Nov 07,2023 TOP STORY

Welldoc Presents Data Showing Use of Digital Health Tool with AI-coaching Leads to Weight Loss and Improved Health Measures, Adding to Over 75 Publications to Date

Welldoc announced data demonstrating that the use of a digital health application in a virtual program for individuals with type 2 diabetes was associated with significant improvements in weight loss, as well as favorable trends in post-meal blood glucose and systolic blood pressure. The data, which were presented as a clinical research poster at the 18th Annual Cardiometabolic Health Congress in Boston, capture the results of a real-world study in which individuals were given access to the Welldoc App, which provides continuous AI-driven digital coaching designed to support self-management behaviors. Data show that the average weight at the endpoint was significantly lower than the baseline, with over 77% of participants losing an average of 4.8% of their baseline body weight. There were also statistically significant improvements in systolic blood pressure and favorable post-meal blood glucose trends. These data demonstrate how overall cardiovascular risk can be reduced in a high-risk population at scale, validating Welldoc’s approach to developing next-generation digital health solutions.

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#mobile app

#coaching

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Nov 07,2023 TOP STORY

Welldoc Presents Data Showing Use of Digital Health Tool with AI-coaching Leads to Weight Loss and Improved Health Measures, Adding to Over 75 Publications to Date

Welldoc announced data demonstrating that the use of a digital health application in a virtual program for individuals with type 2 diabetes was associated with significant improvements in weight loss, as well as favorable trends in post-meal blood glucose and systolic blood pressure. The data, which were presented as a clinical research poster at the 18th Annual Cardiometabolic Health Congress in Boston, capture the results of a real-world study in which individuals were given access to the Welldoc App, which provides continuous AI-driven digital coaching designed to support self-management behaviors. Data show that the average weight at the endpoint was significantly lower than the baseline, with over 77% of participants losing an average of 4.8% of their baseline body weight. There were also statistically significant improvements in systolic blood pressure and favorable post-meal blood glucose trends.

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#mobile app

#coaching

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Nov 01,2023 TOP STORY

Cancer Center Researchers Seek to Harness Wearable Devices to Tailor Medical Treatments

A team of UVA Health researchers has demonstrated the potential of wearable and mobile devices such as smartwatches and smartphones to help doctors tailor treatments to the needs of individual patients. The scientists found that they could use wearable devices to predict patients’ levels of cortisol, the insomnia and stress hormone. Results from their laboratory experiments suggest that patients with pancreatic cancer who have high cortisol levels from disrupted sleep will experience faster growth of their tumors; that suggests that doctors could leverage this information from patients’ mobile devices to help at- risk patients keep their cortisol levels down and, in turn, slow their tumor growth. While the work is still in the early stages, the UVA scientists say their efforts demonstrate the tremendous potential of “mobile sensing” for improving and individualizing cancer care.

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#connected device

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Oct 30,2023

A Digital Therapeutic to Improve Insomnia in Multiple Sclerosis: A Randomized Controlled Trial (NorseMS)

A new randomized controlled trial is registered, aiming to test the effectiveness of digital cognitive behavioral therapy for insomnia (dCBT-I) compared with digital patient education about insomnia for people with Multiple Sclerosis (MS). The main questions it aims to answer are whether dCBT-I is effective in reducing insomnia severity in people with MS, whether dCBT-I is effective in reducing daytime fatigue, psychological distress, cognitive problems, medication use (hypnotic, sedative/anxiolytic and antidepressant), resource utilization and if these changes are mediated by improvements in insomnia severity and whether dCBT-I is feasible for people with MS. The treatment group is designed to receive dCBT-I during 9 weeks including psychoeducation about sleep, sleep hygiene, sleep restriction therapy, stimulus control and challenging beliefs and perception about sleep via Sleep Healthy Using The internet (SHUTi). Teh control group is going be receiving digital patient education about insomnia (PE). The primary outcome measure is between-group difference in insomnia severity at week 9 after randomization assessed with the Insomnia Severity Index (ISI)

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#cbt

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Oct 31,2023

Business vs After-Hours Use of an Artificial Intelligence–Powered Digital Health Platform Among Insured Patients

Digital health programs powered by artificial intelligence (AI) offer patients and clinicians the convenience of accessing and delivering health care services remotely, enabling patients to manage their health from anywhere, at any time. However, there is limited evidence of when patients engage with digital health. This cross-sectional study assessed utilization patterns of a commercially available digital health platform. The primary hypothesis was that members would engage more often with AI-powered coaching after hours than during business hours. This study leveraged data from 79?437 members who participated in 1?464?752 unique coaching sessions from January 2022 to April 2023 on a platform called Lark that offers chronic disease prevention and management programs covered by members’ insurance. They analyzed the percentage of coaching sessions that occurred by hour Monday to Sunday. The findings of this study suggest that many people seek support for prevention and management of their health conditions after standard business hours.

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#mobile app

#coaching

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Oct 30,2023

Acoustic Analysis and Prediction of Type 2 Diabetes Mellitus Using Smartphone-Recorded Voice Segments

The aim of this study is to investigate the potential of voice analysis as a prescreening or monitoring tool for type 2 diabetes mellitus (T2DM) by examining the differences in voice recordings between nondiabetic and T2DM individuals. Total 267 participants diagnosed as nondiabetic (79 women and 113 men) or T2DM (18 women and 57 men) on the basis of American Diabetes Association guidelines were recruited in India between August 30, 2021 and June 30, 2022. Using a smartphone application, participants recorded a fixed phrase up to 6 times daily for 2 weeks, resulting in 18,465 recordings. Fourteen acoustic features were extracted from each recording to analyze differences between nondiabetic and T2DM individuals and create a prediction methodology for T2DM status. Overall, vocal changes were detected in individuals with T2DM compared with those without T2DM. Voice analysis has shown potential as a prescreening or monitoring tool for T2DM, particularly when combined with other risk factors associated with the condition.

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Nov 01,2023

Medical expenditure trajectory and HbA1c progression prior to and after clinical diagnosis of type 2 diabetes in a commercially insured population in the USA

Medical expenditures of individuals with type 2 diabetes escalate before clinical diagnosis. How increases in medical expenditures are related to glucose levels remains unclear. Using insurance claims and laboratory test results from a commercially insured population in the USA, the study researchers built three (2014, 2015, 2016) longitudinal cohorts with type 2 diabetes up to 10 years before and 2 years after the diagnosis (index year). The study included 9847 individuals (83 526 person-years). Medical expenditures and HbA1c levels increased before and peaked at the diagnosis year. Medical expenditures were $8644 lower 10 years and $5781 lower 1 year before diagnosis compared with the index year. HbA1c was 12.18 mmol/mol (1.11 percentage points) and 3.49 mmol/mol (0.32 percentage points) lower, respectively. Medical expenditures and HbA1c values followed similar trajectories before and after diabetes diagnosis. These results can inform economic evaluations of programs and policies aimed at preventing type 2 diabetes.

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Oct 27,2023

Skin Cancer Diagnoses Using AI Are as Reliable as those Made by Medical Experts

Artificial intelligence (AI) is already widely used in medical diagnostics. An Austrian-Australian research team led by dermatologist Harald Kittler from MedUni Vienna investigated the extent to which diagnosis and therapy of pigmented skin lesions benefit from it in a realistic clinical scenario. In a study published by The Lancet Digital Health, the team compared the accuracy in diagnosis and therapy recommendation of two different algorithms in smartphone applications with that of doctors. The results show that the AI application generally performs well in diagnosis. However, doctors were clearly superior when it came to treatment decisions.

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#ai/software

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Oct 26,2023 TOP STORY

First Randomized Controlled Trial Comparing Woebot to Clinician-Led Psychotherapy Reveals Digital Mental Health Intervention is Non-Inferior in Reducing Depressive Symptoms Among Teens

Woebot Health announced positive results from a study at Children’s Hospital of The King’s Daughters (CHKD) showing that the digital mental health intervention W-GenZD, a Woebot-based study app, led to reductions in depressive symptoms that were non-inferior to those achieved by a clinician-led telehealth Cognitive Behavioral Therapy (CBT) skills group. The study was designed to investigate the feasibility, satisfaction and non-inferiority (for PHQ-8) of W-GenZD (n = 71) compared to a group receiving CBT skills delivered via telehealth and led by a licensed mental health clinician (n = 70). Participants in both the W-GenZD and telehealth groups reported a significant reduction in depressive symptoms (PHQ-8) from baseline to end of treatment (week 4) and had similar levels of intervention feasibility and satisfaction. The results were presented in a poster presentation at the American Academy of Child and Adolescent Psychiatry (AACAP) conference.

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#mobile app

#chatbot

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Oct 30,2023

Glucose Monitoring Metrics in Individuals With Type 1 Diabetes Using Different Treatment Modalities: A Real-World Observational Study

A cross-sectional study at Steno Diabetes Center Copenhagen, Denmark, included individuals with type 1 diabetes using CGM, aimed to investigate the association between continuous glucose monitoring (CGM)-derived glycemic metrics and different insulin treatment modalities using real-world data. Data from September 2021 to August 2022 were analyzed if CGM was used for at least 20% of a 4-week period. Individuals were divided into four groups: multiple daily injection (MDI) therapy, insulin pumps with unintegrated CGM (SUP), sensor-augmented pumps with low glucose management (SAP), and automated insulin delivery (AID). The MDI and SUP groups were further subdivided based on CGM alarm features. The primary outcome was percentage of time in range for each treatment group. The proportion of individuals achieving all recommended glycemic targets was significantly higher in SAP and AID compared with MDI without alarm features. Median TIR was 54.0% for MDI, 54.9% for SUP, 62,9% for SAP, and 72,1% for AID users.

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#closed loop

#cgm

#insulin pump

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