a whitepaper by Breyden Taylor - 01/14/2025 - in association with Skyward Prompted


special thanks to Reuven Cohen for giving me confidence enough to write this

1. Executive Summary

Automated or semi-automated healthcare triage systems are playing an increasingly critical role in remote patient management, telemedicine, and emergency call centers. Their core objectives—ensuring patient safety, optimal resource allocation, and standardized decision-making—are intrinsically tied to the underlying logic. Traditional triage protocols often employ heuristic or flowchart-style decision trees that can be difficult to maintain and lack flexibility in handling complex, evolving medical knowledge.

This whitepaper presents a predicate logic–based framework, enriched by symbolic mathematics, to provide a more rigorous, transparent, and adaptable approach to triage. By formalizing symptoms, conditions, and recommended dispositions in well-defined predicates and rules, our system overcomes many limitations of typical rule-based tools. The paper will describe core features such as negative-constraint overrule (red-flag handling), mandatory escalation for critical conditions, edge-case logic for unusual or outlier presentations, and a priority-based mechanism to differentiate levels of care. We also discuss extensions for fuzzy or probabilistic modeling to address real-world uncertainty.

The outcome is a triage model that is more interpretable, scalable, and clinically aligned. It can help reduce under-triage errors, provide clear traceability for audits, and integrate seamlessly into existing electronic health record (EHR) infrastructures.


2. Introduction

2.1 Background

Healthcare triage typically involves an initial assessment of a patient’s condition to determine urgency and appropriate care pathways. While many organizations still rely on human-driven phone triage or in-person screening, these manual processes can be time-consuming, subject to individual variance, and prone to misinterpretation of symptoms. Automated or AI-enhanced triage protocols aim to standardize care while ensuring patients with severe conditions are identified and managed promptly.

2.2 Importance of Symbolic Logic

Most current triage systems use simple decision trees or if-then-else statements that can quickly become unwieldy as the number of conditions and exceptions grows. By contrast, a predicate logic–based approach:

  1. Allows for formal specification of symptoms, constraints, and dispositions.
  2. Facilitates structured reasoning about patient states.
  3. Provides clarity and transparency—every triage decision can be traced to a corresponding logical rule.

2.3 Scope of This Whitepaper

This document details the conceptual design and practical implications of a logic-driven triage system. It provides technical underpinnings of predicate logic, symbolic maths, and how they fit into an end-to-end clinical workflow. We also cover extensions for uncertainty, describe implementation considerations, and discuss benefits and limitations of our approach.


3. Challenges in Traditional Triage Systems