Faculty Bibliography

BACKGROUND:Health equity is receiving increased attention in medical education. However, guidance is often lacking on how to integrate health equity into routine medical education. Journal club presents an opportunity to deepen medical educators' and learners' understanding of health equity principles and use it as a lens through which to critically appraise the literature. AIM/OBJECTIVE:We present a health equity framework, iteratively co-created by faculty and learners, that can be applied in a journal club setting. SETTING/METHODS:Academic medical center in New York City, USA. PARTICIPANTS/METHODS:Faculty, residency program directors, medical students, and residents. PROGRAM DESCRIPTION/METHODS:Authors developed the health equity journal club framework during a medical student selective course. Learner and faculty applied the framework to journal club articles; their feedback informed revisions. Framework domains included authorship, ethics, methodology, language, peer review, and references. PROGRAM EVALUATION/RESULTS:Learner evaluations were overall positive, and 86% (n = 13) of responding residency program directors (n = 15) across 15 departments who were surveyed plan to use the framework moving forward. DISCUSSION/CONCLUSIONS:A health equity journal club framework applied to critical appraisal of the literature may facilitate health equity as a routine part of medical education. Co-creating the framework proved vital to inclusion of learner voices.

BACKGROUND/UNASSIGNED:Usability testing is valuable for assessing a new tool or system's usefulness and ease-of-use. Several established methods of usability testing exist, including think-aloud testing. Although usability testing has been shown to be crucial for successful clinical decision support (CDS) tool development, it is often difficult to conduct across multisite development projects due to its time- and labor-intensiveness, cost, and the skills required to conduct the testing. OBJECTIVE/UNASSIGNED:Our objective was to develop a new method of usability testing that would enable efficient acquisition and dissemination of results among multiple sites. We sought to address the existing barriers to successfully completing usability testing during CDS tool development. METHODS/UNASSIGNED:We combined individual think-aloud testing and focus groups into one session and performed sessions serially across 4 sites (snowball group usability testing) to assess the usability of two CDS tools designed for use by nurses in primary and urgent care settings. We recorded each session and took notes in a standardized format. Each site shared feedback from their individual sessions with the other sites in the study so that they could incorporate that feedback into their tools prior to their own testing sessions. RESULTS/UNASSIGNED:The group testing and snowballing components of our new usability testing method proved to be highly beneficial. We identified 3 main benefits of snowball group usability testing. First, by interviewing several participants in a single session rather than individuals over the course of weeks, each site was able to quickly obtain their usability feedback. Second, combining the individualized think-aloud component with a focus group component in the same session helped study teams to more easily notice similarities in feedback among participants and to discuss and act upon suggestions efficiently. Third, conducting usability testing in series across sites allowed study teams to incorporate feedback based on previous sites' sessions prior to conducting their own testing. CONCLUSIONS/UNASSIGNED:Snowball group usability testing provides an efficient method of obtaining multisite feedback on newly developed tools and systems, while addressing barriers typically associated with traditional usability testing methods. This method can be applied to test a wide variety of tools, including CDS tools, prior to launch so that they can be efficiently optimized.

OBJECTIVE/UNASSIGNED:Our objective was to determine the feasibility and preliminary efficacy of a behavioral nudge on adoption of a clinical decision support (CDS) tool. MATERIALS AND METHODS/UNASSIGNED:We conducted a pilot cluster nonrandomized controlled trial in 2 Emergency Departments (EDs) at a large academic healthcare system in the New York metropolitan area. We tested 2 versions of a CDS tool for pulmonary embolism (PE) risk assessment developed on a web-based electronic health record-agnostic platform. One version included behavioral nudges incorporated into the user interface. RESULTS/UNASSIGNED: < .001). DISCUSSION/UNASSIGNED:We demonstrated feasibility and preliminary efficacy of a PE risk prediction CDS tool developed using insights from behavioral science. The tool is well-positioned to be tested in a large randomized clinical trial. TRIAL REGISTRATION/UNASSIGNED:Clinicaltrials.gov (NCT05203185).

BACKGROUND:During the COVID-19 pandemic, acute respiratory infection (ARI) antibiotic prescribing in ambulatory care markedly decreased. It is unclear if antibiotic prescription rates will remain lowered. METHODS:We used trend analyses of antibiotics prescribed during and after the first wave of COVID-19 to determine whether ARI antibiotic prescribing rates in ambulatory care have remained suppressed compared to pre-COVID-19 levels. Retrospective data was used from patients with ARI or UTI diagnosis code(s) for their encounter from 298 primary care and 66 urgent care practices within four academic health systems in New York, Wisconsin, and Utah between January 2017 and June 2022. The primary measures included antibiotic prescriptions per 100 non-COVID ARI encounters, encounter volume, prescribing trends, and change from expected trend. RESULTS:At baseline, during and after the first wave, the overall ARI antibiotic prescribing rates were 54.7, 38.5, and 54.7 prescriptions per 100 encounters, respectively. ARI antibiotic prescription rates saw a statistically significant decline after COVID-19 onset (step change -15.2, 95% CI: -19.6 to -4.8). During the first wave, encounter volume decreased 29.4% and, after the first wave, remained decreased by 188%. After the first wave, ARI antibiotic prescription rates were no longer significantly suppressed from baseline (step change 0.01, 95% CI: -6.3 to 6.2). There was no significant difference between UTI antibiotic prescription rates at baseline versus the end of the observation period. CONCLUSIONS:The decline in ARI antibiotic prescribing observed after the onset of COVID-19 was temporary, not mirrored in UTI antibiotic prescribing, and does not represent a long-term change in clinician prescribing behaviors. During a period of heightened awareness of a viral cause of ARI, a substantial and clinically meaningful decrease in clinician antibiotic prescribing was observed. Future efforts in antibiotic stewardship may benefit from continued study of factors leading to this reduction and rebound in prescribing rates.

BACKGROUND:Overprescribing of antibiotics for acute respiratory infections (ARIs) remains a major issue in outpatient settings. Use of clinical prediction rules (CPRs) can reduce inappropriate antibiotic prescribing but they remain underutilized by physicians and advanced practice providers. A registered nurse (RN)-led model of an electronic health record-integrated CPR (iCPR) for low-acuity ARIs may be an effective alternative to address the barriers to a physician-driven model. METHODS:Following qualitative usability testing, we will conduct a stepped-wedge practice-level cluster randomized controlled trial (RCT) examining the effect of iCPR-guided RN care for low acuity patients with ARI. The primary hypothesis to be tested is: Implementation of RN-led iCPR tools will reduce antibiotic prescribing across diverse primary care settings. Specifically, this study aims to: (1) determine the impact of iCPRs on rapid strep test and chest x-ray ordering and antibiotic prescribing rates when used by RNs; (2) examine resource use patterns and cost-effectiveness of RN visits across diverse clinical settings; (3) determine the impact of iCPR-guided care on patient satisfaction; and (4) ascertain the effect of the intervention on RN and physician burnout. DISCUSSION:This study represents an innovative approach to using an iCPR model led by RNs and specifically designed to address inappropriate antibiotic prescribing. This study has the potential to provide guidance on the effectiveness of delegating care of low-acuity patients with ARIs to RNs to increase use of iCPRs and reduce antibiotic overprescribing for ARIs in outpatient settings. TRIAL REGISTRATION:ClinicalTrials.gov Identifier: NCT04255303, Registered February 5 2020, https://clinicaltrials.gov/ct2/show/NCT04255303 .

Indiscriminate use of predictive models incorporating race can reinforce biases present in source data and lead to an exacerbation of health disparities. In some countries, such as the United States, there is therefore a push to remove race from prediction models; however, there are still many prediction models that use race as an input. Biomedical informaticists who are given the responsibility of using these predictive models in healthcare environments are likely to be faced with questions like how to deal with race covariates in these models. Thus, there is a need for a pragmatic framework to help model users think through how to include race in their chosen model so as to avoid inadvertently exacerbating disparities. In this paper, we use the case study of lung cancer screening to propose a simple framework to guide how model users can approach the use (or non-use) of race inputs in the predictive models they are tasked with leveraging in electronic health records and clinical workflows.

BACKGROUND:Through our work, we have demonstrated how clinical decision support (CDS) tools integrated into the electronic health record (EHR) assist providers in adopting evidence-based practices. This requires confronting technical challenges that result from relying on the EHR as the foundation for tool development; for example, the individual CDS tools need to be built independently for each different EHR. OBJECTIVE:The objective of our research was to build and implement an EHR-agnostic platform for integrating CDS tools, which would remove the technical constraints inherent in relying on the EHR as the foundation and enable a single set of CDS tools that can work with any EHR. METHODS:We developed EvidencePoint, a novel, cloud-based, EHR-agnostic CDS platform, and we will describe the development of EvidencePoint and the deployment of its initial CDS tools, which include EHR-integrated applications for clinical use cases such as prediction of hospitalization survival for patients with COVID-19, venous thromboembolism prophylaxis, and pulmonary embolism diagnosis. RESULTS:The results below highlight the adoption of the CDS tools, the International Medical Prevention Registry on Venous Thromboembolism-D-Dimer, the Wells' criteria, and the Northwell COVID-19 Survival (NOCOS), following development, usability testing, and implementation. The International Medical Prevention Registry on Venous Thromboembolism-D-Dimer CDS was used in 5249 patients at the 2 clinical intervention sites. The intervention group tool adoption was 77.8% (4083/5249 possible uses). For the NOCOS tool, which was designed to assist with triaging patients with COVID-19 for hospital admission in the event of constrained hospital resources, the worst-case resourcing scenario never materialized and triaging was never required. As a result, the NOCOS tool was not frequently used, though the EvidencePoint platform's flexibility and customizability enabled the tool to be developed and deployed rapidly under the emergency conditions of the pandemic. Adoption rates for the Wells' criteria tool will be reported in a future publication. CONCLUSIONS:The EvidencePoint system successfully demonstrated that a flexible, user-friendly platform for hosting CDS tools outside of a specific EHR is feasible. The forthcoming results of our outcomes analyses will demonstrate the adoption rate of EvidencePoint tools as well as the impact of behavioral economics "nudges" on the adoption rate. Due to the EHR-agnostic nature of EvidencePoint, the development process for additional forms of CDS will be simpler than traditional and cumbersome IT integration approaches and will benefit from the capabilities provided by the core system of EvidencePoint.