AI and large language models (LLMs) in healthcare can improve delivery and management but face challenges in data privacy, security, bias, regulations, and precision. AI can help clinicians by creating textual content, interpreting patient's speech into clinical concepts relevant to possible diagnoses. However, AI struggles with integrating factors like gender and race, leading to biases and data quality issues. The complexity of medical language also causes difficulties for AI. Clinical relevance engine can filter relevant patient information, aiding care quality and compliance. Natural language processing (NLP) can convert LLM generated texts into codes, reducing documentation burden, then is processed using an expert system for actionable, clinically relevant information.

Why healthcare LLMs should address clinical quality measures Healthcare IT News

UC Davis Health introduces digital care program for post-Percutaneous Coronary Intervention (PCI) patients using UC-NOW text-messaging and Clinii for vital monitoring. CliniiMobile Technology enables direct data transmission to healthcare team for guidance. Aimed at optimizing recovery, reducing heart risks and enhancing patient well-being. Collaboration with Clinii expected to improve patient-provider interactions. Program supported by American College of Cardiology, Rosenfeld Foundation. UC Davis Health team to monitor 200 patients daily to prevent complications, reduce readmissions.

UC Davis Health launches at-home care program transforming post-angioplasty care UC Davis Health

Senators Marco Rubio and Angus King introduce Strengthening Cybersecurity in Health Care Act. If passed, the act will mandate regular cybersecurity evaluations for HHS systems and sharing of findings with Congress. The move follows increased cybersecurity attacks on healthcare systems, with data breaches affecting about 133 million people last year. The bill has bipartisan support.

Marco Rubio Cosponsors Bill to Protect Healthcare Systems from Hackers Florida Daily

Health IT firms must satisfy new federal transparency norms starting Feb. 8, supplying health systems with AI. ONC's rule requires certified IT developers to offer clear info about decision-making algorithms; effecting 96% hospitals and 78% office-based doctors. Companies such as Epic, Amazon, and Google opposed, but rule also introduces enhanced interoperability standards, reporting metrics and information-blocking requirements.

HHS rule goes into effect after pushback from Epic, Amazon Beckers Hospital Review