# A multi-stakeholder health policy study using implementation science to advance access to cancer care and clinical trials for medically vulnerable populations: A focus on our Catchment Community

> **NIH NIH P30** · BECKMAN RESEARCH INSTITUTE/CITY OF HOPE · 2023 · $125,000

## Abstract

PROJECT SUMMARY
This application is being re-submitted as a PA-20-272 investigator-initiated request responsive to the Notice of
Special Interest (NOSI) identified as NOT-CA-23-044, and in response to our P30-CA033572-40 strategic
priority to reduce cancer burden and disparities by increasing underrepresented and minority population
access to cancer care and clinical trials. Increasing minority access to specialized cancer care and clinical
interventional treatment trials are top priorities for medical research organizations including NIH, NCI, and our
City of Hope Cancer Center. The strategic plan of the parent P30 grant, and in particular aim 3 of our
Community Outreach and Engagement (COE), prioritizes increasing minority enrollment and addressing
cancer disparities. To advance our P30 strategic priorities and our COE aim, we propose a health policy study
built on multi-stakeholder engagement to increase access to specialty cancer care and clinical trials for
medically vulnerable populations, especially targeting our Catchment Communities. The unacceptably low
representation of minorities in cancer control policy studies and clinical trials continue to hamper public benefit
of medical advancement and legislation. To address this gap, we propose evaluating the implementation of
The California Cancer Care Equity Act (CCEA-SB987) that took effect in January 2023, which expands access
to specialized cancer care and clinical trials. By ensuring community responsiveness in CCEA-SB987
implementation, our long-term goal is to rapidly increase minority access to cancer care and clinical trials at
NCI Cancer Centers. Our innovative approach will enable patients and families, health care providers, health
systems, payors, and community members to better understand guidelines and eligibility, and act upon the
information. Guided by dissemination and implementation conceptual frameworks, we aim to: (1) Evaluate
patient perspectives of notification strategies payors use to inform patients about CCEA-SB987 guidelines and
eligibility, using focus groups with patient advisors. We will explore patient perspectives on payor notification
strategies (type and delivery modality), payor notification quality (content, clarity, and cultural and linguistic
responsiveness), and eligibility guidelines; and (2) Evaluate organization stakeholder perspectives on CCEA-
SB987 implementation, using semi-structured interviews with organization/clinic leaders and providers. We will
conduct in-depth qualitative interviews to learn about perspectives on engagement in policy implementation,
barriers and facilitators to implementation, and eligibility guidelines. We will use the findings from this policy
discovery science research to co-create (advocate, clinician, and researcher) communication strategies for
optimal provider and patient activation to increase access to the highest quality cancer care and clinical
treatment studies afforded by CCEA-SB987. This outcome has direct rel...

## Key facts

- **NIH application ID:** 10885732
- **Project number:** 3P30CA033572-40S3
- **Recipient organization:** BECKMAN RESEARCH INSTITUTE/CITY OF HOPE
- **Principal Investigator:** JOHN D. CARPTEN
- **Activity code:** P30 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2023
- **Award amount:** $125,000
- **Award type:** 3
- **Project period:** 1997-08-01 → 2027-11-30

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/10885732

## Citation

> US National Institutes of Health, RePORTER application 10885732, A multi-stakeholder health policy study using implementation science to advance access to cancer care and clinical trials for medically vulnerable populations: A focus on our Catchment Community (3P30CA033572-40S3). Retrieved via AI Analytics 2026-05-26 from https://api.ai-analytics.org/grant/nih/10885732. Licensed CC0.

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