2 Values and Principles
While there are many potential applications for LLMs in healthcare, the following guiding principles should be considered when developing and deploying LLMs in the academic hospital system. Note that these principles largely apply to any Artificial Intelligence or Machine Learning applications in use on the campus.
2.1 Vision Statement
LLMs must be used in a manner consistent with the mission, vision, and values of the academic hospital system.
The use of LLMs must align with relevant legal and regulatory requirements, including but not limited to data privacy, security, and intellectual property laws.
The deployment of LLMs should prioritize patient safety, privacy, and wellbeing.
LLMs must be used in a transparent manner, with users understanding the capabilities and limitations of the technology.
Continuous improvement and evaluation of LLM usage should be prioritized to ensure ongoing alignment with organizational goals.
2.2 Stakeholder Considerations
2.2.1 Patients
LLMs should be used to augment patient care and improve outcomes, without replacing the human touch and empathy of healthcare providers.
Patients must be informed about the use of LLMs in their care, and they should have the option to opt out if desired.
Patient data used in LLM applications must be anonymized, encrypted, and securely stored to protect patient privacy.
2.2.2 Healthcare Providers
LLMs should be deployed to enhance clinical decision-making and efficiency without undermining the autonomy and expertise of healthcare providers.
Adequate training and support should be provided to healthcare providers to ensure proper use and understanding of LLMs.
Feedback from healthcare providers must be regularly solicited to improve LLM performance and usability.
2.2.3 Researchers
The use of LLMs in research must adhere to ethical standards, including obtaining informed consent and minimizing potential harm.
Collaboration between researchers and LLM developers should be encouraged to drive innovation and address specific research needs.
Research involving LLMs should be transparent and reproducible, with results and methodologies made available to the wider scientific community.
2.2.4 Administrators and Support Staff
LLMs should be deployed in administrative and support functions to improve efficiency, reduce costs, and enhance the overall quality of service.
Staff should receive appropriate training and support to understand and utilize LLMs effectively.
Employee feedback should be actively sought to identify areas of improvement and potential new applications for LLMs.
2.3 Monitoring and Compliance
A designated LLM Steering Committee, comprising representatives from various stakeholder groups, will be responsible for monitoring and enforcing compliance with this policy.
Periodic audits and assessments will be conducted to ensure adherence to this policy and identify areas for improvement.
Policy violations may result in disciplinary action, up to and including termination of employment or access to LLMs