Who Should Attend
Registered nurses, nurse managers, nursing informatics teams, nursing educators, healthcare quality professionals, and hospital digital transformation staff.
Learning Objectives
- Explain major digital health tools and nursing workflow use cases.
- Assess data quality, privacy, security, bias, and AI limitations in healthcare settings.
- Evaluate an AI-enabled nursing scenario with appropriate human oversight.
- Develop a safe, measurable digital nursing pilot proposal.
Curriculum & Instructional Hours
| Module | Key Topics | Hours |
|---|---|---|
| Digital Health & Nursing Workflows | EHR concepts, telehealth, remote monitoring, workflow mapping | 5 |
| Clinical Data Literacy | Data quality, dashboards, documentation, interoperability basics | 5 |
| AI Applications & Limitations | Clinical decision support concepts, generative AI, error modes, bias | 5 |
| Privacy, Security & Governance | Confidentiality, access controls, consent, organizational oversight | 5 |
| Human-Centered Implementation | Usability, staff training, change management, safety evaluation | 5 |
| Digital Nursing Pilot Capstone | Use-case selection, risk assessment, success metrics, evaluation plan | 5 |
Teaching & Assessment
Learning Methods
Interactive seminars, synthetic-data demonstrations, AI-output critique exercises, small-group workflow workshops, and a digital health pilot capstone.
Assessment
Data and AI evaluation exercises (35%), governance/risk checklist (25%), pilot proposal and presentation (40%); proposed weights.
Program Outcomes
- Nursing digital workflow and opportunity map
- AI use-case risk and governance checklist
- Data quality and privacy evaluation exercise
- Digital nursing pilot proposal with success and safety metrics
Program planning notice: Curriculum, duration, faculty, delivery, visits, and completion arrangements are proposed and subject to final institutional confirmation. No clinical practice privileges or professional license eligibility are guaranteed.