Collective intelligence in medical decision-making: a systematic scoping review

Area of Science:

• Medical Decision-Making
• Health Informatics
• Collaborative Intelligence

Background:

• Collective intelligence leverages group insights via technology or manual methods for superior decision-making.
• This approach is increasingly recognized in healthcare for its potential to enhance diagnostic accuracy and patient care.
• Research aims to map the current landscape of collective intelligence in medical decision-making.

Purpose of the Study:

• To systematically review and characterize research on collective intelligence in medical decision-making.
• To describe a framework for understanding diverse studies in this emerging field.
• To identify how collective intelligence is operationalized in medical contexts.

Main Methods:

• A systematic scoping review of literature from PubMed, Embase, Web of Science, and CINAHL.
• Inclusion criteria focused on studies combining insights from multiple medical experts for patient care decisions (diagnosis, treatment, management).
• Excluded studies focused solely on visual identification in radiology or pathology, emphasizing complex decision-making.

Main Results:

• Fifteen studies were included from 3303 original articles, revealing heterogeneity in methods and outcomes.
• A framework was developed to categorize studies based on decision task completion (group vs. individual), opinion synthesis (IT, manual, in-person), and collective intelligence availability.
• The review highlights variations in how collective intelligence is implemented in medical decision-making research.

Conclusions:

• Collective intelligence in medical decision-making is a growing area with potential to improve patient outcomes.
• The heterogeneity of current research methods and outcomes presents challenges in assessing the utility of collective intelligence across different healthcare settings.
• Further understanding and standardization of collective intelligence applications in medicine are needed to enhance medical decision-making and patient care.