Isaac Kohane

Digital health technologies: opportunities & challenges in rheumatology Daniel Solomon, MD MPH & Bob Rudin, PhD Abstract The past decade in rheumatology has seen tremendous innovation in digital health technologies, including the electronic health record, virtual visits, mobile health, wearable technology, digital therapeutics, artificial intelligence and machine learning. The increased availability of these technologies offers opportunities for improving important aspects of rheumatology, including access, outcomes, adherence and research. However, despite its growth in some areas, particularly with non-health-care consumers, digital health technology has not substantially changed the delivery of rheumatology care. This Review discusses key barriers and opportunities to improve application of digital health in rheumatology. Key topics include smart design, voice enablement and the integration of electronic patient-reported outcomes. Smart design involves active engagement with the end users of the technologies, including patients and clinicians through focus groups, user testing sessions and prototype review. Voice enablement using voice assistants could be critical for enabling patients with hand arthritis to effectively use smartphone apps and might facilitate patient engagement with many technologies. Tracking many rheumatic diseases requires frequent monitoring of #patientreportedoutcomes. Current practice only collects this information sporadically, and rarely between visits. #Digitalhealth technology could enable patient-reported outcomes to inform appropriate timing of face-to-face visits and enable improved application of treat-to-target strategies. However, best practice standards for digital health technologies do not yet exist. To achieve the potential of digital health technology in rheumatology, rheumatology professionals will need to be more engaged in the technology design process and provide leadership to effectively incorporate new tools into clinical care. Key points Digital health technology (DHT) offers enormous potential to improve rheumatology care but this potential has so far been largely unrealized. The #electronichealthrecord, virtual visits, mobile health, wearable technology, digital therapeutics, artificial intelligence and machine learning could all have a role individually and in combination to reshape rheumatology practice. Increased use of user-centred design in the development of #digitalrheumatology tools is needed and will facilitate electronic patient-reported outcomes becoming a cornerstone of rheumatology. https://lnkd.in/eEZCSEg7

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Cofactor Genomics' OncoPrism test has garnered national coverage from Medicare contractor Palmetto GBA, showcasing its innovative RNA analysis for precision medicine. This predictive diagnostic tool assesses a patient's tumor immune profile using high-dimensional RNA-based Health Expression Models (HEMs) to predict their response to immune checkpoint inhibitor (ICI) immunotherapy. The result? More informed treatment decisions and improved outcomes for cancer patients, particularly those with recurrent and metastatic head and neck squamous cell carcinoma (RM-HNSCC). Patients in the PREDAPT national clinical trial can benefit from OncoPrism's effectiveness in predicting responses to ICI therapy across eleven solid tumor cancers. Cofactor Genomics' expertise lies in leveraging RNA to tackle healthcare challenges, with their patented HEMs in the PRISM database showcasing advancements in machine learning and RNA analysis. By utilizing vast biological RNA data, these models offer invaluable insights into biology, disease, and therapy response. With OncoPrism as a CAP/CLIA-validated and Medicare-approved test, Cofactor Genomics exemplifies its dedication to advancing precision medicine through RNA decoding. Their groundbreaking work has not only been acknowledged in prestigious scientific journals but has also led to collaborations with various healthcare systems. Discover more about OncoPrism's pivotal role in predicting immunotherapy response in cancer patients: https://lnkd.in/dJjVbeBw #PrecisionMedicine #RNAAnalysis #HealthcareInnovations Jarret Glasscock

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📢New article alert from the Journal of Comparative Effectiveness Research:   Comparing prospectively assigned trial and real-world lung cancer patients   This study evaluates the comparability of clinical trial (CT) cohorts derived from electronic medical records with real-world data cohorts. By comparing overall survival patterns, the study found no statistically significant differences, suggesting that survival patterns between real-world and CT cohorts in non-small cell lung cancer settings are similar and suggesting a potentially appropriate role for external controls.   Authors: Brigham Walker (Tulane University School of Public Health and Tropical Medicine), Herman E Ray (ConcertAI), Ping Shao, Claudio D'Ambrosio, Craig White & Mark S Walker   #heor #RealWorldEvidence #LungCancer #NSCLC #ClinicalTrials   🔗 https://lnkd.in/eQFVeWkZ

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🎉 New Clinical AI Breakthrough 🎉 We’re thrilled to share IMO Health’s latest research collaboration with Harvard Medical School and Mass General Brigham, published in a top The Lancet journal! Together, we’ve co-developed a novel #GenAI algorithm that detects early signs of cognitive decline from real #EHR clinical notes. Our study found that LLMs and traditional machine learning models trained on local EHR data will each produce unique errors. By combining these distinct models into one ensemble model, we can greatly enhance diagnosis precision. This is a major milestone in the #ClinicalAI space and our mission to transform healthcare by transforming data. Read the full publication for more details! https://lnkd.in/gbxyWbsd #HealthcareInnovation #AI #HealthIT #HarvardMedicalSchool

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Now available: Oncology Care Model’s (OCM) final evaluation report: https://lnkd.in/eD5eNTF8 & Patient Perspectives Report: https://lnkd.in/etKN_BBq OCM aimed to improve care coordination, appropriateness of care, and access to care for people undergoing #chemotherapy. Implemented from 2016 to 2022, it also contributed important lessons learned used in the design of the currently recruiting Enhancing Oncology Model: go.cms.gov/eom. The new Oncology Care Model Cancer Care report showcases patient cancer journeys and pinpoints what matters most to people undergoing cancer treatment. It is designed for patients and caregivers to connect and learn about cancer treatment from a patient’s perspective.

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