Study protocol for a type III hybrid effectiveness-implementation trial to evaluate scaling interoperable clinical decision support for patient-centered chronic pain management in primary care

Ramzi G Salloum, Lori Bilello, Jiang Bian, Julie Diiulio, Laura Gonzalez Paz, Matthew J Gurka, Maria Gutierrez, Robert W Hurley, Ross E Jones, Francisco Martinez-Wittinghan, Laura Marcial, Ghania Masri, Cara McDonnell, Laura G Militello, François Modave, Khoa Nguyen, Bryn Rhodes, Kendra Siler, David Willis, Christopher A Harle, Ramzi G Salloum, Lori Bilello, Jiang Bian, Julie Diiulio, Laura Gonzalez Paz, Matthew J Gurka, Maria Gutierrez, Robert W Hurley, Ross E Jones, Francisco Martinez-Wittinghan, Laura Marcial, Ghania Masri, Cara McDonnell, Laura G Militello, François Modave, Khoa Nguyen, Bryn Rhodes, Kendra Siler, David Willis, Christopher A Harle

Abstract

Background: The US continues to face public health crises related to both chronic pain and opioid overdoses. Thirty percent of Americans suffer from chronic noncancer pain at an estimated yearly cost of over $600 billion. Most patients with chronic pain turn to primary care clinicians who must choose from myriad treatment options based on relative risks and benefits, patient history, available resources, symptoms, and goals. Recently, with attention to opioid-related risks, prescribing has declined. However, clinical experts have countered with concerns that some patients for whom opioid-related benefits outweigh risks may be inappropriately discontinued from opioids. Unfortunately, primary care clinicians lack usable tools to help them partner with their patients in choosing pain treatment options that best balance risks and benefits in the context of patient history, resources, symptoms, and goals. Thus, primary care clinicians and patients would benefit from patient-centered clinical decision support (CDS) for this shared decision-making process.

Methods: The objective of this 3-year project is to study the adaptation and implementation of an existing interoperable CDS tool for pain treatment shared decision making, with tailored implementation support, in new clinical settings in the OneFlorida Clinical Research Consortium. Our central hypothesis is that tailored implementation support will increase CDS adoption and shared decision making. We further hypothesize that increases in shared decision making will lead to improved patient outcomes, specifically pain and physical function. The CDS implementation will be guided by the Exploration, Preparation, Implementation, Sustainment (EPIS) framework. The evaluation will be organized by the Reach, Effectiveness, Adoption, Implementation, and Maintenance (RE-AIM) framework. We will adapt and tailor PainManager, an open source interoperable CDS tool, for implementation in primary care clinics affiliated with the OneFlorida Clinical Research Consortium. We will evaluate the effect of tailored implementation support on PainManager's adoption for pain treatment shared decision making. This evaluation will establish the feasibility and obtain preliminary data in preparation for a multi-site pragmatic trial targeting the effectiveness of PainManager and tailored implementation support on shared decision making and patient-reported pain and physical function.

Discussion: This research will generate evidence on strategies for implementing interoperable CDS in new clinical settings across different types of electronic health records (EHRs). The study will also inform tailored implementation strategies to be further tested in a subsequent hybrid effectiveness-implementation trial. Together, these efforts will lead to important new technology and evidence that patients, clinicians, and health systems can use to improve care for millions of Americans who suffer from pain and other chronic conditions.

Trial registration: ClinicalTrials.gov, NCT05256394 , Registered 25 February 2022.

Conflict of interest statement

Laura Militello is a part owner of Applied Decision Science. Bryn Rhodes is a part owner of Dynamic Content Group (DBA Alphora). The other authors declare that they have no competing interests.

© 2022. The Author(s).

Figures

Fig. 1
Fig. 1
EPIS framework applied to interoperable clinical decision support for chronic pain management
Fig. 2
Fig. 2
PainManager interface. Left: current pain treatments; Right: patient-reported goals and barriers from MyPAIN. CQF. Clinical Decision Support for Chronic Pain Management and Shared Decision-Making IG. Retrieved 15 April 2022 from: https://build.fhir.org/ig/cqframework/cds4cpm/
Fig. 3
Fig. 3
Overview of study activities and outcomes
Fig. 4
Fig. 4
User-centered design process for pain management clinical decision support
Fig. 5
Fig. 5
Study diagram with key terminology as recommended by the Consolidated Standards of Reporting Trials (CONSORT) extension for stepped wedge randomized controlled trials. Note: each cluster include two primary care clinics from the University of Florida Health System in Jacksonville, FL

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