Publications by authors named "Michael Kalfin"
Article Synopsis
- Large language models (LLMs) are AI systems that can generate and understand human-like language, which might benefit neurology-related tasks, but their effectiveness in real clinical scenarios is still uncertain.
- The article highlights several limitations of LLMs in healthcare, including issues like limited clinical reasoning and biases, alongside practical challenges such as costs and infrastructure needs.
- To successfully integrate LLMs into clinical practice, healthcare organizations must foster an AI-friendly culture, engage stakeholders, and prioritize patient data privacy while ensuring proper testing and monitoring to mitigate biases.
A multidisciplinary care model to increase access to neurologic ambulatory care.
J Am Assoc Nurse Pract
June 2020
Background: Expert patient care has been associated with improved outcomes for neurology patients, yet timely access to specialists is challenging. The employment of nurse practitioners (NPs) holds great potential to increase access to neurologic ambulatory care, however little practical guidance exists to date for how this may be achieved.
Local Problem: To improve timely care provision for patients with neurologic disease, we employed a multidisciplinary care utilization framework that used NPs to expand clinic appointment availability.
Background: Oncology care is delivered largely in ambulatory settings by interdisciplinary teams. Treatments are often complex, extended in time, dispersed geographically and vulnerable to teamwork failures. To address this risk, we developed and piloted a team training initiative in the breast cancer programme at a comprehensive cancer centre.
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