Pain management is a significant issue for patients with substance use disorders (SUDs). In response to SUD QUERI goals of improving services for patients with SUDs and co-occurring conditions, SUD QUERI funded the development of the ATHENA Opioid Therapy (OT) Clinical Decision Support (CDS) system to (1) promote evidence-based best practices for opioid therapy for chronic pain and (2) improve detection of prescription opioid medication misuse. The VHA National Pain Management Program Office in the Office of Patient Care Services has strongly supported the ATHENA-OT CDS system as an important resource for assuring safe and effective use of opioid medications and as a tool that would meet providers' practice needs.
The objective was to obtain input from a range of VA stakeholders about how to enhance the acceptability and utility of the ATHENA-OT CDS system for use in a wide range of VA clinical settings nationwide. Analysis of this input will facilitate the ATHENA-OT CDS system team's efforts to optimize, enhance, and convert the ATHENA-OT CDS system from Class III to Class I software via the VA Office of Information &Technology Innovation Program.
The ATHENA-OT CDS system was set up in a test environment with hypothetical test patients as cases. Forty-four VA stakeholders in a range of areas/roles (primary care, pain management, mental health, nursing, geriatrics, women's health, polytrauma, pharmacy, facility/network leadership, information technology) participated in a demonstration of the CDS system and responded to a semi-structured interview about the usability/acceptability and opportunities to adapt and enhance the system. Responses were categorized into themes via qualitative data analyses.
VA stakeholders felt that the ATHENA-OT CDS system could improve care coordination by facilitating division of workload, improving patient education, and increasing knowledge of options in other disciplines. Stakeholders generated diverse ideas for adapting the CDS to better facilitate coordinating care for patients with chronic pain. Feedback also covered facilitators and barriers to implementation of the system.
Obtaining feedback on the ATHENA-OT CDS system from a range of VA stakeholders prior to system-wide implementation allows (1) system developers to proactively optimize, enhance, redesign, and convert the system from Class II to Class 1 software and (2) those who implement the system to address potential barriers and plan strategies to maximize the likelihood of successful implementation of a system that meets diverse providers' practice needs and has optimal potential to improve the quality of care of Veteran patients.
External Links for this Project
- Midboe AM, Lewis E, Cronkite R, Chambers D, Goldstein M, Kerns RD, Trafton J. Behavioral medicine perspectives on the design of health information technology to improve decision-making, guideline adherence, and care coordination in chronic pain management. Translational behavioral medicine. 2011 Mar 28; 1(1): 35-44. [view]
- Midboe AM, Lewis ET, Cronkite RC, Goldstein MK, Trafton JA. Behavioral Medicine Perspectives on a Clinical Decision Support System for Chronic Pain. Paper presented at: National Library of Medicine Training Conference; 2011 Jun 28; Bethesda, MD. [view]
- Huggins JL, Bonn-Miller MO, Oser ML, Medina JL, Trafton JA. Cognitive-behavioral therapy for pain among individuals with HIV: The relations between changes in pain acceptance and pain anxiety in terms of pain reduction. Poster session presented at: Association for Behavioral and Cognitive Therapies Annual Convention; 2010 Nov 19; San Francisco, CA. [view]
- Cronkite RC, Trafton JA, Chambers DA, Lewis ET, Midboe AM, Kerns R, Martins SB, Wang D, Ghaus S, Goldstein MK. Veterans Health Administration Stakeholders’ Input on Implementation of ATHENA-Opioid Therapy (OT) Clinical Decision Support (CDS) System. Poster session presented at: American Medical Informatics Association on Translational Bioinformatics Research Annual Summit; 2011 Mar 10; San Francisco, CA. [view]
Substance Use Disorders
Addictive Disorders, Decision support