Risk prediction tools in surgical oncology

Area of Science:

• Oncology
• Medical Informatics
• Patient Engagement

Background:

• Healthcare trends emphasize patient engagement and shared decision-making.
• Decision aids are tools that facilitate informed choices by outlining treatment options and outcomes.
• Surgical oncology presents complex treatment decisions requiring robust decision support.

Purpose of the Study:

• To discuss the application and components of decision aids for surgical oncology patients.
• To explore the integration of risk prediction models within decision aids.
• To address critical aspects of decision aid design, including usability, transparency, and accessibility.

Main Methods:

• Literature review and synthesis of current practices in decision aid development and implementation.
• Analysis of risk prediction models relevant to surgical oncology outcomes (short-term and long-term).
• Discussion of user-centered design principles for decision aids.

Main Results:

• Decision aids can effectively present short-term surgical risks and long-term survival/recurrence predictions.
• Combining short- and long-term risk predictions offers comprehensive guidance for treatment selection.
• Usability, transparency, and accessibility are key factors for successful decision aid adoption.

Conclusions:

• Decision aids are valuable tools for enhancing shared decision-making in surgical oncology.
• Integrating predictive analytics into decision aids empowers patients with personalized risk information.
• Optimizing decision aid design is crucial for effective patient-provider communication and informed treatment choices.