Opportunity Information: Apply for RFA HS 10 015
Apply for RFA HS 10 015
- The Agency for Health Care Research and Quality in the health sector is offering a public funding opportunity titled "ARRA OS Recovery Act 2009 Limited Competition Scalable Distributed Research Networks for Comparative Effectiveness Research (R01)" and is now available to receive applicants.
- This funding opportunity was created on Jan 21, 2010 and posted on Jan 21, 2010.
- Applicants must submit their applications by Mar 10, 2010. (Agency may still review applications by suitable applicants for the remaining/unused allocated funding in 2026.)
- The funding agency has allocated a total of $25,000,000.00 to eligible and selected applicants.
- Each selected applicant is eligible to receive up to $2,770,000.00 in funding.
- Eligible applicants include: Private institutions of higher education Public and State controlled institutions of higher education City or township governments Native American tribal organizations (other than Federally recognized tribal governments) County governments State governments Others (see text field entitled Additional Information on Eligibility for clarification) Native American tribal governments (Federally recognized).
- Other Eligible Applicants include the following Faith based or Community based Organizations Indian/Native American Tribal Governments (Other than Federally Recognized).
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Opportunity Summary:
The grant opportunity titled "ARRA OS Recovery Act 2009 Limited Competition Scalable Distributed Research Networks for Comparative Effectiveness Research (R01)" (Funding Opportunity Number RFA-HS-10-015) was a discretionary research grant program run by the Agency for Healthcare Research and Quality (AHRQ) using funds provided through the U.S. Department of Health and Human Services Office of the Secretary under the American Recovery and Reinvestment Act of 2009 (ARRA, Public Law 111-5). It was posted on January 21, 2010, with an application deadline of March 10, 2010, and later archived on April 10, 2010. The program did not require cost sharing or matching funds.
The central aim of the announcement was to strengthen the national capacity to conduct prospective comparative effectiveness research (CER) by building and improving scalable, distributed research networks that rely on electronic clinical data. In practical terms, AHRQ was looking for projects that could enhance both the infrastructure (the technical and organizational backbone that allows multiple health systems or data partners to participate) and the methods (the study designs, data standards, analytic approaches, and governance practices) needed to collect and use prospective data drawn from electronic clinical databases. The emphasis on prospective data collection signals a focus on strengthening the ability of these networks to plan, standardize, and capture data forward in time for specific research questions, rather than relying only on retrospective extraction of whatever data already happen to be stored.
This FOA was specifically oriented toward distributed research, meaning the participating organizations could keep data at their home institutions while still enabling multi-site analyses through common data models, standardized queries, and coordinated protocols. That model is often used to address privacy, security, proprietary concerns, and operational barriers that come with pooling patient-level data into a single central repository. The term "scalable" indicates that AHRQ wanted networks that could grow in size, increase the number of participating sites, and support multiple studies efficiently, rather than being built for a single, one-off project.
The research focus was comparative effectiveness of healthcare interventions as they are used in real-world clinical care. The opportunity explicitly included a wide range of intervention types: diagnostic approaches, therapeutics such as drugs and biologics, medical devices, behavioral interventions, and surgical procedures. The intent was to enable networks to generate new evidence about outcomes associated with these interventions by leveraging electronic clinical data sources, which could include electronic health records and other routinely collected clinical databases. By targeting outcomes of clinical interventions, the announcement aligns with CER priorities like understanding which treatments work best for which patients, under what circumstances, and with what tradeoffs in benefits and harms.
Funding for the program was substantial. The estimated total funding available across awards was $25,000,000, and the listed award ceiling was $2,770,000 per award. The funding instrument was an R01 Research Project Grant, which generally supports defined projects with specific aims, milestones, and deliverables. While the FOA title notes "limited competition," the provided text does not spell out the restriction details; in many federal programs that phrase usually means eligibility or applicant pools may be constrained by prior participation, specific network status, or other criteria described in the full announcement.
Eligibility was broad across public and private sectors, reflecting the reality that distributed research networks often require partnerships among universities, health systems, and government entities. Eligible applicants included private institutions of higher education, public and state-controlled institutions of higher education, state governments, county governments, and city or township governments. Tribal organizations were also eligible, including federally recognized tribal governments and other Native American tribal organizations. The opportunity further noted that faith-based and community-based organizations could qualify under the "other eligible applicants" category. This range of eligibility suggests AHRQ anticipated applications from academic-led consortia, state or regional health data collaborations, multi-system provider networks, and cross-sector partnerships capable of managing large clinical data assets and multi-site governance.
Administratively, the program was managed through the NIH Office of Extramural Research (OER) systems for accessing the full announcement, with contact emails provided for technical issues related to accessing or linking to the FOA. The full details were available through the NIH grants guide link included in the announcement.
Overall, this ARRA-funded R01 opportunity was designed to accelerate the development of durable, privacy-conscious, multi-institution electronic health data networks that could reliably run prospective comparative effectiveness studies. The government intent was not just to fund individual studies, but to leave behind improved national infrastructure and stronger methodological playbooks for using electronic clinical data to answer practical, patient-centered questions about what works in healthcare.
FAQs: ARRA OS Recovery Act 2009 Limited Competition Scalable Distributed Research Networks for Comparative Effectiveness Research (R01) (RFA-HS-10-015)
What is the official title and funding opportunity number for this grant?
The opportunity is titled "ARRA OS Recovery Act 2009 Limited Competition Scalable Distributed Research Networks for Comparative Effectiveness Research (R01)" and the Funding Opportunity Number is RFA-HS-10-015.
Which federal agency ran this program?
The program was run by the Agency for Healthcare Research and Quality (AHRQ).
What was the source of funding for this opportunity?
Funds were provided through the U.S. Department of Health and Human Services (HHS) Office of the Secretary under the American Recovery and Reinvestment Act of 2009 (ARRA, Public Law 111-5).
What type of grant mechanism was used?
The funding instrument was an R01 Research Project Grant.
When was the opportunity posted, and what was the application deadline?
It was posted on January 21, 2010. The application deadline was March 10, 2010.
Is this funding opportunity still open?
No. The announcement was later archived on April 10, 2010.
Was cost sharing or matching required?
No. The program did not require cost sharing or matching funds.
What was the central aim of the program?
The central aim was to strengthen national capacity to conduct prospective comparative effectiveness research (CER) by building and improving scalable, distributed research networks that rely on electronic clinical data.
What does "comparative effectiveness research (CER)" mean in this context?
In this announcement, CER focused on comparing healthcare interventions as they are used in real-world clinical care, with the goal of generating evidence about outcomes and helping answer practical questions about which interventions work best for which patients and under what circumstances.
What kinds of interventions were included as CER topics?
The opportunity explicitly included diagnostic approaches, therapeutics (such as drugs and biologics), medical devices, behavioral interventions, and surgical procedures.
What types of data were these networks expected to use?
The program emphasized electronic clinical data, including electronic health records and other routinely collected clinical databases.
What does "prospective data collection" mean for this grant?
It signals a focus on improving the ability of networks to plan, standardize, and capture data going forward in time for specific research questions, rather than relying only on retrospective extraction of already-stored data.
What is a "distributed research network" in the sense used by this FOA?
It refers to a multi-organization research approach where participating organizations can keep data at their home institutions while still enabling multi-site analyses through common data models, standardized queries, and coordinated protocols.
Why did the FOA emphasize a distributed approach instead of pooling all data into one central database?
The distributed model is often used to address privacy, security, proprietary concerns, and operational barriers that can come with pooling patient-level data into a single central repository.
What did AHRQ mean by "scalable" distributed research networks?
"Scalable" indicates networks were expected to be able to grow in size, add participating sites, and support multiple studies efficiently, rather than being built for a single one-off project.
What kinds of project activities were encouraged by the FOA?
Projects were expected to enhance both infrastructure (technical and organizational backbone enabling participation across partners) and methods (study designs, data standards, analytic approaches, and governance practices) needed to collect and use prospective data from electronic clinical databases.
How much total funding was estimated to be available?
The estimated total funding available across awards was $25,000,000.
What was the maximum award amount (award ceiling) listed?
The listed award ceiling was $2,770,000 per award.
Who was eligible to apply?
Eligible applicants included private institutions of higher education, public and state-controlled institutions of higher education, state governments, county governments, and city or township governments. Tribal organizations were eligible (including federally recognized tribal governments and other Native American tribal organizations). The opportunity also noted that faith-based and community-based organizations could qualify under "other eligible applicants."
Did the FOA indicate anything about competition being limited?
The title includes "limited competition," but the provided information does not spell out the restriction details. In many federal programs, this phrase typically implies the eligible applicant pool may be constrained by criteria described in the full announcement.
Where were the full announcement details hosted or accessed?
The program was managed through NIH Office of Extramural Research (OER) systems for accessing the full announcement, with an NIH grants guide link referenced in the announcement.
What was the broader intent behind funding these networks?
The intent was not only to fund individual studies, but also to accelerate development of durable, privacy-conscious, multi-institution electronic health data networks and strengthen the methodological playbook for running prospective CER using electronic clinical data.
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