Perioperative uses are stratified by the consequence of failure: lower-risk information processing may be automated when outputs are traceable; intermediate-risk interpretive uses should augment clinicians and require explicit verification; high-risk or time-critical decisions should remain under direct specialist control. These tiers are not fixed properties of task categories; assignment depends on the intended use, downstream clinical consequences, degree of automation, and opportunity for independent verification
This study evaluates the accuracy of two of the foremost large language models (LLMs) used in clinical decision support tools for regional and neuraxial anesthesia procedures for patients receiving antithrombotic medications.
Conner M. Willson, Birpartap S. Thind, Jay Srinivas et al.· Cureus· 0 citations
Hospitals often detect complications retrospectively via error-susceptible mechanisms including self-reporting, manual abstraction, or billing codes. We propose a paradigm of continuous clinical quality observability: a background, non-interruptive layer where AI agents continuously read the EHR narrative to surface em...
Advait Patil, W. Curry, B. Nahed· npj Health Systems· 0 citations
Large language model systems can retrieve and cite medical evidence, yet their outputs may remain difficult to review during care. We define reviewability through evidence adequacy for action-changing claims, exact source verification, and presentation matched to a specified reviewer and decision point. We propose a...
Zonghai Yao, Hong Yu· npj Digital Medicine· 0 citations
Li et al. introduce Quicker, an agentic large language model system that drafts clinical guideline recommendations through a GRADE-based workflow. Building on gaps in the authors’ own evaluation, we propose safeguards for trustworthy use: verifiable, design-aware evidence bundles with explicit scope; calibrated, uncert...
Quan Zhang, Yuan-Yuan Fu· npj Digital Medicine· 0 citations
Large language models (LLMs) are rapidly entering clinical practice, offering opportunities to improve healthcare delivery and clinical decision support. However, concerns regarding hallucinations, patient safety, regulatory oversight, and equitable implementation remain significant. This letter highlights key challeng...
Sibghatullah Laghari, Abdul Samad, Iffa Zaheer· INNOVAPATH· 0 citations
Simple Summary Accurate preoperative surgical risk predictions help predict potential postoperative complications, guide shared doctor–patient decision making, and personalise management strategies to improve perioperative surgical outcomes. We present the development and external validation of the novel GO SOAR surgic...
F. Gaba, O. Blyuss, J. G. Oganezova et al.· Cancers· 0 citations
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