Abstract

Background: Opioid prescriptions for chronic pain are a major contributor towards the ongoing opioid epidemic, adding to a record high number of drug overdose deaths in 2022. Shared decision-making between patients and providers is highly valuable to align the array of treatment options and non-pharmacologic treatments (NPTs) with Veterans’ unique pain experiences. Newer data streams, including patient-generated health data (PGHD) that are created directly by patients, offer rich information not typically assessed during visits (e.g., patient-reported outcomes, pain functioning, physical activity). This CDA-2 aims to enhance pain management by building a shared decision-making tool that collects pain PGHD and harmonizes it with treatment preferences and medications to improve use of NPTs and reduce pain interference and opioid use. Significance/Impact: The opioid crisis is salient for VA, as up to 50% of Veterans (over 2 million) experience chronic pain. There is a critical need to improve pain management and reduce opioid use among Veterans with chronic pain. This research seeks to address these challenges by developing and testing a tool that facilitates shared decision-making and adoption of NPTs. Further, building interoperable clinical informatics tools that can be scaled across the VA will advance the VA’s ongoing electronic health record (EHR) modernization efforts. Innovation: This proposal will improve pain management through three innovations: 1) identification of the content, visualizations, and clinical integration factors needed to support patient-clinician collaboration around pain PGHD, 2) development of an interoperable clinical decision support (CDS) tool that visualizes PGHD and EHR data at the point-of-care, entitled Patient-generated Assessment Technology for improved Health (“PATH for Pain Management”) and 3) identification and characterization of Veterans’ pain treatment preferences and goals through natural language processing methods. Specific Aims: 1) Aim 1: Gather insights from Veterans with chronic pain on preferences for reporting their pain experience and goals. Aim 1a: Examine Veterans’ perspectives on sharing pain-related PGHD with clinicians and preferred pain measures to communicate their pain experience; Aim 1b: Identify and describe pain treatment preferences and goals from clinical progress notes. 2) Aim 2: Iteratively design and develop the PATH for Pain Management CDS tool that incorporates pain PGHD and facilitates shared decision-making to improve chronic pain management. Aim 2a: Design the structure and content for a CDS tool that presents information about a Veteran’s pain experience through interviews with VA pain providers; Aim 2b: Develop a web-based prototype of the tool using the VA’s CDS Program Platform. 3) Aim 3. Conduct a comprehensive usability evaluation to optimize the acceptability and use of the PATH for Pain Management CDS tool that promotes shared decision-making for Veterans with chronic pain. Methodology: In Aim 1a, human-centered design methods will identify Veterans’ preferences for pain measures to communicate with their care team. In Aim 1b, natural language processing will be used to identify and describe treatment preferences and goals among Veterans seen at three multidisciplinary pain clinics. In Aim 2a, interviews will be used to examine VA pain providers’ preferences for the content and visualizations of the CDS tool. In Aim 2b, we will develop a functional prototype based on the feedback from Veterans and providers. In Aim 3, usability and feasibility of clinical integration of the tool will be assessed among providers. Next Steps/Implementation: These findings will inform development of two HSR&D investigator-initiated research (IIR) proposals to be submitted in years 3 and 5, which focus on implementing these novel tools into VA care and evaluating patient outcomes. Notably, this approach can inform future development and implementation of clinical informatics tools that integrate PGHD into VA care for chronic disease management .

NIH Reporter Project Information: https://reporter.nih.gov/project-details/10998031


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