Diabetes-Depression Care-management Adoption Trial (DCAT)

Care Management Technology to Facilitate Depression Care in Safety Net Diabetes Clinics

The specific aims of the proposed study are to:

1. Develop the innovative depression care management technology, including the speech recognition technology for automated monitoring and patient prompts over time, automatic integration of the responses into the patient registry, and evidence-based decision-support algorithms for care actions;
2. Conduct the quasi-experiment in eight Los Angeles County Department of Health Services (LAC-DHS) clinics to test the interventions;
3. Use mixed-method evaluation to assess the extent of the implementation of the interventions, the acceptance to the providers and to the patients, and the impact on adoption of depression screening and treatment management over time, utilization, and cost of healthcare services, and patient health outcomes; and
4. Conduct a cost-effectiveness analysis of the three study arms. Successful completion of the study will demonstrate which Comparative Effectiveness Research (CER) adoption strategies are successful and why, their comparative cost-effectiveness, as well as which strategies are successful under which circumstances to inform system-wide implementation of same.

Hypotheses of the Proposed Study

The following are the main hypotheses of the study:

1. There will be statistically significant difference in the adoption of depression care screening and management over time among the three study groups.

   1.1. The adoption rate will be Technology-supported care (TC) > Supported Care (SC) > Usual Care (UC).

2. There will be statistically significant difference in the depression symptom reduction, and better functional status, and quality of life among the three study groups.

   2.1. The difference between the TC and the SC will not be statistically significant, but both will be greater than the UC group.

3. There will be statistically significant difference in the diabetes care process and outcomes among the three study groups.

   3.1. The difference between the TC and the SC will not be statistically significant, but both will be greater than the UC group.

4. There will also be statistically significant differences in healthcare utilization among the three study groups, with least utilization in the TC group where the greatest level of technology is applied.
5. Of the three groups compared, the TC group will be the most cost-effective approach for accelerating adoption of the CER depression care results.

Study Overview

• Status: Completed
• Conditions: Depression; Diabetes Mellitus
• Intervention / Treatment: Other: Technology-supported care

Detailed Description

In addition, the study will aim to answer the secondary research questions listed below:

1. What is medical provider satisfaction with the technology used in the TC (Technology Care) group?
2. What is patient acceptance with the technology used in the TC group?
3. What factors are identified by medical providers and clinic administrators as related to satisfaction, barriers, and sustaining the intervention post-trial?
4. What are patients' reported satisfaction and facilitating factors and barriers to receipt and acceptance of depression care?

• Study Type: Interventional
• Enrollment (Actual): 1485
• Phase: Not Applicable

Contacts and Locations

Study Locations

• United States
  • California
    • El Monte, California, United States, 91731
      • El Monte Comprehensive Health Center
    • Lancaster, California, United States, 93536
      • High Desert Comprehensive Health Center
    • Long Beach, California, United States, 90813
      • Long Beach Comprehensive Health Center
    • Los Angeles, California, United States, 90007
      • H. Claude Hudson Comprehensive Health Center
    • Los Angeles, California, United States, 90022
      • Roybal Comprehensive Health Center
    • Sylmar, California, United States, 91342
      • Olive View-UCLA Medical Center Diabetes Clinic
    • Van Nuys, California, United States, 91405
      • Mid-Valley Comprehensive Health Center
    • Wilmington, California, United States, 90744
      • Harbor Comprehensive Health Center

Participation Criteria

Eligibility Criteria

• Ages Eligible for Study: 18 years and older (ADULT, OLDER_ADULT)
• Accepts Healthy Volunteers: No
• Genders Eligible for Study: All

Description

Inclusion Criteria:

• age equal to or greater than 18 years
• receiving primary care at DHS safety net clinics
• having a current diagnosis of type 2 diabetes mellitus (non-gestational).
• have a working telephone or cellular phone.

Exclusion Criteria:

• current suicidal ideation;
• inability to speak either English or Spanish;
• a score of 2 or greater on the CAGE (4M) alcohol assessment;
• having schizophrenia, schizoaffective disorder, manic-depressive, or needing lithium;
• and cognitive impairment precluding ability to give informed consent or participating in the intervention, i.e., Short Portable Mental Status Questionnaire(SPMSQ) score of 6 or more errors.

Provider and administrator inclusion criteria are: practicing or managing at one of the eight study sites; involved with diabetes or depression care

No specific exclusion criteria will be applied to providers and administrators.

Study Plan

How is the study designed?

Design Details

• Primary Purpose: HEALTH_SERVICES_RESEARCH
• Allocation: NON_RANDOMIZED
• Interventional Model: PARALLEL
• Masking: NONE

Number of Arms

3

Arms and Interventions

Participant Group / Arm	Intervention / Treatment
EXPERIMENTAL: Technology-supported care; This arm consists of Clinic Resource Management (CRM) clinics and serves as our intervention arm where the tested technology is implemented. Our overarching aim in these comparisons is to assess the potential effects of technology-facilitated depression symptom monitoring, relapse prevention, and medication adjustments and to examine depression care receipt and symptom improvement, patient/provider acceptance, and cost.	Other: Technology-supported care; The depression care-management technology that will interact with patients is the Automated Speech Recognition (ASR) for remote monitoring data collection. The ASR will use automated telephone calls to reach out to patients to repeat depression screening using PHQ-9, triggered either by calendar date or upcoming appointments, and to remind patients of their appointments in pre-determined time. In addition, the ASR will apply a structured script to conduct automatic follow-up with patients regarding their depression treatment adherence and side effects in order to provide data to help primary medical providers promptly and optimally adapt treatment. The ASR script will also include structured relapse prevention prompts. For providers and administrators, the depression care-management technology aimed to improve their workflow regarding depression care is Enhanced Disease Registry (EDR)..
NO_INTERVENTION: Supported-Care; This arm consists of CRM (Clinic Resource Management) clinics and serves as one of the two control arms in the study.
NO_INTERVENTION: Usual Care; This arm consists of non-CRM (Clinic Resource Management) clinics and serves as one of the two control arms in the study.

What is the study measuring?

Primary Outcome Measures

Outcome Measure	Measure Description	Time Frame
Change from baseline in depression outcome at 6-months	Depression is measured using depression scales Patient Health Questionnaire (PHQ)-9. Major depression is classified as PHQ-9>=10.	6-months from enrollment

Secondary Outcome Measures

Outcome Measure	Measure Description	Time Frame
Change from baseline in diabetes self-care score in 6 months	Diabetes self-care is measured using the Toolbert diabetes self-care scale.	6 months from enrollment

Other Outcome Measures

Outcome Measure	Measure Description	Time Frame
Change from baseline in physical functional status in 6 months	Physical functional status is measured using the physical component score of the SF-12 scale	6 months from enrollment
Change from baseline in mental functional status in 6 months	Mental functional status is measured using the mental component score of the SF-12 scale	6 months from enrollment
Change from baseline in physical functional status in 12 months	Physical functional status is measured using the physical component score of the SF-12 scale	12 months from enrollment
Change from baseline in mental functional status in 12 months	Mental functional status is measured using the mental component score of the SF-12 scale	12 months after enrollment
Change from baseline of mental health-related functional impairment in 12 months	Assessed using the Sheehan disability scale	12 months from enrollment
Change from baseline of mental health-related functional impairment in 6 months	Assessed using the Sheehan disability scale	6 months from enrollment
Change from baseline in depression outcome in 12 months	Depression is measured using depression scales Patient Health Questionnaire (PHQ)-9. Major depression is classified as PHQ-9>=10.	12 months from enrollment
Change from baseline in diabetes self-care score in 12 months	Diabetes self-care is measured using Toolbert diabetes self-care scale.	12 months after enrollment
Change from baseline of diabetes symptoms in 12 months	Assessed using the Whitty-9 diabetes symptoms scale	12 months from enrollment
Change from baseline of diabetes symptoms in 6 months	Assessed using the Whitty-9 diabetes symptoms scale	6 months from enrollment
Change from baseline in percentage of patients who receive HbA1C lab test in 12 months	This is one of our diabetes care processes measure. We are going to analyze the percentage of patients who receive the requisite lab tests, including HbA1C, microalbumin, and lipid panel.	12 months from enrollment
Change from baseline in percentage of patients who receive the lipid panel lab test in 12 months	This is one of our diabetes care processes measure. We are going to analyze the percentage of patients who receive the requisite lab tests, including HbA1C, microalbumin, and lipid panel.	12 months from enrollment
Change from baseline in percentage of patients who receive microalbumin lab test in 12 months	This is one of our diabetes care processes measure. We are going to analyze the percentage of patients who receive the requisite lab tests, including HbA1C, microalbumin, and lipid panel.	12 months from enrollment
Change from baseline in percentage of patients who receive HbA1C lab test in 6 months	This is one of our diabetes care processes measure. We are going to analyze the percentage of patients who receive the requisite lab tests, including HbA1C, microalbumin, and lipid panel.	6 months from enrollment
Change from baseline in percentage of patients who receive the lipid panel lab test in 6 months	This is one of our diabetes care processes measure. We are going to analyze the percentage of patients who receive the requisite lab tests, including HbA1C, microalbumin, and lipid panel	6 months from enrollment
Change from baseline in percentage of patients who receive microalbumin lab test in 6 months	This is one of our diabetes care processes measure. We are going to analyze the percentage of patients who receive the requisite lab tests, including HbA1C, microalbumin, and lipid panel.	6 months from enrollment
Change from baseline in percentage of patients whose HbA1C is in control in 12 months	This is part of our diabetes outcome measure. We would like to know the percentage of patients whose HbA1C is in control pre- and post-intervention. HbA1C is considered controlled if it is <7%.	12 months from enrollment
Change from baseline in percentage of patients whose microalbumin is in control in 12 months	This is part of our diabetes outcome measure. We would like to know the percentage of patients whose microalbumin is in control pre- and post-intervention. Microalbumin is considered controlled if it is <30 microg/mg.	12 months from enrollment
Change from baseline in percentage of patients whose total cholesterol is in control in 12 months	This is part of our diabetes outcome measure. We would like to know the percentage of patients whose total cholesterol is in control pre- and post-intervention. Total cholesterol is considered controlled if it is <200mg/dL.	12 months from enrollment
Change from baseline in percentage of patients whose LDL cholesterol is in control in 12 months	This is part of our diabetes outcome measure. We would like to know the percentage of patients whose LDL cholesterol is in control pre- and post-intervention. LDL cholesterol is considered controlled if it is <100mg/dL.	12 months from enrollment
Change from baseline in percentage of patients whose HDL cholesterol is in control in 12 months	This is part of our diabetes outcome measure. We would like to know the percentage of patients whose HDL cholesterol is in control pre- and post-intervention. HDL cholesterol is considered controlled if it is <40mg/dL.	12 months from enrollment
Change from baseline in percentage of patients whose triglycerides is in control in 12 months	This is part of our diabetes outcome measure. We would like to know the percentage of patients whose triglycerides is in control pre- and post-intervention. Triglycerides is considered controlled if it is >200mg/dL.	12 months from enrollment
Change from baseline in percentage of patients whose HbA1C is in control in 6 months	This is part of our diabetes outcome measure. We would like to know the percentage of patients whose HbA1C is in control pre- and post-intervention. HbA1C is considered controlled if it is <7%.	6 months from enrollment
Change from baseline in percentage of patients whose microalbumin is in control in 6 months	This is part of our diabetes outcome measure. We would like to know the percentage of patients whose microalbumin is in control pre- and post-intervention. Microalbumin is considered controlled if it is <20mg/L.	6 months from enrollment
Change from baseline in percentage of patients whose total cholesterol is in control in 6 months	This is part of our diabetes outcome measure. We would like to know the percentage of patients whose total cholesterol is in control pre- and post-intervention. Total cholesterol is considered controlled if it is >240mg/dL	6 months from enrollment
Change from baseline in percentage of patients whose LDL cholesterol is in control in 6 months	This is part of our diabetes outcome measure. We would like to know the percentage of patients whose LDL cholesterol is in control pre- and post-intervention. LDL cholesterol is considered controlled if it is >160mg/dL.	6 months from enrollment
Change from baseline in percentage of patients whose HDL cholesterol is in control in 6 months	This is part of our diabetes outcome measure. We would like to know the percentage of patients whose HDL cholesterol is in control pre- and post-intervention. HDL cholesterol is considered controlled if it is >60mg/dL.	6 months from enrollment
Change from baseline in percentage of patients whose triglycerides is in control in 6 months	This is part of our diabetes outcome measure. We would like to know the percentage of patients whose triglycerides is in control pre- and post-intervention. Triglycerides is considered controlled if it is <150mg/dL	6 months from enrollment
Change from baseline to 12 months in number of outpatient visits during the past 6 months	This is part of our utilization measure. We would like to know the number of outpatient visits during 6-months before baseline and between 6- and 12-months after enrollment.	12 months from enrollment
Change from baseline to 6 months in number of outpatient visits during the past 6 months	This is part of our utilization measure. We would like to know the number of outpatient visits during 6-months before baseline and during the 6-months after enrollment.	6 months from enrollment
Change from baseline to 12 months in percentage of patients who were hospitalized during the past 6 months	This is part of our utilization measure. We would like to know the percentage of hospitalized patients during 6-months before baseline and between 6- and 12-months after enrollment.	12 months from enrollment
Change from baseline to 6 months in percentage of hospitalized patients during the past 6 months	This is part of our utilization measure. We would like to know the percentage of hospitalized patients during 6-months before baseline and during the 6-months after enrollment.	6 months from enrollment
Change from baseline to 12 months in percentage of patients with ER visits during the past 6 months	This is part of our utilization measure. We would like to know the percentage of patients with ER visits during 6-months before baseline and between 6- and 12-months after enrollment.	12 months from enrollment
Change from baseline to 6 months in percentage of patients with ER visits during the past 6 months	This is part of our utilization measure. We would like to know the percentage of patients with ER visits during 6-months before baseline and during the 6-months after enrollment.	6 months from enrollment
Difference between cost of care management in the intervention group and the control groups over a 12-month period per patient	Cost of care management includes automated phone calls, provider time, costs associated with reviewing tasks and follow-ups.	12 months
Change from baseline to 12 months in percentage of patients satisfied with care received for diabetes	Measured by the percentage of patients who answered "satisfied" or "very satisfied" to the question "How satisfied / dissatisfied are you with the overall health care available to you for your diabetes?" (with a 5-point Likert scale response option)	12 months from enrollment
Change from baseline to 6 months in percentage of patients satisfied with care received for diabetes	Measured by the percentage of patients who answered "satisfied" or "very satisfied" to the question "How satisfied / dissatisfied are you with the overall health care available to you for your diabetes?" (with a 5-point Likert scale response option)	6 months from enrollment
Change from baseline to 12 months in percentage of patients satisfied with care received for depression	Measured by the percentage of patients who answered "satisfied" or "very satisfied" to the question "How satisfied / dissatisfied are you with the clinical help received with your emotional problem?" (with a 5-point Likert scale response option)	12 months from enrollment
Change from baseline to 6 months in percentage of patients satisfied with care received for depression	Measured by the percentage of patients who answered "satisfied" or "very satisfied" to the question "How satisfied / dissatisfied are you with the clinical help received with your emotional problem?" (with a 5-point Likert scale response option)	6 months from enrollment

Collaborators and Investigators

• Sponsor: University of Southern California
• Collaborators: Department of Health and Human Services

Publications and helpful links

General Publications

• Lin EH, Katon W, Von Korff M, Rutter C, Simon GE, Oliver M, Ciechanowski P, Ludman EJ, Bush T, Young B. Relationship of depression and diabetes self-care, medication adherence, and preventive care. Diabetes Care. 2004 Sep;27(9):2154-60. doi: 10.2337/diacare.27.9.2154.
• Wells KB, Stewart A, Hays RD, Burnam MA, Rogers W, Daniels M, Berry S, Greenfield S, Ware J. The functioning and well-being of depressed patients. Results from the Medical Outcomes Study. JAMA. 1989 Aug 18;262(7):914-9.
• Katon WJ. The comorbidity of diabetes mellitus and depression. Am J Med. 2008 Nov;121(11 Suppl 2):S8-15. doi: 10.1016/j.amjmed.2008.09.008.
• Anderson RJ, Freedland KE, Clouse RE, Lustman PJ. The prevalence of comorbid depression in adults with diabetes: a meta-analysis. Diabetes Care. 2001 Jun;24(6):1069-78. doi: 10.2337/diacare.24.6.1069.
• Golden SH, Lazo M, Carnethon M, Bertoni AG, Schreiner PJ, Diez Roux AV, Lee HB, Lyketsos C. Examining a bidirectional association between depressive symptoms and diabetes. JAMA. 2008 Jun 18;299(23):2751-9. doi: 10.1001/jama.299.23.2751.
• U.S. Preventive Services Task Force. Screening for depression in adults: U.S. preventive services task force recommendation statement. Ann Intern Med. 2009 Dec 1;151(11):784-92. doi: 10.7326/0003-4819-151-11-200912010-00006.
• Anderson RJ, Gott BM, Sayuk GS, Freedland KE, Lustman PJ. Antidepressant pharmacotherapy in adults with type 2 diabetes: rates and predictors of initial response. Diabetes Care. 2010 Mar;33(3):485-9. doi: 10.2337/dc09-1466. Epub 2009 Dec 23.
• Ell K, Xie B, Quon B, Quinn DI, Dwight-Johnson M, Lee PJ. Randomized controlled trial of collaborative care management of depression among low-income patients with cancer. J Clin Oncol. 2008 Sep 20;26(27):4488-96. doi: 10.1200/JCO.2008.16.6371.
• Cabassa LJ, Hansen MC, Palinkas LA, Ell K. Azucar y nervios: explanatory models and treatment experiences of Hispanics with diabetes and depression. Soc Sci Med. 2008 Jun;66(12):2413-24. doi: 10.1016/j.socscimed.2008.01.054. Epub 2008 Mar 12.
• Katon W, Robinson P, Von Korff M, Lin E, Bush T, Ludman E, Simon G, Walker E. A multifaceted intervention to improve treatment of depression in primary care. Arch Gen Psychiatry. 1996 Oct;53(10):924-32. doi: 10.1001/archpsyc.1996.01830100072009.
• Jin H, Wu S. Text Messaging as a Screening Tool for Depression and Related Conditions in Underserved, Predominantly Minority Safety Net Primary Care Patients: Validity Study. J Med Internet Res. 2020 Mar 26;22(3):e17282. doi: 10.2196/17282.
• Hay JW, Lee PJ, Jin H, Guterman JJ, Gross-Schulman S, Ell K, Wu S. Cost-Effectiveness of a Technology-Facilitated Depression Care Management Adoption Model in Safety-Net Primary Care Patients with Type 2 Diabetes. Value Health. 2018 May;21(5):561-568. doi: 10.1016/j.jval.2017.11.005. Epub 2017 Dec 6.
• Ramirez M, Wu S, Jin H, Ell K, Gross-Schulman S, Myerchin Sklaroff L, Guterman J. Automated Remote Monitoring of Depression: Acceptance Among Low-Income Patients in Diabetes Disease Management. JMIR Ment Health. 2016 Jan 25;3(1):e6. doi: 10.2196/mental.4823.
• Ell K, Katon W, Lee PJ, Guterman J, Wu S. Demographic, clinical and psychosocial factors identify a high-risk group for depression screening among predominantly Hispanic patients with Type 2 diabetes in safety net care. Gen Hosp Psychiatry. 2015 Sep-Oct;37(5):414-9. doi: 10.1016/j.genhosppsych.2015.05.010. Epub 2015 May 29.
• Wu S, Vidyanti I, Liu P, Hawkins C, Ramirez M, Guterman J, Gross-Schulman S, Sklaroff LM, Ell K. Patient-centered technological assessment and monitoring of depression for low-income patients. J Ambul Care Manage. 2014 Apr-Jun;37(2):138-47. doi: 10.1097/JAC.0000000000000027.
• Wu S, Ell K, Gross-Schulman SG, Sklaroff LM, Katon WJ, Nezu AM, Lee PJ, Vidyanti I, Chou CP, Guterman JJ. Technology-facilitated depression care management among predominantly Latino diabetes patients within a public safety net care system: comparative effectiveness trial design. Contemp Clin Trials. 2014 Mar;37(2):342-54. doi: 10.1016/j.cct.2013.11.002. Epub 2013 Nov 8.

Study record dates

Study Major Dates

• Study Start: June 1, 2010
• Primary Completion (ACTUAL): September 1, 2013
• Study Completion (ACTUAL): September 1, 2013

Study Registration Dates

• First Submitted: January 29, 2013
• First Submitted That Met QC Criteria: January 29, 2013
• First Posted (ESTIMATE): January 31, 2013

Study Record Updates

• Last Update Posted (ESTIMATE): December 5, 2014
• Last Update Submitted That Met QC Criteria: December 3, 2014
• Last Verified: December 1, 2014

More Information

Terms related to this study

• Keywords: Care management; Behavioral health; Clinical decision support; Chronic illness; Depression screening; Depression monitoring; Automatic telephone assessment; Suicide alert
• Additional Relevant MeSH Terms: Behavioral Symptoms; Mental Disorders; Glucose Metabolism Disorders; Metabolic Diseases; Mood Disorders; Endocrine System Diseases; Depression; Depressive Disorder; Diabetes Mellitus
• Other Study ID Numbers: RFA-AE-10-001