Many people with HIV (PWH) experience chronic pain that limits daily function and quality of life. PWH with chronic pain have commonly been prescribed opioids, sometimes for many years, and it is unclear if and how the management of these legacy patients should change in light of the current US opioid epidemic. Guidelines, such as the Centers for Disease Control and Prevention Guideline for Prescribing Opioids for Chronic Pain (CDCG), provide recommendations for the management of such patients but have yet to be translated into easily implementable interventions; there is also a lack of strong evidence that adhering to these recommendations improves patient outcomes such as amount of opioid use and pain levels. Herein we describe the development and preliminary testing of a theory-based intervention, called TOWER (TOWard SafER Opioid Prescribing), designed to support HIV primary care providers in CDCG-adherent opioid prescribing practices with PWH who are already prescribed opioids for chronic pain. TOWER incorporates the content of the CDCG into the theoretical and operational framework of the Information Motivation and Behavioral Skills (IMB) model of health-related behavior. The development process included elicitation research and incorporation of feedback from providers and PWH; testing is being conducted via an adaptive feasibility clinical trial. The results of this process will form the basis of a large, well-powered clinical trial to test the effectiveness of TOWER in promoting CDCG-adherent opioid prescribing practices and improving outcomes for PWH with chronic pain.

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Objective In response to the opioid epidemic, the Centers for Disease Control and Prevention issued guidelines (CDCG) in 2016 for the prescription of opioids for chronic pain. To facilitate research into whether CDCG implementation will lead to reductions in opioid prescribing and improved patient safety, we sought to validate a tool that quantifies CDCG adherence based on clinical documentation. Design The Safe Opioid Prescribing Evaluation Tool (SOPET) was developed in four phases as part of a study to improve the implementation of the CDCG in the clinical setting. Four raters with varying levels of clinical experience and expertise were trained to use the SOPET and then used it to evaluate 21 baseline patient encounters. Intraclass correlation coefficient (ICC) estimates and their 95% confident intervals (CIs) were calculated for the total SOPET score based on a mean-rating (k = 4), absolute-agreement, two-way random-effects model. For intrarater reliability, two-way mixed-effect models were used. Results Inter-rater reliability was good, with an average-measures ICC of 0.82 (95% CI = 0.63–0.92). Intrarater reliability was excellent for the three raters, who were MDs, with average-measures ICCs as follows: 0.92 (95% CI = 0.81–0.97), 0.97 (95% CI = 0.92–0.99), 0.99 (95% CI = 0.99–0.99). However, the intrarater reliability for the non-MD rater was lower 0.69 (95% CI = 0.22–0.88). Conclusions Overall, the SOPET is useful for evaluating implementation of the CDCG in clinical documentation. It is an important first step in the design of future studies assessing whether adherence to the CDCG improves patient safety outcomes.

BACKGROUND Collecting patient-reported data needed by clinicians to adhere to opioid prescribing guidelines represents a significant time burden. OBJECTIVE We developed and tested an opioid management app (OM-App) to collect these data directly from patients. METHODS OM-App used a pre-existing digital health platform to deliver daily questions to patients via text-message and organize responses into a dashboard. We pilot tested OM-App over 9 months in 40 diverse participants with HIV who were prescribed opioids for chronic pain. Feasibility outcomes included: ability to export/integrate OM-App data with other research data; patient-reported barriers and adherence to OM-App use; capture of opioid-related harms, risk behaviors and pain intensity/interference; comparison of OM-App data to urine drug testing, prescription drug monitoring program data, and validated questionnaires. RESULTS OM-App data was exported/integrated into the research database after minor modifications. Thirty-nine of 40 participants were able to use OM-App, and over the study duration 70% of all OM-App questions were answered. Although the cross-sectional prevalence of opioid-related harms and risk behaviors reported via OM-App was low, some of these were not obtained via the other measures, and over the study duration all queried harms/risks were reported at least once via OM-App. Clinically meaningful changes in pain intensity/interference were captured. CONCLUSIONS OM-App was used by our diverse patient population to produce clinically relevant opioid- and pain-related data, which was successfully exported and integrated into a research database. These findings suggest that OM-App may be a useful tool for remote monitoring of patients prescribed opioids for chronic pain. CLINICALTRIAL NCT03669939 INTERNATIONAL REGISTERED REPORT RR2-doi:10.1016/j.conctc.2019.100468

Background The 2016 U.S. Centers for Disease Control Opioid Prescribing Guideline (CDC Guideline) is currently being revised amid concern that it may be harmful to people with chronic pain on long-term opioid therapy (CP-LTOT). However, a methodology to faithfully implement the CDC guideline, measure prescriber adherence, and systematically test its effect on patient and public health outcomes is lacking. We developed and tested a CDC Guideline implementation strategy (termed TOWER), focusing on an outpatient HIV-focused primary care setting. Methods TOWER was developed in a stakeholder-engaged, multi-step iterative process within an Information, Motivation and Behavioral Skills (IMB) framework of behavior change. TOWER consists of: 1) a patient-facing opioid management app (OM-App); 2) a progress note template (OM-Note) to guide the office visit; and 3) a primary care provider (PCP) training. TOWER was evaluated in a 9-month, randomized-controlled trial of HIV-PCPs (N = 11) and their patients with HIV and CP-LTOT (N = 40). The primary outcome was CDC Guideline adherence based on electronic health record (EHR) documentation and measured by the validated Safer Opioid Prescribing Evaluation Tool (SOPET). Qualitative data including one-on-one PCP interviews were collected. We also piloted patient-reported outcome measures (PROMs) reflective of domains identified as important by stakeholders (pain intensity and function; mood; substance use; medication use and adherence; relationship with provider; stigma and discrimination). Results PCPs randomized to TOWER were 48% more CDC Guideline adherent (p < 0.0001) with significant improvements in use of: non-pharmacologic treatments, functional treatment goals, opioid agreements, prescription drug monitoring programs (PDMPs), opioid benefit/harm assessment, and naloxone prescribing. Qualitative data demonstrated high levels of confidence in conducting these care processes among intervention providers, and that OM-Note supported these efforts while experience with OM-App was mixed. There were no intervention-associated safety concerns (defined as worsening of any of the PROMs). Conclusions CDC-guideline adherence can be promoted and measured, and is not associated with worsening of outcomes for people with HIV receiving LTOT for CP. Future work would be needed to document scalability of these results and to determine whether CDC-guideline adherence results in a positive effect on public health. Trial registrationhttps://clinicaltrials.gov/ct2/show/NCT03669939. Registration date: 9/13/2018