Achieving Chronic Care equiTy by leVeraging the Telehealth Ecosystem (ACCTiVATE)

This study examines the impact of a multi-level intervention aiming to improve telehealth access for low-income patients managing chronic health conditions, such as hypertension and diabetes. The multi-level intervention includes clinic-level practice facilitation and patient-level digital health coaching.

Study Overview

• Status: Recruiting
• Conditions: Diabetes
• Intervention / Treatment: Other: Digital Health Coaching (Patient-Level Intervention); Other: Practice Facilitation (Clinic-Level Intervention)

Detailed Description

ACCTIVATE is a multi-level intervention (including practice facilitation and patient digital coaching) that aims to tackle patient-level and clinic-level barriers to increase the equitable use of telehealth tools for chronic disease management. Direct patient support via digital coaching can meet the needs of patients who have been left behind in the digital divide. For those with reduced digital literacy and low access to smartphones and broadband, this resource can increase their confidence in using digital technologies and engaging in virtual care. Additionally, primary care clinic support through practice facilitation can empower team members to address racial/ethnic disparities in telehealth use through equitable screening/offering of digital technologies, resources to prepare patients for virtual chronic disease management, and consistent review of telehealth equity data. The investigators hypothesize that this multi-level intervention will improve patient control of chronic health conditions (i.e., glycosylated hemoglobin) as well as digital literacy, while also increasing patient and clinician engagement with patient portals, telehealth video visits and remote monitoring.

Aim 1: Assess the impact of the multi-level intervention on clinical outcomes at 3, 6, 12, and 24 months. Our working hypotheses are that patients randomized to receive digital coaching (vs. usual care) will experience a greater change in mean glycosylated hemoglobin A1C, both overall and among Black and Latinx patients. Clinics randomized to practice facilitation (vs. usual care) will experience a greater clinic-level change in mean glycosylated hemoglobin A1C, both overall and among their Black and Latinx populations.

Aim 2: Assess the impact of the multi-level intervention on process outcomes related to digital literacy, engagement in care, and health IT utilization at 3, 6, 12, and 24 months. The investigators hypothesize that randomization to digital coaching (vs. usual care) will increase patient portal use, digital literacy, and visit show rate, overall and among Black and Latinx patients. Randomization to practice facilitation (vs. usual care) will increase clinic-level use of telehealth video visits and patient-portal communication, overall and with Black and Latinx patients.

Aim 3: Conduct a mixed methods evaluation of intervention implementation outcomes. Quantitative engagement data, direct observations of intervention sessions, and stakeholder interviews will characterize implementation outcomes and factors necessary to integrate the multi-level intervention into clinical operations, applying the RE-AIM implementation science framework.

• Study Type: Interventional
• Enrollment (Estimated): 600
• Phase: Not Applicable

Contacts and Locations

• Study Contact: Name: Andy Ramirez, BS; Phone Number: 415-562-4509; Email: Andy.Ramirez@ucsf.edu
• Study Contact Backup: Name: Alexandra Velasquez, MS; Phone Number: 415-562-4509; Email: ACCTIVATEStudy@ucsf.edu

Study Locations

• United States
  • California
    • San Francisco, California, United States, 94110
      • Recruiting
      • Zuckerberg San Francisco General Hospital (ZSFG) & SF Department of Public Health (DPH)
      • Contact: Andy Ramirez, BS; Phone Number: 415-562-4509; Email: Andy.Ramirez@ucsf.edu
      • Contact: Alexandra Velasquez, MS; Phone Number: 415-562-4509; Email: Alexandra.Velasquez@ucsf.edu
      • Principal Investigator: Delphine Tuot, MD MAS
      • Sub-Investigator: Anjana Sharma, MD

Participation Criteria

Eligibility Criteria

• Ages Eligible for Study: Adult; Older Adult
• Accepts Healthy Volunteers: No

Description

Inclusion Criteria:

• ≥ 18 years of age
• English or Spanish-Speaking
• Have uncontrolled diabetes defined as a listed diagnosis of diabetes with a recorded A1C ≥ 8.0% in the past two years or have uncontrolled HTN defined as a listed diagnosis of HTN and last recorded documented SBP >140 mmHg
• At least 2 visits at a participating SFHN primary care site in the last 24 months

Exclusion Criteria:

• Higher than average digital literacy, defined as an Digital Healthcare Literacy Scale (DHLS) score greater than 10, as determined prior to the baseline study visit; these patients may not benefit from a digital coaching intervention.
• Presence of co-morbid conditions that would make it inappropriate to focus on telehealth chronic disease management. Conditions may include: end-stage or terminal condition with limited life expectancy and severe mental illness.
• Lack of any working phone number
• Visual or hearing impairment that precludes use of telehealth for chronic disease management
• Cognitive impairment defined by the inability to restate study goals during the consent process
• Pregnant

Study Plan

How is the study designed?

Design Details

• Primary Purpose: Health Services Research
• Allocation: Randomized
• Interventional Model: Factorial Assignment
• Masking: Single

Number of Arms

4

Arms and Interventions

Participant Group / Arm	Intervention / Treatment
Experimental: Patient Intervention + Clinic Intervention; Digital coach navigator + Clinic Intervention	Other: Digital Health Coaching (Patient-Level Intervention); The patient-level intervention combines the role of digital health navigator and chronic disease health coach to facilitate access to devices and broadband, offer digital skills training, and provide chronic disease health coaching focused on telehealth modalities.; Other: Practice Facilitation (Clinic-Level Intervention); The clinic-level intervention includes primary care clinic support through practice facilitation that empowers team members to address racial/ethnic disparities in telehealth use through consistent review of telehealth equity data and input from clinic-specific Patient Advisory Councils (PACs).
No Intervention: Patient Usual Care + Clinic Usual Care; Usual Care (Patient-Level) + Clinic Usual Care
Experimental: Patient Intervention + Clinic Usual Care; Digital coach navigator + Clinic Usual Care	Other: Digital Health Coaching (Patient-Level Intervention); The patient-level intervention combines the role of digital health navigator and chronic disease health coach to facilitate access to devices and broadband, offer digital skills training, and provide chronic disease health coaching focused on telehealth modalities.
Experimental: Patient Usual Care + Clinic Intervention; Usual Care (Patient-Level) + Clinic Intervention	Other: Practice Facilitation (Clinic-Level Intervention); The clinic-level intervention includes primary care clinic support through practice facilitation that empowers team members to address racial/ethnic disparities in telehealth use through consistent review of telehealth equity data and input from clinic-specific Patient Advisory Councils (PACs).

What is the study measuring?

Primary Outcome Measures

Outcome Measure	Measure Description	Time Frame
Change in Patient-Level Hemoglobin A1C	Change in A1C (%) will be determined by subtracting month 3, 6, and 12 A1C values from baseline A1C	Baseline, month 3, month 6, and month 12
Change in Patient Portal Use	The average number of patient portal log-ins per month will be obtained from the EHR	Baseline, month 3, month 6, and month 12

Secondary Outcome Measures

Outcome Measure	Measure Description	Time Frame
Medication Adherence	Medication adherence will be ascertained by the eight-item Morisky Medication Adherence Scale (MMAS-8). The scales score ranges from 0 to 8, with higher scores indicating greater medication adherence. High adherence: A score of 8 Medium adherence: A score of 6-8 Low adherence: A score of 6 and below.	Baseline, month 3, month 6, and month 12
Change in Clinic-Wide Blood Pressure (mmHg)	BP readings will be obtained from the EHR	Baseline, month 3, month 6, month 12, and month 24
Change in Clinic-Wide Hemoglobin A1C (average)	Hemoglobin A1C readings will be obtained from the EHR	Baseline, month 3, month 6, month 12, and month 24
Change in Patient-Level Systolic BP (mmHg)	Changes in mean SBP from baseline, using values from the electronic health record.	Baseline, month 3, month 6, month 12
Proportion of Primary care Clinic Visits Completed by Video	This proportion will be ascertained from the electronic health record.	Baseline, month 3, month 6, month 12 and month 24
Number of Patient Portal Communications Completed by Primary Care Team Members	The number of patient portal communications will be ascertained from the EHR	Baseline, month 3, month 6, month 12, and month 24
Clinic-level Visit Show Rates	Visit show rates for in-person, phone, or telehealth video as obtained from the EHR	Baseline, month 3, month 6, month 12, and month 24
Change in Patient-Level urine microalbuminuria (mg/g) among individuals with hypertension and/or diabetes	Urine microalbuminuria (mg/g) will be obtained from the electronic health record.	Baseline, month 3, month 6, month 12
Change in Clinic-Wide Urine Albumin-Creatinine Ratio UACR (mg/g) among individuals with hypertension and/or diabetes.	Microalbuminuria values among individuals with hypertension and/or diabetes will be obtained from the EHR.	Baseline, month 3, month 6, month 12, and month 24
Patient Activation Measure (PAM)	Patient activation will be measured by the Patient Activation Measure (PAM). The PAM-13 consists of 13 items on a 4-point Likert scale (1 = strongly disagree, 2 = disagree, 3 = agree, 4 = strongly agree, 0 = undecided). Item scores are summed to a raw score resulting in theoretical values between 13 and 52, with higher scores indicating higher patient activation.	Baseline, month 3, month 6, and month 12
Digital Literacy	Digital literacy will be ascertained with the Digital Healthcare Literacy Scale (DHLS). The DHLS is an 3-item scale that uses a 5-point Likert scale. Scores range from 0 to 12, with higher scores indicating higher digital health care literacy. Ongoing digital literacy will be ascertained with the Digital Equity Screening Tool Scale (DEST). The DEST is an 5-item scale that uses a 5-point Likert scale.	Baseline, month 3, month 6, and month 12

Collaborators and Investigators

• Sponsor: University of California, San Francisco
• Collaborators: National Institute on Minority Health and Health Disparities (NIMHD); San Francisco Tech Council
• Investigators: Principal Investigator: Delphine Tuot, MD MAS, University of California, San Francisco

Publications and helpful links

General Publications

• Sarkar U, Karter AJ, Liu JY, Adler NE, Nguyen R, Lopez A, Schillinger D. The literacy divide: health literacy and the use of an internet-based patient portal in an integrated health system-results from the diabetes study of northern California (DISTANCE). J Health Commun. 2010;15 Suppl 2(Suppl 2):183-96. doi: 10.1080/10810730.2010.499988.
• Patrick K, Norman GJ, Davila EP, Calfas KJ, Raab F, Gottschalk M, Sallis JF, Godbole S, Covin JR. Outcomes of a 12-month technology-based intervention to promote weight loss in adolescents at risk for type 2 diabetes. J Diabetes Sci Technol. 2013 May 1;7(3):759-70. doi: 10.1177/193229681300700322.
• Grossman LV, Masterson Creber RM, Benda NC, Wright D, Vawdrey DK, Ancker JS. Interventions to increase patient portal use in vulnerable populations: a systematic review. J Am Med Inform Assoc. 2019 Aug 1;26(8-9):855-870. doi: 10.1093/jamia/ocz023.
• Irizarry T, Shoemake J, Nilsen ML, Czaja S, Beach S, DeVito Dabbs A. Patient Portals as a Tool for Health Care Engagement: A Mixed-Method Study of Older Adults With Varying Levels of Health Literacy and Prior Patient Portal Use. J Med Internet Res. 2017 Mar 30;19(3):e99. doi: 10.2196/jmir.7099.
• Taha J, Sharit J, Czaja SJ. The impact of numeracy ability and technology skills on older adults' performance of health management tasks using a patient portal. J Appl Gerontol. 2014 Jun;33(4):416-36. doi: 10.1177/0733464812447283. Epub 2012 Jun 4.
• Sarkar U, Karter AJ, Liu JY, Adler NE, Nguyen R, Lopez A, Schillinger D. Social disparities in internet patient portal use in diabetes: evidence that the digital divide extends beyond access. J Am Med Inform Assoc. 2011 May 1;18(3):318-21. doi: 10.1136/jamia.2010.006015. Epub 2011 Jan 24.
• Wallace LS, Angier H, Huguet N, Gaudino JA, Krist A, Dearing M, Killerby M, Marino M, DeVoe JE. Patterns of Electronic Portal Use among Vulnerable Patients in a Nationwide Practice-based Research Network: From the OCHIN Practice-based Research Network (PBRN). J Am Board Fam Med. 2016 Sep-Oct;29(5):592-603. doi: 10.3122/jabfm.2016.05.160046.
• Lyles CR, Tieu L, Sarkar U, Kiyoi S, Sadasivaiah S, Hoskote M, Ratanawongsa N, Schillinger D. A Randomized Trial to Train Vulnerable Primary Care Patients to Use a Patient Portal. J Am Board Fam Med. 2019 Mar-Apr;32(2):248-258. doi: 10.3122/jabfm.2019.02.180263.
• Ramirez V, Johnson E, Gonzalez C, Ramirez V, Rubino B, Rossetti G. Assessing the Use of Mobile Health Technology by Patients: An Observational Study in Primary Care Clinics. JMIR Mhealth Uhealth. 2016 Apr 19;4(2):e41. doi: 10.2196/mhealth.4928.
• Schickedanz A, Huang D, Lopez A, Cheung E, Lyles CR, Bodenheimer T, Sarkar U. Access, interest, and attitudes toward electronic communication for health care among patients in the medical safety net. J Gen Intern Med. 2013 Jul;28(7):914-20. doi: 10.1007/s11606-012-2329-5. Epub 2013 Feb 20.
• Nishii A, Campos-Castillo C, Anthony D. Disparities in patient portal access by US adults before and during the COVID-19 pandemic. JAMIA Open. 2022 Dec 16;5(4):ooac104. doi: 10.1093/jamiaopen/ooac104. eCollection 2022 Dec.
• Barbosa W, Zhou K, Waddell E, Myers T, Dorsey ER. Improving Access to Care: Telemedicine Across Medical Domains. Annu Rev Public Health. 2021 Apr 1;42:463-481. doi: 10.1146/annurev-publhealth-090519-093711.
• Meng YY, Diamant A, Jones J, Lin W, Chen X, Wu SH, Pourat N, Roby D, Kominski GF. Racial and Ethnic Disparities in Diabetes Care and Impact of Vendor-Based Disease Management Programs. Diabetes Care. 2016 May;39(5):743-9. doi: 10.2337/dc15-1323. Epub 2016 Mar 10.
• Wisniewski H, Gorrindo T, Rauseo-Ricupero N, Hilty D, Torous J. The Role of Digital Navigators in Promoting Clinical Care and Technology Integration into Practice. Digit Biomark. 2020 Nov 26;4(Suppl 1):119-135. doi: 10.1159/000510144. eCollection 2020 Winter.
• Samuels-Kalow M, Jaffe T, Zachrison K. Digital disparities: designing telemedicine systems with a health equity aim. Emerg Med J. 2021 Jun;38(6):474-476. doi: 10.1136/emermed-2020-210896. Epub 2021 Mar 4.
• Uscher-Pines L, Sousa J, Jones M, Whaley C, Perrone C, McCullough C, Ober AJ. Telehealth Use Among Safety-Net Organizations in California During the COVID-19 Pandemic. JAMA. 2021 Mar 16;325(11):1106-1107. doi: 10.1001/jama.2021.0282.
• Jain V, Al Rifai M, Lee MT, Kalra A, Petersen LA, Vaughan EM, Wong ND, Ballantyne CM, Virani SS. Racial and Geographic Disparities in Internet Use in the U.S. Among Patients With Hypertension or Diabetes: Implications for Telehealth in the Era of COVID-19. Diabetes Care. 2021 Jan;44(1):e15-e17. doi: 10.2337/dc20-2016. Epub 2020 Nov 2. No abstract available.
• Alkureishi MA, Choo ZY, Rahman A, Ho K, Benning-Shorb J, Lenti G, Velazquez Sanchez I, Zhu M, Shah SD, Lee WW. Digitally Disconnected: Qualitative Study of Patient Perspectives on the Digital Divide and Potential Solutions. JMIR Hum Factors. 2021 Dec 15;8(4):e33364. doi: 10.2196/33364.
• Gaskin DJ, Hadley J. Population characteristics of markets of safety-net and non-safety-net hospitals. J Urban Health. 1999 Sep;76(3):351-70. doi: 10.1007/BF02345673.
• Khoong EC, Butler BA, Mesina O, Su G, DeFries TB, Nijagal M, Lyles CR. Patient interest in and barriers to telemedicine video visits in a multilingual urban safety-net system. J Am Med Inform Assoc. 2021 Feb 15;28(2):349-353. doi: 10.1093/jamia/ocaa234.
• Tieu L, Schillinger D, Sarkar U, Hoskote M, Hahn KJ, Ratanawongsa N, Ralston JD, Lyles CR. Online patient websites for electronic health record access among vulnerable populations: portals to nowhere? J Am Med Inform Assoc. 2017 Apr 1;24(e1):e47-e54. doi: 10.1093/jamia/ocw098.
• Tieu L, Sarkar U, Schillinger D, Ralston JD, Ratanawongsa N, Pasick R, Lyles CR. Barriers and Facilitators to Online Portal Use Among Patients and Caregivers in a Safety Net Health Care System: A Qualitative Study. J Med Internet Res. 2015 Dec 3;17(12):e275. doi: 10.2196/jmir.4847.
• Omomukuyo A, Ramirez A, Davis A, Velasquez A, Najmabadi AL, Kong M, Willard-Grace R, Brown W 3rd, Broderick A, Suomala K, McCulloch CE, Franco N, Sarkar U, Lyles C, Tran AS, Sharma AE, Tuot DS. Achieving Chronic Care Equity by Leveraging the Telehealth Ecosystem (ACCTIVATE): A Multilevel Randomized Controlled Trial Protocol. Med Res Arch. 2024 Nov;12(11):6087. doi: 10.18103/mra.v12i11.6087.

Study record dates

Study Major Dates

• Study Start (Actual): November 4, 2024
• Primary Completion (Estimated): September 1, 2028
• Study Completion (Estimated): September 1, 2028

Study Registration Dates

• First Submitted: September 13, 2024
• First Submitted That Met QC Criteria: September 17, 2024
• First Posted (Actual): September 19, 2024

Study Record Updates

• Last Update Posted (Actual): January 6, 2026
• Last Update Submitted That Met QC Criteria: January 2, 2026
• Last Verified: January 1, 2026

More Information

Terms related to this study

• Keywords: Telemedicine; Cardiovascular Disease; Telehealth; Library; Blood Pressure; Chronic Kidney Disease (CKD); Socioeconomic Status; Hemoglobin A1C; Adverse Event; Systolic Blood Pressure (SBP); Randomized Control Trial (RCT); Good Clinical Practice; University of California, San Francisco (UCSF); Health Care Systems; Federally Qualified Health Center (FQHC); Informed Consent Form (ICF); Community Advisory Board (CAB); Clinic-level Intervention; Clinical Research Coordinator (CRC); Digital Coach Navigator; Health Insurance Portability and Accountability Act of 1996; Institutional Review Board (IRB); National Institutes of Health (NIH); National Institute of Minority Health and Health Disparities (NIHMD); Patient Advisory Council (PAC); Patient-level Intervention; Principal Investigator (PI); San Francisco Health Network (SFHN); Zuckerberg San Francisco General Hospital (ZSFG)
• Additional Relevant MeSH Terms: Urogenital Diseases; Endocrine System Diseases; Pathologic Processes; Male Urogenital Diseases; Kidney Diseases; Urologic Diseases; Female Urogenital Diseases; Female Urogenital Diseases and Pregnancy Complications; Chronic Disease; Disease Attributes; Metabolic Diseases; Glucose Metabolism Disorders; Renal Insufficiency; Pathological Conditions, Signs and Symptoms; Nutritional and Metabolic Diseases; Cardiovascular Diseases; Diabetes Mellitus; Renal Insufficiency, Chronic
• Other Study ID Numbers: 23-40207; R01MD019042 (U.S. NIH Grant/Contract)

Plan for Individual participant data (IPD)

• Plan to Share Individual Participant Data (IPD)?: YES
• IPD Plan Description: The proposed research will include data from approximately 690 participants recruited from primary care clinics in the San Francisco Health Network with uncontrolled diabetes (defined as glycosylated A1c greater than or equal to 8.0%). The final dataset will include self-reported demographic, telehealth engagement, and chronic disease self-management data from self-report, and additional demographic, clinical outcome, and telehealth utilization data from the electronic medical record. The data will be made available in a de-identified format in a .csv or .dta file. In addition to the IPD data set, the ACCTIVATE study team will share the data set, data dictionary, statistical analysis plan, analytic code, and final protocol with amendments
• IPD Sharing Time Frame: Data will be made available as soon as possible or at the time of associated publication. The duration of preservation and sharing of the data will be a minimum of 5 years after the end of the funding period.
• IPD Sharing Access Criteria: The investigators plan to provide access to the data via Dryad. Anyone can download a dataset via Dryad in the form of a zip file. Dryad will maintain storage and access of the data for as long as it maintains scientific utility.
• IPD Sharing Supporting Information Type: STUDY_PROTOCOL; SAP; ANALYTIC_CODE

Drug and device information, study documents

• Studies a U.S. FDA-regulated drug product: No
• Studies a U.S. FDA-regulated device product: No