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Algorithm-Enabled Engagement of Patients with Advanced Cancer (A-EPAC) to improve goals of care communication among Veterans with Advanced Stages of Cancer

NIH

open
OpenLast verified: 2026-07-13

About This Grant

Background: Early goals of care (GoC) communication regarding prognosis, values, and care preferences improves patient mood and reduces the likelihood of intensive, unwanted care at the end-of-life for Veterans with cancer. In 2017, the VA National Center for Ethics in Health Care (NCEHC) launched the Life-Sustaining Treatment Decisions Initiative (LSTDI), a national program to promote GoC communication between clinicians and their patients. Despite LSTDI, 60% of Veterans with cancer still have no GoC communication or an LST documented note before death. Major barriers include reliance on oncology clinicians to identify appropriate Veterans and initiate these conversations in clinic. In response, we developed the Engagement of Patients with Advanced Cancer (EPAC) intervention – a 6-month telephone-based intervention in which trained lay health workers (LHWs) educate and empower Veterans with cancer to engage in GoC with their oncology clinical teams. To facilitate scale, we propose Algorithm-Enabled EPAC (A-EPAC), which uses the VA Care Assessment Needs (CAN) score to automatically identify patients with cancer who could benefit from EPAC. Significance: Connecting Veterans to the soonest/best care and promoting a culture of safety, learning, and knowledge translation are central to VA priorities. This proposals’ objective for early and equitable GoC communication is strongly aligned with VA’s strategic plan (Goal 2.1) and VHA Directive 1004.03, Advance Care Planning. The research addresses HSR priority topic areas of health care system organization and delivery through access, virtual care, and rural health (remote delivery); behavioral, social, and cultural determinants of health (tailored interventions to address equity); and, strategic methodology areas, including data science (algorithm-based eligibility) and implementation science (type 1 hybrid trial design). Innovation and Impact: Integrating high-tech automated algorithms with high-touch LHW interventions can overcome persistent barriers to GoC communication. Innovative methodologic aspects of this proposal, include: (1) recruitment of oncology sites, including the National Teleoncology Program (NTO), that serve racial and ethnic minorities, women, and Veterans in rural settings; (2) longitudinal assessment of patient mood and care preferences; and (3) decentralized clinical trial with remote recruitment and intervention activities. Specific Aims: 1) Determine whether A-EPAC improves LST documentation within 12 weeks more than usual care alone; 2) Determine whether A-EPAC reduces patient anxiety and depression more than usual care from baseline to 12 weeks; 3) Identify Veteran, clinician, and organizational factors associated with feasibility, adoption, acceptability, and A-EPAC fidelity using the Consolidated Framework for Implementation Research. Methodology: Our intent-to-treat randomized trial is conducted in collaboration with the NTO and the National VA Oncology Program (NOP). We will randomize 200 Veterans with cancer receiving care across 7 VA facilities that serve primarily Black, Latino or Hispanic, and/or rural-dwelling Veterans to either the A-EPAC intervention (algorithm-based identification and referral to EPAC for 6-months) or usual cancer care alone (cancer care provided by oncology teams at the local site). Participants will be followed for 12-months post-enrollment. Our primary outcome is LST documentation within 12 weeks post-enrollment. Secondary outcomes are patient anxiety and depression at 12 weeks measured by PROMIS® short forms. Exploratory outcomes include intensive end-of-life care, advance directive documentation, and acute care use. Using a quant-qual framework, we will conduct validated surveys with 60 Veterans with cancer and Veteran and clinician interviews at 6 months to identify factors associated with feasibility, adoption, acceptability, and A-EPAC fidelity. Next Steps/Implementation: Our collaboration with operational partners including the NTO, NOP, NCEHC, the Veterans Experience Center, and the VA Proactive Patient Centered Care Program founded and directed by MPI Patel, will support widespread dissemination across VA oncology settings.

Grant Summary

Algorithm-Enabled Engagement of Patients with Advanced Cancer (A-EPAC) to improve goals of care communication among Veterans with Advanced Stages of Cancer is a NIH grant providing funding that varies by award for university, nonprofit, healthcare org. Applications are due 2031-06-30 (open). Check eligibility and apply with FindGrants.

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Focus Areas

health research

Eligibility

universitynonprofithealthcare org

How to Apply

Funding Range

Up to $0K

Deadline

2031-06-30

Complexity
Medium
  1. 1Confirm your organization is eligible for Algorithm-Enabled Engagement of Patients with Advanced Cancer (A-EPAC) to improve goals of care communication among Veterans with Advanced Stages of Cancer from NIH, checking organization type, location, and any population or project requirements.
  2. 2Gather the required documents and information, including your organization details, project plan, and budget figures.
  3. 3Draft your application narrative and budget addressing the funder's priorities and review criteria. FindGrants can draft each section for you to review and edit.
  4. 4Review every section against the requirements checklist, then export a submission-ready application pack and submit it to NIH before the deadline.
This record is a past award, contract, or funder profile — useful for research, but not an open grant application. Check the original source for current opportunities from this funder.

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Algorithm-Enabled Engagement of Patients with Advanced Cancer (A-EPAC) to improve goals of care communication among Veterans with Advanced Stages of Cancer: Frequently Asked Questions

Who is eligible for the Algorithm-Enabled Engagement of Patients with Advanced Cancer (A-EPAC) to improve goals of care communication among Veterans with Advanced Stages of Cancer?

Algorithm-Enabled Engagement of Patients with Advanced Cancer (A-EPAC) to improve goals of care communication among Veterans with Advanced Stages of Cancer is offered by NIH and is generally open to university, nonprofit, healthcare org. It is open to organizations nationwide unless the funder specifies otherwise. Review the specific eligibility terms before applying, since funders set their own requirements around organization type, location, and the population or project being served.

How much funding does the Algorithm-Enabled Engagement of Patients with Advanced Cancer (A-EPAC) to improve goals of care communication among Veterans with Advanced Stages of Cancer provide?

Algorithm-Enabled Engagement of Patients with Advanced Cancer (A-EPAC) to improve goals of care communication among Veterans with Advanced Stages of Cancer provides an amount that varies by award per award from NIH. Actual award sizes depend on the scope of your project, available program funds, and the number of applicants, so build a budget that reflects realistic, allowable costs rather than the maximum figure.

When is the Algorithm-Enabled Engagement of Patients with Advanced Cancer (A-EPAC) to improve goals of care communication among Veterans with Advanced Stages of Cancer deadline?

Applications for Algorithm-Enabled Engagement of Patients with Advanced Cancer (A-EPAC) to improve goals of care communication among Veterans with Advanced Stages of Cancer are due 2031-06-30 (open). Because deadlines can change, verify the date with the funder, NIH, and give yourself enough time to prepare a complete, competitive application before the close date.

How do you apply for the Algorithm-Enabled Engagement of Patients with Advanced Cancer (A-EPAC) to improve goals of care communication among Veterans with Advanced Stages of Cancer?

To apply for Algorithm-Enabled Engagement of Patients with Advanced Cancer (A-EPAC) to improve goals of care communication among Veterans with Advanced Stages of Cancer, confirm your eligibility, gather the required documents, and prepare a narrative and budget that address the funder's priorities. FindGrants guides you step by step and can draft each section, then exports a submission-ready application pack for this grant from NIH.