Sage Journals: Discover world-class research

Abstract

Background: Depression concomitant with chronic medical conditions is common and burdensome in primary care. Objective: To assess the effectiveness of practice-based interventions for improving depression and chronic medical outcomes. Data Sources: MEDLINE, Embase, the Cochrane Library, CINAHL, and PsycINFO from inception to June 11, 2012. Study Selection, Appraisal, and Synthesis: Two reviewers independently selected, extracted data from, and rated the quality of trials and systematic reviews. Strength of evidence (SOE) was graded using established criteria. Results: Twenty-four published articles reported data from 12 studies, all at least 6 months long. All studies compared a form of collaborative care with usual or enhanced usual care. Studies evaluated adults with arthritis, cancer, diabetes, heart disease, HIV, or multiple medical conditions. Meta-analyses found that intervention recipients achieved greater improvement than controls in depression symptoms, response, remission, and depression-free days (moderate SOE); satisfaction with care (moderate SOE); and quality of life (moderate SOE). Few data were available on outcomes for chronic medical conditions. Meta-analyses revealed that patients with diabetes receiving collaborative care exhibited no difference in diabetes control compared with control groups (change in HbA1c: weighted mean difference 0.13, 95% confidence interval = −0.22 to 0.48 at 6 months; 0.24, 95% confidence interval = −0.14 to 0.62 at 12 months; low SOE). The only study to use HbA1c as a predefined outcome measure and a “treat-to-target” intervention for diabetes as well as depression, TEAMcare, reported significant reductions in HbA1c (7.42 vs 7.87 at 6 months; 7.33 vs 7.81 at 12 months; overall P < .001). Limitations: Few relevant trials reported on medical outcomes. Conclusions: Collaborative care interventions improved outcomes for depression and quality of life in primary care patients with varying medical conditions. Few data were available on medical outcomes. Future studies of concomitant depression and chronic medical conditions should consider measures of medical outcomes as primary outcomes.

Keywords

collaborative care depression chronic disease primary care disease management health outcomes

Introduction

The arena of mental health and primary care is moving from consideration of single conditions and their outcomes to more real-world, complex-care paradigms.^1,2 However, to date, no synthesis has been done of the evidence on practice-based interventions that accounts for the primary care patient with multiple chronic conditions^3,4 and examines both mental health and chronic medical outcomes simultaneously. Repeated evidence reviews show the benefits of integrated and collaborative care models, as compared with usual care, on depression outcomes in the general health setting, but it remains unclear whether better treatment of depression in primary care can also improve chronic medical outcomes, such as for diabetes.^{5
-7}

Half of all Americans live with a chronic medical condition⁸ and up to one quarter of people living with chronic medical conditions have limitations in daily activity.⁸ Living with chronic disease also takes a personal and emotional toll on patients and their families, owing to significant reductions in quality of life.⁸ Depression is common in patients with chronic medical conditions, including arthritis (13% to 20%),^9,10 heart disease (10% to 47%),¹¹ diabetes (11% to 31%),^12,13 asthma and chronic obstructive pulmonary disease (27% for each),^14,15 and cancer (9% to 50%).^16,17 Depression among people with chronic medical conditions has also been linked to an increase in health care utilization, disability, and work absenteeism when compared with those without depression, even after controlling for the varying burden of the chronic medical condition.^18,19

For the Agency for Healthcare Research and Quality, we conducted a systematic review and meta-analysis to summarize the body of evidence that examines the effectiveness of practice-based interventions aimed at improving depression or both depression and chronic medical conditions in adult primary care patients with depression and chronic medical condition(s).²⁰ We were interested in interventions that targeted the care process within a system of care, such as coordinated care, integrated care, or collaborative care; medication-only studies or psychotherapy-only studies were not the focus of this report.

Methods

We developed and followed a standard protocol. A technical report that details methods and includes search strategies and additional evidence tables is available at http://www.effectivehealthcare.ahrq.gov/reports/final.cfm. This article reports on mental health outcomes, chronic medical outcomes, and harms.

Data Sources and Searches

We searched MEDLINE, Embase, the Cochrane Library, CINAHL, and PsycINFO from the inception of each database (1948, 1947, 1898, 1937, and 1880, respectively) through June 11, 2012, limited to English-language articles. We used Medical Subject Headings as search terms when available and key words when appropriate, focusing on terms to describe the relevant population and interventions. We consulted with experts in the field and manually searched reference lists of pertinent reviews, included trials, and background articles to look for any relevant citations that our searches might have missed.

Study Selection

We developed inclusion and exclusion criteria with respect to populations, interventions, comparators, outcomes, timing, settings, and study designs.^21,22 We included controlled studies of at least 6 months’ duration in adults (age 18 years or older) with depression and one or more chronic medical conditions defined as priority conditions by the Agency for Healthcare Research and Quality²³ and the Institute of Medicine²⁴: arthritis; diabetes; asthma or chronic obstructive pulmonary disease; cancer; chronic pain; stroke; HIV/AIDS; heart disease, heart failure, myocardial ischemia, coronary artery bypass graft, postmyocardial infarction, and coronary artery disease; “complex” patients with multiple comorbidities; and frailty due to old age. We also searched for systematic reviews of such studies.

Depression was defined as meeting criteria for a disorder as determined by valid and reliable measures with established cut points but not necessarily confirmed by gold standard interview; we excluded subthreshold symptoms and minor depression. Included studies must have used practice-based interventions aimed at improving the mental health condition or both the mental health and chronic medical condition(s). We defined “practice-based” as any intervention that (a) targets the care process within a system of care and (b) aims to improve depression or both depression and chronic medical conditions. Examples of practice-based interventions include but are not limited to coordinated care, integrated care, and collaborative care; they often involve a care manager. Each of these terms has varying, and possibly overlapping definitions and is not specifically defined for the purposes of this report. In general, we perceive them broadly to mean primary care providers and mental health providers working together to address the comprehensive needs of the patient. Eligible controls were other practice-based interventions or usual care.

Two investigators independently reviewed titles and abstracts, and then another 2 investigators independently reviewed the full text of all articles marked for possible inclusion to determine final inclusion/exclusion. Disagreements were resolved by discussion and consensus among all investigators, as facilitated by a senior member of the team most experienced in comparative effectiveness research methods.

Data Extraction and Quality Assessment

We designed and used structured forms to extract pertinent information from each article, including information about the methods and populations, interventions, comparators, outcomes, timing, settings, and study designs. All data extractions were reviewed for completeness and accuracy by a second team member.

To assess the quality (internal validity) of studies, we used predefined criteria based on those developed by the United States Preventive Services Task Force (ratings: good, fair, or poor)²⁵ and the University of York Centre for Reviews and Dissemination.²⁶ These included assessment of the adequacy of randomization, allocation concealment, similarity of groups at baseline, masking, attrition, and whether intention-to-treat analysis was used. Two independent reviewers assigned quality ratings for each study. Disagreements were resolved by consulting an experienced member of the team. Studies with significant risk of bias (e.g., stemming from serious errors in design or analysis) that may invalidate their results were rated “poor” and excluded from this review (N = 2).

Data Synthesis and Analysis

Quantitative analyses were conducted of outcomes reported by a sufficient number of studies that were homogeneous enough for us to justify combining their results. We used random-effects models to estimate pooled effects.²⁷ For continuous outcomes, we used the weighted mean difference as the effect measure; if the measurement scale differed among trials, we calculated the standardized mean difference. For most dichotomous outcomes, we report risk differences. Sensitivity analyses were conducted for all analyses in which considerable heterogeneity was present (ie, I ² statistic greater than 75%).

When quantitative analyses were not appropriate (e.g., because of heterogeneity, insufficient numbers of similar studies, or insufficiency or variation in outcome reporting), we synthesized the data qualitatively.

We graded the strength of evidence (SOE) based on the guidance established for the Evidence-Based Practice Center Program.²⁸ Two reviewers assessed each domain for each key outcome, and differences were resolved by consensus.

Results

Twenty-four published articles reported data from 12 studies (9 randomized controlled trials and 3 preplanned subgroup analyses from a separate randomized controlled trial; Figure 1).

Figure 1.

PRISMA flow diagram.

Results are organized by main outcomes and grouped by medical condition(s) when possible. Our results pertain to the general adult population; no studies that met our inclusion criteria reported on young adults or pregnant women. Regarding older adults, one study selectively recruited participants aged 60 years or older^{29

-33}; however, participants across all studies in this review tended to be middle aged or older (mean age = 59 years; range of means = 47-72), so we do not report results for older adults separately. Several studies reported on traditionally underrepresented populations, including women,^{34
-36} Spanish speakers,^{34

-37} and predominantly African American male veterans with HIV;³⁸ we report these results in the context of overall results by medical condition, not in separate categories (Table 1).

Table 1.

Characteristics of Included Studies, by Chronic Medical Condition.

Author(s) (Year)	Study Name	Country	Setting	n	Duration (Months)	Depression-Related Eligibility Requirement	Baseline Depression Score^a	Quality^b
Arthritis
Lin et al (2003)³³; Lin et al (2006)³⁰	IMPACT	US	PC	1001	24	Current DSM-IV diagnosis of MDD and/or dysthymia	SCL-20: 1.7	Fair
Cancer
Dwight-Johnson et al (2005)³⁴	MODP	US	PC-like	55	8	Major depression per PHQ-9 or dysthymia per PRIME-MD	PHQ-9: 12.6-13.4	Fair
Ell et al (2008)³⁶; Ell et al (2011)³⁹	ADAPt-C	US	PC-like	472	24	PHQ-9 ≥10 or dysthymia per DSM-IV SCI	PHQ-9: 13.1	Fair
Fann et al (2009)²⁹	IMPACT	US	PC	215	24	Major depression or dysthymia per DSM-IV SCI	SCL-20: 1.6	Fair
Strong et al (2008)⁴⁰	SMaRT Oncology 1	UK	PC-like	200	12	HADS ≥15 and major depression per DSM-IV SCI and SCL-20 ≥1.75	SCL-20: 2.3-2.4 (median)	Fair
Diabetes
Ell et al (2010)³⁵; Ell et al (2011)⁴¹; Hay et al (2012)⁴²	MDDP	US	PC and PC-like	387	24	PHQ-9 ≥10	SCL-20: 1.4-1.7	Fair
Ciechanowski et al (2006)⁷; Katon et al (2008)⁴³; Katon et al (2004)⁵; Kinder et al (2006)⁴⁴; Lin et al (2006)⁴⁵; Simon et al (2007)⁴⁶	Pathways	US	PC	329	60	PHQ-9 ≥10 and SCL-20 ≥1.1	SCL-20: 1.63-1.71	Fair
Williams et al (2004)³²; Katon et al (2006)³¹	IMPACT	US	PC	417	24	Major depression or dysthymia per DSM-IV SCI	SCL-20: 1.67-1.72	Fair
Heart disease
Rollman et al (2009)⁴⁷	Bypassing the Blues	US	Unclear^c	302	8	PHQ-9 ≥11	PHQ-9: 13.5-13.6; HRSD: 15.9-16.5	Good
HIV
Pyne et al (2011)³⁸	HITIDES	US	PC-like	276	12	PHQ-9 ≥10	PHQ-9: 15.7-16.0; SCL-20: 1.8-1.9	Good
Multiple conditions
Katon et al (2010)⁴⁸; Von Korff (2011)⁴⁹; Lin et al (2012)⁵⁰	TEAMcare^d	US	PC	214	12	PHQ-9 ≥10	PHQ-9: 13.9-14.7; SCL-20: 1.7	Fair
Vera et al (2010)³⁷	None	US (Puerto Rico)	PC	179	6	PHQ-9 (cutoff NR) and SCL-20 >1.0	SCL-20: 2.2-2.3	Good

Abbreviations: ADAPt-C = Alleviating Depression Among Patients with Cancer; DSM-IV = Diagnostic and Statistical Manual of Mental Disorders, fourth edition; MDD, major depressive disorder; HADS = Hospital Anxiety and Depression Scale; HITIDES = HIV Implementation of Translating Initiatives for Depression into Effective Solutions; HRSD = Hamilton Rating Scale for Depression; IMPACT = Improving Mood—Promoting Access to Collaborative Treatment; MDDP = Multifaceted Diabetes and Depression Program; MODP = Multifaceted Oncology Depression Program; NR = not reported; PC = primary care; PHQ = Patient Health Questionnaire; PRIME-MD = Primary Care Evaluation of Mental Disorders; SCI = structured clinical interview; SCL = Symptoms Checklist; SMaRT = Symptom Management Research Trial in Oncology; UK = United Kingdom; US = United States.

Overall mean as reported, range of means for treatment groups, or overall mean calculated using mean age from each treatment group.

These criteria assess for biases including appropriate masking/blinding, attrition, and intent-to-treat analyses. In general terms, a “good” study has the least risk of bias and its results are considered to be valid. A “fair” study is susceptible to some bias but probably not sufficient to invalidate its results.

Patients were recruited before hospital discharge; intervention took place over the telephone.

Diabetes and/or heart disease.

Sample sizes ranged from 55 to 1001, and study duration ranged from 6 to 60 months. Most trials were conducted in the United States (including one in Puerto Rico³⁷); one took place in Scotland.⁴⁰ All included studies characterized their respective intervention as a form of collaborative care, not another form of a practice-based intervention (such as integrated care). Three studies described in 5 publications^{29

-33} are secondary analyses from the Improving Mood—Promoting Access to Collaborative Treatment (IMPACT) trial⁵¹; it tested a collaborative care depression intervention in older adult primary care patients, including preplanned subgroups of patients with arthritis, cancer, and diabetes. For ease of interpretation, we consider each subgroup a unique “study.” Consequently, our results include data from 12 studies (9 stand-alone randomized controlled trials and 3 IMPACT subgroups). The chronic medical conditions included arthritis,^30,33 cancer,^29,34,36,40 diabetes,^{5,7,35,43

-46} heart disease,⁴⁷ and HIV.³⁸ Two studies selected patients with one or more active chronic medical conditions.^37,48 Each study compared the intervention with usual or enhanced usual care (Table 2).

Table 2.

Characteristics of Interventions, by Chronic Medical Condition.

Author(s) (Year), Study Name	Intervention Summary	Comparator	Intervention Delivery Method	Delivered by
Arthritis
Lin et al (2003)³³; Lin et al (2006),³⁰ IMPACT	Care management based on stepped care treatment algorithm; patient preference for treatment: antidepressants or problem-solving therapy (6-8 sessions); monitoring of treatment response (“IMPACT model”)	Usual care^a	In-person and telephone	Depression care specialist (nurse or clinical psychologist) with psychiatrist supervision
Cancer
Dwight-Johnson et al (2005),³⁴ MODP	Described as being based on the IMPACT model	Usual care^a	In-person and telephone	Bilingual cancer depression care specialist (master’s level social worker)
Ell et al (2008)³⁶; Ell et al (2011),³⁹ ADAPt-C	Described as being based on the IMPACT model	Enhanced usual care^a	In-person and telephone	Bilingual cancer depression care specialist (master’s level social worker) with psychiatrist supervision
Fann et al (2009),²⁹ IMPACT	IMPACT model	Usual care^a	In-person and telephone	Depression care specialist (nurse or clinical psychologist) with psychiatrist supervision
Strong et al (2008),⁴⁰ SMaRT Oncology 1	Manual-based depression care for people with cancer; up to 10 sessions of problem-solving treatment to address coping; progress monitored by telephone; advice on choice of antidepressant if requested	Usual care^a	In-person and telephone	Nurses with no psychiatry experience with psychiatrist supervision
Diabetes
Ell et al (2010)³⁵; Ell et al (2011)⁴¹; Hay et al (2012),⁴² MDDP	Described as being based on the IMPACT model	Enhanced usual care^a	In-person and telephone	Bilingual diabetes depression care specialist (master’s level social worker) with psychiatrist supervision
Ciechanowski et al (2006)⁷; Katon et al (2008)⁴³; Katon et al (2004)⁵; Kinder et al (2006)⁴⁴; Lin et al (2006)⁴⁵; Simon et al (2007),⁴⁶ Pathways	Described as being based on the IMPACT model	Enhanced usual care^a	In-person and telephone	Depression clinical specialist (nurse) with psychiatrist supervision
Williams et al (2004)³²; Katon et al (2006),³¹ IMPACT	IMPACT model	Usual care^a	In-person and telephone	Depression care specialist (nurse or clinical psychologist) with psychiatrist supervision
Heart disease
Rollman et al (2009),⁴⁷ Bypassing the Blues	Education on depression and CHD; support to PCP on antidepressants; referral to mental health specialists as needed; phone monitoring for symptoms	Usual care^a	Telephone	Nurse care manager with psychiatrist supervision
HIV
Pyne et al (2011),³⁸ HITIDES	Stepped care approach; education/activation; recommendations for medications and/or mental specialty referral; Web-based decision support	Usual care^a	Telephone	Off-site depression care team: nurse depression care manager, pharmacist, psychiatrist with psychiatrist supervision
Multiple conditions
Katon et al (2010)⁴⁸; Von Korff et al (2011)⁴⁹; Lin et al (2012),⁵⁰ (TEAMcare^b)	Support for self-care of depression (including pharmacotherapy) and individualized goal-setting; treat-to-target program for DM and/or CHD; motivational coaching; maintenance support	Enhanced usual care^a	In-person and telephone	Medically supervised nurse trained in diabetes education with psychiatrist supervision
Vera et al (2010),³⁷ None	Depression education; antidepressant medications and/or 13 sessions of cognitive behavioral therapy	Usual care^a	In-person and telephone	Master’s level counselor or psychologist with psychiatrist supervision

Abbreviations: ADAPt-C, Alleviating Depression Among Patients with Cancer; CHD, coronary heart disease; DM, diabetes mellitus; HITIDES, HIV Implementation of Translating Initiatives for Depression into Effective Solutions; IMPACT, Improving Mood—Promoting Access to Collaborative Treatment; MDDP, Multifaceted Diabetes and Depression Program; MODP, Multifaceted Oncology Depression Program; PCP = primary care provider.

Usual care consisted of informing patients of their depression status and advising them to share this information with their primary care provider. Enhanced usual care usually included some degree of additional communication between the research staff or diabetes care manager and the patient’s primary care provider and/or family about the patient’s depression status.

Diabetes and/or heart disease.

Mental Health Outcomes

We summarize the mental health-related outcomes and SOE in Table 3. These results were consistent across medical conditions and reflect clinically meaningful changes on well-accepted measures of depression (the Patient Health Questionnaire–9, the Symptom Checklist–20, the Symptom Checklist–90, and the Hamilton Rating Scale for Depression–17, all using valid and reliable cut-points). Figure 2 shows forest plots for the comparison between collaborative care interventions and usual care on the outcome of depression response (at least 50% reduction in depression score) at 6 and 12 months. The evidence showed that 5 patients would need to be treated to achieve one more depression response than would be seen with usual care at 6 months, with a number needed to treat of 6 patients at 12 months.

Table 3.

Summary of Results for Collaborative Care Interventions Compared With Controls for People With Depression and One or More Chronic Medical Conditions: Mental Health Outcomes.

Outcome	Summary of Results	Strength of Evidence
Symptom improvement	Greater symptom improvement scores in intervention groups at both 6 months (SMD, 0.45; 95% CI, 0.29-0.61; 7 studies^{5,29,32,36,40,47,48}) and 12 months (SMD, 0.47; 95% CI, 0.29-0.65; 6 studies^{5,29,32,36,40,48}) compared with control groups. Benefits were sustained through 24 months, but the magnitude of benefit was reduced (WMD, 0.18; 95% CI, 0.10-0.26; 3 studies^5,29,35)	Moderate
Depression-free days	More depression-free days at 12 months for those in intervention groups than usual care groups (5 studies^{5,29 -33,35,38}, range of differences between intervention and control groups: 20-59 days)	Moderate
Response (≥50% reduction)	Higher rates of depression response in intervention groups than usual care, based on 10 studies^{5,29,33 -38,47,48} (NNT, 5 at 6 months; NNT, 6 at 12 months). Benefits persisted, but to a lesser degree, at 18 months (RD 0.12; 95% CI, 0.02-0.22; 3 studies^5,29,36)	Moderate
Remission	Remission of depression favored intervention over usual care at 6 months and at 12 months based on 5 studies^{29,33,36,38,39,41} (NNT, 8 at 6 months; NNT, 12.5 at 12 months). Benefits persisted at 18 months, but showed no difference between groups at 24 months	Moderate
Recurrence	Only 1 study^36,39 (of patients with cancer) addressed recurrence as an outcome, and showed no difference between groups at 18 or 24 months	Insufficient
Treatment adherence	Mixed results: 1 study⁴⁵ reported significantly greater adherence to antidepressants in the intervention arm at 6 and 12 months; the other³⁸ reported no difference between groups at 6 and 12 months	Insufficient
Treatment satisfaction	Greater satisfaction with care for intervention participants than controls at 12 months (RD, 0.21; 95% CI, 0.11-0.30; 4 studies^5,29,35,48),^a and this extended to 24 months (RD, 0.14, 95% CI, 0.06-0.21; 3 studies^29,35,36)	Moderate
Use of antidepressants	Greater antidepressant use for collaborative care interventions than for usual care at 12 months (RD, 0.23; 95% CI, 0.15-0.30; 5 studies^{29,32,33,35,36,38}),^b but not 6 months (RD, 0.09; 95% CI, −0.02 to 0.20; 3 studies^29,38,47)	Low
MH-related quality of life	Greater mental health–related quality of life for patients in collaborative care intervention arms than usual care at 6 and 12 months using the mental component of the Medical Outcomes Study Short Form (WMD, 2.98; 95% CI, 1.41-4.55 at 12 months; 4 studies^32,35,36,38)	Moderate
MH care utilization	At 6 months, greater use of any MH services other than or in addition to antidepressants with the collaborative care interventions (range: 40% to 97%) than with usual care (range: 15% to 57%), based on 2 studies.^29,37 At 12 months, greater use with collaborative care (range: 42% to 84%) than with usual care (range: 16% to 33%), based on 4 studies^{29,35,39,41,45}	Low

Abbreviations: CI = confidence interval; HITIDES = HIV Implementation of Translating Initiatives for Depression into Effective Solutions; MH = mental health; NA = not applicable; NNT = number needed to treat; RCT = randomized controlled trial; RD = risk difference; SMD = standardized mean difference; WMD = weighted mean difference.

Results are from meta-analysis of the 4 trials that reported satisfaction for both intervention and control arms. Two additional trials reported treatment satisfaction for the intervention arm but not the usual care arm.

Results of the meta-analysis excluding the HITIDES data, which was an outlier and accounted for significant heterogeneity.

Figure 2.

Forest plots for depression score response (at least 50% reduction) for practice-based interventions compared with controls.

Meta-analysis of data from 4 studies^32,35,36,38 showed greater mental health–related quality of life for patients in collaborative care intervention arms than usual care at 6 and 12 months using the mental component of the Medical Outcomes Study Short Form. One suicide was reported in the usual care arm of a cancer trial.⁴⁰ No data were available on sick days or employment stability (insufficient SOE).

Chronic Medical Outcomes

We summarize the effects and SOE of collaborative care interventions on outcomes for the specified chronic medical condition(s) in Table 4. For most chronic medical conditions of interest, we found just one study. We found multiple studies of people with diabetes and depression.

Table 4.

Summary of Results for Collaborative Care Interventions Compared With Controls for People With Depression and One or More Chronic Medical Conditions: Chronic Medical Outcomes.

General Outcome	Specific Disease-Related Outcome	Summary of Results	Strength of Evidence
Symptom improvement	Arthritis: pain	Mixed evidence from 1 subgroup analysis³³	Insufficient
Symptom improvement	HIV: symptom severity	Mixed evidence from 1 RCT³⁸	Insufficient
Response	Diabetes: HbA1c	Meta-analysis: WMD, 0.13; 95% CI, −0.22 to 0.48 at 6 months (3 studies^32,35,48); WMD, 0.24; 95% CI, −0.14 to 0.62 at 12 months (3 studies^32,35,48); a single study⁴¹ showed no difference between groups at 18 and 24 months	Low
Response	Heart disease: ≥10 mm Hg decrease in SBP	In 1 RCT⁴⁷ at 12 months, 41 intervention patients and 25 controls achieved response (P = .016) from an overall sample of 214	Insufficient
Adherence	Cancer: followed treatment	1 RCT³⁴ reported greater adherence to recommended treatment (OR 3.51; 95% CI, 0.82-15.03)	Insufficient
	Diabetes: diet	No between-group difference at any time point in 3 studies^32,45,48	Moderate
	Diabetes: exercise	3 of 3 studies^32,45,48 found no difference between groups at 6 months; of these same trials, 2 studies^32,45 of 3 found no difference at 12 months	Low
	Diabetes: medications	Mixed evidence from 2 studies^32,45	Insufficient
	HIV: medications	Insufficient evidence from 1 RCT³⁸ to draw conclusions	Insufficient
Satisfaction with care	Diabetes, heart disease, or both	1 RCT⁴⁸ reported greater satisfaction in the intervention group compared with controls at 12 months (86% vs 70%)	Insufficient
Mortality	All conditions	Meta-analyses revealed no difference between groups, with few overall events at 6 months (RD, 0.00; 95% CI, −0.02 to 0.02; 7 studies^{29,32 -34,36,38,47}) and 12 months (RD, 0.00; 95% CI, −0.02 to 0.01; 7 studies^{29,32,33,36,38,40,48})	Moderate
Physical health quality of life	All conditions	Patients receiving collaborative care interventions generally reported significantly greater physical health quality of life than control patients at 6 and 12 months (6 studies,^{29,33,34,36,38,39,41} based on several different measures^a	Moderate

Abbreviations: OR, odds ratio; CI, confidence interval; HbA1c = hemoglobin A1c; mm Hg = millimeters of mercury; RCT = randomized controlled trial; SBP = systolic blood pressure; WMD = weighted mean difference.

Five studies^{32,35,36,38,47} measured self-reported quality of life using the physical component of SF-12^32,35,36,38 or SF-36.⁴⁷ Four studies^29,33,35,48 used the Sheehan Disability Scale of Functional Impairment.⁵² One study³⁸ used the Quality of Well-Being Self-Administered Scale (QWB-SA). In 3 studies,^29,30,32,33 patients were asked to self-rate on a scale that ranged from 0 to 10.

HbA1c was reported as a measure of response in 4 trials described in 5 publications^{5,32,35,41,48} of people with diabetes; baseline HbA1c ranged from 7.28% to 9.03%. Our meta-analyses of the 3 trials (4 publications) with usable data^32,35,41,48 found no significant differences between intervention and control groups at either 6 or 12 months (Figure 3); findings were somewhat inconsistent and lacked precision (low SOE). However, the only study to use HbA1c as a predefined outcome measure, the TEAMcare study,⁴⁸ reported significant differences in HbA1c. The values were as follows for intervention versus control groups: 8.14 versus 8.04 at baseline; 7.42 versus 7.87 at 6 months; and 7.33 versus 7.81 at 12 months (overall P < .001).

Figure 3.

Forest plots for reduction in HbA1c for practice-based interventions compared with controls among adults with diabetes.

Meta-analysis of data from 6 studies^{29,33,34,36,38,39,49} found that patients receiving collaborative care interventions generally reported significantly greater physical health quality of life than control patients at 6 and 12 months. Six trials,^{31,35,36,40,43,48} using various methods, reported costs of the intervention. Using the reported per-patient intervention costs and accounting for variability in study duration, we estimated the average cost of the intervention per patient was $705.00. Individual studies measured other aspects of cost but were not amenable to pooling.

Harms

Very few data were reported on harms, leaving insufficient evidence to draw conclusions. Only the TEAMcare study, in patients with depression and comorbid diabetes and/or heart disease,⁴⁸ defined adverse events; the investigators reported higher rates of mild (e.g., medication side effects) and of moderate (e.g., falls) adverse events in the intervention arm.

Discussion

Our findings reinforce the evidence for the effectiveness of collaborative care interventions for treating depression in primary care.⁵³ Moreover, they add a level of detail that had previously not been systematically reviewed. We selected trials that required the diagnosis of one or more chronic medical conditions (rather than generic primary care samples), and we reported on both the depression and the chronic medical outcomes. This review also extended the parameters of primary care to include settings in which certain patients with chronic disease receive the majority of their care. We found that recipients of collaborative care had significantly greater improvement in depression outcomes as compared with patients receiving usual care, for people with arthritis, cancer, diabetes, heart disease, and HIV.

Although the relationship between depression and chronic disease is established,^13,54,55 the extent to which successful treatment of depression improves chronic medical conditions remains unknown. As we move to consider shared savings programs, such as accountable care organizations⁵⁶ and the patient-centered medical home,⁵⁷ consumers and payers are eager to identify interventions and processes that can streamline care for multiple conditions and improve the quality and efficiency of care. Our review shows that investigators are beginning to examine these outcomes, particularly in diabetes, although largely as secondary outcomes and with negative or inconclusive findings at present. We excluded some relevant studies because of duration of follow-up less than 6 months⁵⁸ or because the treatment occurred outside the purview of a primary care–like setting.^{59
-61} However, our inability to answer the basic question posed by a primary care provider, “Will treating my patient’s depression (with an evidence-based collaborative care program) improve his or her medical conditions?” was both surprising and disappointing.

One study in the review, TEAMcare,⁴⁸ is unique because it identified markers of disease risk for multiple conditions as primary outcomes. Using a guideline-based “treat-to-target” approach delivered by a medically trained nurse, the investigators targeted patients with poorly controlled diabetes, coronary artery disease, or both and coexisting depression; their aim was to reduce overall risk factors. This approach differs from the traditional model, in which the focus is on collaborative care of depression, presumably in the hope that treating depression will improve overall health. Perhaps partly because of the benefits of having an integrated health care system, TEAMcare recipients showed clear improvements not only in depression but also in reducing HbA1c and systolic blood pressure to target goals.

The paucity of data on harms in the included studies could be attributed to increased rates of medication adjustment related to the collaborative care intervention. Additionally, patients in the intervention arm had more frequent contacts with the care manager and thus had more opportunities to report adverse events, so findings might be the result of detection bias.

Applicability

Our findings are generally applicable to primary care patients with depression and at least one chronic medical condition, but they may not apply to patients with multiple chronic conditions. The average age across studies was 59 years, an age-group likely to have chronic disease. For that reason, we cannot speak directly to the relevance of these results to young adults with chronic disease. People of Hispanic origin (predominantly female)^35,36 and male veterans³⁸ were represented and appeared to respond similarly across outcomes, but there were too few data to analyze separately. Reported studies used clinically meaningful measures and had study durations (at least 6 months) that provided a real-world context.

Although these trials represented several settings, including primary care–like cancer and HIV clinics, they all had in common a care manager who directed the intervention. The mental health outcomes achieved might, therefore, apply only to settings that can accommodate and afford to provide such services.

Limitations

Defining the interventions of interest was challenging because we wanted to be inclusive of the widest possible range of service level interventions that occurred in the primary care setting. With input from our Technical Expert Panel, we arrived at the term practice-based to differentiate interventions relative to this review from person-level interventions such as medications or stand-alone psychotherapy. We did not find the term practice-based in the literature, but we used other eligibility criteria, a general intervention term and known interventions to inform our searches. Even though we also added the terms collaborative care, integrated care, and telemedicine to guide our search, we may have missed relevant interventions that are not indexed in these categories.

We chose to exclude studies without comparison groups because of the potential risk of bias in such studies (especially the risk of selection bias and confounding). Important and innovative systems efforts in the fields of mental health and primary care⁶² may be overlooked using these methods. However, the purpose of this review was not to uncover hypothesis-generating information but rather to find evidence with sufficiently low risk of bias to provide more definitive answers to the key questions.

Few relevant trials reported medical outcomes as a primary interest; only 1 of 12 studies⁴⁸ was specifically designed to assess medical outcomes. The remainder aimed to look at mental health outcomes in patients with different medical conditions. Finally, studies did not necessarily screen for mental health comorbidities (such as substance abuse), which may have negatively influenced medical outcomes, particularly related to self-care activities, and biased toward the null. A completely unexplored area is personality disorders, which are pervasive by nature and can prove a barrier to achieving therapeutic goals.⁶³

Research Gaps

Although it is clear that collaborative care works to improve depression in primary care, we do not know if it outperforms other practice-based interventions (such as integrated care or co-location of mental health services) because no head-to-head studies exist. We also do not know whether the effective treatment of depression in the primary care setting can alter the course of chronic disease. To determine the relative benefit of implementing collaborative care programs for depression (or other mental health conditions) on overall health, we need studies designed to measure the effectiveness of practice-based interventions on medical outcomes. The TEAMcare approach offers an example, in which treatment goals included targets for all relevant diseases and individualized approaches to reach these targets. Designing, implementing, and sustaining such approaches will not be without considerable challenge, and studies will require larger sample sizes, longer time frames, and, optimally, higher levels of joint funding from multiple institutes more used to focusing on one disease.

Conclusions

Collaborative care interventions improved outcomes for depression and quality of life in primary care patients with varying medical conditions. Few data were available on medical outcomes. Future studies of concomitant depression and chronic medical conditions should be designed to consider measures of medical outcomes as primary outcomes.

Footnotes

Acknowledgements

The authors gratefully acknowledge the contributions of Carol Woodell (Project Manager), Tania Wilkins (biostatistician), Sonia Tyutyulkova and Beth Collins-Sharp (AHRQ Task Order Officers), and Megan Van Noord (literature search).

Authors’ Note

The views expressed in this article do not represent and should not be construed to represent a determination or policy of the Agency for Healthcare Research and Quality or the US Department of Health and Human Services.

Declaration of Conflicting Interests

The author(s) declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article.

Funding

The author(s) disclosed receipt of the following financial support for the research, authorship, and/or publication of this article: This research was supported by the Agency for Healthcare Research and Quality, Contract No. 290 2007 10056 I.

Author Biographies

Lea C. Watson is a board-certified adult and geriatric psychiatrist at the University of North Carolina (UNC) School of Medicine, Department of Psychiatry. She is actively involved in clinical service, teaching and research. Dr. Watson also directs the UNC Department of Psychiatry Outpatient Clinics.

Halle R. Amick is a Research Specialist with the Research Triangle Institute-University of North Carolina Evidence-based Practice Center (RTI-UNC EPC) whose work includes reviews of screening and treatment of mental health, behavioral health, and cerebrovascular conditions.

Bradley N. Gaynes is a Professor of Psychiatry in the UNC School of Medicine and a Faculty Research Fellow of the Sheps Center for Health Services Research. He splits his time between patient care and mental health services research focusing on the integration of mental health care in primary care practices.

Kimberly A. Brownley is an Assistant Professor of Psychiatry and a principal faculty member of the UNC Stress and Health Research Program. She is trained in both experimental and clinical psychology.

Samruddhi Thaker is a Senior Research Scientist with the RTI International’s Health Care Quality and Outcomes Program. Her primary areas of interest and expertise include health services research; health care program and policy evaluation; and the development and implementation of quality reporting programs and policies at the federal, state and local levels.

Meera Viswanathan is the Director of the RTI-UNC EPC and a senior researcher at RTI International. Her areas of expertise include women’s and maternal health, child health, transmission of HIV and other STDs, research design, primary data collection, analysis of secondary data, and policy analysis.

Daniel E. Jonas is the Co-Director of the RTI-UNC EPC and an Assistant Professor in the Division of General Medicine at UNC. His research interests include comparative effectiveness, evidence-based medicine, pharmacogenomics, individualized therapy, health economics, cancer screening, anticoagulation, and patient time costs.

References

Bogner

de Vries

. Integrating type 2 diabetes mellitus and depression treatment among African Americans: a randomized controlled pilot trial. Diabetes Educ. 2010;36:284-292.

Unützer

Schoenbaum

Druss

Katon

. Transforming mental health care at the interface with general medicine: report for the presidents commission. Psychiatr Serv. 2006;57:37-47.

Schneider

O’Donnell

Dean

. Prevalence of multiple chronic conditions in the United States’ Medicare population. Health Qual Life Outcomes. 2009;7:82.

Beatty

Koczwara

Rice

Wade

. A randomised controlled trial to evaluate the effects of a self-help workbook intervention on distress, coping and quality of life after breast cancer diagnosis. Med J Aust. 2010;193(5 suppl):S68-S73.

Katon

Von Korff

Lin

. The Pathways Study: a randomized trial of collaborative care in patients with diabetes and depression. Arch Gen Psychiatry. 2004;61:1042-1049.

Bogner

Morales

Post

Bruce

. Diabetes, depression, and death: a randomized controlled trial of a depression treatment program for older adults based in primary care (PROSPECT). Diabetes Care. 2007;30:3005-3010.

Ciechanowski

Russo

Katon

. The association of patient relationship style and outcomes in collaborative care treatment for depression in patients with diabetes. Med Care. 2006;44:283-291.

Partnership for Solutions National Program Office. Chronic conditions: making the case for ongoing care. 2004. http://www.partnershipforsolutions.org/DMS/files/chronicbook2004.pdf. Accessed September 26, 2011.

Creed

. Psychological disorders in rheumatoid arthritis: a growing consensus? Ann Rheum Dis. 1990;49:808-812.

10.

Creed

Murphy

Jayson

. Measurement of psychiatric disorder in rheumatoid arthritis. J Psychosom Res. 1990;34:79-87.

11.

Bush

Ziegelstein

Patel

. Post-myocardial infarction depression. Evid Rep Technol Assess Summ. 2005;(123):1-8.

12.

Ali

Stone

Peters

Davies

Khunti

. The prevalence of co-morbid depression in adults with Type 2 diabetes: a systematic review and meta-analysis. Diabet Med. 2006;23:1165-1173.

13.

Anderson

Freedland

Clouse

Lustman

. The prevalence of comorbid depression in adults with diabetes: a meta-analysis. Diabetes Care. 2001;24:1069-1078.

14.

Schneider

Lowe

Meyer

Biessecker

Joos

Szecsenyi

. Depression and panic disorder as predictors of health outcomes for patients with asthma in primary care. Respir Med. 2008;102:359-366.

15.

Chavannes

Huibers

Schermer

. Associations of depressive symptoms with gender, body mass index and dyspnea in primary care COPD patients. Fam Pract. 2005;22:604-607.

16.

Pasquini

Biondi

. Depression in cancer patients: a critical review. Clin Pract Epidemiol Ment Health. 2007;3:2.

17.

Honda

Goodwin

. Cancer and mental disorders in a national community sample: findings from the national comorbidity survey. Psychother Psychosom. 2004;73:235-242.

18.

Stein

Cox

Afifi

Belik

Sareen

. Does co-morbid depressive illness magnify the impact of chronic physical illness? A population-based perspective. Psychol Med. 2006;36:587-596.

19.

Sherbourne

Jackson

Meredith

Camp

Wells

. Prevalence of comorbid anxiety disorders in primary care outpatients. Arch Fam Med. 1996;5:27-34.

20.

Watson

Amick

Gaynes

Practice-Based Interventions Addressing Concomitant Depression and Chronic Medical Conditions in the Primary Care Setting (Prepared by the RTI-UNC Evidence-based Practice Center under Contract No. 290 2007 10056 I). Rockville, MD: Agency for Healthcare Research and Quality; 2012.

21.

Counsell

. Formulating questions and locating primary studies for inclusion in systematic reviews. Ann Intern Med. 1997;127:380-387.

22.

Agency for Healthcare Research and Quality. AHRQ EHCP Methods Guide for Comparative Effectiveness Reviews of Medical Interventions (Provisional 11-2010). Rockville, MD: Agency for Healthcare Research and Quality; 2010.

23.

Agency for Healthcare Research and Quality. List of priority conditions for research under Medicare Modernization Act released. Press Release, December 15, 2004. http://archive.ahrq.gov/news/press/pr2004/mmapr.htm. Accessed December 12, 2011.

24.

Adams

Corrigan

eds. Priority Areas for National Action: Transforming Health Care Quality. Washington, DC: National Academies Press; 2003.

25.

Harris

Helfand

Woolf

. Current methods of the US Preventive Services Task Force: a review of the process. Am J Prev Med. 2001;20(3 suppl):21-35.

26.

Centre for Reviews and Dissemination. Systematic Reviews: CRD’s Guidance for Undertaking Reviews in Healthcare. York, England: University of York; 2009.

27.

Sutton

Abrams

Jones

Sheldon

Song

. Methods for Meta-Analysis in Medical Research (Wiley Series in Probability and Statistics - Applied Probability and Statistics Section). London, England: Wiley; 2000.

28.

Owens

Lohr

Atkins

. AHRQ series paper 5: grading the strength of a body of evidence when comparing medical interventions—Agency for Healthcare Research and Quality and the Effective Health Care Program. J Clin Epidemiol. 2010;63:513-523.

29.

Fann

Fan

Unützer

. Improving primary care for older adults with cancer and depression. J Gen Intern Med. 2009;24(suppl 2):S417-S424.

30.

Lin

Tang

Katon

Hegel

Sullivan

Unützer

. Arthritis pain and disability: response to collaborative depression care. Gen Hosp Psychiatry. 2006;28:482-486.

31.

Katon

Unützer

Fan

. Cost-effectiveness and net benefit of enhanced treatment of depression for older adults with diabetes and depression. Diabetes Care. 2006;29: 265-270.

32.

Williams

Jr Katon

Lin

. The effectiveness of depression care management on diabetes-related outcomes in older patients. Ann Intern Med. 2004;140:1015-1024.

33.

Lin

Katon

Von Korff

; IMPACT Investigators. Effect of improving depression care on pain and functional outcomes among older adults with arthritis: a randomized controlled trial. JAMA. 2003;290:2428-2429.

34.

Dwight-Johnson

Ell

Lee

. Can collaborative care address the needs of low-income Latinas with comorbid depression and cancer? Results from a randomized pilot study. Psychosomatics. 2005;46:224-232.

35.

Ell

Katon

Xie

. Collaborative care management of major depression among low-income, predominantly Hispanic subjects with diabetes: a randomized controlled trial. Diabetes Care. 2010;33:706-713.

36.

Ell

Xie

Quon

Quinn

Dwight-Johnson

Lee

. Randomized controlled trial of collaborative care management of depression among low-income patients with cancer. J Clin Oncol. 2008;26:4488-4496.

37.

Vera

Perez-Pedrogo

Huertas

. Collaborative care for depressed patients with chronic medical conditions: a randomized trial in Puerto Rico. Psychiatr Serv. 2010;61:144-150.

38.

Pyne

Fortney

Curran

. Effectiveness of collaborative care for depression in human immunodeficiency virus clinics. Arch Intern Med. 2011;171:23-31.

39.

Ell

Xie

Kapetanovic

. One-year follow-up of collaborative depression care for low-income, predominantly Hispanic patients with cancer. Psychiatr Serv. 2011;62: 162-170.

40.

Strong

Waters

Hibberd

. Management of depression for people with cancer (SMaRT oncology 1): a randomised trial. Lancet. 2008;372:40-48.

41.

Ell

Katon

Xie

. One-year postcollaborative depression care trial outcomes among predominantly Hispanic diabetes safety net patients. Gen Hosp Psychiatry. 2011;33:436-442.

42.

Hay

Katon

Ell

Lee

Guterman

. Cost-effectiveness analysis of collaborative care management of major depression among low-income, predominantly Hispanics with diabetes. Value Health. 2012;15:249-254.

43.

Katon

Russo

Von Korff

Lin

Ludman

Ciechanowski

. Long-term effects on medical costs of improving depression outcomes in patients with depression and diabetes. Diabetes Care. 2008;31:1155-1159.

44.

Kinder

Katon

Ludman

. Improving depression care in patients with diabetes and multiple complications. J Gen Intern Med. 2006;21:1036-1041.

45.

Lin

Katon

Rutter

. Effects of enhanced depression treatment on diabetes self-care. Ann Fam Med. 2006;4:46-53.

46.

Simon

Katon

Lin

. Cost-effectiveness of systematic depression treatment among people with diabetes mellitus. Arch Gen Psychiatry. 2007;64:65-72.

47.

Rollman

Belnap

LeMenager

. Telephone-delivered collaborative care for treating post-CABG depression: a randomized controlled trial. JAMA. 2009;302:2095-2103.

48.

Katon

Lin

Von Korff

. Collaborative care for patients with depression and chronic illnesses. N Engl J Med. 2010;363:2611-2620.

49.

Von Korff

Katon

Lin

. Functional outcomes of multi-condition collaborative care and successful ageing: results of randomised trial. BMJ. 2011;343:d6612.

50.

Lin

Von Korff

Ciechanowski

. Treatment adjustment and medication adherence for complex patients with diabetes, heart disease, and depression: a randomized controlled trial. Ann Fam Med. 2012;10:6-14.

51.

Unützer

Katon

Callahan

; IMPACT Investigators. Collaborative care management of late-life depression in the primary care setting: a randomized controlled trial. JAMA. 2002;288:2836-2845.

52.

Leon

Olfson

Portera

Farber

Sheehan

. Assessing psychiatric impairment in primary care with the Sheehan Disability Scale. Int J Psychiatry Med. 1997;27: 93-105.

53.

Gilbody

Bower

Fletcher

Richards

Sutton

. Collaborative care for depression: a cumulative meta-analysis and review of longer-term outcomes. Arch Intern Med. 2006;166:2314-2321.

54.

Katon

. Clinical and health services relationships between major depression, depressive symptoms, and general medical illness. Biol Psychiatry. 2003;54:216-226.

55.

Joynt

Whellan

O’Connor

. Depression and cardiovascular disease: mechanisms of interaction. Biol Psychiatry. 2003;54:248-261.

56.

Centers for Medicare & Medicaid Services, Department of Health and Human Services. Summary of Proposed Rule Provisions for Accountable Care Organizations Under the Medicare Shared Savings Program. Medicare Learning Network 2011. http://www.ftc.gov/opp/aco/cms-proposedrule.PDF. Accessed December 12, 2011.

57.

National Committee for Quality Assurance. Patient-centered medical home. 2011; http://www.ncqa.org/tabid/631/default.aspx. Accessed November 7, 2011.

58.

Bogner

de Vries

. Integration of depression and hypertension treatment: a pilot, randomized controlled trial. Ann Fam Med. 2008;6:295-301.

59.

Piette

Richardson

Himle

. A randomized trial of telephonic counseling plus walking for depressed diabetes patients. Med Care. 2011;49:641-648.

60.

Davidson

Rieckmann

Clemow

. Enhanced depression care for patients with acute coronary syndrome and persistent depressive symptoms: coronary psychosocial evaluation studies randomized controlled trial. Arch Intern Med. 2010;170:600-608.

61.

Berkman

Blumenthal

Burg

. Effects of treating depression and low perceived social support on clinical events after myocardial infarction: the Enhancing Recovery in Coronary Heart Disease Patients (ENRICHD) randomized trial. JAMA. 2003;289:3106-3116.

62.

Institute for Clinical Systems Improvement. Health care redesign: DIAMOND. Updated 2010. http://www.icsi.org/health_care_redesign_/diamond_35953/. Accessed April 4, 2012.

63.

Gunderson

. Clinical practice. Borderline personality disorder. N Engl J Med. 2011;364:2037-2042.