A pragmatic study of Clinical Decision Support to promote Prescription Drug Monitoring Program use

Posted on May 7, 2021May 18, 2021 by coprhcon

INTRODUCTION

Providing appropriate, safe analgesia during the opioid crisis a challenge. Prescription Drug Monitoring Programs (PDMPs), an evidence-based intervention to improve prescribing decisions, are underutilized. Electronic health record (EHR) based clinical decision support (CDS) represents a pragmatic, patient-specific and scalable implementation strategy to promote behavior change. Our objective is to assess the development and early deployment of a pragmatic, cluster randomized trial of CDS tools to facilitate PDMP use.

METHODS

This is an IRB-approved cluster randomized study. Using published best practices and a literature review, we developed two prototype logic-driven patient-specific CDS to identify patients at risk of opioid abuse/overdose and trigger an interruptive alert to review the PDMP:(1) PDMP risk criteria alone and (2) PDMP + EHR risk criteria. Iterative CDS modifications were informed by interviews with target adopters and organizational decision makers, including clinical observations. Following silent testing of the revised alerts, we randomized providers to receive one of the two alerts or a control alert (fires for all opioid/benzodiazepine e-prescriptions). Alerts were tested live in the academic ED (156 providers and 88k unique patients in 2020) for one month prior to activation in all system EDs. Inpatient and ambulatory settings were activated in a staggered fashion. Education was disseminated through presentations, emails from leadership, a featured article in the system EHR newsletter, and individual provider contacts.

RESULTS

Qualitative feedback from 20 interviews and 10 workflow observations identified concerns for interruptions, alert fatigue, and alert suppression. We completed 3 months of silent testing on ED discharges: control alert triggered 8.1% (95%CI 7.9-8.3%) of discharges, with variability across EDs (5.1-11.3%). PDMP only alert triggered 2.8% (95%CI 2.7-3.0%) before modification and 2.0% (95%CI 1.9-2.1%) after user-driven modification. PDMP + EHR alert triggered 4.2% (95%CI 4.1-4.4%) before modification and 3.7% (95%CI 3.5-3.9%) afterward. Study is ongoing: firing rates, adoption, and PDMP use for all 3 CDS tools in EDs, inpatient facilities and ambulatory clinics will be reported.

Virtual Dissemination Strategies to Raise Awareness of a Community-drive COVID-19 Testing Program

Posted on May 7, 2021May 18, 2021 by coprhcon

BACKGROUND

Dissemination through social media can be an effective strategy in developing and strengthening community engagement/awareness of community-driven research programs. One such NIH-funded program is CO-CREATE (Community-Driven Optimization of COVID-19 Testing to Reach and Engage underserved Areas for Testing Equity), which aims to promote equity in COVID-19 testing for underserved communities. We describe use of two social media outlets (Instagram and Twitter) along with a program-specific website to disseminate program information and engage community members in our collaborative work.

METHODS

CO-CREATE established its social media campaign in 3 stages:
1) developing a strategic plan of action (i.e., selecting appropriate platforms, identifying strategies to increase followers among our target populations of San Ysidro residents, health practitioners, and community organizations, and understanding the best methods for content promotion);
2) creating and disseminating content in line with CO-CREATE’s goals; 3) reviewing data analytics to further adapt and curate online content.

RESULTS

Three social media platforms were deployed as part of the CO-CREATE social media campaign. They were: 1) Instagram (@ucsdcocreateproject), 2) Twitter (@ucsdcocreate), and 3) a public-facing program website (co-create-radx.com). All were launched in January/February 2021. Based on analytics data, Instagram followers have increased by 21.9% between February 4 and March 5. To date, our Instagram page has amassed 111 followers, of which 67.3% identify as female and 67.8% are between the ages of 25-34. Instagram followers are most active on Instagram on Saturday evenings and top locations include San Diego, Chula Vista, Tijuana, which are neighboring regions that are the focus of CO-CREATE. In comparison, the CO-CREATE Twitter page has gained a total of nine followers. With a total of 3 tweets (posts), our average number of impressions (quantity of all the times the tweet has been seen) and engagements (when someone interacts with a tweet) is 63.3 and 5.3, respectively. Finally, the CO-CREATE website has accumulated 93 site sessions, 54 unique visitors, and 283 page views, with an average session duration of two minutes. The most popular page is the “team” page, meaning visitors are most interested in who is involved with the project.

Leave Me Out! Patients’ Characteristics and Reasons for Opting Out of a Pragmatic Clinical Trial

Posted on May 7, 2021May 18, 2021 by coprhcon

BACKGROUND

Pragmatic clinical trials (PCT) aim to inform healthcare decisions and treatment effectiveness based on data from real-world settings and populations. This generally requires that data be collected from a large and representative population, which in turn necessitates minimizing costs and burdens for patients and clinicians that can be associated with traditional clinical research, such as elaborate written informed consent processes. Opt out consent practices are sometimes used as a means to promote patients’ autonomous preferences regarding research participation while reducing both patient and researcher burden. Despite this, little is known about the characteristics of patients who choose to opt-out of research and their reasons for doing so. Therefore, we gathered such information in a large PCT seeking to improve medication adherence via evidence-based text messages employing nudge theory.

RESULTS

Of 9,444 patients eligible for the trial, 895 (9.5%) patients opted out. Of those who opted out, 451 (50.1%) returned the opt out survey. Patients who opted out were more likely to be older, male, white, and non-Hispanic than those that did not (p<0.001 for all). Nearly half (46.6%) of respondents reported concerns about time as a reason to opt out of the study. Perceptions of not needing the intervention (19.5%) and discomfort with technology (18.6%) were the next most common responses. Conclusions: In this PCT focused on medication adherence improvement, less than 10% of patients opted out of participation, with significant differences in age, race, gender, and ethnicity between patients that opted out and those that did not. Future trials may wish to provide additional information to address the most commonly cited reasons by patients for opting out of a low-risk trial. The impact additional patient characteristics may have on opting out will be analyzed in April and May.