were changes in depression severity and treatment response and remission. Depression severity was measured continuously using the 20-item Hopkins Symptom Checklist (HSCL) (43, 44). Response, measured dichotomously, was defined as a decrease of ≥50% in HSCL score between baseline and follow-up. Remission, measured dichotomously, was defined as an HSCL score <0.5. Secondary outcome measures included health status (based on the physical and mental health composite scale scores from the 12-item Short-Form Health Survey) (45, 46), quality of life (based on the Quality of Well-Being scale) (4750), and satisfaction with care (based on the Consumer Assessment of Healthcare Providers and Systems) (51).

Statistical Analysis

Patients were the unit of the intent-to-treat analysis. Clinic-level intraclass correlation coefficients for HSCL change scores were not significant. Provider-level intraclass correlation could not be calculated because patients could have multiple primary care providers. For the hypotheses examining fidelity, separate logistic regressions were specified for the first 6 months and the second 6 months. For the hypotheses examining other outcomes, we used mixed models and included data from all completed research assessments (52). Case-mix variables were selected using the method of purposeful selection (53). Case-mix variables with missing values were imputed using the PROC MI procedure in SAS, version 9.3 (SAS Institute, Cary, N.C.). PROC MIXED and PROC GLIMMIX were used with the PROC MIANALYZE procedure to model outcomes with linear, binomial, negative binomial, or ordinal distributions. All models specified clinic as a random effect to control for intraclass correlation coefficient. Time was included as a fixed effect. The model specifications included main effects for group and time (with practice-based collaborative care assigned as the reference group) and interaction effects for group by time. The main group effect was used to test the hypotheses for dependent variables not measured at baseline (e.g., treatment response). For dependent variables that were measured at baseline (e.g., HSCL score), group-by-time interaction effects were used to test the hypothesis that the rate of improvement differed across the two groups. Because there were multiple group-by-time interaction terms, an omnibus test was used to determine whether these variables collectively explained a significant amount of the variance in the dependent variable (54). If the omnibus test was significant at the conservative alpha level of 0.10, we report group differences and significance tests for each time period. Otherwise, we report group differences averaged across the time periods and one significance test. The analysis had an 85% power to detect a 15% difference (e.g., 30% versus 45%) in response rates.

Results

The study participants’ socioeconomic and clinical characteristics are summarized in Table 1. Two-thirds (64.5%) were unemployed, 69.7% had an annual household income <$20,000, 50.8% were uninsured, and 68.1% lived in a rural area. At baseline, 83.2% met diagnostic criteria for major depressive disorder, and the mean HSCL score was 1.9, indicating moderately severe depression. The mean number of chronic physical health disorders was 4.6 (SD=2.6), and psychiatric comorbidity was common. Mean physical and mental health composite scale scores were nearly two standard deviations below those for the general population. Nearly half (48.4%) were already receiving depression treatment at enrollment, indicating treatment resistance.
TABLE 1. Baseline Sociodemographic and Clinical Characteristics of Participants in a Randomized Study of Practice-Based or Telemedicine-Based Collaborative Carea
CharacteristicbAll Patients (N=364)Telemedicine-Based Group (N=179)Practice-Based Group (N=185)
 N%N%N%
Male6718.43217.93518.9
Race/ethnicity      
 Caucasian26171.712871.513371.9
 African American7620.93921.83720.0
 Native American185.073.9116.0
 Other92.552.842.2
Income      
 <$10,00010429.75933.74525.7
 $10,000–$14,9998424.04224.04224.0
 $15,000–$19,9995616.02916.62715.4
 $20,000–$29,9996117.42514.33620.6
 $30,000–$39,999246.9105.7148.0
 $40,000–$49,999123.463.463.4
 ≥$50,00092.642.352.9
Rural residence24868.111966.512969.7
Married16244.57944.18344.9
High school graduate26573.012570.214075.7
Employed12935.55731.87239.1
Insurancec      
 Public11030.26435.84624.9
 Private5414.82815.62614.1
 Public and private154.173.984.3
 Uninsured18550.88044.710556.8
 MeanSDMeanSDMeanSD
Social support (0–1)0.40.20.40.20.40.2
Perceived barriers (0–9)d3.72.04.02.13.41.9
Perceived need (0–6)3.01.53.11.53.01.5
Perceived treatment effectiveness (0–2)1.30.71.30.71.30.7
Hopkins Symptom Checklist score (depression severity; 0–4)1.90.71.90.81.90.7
Short-Form Health Survey, physical health composite score (0–100)36.913.435.713.138.013.7
Short-Form Health Survey, mental health composite score (0–100)31.311.232.411.130.311.2
Quality of Well-Being score (0–1)0.40.10.40.10.40.1
Chronic physical illness counte4.62.64.82.54.32.6
Prior depression episodes count4.21.64.21.64.21.6
Age (years)47.212.647.712.546.812.8
 N%N%N%
Age <18 years at depression onset14441.06739.27742.8
Family history of depression20958.211062.59954.1
Prior antidepressant treatment26773.3512871.5113975.14
Prior counseling10729.405128.495630.27
Current depression treatment17648.48446.99249.7
Antidepressants acceptable30385.114984.715485.6
Counseling acceptability27376.913677.713776.1
Current major depressive disorder30383.214480.515986.0
Current dysthymia123.373.952.7
Current panic disorder328.8168.9168.7
Current generalized anxiety disorder23163.511463.711763.2
Current posttraumatic stress disorder5815.93016.82815.1
Current at-risk drinking205.5126.784.3
a
There were no significant differences between groups, except as otherwise noted. Some numbers do not add up to total number of patients because of missing data, and some percentages do not add up to 100 because of rounding.
b
Numbers in parentheses indicate the possible range.
c
Percentages do not add up to 100 because some patients had more than one type of insurance.
d
Significant difference between groups, p=0.01.
e
Significant difference between groups, p=0.05.

Care Manager Fidelity

Table 2 describes care manager fidelity. At the 6- and 12-month follow-ups, significantly more patients in the telemedicine-based group than in the practice-based group reported that a health care professional other than their primary care provider 1) gave them helpful information about depression or depression treatment (odds ratios, 2.77 at 6 months and 2.32 at 12 months); 2) made helpful suggestions about things they could do to help depression, such as exercise or becoming more socially active (odds ratios, 3.47 at 6 months and 2.50 at 12 months); 3) asked them about their depression symptoms (odds ratios, 3.60 at 6 months and 2.63 at 12 months); and 4) asked them if they were taking antidepressant medications as prescribed or attending scheduled counseling sessions (odds ratios, 4.70 at 6 months and 3.96 at 12 months). More patients in the telemedicine-based group also reported that their primary care provider worked collaboratively with a mental health specialist (odds ratios, 4.63 at 6 months and 9.05 at 12 months).
TABLE 2. Group Differences in Fidelity to the Care Manager Protocol in a Randomized Study of Practice-Based or Telemedicine-Based Collaborative Care
MeasureTelemedicine-Based GroupPractice-Based GroupGroup ComparisonAnalysis
Patient Self-ReportN%N%pAdjusted Odds Ratio95% CIp
Educationa        
 6 months    <0.0012.771.67, 4.61<0.001
  Frequently38/15324.8418/16510.91    
  Occasionally39/15325.4929/16517.58    
  Not at all76/15349.67118/16571.52    
 12 months    0.0102.321.37, 3.940.002
  Frequently24/13817.3911/1497.38    
  Occasionally31/13822.4626/14917.45    
  Not at all83/13860.14112/14975.17    
Self-managementb        
 6 months    <0.0013.472.15, 5.62<0.001
  Frequently49/15332.0322/16513.33    
  Occasionally51/15333.3342/16525.45    
  Not at all53/15334.64101/16561.21    
 12 months    <0.0012.501.48, 4.23<0.001
  Frequently35/13825.3612/1498.05    
  Occasionally25/13818.1231/14920.81    
  Not at all78/13856.52106/14971.14    
Symptom monitoringc        
 6 months    <0.0013.602.21, 5.86<0.001
  Frequently53/15334.6424/16514.55    
  Occasionally41/15326.8029/16517.58    
  Not at all59/15338.56112/16567.88    
 12 months    <0.0012.631.54, 4.52<0.001
  Frequently34/13824.6412/1498.05    
  Occasionally23/13816.6727/14918.12    
  Not at all81/13858.70110/14973.83    
Antidepressant monitoringd        
 6 months    <0.0014.702.82, 7.84<0.001
  Frequently46/15330.0718/16510.91    
  Occasionally47/15330.7228/16516.97    
  Not at all60/15339.22119/16572.12    
 12 months        
  Frequently33/13823.9111/1497.38<0.0013.962.22, 7.05<0.001
  Occasionally27/13819.5718/14912.08    
  Not at all78/13856.52120/14980.54    
Collaboratione        
 6 months    0.0014.632.08, 10.30<0.001
  Frequently22/9622.928/1127.14    
  Occasionally13/9613.549/1128.04    
  Not at all61/9663.5495/11284.82    
 12 months    0.0069.053.04, 26.93<0.001
  Frequently12/9113.194/1113.60    
  Occasionally10/9110.995/1114.50    
  Not at all69/9175.82102/11191.89    
Chart reviewMeanSDMeanSDpAdjusted Incidence Rate Ratio95% CIp
Educationf        
 0–6 months0.560.650.160.48<0.0012.031.38, 2.98<0.001
 6–12 months0.020.130.020.150.7431.060.27, 4.170.932
Self-management        
 0–6 months4.122.560.771.47<0.0015.624.46, 7.07<0.001
 6–12 months2.082.700.260.92<0.0018.845.44, 14.35<0.001
Symptom monitoring        
 0–6 months4.852.691.191.65<0.0014.103.41, 4.92<0.001
 6–12 months2.112.730.441.07<0.0014.643.19, 6.74<0.001
Antidepressant monitoringg        
 0–6 months5.402.291.971.81<0.0012.692.20, 3.28<0.001
 6–12 months3.942.491.471.72<0.0012.491.69, 3.67<0.001
Side effect monitoringf,g        
 0–6 months5.182.291.241.49<0.0014.223.32, 5.36<0.001
 6–12 months3.732.450.801.19<0.0014.462.75, 7.25<0.001
Counseling monitoringg        
 0–6 months3.442.682.701.640.4171.130.63, 2.050.664
 6–12 months2.572.272.002.710.6582.910.08, 110.940.419
a
Based on the question “How often did a health care professional other than your primary care physician give you helpful information about depression or depression treatment?”
b
Based on the question “How often did a health care professional other than your primary care physician make helpful suggestions about things you can do to help depression, such as exercise or becoming more active socially?”
c
Based on the question “How often did a health care professional other than your primary care physician ask you about your depression symptoms?”
d
Based on the question “How often did a health care professional other than your primary care physician ask you whether you were taking antidepressant medications as prescribed or attending scheduled counseling sessions?”
e
Based on the question “How often did your primary care physician work together with a mental health specialist to care for your depression symptoms?”
f
Model did not include a random effect to control for intraclass correlation coefficient because when included, the variance-covariance matrix was not positive definite, indicating not enough variation in the dependent variable attributable to variation in the random effect.
g
Antidepressant analysis conducted on subsample of 187 patients. Counseling analysis conducted on subsample of 42 patients.
Compared with patients in the practice-based group, those in the telemedicine-based group had significantly more depression care manager encounters in which Patient Health Questionnaire depression severity scores were documented in the medical record during both the first 6 months and the second 6 months (incidence rate ratios, 4.10 and 4.64, respectively). Patients in the telemedicine-based group also had significantly more depression care manager encounters in which self-management goals were documented during the first 6 months (incidence rate ratio=5.62). Among patients who received a prescription for an antidepressant, those in the telemedicine-based group had significantly more depression care manager encounters in which medication adherence was documented during both the first 6 months and the second 6 months (incidence rate ratios, 2.69 and 2.49, respectively). Likewise, patients in the telemedicine-based group who received a prescription for an antidepressant had significantly more depression care manager encounters in which the presence or absence of side effects was documented during both the first 6 months and the second 6 months (incidence rate ratios, 4.22 and 4.46, respectively). Among patients who were referred to counseling, there were no significant group differences in the number of depression care manager encounters in which session attendance was documented in the medical record.

Stepped Care Fidelity

Among patients in the telemedicine-based group who failed to respond to at least one medication trial (N=73), 8.2% (N=6) had a telephone encounter with the pharmacist. Among those who had failed to respond to two trials (N=29), 48.3% (N=14) had a telepsychiatry consultation. Another seven patients had an ad hoc telepsychiatry consultation. Also, 16.6% of patients (N=30) attended at least one telepsychotherapy session, and 7.8% (N=14) completed eight or more sessions.

Treatment Process Outcomes

Table 3 summarizes the treatment provided to the two groups. There were no significant group differences at baseline, and no significant group-by-time interactions for number of primary care visits or number of depression-related primary care visits, or mental health visits. With respect to antidepressant treatment, there were no significant group main effects for receiving an antidepressant prescription, number of prescribed antidepressants, dosage level (starting, usual, high), or adherence.
TABLE 3. Group Differences in Services Utilization and Antidepressant Treatment in a Randomized Study of Practice-Based or Telemedicine-Based Collaborative Care
MeasureTelemedicine-Based GroupPractice-Based GroupUnadjusted AnalysisAdjusted Analysis
MeanSDMeanSDDifference pIncidence Rate Ratio95% CIpOmnibus Test p
Service utilization           
Primary care visits       1.160.98, 1.360.0810.16
 Baseline4.253.733.633.040.62 0.081    
 6 months3.823.343.693.980.13 0.749    
 12 months3.092.713.393.44–0.30 0.419    
 18 months2.722.362.983.54–0.26 0.463    
Depression-related primary care visitsa       0.990.72, 1.370.9580.29
 Baseline1.071.431.161.55–0.09 0.592    
 6 months1.071.931.172.24–0.10 0.658    
 12 months0.681.311.051.98–0.37 0.068    
 18 months0.581.170.942.06–0.36 0.080    
 N%N%Odds Ratio95% CIpOdds Ratio95% CIpOmnibus p
Any specialty mental health visitsb       0.560.24, 1.820.4250.16
 Baseline8/1794.4712/1856.490.670.27, 1.690.399    
 6 months31/15320.2621/16512.731.740.95, 3.190.070    
 12 months20/13814.4913/1498.721.770.85, 3.720.126    
 18 months13/1329.8518/15111.920.810.38, 1.720.578    
Antidepressant medications           
Any prescription       1.640.75, 3.580.2120.37
 Baseline         
 6 months100/15365.36100/16560.611.230.78, 1.940.381    
 12 months91/13865.9486/14957.721.420.88, 2.290.152    
 18 months74/13256.0686/15156.950.960.60, 1.540.880    
Adherencec,d       1.220.38, 3.890.7370. 86
 Baseline         
 6 months82/9289.1381/9585.261.420.60, 3.380.429    
 12 months74/8686.0567/8083.751.200.51, 2.800.679    
 18 months62/6989.8673/8190.120.970.33, 2.830.957    
Dosage levele       1.840.77, 4.380.1690.69
 Baseline         
 6 months      0.147    
  Starting44/9844.9045/9248.91       
  Usual42/9842.8643/9246.74       
  High12/9812.244/924.35       
 12 months           
  Starting32/8637.2134/8540.00  0.551    
  Usual40/8646.5142/8549.41       
  High14/8616.289/8510.59       
 18 months           
  Starting27/6939.1337/7946.84  0.444    
  Usual33/6947.8336/7945.57       
  High9/6913.046/797.59       
 MeanSDMeanSDDifference pIncidence Rate Ratio95% CIpOmnibus p
Number of prescribed antidepressants       1.190.92, 1.560.1910.49
 Baseline         
 6 months0.750.620.680.620.07 0.339    
 12 months0.770.650.660.630.11 0.174    
 18 months0.620.600.690.68–0.07 0.377    
a
Number of primary care visits during which depression symptoms were discussed.
b
Any visit to a mental health specialist, either face-to-face with a provider in the community or via videoconferencing with a study telepsychologist or telepsychiatrist.
c
Adherence coded as 1 if taking antidepressant ≥80% of days in past month, and 0 otherwise.
d
Analysis conducted on the subsample of patients with an active antidepressant prescription and not reporting antidepressant discontinuation as a result of primary care physician instruction; at the 6-month follow-up, N=187; at the 12-month follow-up, N=166; and at the 18-month follow-up, N=150.
e
Analysis conducted on the subsample of patients with an active antidepressant prescription with nonmissing dosages; at 6-month follow-up, N=190; at 12-month follow-up, N=171; and at 18-month follow-up, N=148.

Clinical Outcomes

Clinical outcomes are presented in Table 4. A significant group main effect was observed for both response (odds ratio=7.74) and remission (odds ratio=12.69), with patients in the telemedicine-based group having better outcomes. We also observed a significant overall group-by-time interaction effect for HSCL score (χ2=40.51, df=3, p<0.001), with greater reductions in severity for patients in the telemedicine-based group (Figure 1). There was also a significant overall group-by-time interaction effect for mental health composite scale score (χ2=11.46, df=3, p=0.01) and Quality of Well-Being score (χ2=6.55, df=3, p=0.09), with greater improvements among patients in the telemedicine-based group. There were no significant overall group-by-time interaction effects for physical health composite scale score, although this finding is likely an artifact resulting from the orthogonal factor rotation and negative weights used to score the physical and mental health composite scales (55). There were no group differences in satisfaction at baseline, but the omnibus test of the group-by-time interactions was significant at the 0.10 level (χ2=6.69, df=3, p=0.08), with the telemedicine-based group having higher satisfaction.
TABLE 4. Group Differences in Clinical Outcomes in a Randomized Study of Practice-Based or Telemedicine-Based Collaborative Care
MeasureTelemedicine-Based GroupPractice-Based GroupUnadjusted AnalysisAdjusted Analysis
 N%N%Odds Ratio95% CIpOdds Ratio95% CIpOmnibus p
Satisfactiona          0.08
 Baseline79/16747.3182/17646.591.030.67, 1.570.8951.080.64, 1.830.765 
 6 months120/15080.00101/15963.522.301.37, 3.840.0012.761.50, 5.010.001 
 12 months99/13374.4487/14062.141.771.06, 2.980.0291.991.06, 3.710.031 
 18 months95/12874.2296/14864.861.560.93, 2.620.0931.670.89, 3.130.107 
Responseb       7.743.94, 15.20<0.0010.52
 Baseline         
 6 months70/15345.7525/16515.154.722.78, 8.03<0.001    
 12 months73/13852.9031/14920.814.272.55, 7.18<0.001    
 18 months63/13247.7333/15121.853.261.95, 5.47<0.001    
Remissionc       12.694.81, 33.46<0.0010.27
 Baseline         
 6 months44/15328.7611/1656.675.652.79, 11.44<0.001    
 12 months43/13831.1617/14911.413.511.89, 6.54<0.001    
 18 months34/13225.7615/1519.933.151.62, 6.09<0.001    
 MeanSDMeanSDGroup Differencep Group Difference95% CIpOmnibus p
Hopkins Symptom Checklist score (depression severity; 0–4)          <0.001
 Baseline1.880.771.900.72–0.020.732 –0.04–0.18, 0.100.594 
 6 months1.160.901.640.75–0.48<0.001 –0.50–0.65, –0.35<0.001 
 12 months1.040.791.530.85–0.49<0.001 –0.49–0.65, –0.33<0.001 
 18 months1.130.851.490.75–0.36<0.001 –0.33–0.49, –0.18<0.001 
Short-Form Health Survey, mental health composite score (0–100)          0.01
 Baseline32.3911.0830.3111.222.080.076 1.82–0.65, 4.300.149 
 6 months44.3414.2237.4911.986.85<0.001 6.533.91, 9.15<0.001 
 12 months46.5312.9840.5813.205.94<0.001 5.392.66, 8.12<0.001 
 18 months44.6013.5239.8612.244.750.002 4.011.26, 6.760.004 
Short-Form Health Survey, physical health composite score (0–100)       –0.22–2.26, 1.820.8340.46
 Baseline35.7313.0937.9613.68–2.230.112     
 6 months33.9312.5435.9813.54–2.050.162     
 12 months32.9813.1835.6212.77–2.640.086     
 18 months34.5212.5335.3113.22–0.790.609     
Quality of Well-Being score (0–1)          0.09
 Baseline0.430.150.440.14–0.010.608 0.01–0.02, 0.030.655 
 6 months0.490.180.460.150.030.097 0.030.003, 0.060.032 
 12 months0.500.170.490.170.020.400 0.030.002, 0.060.037 
 18 months0.500.150.480.170.020.220 0.040.02, 0.070.002 
a
Satisfaction coded 1 if patient reported very satisfied or satisfied and 0 if patient reported very dissatisfied, dissatisfied, or neither satisfied or dissatisfied.
b
Response coded 1 if patient experienced a reduction of ≥50% in depression severity according to the Hopkins Symptom Checklist, and 0 otherwise.
c
Remission coded 1 if patient reported a Hopkins Symptom Checklist score <0.5, and 0 otherwise.
FIGURE 1. Adjusted Depression Severity Scores for Patients Receiving Practice-Based or Telemedicine-Based Collaborative Carea
a The graph shows least square means of scores on the Hopkins Symptom Checklist. Least square means, or marginal means, are the estimated group means controlling for the covariates, which are held constant at their mean values. Error bars indicate 95% confidence intervals.

Discussion

Study participants were recruited from small, remote primary care clinics associated with the largest publicly funded health care system in the country. The sample was predominantly rural, unemployed, and uninsured. Patients had numerous comorbidities, and their depression was treatment resistant. The high degree of treatment resistance likely contributed to the low response and remission rates among those assigned to the practice-based collaborative care group. Compared with patients assigned to the practice-based collaborative care group, those in the telemedicine-based group had significantly and substantially greater treatment response rates, remission rates, reductions in depression severity, and increases in mental health status and quality of life. Improved outcomes were achieved in the telemedicine-based group without increasing the number of primary care visits. Improved outcomes appear to be due to higher fidelity to the care manager protocol in the telemedicine-based collaborative care model, despite the fact that off-site and on-site depression care managers had similar levels of clinical experience at baseline and underwent identical training. The higher fidelity to the care manager protocol in the telemedicine-based model may have been due to the fact that the off-site depression care manager practiced under more intensive clinical supervision and dedicated 100% of her time to depression care manager activities.
The greater fidelity to the care manager protocol did not translate into improvements in the quality of pharmacotherapy for the telemedicine-based group. The majority of patients in both groups initiated antidepressant treatment at therapeutic dosages, and adherence was high. Likewise, the psychotherapy available to patients in the telemedicine-based group via videoconferencing was not highly utilized and was not likely to have contributed substantially to improved outcomes. Our findings were essentially unchanged when patients who received telepsychotherapy were excluded from the analytical sample. Because group differences in outcomes are not likely to be attributable to either pharmacotherapy or psychotherapy, we hypothesize that patients assigned to telemedicine-based collaborative care were more likely to engage in self-management activities, such as physical, rewarding, and social activities. This hypothesis is based on the finding that patients in the telemedicine-based group received more encouragement from the depression care manager to engage in self-management activities. Previous research has demonstrated that behavioral activation is a clinically effective stand-alone treatment for depression (56, 57). Also, patients in the practice-based collaborative care intervention in Project Impact (58) were found to have significantly better treatment response rates if the depression care manager documented in the medical record that the patient scheduled physical, rewarding, and social activities. This hypothesis needs to be tested using an experimental dismantling study specifically designed to estimate the incremental treatment effect of scheduling self-management activities. Another possibility is that the more frequent depression care manager encounters provided to the telemedicine-based group resulted in greater social support, which in turn reduced depressive symptoms. This was the conclusion of Hunkeler et al. (59), who similarly reported that a depression care manager program at Kaiser Permanente did not improve antidepressant management, but did reduce depression symptoms.
An inherent limitation of this pragmatic trial is that the results are not conclusive with respect to identifying treatment mechanisms. Explanatory trial designs are needed to determine why patients assigned to receive telemedicine-based collaborative care had better outcomes than those assigned to receive practice-based collaborative care. However, for policy makers at HRSA and federally qualified health centers lacking on-site mental health personnel, these results clearly indicate that contracting with an off-site depression care team yields better depression outcomes than implementing collaborative care with staff available on-site. Future research should also examine whether having on-site nurse care managers supported by off-site psychiatrists, psychologists, and pharmacists via telephone and videoconferencing is an effective organizational approach to delivering collaborative care.

Acknowledgments

The authors gratefully acknowledge the patients and staff at the Boston Mountain Rural Health Center, Community Clinic NWA, Corning Area Healthcare, East Arkansas Family Health Center, and Jefferson Comprehensive Care Systems, as well as staff at the Community Health Centers of Arkansas. They also acknowledge the important contributions of project staff, including Amanda Davis, Loretta Ducker, Debbie Hodges, Choi Lai, Liya Lu, Michael McCarther, Camille Mack, Jennifer Stephens, and Vera Tate, as well as the contributions of the anonymous manuscript reviewers.

Footnote

Clinicaltrials.gov identifier: NCT00439452.

Supplementary Material

Supplementary Material (414_ds001.pdf)

References

1.
Katon W, Von Korff M, Lin E, Simon G, Walker E, Unützer J, Bush T, Russo J, Ludman E: Stepped collaborative care for primary care patients with persistent symptoms of depression: a randomized trial. Arch Gen Psychiatry 1999; 56:1109–1115
2.
Katon W, Robinson P, Von Korff M, Lin E, Bush T, Ludman E, Simon G, Walker E: A multifaceted intervention to improve treatment of depression in primary care. Arch Gen Psychiatry 1996; 53:924–932
3.
Rost K, Nutting P, Smith J, Werner J, Duan N: Improving depression outcomes in community primary care practice: a randomized trial of the quEST intervention. J Gen Intern Med 2001; 16:143–149
4.
Wells KB, Sherbourne C, Schoenbaum M, Duan N, Meredith L, Unützer J, Miranda J, Carney MF, Rubenstein LV: Impact of disseminating quality improvement programs for depression in managed primary care: a randomized controlled trial. JAMA 2000; 283:212–220
5.
Unützer J, Katon W, Callahan CM, Williams JW, Hunkeler E, Harpole L, Hoffing M, Della Penna RD, Noël PH, Lin EH, Areán PA, Hegel MT, Tang L, Belin TR, Oishi S, Langston CIMPACT Investigators (Improving Mood-Promoting Access to Collaborative Treatment): Collaborative care management of late-life depression in the primary care setting: a randomized controlled trial. JAMA 2002; 288:2836–2845
6.
Alexopoulos GS, Katz IR, Bruce ML, Heo M, Ten Have T, Raue P, Bogner HR, Schulberg HC, Mulsant BH, Reynolds CFPROSPECT Group: Remission in depressed geriatric primary care patients: a report from the PROSPECT study. Am J Psychiatry 2005; 162:718–724
7.
Bruce ML, Ten Have TR, Reynolds CF, Katz II, Schulberg HC, Mulsant BH, Brown GK, McAvay GJ, Pearson JL, Alexopoulos GS: Reducing suicidal ideation and depressive symptoms in depressed older primary care patients: a randomized controlled trial. JAMA 2004; 291:1081–1091
8.
Williams JW, Rost K, Dietrich AJ, Ciotti MC, Zyzanski SJ, Cornell J: Primary care physicians’ approach to depressive disorders: effects of physician specialty and practice structure. Arch Fam Med 1999; 8:58–67
9.
Gensichen J, von Korff M, Peitz M, Muth C, Beyer M, Güthlin C, Torge M, Petersen JJ, Rosemann T, König J, Gerlach FMPRoMPT (Primary Care Monitoring for Depressive Patients Trial): Case management for depression by health care assistants in small primary care practices: a cluster randomized trial. Ann Intern Med 2009; 151:369–378
10.
Gilbody S, Whitty P, Grimshaw J, Thomas R: Educational and organizational interventions to improve the management of depression in primary care: a systematic review. JAMA 2003; 289:3145–3151
11.
Fortney JC, Pyne JM, Edlund MJ, Williams DK, Robinson DE, Mittal D, Henderson KL: A randomized trial of telemedicine-based collaborative care for depression. J Gen Intern Med 2007; 22:1086–1093
12.
Pyne JM, Fortney JC, Tripathi SP, Maciejewski ML, Edlund MJ, Williams DK: Cost-effectiveness analysis of a rural telemedicine collaborative care intervention for depression. Arch Gen Psychiatry 2010; 67:812–821
13.
Fortney J, Enderle M, McDougall S, Clothier J, Otero J, Altman L, Curran G: Implementation outcomes of evidence-based quality improvement for depression in VA community based outpatient clinics. Implement Sci 2012; 7:30
14.
Rohland BM, Saleh SS, Rohrer JE, Romitti PA: Acceptability of telepsychiatry to a rural population. Psychiatr Serv 2000; 51:672–674
15.
Callahan EJ, Hilty DM, Nesbitt TS: Patient satisfaction with telemedicine consultation in primary care: comparison of ratings of medical and mental health applications. Telemed J 1998; 4:363–369
16.
Germain V, Marchand A, Bouchard S, Guay S, Drouin MS: Assessment of therapeutic alliance in face-to-face or videoconference treatment for posttraumatic stress disorder. Cyberpsychol Behav Soc Netw 2010; 13:29–35
17.
Simpson S: The provision of a telepsychology service to Shetland: client and therapist satisfaction and the ability to develop a therapeutic alliance. J Telemed Telecare 2001; 7(suppl 1):34–36
18.
Ruskin PE, Silver-Aylaian M, Kling MA, Reed SA, Bradham DD, Hebel JR, Barrett D, Knowles F, Hauser P: Treatment outcomes in depression: comparison of remote treatment through telepsychiatry to in-person treatment. Am J Psychiatry 2004; 161:1471–1476
19.
Ruskin PE, Reed S, Kumar R, Kling MA, Siegel E, Rosen M, Hauser P: Reliability and acceptability of psychiatric diagnosis via telecommunication and audiovisual technology. Psychiatr Serv 1998; 49:1086–1088
20.
O’Reilly R, Bishop J, Maddox K, Hutchinson L, Fisman M, Takhar J: Is telepsychiatry equivalent to face-to-face psychiatry? Results from a randomized controlled equivalence trial. Psychiatr Serv 2007; 58:836–843
21.
Hailey D, Roine R, Ohinmaa A: The effectiveness of telemental health applications: a review. Can J Psychiatry 2008; 53:769–778
22.
Nelson EL, Barnard M, Cain S: Treating childhood depression over videoconferencing. Telemed J E Health 2003; 9:49–55
23.
Bouchard S, Paquin B, Payeur R, Allard M, Rivard V, Fournier T, Renaud P, Lapierre J: Delivering cognitive-behavior therapy for panic disorder with agoraphobia in videoconference. Telemed J E Health 2004; 10:13–25
24.
Frueh BC, Monnier J, Yim E, Grubaugh AL, Hamner MB, Knapp RG: A randomized trial of telepsychiatry for post-traumatic stress disorder. J Telemed Telecare 2007; 13:142–147
25.
Germain V, Marchand A, Bouchard S, Drouin MS, Guay S: Effectiveness of cognitive behavioural therapy administered by videoconference for posttraumatic stress disorder. Cogn Behav Ther 2009; 38:42–53
26.
Morland LA, Greene CJ, Rosen CS, Foy D, Reilly P, Shore J, He Q, Frueh BC: Telemedicine for anger management therapy in a rural population of combat veterans with posttraumatic stress disorder: a randomized noninferiority trial. J Clin Psychiatry 2010; 71:855–863
27.
Thorpe KE, Zwarenstein M, Oxman AD, Treweek S, Furberg CD, Altman DG, Tunis S, Bergel E, Harvey I, Magid DJ, Chalkidou K: A pragmatic-explanatory continuum indicator summary (PRECIS): a tool to help trial designers. J Clin Epidemiol 2009; 62:464–475
28.
Institute of Medicine: Initial National Priorities for Comparative Effectiveness Research. Washington, DC, National Academies Press, 2009
29.
Tunis SR, Stryer DB, Clancy CM: Practical clinical trials: increasing the value of clinical research for decision making in clinical and health policy. JAMA 2003; 290:1624–1632
30.
Druss BG, Bornemann T, Fry-Johnson YW, McCombs HG, Politzer RM, Rust G: Trends in mental health and substance abuse services at the nation’s community health centers: 1998–2003. Am J Public Health 2006; 96:1779–1784
31.
National Association of Community Health Centers: US Health Center Fact Sheet: 2006. Bethesda, Md, National Association of Community Health Centers, 2007 (www.nachc.com/client/documents/US_Fact_Sheet_2007.pdf)
32.
Landon BE, Hicks LS, O’Malley AJ, Lieu TA, Keegan T, McNeil BJ, Guadagnoli E: Improving the management of chronic disease at community health centers. N Engl J Med 2007; 356:921–934
33.
Meredith LS, Mendel P, Pearson M, Wu SY, Joyce G, Straus JB, Ryan G, Keeler E, Unützer J: Implementation and maintenance of quality improvement for treating depression in primary care. Psychiatr Serv 2006; 57:48–55
34.
Fortney JC, Pyne JM, Steven CA, Williams JS, Hedrick RG, Lunsford AK, Raney WN, Ackerman BA, Ducker LO, Bonner LM, Smith JL: A web-based clinical decision support system for depression care management. Am J Manag Care 2010; 16:849–854
35.
Smith GR Jr, Burnam A, Burns BJ, Cleary P, Rost KM: Depression Outcomes Module (DOM), in Handbook of Psychiatric Measures. Edited by American Psychiatric Association. Washington, DC, American Psychiatric Association, 2000, pp 213–215
36.
Kramer TL, Smith GR, D’Arezzo KW, Card-Higginson P: Depression Outcomes Module. Little Rock, Ark, The Guide to Behavioral Health Outcomes Management Systems, 2000, pp 71–83
37.
Lecrubier Y, Sheehan DV, Weiller E, Amorim P, Bonora I, Sheehan KH, Janavs J, Dunbar GC: The Mini International Neuropsychiatric Interview (MINI), a short diagnostic structured interview: reliability and validity according to the CIDI. Eur Psychiatry 1997; 12:224–231
38.
Sheehan DV, Lecrubier Y, Sheehan KH, Janavs J, Weiller E, Keskiner A, Schinka J, Knapp E, Sheehan MF, Dunbar GC: The validity of the Mini International Neuropsychiatric Interview (MINI) according to the SCID-P and its reliability. Eur Psychiatry 1997; 12:232–241
39.
Parkerson GR, Michener JL, Wu LR, Finch JN, Muhlbaier LH, Magruder-Habib K, Kertesz JW, Clapp-Channing N, Morrow DS, Chen AL, Jokerst E: Associations among family support, family stress, and personal functional health status. J Clin Epidemiol 1989; 42:217–229
40.
Parkerson GR, Broadhead WE, Tse CK: Quality of life and functional health of primary care patients. J Clin Epidemiol 1992; 45:1303–1313
41.
Edlund MJ, Fortney JC, Reaves CM, Pyne JM, Mittal D: Beliefs about depression and depression treatment among depressed veterans. Med Care 2008; 46:581–589
42.
Simon GE, Lin EHB, Katon W, Saunders K, VonKorff M, Walker E, Bush T, Robinson P: Outcomes of “inadequate” antidepressant treatment. J Gen Intern Med 1995; 10:663–670
43.
Derogatis LR, Lipman RS, Rickels K, Uhlenhuth EH, Covi L: The Hopkins Symptom Checklist (HSCL): a measure of primary symptom dimensions. Mod Probl Pharmacopsychiatry 1974; 7:79–110
44.
Derogatis LR, Lipman RS, Rickels K, Uhlenhuth EH, Covi L: The Hopkins Symptom Checklist (HSCL): a self-report symptom inventory. Behav Sci 1974; 19:1–15
45.
Jones D, Kazis L, Lee A, Rogers W, Skinner K, Cassar L, Wilson N, Hendricks A: Health status assessments using the Veterans SF-12 and SF-36: methods for evaluating otucomes in the Veterans Health Administration. J Ambul Care Manage 2001; 24:68–86
46.
Kazis LE, Miller DR, Clark J, Skinner K, Lee A, Rogers W, Spiro A, Payne S, Fincke G, Selim A, Linzer M: Health-related quality of life in patients served by the Department of Veterans Affairs: results from the Veterans Health Study. Arch Intern Med 1998; 158:626–632
47.
Kaplan RM, Anderson JP: The general health policy model: an integrated approach, in Quality of Life and Pharmacoeconomics in Clinical Trials, 2nd ed. Edited by, Spiker B. Philadelphia, Lippincott-Raven, 1996, pp 309–321
48.
Kaplan RM, Bush JW: Health-related quality of life measurement for evaluation research and policy analysis. Health Psychol 1982; 1:61–80
49.
Pyne JM, Patterson TL, Kaplan RM, Gillin JC, Koch WL, Grant I: Assessment of the quality of life of patients with major depression. Psychiatr Serv 1997; 48:224–230
50.
Pyne JM, Patterson TL, Kaplan RM, Ho S, Gillin JC, Golshan S, Grant I: Preliminary longitudinal assessment of quality of life in patients with major depression. Psychopharmacol Bull 1997; 33:23–29
51.
Beebe TJ, Harrison PA, McRae JA, Asche SE: Evaluating behavioral health services in Minnesota’s Medicaid population using the Experience of Care and Health Outcomes (ECHO) Survey. J Health Care Poor Underserved 2003; 14:608–621
52.
Little RC, Milliken GA, Stroup WW, Wolfinger RD: SAS System for Mixed Models. Cary, NC, SAS Institute Inc., 1996
53.
Bursac Z, Gauss CH, Williams DK, Hosmer DW: Purposeful selection of variables in logistic regression. Source Code Biol Med 2008; 3:17
54.
Hogan JW, Laird NM: Intention-to-treat analyses for incomplete repeated measures data. Biometrics 1996; 52:1002–1017
55.
Simon GE, Revicki DA, Grothaus L, Vonkorff M: SF-36 summary scores: are physical and mental health truly distinct? Med Care 1998; 36:567–572
56.
Spates CR, Pagoto S, Kalata A: A qualitative and quantitative review of behavioral activation treatment of major depressive disorder. Behav Analyst Today 2006; 74:508–518
57.
Dimidjian S, Hollon SD, Dobson KS, Schmaling KB, Kohlenberg RJ, Addis ME, Gallop R, McGlinchey JB, Markley DK, Gollan JK, Atkins DC, Dunner DL, Jacobson NS: Randomized trial of behavioral activation, cognitive therapy, and antidepressant medication in the acute treatment of adults with major depression. J Consult Clin Psychol 2006; 74:658–670
58.
Riebe G, Fan MY, Unützer J, Vannoy S: Activity scheduling as a core component of effective care management for late-life depression. Int J Geriatr Psychiatry 2012; 27:1298–1304
59.
Hunkeler EM, Meresman JF, Hargreaves WA, Fireman B, Berman WH, Kirsch AJ, Groebe J, Hurt SW, Braden P, Getzell M, Feigenbaum PA, Peng T, Salzer M: Efficacy of nurse telehealth care and peer support in augmenting treatment of depression in primary care. Arch Fam Med 2000; 9:700–708

Information & Authors

Information

Published In

Go to American Journal of Psychiatry
Go to American Journal of Psychiatry
American Journal of Psychiatry
Pages: 414 - 425
PubMed: 23429924

History

Received: 28 May 2012
Revision received: 17 September 2012
Accepted: 12 October 2012
Published online: 1 April 2013
Published in print: April 2013

Authors

Details

John C. Fortney, Ph.D.
From the Division of Health Services Research, Department of Psychiatry, College of Medicine, the Department of Biostatistics, College of Public Health, and the Center for Distance Health, University of Arkansas for Medical Sciences, Little Rock; Health Services Research and Development and the South Central Mental Illness Education and Clinical Center, Central Arkansas Veterans Healthcare System, North Little Rock; Community Health Centers of Arkansas, North Little Rock; United Family Services, Little Rock; and the Department of Mental Health Law and Policy, College of Behavioral and Community Sciences, University of South Florida, Tampa.
Jeffrey M. Pyne, M.D.
From the Division of Health Services Research, Department of Psychiatry, College of Medicine, the Department of Biostatistics, College of Public Health, and the Center for Distance Health, University of Arkansas for Medical Sciences, Little Rock; Health Services Research and Development and the South Central Mental Illness Education and Clinical Center, Central Arkansas Veterans Healthcare System, North Little Rock; Community Health Centers of Arkansas, North Little Rock; United Family Services, Little Rock; and the Department of Mental Health Law and Policy, College of Behavioral and Community Sciences, University of South Florida, Tampa.
Sip B. Mouden, M.S., C.R.C.
From the Division of Health Services Research, Department of Psychiatry, College of Medicine, the Department of Biostatistics, College of Public Health, and the Center for Distance Health, University of Arkansas for Medical Sciences, Little Rock; Health Services Research and Development and the South Central Mental Illness Education and Clinical Center, Central Arkansas Veterans Healthcare System, North Little Rock; Community Health Centers of Arkansas, North Little Rock; United Family Services, Little Rock; and the Department of Mental Health Law and Policy, College of Behavioral and Community Sciences, University of South Florida, Tampa.
Dinesh Mittal, M.D.
From the Division of Health Services Research, Department of Psychiatry, College of Medicine, the Department of Biostatistics, College of Public Health, and the Center for Distance Health, University of Arkansas for Medical Sciences, Little Rock; Health Services Research and Development and the South Central Mental Illness Education and Clinical Center, Central Arkansas Veterans Healthcare System, North Little Rock; Community Health Centers of Arkansas, North Little Rock; United Family Services, Little Rock; and the Department of Mental Health Law and Policy, College of Behavioral and Community Sciences, University of South Florida, Tampa.
Teresa J. Hudson, Pharm.D.
From the Division of Health Services Research, Department of Psychiatry, College of Medicine, the Department of Biostatistics, College of Public Health, and the Center for Distance Health, University of Arkansas for Medical Sciences, Little Rock; Health Services Research and Development and the South Central Mental Illness Education and Clinical Center, Central Arkansas Veterans Healthcare System, North Little Rock; Community Health Centers of Arkansas, North Little Rock; United Family Services, Little Rock; and the Department of Mental Health Law and Policy, College of Behavioral and Community Sciences, University of South Florida, Tampa.
Gary W. Schroeder, Ph.D.
From the Division of Health Services Research, Department of Psychiatry, College of Medicine, the Department of Biostatistics, College of Public Health, and the Center for Distance Health, University of Arkansas for Medical Sciences, Little Rock; Health Services Research and Development and the South Central Mental Illness Education and Clinical Center, Central Arkansas Veterans Healthcare System, North Little Rock; Community Health Centers of Arkansas, North Little Rock; United Family Services, Little Rock; and the Department of Mental Health Law and Policy, College of Behavioral and Community Sciences, University of South Florida, Tampa.
David K. Williams, Ph.D.
From the Division of Health Services Research, Department of Psychiatry, College of Medicine, the Department of Biostatistics, College of Public Health, and the Center for Distance Health, University of Arkansas for Medical Sciences, Little Rock; Health Services Research and Development and the South Central Mental Illness Education and Clinical Center, Central Arkansas Veterans Healthcare System, North Little Rock; Community Health Centers of Arkansas, North Little Rock; United Family Services, Little Rock; and the Department of Mental Health Law and Policy, College of Behavioral and Community Sciences, University of South Florida, Tampa.
Carol A. Bynum, Ph.D.
From the Division of Health Services Research, Department of Psychiatry, College of Medicine, the Department of Biostatistics, College of Public Health, and the Center for Distance Health, University of Arkansas for Medical Sciences, Little Rock; Health Services Research and Development and the South Central Mental Illness Education and Clinical Center, Central Arkansas Veterans Healthcare System, North Little Rock; Community Health Centers of Arkansas, North Little Rock; United Family Services, Little Rock; and the Department of Mental Health Law and Policy, College of Behavioral and Community Sciences, University of South Florida, Tampa.
Rhonda Mattox, M.D.
From the Division of Health Services Research, Department of Psychiatry, College of Medicine, the Department of Biostatistics, College of Public Health, and the Center for Distance Health, University of Arkansas for Medical Sciences, Little Rock; Health Services Research and Development and the South Central Mental Illness Education and Clinical Center, Central Arkansas Veterans Healthcare System, North Little Rock; Community Health Centers of Arkansas, North Little Rock; United Family Services, Little Rock; and the Department of Mental Health Law and Policy, College of Behavioral and Community Sciences, University of South Florida, Tampa.
Kathryn M. Rost, Ph.D.
From the Division of Health Services Research, Department of Psychiatry, College of Medicine, the Department of Biostatistics, College of Public Health, and the Center for Distance Health, University of Arkansas for Medical Sciences, Little Rock; Health Services Research and Development and the South Central Mental Illness Education and Clinical Center, Central Arkansas Veterans Healthcare System, North Little Rock; Community Health Centers of Arkansas, North Little Rock; United Family Services, Little Rock; and the Department of Mental Health Law and Policy, College of Behavioral and Community Sciences, University of South Florida, Tampa.

Notes

Address correspondence to Dr. Fortney ([email protected]).

Funding Information

The authors report no financial relationships with commercial interests.
Supplementary Material
Supported by NIMH grant R01 MH076908/MH076908-04S1 to Dr. Fortney.

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