Fuzzy Model of Digital Assessment of Donation Systems’ Level in COVID-19
- DOI
- 10.2991/aebmr.k.200502.199How to use a DOI?
- Keywords
- blood donation system, Blood Service, digital assessment, COVID-19, fuzzy control technology
- Abstract
The digitalization of the healthcare system, consisting of the use of digital tools in patient treatment procedures, takes the donation system and the Blood Service to a new level of development. The most important components of the donation systems’ management are digital models that reduce the role of a person in making various decisions and increase the level of effectiveness. Assessment of the donation systems’ level of development on a global scale as a whole and in various regions of Russia, in particular, has been and remains an essential component of effective management in the context of the health care system digitalization. As part of this work, it is proposed to build a digital model for assessing the effectiveness and development of donation systems, based on the one hand on fuzzy management technologies, and on the other, on a systematic analysis of data in conditions of incomplete information. The proposed model allows ranking donor systems, distributing them into classes of “low”, “medium”, “high”. The article shows the principles of constructing a fuzzy management model based on real data from the regional donor system of the Sverdlovsk region, taking into account COVID-19.
- Copyright
- © 2020, the Authors. Published by Atlantis Press.
- Open Access
- This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).
Cite this article
TY - CONF AU - D.M. Nazarov PY - 2020 DA - 2020/05/05 TI - Fuzzy Model of Digital Assessment of Donation Systems’ Level in COVID-19 BT - Proceedings of the 2nd International Scientific and Practical Conference “Modern Management Trends and the Digital Economy: from Regional Development to Global Economic Growth” (MTDE 2020) PB - Atlantis Press SP - 1201 EP - 1206 SN - 2352-5428 UR - https://doi.org/10.2991/aebmr.k.200502.199 DO - 10.2991/aebmr.k.200502.199 ID - Nazarov2020 ER -