NYSDA Publications

AHRQ Issues CDSiC Newsletter

Jul 2, 2025

The Agency for Healthcare Research and Quality (AHRQ) has issued its Clinical Decision Support Innovation Collaborative (CDSiC) newsletter.

Issue Number 30 | July 2, 2025
In this edition of the Insider, we highlight a new AHRQ CDSiC resource on the use of artificial intelligence (AI) in patient-centered clinical decision support (PC CDS), AHRQ CDSiC tools that facilitate collaboration with patient partners in the design and development of PC CDS tools, and recent journal publications on patient-centered topics of interest to the PC CDS community.  We also spotlight two Requests for Information (RFIs) from the Department of Health and Human Services (HHS) that involve CDS research.
Table of Contents:
AI has the potential to strengthen PC CDS and ultimately improve patient care.  PC CDS tools use AI in a variety of ways, from analyzing patient data to facilitating self-management.  However, patients and their care teams need to be aware of the challenges involved in the use of AI, and what strategies can be used to overcome them.

In response, the AHRQ CDSiC created a new resource that shares key considerations for stakeholders interested in understanding, developing, or implementing AI-supported PC CDS.  This resource summarizes takeaways from multiple AHRQ CDSiC reports, including two real-world PC CDS pilots and work documenting patient and caregiver perspectives on this rapidly evolving topic.  Together, it provides strategies for improving the use of AI in PC CDS to ensure they support, rather than compromise, shared decision making and care quality.

Check out this valuable resource here, and all of the AHRQ CDSiC's AI-focused work here!

HHS is seeking input on two RFIs that involve CDS research and asks for input about where CDS work can continue across the Department.

The first RFI from NIH invites comments on NIH's future AI Strategy.  Its purpose is to develop an institute-wide AI strategy that charts a progression from today's data-science-driven analytics through semi-autonomous AI agents to fully autonomous, self-documenting biomedical AI beings.  Under the section for 'Research & Innovation Actions,' NIH is seeking high-impact use-cases for AI in biomedical discovery, public health protection, and CDS.  Submit comments by July 15.

The second RFI from NIH's National Library of Medicine (NLM) invites comments on the future of the NLM Biomedical and Data Science Extramural Research Programs.  In the past, CDS systems have been supported under the clinical informatics umbrella.  Now, NLM is looking for underexplored areas or for specific gaps in its current funding investments.  NLM wants to know how addressing these research gaps can lead to transformative impacts or advancements.  In addition to continuing support for clinical informatics, NLM seeks feedback on how to support emerging AI technologies that hold the most promise for advancing biomedical discovery, clinical decision making, and public health interventions.  Submit comments by July 14.

Effective, consistent engagement with patients is essential to ensure that PC CDS tools are aligned with these key users' needs, priorities, and interests.  It is also critical to seek out patients' perspectives throughout the development of PC CDS to facilitate the creation of tools that are truly accessible and usable.  However, it can be challenging for CDS developers to meaningfully collaborate with patients.

In response, the AHRQ CDSiC has developed several resources that facilitate collaborating with patients throughout the design and implementation of PC CDS.  These include:
  • A handbook that provides practical guidance on patient engagement throughout the PC CDS development cycle, highlights different engagement methods, and shares real-world examples of patient engagement activities.
  • A detailed report that shares insights into effective patient engagement learned from nine AHRQ-funded PC CDS projects.
  • A resource that outlines a range of methods and strategies that can be used to involve patients in the co-design of PC CDS.
To access all of the AHRQ CDSiC's patient engagement resources, click here!
This section highlights three recently published journal articles that focus on critical patient-centered topics relevant to AHRQ CDSiC stakeholders.  These articles further the PC CDS research agenda with their contributions to these key areas, including:
  • Patient perspectives on AI-supported CDS
  • The user-centered design and development of a patient-facing CDS app
  • The impact of a patient-facing CDS tool on symptom self-management and quality of life
Indecision on the Use of Artificial Intelligence in Healthcare—A Qualitative Study of Patient Perspectives on Trust, Responsibility and Self-Determination Using AI-CDSS

This qualitative study explored patients' attitudes toward AI-supported CDS systems.  Through focus group sessions, patients recognized the potential of AI-supported CDS tools to supplement clinicians' knowledge and increase efficiency.  However, patients also shared that AI-supported CDS could undermine trust between patients and clinicians, or lead to clinicians transferring responsibility to a separate technology.  These results emphasize the importance of patient involvement in the design and development of these tools to better ensure their alignment with patients' interests.
Extending Care Beyond the Clinic: Integrating Patient-Reported Outcomes in Chronic Pain Management Through Human Factors Engineering

This article describes the development of a patient- and clinician-facing CDS app intended to support tapering prescription opioid pain medication.  While designing the app, the study team engaged with stakeholders – including patients, caregivers, and pain specialists – through key informant interviews and usability tests to ensure the app met the needs of its intended users.  This engaged design process led to the creation of a user-friendly, accessible technology that incorporated patient data and supported shared decision making.
Effect of the Decision Support System Developed for Symptom Self-Management on Symptom Management, Quality of Life and Unplanned Hospital Admissions in Patients With Non-Hodgkin's Lymphoma: A Randomized Active-Controlled Trial

This article describes a randomized active-controlled trial that evaluated a patient-facing CDS app, LympCARE, designed to support symptom self-management.  CDS serve as valuable tools for supporting patients in self-management by providing up-to-date information, generating care reminders, and facilitating communication between patients and their care team.  This study found that LympCARE was effective in increasing quality of life and self-management, and reduced unplanned hospital admissions, demonstrating the potential for CDS interventions in this important area.
 
The Clinical Decision Support Innovation Collaborative (CDSiC) is a community of broad, diverse stakeholders at the forefront of using technology to better support care teams, patients, and caregivers.  The CDSiC is working toward healthcare decisions that are driven by both patient-centered and patient-specific information and that align with patient needs, preferences, and values.  The CDSiC is funded by the Agency for Healthcare Research and Quality (AHRQ) as part of a multi-component initiative to help advance patient-centered outcomes research into practice through CDS.  For any inquiries regarding the CDSiC you may contact the project team at CDSiC@norc.org.