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Original Article |

Two-Year Effects of Quality Improvement Programs on Medication Management for Depression FREE

Jürgen Unützer, MD, MPH; Lisa Rubenstein, MD, MSPH; Wayne J. Katon, MD; Lingqi Tang, PhD; Naihua Duan, PhD; Isabel T. Lagomasino, MD; Kenneth B. Wells, MD, MPH
[+] Author Affiliations

From the Neuropsychiatric Institute, University of California, Los Angeles (Drs Unützer, Tang, Duan, and Wells); VA Greater Los Angeles Healthcare System (Dr Rubenstein) and the Department of Psychiatry, Charles R. Drew University (Dr Lagomasino), Los Angeles, Calif; RAND, Santa Monica, Calif (Drs Rubenstein and Wells); and the Department of Psychiatry, University of Washington, Seattle (Dr Katon).


Arch Gen Psychiatry. 2001;58(10):935-942. doi:10.1001/archpsyc.58.10.935.
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Published online

Background  Significant underuse of evidence-based treatments for depression persists in primary care. We examined the effects of 2 primary care–based quality improvement (QI) programs on medication management for depression.

Methods  A total of 1356 patients with depressive symptoms (60% with depressive disorders and 40% with subthreshold depression) from 46 primary care practices in 6 nonacademic managed care organizations were enrolled in a randomized controlled trial of QI for depression. Clinics were randomized to usual care or to 1 of 2 QI programs that involved training of local experts who worked with patients' regular primary care providers (physicians and nurse practitioners) to improve care for depression. In the QI-medications program, depression nurse specialists provided patient education and assessment and followed up patients taking antidepressants for up to 12 months. In the QI-therapy program, depression nurse specialists provided patient education, assessment, and referral to study-trained psychotherapists.

Results  Participants enrolled in both QI programs had significantly higher rates of antidepressant use than those in the usual care group during the initial 6 months of the study (52% in the QI-medications group, 40% in the QI-therapy group, and 33% in the usual care group). Patients in the QI-medications group had higher rates of antidepressant use and a reduction in long-term use of minor tranquilizers for up to 2 years, compared with patients in the QI-therapy or usual care group.

Conclusions  Quality improvement programs for depression in which mental health specialists collaborate with primary care providers can substantially increase rates of antidepressant treatment. Active follow-up by a depression nurse specialist in the QI-medications program was associated with longer-term increases in antidepressant use than in the QI model without such follow-up.

Figures in this Article

DEPRESSION is a major cause of disability worldwide1 and is common in primary care.2,3 Despite dissemination of practice guidelines for depression,46 significant underuse of evidence-based treatments for depression persists in primary care.7,8 Quality improvement (QI) efforts in primary care have been shown to increase rates of care and clinical outcomes for major depression for up to 8 months,912 but improvements in care were not sustained at longer-term follow-ups.13,14 We describe the impact of 2 QI interventions on the use of antidepressant medications and minor tranquilizers over 2 years.

This article is based on a randomized quasi experiment of an evidence-based QI intervention that was conducted in 46 nonacademic managed primary care practices in 5 states. Clinics were randomized to usual care (UC) or to 1 of 2 QI programs.15,16 To mirror the diverse clinical status of patients in community primary care settings, the study included depressed patients who met the research diagnostic criteria for major depression or dysthymic disorder and those with subthreshold depression.15

In this article, we follow the Institute of Medicine's formulation of quality of care17 and examine whether problems with underuse (lack of use of maintenance antidepressants by patients at high risk for relapse) or overuse (inappropriate long-term use of minor tranquilizers for depression) were affected by our interventions. We expected that the QI-medications (QI-Meds) program would lead to higher rates of antidepressant use than the QI-therapy program because of additional resources devoted to following up patients taking antidepressant medications.

STUDY DESIGN AND STUDY SITES

Partners in Care is a group-level randomized controlled trial carried out in 6 nonacademic managed care organizations in geographically diverse areas of the country.15 Forty-six of 48 clinics belonging to these 6 organizations and 181 of 183 primary care providers (physicians and nurse practitioners) agreed to participate. Clinics were grouped into 27 clusters that were matched into 9 blocks of 3 clusters each based on patient demographics, clinician specialty, and distance to specialty mental health providers (psychiatrists, psychologists, or psychotherapists). Within each block, clinic clusters were randomly assigned to UC or to 1 of 2 QI programs (QI-Meds or QI-therapy). Participating organizations included prepaid, staff-model, mixed fee-for-service/prepaid, and network-model group practices and rural, managed, public health clinics.16

Study staff screened consecutive patients in the waiting rooms of participating clinics during a 6-month period between June 1996 and March 1997. Eligible patients were aged 18 years or older, intended to use the clinic as their main source of medical care in the coming year, and were determined to have depression by a 6-item screening instrument that included the "stem" items for major depression and dysthymic disorder from the 12-month Composite International Diagnostic Interview (CIDI; edition 2.1), and items assessing the presence of depressive symptoms in the past month. Based on research diagnoses obtained by the full affective disorders section of the CIDI, the positive predictive value of this screener for depressive disorder (major depression or dysthymic disorder) was 55%.15 Patients who had an immediate medical emergency, did not speak English or Spanish, or did not have either insurance or a public-pay arrangement that covered the study interventions were excluded.

A total of 44 052 persons were approached in clinic waiting rooms, but 10 120 were not eligible for screening, mainly because they were not patients of participating primary care providers. Of the 27 332 patients completing the screener, 3918 were potentially eligible, but many left the clinic before completing the multistage enrollment process. Of the 2417 patients available to confirm insurance eligibility, 241 had ineligible health insurance. Of those who read the informed consent, 1356 enrolled. The remaining 21% either refused to participate or left the clinic. The enrolled sample includes 443 patients in the UC group, 424 in the QI-Meds group, and 489 in the QI-therapy group (Table 1). We controlled for differences in sex, educational level, and depression diagnosis in the analyses.

Table Graphic Jump LocationTable 1. Characteristics of the 1356 Subjects: Overall and by Intervention Conditions*
INTERVENTIONS

Our QI approach used a combination of expert intervention design, local managed care organization involvement, and provider behavior change strategies that have been described in detail previously.16 Both QI interventions had a common core of physician education and patient screening, assessment, and education by a depression nurse specialist (DNS). Physician and nurse education followed a treatment manual adapted from the Agency for Healthcare Research and Quality (formerly the Agency for Health Care Policy and Research) treatment guidelines for depression in primary care.18 Providers in both groups were encouraged to initiate treatment with antidepressants or psychotherapy for patients who met the diagnostic criteria for major depression or dysthymic disorder. Patients and providers were free to use either antidepressant medications or psychotherapy, both, or neither. In addition to this common core, each intervention provided clinics with a unique set of resources. The QI-Meds program provided participants in clinics that had been randomized to this intervention access to a DNS who offered to support ongoing antidepressant treatment by the patients' primary care providers for either 6 or 12 months (randomly assigned at the patient level). This follow-up focused on increasing adherence to guidelines for appropriate use of antidepressant medications.18 In the QI-therapy program, DNSs assisted all patients in QI-therapy clinics whose clinicians determined that psychotherapy was appropriate, with a referral to a study-trained psychotherapist to offer individual or group cognitive-behavioral therapy at a reduced copayment.16 Prior analyses showed that the DNSs attempted to contact 96% of eligible patients with depression, and completed an initial assessment visit with 73% (76% in the QI-Meds group and 71% in the QI-therapy group). About 55% of eligible participants completed all visits with the DNS. The mean number of nurse follow-up contacts was 1.8 in the QI-therapy group and 5.1 in the QI-Meds group.16

Usual care clinics were mailed copies of the Agency for Healthcare Research and Quality provider guidelines for depression in primary care.4 Patients in these clinics had access to all usually available primary care or specialty mental health treatments, but no extra resources were provided by the study.

OUTCOMES EXAMINED

Enrolled patients were asked to complete a telephone interview that included the affective disorders section of the CIDI, information on comorbid anxiety disorders, and economic information at baseline. Patients also completed a self-administered mail survey at baseline and at 6, 12, 18, and 24 months. The surveys assessed the use of psychotherapy or prescription medications during the prior 6 months. We updated dosage recommendations from the Agency for Healthcare Research and Quality treatment guidelines4 for newer antidepressants using a consensus panel of 10 academic expert psychiatrists, and used the low end of the dosage recommendations as "minimum recommended daily doses" (Table 2).

Table Graphic Jump LocationTable 2. Guideline-Level Antidepressant Doses for Patients With Depressive Disorders

Because the study enrolled a clinically diverse group of patients with major depression, dysthymic disorder, and subthreshold depression for whom treatment guidelines are less clear, we used 2 approaches to examine care for depression. For the entire sample of patients (including those with subthreshold depression), we describe any use of antidepressant medications (either 1 month of use during the prior 6 months or any use in the prior 30 days) or any counseling (at least 1 visit) as indicators of depression treatment.

For the 562 subjects who met the diagnostic criteria for DSM-IV major depression or dysthymic disorder at baseline and who were at high risk of relapse based on dysthymic disorder or a history of 2 or more episodes of depression, we examined 3 additional quality indicators: antidepressant use at minimum daily recommended doses (Table 2) for at least 25 of the past 30 days, for at least 2 of the past 6 months, and for at least 6 months in the past year (data for this indicator are not available at 24 months).

We also examined long-term minor tranquilizer use (use for >3 of the past 6 months). Our intervention materials recommended against such long-term use in patients with depression who did not have comorbid anxiety disorders because of the lack of efficacy data for this group of patients and because of substantial costs and risks associated with the long-term use of minor tranquilizers.

STATISTICAL ANALYSES

Our analyses examine the effects of the 2 QI models (randomly assigned at the clinic level) compared with UC on the use of medications by patients enrolled in the respective clinics. We used all 1092 subjects who had baseline data and at least one follow-up data point and who did not meet the CIDI criteria for bipolar disorder for the analyses. We performed multilevel analyses, testing the primary hypotheses that the intervention conditions increased rates of treatment (as previously specified) significantly more than UC. We tested secondary hypotheses about the targeting of depression treatments by performing analyses that interacted the intervention status with baseline disorder status, treatment preferences, and prior treatment. Because both interventions recommended against the long-term use of minor tranquilizers in patients without comorbid anxiety disorders, we also tested the hypothesis that patients in the QI clinics had lower rates of potentially inappropriate minor tranquilizer use over time.

For each dependent variable, we fitted 3-level mixed-effects logistic regression models using follow-up data at 6, 12, 18, and 24 months with regression adjustment for baseline depression treatments in the past 6 months, accounting for the multilevel data structure with patients nested within clinics and repeated measurements nested within patients. We treated time as a categorical variable, and examined the fixed effects for time, intervention condition, and their interactions. To account for the intraclass correlation expected in the data, we specified random effects at the clinic and patient level, including random intercepts and random slopes for the difference among waves. At the patient level, we specified the covariance structure among the random effects as the most general unstructured model. At the clinic level, we specified a more restrictive variance component model because of the limited degrees of freedom available. Our model specification is analogous to the models used by others.1921 We also included several covariates for additional adjustment: age, squared age, sex, educational level (less than high school, completed high school, some college, completed college, or more), chronic medical conditions from a total of 19 (0, 1, 2, or ≥3), depressive disorder determined by the CIDI, an indicator of having at least 2 prior depressive episodes, comorbid anxiety disorders (CIDI), likely problem drinking determined by the Alcohol Use Disorders Identification Test, baseline preferences for treatment (antidepressant medications, counseling, nothing, or wait), study site, and a summary variable of household wealth modeled after the Health and Retirement Survey.

To test intervention effects at each time point (months 6, 12, 18, and 24), we conducted pairwise 2-sided t tests comparing QI-Meds vs UC, QI-therapy vs UC, and QI-Meds vs QI-therapy.

To present the effect size of intervention effects, we calculated standardized predictions for each outcome studied.22 In deriving these predictions, regression parameters and each individual's actual covariate values other than intervention status are used to derive 3 predicted values for each individual, first as a QI-Meds group subject, then as a QI-therapy group subject, and then as a UC group subject. Predictions under the QI-Meds scenario are then averaged across the entire analytic sample to obtain an overall assessment of the QI-Meds outcome; the procedure is then repeated for the other conditions. This procedure thus standardizes the comparisons to the characteristics of the full analytic sample.

We used an extended hot deck multiple imputation technique that modifies the predictive mean matching method23 to impute missing covariates. (Outcome variables were not imputed.) Instead of filling in a single value for each missing value, we used the multiple imputation strategy of Rubin24 to create 5 imputed data sets. Each of 5 complete data sets was then analyzed using standard complete-data methods. The predictions across 5 imputed data sets were combined by averaging, and SEs were derived using the Rubin method to combine within-imputation variability and between-imputation variability.

TREATMENTS FOR DEPRESSION

There were no significant baseline differences in the use of depression treatments (antidepressants or psychotherapy) by intervention status (Table 3). At baseline, the rate of any treatment was somewhat higher in the QI-therapy group than in the UC group, and we controlled for this in our analyses.

Table Graphic Jump LocationTable 3. Use of Depression Treatments by 1092 Depressed Participants*

During the initial 6 months of the study, antidepressant use was greater in the QI-Meds and QI-therapy groups than in the UC group. Patients in the QI-Meds group were more likely than patients in the UC group to report antidepressant use at 6, 12, 18, and 24 months, but the difference was only statistically significant at 6 and 12 months. Patients in the QI-Meds group had significantly higher rates of antidepressant use than those in the QI-therapy group at 6, 12, and 24 months. Participants in the QI-Meds group who were randomly assigned to nurse case management for 12 months did not have higher rates of antidepressant use than those who were assigned to case management for 6 months (data not shown).

As a context for our findings on antidepressant use, we also examined rates of any depression treatment (any use of antidepressants or psychotherapy) in the prior 6 months. At 6 months, patients in the QI-Meds and QI-therapy groups reported higher rates of any depression treatment than those in the UC group. Those in the QI-Meds group had consistently higher rates of any depression treatment than those in the UC or QI-therapy group, but the difference was only statistically significant at 6 and 12 months. Further detail on counseling treatments is available elsewhere.16,17

We observed significant interaction effects of intervention type with disorder status (F = 4.09, P = .02) and intervention type with prior use of counseling (F = 7.49, P<.001), indicating greater targeting of antidepressants to patients with depressive disorders or those who underwent prior counseling in the 2 intervention groups than in the UC group. For example, at the 6-month follow-up, between 26% (UC group) and 38% (QI-Meds group) of the participants who did not meet the CIDI criteria for major depression or dysthymic disorder at baseline reported using antidepressants, compared with 37% (UC group) to 62% (QI-Meds group) of those who had depressive disorders at baseline. Figure 1 shows standardized predictions of the proportion of patients who used antidepressants during the 2-year study period stratified by baseline antidepressant use. These estimates were derived from the mixed-effects logistic regression model that included interactions of intervention type with prior treatment and disorder status.

Place holder to copy figure label and caption

Proportion of patients who used antidepressants in the prior 6 months stratified by baseline antidepressant use. QI indicates quality improvement.

Graphic Jump Location
TYPES OF ANTIDEPRESSANTS USED

At baseline, selective serotonin reuptake inhibitors accounted for about 60% of the antidepressants used in all 3 groups; other newer antidepressants, such as bupropion hydrochloride, nefazodone hydrochloride, or venlafaxine hydrochloride, accounted for about 20%; tertiary amine tricyclic antidepressants accounted for about 15%; and secondary amine tricyclic antidepressants accounted for about 5%. Monoamine oxidase inhibitors and other antidepressants, such as amoxapine or maprotiline, represented less than 1% of all antidepressants used. During the 2 years of follow-up, there was a slight increase in the use of newer antidepressants other than selective serotonin reuptake inhibitors in all 3 groups and a corresponding decrease in the use of tricyclic antidepressants. Between 5% and 9% of the participants used more than 1 antidepressant during each 6-month period. There were no substantial intervention group differences in the types of antidepressants used over time.

ADEQUACY OF ANTIDEPRESSANT USE AMONG SUBJECTS WITH DEPRESSION AT HIGH RISK FOR RELAPSE

Most patients (562 of 674) who met the criteria for major depression or dysthymic disorder at baseline were at high risk for relapse, as defined by current dysthymic disorder or a history of 2 or more episodes of depression.4 At baseline, patients in the QI-therapy group at high risk for relapse reported significantly greater antidepressant use than patients in the QI-Meds or UC group (Table 4), and we controlled for these baseline differences in the analyses.

Table Graphic Jump LocationTable 4. Antidepressant Use by the 562 Participants With Depression at High Risk for Relapse*

Rates of guideline-level antidepressant use, as defined by our 3 quality indicators, were significantly greater in the QI-Meds group than in the UC group at 6, 12, and 18 months but not at 24 months. Appropriate antidepressant use was consistently higher in the QI-Meds group than in the QI-therapy group, but the differences were not always statistically significant.

LONG-TERM USE OF MINOR TRANQUILIZERS

The proportion of subjects using minor tranquilizers for more than 3 months at baseline ranged from 7.1% (QI-therapy group) to 9.2% (UC group). At the 24-month follow-up, 6.2% of the patients in the QI-Meds group reported long-term use of minor tranquilizers compared with 10.0% in the QI-therapy group (t = −2.01, P = .04) and 10.3% in the UC group (t = −1.87, P = .06). A similar picture emerged when we examined the use of minor tranquilizers for 3 or more months without a concurrent prescription of an antidepressant medication. Over 2 years, this rate declined from 4.6% to 2.5% in the QI-Meds group, but it remained relatively stable in the QI-therapy (4%-6%) and the UC (4%-7%) groups.

There was no significant interaction between anxiety disorder status and intervention group, meaning that the interventions did not increase the targeting of long-term minor tranquilizers to those who had comorbid anxiety disorders.

Our results suggest that QI interventions that combine key components from established chronic care models,25,26 such as clinician education, patient education, case management, and specialist involvement in primary care, can lead to relatively long-term increases in antidepressant use in managed primary care practices. Prior studies27,28 document that less intensive interventions, such as provider feedback, do not lead to persistent increases in depression treatment or improvement in clinical outcomes. The necessity for a more intensive model of care for changing antidepressant use is consistent with the literature2931 on health care provider behavior in general, which indicates that while 1-step behaviors such as ordering a mammogram have responded to computer feedback, conditions requiring sustained patient and provider behavior change have not.

While short-term antidepressant use was increased by the QI-Meds and QI-therapy interventions, longer-term increases in the rates of medication use were limited to the QI-Meds group. The increased antidepressant use in the QI-therapy and QI-Meds groups at 6 months implies that intervention components common to the 2 interventions improved antidepressant use in the short-term. These include provider education, collaboration of primary care providers with DNSs, assessment and education of patients by the DNS, and encouragement of the use of antidepressant medications or psychotherapy for patients with major depression or dysthymic disorder. The finding of greater antidepressant use in the QI-Meds group at 12, 18, and 24 months implies that the addition of at least 6 months of active follow-up by a DNS (available in QI-Meds practices only) is associated with relatively long-term increases in the use of antidepressants. Contrary to our expectations, patients in the QI-Meds group who were in the 12-month case management group had no greater use of antidepressants than those who were in the 6-month case management group over time. This could be because 12-month case management has no additional effect compared with 6 months or because most patients eligible for the 12-month follow-up did not use it for the full available duration.16 Future studies should examine if even shorter periods of follow-up (ie, 3 months) can achieve similar effects on antidepressant use or if a more fully implemented longer-term follow-up would lead to even greater long-term increases in medication use.

Earlier trials911 of collaborative care for depression included patients who had already started taking antidepressants. We found that patients with and without prior antidepressant treatment had increases in their rates of care, suggesting that QI interventions for depression are effective in increasing antidepressant use in both groups. While treatment rates were between 50% and 75% higher in the QI groups than in the UC group, it is important to emphasize that only about 50% of patients who met the diagnostic criteria for major depression ordysthymic disorder at baseline received appropriate antidepressant management during the first 6 months of the study. There is, thus, substantial room for improvement. Our interventions were less intensive than most previous evaluations of collaborative care for depression and were self-applied by usual nonacademic primary care practices to a diverse population of patients, without direct involvement of researchers in patient care. We expect that interventions to improve care for depression will show smaller effects in actual use than in carefully controlled trials because of the greater diversity of patients and primary care providers involved. The observed improvement in this study may mirror more closely than previous studies the impacts that might be achievable in a broad-scale dissemination of QI for depression. If these results held true in large-scale use, the health impact of such QI on a population level could be substantial.

Our sample included several patients who did not meet the diagnostic criteria for depressive disorders, and the literature does not consistently support the efficacy of antidepressants or psychotherapy for subthreshold depression. Our educational materials encouraged clinicians to recognize subthreshold depression and to target antidepressant medications and full doses of cognitive-behavioral therapy to those with major depression or dysthymic disorder. Patients with depression who were at risk for relapse had the highest rates of antidepressant use in all 3 groups, and patients at risk for relapse in the QI-Meds group had consistently higher rates of medication use than patients in the QI-therapy or UC group. Our study was not designed to determine the need for or effectiveness of long-term antidepressant use for different types of patients. Future studies should, thus, focus increased attention on the need for long-term follow-up and maintenance therapy for diverse populations of patients with depression.

Our educational materials specifically recommended the use of secondary amine tricyclic antidepressants or selective serotonin reuptake inhibitors as "first-line" antidepressant medications and pointed out that both types of medications are equally efficacious. Despite this recommendation, secondary amine tricyclic agents accounted for 5% or less of the antidepressants used, and their use declined during the 2 years of the study. Selective serotonin reuptake inhibitors and other newer antidepressants made up about 80% of all antidepressants used, without substantial differences among intervention groups. The greater use of newer antidepressants that can be easier to titrate and tolerate3234 than older antidepressants represents a substantial change from earlier studies7,32,34 of depression management in primary care.

The availability of newer antidepressants that are better tolerated and indicated for depression and anxiety disorders may also account for relatively low rates of long-term minor tranquilizer use compared with earlier studies.7 Minor tranquilizer use was particularly low in participants without comorbid anxiety disorders, indicating that primary care providers targeted these medications to patients who were more likely to benefit from them. We discouraged the long-term use of minor tranquilizers in our educational materials, and we found substantial reductions in minor tranquilizer use in the QI-Meds group compared with the QI-therapy or UC group. Thus, it appears possible for QI interventions to simultaneously correct problems related to potential underuse of appropriate antidepressant medications and overuse of inappropriate long-term minor tranquilizers.

While we sampled patients from 6 diverse organizations across the country,15 our sample has limited generalizability to primary care in general. Our ability to generalize is further limited by a relatively high nonparticipation rate. We are also limited by our reliance on self-report data for use of medications and counseling. It is possible that patients underreport such treatments, but an earlier study by Katon and colleagues9 showed that self-report of antidepressant use during the past 30 days (one of our quality indicators) was strongly associated with automated pharmacy data.

Our models may somewhat understate the true intervention effects because, over time, the need for treatment may have decreased more in the intervention groups than in the UC group.15 An alternative method to examine the long-term effects of QI on antidepressant prescribing would have been to examine antidepressant use in a new cohort of patients with depression. It is also possible that more patients in the QI-therapy group had sustained clinical benefits that made it less necessary for them to undergo long-term antidepressant treatment. However, almost half of our participants were at high risk for relapse and, thus, candidates for long-term maintenance antidepressant treatment.18

In conclusion, implementation of QI for depression by diverse managed primary care practices can substantially increase rates of antidepressant treatment for depression. The inclusion of at least 6 months of active nurse care management leads to larger and longer-term increases in antidepressant use than does the collaborative care model without such follow-up.

Accepted for publication April 19, 2001.

This study was supported by grant R01-HS08349 from the Agency for Healthcare Research and Quality, Rockville, Md; grant P50 MH54623 from the National Institute of Mental Health, Rockville; and grant 96-42901A-HE from the John D. and Catherine T. MacArthur Foundation, Chicago, Ill.

We thank Robert Bell, PhD, Tom Belin, PhD, and Daniel McCaffrey, PhD, for their statistical advice; Maga Jackson-Triche, MD, MSHS, for her assistance with the design and implementation of the interventions; and Bernadette Benjamin, MS, for her meticulous programming support. This study is a sister study to the National Institute of Mental Health Cooperative Agreement to Test Depression Practice Guidelines (Lisa Rubenstein, MD, MSHS, Kathryn Rost, PhD, and Daniel Ford, MD, MPH, principal investigators). We acknowledge the following participating managed care organizations that provided access to their expertise and patients, implemented interventions, and provided in-kind resources: Allina Medical Group, Minneapolis, Minn; Patuxent Medical Group, Columbia, Md; Humana Health Care Plans, San Antonio, Tex; MedPartners, Los Angeles, Calif; PacifiCare of Texas, San Antonio; and Valley-Wide Health Services, San Luis Valley, Colo. We also acknowledge their internal behavioral health organizations and participating contract behavioral health organizations: Alamo Mental Health Group, San Antonio; San Luis Valley Mental Health/Colorado Health Networks, San Luis Valley; and Greenspring Mental Health Services, Columbia. Finally, we acknowledge the clinicians and patients who contributed their time and efforts to this study.

Corresponding author and reprints: Jürgen Unützer, MD, MPH, Center for Health Services Research, Neuropsychiatric Institute, University of California, Los Angeles, 10920 Wilshire Blvd, Suite 300, Los Angeles, CA 90024 (e-mail: unutzer@ucla.edu).

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Graubard  BIKorn  EL Predictive margins with survey data. Biometrics. 1999;55652- 659
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Little  RJ Missing-data adjustments in large surveys. J Business Econ Stat. 1988;6287- 301
Rubin  DB Multiple Imputation for Nonresponse in Surveys.  New York, NY John Wiley & Sons Inc1987;
Wagner  EHAustin  BTVon Korff  M Improving outcomes in chronic illness. Manag Care Q. 1996;412- 25
Katon  WVon Korff  MLin  EUnützer  JSimon  GWalker  ELudman  EBush  T Population-based care for depression: effective disease management strategies to decrease prevalence. Gen Hosp Psychiatry. 1997;19169- 178
Link to Article
Simon  GEVon Korff  MRutter  CWagner  E Randomized trial of monitoring, feedback, and management of care by telephone to improve treatment of depression in primary care. BMJ. 2000;320550- 554
Link to Article
Kroenke  KTaylor-Vaisey  ADietrich  AJOxman  TE Intervention to improve provider diagnosis and treatment of mental disorders in primary care. Psychosomatics. 2000;4139- 52
Link to Article
Davis  DAThomson  MAOxman  ADHaynes  RB Changing physician performance: a systematic review of the effect of continuing medical education strategies. JAMA. 1995;274700- 705
Link to Article
Rubenstein  LVMittman  BSYano  EMMulrow  CD From understanding health care provider behavior to improving health care: the QUERI framework for quality improvement: Quality Enhancement Research Initiative. Med Care. 2000;38(suppl 1)I129- I141
Link to Article
Oxman  ADThomson  MADavis  DAHaynes  RB No magic bullets: a systematic review of 102 trials of interventions to improve professional practice. CMAJ. 1995;1531423- 1431
Simon  GEVon Korff  MWagner  EHBarlow  W Patterns of antidepressant use in community practice. Gen Hosp Psychiatry. 1993;15399- 408
Link to Article
Simon  GEHeiligenstein  JRevicki  DVon Korff  MKaton  WJLudman  EGrothaus  LWagner  E Long-term outcomes of initial antidepressant drug choice in a "real world" randomized trial. Arch Fam Med. 1999;8319- 325
Link to Article
Katon  WVon Korff  MLin  EBush  TOrmel  J Adequacy and duration of antidepressant treatment in primary care. Med Care. 1992;3067- 76
Link to Article

Figures

Place holder to copy figure label and caption

Proportion of patients who used antidepressants in the prior 6 months stratified by baseline antidepressant use. QI indicates quality improvement.

Graphic Jump Location

Tables

Table Graphic Jump LocationTable 1. Characteristics of the 1356 Subjects: Overall and by Intervention Conditions*
Table Graphic Jump LocationTable 2. Guideline-Level Antidepressant Doses for Patients With Depressive Disorders
Table Graphic Jump LocationTable 3. Use of Depression Treatments by 1092 Depressed Participants*
Table Graphic Jump LocationTable 4. Antidepressant Use by the 562 Participants With Depression at High Risk for Relapse*

References

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Spitzer  RLWilliams  JBKroenke  KLinzer  MdeGruy  FV  IIIHahn  SRBrody  DJohnson  JG Utility of a new procedure for diagnosing mental disorders in primary care: the PRIME MD 1000 study. JAMA. 1994;2721749- 1756
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Depression Guidelines Panel, Depression in Primary Care: Treatment of Major Depression.  Rockville, Md US Dept of Health and Human Services1993;AHRQ (formerly AHCPR), US Public Health Services, publication 93-0551
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Schulberg  HCKaton  WJSimon  GERush  AJ Best clinical practice: guidelines for managing major depression in primary medical care. J Clin Psychiatry. 1999;60(suppl 7)19- 26discussion, 27-28.
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Link to Article
Katon  WVon Korff  MLin  EWalker  ESimon  GBush  TRobinson  PRusso  J Collaborative management to achieve treatment guidelines: impact on depression in primary care. JAMA. 1995;2731026- 1031
Link to Article
Katon  WRobinson  PVon Korff  MLin  EBush  TLudman  ESimon  GWalker  E A multifaceted intervention to improve treatment of depression in primary care. Arch Gen Psychiatry. 1996;53924- 932
Link to Article
Katon  WVon Korff  MLin  ESimon  GWalker  EUnützer  JBush  TRusso  JLudman  E Stepped collaborative care for primary care patients with persistent symptoms of depression: a randomized trial. Arch Gen Psychiatry. 1999;561109- 1115
Link to Article
Schulberg  HCBlock  MRMadonia  MJScott  CPRodriguez  EImber  SDPerel  TLave  JHouck  PRCoulehan  JL Treating major depression in primary care practice: eight-month clinical outcomes. Arch Gen Psychiatry. 1996;53913- 919
Link to Article
Lin  EHKaton  WJSimon  GEVon Korff  MBush  TMRutter  CMSaunders  KWWalker  EA Achieving guidelines for the treatment of depression in primary care: is physician education enough? Med Care. 1997;35831- 842
Link to Article
Lin  ESimon  GEKaton  WJRusso  JEVon Korff  MBush  TMLudman  EJWalker  E Can enhanced acute phase treatment of depression improve long-term outcomes? a report of randomized trials in primary care. Am J Psychiatry. 1999;156643- 645
Wells  KBSherbourne  CSchoenbaum  MDuan  NMeredith  LUnützer  J Impact of disseminating quality improvement programs for depression in managed primary care: a randomized controlled trial. JAMA. 2000;283212- 220
Link to Article
Rubenstein  LVJackson-Triche  MUnützer  JMiranda  JMinnium  KPearson  MLWells  KB Evidence-based care for depression in managed primary care practices. Health Aff (Millwood). 1999;1889- 105
Link to Article
Chassin  MRGalvin  RW The urgent need to improve health care quality: Institute of Medicine National Roundtable on Health Care Quality. JAMA. 1998;2801000- 1005
Link to Article
Rubenstein  LVUnützer  JMiranda  JKaton  WWieland  MJackson-Triche  MMinnium  KMulrow  CWells  K Clinician Guide to Depression and Management in Primary Care Settings.  Santa Monica, Calif RAND1996;
Gibbons  RDBock  RD Trend in correlated proportions. Psychometrika. 1987;52113- 124
Link to Article
Gibbons  RDHedeker  D Application of random-effects probit regression models. J Consult Clin Psychol. 1994;62285- 296
Link to Article
Hedeker  DGibbons  RD A random-effects ordinal regression model for multilevel analysis. Biometrics. 1994;50933- 944
Link to Article
Graubard  BIKorn  EL Predictive margins with survey data. Biometrics. 1999;55652- 659
Link to Article
Little  RJ Missing-data adjustments in large surveys. J Business Econ Stat. 1988;6287- 301
Rubin  DB Multiple Imputation for Nonresponse in Surveys.  New York, NY John Wiley & Sons Inc1987;
Wagner  EHAustin  BTVon Korff  M Improving outcomes in chronic illness. Manag Care Q. 1996;412- 25
Katon  WVon Korff  MLin  EUnützer  JSimon  GWalker  ELudman  EBush  T Population-based care for depression: effective disease management strategies to decrease prevalence. Gen Hosp Psychiatry. 1997;19169- 178
Link to Article
Simon  GEVon Korff  MRutter  CWagner  E Randomized trial of monitoring, feedback, and management of care by telephone to improve treatment of depression in primary care. BMJ. 2000;320550- 554
Link to Article
Kroenke  KTaylor-Vaisey  ADietrich  AJOxman  TE Intervention to improve provider diagnosis and treatment of mental disorders in primary care. Psychosomatics. 2000;4139- 52
Link to Article
Davis  DAThomson  MAOxman  ADHaynes  RB Changing physician performance: a systematic review of the effect of continuing medical education strategies. JAMA. 1995;274700- 705
Link to Article
Rubenstein  LVMittman  BSYano  EMMulrow  CD From understanding health care provider behavior to improving health care: the QUERI framework for quality improvement: Quality Enhancement Research Initiative. Med Care. 2000;38(suppl 1)I129- I141
Link to Article
Oxman  ADThomson  MADavis  DAHaynes  RB No magic bullets: a systematic review of 102 trials of interventions to improve professional practice. CMAJ. 1995;1531423- 1431
Simon  GEVon Korff  MWagner  EHBarlow  W Patterns of antidepressant use in community practice. Gen Hosp Psychiatry. 1993;15399- 408
Link to Article
Simon  GEHeiligenstein  JRevicki  DVon Korff  MKaton  WJLudman  EGrothaus  LWagner  E Long-term outcomes of initial antidepressant drug choice in a "real world" randomized trial. Arch Fam Med. 1999;8319- 325
Link to Article
Katon  WVon Korff  MLin  EBush  TOrmel  J Adequacy and duration of antidepressant treatment in primary care. Med Care. 1992;3067- 76
Link to Article

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