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Tag: data collection

AI Plus Mobile App May Help With Smoking Cessation

Article Excerpt: A new artificial intelligence (AI)-powered mobile app can help individuals quit smoking, according to the results of a recent study published in Nicotine & Tobacco Research. The app uses machine learning to collect information on the location, timing, and triggers of past smoking events to curate messages that assist smokers in managing their urges. Prior to this app, there had been no other ways to provide support to help smokers manage social situations and urges after quitting, Felix Naughton, PhD, MSc, a primary researcher and professor of health psychology at the University of East Anglia School of Health Sciences in England, said in a statement.

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Article Source: Pharmacy Times


Augmenting project ECHO for opioid use disorder with data‑informed quality improvement

Murray OB, Doyle M, McLeman BM, Marsch LA, Saunders EC, Cox KM, Watts D, Ryder J. Augmenting project ECHO for opioid use disorder with data-informed quality improvement. Addict Sci Clin Pract 18, 24 (2023).

Learning collaboratives can address barriers to medication for opioid use disorder availability by training clinic staff on best-practice performance data collection and quality improvement (QI). Project ECHO is an evidence-based method using teleconferencing to link experts with community-based providers to enhance opioid use disorder (OUD) care. This study examined the feasibility of training of 18 clinics in New Hampshire using an additional component, ECHO-AMPLIFI, to collect and review performance data and develop QI initiatives for best practice of OUD care. Feasibility was assessed descriptively through each clinic’s participation in training sessions, data collection, and QI initiatives. At the end of the project, clinic staff completed surveys on their perspectives of usability and acceptability of the project. Five of the 18 clinics joined the ECHO-AMPLIFI project for 8 months and met the minimum engagement requirements (completed at least one training session, at least one month of performance data, and at least one QI initiative). Results from staff surveys showed the training and data collection was useful. However, there were several problems identified with data collection, including lack of staff time and lack of standardization of documentation in electronic health records. Findings indicate that implementing performance data-informed QI as a supplement to Project ECHO has potential to inform best practices, but challenges to collecting consistent performance data must be addressed. Future assessments could provide further information on the utility of performance data in helping clinics.


Can Machine Learning, Wearable Tech Help Treat Mental Health?

Article Excerpt: New research from the Icahn School of Medicine at Mount Sinai in New York indicated that using Apple Watch data, such as heart rate variability and resting heart rate, could assist in training machine learning models to determine patient well-being and resilience. According to the Centers for Disease Control and Prevention (CDC), over 20 percent of US adults have a mental illness. The CDC also noted that mental health diagnoses are some of the most common health conditions in the US. This latest study showed that wearable devices could help support patients with mental health diagnoses by collecting assistive data.

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Article Source: Health IT Analytics


ChatGPT Gets Dartmouth Talking

Article Excerpt: ChatGPT, OpenAI’s trending chatbot that generates conversational responses to user prompts through advanced artificial intelligence, has been busy since its launch in late November… “ChatGPT and other generative AI technologies have huge potential for—and will have huge effects on—education,” says Provost David Kotz ’86, the Pat and John Rosenwald Professor in the Department of Computer Science. “My hope is to provide immediate support to faculty and instructors to become familiar with the technology and its impacts, and then look further down the road to consider how we can leverage it as a pedagogical tool, recognizing that it will be part of the future of teaching, learning, scholarship, and work.”

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Article Source: Dartmouth News


‘There’s a Sense of Urgency’: How Wearables Could Reshape Addiction Treatment

Article Excerpt: Wearables offer addiction treatment providers tantalizing opportunities to improve care outcomes. Increasingly sophisticated devices are now available at affordable price points. Effortless data collection opens the door to more objectivity in a highly subjective field. But there’s a serious problem. Researchers and practitioners still need to figure out what to do with the mountains of data that wearables could produce.

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Article Source: Behavioral Health Business


Are Wearables Helpful for Dying Patients?

Article Excerpt: A 2019 study found that health tech wearables may improve the outpatient monitoring of cancer patients. The device could detect a decline in a patient’s condition and send the data to a doctor, catching the issue much earlier than the typical trip to the emergency department. This early catch supports patient comfort and reduces costly readmissions for the patient and the health system. Data collection could also improve telehealth visits by recording vital signs and other assessment data before or during appointments.

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Article Source: Health News


Mobile App–Based Self-Report Questionnaires for the Assessment and Monitoring of Bipolar Disorder: Systematic Review

Chan E, Sun Y, Aitchison K, Sivapalan S. Mobile App–Based Self-Report Questionnaires for the Assessment and Monitoring of Bipolar Disorder: Systematic Review. JMIR Form Res 2021;5(1):e13770 DOI: 10.2196/13770

to determine the state of evidence for feasibility and validity of mobile app-based self-report questionnaires as tools for monitoring of bipolar symptoms. All papers published in English that assessed adherence to and validity of mobile app-based self-report surveys for monitoring patients with bipolar disorder were included. A total of 13 articles were identified. Four studies assessed the concurrent validity of mobile self-report tools and all 4 found a statistically significant association between mood ratings collected via mobile app self-report and clinical assessment using the Hamilton Depression Rating Scale or Montgomery-Asberg Depression Rating Scale. . Two studies observed statistically significant associations between data collected via mobile app self-report tools and instruments assessing clinically- related factors. Satisfactory adherence rates (at least 70%) were observed in all but 1 study that used a once-daily assessment. There was a wide range of adherence rates in studies using twice-daily assessments (42-95%). Overall, the review demonstrated that mobile app-based self-report instruments are valid relative to established assessment methods for measuring symptoms of mania and depression in patients with bipolar disorder. Future research is needed to evaluate feasibility of mobile self-report methods for identifying acute episodes and to inform insights into differences between patients with bipolar disorder and those without lived experience of this condition.


Leveraging Data From Wearable Medical Devices

Article Excerpt: Diabetes, and other chronic conditions like cancer or cardiovascular disease, require a lifetime of management. In recent years, a slew of wearable devices such as glucose monitors, activity trackers, heart rate monitors, and pulse oximeters have been adopted by patients and health care providers to track and manage these conditions more effectively. These devices are also a rich source of data that can be analyzed to better understand the factors and behaviors that lead to improved health outcomes. “But they’re vastly underutilized,” says Temiloluwa Prioleau, assistant professor of computer science and co-director of the Augmented Health Lab, which is focused on bridging this gap.

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Article Source: Dartmouth News


In the US, A New Approach to Counting Overdoses

Article Excerpt: Accessing overdose data is particularly tricky in Texas, although a dearth of timely and complete numbers is also a problem in many other states. Often, the data isn’t updated in real time, nor does it include non-fatal overdoses. There may also be inconsistencies in how the deaths are reported. To change that, researchers across the United States have been setting up new digital platforms with reports from people who use drugs, medical examiners, and others. While these platforms may lack the rigor of official government numbers, the academics say the new data could tell Project Vida and programs like it where to focus efforts — and, they argue, could save lives.

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Article Source: GCN