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Through a new telehealth partnership with Trustmark Small Business Benefits, employees can access nonoperative musculoskeletal care to address muscle and joint pain.

A health tech CEO offers guidance on investment in analytics and IT infrastructure to accelerate the transition to VBC, strategies to get clinician buy-in, and how tech can be used to compare pricing on a market-by-market basis.

A prehospital health information exchange in Michigan that provides bidirectional interoperability will bridge ambulatory data gaps and enhance care coordination en route to the hospital and during post-discharge care transitions.

Providers should push hard to maximize the use of generative AI and natural language processing tools – but validate performance for each system rigorously before making it available for widespread use, a physician author says.

Also: A Virginia man is facing more than 20 years for unauthorized access and exposure of U.S. Supreme Court Justice Ruth Bader Ginsburg's PHI in 2019 to fuel a political conspiracy theory.

This comes as part of its 10-year strategy to improve health outcomes for people living with rare disorders.

AI has permeated various aspects of daily life in recent years, but its impact on healthcare has been hailed as revolutionary. Studies have predicted that by the end of 2026, 55% of healthcare organisations in Asia Pacific will have data governance frameworks that prioritise AI’s ethical and explainable use.  Such vast projected AI use in healthcare can be attributed to its active and proactive capabilities in optimising patient and health journeys.  AI capabilities in HealthTech  Active - Streamlining Medical Data Management  AI has the potential to streamline manual processes by automatically and swiftly summarising large amounts of healthcare data. Consequently, AI can assist in optimising patient journeys by automatically generating precise information regarding wait times, appointment hours, and treatment plans.   Overall, such approaches can help patients manage their expectations while alleviating their anxiety regarding future health appointments and procedures.  Proactive – Forecasting system and patient vulnerabilities  Numerous AI tools, such as machine learning algorithms and natural language processing, can help healthcare systems analyse large datasets, detect patterns, and generate actionable insights in real-time.   This feature is crucial for the cybersecurity of sensitive health data such as Electronic Medical Records (EMR). Not only can AI detect risks in real-time, but it can also forecast potential vulnerabilities and prescribe fixes.   AI-powered solutions transforming APAC healthcare  Data-based Operation and Communication Center (DOCC) PAN  The DOCC PAN is an AI-powered platform developed by South Korea's Samsung Medical Center (SMC) that employs predictive modelling. Using DOCC PAN, employees can input operational data at 30-minute intervals to estimate patient influx and reallocate staff during peak hours. In SMC's busy and crowded Blood Collecting room, implementing DOCC PAN has significantly reduced patient wait times.    “The median waiting time eventually plummeted dramatically, from a range of nine to 10 minutes to a mere four minutes,” said Oksoon Jeong, Manager, Data Service Platform, Samsung Medical Centre.  Intelligent Anti-Microbial System (i.A.M.S.)  i.A.M.S is a comprehensive antimicrobial AI platform recently implemented in China Medical University Hospital (CMUH). The four-in-one functioning platform can leverage AI to detect drug-resistant strains and predict and monitor the risk of infectious sepsis and mortality.   Since its inception, CMUH has significantly benefited from the platform's ability to automatically compare drug-drug interactions and allergy history, allowing the hospital to learn and generate smart medicine dosage recommendations.  “Three months after the system (i.A.M.S) was launched, the mortality rate due to sepsis was successfully reduced by 7.1%,” said Lu-Ching Ho, Clinical Pharmacist and CMUH HIMSS Project Group Secretary.  Digital maturity can be maximised with the right network and guidance  To attain comparable transformative digital maturity, healthcare providers must place themselves in environments that facilitate key information sharing, collaboration, and expert guidance on how to leverage AI in healthcare. The upcoming Innotech Conference is one example of such a setting.  This premier event will bring together leaders from healthcare, government, and tech sectors, along the wider medical community to discuss the future of digital healthcare transformation.   Guest of Honour, Ong Ye Kung, Singapore’s Minister of Health, will deliver a keynote address highlighting Singapore's vision for digital healthcare transformation, among other digital health developments.  Additionally, panel discussions featuring innovators and thought leaders like Tan Bin Ru, President, Enterprise Digital at ST Engineering, and healthcare futurist, Lucien Englen, will examine the use of AI-driven technology to improve healthcare systems.   Discussions at the event can inspire and empower attendees with actionable insights into AI, driving meaningful advancements that prioritise patient-centred care while assuring sustainable healthcare transformation.   The InnoTech Conference will be held on 3 September 2024 from 11.30am – 3.30pm at the Marina Bay Sands. For more event information or to register, click here. 

Encryption technology used in elections can potentially improve an AI model's predictive capability without compromising patient data privacy.

Offered in partnership with Novo Nordisk Foundation, the fellowship will focus on technologies that analyze vast amounts of data to increase diagnostic accuracy, speed personalized medicine and improve clinical trials.