Abstract
Kevin Dooley (1997), defined Complex Adaptive System (CAS) as a group of semi-autonomous agents who interact in interdependent ways to produce system-wide patterns, such that those patterns then influence behavior of the agents. A healthcare system is considered as a Complex Adaptive System of system (SoS) with agents composed of strategies, people, process, and technology. Healthcare systems are fragmented with independent systems and information. The enterprise architecture (EA) aims to address these fragmentations by creating boundaries around the business strategy and key performance attributes that drive integration across multiple systems of processes, people, and technology. This paper uses a SoS Explorer to select an optimal architecture that provide the necessary capabilities to meet key performance attributes (KPAs) in a dynamic, complex healthcare business environment. The SoS Explorer produced an optimal meta-architecture where all but two systems (disease and facility processes) participated with many of the systems having at least four interfaces. The healthcare meta-architecture produced in this study is not a solution to address the challenges of the healthcare enterprise architecture but provides insight on the areas - systems, capabilities, characteristics, and interfaces - to pay attention to where agility is an important attribute and not to be severely compromised.
Recommended Citation
J. Goldschmid et al., "SoS Explorer Application with Fuzzy-Genetic Algorithms to Assess an Enterprise Architecture -- A Healthcare Case Study," Procedia Computer Science, vol. 185, pp. 55 - 62, Elsevier B. V., Jun 2021.
The definitive version is available at https://doi.org/10.1016/j.procs.2021.05.006
Meeting Name
Complex Adaptive Systems Conference Theme: Big Data, IoT, and AI for a Smarter Future (2021: Jun. 16-18, Malvern, PA)
Department(s)
Engineering Management and Systems Engineering
Keywords and Phrases
Enterprise Architecture; Genetic Algorithms; Healthcare; Meta-Architectures; System-Of-Systems
International Standard Serial Number (ISSN)
1877-0509
Document Type
Article - Conference proceedings
Document Version
Final Version
File Type
text
Language(s)
English
Rights
© 2021 The Authors, All rights reserved.
Creative Commons Licensing
This work is licensed under a Creative Commons Attribution-Noncommercial-No Derivative Works 4.0 License.
Publication Date
18 Jun 2021
