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An Actionable Expert-System Algorithm to Support Nurse-Led Cancer Survivorship Care: Algorithm Development Study.

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A new algorithm, No Evidence of Disease (Ned), supports nurse-led survivorship care for prostate cancer patients. It enhances decision-making and care continuity by automating checkpoints and empowering patient self-management.

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AIalgorithm developmentartificial intelligence–powered decision supportcancercancer treatmentdigital healthexpert systemnurse-led model of carenursingpatient-reported outcomesprostate cancersurvivorship

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Area of Science:

  • Oncology
  • Nursing
  • Health Services Research

Background:

  • Improved survivorship care models are crucial for managing long-term physical and psychosocial needs of cancer survivors.
  • Prostate cancer (PCa) survivorship presents unique challenges requiring specialized care coordination.

Purpose of the Study:

  • To present the expert-informed, rules-based No Evidence of Disease (Ned) algorithm for a nurse-led PCa survivorship care model.
  • To enhance decision-making, safety, and continuity of care for men with prostate cancer.

Main Methods:

  • Developed an initial rule set refined by clinical experts and patient partners in Canada.
  • Defined algorithm priorities through multidisciplinary consensus meetings.
  • Validated and refined the system using the nominal group technique.

Main Results:

  • Established four alert classification levels based on survey responses and clinical factors.
  • Incorporated patient autonomy through tailored education and a patient-initiated consultation pathway.
  • Alert escalation was mediated by alert thresholds, history, and clinical urgency.

Conclusions:

  • The Ned algorithm can facilitate high-ratio nurse-led PCa survivorship care models.
  • It offers a defined escalation pathway for urgent symptoms while respecting patient preferences.
  • Anticipated benefits include improved decision-making, care continuity, and patient self-management.