Table 1.

An example of the incorporation of AI-assisted technology into oncology nursing care planning.

Steps	Example	Action by LLM/AI
Background	Mrs. Jones, a 55-year-old female, was recently diagnosed with stage II breast cancer. She has a family history of cancer and is anxious about her treatment and prognosis.	The LLM can also prompt relevant questions to gather a complete patient history such as asking about familial disease prevalence, lifestyle factors, mental health status, or medication adherence.
Step 1: Data collection	Oncology nurse Joyce collected comprehensive data including Mrs. Jones' medical history, family history, lifestyle, and mental health status. Vital signs, lab results, and diagnostic imaging reports were obtained and integrated into the hospital's EHRs.	The AI system processes and organizes the collected data, making it easily accessible for reference and analysis.
Step 2: Formulating nursing diagnoses	•Anxiety related to cancer diagnosis and treatment •Risk for Infection related to CTX-induced immunosuppression	The LLM suggests potential nursing diagnoses based on its analysis.
Step 3: Goals and expected outcomes	These include reducing Mrs. Jones' anxiety, preventing infections during treatment, and improving her understanding and management of her condition.	The model, based on evidence-based research, predicts expected outcomes and helps set SMART goals.
Step 4: Nursing interventions	•Individualized anxiety management •Infection prevention precautions and education	The model recommends several evidence-based nursing interventions
Step 5: Documentation and patient education material	Joyce documents the care plan and prepares patient education materials.	The AI helps Joyce document the care plan efficiently. Moreover, it generates patient education materials tailored to Mrs. Jones's condition and comprehension level.
Step 6: Evaluation criteria	An ongoing evaluation is conducted to monitor Mrs. Jones' response to the treatment and the efficacy of the nursing interventions.	The model uses continuous data input from Mrs. Jones' EHR to evaluate her response to the treatment and the efficacy of the nursing interventions. Joyce uses this information to adjust the care plan as needed, ensuring optimal patient outcomes and timely detection of potential complications.

CTX, Chemotherapy; HER, Electronic health record; LLM, Large language model; SMART, Specific, Measurable, Achievable, Relevant and Time-Bound; AI, artificial intelligence.