AHRQ – Health Information Technology (IT) to Improve Health Care Quality and Outcomes (R21)

April 21, 2017 by School of Medicine Webmaster

This FOA issued by AHRQ invites grant applications for funding to conduct exploratory and developmental research grants (R21) for projects in the early and conceptual stages of development that will contribute to the evidence base of how health information technology (IT) improves health care quality and outcomes.


AHRQ is interested in exploring how health IT can improve health care quality and outcomes by enabling more effective population health management and patient-centered care delivery and coordination.  Health IT can enable these key functions of learning health systems by helping small and large health care providers effectively share information and apply available data and evidence to support care decisions and continuous improvement at both the individual and population levels.

Health care organizations and delivery systems are increasingly focused on improving the quality of care and health outcomes for the populations they serve. Availability and use of data from diverse sources is required to achieve these objectives. Population health management is central to many growing models of care delivery including patient-centered medical homes, accountable care organizations, and accountable health communities. Health care organizations require health IT systems and applications to enable effective population health management.

Effective delivery of patient-centered care requires that personal health information needs to follow patients as they interact with the health system.  All patients would benefit from coordinated health IT systems, enabling access to a comprehensive, longitudinal view of the patient’s health status and history. This is especially important for patients with multiple chronic conditions or complex health conditions including those that require health care services from multiple settings and specialties. Unfortunately, most patient health-related data are siloed, often inaccessible, and not presented in meaningful ways to facilitate shared decision making.  The result can be inefficient care handoffs, delayed services, and missed opportunities for shared decision making or optimal treatments, all yielding potential harm to patients.  Health IT has proven integral to key care management processes like scheduling comprehensive care management, determining the effectiveness and cost of health delivery models or interventions, and engaging patients in their own care.

The United States has invested heavily in the widespread adoption and use of health-related products and data systems that capture information to serve personal, clinical, research, and financial purposes.  The next critical step is maximizing this investment by gathering evidence on how best to utilize health IT to generate, integrate, and synthesize disparate electronic data and evidence to support systems and processes that continuously improve patient outcomes.

Health systems that effectively apply data and evidence to improve patient outcomes are called “learning health systems (LHS).” The Institute of Medicine (IOM), now referred to as the Health and Medicine Division (HMD), National Academy of Science, defines an LHS as a health care system that is “designed to generate and apply the best evidence for the collaborative health care choices of each patient and provider; to drive the process of discovery as a natural outgrowth of patient care; and to ensure innovation, quality, safety, and value in health care (IOM, 2007).” Recent developments are converging to make the vision of an LHS increasingly possible. AHRQ believes that learning health systems can provide the means to positively impact population health and achieve patient-centered care. Hence, AHRQ is seeking innovative health IT solutions to further enable learning health systems and thereby support better population management and patient-centered care delivery and coordination.

Objectives and Scope

The overarching objective of this FOA is to advance the use of health IT to manage population health and deliver patient-centered care.  This FOA aims to support exploratory and developmental health IT projects that seek to apply data and evidence in innovative ways to facilitate population health management and patient-centered care delivery and coordination.

Exploratory projects should be designed to develop health IT solutions that enable or facilitate population health management and patient-centered care delivery within health care organizations and health systems in a way that makes the solution shareable and configurable across different health domains and levels of scale.

Accordingly, this FOA is focused on two research areas of interest. Examples of research projects responsive to AHRQ health IT priorities under this FOA include but are not limited to those expressed within the following research areas of interest:

Bring Research Evidence to Clinical Practice

  • Apply research evidence by implementing and evaluating health IT solutions that (1) probe clinical and other health-related data sources to routinely identify the populations to whom the evidence pertains and (2) track health care system follow up on the application of the evidence to that population.
  • Develop and evaluate workflow tools that optimize implementation of evidence in a uniform way so that the evidence is rapidly and systematically applied to everyday practice at the point of care and so that health IT systems monitor the progress of moving evidence into practice.
  • Develop and evaluate innovative health IT solutions to quickly adapt evidence for clinical practice use so that patients receive appropriate, evidence-based care.
  • Develop a platform to share and analyze practice data in a way that makes knowledge learned from practice data actionable and shareable, including tailoring messages to decision makers.
  • Develop and evaluate a health IT solution that combines use of natural language processing (NLP) with a decision support tool in order to turn unstructured clinical  data into knowledge and knowledge into practice.
  • Develop and evaluate workflow-friendly decision support systems to transform clinical and health-related data (i.e., clinical, claims, socio-demographic, registry, quality improvement, environmental, social determinants of health, patient generated health data) into actionable information, improving overall quality, efficiency, and safety.

Use Clinical Data to Improve Care Delivery and Support Shared Decision Making

  • Develop and evaluate data analytic tools that are designed to scale-up across health care settings to help healthcare providers generate new knowledge from their practice data.
  • Develop and evaluate health IT solutions that support providers and patients in shared decision making by using practice data about the patient population to inform application of evidence to support identification of appropriate treatment options given expected treatment outcomes and patient preferences.
  • Develop and evaluate scalable tools aligned with workflow that support providers and patients in the effective, uniform use of clinical data plus evidence for shared decision making.
  • Develop technical solutions that support health care providers in learning about the effectiveness of practice changes, including quality improvement interventions and new models of care delivery, as changes are implemented.
  • Develop health IT resources that facilitate sharing and use of multiple data sources to support treatment decisions, care coordination, and care integration across multiple providers and evaluate the use of novel health IT tools for patients with multiple chronic conditions and/or patients from diverse populations.

Deadline:  standard dates apply

URL:  https://grants.nih.gov/grants/guide/pa-files/PA-17-246.html

Filed Under: Funding Opportunities