Current Issue

EFFICIENCY EVALUATION OF INTELLIGENT HEALTHCARE SYSTEMS BASED ON INNOVATIVE DEA MODEL - TAKING THE APPLICATION OF UNMANNED AIRCRAFT SYSTEM (UAS) AS AN EXAMPLE

Mu-Lin Chiou*, Po-Husan Hsieh, Huan-Zhang Lin, Hsiang-Chen Hsu, Mu-Lin Chiou

National Kaohsiung University of Science and Technology

*Corresponding author: This email address is being protected from spambots. You need JavaScript enabled to view it.

Abstract

This paper investigates the efficiency evaluation and strategic application of Unmanned Aerial Systems (UAS) within the smart healthcare ecosystem. Driven by the profound integration of Artificial Intelligence (AI), the nascent 6G communications, and the low-altitude economy, smart healthcare has transitioned toward the construction of highly resilient, automated logistics networks. As a critical mobile medical infrastructure, UAS has demonstrated a decisive impact on mitigating healthcare disparities in remote areas and shortening emergency response times within the critical "Golden Hour."

This paper adopts an innovative Data Envelopment Analysis (DEA) model -- the Three-stage Entropic Weight Method with Assurance Region (tEWM-AR) approach -- to measure operational efficiency across scenarios such as emergency medical supply delivery, remote deployment of Automated External Defibrillators (AEDs), and dynamic patient monitoring in aging communities. Empirical results indicate that the tEWM-AR model effectively addresses high-uncertainty variables within medical environments, confirming that the integration of UAS significantly enhances the service resilience and carbon-neutral operational efficiency of healthcare institutions.

According to the latest report from IDTechEx, the global drone market (encompassing both commercial and consumer sectors) is projected to grow from $69 billion in 2026 to $147.8 billion by 2036, with a compound annual growth rate (CAGR) of 7.9%. Notably, the deployment of commercial drones is accelerating, with annual shipments expected to exceed 9 million units by 2036 (MakerPRO, 2026/01). This trend underscores the robust global demand for high-frequency, low-latency medical logistics solutions. The evaluation framework proposed herein not only provides a scientific metric for mobile healthcare technologies but also offers critical empirical support for policymakers in designing low-altitude medical rescue corridors and establishing technical standards.

Keywords: Unmanned Aerial Systems (UAS), Smart Healthcare, Low-Altitude Economy, Data Envelopment Analysis (DEA), tEWM-AR Model, Healthcare Resilience, Service Efficiency, Accessibility.