Clinician perceptions of a clinical decision support system to reduce cardiovascular risk among prediabetes patients in a predominantly rural healthcare system.

BACKGROUND: The early detection and management of uncontrolled cardiovascular risk factors among prediabetes patients can prevent cardiovascular disease (CVD). Prediabetes increases the risk of CVD, which is a leading cause of death in the United States. CVD clinical decision support (CDS) in primary care settings has the potential to reduce cardiovascular risk in patients with prediabetes while potentially saving clinicians time. The objective of this study is to understand primary care clinician (PCC) perceptions of a CDS system designed to reduce CVD risk in adults with prediabetes. METHODS: We administered pre-CDS implementation (6/30/2016 to 8/25/2016) (n = 183, 61% response rate) and post-CDS implementation (6/12/2019 to 8/7/2019) (n = 131, 44.5% response rate) independent cross-sectional electronic surveys to PCCs at 36 randomized primary care clinics participating in a federally funded study of a CVD risk reduction CDS tool. Surveys assessed PCC demographics, experiences in delivering prediabetes care, perceptions of CDS impact on shared decision making, perception of CDS impact on control of major CVD risk factors, and overall perceptions of the CDS tool when managing cardiovascular risk. RESULTS: We found few significant differences when comparing pre- and post-implementation responses across CDS intervention and usual care (UC) clinics. A majority of PCCs felt well-prepared to discuss CVD risk factor control with patients both pre- and post-implementation. About 73% of PCCs at CDS intervention clinics agreed that the CDS helped improve risk control, 68% reported the CDS added value to patient clinic visits, and 72% reported they would recommend use of this CDS system to colleagues. However, most PCCs disagreed that the CDS saves time talking about preventing diabetes or CVD, and most PCCs also did not find the clinical domains useful, nor did PCCs believe that the clinical domains were useful in getting patients to take action. Finally, only about 38% reported they were satisfied with the CDS. CONCLUSIONS: These results improve our understanding of CDS user experience and can be used to guide iterative improvement of the CDS. While most PCCs agreed the CDS improves CVD and diabetes risk factor control, they were generally not satisfied with the CDS. Moreover, only 40-50% agreed that specific suggestions on clinical domains helped patients to take action. In spite of this, an overwhelming majority reported they would recommend the CDS to colleagues, pointing for the need to improve upon the current CDS. TRIAL REGISTRATION: NCT02759055 03/05/2016.

Depression and cardiovascular risk in primary care patients.

OBJECTIVE: This study assessed the relationship of both depression diagnosis and clinically significant depressive symptoms with individual cardiovascular risk factors and estimated total cardiovascular risk in primary care patients. METHODS: This study used a cross-sectional and retrospective design. Patients who had a primary care encounter between January 2016 and September 2018 and completed depression screening (PHQ-9) during the year prior to their appointment (N = 70,980) were included in this study. Data examining estimated total cardiovascular risk, specific cardiovascular risk factors, and relevant clinical diagnoses (including depression diagnosis) were extracted from the electronic health record. Patients were categorized into three groups: no depression (PHQ-9 < 10 and no depression diagnosis), controlled depression (PHQ-9 < 10 with previous depression diagnosis), and current depression (PHQ-9 ≥ 10). Groups were compared on estimated total risk and specific cardiovascular risk factors (e.g., body mass index [BMI], smoking status, lipids, blood pressure, and glucose). RESULTS: In adjusted analyses, patients with current depression (n = 18,267) demonstrated significantly higher 10-year and 30-year cardiovascular risk compared to patients with controlled depression (n = 33,383; 10-year: b = 0.59 [95% CI = 0.44,0.74]; 30-year: OR = 1.32 [95% CI = 1.26,1.39]) and patients without depression (n = 19,330; 10-year: b = 0.55 [95% CI = 0.37,0.73]; 30-year: OR = 1.56 [95% CI = 1.48,1.65]). Except for low-density lipoprotein (LDL), patients with current depression had the greatest cardiovascular risk across specific risk factors. CONCLUSIONS: Individuals who had a depression diagnosis and clinically significant depressive symptoms had the greatest cardiovascular risk. Pathways to prevent cardiovascular disease in those with depression might focus on treating depressive symptoms as well as specific uncontrolled cardiovascular risk factors.

Effect of Clinical Decision Support on Cardiovascular Risk Among Adults With Bipolar Disorder, Schizoaffective Disorder, or Schizophrenia: A Cluster Randomized Clinical Trial.

IMPORTANCE: Adults with schizophrenia, schizoaffective disorder, or bipolar disorder, collectively termed serious mental illness (SMI), have shortened life spans compared with people without SMI. The leading cause of death is cardiovascular (CV) disease. OBJECTIVE: To assess whether a clinical decision support (CDS) system aimed at primary care clinicians improves CV health for adult primary care patients with SMI. DESIGN, SETTING, AND PARTICIPANTS: In this cluster randomized clinical trial conducted from March 2, 2016, to September 19, 2018, restricted randomization assigned 76 primary care clinics in 3 Midwestern health care systems to receive or not receive a CDS system aimed at improving CV health among patients with SMI. Eligible clinics had at least 20 patients with SMI; clinicians and their adult patients with SMI with at least 1 modifiable CV risk factor not at the goal set by the American College of Cardiology/American Heart Association guidelines were included. Statistical analysis was conducted on an intention-to-treat basis from January 10, 2019, to December 29, 2021. INTERVENTION: The CDS system assessed modifiable CV risk factors and provided personalized treatment recommendations to clinicians and patients. MAIN OUTCOMES AND MEASURES: Patient-level change in total modifiable CV risk over 12 months, summed from individual modifiable risk factors (smoking, body mass index, low-density lipoprotein cholesterol level, systolic blood pressure, and hemoglobin A1c level). RESULTS: A total of 80 clinics were randomized; 4 clinics were excluded for having fewer than 20 eligible patients, leaving 42 intervention clinics and 34 control clinics. A total of 8937 patients with SMI (4922 women [55.1%]; mean [SD] age, 48.4 [13.5] years) were enrolled. There was a 4% lower rate of increase in total modifiable CV risk among intervention patients relative to control patients (relative rate ratio [RR], 0.96; 95% CI, 0.94-0.98). The intervention favored patients who were 18 to 29 years of age (RR, 0.89; 95% CI, 0.81-0.98) or 50 to 59 years of age (RR, 0.93; 95% CI, 0.90-0.96), Black (RR, 0.93; 95% CI, 0.88-0.98), or White (RR, 0.96; 95% CI, 0.94-0.98). Men (RR, 0.96; 95% CI, 0.94-0.99) and women (RR, 0.95; 95% CI, 0.92-0.97), as well as patients with any SMI subtype (bipolar disorder: RR, 0.96; 95% CI, 0.94-0.99; schizoaffective disorder: RR, 0.94; 95% CI, 0.90-0.98; schizophrenia: RR, 0.92; 95% CI, 0.85-0.99) also benefited from the intervention. Despite treatment effects favoring the intervention, there were no significant differences in individual modifiable risk factors. CONCLUSIONS AND RELEVANCE: This CDS intervention resulted in a rate of change in total modifiable CV risk that was 4% lower among intervention patients compared with control patients. Results were driven by the cumulative effects of incremental and mostly nonsignificant changes in individual modifiable risk factors. These findings emphasize the value of using CDS to prompt early primary care intervention for adults with SMI. TRIAL REGISTRATION: ClinicalTrials.gov Identifier: NCT02451670.

Assessing the implementation of a clinical decision support tool in primary care for diabetes prevention: a qualitative interview study using the Consolidated Framework for Implementation Science.

BACKGROUND: In this paper we describe the use of the Consolidated Framework for Implementation Research (CFIR) to study implementation of a web-based, point-of-care, EHR-linked clinical decision support (CDS) tool designed to identify and provide care recommendations for adults with prediabetes (Pre-D CDS). METHODS: As part of a large NIH-funded clinic-randomized trial, we identified a convenience sample of interview participants from 22 primary care clinics in Minnesota, North Dakota, and Wisconsin that were randomly allocated to receive or not receive a web-based EHR-integrated prediabetes CDS intervention. Participants included 11 clinicians, 6 rooming staff, and 7 nurse or clinic managers recruited by study staff to participate in telephone interviews conducted by an expert in qualitative methods. Interviews were recorded and transcribed, and data analysis was conducted using a constructivist version of grounded theory. RESULTS: Implementing a prediabetes CDS tool into primary care clinics was useful and well received. The intervention was integrated with clinic workflows, supported primary care clinicians in clearly communicating prediabetes risk and management options with patients, and in identifying actionable care opportunities. The main barriers to CDS use were time and competing priorities. Finally, while the implementation process worked well, opportunities remain in engaging the care team more broadly in CDS use. CONCLUSIONS: The use of CDS tools for engaging patients and providers in care improvement opportunities for prediabetes is a promising and potentially effective strategy in primary care settings. A workflow that incorporates the whole care team in the use of such tools may optimize the implementation of CDS tools like these in primary care settings. Trial registration Name of the registry: Clinicaltrial.gov. TRIAL REGISTRATION NUMBER: NCT02759055. Date of registration: 05/03/2016. URL of trial registry record: https://clinicaltrials.gov/ct2/show/NCT02759055 Prospectively registered.

Implementing a prediabetes clinical decision support system in a large primary care system: Design, methods, and pre-implementation results.

BACKGROUND: Early detection of prediabetes and management of cardiovascular (CV) risk factors to prevent CV disease is essential, but clinicians are often slow to address this risk. Clinical decision support (CDS) systems, with appropriate implementation, can potentially improve prediabetes identification and treatment. METHODS/DESIGN: 34 Midwestern primary care clinics were randomized to receive or not receive access to a prediabetes (PreD) CDS tool. Between October 2016 and December 2019, primary care clinicians (PCPs) received Pre-D CDS alerts during visits with adult patients identified with prediabetes and who met minimal inclusion criteria and had at least one CV risk factor not at goal. The PCP Pre-D CDS included a summary of six modifiable CV risk factors and patient-specific treatment recommendations. Study outcomes included total modifiable CV risk, six modifiable CV risk factors, use of CV medications, and referrals. The Consolidated Framework for Implementation Research was used to examine CDS implementation processes. DISCUSSION: This cluster-randomized pragmatic trial allowed PCPs the opportunity to improve CV risk in a timely manner for patients with prediabetes. Effectiveness will be assessed using an intent-to-treat analysis. Implementation processes and outcomes will be assessed through interviews, surveys, and electronic health record data harvested by the CDS tool itself. Pre-implementation interviews and activities identified key strategies to incorporate as part of the Pre-D CDS implementation process to ensure acceptability and high use rates. Analyses are ongoing and trial results are expected in mid-2021.

Pragmatic trial design of an intervention to reduce cardiovascular risk in people with serious mental illness.

BACKGROUND: Cardiovascular (CV) disease is the leading cause of death for people with serious mental illness (SMI), but clinicians are often slow to address this risk. METHODS/DESIGN: 78 Midwestern primary care clinics were randomized to receive or not receive access to a clinical decision support (CDS) tool. Between March 2016 and September 2018, primary care clinicians (PCPs) received CDS alerts during visits with adult patients with SMI who met minimal inclusion criteria and had at least one CV risk factor not at goal. The PCP CDS included a summary of six modifiable CV risk factors and patient-specific treatment recommendations. Psychiatrists received CDS alerts during their next visit with an eligible patient with SMI that alerted them to an elevated body mass index or recent weight gain and the presence of an obesogenic SMI medication. Study outcomes include total modifiable CV risk, six modifiable CV risk factors, and use of obesogenic SMI medications. DISCUSSION: This cluster-randomized pragmatic trial allowed PCPs and psychiatrists the opportunity to improve CV risk in a timely manner for patients with SMI. Effectiveness will be assessed using an intent-to-treat analysis, and outcomes will be assessed largely through electronic health record data harvested by the CDS tool itself. In total, 10,347 patients with SMI had an index primary care visit in a randomized clinic, and 8937 patients had at least one follow-up visit. Analyses are ongoing, and trial results are expected in mid-2020. TRIAL REGISTRATION: ClinicalTrials.gov Identifier: NCT02451670.

Understanding Primary Care Provider Attitudes and Behaviors Regarding Cardiovascular Disease Risk and Diabetes Prevention in the Northern Midwest.

IN BRIEF We sought to fill critical gaps in understanding primary care providers' (PCPs') beliefs regarding diabetes prevention and cardiovascular disease risk in the prediabetes population, including through comparison of attitudes between rural and non-rural PCPs. We used data from a 2016 cross-sectional survey sent to 299 PCPs practicing in 36 primary clinics that are part of a randomized control trial in a predominately rural northern Midwestern integrated health care system. Results showed a few significant, but clinically marginal, differences between rural and non-rural PCPs. Generally, PCPs agreed with the importance of screening for prediabetes and thoroughly and clearly discussing CV risk with high-risk patients.

Potentially Preventable Hospital and Emergency Department Events: Lessons from a Large Innovation Project.

INTRODUCTION: There are few proven strategies to reduce the frequency of potentially preventable hospitalizations and Emergency Department (ED) visits. To facilitate strategy development, we documented these events among complex patients and the factors that contribute to them in a large care-improvement initiative. METHODS: Observational study with retrospective audits and selective interviews by the patients' care managers among 12 diverse medical groups in California, Minnesota, Pennsylvania, and Washington that participated in an initiative to implement collaborative care for patients with both depression and either uncontrolled diabetes, uncontrolled hypertension, or both. We reviewed information about 373 adult patients with the required conditions who belonged to these medical groups and had experienced 389 hospitalizations or ED visits during the 12-month study period from March 30, 2014, through March 29, 2015. The main outcome measures were potentially preventable hospitalizations or ED visit events. RESULTS: Of the studied events, 28% were considered to be potentially preventable (39% of ED visits and 14% of hospitalizations) and 4.6% of patients had 40% of events. Only type of insurance coverage; patient lack of resources, caretakers, or understanding of care; and inability to access clinic care were more frequent in those with potentially preventable events. Neither disease control nor ambulatory care-sensitive conditions were associated with potentially preventable events. CONCLUSION: Among these complex patients, patient characteristics, disease control, and the presence of ambulatory care-sensitive conditions were not associated with likelihood of ED visits or hospital admissions, including those considered to be potentially preventable. The current focus on using ambulatory care-sensitive conditions as a proxy for potentially preventable events needs further evaluation.

The Challenges of Collecting and Using Patient Care Data From Diverse Care Systems: Lessons From COMPASS.

The ability to aggregate clinical data across multiple diverse organizations and to use it for performance measurement, quality improvement, evaluation, and research is rapidly becoming a national necessity, but there are few examples of how to do that. This article uses lessons from a national effort to implement the collaborative care management model for patients with both depression and diabetes or heart disease across 8 partner organizations, 18 medical groups, and more than 170 clinics in 8 states to identify the challenges and provide experience-based recommendations for those tasks. The challenges are divided into those needed for (1) collecting similar data, (2) aggregating those data across care systems, and (3) using the data to both improve and evaluate care. Start with agreement on goals, methods, transparency, and a data system integrated into the electronic medical record while promptly addressing all the legal, regulatory, and human subject requirements.

Impact of A National Collaborative Care Initiative for Patients With Depression and Diabetes or Cardiovascular Disease.

(Reprinted with permission from General Hospital Psychiatry 44 (2017) 77-85).

Impact of a national collaborative care initiative for patients with depression and diabetes or cardiovascular disease.

OBJECTIVE: The spread of evidence-based care is an important challenge in healthcare. We evaluated spread of an evidence-based large-scale multisite collaborative care model for patients with depression and diabetes and/or cardiovascular disease (COMPASS). METHODS: Primary care patients with depression and comorbid diabetes or cardiovascular disease were recruited. Collaborative care teams used care management tracking systems and systematic case reviews to track and intensify treatment for patients not improving. Targeted outcomes were depression remission and response (assessed with the Patient Health Questionnaire-9) and control of diabetes (assessed by HbA1c) and blood pressure. Patients and clinicians were surveyed about satisfaction with care. RESULTS: Eighteen care systems and 172 clinics enrolled 3609 patients across the US. Of those with uncontrolled disease at enrollment, 40% achieved depression remission or response, 23% glucose control and 58% blood pressure control during a mean follow-up of 11 months. There were large variations in outcomes across medical groups. Patients and clinicians were satisfied with COMPASS care. CONCLUSIONS: COMPASS was successfully spread across diverse care systems and demonstrated improved outcomes for complex patients with previously uncontrolled chronic disease. Future large-scale implementation projects should create robust processes to identify and reduce expected variation in implementation to consistently provide improved care.

A stepped-wedge evaluation of an initiative to spread the collaborative care model for depression in primary care.

PURPOSE: Scale-up and spread of evidence-based practices is one of the most important challenges facing health care. We tested whether a statewide initiative, Depression Improvement Across Minnesota-Offering a New Direction (DIAMOND), to implement the collaborative care model for depression in 75 primary care clinics resulted in patient outcome improvements corresponding to those reported in randomized controlled trials. METHODS: Health plans provided a new monthly payment to participating clinics after a 6-month intensive training program with ongoing data submission, networking, and consultation. Implementation was staggered, with 5 sequences of 10 to 40 clinics every 6 months. Payers provided weekly contact information for members from participating clinics who were filling antidepressant prescriptions, and we conducted baseline and 6-month surveys of 1,578 patients about their care and outcomes. RESULTS: There were 466 patients in DIAMOND clinics who received usual care before implementation (UCB), 559 who received usual care in DIAMOND clinics after implementation (UCA), 245 who received DIAMOND care after implementation (DCA), and 308 who received usual care in comparison clinics (UC). Patients who received DIAMOND care after implementation reported more collaborative care depression services than the 3 comparison groups (10.9 vs 6.4-6.7, on a scale of 0 of 14, where higher numbers indicate more services; P <.001) and more satisfaction with their care (4.0 vs 3.4 on a scale 1 to 5, in which higher scores indicate higher satisfaction; P ≤.001). Depression remission rates, however, were not significantly different among the 4 groups (36.4% DCA vs 35.8% UCB, 35.0% UCA, 33.9% UC; P = .94). CONCLUSIONS: Despite the incentive of a supporting payment change and intensive training and support for clinics volunteering to participate, no difference in depression outcomes was documented. Specific unmeasured actions present in trials but not present in these clinics may be critical for successful outcome improvement.

Methods for engaging stakeholders in comparative effectiveness research: a patient-centered approach to improving diabetes care.

Engaging stakeholders in the research process has the potential to improve quality of care and the patient care experience. Online patient community surveys can elicit important topic areas for comparative effectiveness research. Stakeholder meetings with substantial patient representation, as well as representation from health care delivery systems and research funding agencies, are a valuable tool for selecting and refining pilot research and quality improvement projects. Giving patient stakeholders a deciding vote in selecting pilot research topics helps ensure their 'voice' is heard. Researchers and health care leaders should continue to develop best-practices and strategies for increasing patient involvement in comparative effectiveness and delivery science research.

Effective Implementation of collaborative care for depression: what is needed?

OBJECTIVES: To identify the care model factors that were key for successful implementation of collaborative depression care in a statewide Minnesota primary care initiative. STUDY DESIGN: We used a mixed-methods design incorporating both qualitative data from clinic site visits and quantitative measures of patient activation and 6-month remission rates. METHODS: Care model factors identified from the site visits were tested for association with rates of activation into the program and remission rates. RESULTS: Nine factors were identified as important for successful implementation of collaborative care by the consultants who had trained and interviewed participating clinic teams, and rated according to a Likert Scale. Factors correlated with higher patient activation rates were: strong leadership support (0.63), well-defined and -implemented care manager roles (0.62), a strong primary care physician champion (0.60), and an on-site and accessible care manager (0.59). However, remission rates at 6 months were correlated with: an engaged psychiatrist (0.62), not seeing operating costs as a barrier to participation (0.56), and face-to-face communication (warm handoffs) between the care manager and primary care physician for new patients (0.54). CONCLUSIONS: Care model factors most important for successful program implementation differ for patient activation into the program versus remission at 6 months. Knowing which implementation factors are most important for successful activation will be useful for those interested in adopting this evidence-based approach to improving primary care for patients with depression.

Randomized trial of telephone outreach to improve medication adherence and metabolic control in adults with diabetes.

OBJECTIVE: Medication nonadherence is a major obstacle to better control of glucose, blood pressure (BP), and LDL cholesterol in adults with diabetes. Inexpensive effective strategies to increase medication adherence are needed. RESEARCH DESIGN AND METHODS: In a pragmatic randomized trial, we randomly assigned 2,378 adults with diabetes mellitus who had recently been prescribed a new class of medication for treating elevated levels of glycated hemoglobin (A1C) ≥8% (64 mmol/mol), BP ≥140/90 mmHg, or LDL cholesterol ≥100 mg/dL, to receive 1) one scripted telephone call from a diabetes educator or clinical pharmacist to identify and address nonadherence to the new medication or 2) usual care. Hierarchical linear and logistic regression models were used to assess the impact on 1) the first medication fill within 60 days of the prescription; 2) two or more medication fills within 180 days of the prescription; and 3) clinically significant improvement in levels of A1C, BP, or LDL cholesterol. RESULTS: Of the 2,378 subjects, 89.3% in the intervention group and 87.4% in the usual-care group had sufficient data to analyze study outcomes. In intent-to-treat analyses, intervention was not associated with significant improvement in primary adherence, medication persistence, or intermediate outcomes of care. Results were similar across subgroups of patients defined by age, sex, race/ethnicity, and study site, and when limiting the analysis to those who completed the intended intervention. CONCLUSIONS: This low-intensity intervention did not significantly improve medication adherence or control of glucose, BP, or LDL cholesterol. Wide use of this strategy does not appear to be warranted; alternative approaches to identify and improve medication adherence and persistence are needed.

Novel use and utility of integrated electronic health records to assess rates of prediabetes recognition and treatment: brief report from an integrated electronic health records pilot study.

OBJECTIVE: This study uses novel methods to examine the frequency of diagnosis and treatment of prediabetes in real-world clinical settings using electronic health record (EHR) data. RESEARCH DESIGN AND METHODS: We identified a cohort of 358,120 adults with incident prediabetes (fasting plasma glucose [FPG] 100-125 mg/dL or glycated hemoglobin 5.7-6.4% [39-46 mmol/mol]) between 2006 and 2010 and examined rates of diagnosis and treatment in the 6 months after identification. RESULTS: In the 6 months after identification of prediabetes, 18% of patients had their blood glucose levels retested; 13% received a physician diagnosis of prediabetes/hyperglycemia; 31.0% had prediabetes, diabetes, or lifestyle documented in the clinical notes; and <0.1% initiated metformin. Among patients with FPG 120-125 mg/dL, 31% were retested; metformin initiation remained <1%. CONCLUSIONS: Documented rates of follow-up and treatment for prediabetes are low. EHR data may be a valuable tool to improve identification and treatment of prediabetes in the U.S.

The DIAMOND initiative: implementing collaborative care for depression in 75 primary care clinics.

BACKGROUND: The many randomized trials of the collaborative care model for improving depression in primary care have not described the implementation and maintenance of this model. This paper reports how and the degree to which collaborative care process changes were implemented and maintained for the 75 primary care clinics participating in the DIAMOND Initiative (Depression Improvement Across Minnesota-Offering a New Direction). METHODS: Each clinic was trained to implement seven components of the model and participated in ongoing evaluation and facilitation activities. For this study, assessment of clinical process implementation was accomplished via completion of surveys by the physician leader and clinic manager of each clinic site at three points in time. The physician leader of each clinic completed a survey measure of the presence of various practice systems prior to and one and two years after implementation. Clinic managers also completed a survey of organizational readiness and the strategies used for implementation. RESULTS: Survey response rates were 96% to 100%. The systems survey confirmed a very high degree of implementation (with large variation) of DIAMOND depression practice systems (mean of 24.4 ± 14.6%) present at baseline, 57.0 ± 21.0% at one year (P = <0.0001), and 55.9 ± 21.3% at two years. There was a similarly large increase (and variation) in the use of various quality improvement strategies for depression (mean of 29.6 ± 28.1% at baseline, 75.1 ± 22.3% at one year (P = <0.0001), and 74.6 ± 23.0% at two years. CONCLUSIONS: This study demonstrates that under the right circumstances, primary care clinics that are prepared to implement evidence-based care can do so if financial barriers are reduced, effective training and facilitation are provided, and the new design introduces the specific mental models, new care processes, and workers and expertise that are needed. Implementation was associated with a marked increase in the number of improvement strategies used, but actual care and outcomes data are needed to associate these changes with patient outcomes and patient-reported care.

Designing and implementing research on a statewide quality improvement initiative: the DIAMOND study and initiative.

OBJECTIVE: To demonstrate a rigorous methodology that optimally balanced internal validity with generalizability to evaluate a statewide collaborative that implemented an evidence-based, collaborative care model for depression management in primary care. STUDY DESIGN AND SETTING: Several operational features of the DIAMOND (Depression Improvement Across Minnesota, Offering a New Direction) Initiative suggested that the DIAMOND Study use a staggered implementation design with repeated cross-sections of patients across clinical settings. A multilevel recruitment strategy elicited virtually complete study participation from the medical groups, clinics, and health plans that coordinated efforts to deliver and reimburse DIAMOND care. Patient identification capitalized on large health plan claims databases to rapidly identify the population of patients newly treated for depression in DIAMOND clinics. RESULTS: The staggered implementation design and multilevel recruitment strategy made it possible to evaluate DIAMOND by holding confounding factors constant and accurately identifying an intent-to-treat population of patients treated for depression without intruding on or requiring effort from their clinics. CONCLUSIONS: Recruitment and data collection from health plans, medical groups and clinics, and patients ensured a representative, intent-to-treat sample of study-enrolled patients. Separating patient identification from care delivery reduced threats of selection bias and enabled comparisons between the treated population and study sample. A key challenge is that intent-to-treat patients may not be exposed to DIAMOND which dilutes the effect size but offers realistic expectations of the impact of quality improvement in a population of treated patients.