A qualitative evaluation of an operational research course for acute care trainees in Kigali, Rwanda

Introduction: the blended SORT-IT model uses a combination of online modules and teleconferences with local and international mentors to teach operational research. We modified SORT-IT to create the Acute Care Operational Research (ACOR) course directed to anesthesiology residents in Kigali, Rwanda. This course takes students from an initial research idea through submitting a paper for publication. Our viewpoint on entering this study was that ACOR participants would have adequate resources to complete the course, but be hampered by cultural unfamiliarity with the blended teaching approach. Methods: we conducted a qualitative analysis of the experiences of all those who participated in the ACOR course to understand obstacles and improve future course iterations. Six anesthesiology residents participated in the first iteration of the course, with 4 local mentors and 2 secondary mentors, one of whom was based at the University of Virginia, with a total of 12 participants. Semi-structured interviews were conducted with all participants and mentors, which were independently coded for topics by two reviewers. Results: there was a 50% publication rate for those enrolled in the course and an expected 100% acceptance rate for those who completed the course. Some reported benefits to the course included improved research knowledge, societal improvements, and knowledge exchange. Some reported obstacles to successful course completion included time limitations, background knowledge, and communication. Of note, only 4 out of 12 participants recognized cultural barriers. Conclusion: although successful in the sense that all participants completed their research project, ACOR did not fully solve the main issues hindering research training. Our results show that research training in low-resource settings needs a continuing and formal focus on the factors that hinder participants´ success: mentorship and time

Exploring the Use of Wearable Sensors and Natural Language Processing Technology to Improve Patient-Clinician Communication: Protocol for a Feasibility Study

BackgroundEffective communication is the bedrock of quality health care, but it continues to be a major problem for patients, family caregivers, health care providers, and organizations. Although progress related to communication skills training for health care providers has been made, clinical practice and research gaps persist, particularly regarding how to best monitor, measure, and evaluate the implementation of communication skills in the actual clinical setting and provide timely feedback about communication effectiveness and quality. ObjectiveOur interdisciplinary team of investigators aims to develop, and pilot test, a novel sensing system and associated natural language processing algorithms (CommSense) that can (1) be used on mobile devices, such as smartwatches; (2) reliably capture patient-clinician interactions in a clinical setting; and (3) process these communications to extract key markers of communication effectiveness and quality. The long-term goal of this research is to use CommSense in a variety of health care contexts to provide real-time feedback to end users to improve communication and patient health outcomes. MethodsThis is a 1-year pilot study. During Phase I (Aim 1), we will identify feasible metrics of communication to extract from conversations using CommSense. To achieve this, clinical investigators will conduct a thorough review of the recent health care communication and palliative care literature to develop an evidence-based “ideal and optimal” list of communication metrics. This list will be discussed collaboratively within the study team and consensus will be reached regarding the included items. In Phase II (Aim 2), we will develop the CommSense software by sharing the “ideal and optimal” list of communication metrics with engineering investigators to gauge technical feasibility. CommSense will build upon prior work using an existing Android smartwatch platform (SWear) and will include sensing modules that can collect (1) physiological metrics via embedded sensors to measure markers of stress (eg, heart rate variability), (2) gesture data via embedded accelerometer and gyroscope sensors, and (3) voice and ultimately textual features via the embedded microphone. In Phase III (Aim 3), we will pilot test the ability of CommSense to accurately extract identified communication metrics using simulated clinical scenarios with nurse and physician participants. ResultsDevelopment of the CommSense platform began in November 2021, with participant recruitment expected to begin in summer 2022. We anticipate that preliminary results will be available in fall 2022. ConclusionsCommSense is poised to make a valuable contribution to communication science, ubiquitous computing technologies, and natural language processing. We are particularly eager to explore the ability of CommSense to support effective virtual and remote health care interactions and reduce disparities related to patient-clinician communication in the context of serious illness. International Registered Report Identifier (IRRID)PRR1-10.2196/3797

Evaluation of the Implementation and Effectiveness of a Mobile Health Intervention to Improve Outcomes for People With HIV in the Washington, DC Cohort: Study Protocol for a Cluster Randomized Controlled Trial

BACKGROUND: Gaps remain in achieving retention in care and durable HIV viral load suppression for people with HIV in Washington, DC (hereafter DC). Although people with HIV seeking care in DC have access to a range of supportive services, innovative strategies are needed to enhance patient engagement in this setting. Mobile health (mHealth) interventions have shown promise in reaching previously underengaged groups and improving HIV-related outcomes in various settings. OBJECTIVE: This study will evaluate the implementation and effectiveness of a clinic-deployed, multifeature mHealth intervention called PositiveLinks (PL) among people with HIV enrolled in the DC Cohort, a longitudinal cohort of people with HIV receiving care in DC. A cluster randomized controlled trial will be conducted using a hybrid effectiveness-implementation design and will compare HIV-related outcomes between clinics randomized to PL versus usual care. METHODS: The study aims are threefold: (1) We will perform a formative evaluation of PL in the context of DC Cohort clinics to test the feasibility, acceptability, and usability of PL and tailor the platform for use in this context. (2) We will conduct a cluster randomized controlled trial with 12 DC Cohort clinics randomized to PL or usual care (n=6 [50%] per arm) and measure the effectiveness of PL by the primary outcomes of patient visit constancy, retention in care, and HIV viral load suppression. We aim to enroll a total of 482 participants from DC Cohort clinic sites, specifically including people with HIV who show evidence of inconsistent retention in care or lack of viral suppression. (3) We will use the Consolidated Framework for Implementation Research (CFIR) and the Reach Effectiveness Adoption Implementation Maintenance (RE-AIM) framework to measure implementation success and identify site, patient, provider, and system factors associated with successful implementation. Evaluation activities will occur pre-, mid-, and postimplementation. RESULTS: Formative data collection was completed between April 2021 and January 2022. Preliminary mHealth platform modifications have been performed, and the first round of user testing has been completed. A preimplementation evaluation was performed to identify relevant implementation outcomes and design a suite of instruments to guide data collection for evaluation of PL implementation throughout the trial period. Instruments include those already developed to support DC Cohort Study activities and PL implementation in other cohorts, which required modification for use in the study, as well as novel instruments designed to complete data collection, as guided by the CFIR and RE-AIM frameworks. CONCLUSIONS: Formative and preimplementation evaluations will be completed in spring 2022 when the trial is planned to launch. Specifically, comprehensive formative data analysis will be completed following data collection, coding, preliminary review, and synthesis. Corresponding platform modifications are ready for beta testing within the DC Cohort. Finalization of the platform for use in the trial will follow beta testing. TRIAL REGISTRATION: ClinicalTrials.gov NCT04998019; https://clinicaltrials.gov/ct2/show/NCT04998019. INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID): PRR1-10.2196/37748

An mHealth Platform for People With HIV Receiving Care in Washington, District of Columbia: Qualitative Analysis of Stakeholder Feedback

BackgroundHIV viral suppression and retention in care continue to be challenging goals for people with HIV in Washington, District of Columbia (DC). The PositiveLinks mobile app is associated with increased retention in care and viral load suppression in nonurban settings. The app includes features such as daily medication reminders, mood and stress check-ins, an anonymized community board for peer-to-peer social support, secure messaging to care teams, and resources for general and clinic-specific information, among other features. PositiveLinks has not been tailored or tested for this distinct urban population of people with HIV. ObjectiveThis study aimed to inform the tailoring of a mobile health app to the needs of people with HIV and their providers in Washington, DC. MethodsWe conducted a 3-part formative study to guide the tailoring of PositiveLinks for patients in the DC Cohort, a longitudinal cohort of >12,000 people with HIV receiving care in Washington, DC. The study included in-depth interviews with providers (n=28) at study clinics, focus groups with people with HIV enrolled in the DC Cohort (n=32), and a focus group with members of the DC Regional Planning Commission on Health and HIV (COHAH; n=35). Qualitative analysis used a constant comparison iterative approach; thematic saturation and intercoder agreement were achieved. Emerging themes were identified and grouped to inform an adaptation of PositiveLinks tailored for patients and providers. ResultsEmerging themes for patients, clinic providers, and COHAH providers included population needs and concerns, facilitators and barriers to engagement in care and viral suppression, technology use, anticipated benefits, questions and concerns, and suggestions. DC Cohort clinic and COHAH provider interviews generated an additional theme: clinic processes. For patients, the most commonly discussed potential benefits included improved health knowledge and literacy (mentioned n=10 times), self-monitoring (n=7 times), and connection to peers (n=6 times). For providers, the most common anticipated benefits were improved communication with the clinic team (n=21), connection to peers (n=14), and facilitation of self-monitoring (n=11). Following data review, site principal investigators selected core PositiveLinks features, including daily medication adherence, mood and stress check-ins, resources, frequently asked questions, and the community board. Principal investigators wanted English and Spanish versions depending on the site. Two additional app features (messaging and documents) were selected as optional for each clinic site. Overall, 3 features were not deployed as not all participating clinics supported them. ConclusionsPatient and provider perspectives of PositiveLinks had some overlap, but some themes were unique to each group. Beta testing of the tailored app was conducted (August 2022). This formative work prepared the team for a cluster randomized controlled trial of PositiveLinks’ efficacy. Randomization of clinics to PositiveLinks or usual care occurred in August 2022, and the randomized controlled trial launched in November 2022. International Registered Report Identifier (IRRID)RR2-10.2196/3774

Six-month outcomes of the HOPE smartphone application designed to support treatment with medications for opioid use disorder and piloted during an early statewide COVID-19 lockdown

Abstract Background Morbidity and mortality related to opioid use disorder (OUD) in the U.S. is at an all-time high. Innovative approaches are needed to address gaps in retention in treatment with medications for opioid use disorder (MOUD). Mobile health (mHealth) approaches have shown improvement in engagement in care and associated clinical outcomes for a variety of chronic diseases, but mHealth tools designed specifically to support patients treated with MOUD are limited. Methods Following user-centered development and testing phases, a multi-feature smartphone application called HOPE (Heal. Overcome. Persist. Endure) was piloted in a small cohort of patients receiving MOUD and at high risk of disengagement in care at an office-based opioid treatment (OBOT) clinic in Central Virginia. Outcomes were tracked over a six-month period following patient enrollment. They included retention in care at the OBOT clinic, usage of various features of the application, and self-rated measures of mental health, substance use, treatment and recovery. Results Of the 25 participants in the HOPE pilot study, a majority were retained in care at 6 months (56%). Uptake of bi-directional features including messaging with providers and daily check-ins of mood, stress and medication adherence peaked at one month, and usage persisted through the sixth month. Patients who reported that distance to clinic was a problem at baseline had higher loss to follow up compared to those without distance as a reported barrier (67% vs 23%, p = 0.03). Patients lost to in-person clinic follow up continued to engage with one or more app features, indicating that mHealth approaches may bridge barriers to clinic visit attendance. Participants surveyed at baseline and 6 months (N = 16) scored higher on scales related to overall self-control and self-efficacy related to drug abstinence. Conclusions A pilot study of a novel multi-feature smartphone application to support OUD treatment showed acceptable retention in care and patient usage at 6 months. Further study within a larger population is needed to characterize ‘real world’ uptake and association with outcomes related to retention in care, relapse prevention, and opioid-associated mortality.http://deepblue.lib.umich.edu/bitstream/2027.42/173961/1/13722_2022_Article_296.pd