Mayo Clinic Proceedings. Digital health最新文献

{"title":"Embedding Internal Accountability Into Health Care Institutions for Safe, Effective, and Ethical Implementation of Artificial Intelligence Into Medical Practice: A Mayo Clinic Case Study","authors":"Brenna Loufek MS ,&nbsp;David Vidal JD ,&nbsp;David S. McClintock MD ,&nbsp;Mark Lifson PhD ,&nbsp;Eric Williamson MD ,&nbsp;Shauna Overgaard PhD ,&nbsp;Kathleen McNaughton JD ,&nbsp;Melissa C. Lipford MD ,&nbsp;Darrell S. Pardi MD","doi":"10.1016/j.mcpdig.2024.08.008","DOIUrl":"10.1016/j.mcpdig.2024.08.008","url":null,"abstract":"<div><div>Health care organizations are building, deploying, and self-governing digital health technologies (DHTs), including artificial intelligence, at an increasing rate. This scope necessitates expertise and quality infrastructure to ensure that the technology impacting patient care is safe, effective, and ethical throughout its lifecycle. The objective of this article is to describe Mayo Clinic’s approach for embedding internal accountability as a case study for other health care institutions seeking modalities for responsible implementation of artificial intelligence–enabled DHTs. Mayo Clinic aims to enable and empower innovators by (1) building internal skills and expertise, (2) establishing a centralized review board, and (3) aligning development and deployment processes with regulations, standards, and best practices. In 2022, Mayo Clinic established the Software as a Medical Device Review Board (The Board), an independent body of physicians and domain experts to represent the organization in providing innovators regulatory and risk mitigation recommendations for DHTs. Hundreds of digital health product teams have since benefited from this function, intended to enable responsible innovation in alignment with regulation and state-of-the-art quality management practices. Other health care institutions can adopt similar internal accountability bodies using this framework. Opportunity remains to iterate on Mayo Clinic’s approach in alignment with advancing best practices and enhance representation on The Board as part of standard continuous improvement practices.</div></div>","PeriodicalId":74127,"journal":{"name":"Mayo Clinic Proceedings. Digital health","volume":"2 4","pages":"Pages 574-583"},"PeriodicalIF":0.0,"publicationDate":"2024-09-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142419546","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Echocardiographic Diagnosis of Hypertrophic Cardiomyopathy by Machine Learning","authors":"Nasibeh Zanjirani Farahani PhD ,&nbsp;Mateo Alzate Aguirre MD ,&nbsp;Vanessa Karlinski Vizentin MD ,&nbsp;Moein Enayati PhD ,&nbsp;J. Martijn Bos MD, PhD ,&nbsp;Andredi Pumarejo Medina MD ,&nbsp;Kathryn F. Larson MD ,&nbsp;Kalyan S. Pasupathy PhD ,&nbsp;Christopher G. Scott MS ,&nbsp;April L. Zacher MS ,&nbsp;Eduard Schlechtinger MS ,&nbsp;Bruce K. Daniels RDCS ,&nbsp;Vinod C. Kaggal MS ,&nbsp;Jeffrey B. Geske MD ,&nbsp;Patricia A. Pellikka MD ,&nbsp;Jae K. Oh MD ,&nbsp;Steve R. Ommen MD ,&nbsp;Garvan C. Kane MD ,&nbsp;Michael J. Ackerman MD, PhD ,&nbsp;Adelaide M. Arruda-Olson MD, PhD","doi":"10.1016/j.mcpdig.2024.08.009","DOIUrl":"10.1016/j.mcpdig.2024.08.009","url":null,"abstract":"<div><h3>Objective</h3><div>To develop machine learning tools for automated hypertrophic cardiomyopathy (HCM) case recognition from echocardiographic metrics, aiming to identify HCM from standard echocardiographic data with high performance.</div></div><div><h3>Patients and Methods</h3><div>Four different random forest machine learning models were developed using a case-control cohort composed of 5548 patients with HCM and 16,973 controls without HCM, from January 1, 2004, to March 15, 2019. Each patient with HCM was matched to 3 controls by sex, age, and year of echocardiography. Ten-fold crossvalidation was used to train the models to identify HCM. Variables included in the models were demographic characteristics (age, sex, and body surface area) and 16 standard echocardiographic metrics.</div></div><div><h3>Results</h3><div>The models were differentiated by global, average, individual, or no strain measurements. Area under the receiver operating characteristic curves (area under the curve) ranged from 0.92 to 0.98 for the 4 separate models. Area under the curves of model 2 (using left ventricular global longitudinal strain; 0.97; 95% CI, 0.95-0.98), 3 (using averaged strain; 0.96; 95% CI, 0.94-0.97), and 4 (using 17 individual strains per patient; 0.98; 95% CI, 0.97-0.99) had comparable performance. By comparison, model 1 (no strain data; 0.92; 95% CI, 0.90-0.94) had an inferior area under the curve.</div></div><div><h3>Conclusion</h3><div>Machine learning tools that analyze echocardiographic metrics identified HCM cases with high performance. Detection of HCM cases improved when strain data was combined with standard echocardiographic metrics.</div></div>","PeriodicalId":74127,"journal":{"name":"Mayo Clinic Proceedings. Digital health","volume":"2 4","pages":"Pages 564-573"},"PeriodicalIF":0.0,"publicationDate":"2024-09-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142419545","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Transforming Large Language Models into Superior Clinical Decision Support Tools by Embedding Clinical Practice Guidelines","authors":"Yanshan Wang PhD ,&nbsp;Xiaoxi Yao PhD, MPH ,&nbsp;Xizhi Wu","doi":"10.1016/j.mcpdig.2024.05.018","DOIUrl":"10.1016/j.mcpdig.2024.05.018","url":null,"abstract":"","PeriodicalId":74127,"journal":{"name":"Mayo Clinic Proceedings. Digital health","volume":"2 3","pages":"Pages 491-492"},"PeriodicalIF":0.0,"publicationDate":"2024-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.sciencedirect.com/science/article/pii/S2949761224000531/pdfft?md5=1fdf44c4e47001acd445c32b0cc3c93b&pid=1-s2.0-S2949761224000531-main.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142239433","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Validating a Portable, Camera-Based System to Scale the Clinical Gait Assessment as a Tele-Health Solution","authors":"Kevin A. Mazurek Ph.D. ,&nbsp;Leland Barnard Ph.D. ,&nbsp;Hugo Botha M.B., Ch.B. ,&nbsp;Teresa Christianson ,&nbsp;Jonathan Graff-Radford M.D. ,&nbsp;David T. Jones M.D. ,&nbsp;David S. Knopman M.D. ,&nbsp;Ronald C. Petersen M.D., Ph.D. ,&nbsp;Prashanthi Vemuri Ph.D. ,&nbsp;Clifford R. Jack Jr. M.D. ,&nbsp;Farwa Ali M.B.B.S.","doi":"10.1016/j.mcpdig.2024.05.020","DOIUrl":"10.1016/j.mcpdig.2024.05.020","url":null,"abstract":"","PeriodicalId":74127,"journal":{"name":"Mayo Clinic Proceedings. Digital health","volume":"2 3","pages":"Page 491"},"PeriodicalIF":0.0,"publicationDate":"2024-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.sciencedirect.com/science/article/pii/S2949761224000555/pdfft?md5=228cc31f76fd54738eca72fe1a0edf54&pid=1-s2.0-S2949761224000555-main.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142239432","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"The Proceedings of the Inaugural Mayo Clinic Digital Health Research Symposium","authors":"Bart M. Demaerschalk MD, MSc,&nbsp;Barbara J. Copeland,&nbsp;Christopher M. Wittich MD","doi":"10.1016/j.mcpdig.2024.05.011","DOIUrl":"10.1016/j.mcpdig.2024.05.011","url":null,"abstract":"","PeriodicalId":74127,"journal":{"name":"Mayo Clinic Proceedings. Digital health","volume":"2 3","pages":"Pages 486-487"},"PeriodicalIF":0.0,"publicationDate":"2024-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.sciencedirect.com/science/article/pii/S2949761224000464/pdfft?md5=aa64aa27223f9a9164c21934b1927c7a&pid=1-s2.0-S2949761224000464-main.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142239174","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Utilization of Emergency Medicine Telehealth Support for Pediatric Patients in Community Emergency Departments","authors":"Elizabeth C. Fogelson MD ,&nbsp;Jacob A. Klinger ,&nbsp;Aidan F. Mullan MS ,&nbsp;David M. Nestler MD MS ,&nbsp;M. Fernanda Bellolio MD MS ,&nbsp;Laura E. Walker MD MBA","doi":"10.1016/j.mcpdig.2024.05.021","DOIUrl":"10.1016/j.mcpdig.2024.05.021","url":null,"abstract":"","PeriodicalId":74127,"journal":{"name":"Mayo Clinic Proceedings. Digital health","volume":"2 3","pages":"Pages 494-495"},"PeriodicalIF":0.0,"publicationDate":"2024-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.sciencedirect.com/science/article/pii/S2949761224000567/pdfft?md5=7a84a2d68b4b70134e1b6792719afe35&pid=1-s2.0-S2949761224000567-main.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142238281","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Impact of an Automated Digital Navigation Program on Colonoscopy No-Show Rates: A Study in an Underserved Population","authors":"Morish Shah B.S. ,&nbsp;Shashank Garg M.S. ,&nbsp;Sarthak Kakkar M.S. ,&nbsp;Dr. Ashish Atreja M.D., M.P.H.","doi":"10.1016/j.mcpdig.2024.05.019","DOIUrl":"10.1016/j.mcpdig.2024.05.019","url":null,"abstract":"","PeriodicalId":74127,"journal":{"name":"Mayo Clinic Proceedings. Digital health","volume":"2 3","pages":"Pages 493-494"},"PeriodicalIF":0.0,"publicationDate":"2024-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.sciencedirect.com/science/article/pii/S2949761224000543/pdfft?md5=ebf7c837aabfdcdf9f0c2fd67db3ce21&pid=1-s2.0-S2949761224000543-main.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142238280","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Digital Health Research Symposium: Closing Panel Commentary","authors":"Judd E. Hollander MD,&nbsp;Kristin L. Rising MD,&nbsp;Brian M. Dougan MD","doi":"10.1016/j.mcpdig.2024.06.003","DOIUrl":"10.1016/j.mcpdig.2024.06.003","url":null,"abstract":"","PeriodicalId":74127,"journal":{"name":"Mayo Clinic Proceedings. Digital health","volume":"2 3","pages":"Pages 496-498"},"PeriodicalIF":0.0,"publicationDate":"2024-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.sciencedirect.com/science/article/pii/S2949761224000646/pdfft?md5=754728474191cc9290a9c7ee3cbdc576&pid=1-s2.0-S2949761224000646-main.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142238282","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Identifying Patient Preferences for Information About Healthcare AI: A Discrete Choice Experiment","authors":"Xuan Zhu PhD ,&nbsp;Austin M. Stroud MA ,&nbsp;Sarah A. Minteer PhD ,&nbsp;Dong Whi Yoo PhD ,&nbsp;Jennifer L. Ridgeway PhD ,&nbsp;Maryam Mooghali MD, MSc ,&nbsp;Jennifer E. Miller PhD ,&nbsp;Barbara A. Barry PhD","doi":"10.1016/j.mcpdig.2024.05.017","DOIUrl":"10.1016/j.mcpdig.2024.05.017","url":null,"abstract":"","PeriodicalId":74127,"journal":{"name":"Mayo Clinic Proceedings. Digital health","volume":"2 3","pages":"Pages 492-493"},"PeriodicalIF":0.0,"publicationDate":"2024-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.sciencedirect.com/science/article/pii/S294976122400052X/pdfft?md5=a6271f68ccc995d386273727c9f28251&pid=1-s2.0-S294976122400052X-main.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142239434","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Virtual Reality Videos for Symptom Management in Hospice and Palliative Care","authors":"James R. Deming MD ,&nbsp;Kassie J. Dunbar APSW ,&nbsp;Joshua F. Lueck MSN ,&nbsp;Yoonsin Oh PhD","doi":"10.1016/j.mcpdig.2024.08.002","DOIUrl":"10.1016/j.mcpdig.2024.08.002","url":null,"abstract":"<div><h3>Objective</h3><p>To learn more about the effect of virtual reality videos on patients’ symptoms near the end of life, including which are most effective, how long the effect lasts, and which patients benefit the most.</p></div><div><h3>Patients and Methods</h3><p>We conducted a prospective study of 30 patients in a regional hospice and palliative care program from March 11, 2022, through July 14, 2023. Using a head-mounted display virtual reality, all participants viewed a 15-minute video of serene nature scenes with ambient sounds. Fifteen patients also participated in a second session of viewing bucket-list video clips they selected. Symptoms were measured with the revised Edmonton Symptom Assessment Scale before, immediately after, and 2 days after each experience. Participants rated their bucket-list selections by level of previous experience, strength of connection, and overall video quality. Functional status was also recorded.</p></div><div><h3>Results</h3><p>Nature scenes significantly improved total symptom scores (30% decrease, <em>P</em>&lt;.001), as well as scores for drowsiness, tiredness, depression, anxiety, well-being, and dyspnea. The improved scores were not sustained 2 days later. Overall, bucket-list videos did not significantly improve symptoms. Neither previous experience with an activity nor a strong connection correlated with significant improvement; however, when patients rated video quality as outstanding, scores improved (31% decrease, <em>P</em>=.03). Patients with lower functional status tended to have more symptoms beforehand and improve the most.</p></div><div><h3>Conclusion</h3><p>Serene nature head-mounted display virtual reality scenes safely reduce symptoms at the end of life. Bucket-list experiences may be effective if they are high-quality. More infirm patients may benefit the most.</p></div>","PeriodicalId":74127,"journal":{"name":"Mayo Clinic Proceedings. Digital health","volume":"2 3","pages":"Pages 477-485"},"PeriodicalIF":0.0,"publicationDate":"2024-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.sciencedirect.com/science/article/pii/S2949761224000762/pdfft?md5=a385f0a4fa18d971e26d0b9d479d821c&pid=1-s2.0-S2949761224000762-main.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142117621","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}