Clinical Scorecard: Perspectives of Hospital HR Managers on Organizational Preparedness for Generative AI Competencies: A Qualitative Descriptive Analysis

At a Glance

Key Highlights

• Generative AI entails specific organizational and workforce questions as it expands in healthcare.
• Healthcare workers require applied skills for prompting, verifying content, and detecting inaccuracies.
• AI literacy, data literacy, ethics, and communication are core domains for healthcare professionals.
• Existing literature emphasizes normative skills rather than organizational feasibility assessments.
• Healthcare professionals' experiences with AI vary widely, affecting trust and perceived usefulness.

Guideline-Based Recommendations

Diagnosis

Management

Monitoring & Follow-up

Risks

• Generative AI may produce outputs that appear plausible yet are inaccurate.
• There are privacy and security risks when sensitive information is submitted to external systems.

Patient & Prescribing Data

Not applicable

Not applicable

Clinical Best Practices

• Targeted training for healthcare workers on generative AI competencies is essential.
• Healthcare organizations should assess the feasibility of required AI skills across their workforce.

Related Resources & Content

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• Generative AI in medical practice: in-depth exploration of privacy and security challenges
• Transforming public health practice with generative artificial intelligence
• Artificial intelligence in health and health care: priorities for action
• Essential AI skills for clinicians in the large language model era