Community Health Workers Systematically Assessing and Addressing Social Determinants of Health to Improve Outcomes in Community Health Centers (CHW-SYSTIM)

Page last updated August 6, 2026

ClinicalTrials.gov#: NCT06926855
Study Design: 
Intervention Trial
PCORnet Infrastructure: Common Data Model (CDM), Single IRB, Patient partners or engagement
Principal Investigator: Rachel Gold and Erika Cottrell
Institution: OCHIN
PCORnet® Network Partner: ADVANCE
Funder: Federal (NIH/National Heart, Lung, and Blood Institute (NHLBI))
Funding Date: 2023
Study Duration: 2024 – 2026
Therapeutic Area: Healthcare Delivery, Cardiovascular, Health Disparities, Metabolic Disorders
Status: Completed

Research Question(s):

Community health workers (CHWs) often provide patient education and care coordination in community health center (CHC) settings. CHWs have unique skill sets to support patient education, connect patients with resources, and understand patient needs in the context of their culture and community. Both CHCs and CHWs are recognized as valuable research partners because of the trust and knowledge they hold with the patient populations they serve. This study asked if CHWs can help improve health for people with diabetes or high blood pressure by asking about and helping to address their social needs. CHWs asked people about needs related to food, housing, transportation, or medications and then helped to connect them with available services based on each patient’s given needs. CHWs then followed-up with each patient to see if they connected with any resources.

Detection of Elder Abuse Through Emergency Care Technicians – Revised for Primary Care

Page last updated August 6, 2026

ClinicalTrials.gov#: NCT05958654
Study Design: 
Intervention Trial
PCORnet Infrastructure: Common Data Model (CDM), Single IRB, Patient partners or engagement
Principal Investigator: Brad Cannell
Institution: University of Texas Health Science Center at Houston
Funder: Federal (NIH/NIA)
Funding Date: 2022
Study Duration: 2022 – 2028
Participating PCORnet® Clinical Research Networks: GPC, OneFlorida+, PaTH, REACHnet
Therapeutic Area: Healthcare Delivery, Data Science, Mental and Behavioral Health, Neurology
Status: Active, not recruiting

Research Question(s):

Can a structured screening and reporting program — used by home-based primary care clinicians during routine visits — help identify older adults who may be experiencing abuse, neglect, or financial exploitation, particularly those living with dementia, and connect them with needed services and supports?

Primary Publication(s):

Cannell B, Sevey N, Livingston MD, Burnett J, Lees Haggerty K, Pickering C. Detection of Elder Abuse Through Emergency Care Technicians Screening Tool Revision for Home-Based Primary Care (DETECT-RPC): a cluster randomised controlled trial study protocol. BMJ Open. 2025;15(1):e089028. doi:10.1136/bmjopen-2024-089028

Lees Haggerty K, Campetti R, Ojelabi O, et al. Adaptation of DETECT for use in home-based primary care: Clinician perspectives. J Am Geriatr Soc. 2026;74(5):1421-1428. doi:10.1111/jgs.70296

Oregon Medicaid Policy, Social Services, and Health (RESOLVE)

Page last updated June 06, 2026

Study Design: Other
PCORnet Infrastructure: Common Data Model (CDM), Single IRB, Patient partners or engagement
Principal Investigator: Caroline Fichtenberg and Danielle Hessler Jones
Institution: University of California, San Francisco
PCORnet® Network Partner: REACHnet
Funder: Federal (NIH)
Funding Date: 2024
Study Duration: 2024 – 2029
Participating PCORnet® Clinical Research Networks: ADVANCE, REACHnet
Therapeutic Area: Healthcare Delivery, Cardiovascular, Endocrinology, Healthcare Delivery, Health Disparities, Mental and Behavioral Health, Other
Status: Active, not recruiting

Research Question(s):

Oregon implemented new Medicaid policies intended to increase referrals to connect patients endorsing specific social risks with local non-medical services.

  1. How do Oregon's new Medicaid policies impact rates of screening, referrals, and receipt of services for
    social needs?
  2. Do these policies decrease the difference in rates of screening, referrals, and receipt of services between various demographic groups?
  3. How do screening, referrals, and receipt of services for social needs impact chronic disease outcome and
    healthcare utilization? Is the impact different for various demographic groups?

Behavioral Economic and Staffing Strategies to Increase Adoption of the ABCDEF Bundle in the ICU (BEST-ICU)

Page last updated May 11, 2026

ClinicalTrials.gov#: NCT06184945
Study Design: Intervention Trial
PCORnet Infrastructure: Common Data Model (CDM), Single IRB, Patient partners or engagement
Principal Investigator: Michele Balas
Institution: University of Nebraska Medical Center
PCORnet® Network Partner: GPC
Funder: Federal (NIH NHLBI & NINR)
Funding Date: 2024
Study Duration: 2024 - 2028
Participating PCORnet® Clinical Research Networks: GPC, PaTH
Therapeutic Area: Healthcare Delivery
Status: Active, not recruiting

Research Question(s): What is the best way to encourage ICU clinicians to consistently and completely implement the ABCDEF Bundle in their care of mechanically ventilated patients?

Primary Publication(s):

Conte M, Schlaeger J, Marsolo K, et al. Computable phenotypes for research using real-world data: experiences from the NIH Pragmatic Trials Collaboratory. J Am Med Inform Assoc. In review.

Vasilevskis, Eduard E., Jungyoon Kim, Christopher Wichman, Ronnie Horner, James R. Campbell, Carol Reynolds Geary, Justin Birge et al. "Behavioral Economic and Staffing Strategies To Increase Adoption of the ABCDEF Bundle in the Intensive Care Unit (BEST ICU): study protocol for a multi-site stepped-wedge cluster randomized controlled trial in the USA." Trials (2025). doi.org/10.1186/s13063-025-09331-6

REducing future fractureS and improving ouTcOmes of fRagility fracture (RESTORE)

Page last updated August 22, 2025

ClinicalTrials.gov#NCT06455085
Study Design: Intervention Trial
PCORnet Infrastructure: Common Data Model (CDM), Single IRB, Patient partners or engagement
Principal Investigator: Kenneth Saag
Institution: University of Alabama at Birmingham
PCORnet® Network Partner: OneFlorida+
Funder: Patient-Centered Outcomes Research Institute (PCORI); (Project webpage)
Funding Date: 2023
Study Duration: 2024 - 2029
Participating PCORnet® Clinical Research Networks: GPC, INSIGHT, OneFlorida+, PaTH, REACHnet, STAR
Therapeutic Area: Healthcare Delivery
Status: Recruiting

Research Question(s): For adults 50 and older who have had a recent fracture, can a Fracture Liaison Service that includes a patient navigator, access to a bone health provider, and increased use of bone-strengthen medications help prevent future fractures and improve quality of life?

Evaluating the Comparative Effectiveness of Telemedicine in Primary Care: Learning from the COVID-19 Pandemic

Page last updated February 4, 2026

ClinicalTrials.gov#: NCT04684836
Study Design: Other, Telephone survey of primary care practice leadership, qualitative interview study with patients and primary care providers, observational data analysis
PCORnet Infrastructure: Common Data Model (CDM), Single IRB, Patient partners or engagement
Principal Investigator:
Jessica Ancker and Rainu Kaushal
Institution: Weill Cornell Medicine
PCORnet® Network Partner: INSIGHT
Funder: Patient-Centered Outcomes Research Institute (PCORI); (project webpage)
Funding Date: 2020
Study Duration: 2020 – 2023
Participating PCORnet® Clinical Research Networks: INSIGHT, OneFlorida+, STAR
Therapeutic Area: Healthcare Delivery
Condition: Asthma; Chronic Obstructive Pulmonary Disease (COPD); Congestive Heart Failure; Diabetes; Hypertension
Age Range: 19 Years and older (Adult, Older Adult)
Status: Completed

Research Question(s):

  1. What are the features of primary care telemedicine programs that have been newly implemented or expanded in response to the COVID-19 pandemic.
  2. How do different populations experience these programs?

Primary Publications(s):

Lin, J.J., Horowitz, C.R., Ancker, J.S. An Urgent Need for Guidelines for Telemedicine Use. J Gen Intern Med 38, 1061–1062 (2023). doi:10.1007/s11606-022-07905-7

Yu J, Andreadis K, Schpero WL, et al. Patient experiences with and preferences for telemedicine relative to in-person care during the COVID-19 pandemic. Telemedicine and e-Health. Published online 2023. doi:10.1089/tmj.2022.0311

Muellers KA, Andreadis K, Ancker JS, et al. Provider and patient experiences of delays in primary care during the early COVID-19 pandemic. Journal for Healthcare Quality. 2023;45(3):169-176. doi:10.1097/jhq.0000000000000380