JAMA Medical News
AI and Clinical Practice—Building Patient and Clinician Trust in a Health Care System
Oct 18, 2023
Dr. Andrew Bindman, CMO of Kaiser Permanente, discusses the impact of AI in healthcare, addressing equity, patient privacy, and social risk factors. The conversation explores the use of AI technologies in improving patient care, managing biases, and maximizing health outcomes by addressing social determinants. The discussion also emphasizes striking a balance between the promises and risks of AI in healthcare innovation, focusing on patient-centric practices and enhancing healthcare experiences.
25:26
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Quick takeaways
- AI tools can predict patient decline in hospital settings by analyzing vital signs, neurologic checks, and lab results.
- Efforts to address equity concerns in AI development involve eliminating bias, enhancing trust, and implementing surveillance systems.
Deep dives
AI Tools for Disease Detection and Outcome Prediction
Clinicians are increasingly utilizing AI technologies to improve clinical practice. AI tools can enhance disease detection and predict patient outcomes. For example, in hospital settings, integrated AI tools analyze vital signs, neurologic checks, and lab results to predict patient decline and alert primary physicians. This improves patient care and outcomes. AI is also being used to identify patients at higher risk of conditions like sepsis based on natural language notes. Furthermore, AI tools help analyze social risk factors like missed appointments and medication pick-ups, aiding in interventions for patients facing challenges.
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