Cognition in a Monolithic System: A Case Study in Architectural Failure and Adaptive Care

This paper introduces the Modular Pod System (MPS), a next-generation healthcare architecture designed to replace monolithic, protocol-locked designs with adaptive, human-scaled care units. Through a lived case study—a misfiring bed alarm, a blocked PT reassessment, a camera threat framed as “safety,” and a self-directed exit—it demonstrates how modern healthcare institutions routinely misclassify patients whose bodies are impaired but whose cognition remains intact. The paper proposes an alternative design: pod-based authority structures, real-time cognitive profiling, PT-driven mobility reassessment, and a bedside AI companion. The counterfactual model shows that within MPS, the misclassifications described here would be architecturally impossible.

Publication Details

Journal
Zenodo (CERN European Organization for Nuclear Research)
Published
2025-11-24
DOI
https://doi.org/10.5281/zenodo.17698220
Primary Topic
Healthcare Technology and Patient Monitoring
Type
article
Field-Weighted Citation Impact
0.00
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article

Cognition in a Monolithic System: A Case Study in Architectural Failure and Adaptive Care

Zenodo (CERN European Organization for Nuclear Research)
Healthcare Technology and Patient Monitoring
article

Cognition in a Monolithic System: A Case Study in Architectural Failure and Adaptive Care

article en

Abstract

This paper introduces the Modular Pod System (MPS), a next-generation healthcare architecture designed to replace monolithic, protocol-locked designs with adaptive, human-scaled care units. Through a lived case study—a misfiring bed alarm, a blocked PT reassessment, a camera threat framed as “safety,” and a self-directed exit—it demonstrates how modern healthcare institutions routinely misclassify patients whose bodies are impaired but whose cognition remains intact. The paper proposes an alternative design: pod-based authority structures, real-time cognitive profiling, PT-driven mobility reassessment, and a bedside AI companion. The counterfactual model shows that within MPS, the misclassifications described here would be architecturally impossible.

Zenodo (CERN European Organization for Nuclear Research)
Openalex Percentile: Top 31%
Healthcare Technology and Patient Monitoring
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