4PM: Privacy-Preserving Patient-Provider Matching Service in Digital Healthcare System.

Area of Science:

• Digital Health
• Health Informatics
• Privacy-Preserving Technologies

Background:

• Digital health platforms face challenges in balancing patient privacy with efficient patient-provider matching.
• Current systems often exhibit privacy leakage, imprecise matching, and poor performance with large datasets.

Purpose of the Study:

• To introduce 4PM, a novel privacy-preserving patient-provider matching scheme.
• To ensure strong privacy guarantees and efficient, accurate matching using secure computation.

Main Methods:

• Data partitioning using secret sharing between two non-colluding servers.
• Optimized Millionaires' Protocol for secure ranking.
• Oblivious retrieval techniques for privacy-preserving matching.

Main Results:

• 4PM significantly reduces computational complexity for high-dimensional data.
• Achieved end-to-end latency under 0.5 seconds with 200 doctors and 200-dimensional symptom vectors.
• Demonstrated strong privacy guarantees and high matching accuracy.

Conclusions:

• 4PM offers an efficient and secure solution for patient-provider matching in digital health.
• The proposed scheme enhances trust and security in digital healthcare systems.
• Contributes to the advancement of privacy-preserving technologies in healthcare.