Faculty Bibliography

Cluster-randomized trials (CRTs) often allocate intact clusters of participants to treatment or control conditions and are increasingly used to evaluate healthcare delivery interventions. While previous studies have developed sample size methods for testing confirmatory hypotheses of treatment effect heterogeneity in CRTs (i.e., targeting the difference between subgroup-specific treatment effects), sample size methods for testing the subgroup-specific treatment effects themselves have not received adequate attention-despite a rising interest in health equity considerations in CRTs. In this article, we develop formal methods for sample size and power analyses for testing subgroup-specific treatment effects in parallel-arm CRTs with a continuous outcome and a binary subgroup variable. We point out that the variances of the subgroup-specific treatment effect estimators and their covariance are given by weighted averages of the variance of the overall average treatment effect estimator and the variance of the heterogeneous treatment effect estimator. This analytical insight facilitates an explicit characterization of the requirements for both the omnibus test and the intersection-union test to achieve the desired level of power. Generalizations to allow for subgroup-specific variance structures are also discussed. We report on a simulation study to validate the proposed sample size methods and demonstrate that the empirical power corresponds well with the predicted power for both tests. The design and setting of the Umea Dementia and Exercise (UMDEX) CRT in older adults are used to illustrate our sample size methods.

The cluster randomized crossover design has been proposed to improve efficiency over the traditional parallel-arm cluster randomized design. While statistical methods have been developed for designing cluster randomized crossover trials, they have exclusively focused on testing the overall average treatment effect, with little attention to differential treatment effects across subpopulations. Recently, interest has grown in understanding whether treatment effects may vary across pre-specified patient subpopulations, such as those defined by demographic or clinical characteristics. In this article, we consider the two-treatment two-period cluster randomized crossover design under either a cross-sectional or closed-cohort sampling scheme, where it is of interest to detect the heterogeneity of treatment effect via an interaction test. Assuming a patterned correlation structure for both the covariate and the outcome, we derive new sample size formulas for testing the heterogeneity of treatment effect with continuous outcomes based on linear mixed models. Our formulas also address unequal cluster sizes and therefore allow us to analytically assess the impact of unequal cluster sizes on the power of the interaction test in cluster randomized crossover designs. We conduct simulations to confirm the accuracy of the proposed methods, and illustrate their application in two real cluster randomized crossover trials.

BACKGROUND:Non-fatal overdose is a leading predictor of subsequent fatal overdose. For individuals who are incarcerated, the risk of experiencing an overdose is highest when transitioning from a correctional setting to the community. We assessed if enrollment in jail-based medications for opioid use disorder (MOUD) is associated with lower risk of non-fatal opioid overdoses after jail release among individuals with opioid use disorder (OUD). METHODS:This was a retrospective, observational cohort study of adults with OUD who were incarcerated in New York City jails and received MOUD or did not receive any MOUD (out-of-treatment) within the last three days before release to the community in 2011-2017. The outcome was the first non-fatal opioid overdose emergency department (ED) visit within 1 year of jail release during 2011-2017. Covariates included demographic, clinical, incarceration-related, and other characteristics. We performed multivariable cause-specific Cox proportional hazards regression analysis to compare the risk of non-fatal opioid overdose ED visits within 1 year after jail release between groups. RESULTS:MOUD group included 8660 individuals with 17,119 incarcerations; out-of-treatment group included 10,163 individuals with 14,263 incarcerations. Controlling for covariates and accounting for competing risks, in-jail MOUD was associated with lower non-fatal opioid overdose risk within 14 days after jail release (adjusted HR=0.49, 95% confidence interval=0.33-0.74). We found no significant differences 15-28, 29-56, or 57-365 days post-release. CONCLUSION/CONCLUSIONS:MOUD group had lower risk of non-fatal opioid overdose immediately after jail release. Wider implementation of MOUD in US jails could potentially reduce post-release overdoses, ED utilization, and associated healthcare costs.

INTRODUCTION/BACKGROUND:This study aimed to assess emergency nurses' perceived barriers toward engaging patients in serious illness conversations. METHODS:Using a mixed-method (quant + QUAL) convergent design, we pooled data on the emergency nurses who underwent the End-of-Life Nursing Education Consortium training across 33 emergency departments. Data were extracted from the End-of-Life Nursing Education Consortium post-training questionnaire, comprising a 5-item survey and 1 open-ended question. Our quantitative analysis employed a cross-sectional design to assess the proportion of emergency nurses who report that they will encounter barriers in engaging seriously ill patients in serious illness conversations in the emergency department. Our qualitative analysis used conceptual content analysis to generate themes and meaning units of the perceived barriers and possible solutions toward having serious illness conversations in the emergency department. RESULTS:A total of 2176 emergency nurses responded to the survey. Results from the quantitative analysis showed that 1473 (67.7%) emergency nurses reported that they will encounter barriers while engaging in serious illness conversations. Three thematic barriers-human factors, time constraints, and challenges in the emergency department work environment-emerged from the content analysis. Some of the subthemes included the perceived difficulty of serious illness conversations, delay in daily throughput, and lack of privacy in the emergency department. The potential solutions extracted included the need for continued training, the provision of dedicated emergency nurses to handle serious illness conversations, and the creation of dedicated spaces for serious illness conversations. DISCUSSION/CONCLUSIONS:Emergency nurses may encounter barriers while engaging in serious illness conversations. Institutional-level policies may be required in creating a palliative care-friendly emergency department work environment.

BACKGROUND:EM Talk is a communication skills training program designed to improve emergency providers' serious illness conversational skills. Using the Reach, Effectiveness, Adoption, Implementation, and Maintenance (RE-AIM) framework, this study aims to assess the reach of EM Talk and its effectiveness. METHODS:EM Talk consisted of one 4-h training session during which professional actors used role-plays and active learning to train providers to deliver serious/bad news, express empathy, explore patients' goals, and formulate care plans. After the training, emergency providers filled out an optional post-intervention survey, which included course reflections. Using a multi-method analytical approach, we analyzed the reach of the intervention quantitatively and the effectiveness of the intervention qualitatively using conceptual content analysis of open-ended responses. RESULTS:A total of 879 out of 1,029 (85%) EM providers across 33 emergency departments completed the EM Talk training, with the training rate ranging from 63 to 100%. From the 326 reflections, we identified meaning units across the thematic domains of improved knowledge, attitude, and practice. The main subthemes across the three domains were the acquisition of Serious Illness (SI) communication skills, improved attitude toward engaging qualifying patients in SI conversations, and commitment to using these learned skills in clinical practice. CONCLUSION/CONCLUSIONS:Our study showed the extensive reach and the effectiveness of the EM Talk training in improving SI conversation. EM Talk, therefore, can potentially improve emergency providers' knowledge, attitude, and practice of SI communication skills. TRIAL REGISTRATION/BACKGROUND:Clinicaltrials.gov: NCT03424109; Registered on January 30, 2018.

BACKGROUND/UNASSIGNED:Precision medicine has led to the development of targeted treatment strategies tailored to individual patients based on their characteristics and disease manifestations. Although precision medicine often focuses on a single health outcome for individualized treatment decision rules (ITRs), relying only on a single outcome rather than all available outcomes information leads to suboptimal data usage when developing optimal ITRs. METHODS/UNASSIGNED:To address this limitation, we propose a Bayesian multivariate hierarchical model that leverages the wealth of correlated health outcomes collected in clinical trials. The approach jointly models mixed types of correlated outcomes, facilitating the "borrowing of information" across the multivariate outcomes, and results in a more accurate estimation of heterogeneous treatment effects compared to using single regression models for each outcome. We develop a treatment benefit index, which quantifies the relative treatment benefit of the experimental treatment over the control treatment, based on the proposed multivariate outcome model. RESULTS/UNASSIGNED:We demonstrate the strengths of the proposed approach through extensive simulations and an application to an international Coronavirus Disease 2019 (COVID-19) treatment trial. Simulation results indicate that the proposed method reduces the occurrence of erroneous treatment decisions compared to a single regression model for a single health outcome. Additionally, the sensitivity analysis demonstrates the robustness of the model across various study scenarios. Application of the method to the COVID-19 trial exhibits improvements in estimating the individual-level treatment efficacy (indicated by narrower credible intervals for odds ratios) and optimal ITRs. CONCLUSION/UNASSIGNED:The study jointly models mixed types of outcomes in the context of developing ITRs. By considering multiple health outcomes, the proposed approach can advance the development of more effective and reliable personalized treatment.

BACKGROUND/UNASSIGNED:The long-term effect of coronavirus disease 2019 (COVID-19) acute treatments on postacute sequelae of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection (PASC) is unknown. The CONTAIN-Extend study explores the long-term impact of COVID-19 convalescent plasma (CCP) therapy on postacute sequelae of SARS-CoV-2 infection (PASC) symptoms and general health 18 months following hospitalization. METHODS/UNASSIGNED:The CONTAIN-Extend study examined 281 participants from the original CONTAIN COVID-19 trial (CONTAIN-RCT, NCT04364737) at 18 months post-hospitalization for acute COVID-19. Symptom surveys, global health assessments, and biospecimen collection were performed from November 2021 to October 2022. Multivariable logistic and linear regression estimated associations between the randomization arms and self-reported symptoms and Patient-Reported Outcomes Measurement Information System (PROMIS) scores and adjusted for covariables, including age, sex, race/ethnicity, disease severity, and CONTAIN enrollment quarter and sites. RESULTS/UNASSIGNED:There were no differences in symptoms or PROMIS scores between CCP and placebo (adjusted odds ratio [aOR] of general symptoms, 0.95; 95% CI, 0.54-1.67). However, females (aOR, 3.01; 95% CI, 1.73-5.34), those 45-64 years (aOR, 2.55; 95% CI, 1.14-6.23), and April-June 2020 enrollees (aOR, 2.39; 95% CI, 1.10-5.19) were more likely to report general symptoms and have poorer PROMIS physical health scores than their respective reference groups. Hispanic participants (difference, -3.05; 95% CI, -5.82 to -0.27) and Black participants (-4.48; 95% CI, -7.94 to -1.02) had poorer PROMIS physical health than White participants. CONCLUSIONS/UNASSIGNED:CCP demonstrated no lasting effect on PASC symptoms or overall health in comparison to the placebo. This study underscores the significance of demographic factors, including sex, age, and timing of acute infection, in influencing symptom reporting 18 months after acute hypoxic COVID-19 hospitalization.

The objective of this study was to estimate the associations of jail-initiated medication for opioid use disorder (MOUD) and patient navigation (PN) with opioid use disorder (OUD) at 6 months post-release. Three randomized trials (combined N = 330) were combined to assess whether MOUD (extended-release naltrexone or interim methadone) initiated prior to release from jail with or without PN would reduce the likelihood of a DSM-5 diagnosis of OUD 6 months post-release relative to enhanced treatment-as-usual (ETAU). Across the three studies, assignment to MOUD compared to ETAU was not associated with an OUD diagnosis at 6 months post-release (69% vs. 75%, respectively, OR = 0.67, 95% CI: 0.42 to 1.20). Similarly, PN compared to MOUD without PN was not associated with an OUD diagnosis (63% vs 77%, respectively, OR = 0.61, 95% CI: 0.27 to 1.53). Results underscore the need to further optimize the effectiveness of MOUD for patients initiating treatment in jail, beginning with an emphasis on post-release treatment adherence.