The Trust and Patient-Centeredness Workgroup Option Year 2 Charter is a document that describes the roles and key activities of the Workgroup under the CDSiC Stakeholder Community and Outreach Center.

This article published in JAMIA Open summarizes key themes that arose from stakeholder discussions at the inaugural Clinical Decision Support Innovation Collaborative (CDSiC) 2023 Annual Meeting. The authors analyzed compiled meeting notes to synthesize key themes and concluded that innovative approaches are needed to ensure patients’ and caregivers’ voices are meaningfully included to advance PC CDS. Click here to read the article. 

Patient preferences are an essential component of the patient voice, and their subsequent use in patient-centered clinical decision support can advance patient-centered care.This infographic presents an organizing framework that includes six domains for patient preference information most relevant to patient-centered clinical decision support (PC CDS), as well as key considerations for collecting and incorporating patient preferences within PC CDS.

This report offers various methods for capturing different types of patient preference data and visualizes these within patient lifeflows and clinical workflows.Developed by the AHRQ Clinical Decision Support Innovation Collaborative’s Trust and Patient-Centeredness Workgroup, this report identifies key considerations for optimizing the collection and use of patient preferences for patient-centered clinical decision support (PC CDS) to reduce patient and clinician burden, as well as opportunities to incorporate patient preferences into PC CDS.

This report aims to identify what measurement areas within the patient health journey are important to patients when determining if patient-centered clinical decision support (PC CDS) is achieving its intended purpose.Developed by the AHRQ Clinical Decision Support Innovation Collaborative’s Measurement and Outcomes Workgroup, this report highlights what patient health journey measurement areas should be prioritized.

This report assesses use of artificial intelligence to scale patient-centered clinical decision support.Developed by the AHRQ Clinical Decision Support Innovation Collaborative’s Implementation, Adoption, and Scaling Workgroup, this report provides an overview of current approaches for using artificial intelligence (AI) to scale patient-centered clinical decision support (PC CDS), outlines existing challenges, and highlights promising practices to ensure patient safety and privacy.

This report provides descriptions of patient and caregiver perspectives on the use of generative artificial intelligence in patient-centered clinical decision support.

This article, published in the Journal of the American Medical Informatics Association (JAMIA), uses workflow execution models to highlight new considerations for patient-centered clinical decision support (PC CDS) policies, processes, procedures, technology, and expertise required to support new workflows. Implementing and working with these new PC CDS-focused workflow execution models can lead to long-term positive impacts on patient health.

This inventory spreadsheet identifies available patient preference measurement tools from the literature to support the incorporation of patient preferences into PC CDS tools.Developed by the AHRQ CDSiC Measurement and Outcomes Workgroup, this spreadsheet can be used by PC CDS developers, implementers, and evaluators with the accompanying report, the Measurement and Outcomes Workgroup: Inventory of Patient Preference Measurement Tools for PC CDS Report.

This report describes an inventory of tools to collect patient preference information.