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Research ArticleOriginal Research

Intervention to Improve Psychosocial Care for People with Type 2 Diabetes

Deborah J. Cohen, Shannon M. Sweeney, Rachel Springer, Bijal A. Balasubramanian, LeAnn Michaels, Miguel Marino, Danielle Hessler, Andrea Baron and Johanna Nesse
The Journal of the American Board of Family Medicine March 2025, 38 (2) 253-274; DOI: https://doi.org/10.3122/jabfm.2024.240265R1
Deborah J. Cohen
From the Department of Family Medicine, Oregon Health & Science University, 3181 Sam Jackson Park Road, Portland, OR (DJC, SMS, RS, LM, MM, AN); Department of Epidemiology, University of Texas Health Science Center at Houston School of Public Health, Dallas, TX (BAB); Department of Family Medicine, University of California, San Francisco, CA (DH); OHSU Primary Care, Beaverton, OR (JN).
PhD
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Shannon M. Sweeney
From the Department of Family Medicine, Oregon Health & Science University, 3181 Sam Jackson Park Road, Portland, OR (DJC, SMS, RS, LM, MM, AN); Department of Epidemiology, University of Texas Health Science Center at Houston School of Public Health, Dallas, TX (BAB); Department of Family Medicine, University of California, San Francisco, CA (DH); OHSU Primary Care, Beaverton, OR (JN).
MPH, PhD
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Rachel Springer
From the Department of Family Medicine, Oregon Health & Science University, 3181 Sam Jackson Park Road, Portland, OR (DJC, SMS, RS, LM, MM, AN); Department of Epidemiology, University of Texas Health Science Center at Houston School of Public Health, Dallas, TX (BAB); Department of Family Medicine, University of California, San Francisco, CA (DH); OHSU Primary Care, Beaverton, OR (JN).
MS
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Bijal A. Balasubramanian
From the Department of Family Medicine, Oregon Health & Science University, 3181 Sam Jackson Park Road, Portland, OR (DJC, SMS, RS, LM, MM, AN); Department of Epidemiology, University of Texas Health Science Center at Houston School of Public Health, Dallas, TX (BAB); Department of Family Medicine, University of California, San Francisco, CA (DH); OHSU Primary Care, Beaverton, OR (JN).
MBBS, PhD
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LeAnn Michaels
From the Department of Family Medicine, Oregon Health & Science University, 3181 Sam Jackson Park Road, Portland, OR (DJC, SMS, RS, LM, MM, AN); Department of Epidemiology, University of Texas Health Science Center at Houston School of Public Health, Dallas, TX (BAB); Department of Family Medicine, University of California, San Francisco, CA (DH); OHSU Primary Care, Beaverton, OR (JN).
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Miguel Marino
From the Department of Family Medicine, Oregon Health & Science University, 3181 Sam Jackson Park Road, Portland, OR (DJC, SMS, RS, LM, MM, AN); Department of Epidemiology, University of Texas Health Science Center at Houston School of Public Health, Dallas, TX (BAB); Department of Family Medicine, University of California, San Francisco, CA (DH); OHSU Primary Care, Beaverton, OR (JN).
PhD
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Danielle Hessler
From the Department of Family Medicine, Oregon Health & Science University, 3181 Sam Jackson Park Road, Portland, OR (DJC, SMS, RS, LM, MM, AN); Department of Epidemiology, University of Texas Health Science Center at Houston School of Public Health, Dallas, TX (BAB); Department of Family Medicine, University of California, San Francisco, CA (DH); OHSU Primary Care, Beaverton, OR (JN).
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Andrea Baron
From the Department of Family Medicine, Oregon Health & Science University, 3181 Sam Jackson Park Road, Portland, OR (DJC, SMS, RS, LM, MM, AN); Department of Epidemiology, University of Texas Health Science Center at Houston School of Public Health, Dallas, TX (BAB); Department of Family Medicine, University of California, San Francisco, CA (DH); OHSU Primary Care, Beaverton, OR (JN).
MPH
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Johanna Nesse
From the Department of Family Medicine, Oregon Health & Science University, 3181 Sam Jackson Park Road, Portland, OR (DJC, SMS, RS, LM, MM, AN); Department of Epidemiology, University of Texas Health Science Center at Houston School of Public Health, Dallas, TX (BAB); Department of Family Medicine, University of California, San Francisco, CA (DH); OHSU Primary Care, Beaverton, OR (JN).
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    Figure 1.

    American Diabetes Association (ADA) recommendations for psychosocial care for patients with diabetes.1

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    Table 1.

    Intervention Components, Description, Frequency, and Timeline

    Intervention ComponentWho Provided SupportDescriptionFrequency and Timeline
    Expert TrainingPhysician, BHC, and expert in implementing DDEducation for clinical teams in ADA recommendations and self-management support materials on the following topics:
    • Psychosocial care, type 2 diabetes and DD training for all clinical roles delivered by a physician and DD expert

    • BHC training about the role of the BHC in caring for patient with type 2 diabetes delivered by a clinical psychologist with expertise in integrated behavioral health and primary care

    IC1 received these remotely March and May 2021
    IC2 was given a recording of these trainings. We do not know if these were reviewed by IC2.
    FacilitationPractice FacilitatorCustomized remote once-a-month meetings with an experienced practice facilitator using Bodenheimer’s Building Blocks framework and Plan Do Study Act (PDSA) cycles. Meeting topics were tailored to the clinic’s experience and aligned with ADA recommendations and included:
    • Patient education materials for BH and self-management support

    • Implementation of systematic screenings for DD, depression, anxiety

    • Identifying changes in roles/responsibilities, new processes/workflows for screening and treatment

    • Identify cross-functional practice team, train team in QI

    • Proactive outreach to patients regarding DMII, self-management status, community and family needs

    • Pre-visit planning and huddling, scheduling BHC visits with warm handoffs

    IC1: December 2020-February 2022
    IC2: June 2021-May 2022
    • Abbreviations: IC, Intervention clinic; BHC, Behavioral health clinician; DD, Diabetes distress; QI, Quality improvement; DMII, Type 2 Diabetes mellitus; ADA, American Diabetes Association.

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    Table 2.

    Study Measures, Variables and Data Sources

    Variable/DefinitionData SourceData Collection/Analysis
    Assess the Feasibility, Appropriateness and Acceptability of INTEGRATE-D
    Acceptability – extent to which intervention is agreeable, palatable, satisfactoryAssessed via survey15 and semi-structured interview. Survey had four questions per variable. See Online Appendix for items.Collected from clinic members exposed to the intervention ICs at the end of the intervention.
    Descriptive analysis for ICs only. Survey scores, which ranged from 1 (strongly disagree) to 5 (strongly agree) for each clinic member response were averaged at the clinic-level.
    Appropriateness – extent to which intervention fits and is compatible for addressing issue or problem
    Feasibility – extent to which an intervention can be successfully used or carried out
    Compare changes in use of quality-improving strategies
    Clinics’ ability to implement quality improving strategies related integrated type 2 diabetes careAssessed via survey using 14 items from the Change Process Capability Questionnaire (CPCQ).30 See Appendix 2 for items.One person at IC and CCs completed the survey at the same time, pre- and post-intervention.
    Survey scores, which ranged from −2 (strongly disagree) to +2 (strongly agree), were summed for each clinic with possible sums ranging from −28 to +28. Average aggregate scores were compared between IC versus CCs
    Compare changes in process of care screening rates
    A1C screening – binary variable indicating whether the patient was screened at least once during the periodElectronic Health Record (EHR) data abstracted through manual and automated methodsOperationalized at the patient level for pre- and post-intervention periods, means aggregated at the clinic-level for IC and CC. Pre-intervention defined as the time during the 12 months before the intervention; post-intervention defined as any time during the 12 months following the start of the intervention.
    Cholesterol screening - binary variable indicating whether the patient was screened at least once during the period
    Nephropathy screening - binary variable indicating whether the patient was screened at least once during the period
    Psychosocial screenings – binary variables indicating whether the patient was screened at least once during the period for depression (PHQ-2 and/or PHQ-9) and/or for diabetes distress (DD)1
    Compare changes in clinical outcomes (PHQ-9 scores and A1C levels)
    Behavioral health – change in symptoms (PHQ-9) for patients with depression symptoms (PHQ-9 > 9); data abstracted through manual and automated methodsOperationalized at the patient level for pre- and post-intervention periods, means aggregated for intervention and control clinics; pre-intervention defined as score closest to the intervention start date; post-intervention defined as score closest to the intervention end date.
    Diabetes Management – change in A1C for patients diagnosed with type 2 diabetes
    Confounding Variables - Patient socio-demographics, comorbidity, insurance, and utilization
    Age, gender, language preference, race/ethnicity, income/federal poverty level, insurance type, physical, mental/behavioral health comorbidity, healthcare utilizationEHR data abstracted through manual and automated methodsOperationalized at the patient level
    • ↵1 Diabetes distress (DD) screening was implemented by IC; clinics did not screen for this pre-intervention.

    • Abbreviations: IC, intervention clinics; CC, control clinics.

    • View popup
    Table 3.

    Clinic Characteristics

    InterventionControl
    Practice number1212
    OwnershipFQHCHospitalFQHCHospital
    Geographic locationRuralUrbanRuralUrban
    Number of clinicians (MD, DO, NP, PA)1571012
    Number of licensed BHCs7141
    • Abbreviations: MD, Medical doctor; DO, Doctor of osteopathic medicine; NP, Nurse practitioner; PA, Physician assistant; BHC, Behavioral health clinicians.

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    Table 4.

    Change in CPCQ Measure

    PracticeBaselineFollow-upChangeCPCQ Items That Showed Most Change in ICs
    Intervention Clinic 1112+11
    • Providing information and skills-training

    • Using rapid cycling, piloting, pre-testing or other vehicles for reducing the risk of negative results from introducing organization-wide change in care

    • Deliberately designing care improvements to make the care process more beneficial to the patient

    • Customizing the implementation of diabetes disease prevention care changes to the practice

    Intervention Clinic 21422*+8
    Total average intervention7.517+9.5
    Control Clinic 11721+4
    Control Clinic 21621+5
    Total average control16.521+4.5
    • ↵*Left missing (computed as 0 = neutral) on two questions that were previously completed as +2. Were these +2 responses carried forward, the follow-up score for this clinic would be 26.

    • Abbreviations: CPCQ, change process capability questionnaire; IC, intervention clinics.

    • View popup
    Table 5.

    Change in Process of Care Measures

    InterventionControl
    Clinic 1Clinic 2Clinic 1Clinic 2
    Pre-Post-Pre-Post-Pre-Post-Pre-Post-
    Group 1*: Patients with type II diabetes who did not screen positive for depression or diabetes distress, N (%)
    Screening PHQ-2 or 930 (60%)15 (30%)12 (24%)21 (42%)32 (62%)29 (58%)29 (58%)36 (72%)
    Screening diabetes distress (DD)0 (0%)0 (0%)0 (0%)0 (0%)0 (0%)0 (0%)0 (0%)0 (0%)
    Up-to-date A1C screening41 (82%)38 (76%)44 (88%)47 (95%)37 (74%)30 (60%)46 (92%)47 (94%)
    Up-to-date nephrology screening44 (88%)38 (76%)44 (88%)39 (77%)30 (60%)23 (46%)47 (94%)47 (94%)
    Up-to-date cholesterol screening31 (62%)27 (54%)36 (72%)36 (72%)34 (68%)31 (62%)36 (72%)28 (58%)
    Group 2**: Patients with type II diabetes who screened positive for depression or diabetes distress, N (%)
    Screening PHQ-2 or 92 (7%)3 (10%)0 (0%)0 (0%)12 (40%)10 (33%)8 (27%)13 (43%)
    Screening diabetes distress (DD)0 (0%)11 (37%)0 (0%)1 (25%)0 (0%)0 (0%)0 (0%)0 (0%)
    Up-to-date A1C screening26 (87%)26 (87%)4 (100%)4 (100%)25 (83%)25 (83%)28 (93%)25 (83%)
    Up-to-date nephrology screening25 (83%)29 (97%)4 (100%)3 (75%)15 (50%)23 (78%)24 (80%)26 (87%)
    Up-to-date cholesterol screening18 (60%)20 (67%)2 (50%)3 (75%)19 (63%)27 (90%)21 (70%)21 (70%)
    • ↵*Sample of 50 patients per clinic.

    • ↵**Sample of 30 patients per clinic, with the exception of Clinic 2, where only 4 patients screened positive for depression or diabetes distress.

    • View popup
    Table 6.

    Adjusted* Change in PHQ-9 and A1C, Means and 95% Confidence Intervals (CIs)

    InterventionControl
    Pre-Post-Pre-Post-P value**
    Group 1: Patients with type II diabetes who did not screen positive for depression or diabetes distress, N (%)******
    A1C (mean. 95% CI)7.69 (7.33, 8.05)7.67 (7.29, 8.05)6.87 (6.48, 7.25)6.77 (6.37, 7.18)0.747
    Group 2: Patients with type II diabetes who screened positive for depression or diabetes distress***
    A1C (mean, 95% CI)7.37 (6.78, 7.95)7.44 (6.82, 8.07)7.25 (6.82, 7.68)7.38 (6.92, 7.83)0.905
    PHQ-9 (mean, 95% CI)13.91 (9.38, 18.44)15.77 (8.64, 22.89)10.66 (8.64, 12.67)12.61 (10.54, 14.68)0.980
    • The Patient Health Questionnaire-9 (PHQ-9) is a depression screening tool that uses a scoring range of 0–27 to indicate the Severity of depression: 0–4: None to minimal depression, and the patient may not need treatment; 5–9: Mild depression; 10–14: Moderate depression; 15–19: Moderately severe depression; 20–27: Severe depression.

    • *Covariate adjustment incorporates patient socio-demographic characteristics as shown in Table 2.

    • ↵**Tests the difference in pre- versus post- change between intervention and control group.

    • ↵***Group 1 had a sample of 50 patients per clinic; group 2 had a sample of 30 patients per clinic, with the exception of Clinic 2, where only 4 patients screened positive for depression or diabetes distress.

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The Journal of the American Board of Family     Medicine: 38 (2)
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Intervention to Improve Psychosocial Care for People with Type 2 Diabetes
Deborah J. Cohen, Shannon M. Sweeney, Rachel Springer, Bijal A. Balasubramanian, LeAnn Michaels, Miguel Marino, Danielle Hessler, Andrea Baron, Johanna Nesse
The Journal of the American Board of Family Medicine Mar 2025, 38 (2) 253-274; DOI: 10.3122/jabfm.2024.240265R1

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Intervention to Improve Psychosocial Care for People with Type 2 Diabetes
Deborah J. Cohen, Shannon M. Sweeney, Rachel Springer, Bijal A. Balasubramanian, LeAnn Michaels, Miguel Marino, Danielle Hessler, Andrea Baron, Johanna Nesse
The Journal of the American Board of Family Medicine Mar 2025, 38 (2) 253-274; DOI: 10.3122/jabfm.2024.240265R1
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Keywords

  • Behavioral Counseling
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