Center for Dissemination and Implementation Science at Stanford (C-DIAS)
Funded by the National Institute on Drug Abuse (P50DA054072), C-DIAS’ goal is to advance the science of implementation and improve equitable access to the best addiction treatments available for the people who need them the most. C-DIAS innovatively responds to enormous gaps in addiction treatment services and research by:
- Building expert capacity through a range of resources, training and mentoring;
- Improving and accelerating the quality of the dissemination and implementation (D&I) science using a platform of 4 innovative research projects; and
- Impacting public health by increasing access to the proven treatments for addiction and sustaining these treatments through policy and financing mechanisms.
Dr. Mark McGovern directs the Center for Dissemination and Implementation. His work focuses on implementation science, with emphasis on integrated behavioral health services for persons with co-occurring substance use and psychiatric disorders in both primary care and specialty settings. He actively collaborates with health systems, including Stanford Health Care and Intermountain Healthcare, on developing implementable and sustainable models of integrated behavioral health in primary care practice. His research interests also include scaling up access to FDA-approved medications in specialty care and in general medical practice settings.
Hélène Chokron Garneau
Dr. Hélène Chokron Garneau joined the Center for Dissemination and Implementation in 2019 as a Senior Research Scientist. Dr. Chokron Garneau has extensive research experience in public health and substance use, with an emphasis on co-occurring psychiatric and substance use disorders. Her current efforts at CDI focus on advancing implementation science by disentangling mechanisms through which implementation strategies operate. She is particularly interested in applying this knowledge to eliminate disparities in health services for mental health and addiction treatment.
Dr. Chokron Garneau obtained both her PhD and MPH in Public Health from UCLA where she concurrently worked to assist in the development, implementation, and evaluation of behavioral interventions for substance users with comorbid psychiatric diagnoses.
C. Hendricks Brown
Shubhi Sharma, MPH
Stanford University School of Medicine
Shubhi Sharma, MPH is the Project Coordinator for the Center for Dissemination and Implementation Science at Stanford (C-DIAS). Her role for C-DIAS primarily focuses on providing critical research and data analysis support for the Financing and Policy Research Core and Research Project 2. She pursued her MPH from Boston University School of Public Health (BUSPH), specializing in Global Health Program Design, Monitoring and Evaluation. Prior to joining CDI, she led the patient recruitment and retention for NIH's Researching COVID to Enhance Recovery (RECOVER) initiative at Boston Medical Center. Shubhi is curious to learn more ways to mitigate accessibility to basic healthcare needs through the decolonization of public health.
Naomi Fedna-Thompson, MDiv
Naomi Fedna-Thompson, MDiv, is the Communications Specialist for the Center for Dissemination and Implementation. She obtained her Bachelor of Arts in English and Bachelor of Science in Public Health from the University of Massachusetts Amherst and her Master of Divinity from Harvard Divinity School. She has a strong interest in using creative writing, storytelling and digital media to amplify movements that are dedicated to improving the lives of disenfranchised communities.
Mia Navarro, MS
Stanford University School of Medicine
Mia Navarro, MS, joined the Center for Dissemination and Implementation in 2023 as a Project Coordinator for the Center for Dissemination and Implementation at Stanford (C-DIAS). Mia's research at CDI aims to standardize implementation science methodology and to employ accessible addiction treatment programs throughout the US. Mia received her MS in Epidemiology and Clinical Research from Stanford University and her BS in Computational and Systems Biology from UCLA.
Lia Chin-Purcell, MS
Stanford University School of Medicine
Lia Chin-Purcell, MS is a research data analyst at CDI sporting C-DIAS and the RASC. She holds a Master's degree from the University of California, Berkeley, where she studied Information Management and Systems with a focus on data science. At CDI, she applies her expertise in machine learning and data analysis to help researchers and clinicians effectively implement evidence-based practices and interventions that improve healthcare outcomes.
C-DIAS has 3 overarching objectives:
- To PREPARE the addiction treatment services research community for advanced D&I research by developing human capital, building expert capacity and serving as a national resource.
- To IMPLEMENT increasingly standardized measures and methods, examine the causal mechanisms of implementation strategies, harmonize data across studies, and use modeling techniques to advance D&I science in addiction treatment services research.
- To SUSTAIN and scale-up equitable evidence-based addiction treatment services in public and private health systems by providing decision-makers with information on how to effectively and efficiently implement evidence-based treatments.
To achieve these aims, C-DIAS is organized in 2 cores:
The Administrative Core oversees and nurtures a physical and interpersonal environment to build technical capacity, enhance scientific innovation, and impact public health. It will host an efficient centralized home for C-DIAS operations, provide administrative and scientific leadership, and produce and maintain user-friendly accessible communication platforms that creatively disseminate knowledge via interactive online tools and resources.
The Research Core supports 3 innovative research projects and is organized into 3 sections:
The Methods & Measures Section, led by Lisa Saldana, focuses on developing, extending, and refining pragmatic standardized methods and measures of context, implementation strategies, and their underlying mechanisms.
The Design & Modeling Section, led by C. Hendricks Brown, is developing agent-based modeling and cost modeling to develop empirically-based tools for designs, power estimations, and selection of implementation strategies.
The Policy & Financing Section, led by Keith Humphreys, focuses on identifying policy and financing strategies to support sustainment of proven interventions for addiction in public and private health systems, and developing practical sustainment strategy toolkits and briefs that can be used as templates for state or systems leaders to influence policymakers and payers.
A set of 3 coordinated Research Projects serve as study vehicles to improve D&I science in addiction by reducing variation and increasing standardization in measures and methods, translating and harmonizing data across studies, and using agent-based and economic modeling to scientifically respond rather than merely react to substance-related epidemics and health care disparities.
C-DIAS Research Project 1 (PI: C. Hendricks Brown) engages a constellation of 3 county systems to model interventions and implementation strategies to reduce overdose death from opioids and increasingly stimulants.
C-DIAS Research Project 2 (PI: Sara Becker) evaluates the implementation of contingency management for a rising stimulant problem in specialty public addiction treatment programs across a state system of care.
C-DIAS Research Project 3 (PI: Joe Glass), conducted within a private healthcare system, aims to scale up digital treatments for complex patients with substance use disorders.
C-DIAS Bonus Project 4, Stagewise Implementation-To-Target: Medications for Addiction Treatment (SITT-MAT; 1R01DA052975-01A1), uses an innovative stagewise implementation-to-target approach, within an adaptive implementation strategy trial design, to expand access to medications for opioid use disorder in addiction treatment programs and primary care clinics. The relative impact of 5 possible paths of implementation strategies on RE-AIM target outcomes: reach, effectiveness, adoption, and implementation quality will be evaluated.