Nurse-Task Matching Decision Support System Based on FSPC-HEART Method to Prevent Human Errors for Sustainable Healthcare

ArticleAçık Erişim

Özet

To increase the levels of sustainability of service quality as well as to ensure satisfaction and assurance of patients in the health sector, minimizing the probability of making mistakes nurses is of great importance. The extent of this probability is considerably affected by task types, physical conditions of the working environment, workload, and working conditions. Moreover, the physical and mental characteristics of nurses also have a colossal influence on this probability. It is also possible to increase the sustainability of health services by matching nurses appropriately to a specific task according to related risk levels, and by balancing their workload accordingly. This study proposes FSPC-HEART method in that purpose, as a new type of human error reduction and assessment technique (HEART) application based on fuzzy step-wise weight assessment ratio analysis and principal component analysis methods. Unlike the methods in the literature, this new method offers a person-specific proactive error prevention approach. With FSPC-HEART, the probability of each nurse to make a mistake, that is, the human error probability (HEP) values are calculated separately for each task. Also, the combined effect of physical and mental workload factors for each employee was taken into account. In the proposed method, the effect of the subjective judgments of the decision-makers on the objectively obtained HEP values was tried to be reduced. The developed nurse-task matching decision support system enables the FSPC-HEART method to be easily used by decision-makers, and to assign employees to tasks with low error probabilities. © 2023, The Author(s).

Anahtar Kelimeler

RDL Kalıcı Bağlantı (PID)
https://rdlopen.rawdatalibrary.net/r/ebyu/11615Resmi atıflarda kullanılan kalıcı adres
DOI
https://doi.org/10.1007/s44196-023-00224-7Yayıncı resmi DOI adresi
Tam Kayıt
AlanDeğerDil
dc.contributor.authorKoseoglu, Salih Cihan
dc.contributor.authorDelice, Elif Kılıc
dc.contributor.authorErdebilli, Babek
dc.date.accessioned2026-10-18T20:26:38.445147049Z
dc.date.available2026-10-18T20:26:38.445147049Z
dc.date.issued2023
dc.description.abstractTo increase the levels of sustainability of service quality as well as to ensure satisfaction and assurance of patients in the health sector, minimizing the probability of making mistakes nurses is of great importance. The extent of this probability is considerably affected by task types, physical conditions of the working environment, workload, and working conditions. Moreover, the physical and mental characteristics of nurses also have a colossal influence on this probability. It is also possible to increase the sustainability of health services by matching nurses appropriately to a specific task according to related risk levels, and by balancing their workload accordingly. This study proposes FSPC-HEART method in that purpose, as a new type of human error reduction and assessment technique (HEART) application based on fuzzy step-wise weight assessment ratio analysis and principal component analysis methods. Unlike the methods in the literature, this new method offers a person-specific proactive error prevention approach. With FSPC-HEART, the probability of each nurse to make a mistake, that is, the human error probability (HEP) values are calculated separately for each task. Also, the combined effect of physical and mental workload factors for each employee was taken into account. In the proposed method, the effect of the subjective judgments of the decision-makers on the objectively obtained HEP values was tried to be reduced. The developed nurse-task matching decision support system enables the FSPC-HEART method to be easily used by decision-makers, and to assign employees to tasks with low error probabilities. © 2023, The Author(s).
dc.description.sponsorshipUK Research and Innovation, UKRI, (104887)
dc.identifier.doi10.1007/s44196-023-00224-7
dc.identifier.eissn1875-6883
dc.identifier.issn1875-6891
dc.identifier.issue1
dc.identifier.scopus2-s2.0-85153073953
dc.identifier.startpage53
dc.identifier.urihttps://rdlopen.rawdatalibrary.net/r/ebyu/11615
dc.identifier.volume16
dc.identifier.wosWOS:000966426000001
dc.language.isoen
dc.publisherSpringer Science and Business Media B.V.
dc.relation.ispartofInternational Journal of Computational Intelligence Systems
dc.rightsinfo:eu-repo/semantics/openAccess
dc.subjectDecision support system
dc.subjectFSWARA
dc.subjectHEART
dc.subjectHuman error nurses
dc.subjectPCA
dc.subjectArtificial intelligence
dc.subjectDecision making
dc.subjectDecision support systems
dc.subjectErrors
dc.subjectHealth risks
dc.subjectNursing
dc.subjectPrincipal component analysis
dc.subjectSustainable development
dc.subjectDecision makers
dc.subjectHuman error nurse
dc.subjectHuman error probability
dc.subjectHuman errors
dc.subjectPhysical conditions
dc.subjectTask matching
dc.subjectTask type
dc.subjectWorking environment
dc.titleNurse-Task Matching Decision Support System Based on FSPC-HEART Method to Prevent Human Errors for Sustainable Healthcare
dc.typeArticle
dspace.entity.typePublication
rdl.citation.scopus7
rdl.citation.wos5
rdl.oa.statusgold
rdl.source.indexSCOPUS
rdl.source.indexWOS
rdl.wos.indexScience Citation Index Expanded (SCI-EXPANDED)