Discontinuing semaglutide after weight loss: strategy for weight maintenance and a possible new side effect.

Glucagon-like peptide-1 receptor agonists (GLP-1 RAs) facilitate weight loss. Weight regain off therapy is concerning. We reported the case of a 35-year-old male prescribed oral semaglutide with 22.7 kg weight loss over 120 days. Herein, we describe the clinical course when discontinuing GLP-1 RA therapy, one approach to maintaining weight loss after discontinuation, and a possible new side effect. At day 120, we continued oral semaglutide 7 mg daily, down from 14 mg, for weight maintenance with subsequent weight regain. We re-increased semaglutide to 14 mg/day with weight re-loss within 1 month and weight maintance for a year. We then discontinued semaglutide; weight loss was maintained for 6 months. The patient reported lactose intolerance ∼13 months before starting semaglutide. During semaglutide therapy, the patient reported worsened lactose intolerance and new gluten intolerance. Food allergy/celiac testing were negative. Intolerances did not improve with semaglutide discontinuation. Six months after semaglutide discontinuation, the patient was diagnosed with small intestinal bacterial overgrowth, possibly worsened by semaglutide. Factors potentially supporting weight maintenance were early drug treatment for new-onset obesity, non-geriatric age, strength training, and diet modification. The case highlights tailoring approaches to maintain weight loss without GLP-1 RAs. Trials are needed to optimize weight maintenance strategies.

Travel Distance Between Participants in US Telemedicine Sessions With Estimates of Emissions Savings: Observational Study.

BACKGROUND: Digital health and telemedicine are potentially important strategies to decrease health care's environmental impact and contribution to climate change by reducing transportation-related air pollution and greenhouse gas emissions. However, we currently lack robust national estimates of emissions savings attributable to telemedicine. OBJECTIVE: This study aimed to (1) determine the travel distance between participants in US telemedicine sessions and (2) estimate the net reduction in carbon dioxide (CO2) emissions attributable to telemedicine in the United States, based on national observational data describing the geographical characteristics of telemedicine session participants. METHODS: We conducted a retrospective observational study of telemedicine sessions in the United States between January 1, 2022, and February 21, 2023, on the doxy.me platform. Using Google Distance Matrix, we determined the median travel distance between participating providers and patients for a proportional sample of sessions. Further, based on the best available public data, we estimated the total annual emissions costs and savings attributable to telemedicine in the United States. RESULTS: The median round trip travel distance between patients and providers was 49 (IQR 21-145) miles. The median CO2 emissions savings per telemedicine session was 20 (IQR 8-59) kg CO2). Accounting for the energy costs of telemedicine and US transportation patterns, among other factors, we estimate that the use of telemedicine in the United States during the years 2021-2022 resulted in approximate annual CO2 emissions savings of 1,443,800 metric tons. CONCLUSIONS: These estimates of travel distance and telemedicine-associated CO2 emissions costs and savings, based on national data, indicate that telemedicine may be an important strategy in reducing the health care sector's carbon footprint.

Will the United States pass on telemedicine progress?

Background: During the COVID-19 pandemic, federal and state health policies allowed temporary flexibilities for Medicare and Medicaid beneficiaries, leading to a sharp increase in telemedicine use. However, many of the flexibilities that enabled innovation and growth in telemedicine continue temporarily since the federal emergency declaration ended in May 2023, and the United States has not made permanent decisions about telemedicine policy. Analysts have raised concerns about increased spending, program integrity, safety, and equity, and recommend strengthening oversight. Methods: Here, we argue that we must continue the flexibilities to better understand telemedicine's quality, safety, and outcomes, and until the United States can develop an evidence-based digital health strategy. A premature regression to pre-pandemic telemedicine policies risks unintended consequences. Conclusion: We must continue the current policy flexibilities, safeguard against fraud and abuse, and immediately prioritize research and evaluation of telemedicine's quality, safety, and outcomes, to avoid unintended consequences and support more permanent policy decision-making.

User Preferences and Needs for Health Data Collection Using Research Electronic Data Capture: Survey Study.

BACKGROUND: Self-administered web-based questionnaires are widely used to collect health data from patients and clinical research participants. REDCap (Research Electronic Data Capture; Vanderbilt University) is a global, secure web application for building and managing electronic data capture. Unfortunately, stakeholder needs and preferences of electronic data collection via REDCap have rarely been studied. OBJECTIVE: This study aims to survey REDCap researchers and administrators to assess their experience with REDCap, especially their perspectives on the advantages, challenges, and suggestions for the enhancement of REDCap as a data collection tool. METHODS: We conducted a web-based survey with representatives of REDCap member organizations in the United States. The survey captured information on respondent demographics, quality of patient-reported data collected via REDCap, patient experience of data collection with REDCap, and open-ended questions focusing on the advantages, challenges, and suggestions to enhance REDCap's data collection experience. Descriptive and inferential analysis measures were used to analyze quantitative data. Thematic analysis was used to analyze open-ended responses focusing on the advantages, disadvantages, and enhancements in data collection experience. RESULTS: A total of 207 respondents completed the survey. Respondents strongly agreed or agreed that the data collected via REDCap are accurate (188/207, 90.8%), reliable (182/207, 87.9%), and complete (166/207, 80.2%). More than half of respondents strongly agreed or agreed that patients find REDCap easy to use (165/207, 79.7%), could successfully complete tasks without help (151/207, 72.9%), and could do so in a timely manner (163/207, 78.7%). Thematic analysis of open-ended responses yielded 8 major themes: survey development, user experience, survey distribution, survey results, training and support, technology, security, and platform features. The user experience category included more than half of the advantage codes (307/594, 51.7% of codes); meanwhile, respondents reported higher challenges in survey development (169/516, 32.8% of codes), also suggesting the highest enhancement suggestions for the category (162/439, 36.9% of codes). CONCLUSIONS: Respondents indicated that REDCap is a valued, low-cost, secure resource for clinical research data collection. REDCap's data collection experience was generally positive among clinical research and care staff members and patients. However, with the advancements in data collection technologies and the availability of modern, intuitive, and mobile-friendly data collection interfaces, there is a critical opportunity to enhance the REDCap experience to meet the needs of researchers and patients.

Telemedicine appointments are more likely to be completed than in-person healthcare appointments: a retrospective cohort study.

Objectives: Missed appointments can lead to treatment delays and adverse outcomes. Telemedicine may improve appointment completion because it addresses barriers to in-person visits, such as childcare and transportation. This study compared appointment completion for appointments using telemedicine versus in-person care in a large cohort of patients at an urban academic health sciences center. Materials and Methods: We conducted a retrospective cohort study of electronic health record data to determine whether telemedicine appointments have higher odds of completion compared to in-person care appointments, January 1, 2021, and April 30, 2023. The data were obtained from the University of South Florida (USF), a large academic health sciences center serving Tampa, FL, and surrounding communities. We implemented 1:1 propensity score matching based on age, gender, race, visit type, and Charlson Comorbidity Index (CCI). Results: The matched cohort included 87 376 appointments, with diverse patient demographics. The percentage of completed telemedicine appointments exceeded that of completed in-person care appointments by 9.2 points (73.4% vs 64.2%, P < .001). The adjusted odds ratio for telemedicine versus in-person care in relation to appointment completion was 1.64 (95% CI, 1.59-1.69, P < .001), indicating that telemedicine appointments are associated with 64% higher odds of completion than in-person care appointments when controlling for other factors. Discussion: This cohort study indicated that telemedicine appointments are more likely to be completed than in-person care appointments, regardless of demographics, comorbidity, payment type, or distance. Conclusion: Telemedicine appointments are more likely to be completed than in-person healthcare appointments.

Narrative review of telemedicine applications in decentralized research.

Telemedicine enables critical human communication and interaction between researchers and participants in decentralized research studies. There is a need to better understand the overall scope of telemedicine applications in clinical research as the basis for further research. This narrative, nonsystematic review of the literature sought to review and discuss applications of telemedicine, in the form of synchronous videoconferencing, in clinical research. We searched PubMed to identify relevant literature published between January 1, 2013, and June 30, 2023. Two independent screeners assessed titles and abstracts for inclusion, followed by single-reviewer full-text screening, and we organized the literature into core themes through consensus discussion. We screened 1044 publications for inclusion. Forty-eight publications met our inclusion and exclusion criteria. We identified six core themes to serve as the structure for the narrative review: infrastructure and training, recruitment, informed consent, assessment, monitoring, and engagement. Telemedicine applications span all stages of clinical research from initial planning and recruitment to informed consent and data collection. While the evidence base for using telemedicine in clinical research is not well-developed, existing evidence suggests that telemedicine is a potentially powerful tool in clinical research.

A Reproducible Model Based on Clinical Text for Predicting Suicidal Behavior.

Suicide risk models are critical for prioritizing patients for intervention. We demonstrate a reproducible approach for training text classifiers to identify patients at risk. The models were effective in phenotyping suicidal behavior (F1=.94) and moderately effective in predicting future events (F1=.63).

User experience of a family health history chatbot: A quantitative analysis.

OBJECTIVE: Family health history (FHx) is an important tool in assessing one's risk towards specific health conditions. However, user experience of FHx collection tools is rarely studied. ItRunsInMyFamily.com (ItRuns) was developed to assess FHx and hereditary cancer risk. This study reports a quantitative user experience analysis of ItRuns. METHODS: We conducted a public health campaign in November 2019 to promote FHx collection using ItRuns. We used software telemetry to quantify abandonment and time spent on ItRuns to identify user behaviors and potential areas of improvement. RESULTS: Of 11,065 users who started the ItRuns assessment, 4305 (38.91%) reached the final step to receive recommendations about hereditary cancer risk. Highest abandonment rates were during Introduction (32.82%), Invite Friends (29.03%), and Family Cancer History (12.03%) subflows. Median time to complete the assessment was 636 s. Users spent the highest median time on Proband Cancer History (124.00 s) and Family Cancer History (119.00 s) subflows. Search list questions took the longest to complete (median 19.50 s), followed by free text email input (15.00 s). CONCLUSION: Knowledge of objective user behaviors at a large scale and factors impacting optimal user experience will help enhance the ItRuns workflow and improve future FHx collection.

Decentralized research technology use in multicenter clinical research studies based at U.S. academic research centers.

Introduction: During the COVID-19 pandemic, research organizations accelerated adoption of technologies that enable remote participation. Now, there's a pressing need to evaluate current decentralization practices and develop appropriate research, education, and operations infrastructure. The purpose of this study was to examine current adoption of decentralization technologies in a sample of clinical research studies conducted by academic research organizations (AROs). Methods: The setting was three data coordinating centers in the U.S. These centers initiated coordination of 44 clinical research studies during or after 2020, with national recruitment and enrollment, and entailing coordination between one and one hundred sites. We determined the decentralization technologies used in these studies. Results: We obtained data for 44/44 (100%) trials coordinated by the three centers. Three technologies have been adopted across nearly all studies (98-100%): eIRB, eSource, and Clinical Trial Management Systems. Commonly used technologies included e-Signature (32/44, 73%), Online Payments Portals (26/44, 59%), ePROs (23/44, 53%), Interactive Response Technology (22/44, 50%), Telemedicine (19/44, 43%), and eConsent (18/44, 41%). Wearables (7/44,16%) and Online Recruitment Portals (5/44,11%) were less common. Rarely utilized technologies included Direct-to-Patient Portals (1/44, 2%) and Home Health Nurse Portals (1/44, 2%). Conclusions: All studies incorporated some type of decentralization technology, with more extensive adoption than found in previous research. However, adoption may be strongly influenced by institution-specific IT and informatics infrastructure and support. There are inherent needs, responsibilities, and challenges when incorporating decentralization technology into a research study, and AROs must ensure that infrastructure and informatics staff are adequate.