Opportunity Information: Apply for PA 24 261
The grant opportunity "Examining the Impact of Artificial Intelligence (AI) on Healthcare Safety (R18)" (Funding Opportunity Number PA-24-261) is a discretionary grant from the Agency for Health Care Research and Quality (AHRQ) under CFDA 93.226. It is designed to fund research that strengthens healthcare safety by taking a hard look at how emerging, high-impact ("breakthrough") AI applications influence patient safety in real-world care and what it actually takes to implement and use these AI systems safely. The core idea is to move beyond broad claims that AI will improve care and instead generate evidence about when AI helps, when it introduces new safety risks, and how organizations can reduce patient harm and user burden when deploying AI in clinical settings.
The notice emphasizes two central research aims. First, applicants are expected to examine whether and how specific AI uses affect patient safety. That can include identifying safety benefits (for example, earlier detection of deterioration, fewer medication errors, improved diagnostic support) as well as safety hazards (such as biased predictions, automation complacency, incorrect recommendations, overreliance on imperfect models, workflow disruptions, or failure modes that only appear after deployment). Second, the opportunity calls for studies that clarify how AI can be implemented and used safely, which points to practical issues like governance, monitoring, human factors, training, workflow integration, transparency, accountability, and strategies to detect and mitigate harm over time. The framing recognizes that AI may improve safety, effectiveness, efficiency, access, and affordability, but it also stresses that these potential gains must be balanced against the risk of patient harm and the added workload or cognitive burden AI can create for clinicians, staff, and patients.
Eligibility is broad and includes many common applicant types across government, academia, and the private and nonprofit sectors. Eligible applicants listed include state, county, city or township governments; special district governments; independent school districts; public and state-controlled institutions of higher education; private institutions of higher education; Native American tribal governments (federally recognized); Native American tribal organizations (other than federally recognized tribal governments); public housing authorities/Indian housing authorities; nonprofits with or without 501(c)(3) status (other than institutions of higher education); for-profit organizations other than small businesses; and small businesses. The announcement also highlights additional eligible categories such as Alaska Native and Native Hawaiian Serving Institutions, Asian American Native American Pacific Islander Serving Institutions (AANAPISI), Hispanic-serving Institutions, Historically Black Colleges and Universities (HBCUs), Tribally Controlled Colleges and Universities (TCCUs), faith-based or community-based organizations, regional organizations, U.S. territories or possessions, and eligible agencies of the federal government. At the same time, it clearly excludes non-domestic (non-U.S.) entities (foreign organizations) from applying, and it also states that non-domestic components of U.S. organizations are not eligible to apply.
Key administrative details from the source information include the opportunity title, number (PA-24-261), agency (AHRQ), funding instrument (grant), activity category (health), and an original closing date of 2027-05-25, with a creation date of 2024-07-16. The award ceiling and expected number of awards are not specified in the provided data, which typically means applicants should consult the full notice for budget limits, project period expectations, and any submission cycles or review dates that may apply before the listed closing date.
Overall, this NOFO is aimed at building practical, safety-focused evidence about AI in healthcare: what it changes about patient risk, where it can fail, who might be disproportionately affected, and what safeguards, implementation practices, and ongoing monitoring are needed so AI can be integrated into care in a way that improves outcomes without creating new, avoidable harms or burdens.Apply for PA 24 261
- The Agency for Health Care Research and Quality in the health sector is offering a public funding opportunity titled "Examining the Impact of Artificial Intelligence (AI) on Healthcare Safety (R18)" and is now available to receive applicants.
- Interested and eligible applicants and submit their applications by referencing the CFDA number(s): 93.226.
- This funding opportunity was created on 2024-07-16.
- Applicants must submit their applications by 2027-05-25.
- Eligible applicants include: State governments, County governments, City or township governments, Special district governments, Independent school districts, Public and State controlled institutions of higher education, Native American tribal governments (Federally recognized), Public housing authorities/Indian housing authorities, Native American tribal organizations (other than Federally recognized tribal governments), Nonprofits having a 501 (c) (3) status with the IRS, other than institutions of higher education, Nonprofits that do not have a 501 (c) (3) status with the IRS, other than institutions of higher education, Private institutions of higher education, For-profit organizations other than small businesses, Small businesses, Others.
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FAQs: Examining the Impact of Artificial Intelligence (AI) on Healthcare Safety (R18) (PA-24-261)
What is the title of this grant opportunity?
The opportunity is titled "Examining the Impact of Artificial Intelligence (AI) on Healthcare Safety (R18)."
What is the Funding Opportunity Number (FON)?
The Funding Opportunity Number is PA-24-261.
Which agency is offering this grant?
The grant is offered by the Agency for Health Care Research and Quality (AHRQ).
What type of funding instrument is this?
This is a grant (discretionary grant).
What is the CFDA number associated with this opportunity?
The CFDA number listed is 93.226.
What is the overall purpose of this funding opportunity?
This opportunity is designed to fund research that strengthens healthcare safety by examining how emerging, high-impact ("breakthrough") AI applications affect patient safety in real-world care and what it takes to implement and use these AI systems safely.
What is the main idea behind the research this NOFO is trying to support?
The core idea is to move beyond broad claims that AI will improve care and instead generate evidence about when AI improves safety, when it introduces new safety risks, and how organizations can reduce patient harm and user burden when deploying AI in clinical settings.
What kinds of research aims does the notice emphasize?
The notice emphasizes two central aims: (1) examining whether and how specific AI uses affect patient safety, and (2) clarifying how AI can be implemented and used safely in practice.
What does the first research aim focus on?
The first aim focuses on whether and how specific AI applications influence patient safety, including both safety benefits and safety hazards that may occur in real-world clinical use.
What are examples of safety benefits the research might examine?
Examples mentioned include earlier detection of deterioration, fewer medication errors, and improved diagnostic support.
What are examples of safety hazards or risks the research might examine?
Examples mentioned include biased predictions, automation complacency, incorrect recommendations, overreliance on imperfect models, workflow disruptions, and failure modes that only appear after deployment.
What does the second research aim focus on?
The second aim focuses on how AI can be implemented and used safely, including practical considerations organizations face when deploying AI in clinical environments.
What implementation and safe-use topics are specifically called out?
The notice points to governance, monitoring, human factors, training, workflow integration, transparency, accountability, and strategies to detect and mitigate harm over time.
Does the notice assume AI will automatically improve healthcare safety?
No. The framing explicitly encourages evidence generation rather than relying on general promises about AI. It recognizes potential benefits, but stresses the need to balance them against possible patient harm and added workload or cognitive burden.
Beyond safety, what other potential areas of improvement are recognized?
The notice recognizes that AI may improve safety, effectiveness, efficiency, access, and affordability.
What concerns does the notice raise about the impact of AI on clinicians, staff, and patients?
It highlights that AI can create added workload or cognitive burden for clinicians, staff, and patients, and that these burdens should be considered alongside safety outcomes.
Who is eligible to apply?
Eligibility is broad and includes state, county, city or township governments; special district governments; independent school districts; public and state-controlled institutions of higher education; private institutions of higher education; Native American tribal governments (federally recognized); Native American tribal organizations (other than federally recognized tribal governments); public housing authorities/Indian housing authorities; nonprofits with or without 501(c)(3) status (other than institutions of higher education); for-profit organizations other than small businesses; and small businesses.
Are specific types of colleges and minority-serving institutions mentioned as eligible?
Yes. The announcement highlights eligibility for Alaska Native and Native Hawaiian Serving Institutions, Asian American Native American Pacific Islander Serving Institutions (AANAPISI), Hispanic-serving Institutions, Historically Black Colleges and Universities (HBCUs), and Tribally Controlled Colleges and Universities (TCCUs).
Are faith-based or community-based organizations included in the eligible categories?
Yes. Faith-based or community-based organizations are specifically highlighted as eligible categories.
Are U.S. territories or possessions eligible?
Yes. U.S. territories or possessions are included among the additional eligible categories highlighted.
Are federal agencies eligible to apply?
Yes. The opportunity notes that eligible agencies of the federal government are included among eligible categories.
Are foreign (non-U.S.) organizations eligible to apply?
No. Non-domestic (non-U.S.) entities (foreign organizations) are excluded from applying.
Can a U.S. organization apply if the work is being led by a non-U.S. component of that organization?
No. The notice states that non-domestic components of U.S. organizations are not eligible to apply.
What is the activity category listed for this opportunity?
The activity category is listed as health.
What are the key dates provided for this opportunity?
The creation date is 2024-07-16, and the original closing date is 2027-05-25.
Is the award ceiling provided in the information shared?
No. The award ceiling is not specified in the provided data.
Is the expected number of awards provided in the information shared?
No. The expected number of awards is not specified in the provided data.
What does it mean that budget limits and project period expectations are not specified here?
Based on the provided information, those details are not included, which typically means applicants should consult the full notice for budget limits, project period expectations, and any submission cycles or review dates that may apply before the listed closing date.
What kind of evidence is this NOFO aiming to build?
It aims to build practical, safety-focused evidence about AI in healthcare: what AI changes about patient risk, where it can fail in real-world use, who might be disproportionately affected, and what safeguards, implementation practices, and ongoing monitoring are needed to improve outcomes without creating new, avoidable harms or burdens.
Does this opportunity focus on AI in real-world clinical settings or only in controlled research environments?
The description emphasizes real-world care and the realities of implementation and use of AI systems in clinical settings.
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