The method of Human Reliability Analysis aims to identify and surface the potential failures of the system resulting from human errors, analyze causes and identify appropriate countermeasures to prevent and reduce the linked risk and resultant patient harm. These methods are well-accepted and integrated into the safety management process in most industries. These methods allow the investigation of medical error and patient harm and to develop the applications of these methods to the problem of adverse reactions to treatment and other associated risks in healthcare. In this paper a new method for evaluation of human factor in healthcare is proposed. Important specifics of this method is the examination based on ambiguously and incompletely specified clinical data with application of principles from Data Mining.
References
1.
ApostolakisG.BarachP. (2003). Lessons learned from nuclear power. In HatlieM.TavillK. (Eds), Patient Safety, International Textbook, Aspen Publications, 205-225.
2.
AvenT.ZioE.BaraldiP.FlageR. (2014). Uncertainty in Risk Assessment: The Representation and Treatment of Uncertainties by Probabilistic and Non-Probabilistic Methods, Wiley, doi: 10.1002/9781118763032.ch07
3.
BarachPKubatM. (2006). Probabilistic Decision Trees and Data-mining methods of Intraoperative Medical Records for Predicting Adverse Events International. International Anesthesia Research Society 80 Clinical and Scientific Congress, San Francisco, CA.
4.
BarachP. (2016) Designing high-reliability healthcare teams. Proc of Int. Conf. on Information and Digital Technologies, Rzeszów, Poland, doi: 10.1109/DT.2016.7557144
5.
BrallA. (2006), Human Reliability Issues in Medical Care – A Customer Viewpoint, Proc. on Annual Reliability and Maintainability Symp. (RAMS '06), Newport Beach, CA, 46–50, 10.1109/RAMS.2006.1677348
6.
CatelaniM.CianiL.RisalitiC. (2014), Risk assessment in the use of medical devices: a proposal to evaluate the impact of the human factor, Proc. of IEEE Int. Symp. on Medical Measurements and Applications (MeMeA), Lisboa, doi: 10.1109/MeMeA.2014.6860088
7.
DhillonB.S. (2003), Human Reliability and Error in Medicine, World Scientific, 233p.
8.
DeeterJ.RantanenE. (2012), Human Reliability Analysis in Healthcare, Proc. of 2012 Symp. on Human Factor and Ergonomics in Health Care, Baltimore, USA, 45-51, doi: 10.1518/HCS-2012.945289401.008
9.
FrenchS.BedfordT.. (2011), Human reliability analysis: A critique and review for managers, Safety Science, 49(6), 753-763, doi: 10.1016/j.ssci.2011.02.008
10.
JoiceP.HannaG.B.CushcieriA. (1998), Errors enacted during endoscopic surgery – a human reliability analysis, Applied Ergonomics29(6), 409–414, doi: 10.1016/S0003-6870(98)00016-7
11.
KruseRDoringCh.LesotM.-J. (2007), Fundamentals of Fuzzy Clustering. In: Advances in Fuzzy Clustering and its Applications, eds.Valente de OliveiraJ.PedryczW.Wiley, 434, doi: 10.1002/9780470061190.ch1
12.
LiuK. F. R.Che-FanLu (2009), BBN-Based Decision Support for Health Risk Analysis, Proc. of the 2009 Fifth Int. Joint Conf. on INC, IMS and IDC, 696-702, doi: 10.1109/NCM.2009.187.690
13.
LevashenkoV.ZaitsevaE.. (2016), Reliability estimation of healthcare systems using Fuzzy Decision Trees, Proc. of the Federated Conf. on Computer Science & Information Systems, Gdansk, Poland, 331-340.
14.
LyonsM.AdamsS.. (2004) Human reliability analysis in healthcare: A review of techniques, Int. J. of Risk and Safety in Medicine, 16(4), 223–237, doi:
15.
MitraS.KonwarK.M.PalS.K. (2002), Fuzzy Decision Tree, Linguistic Rules and Fuzzy Knowledge-Based Network: Generation and Evaluation. Journal of IEEE Trans. on Syst., Man Cybernetics — Part C: Applications and Reviews, 32, 328-339, doi:10.1109/TSMCC.2002.806060
16.
OlaruC.WhenkelL. (2003), A Complete Fuzzy Decision Tree Technique, Fuzzy Sets and Systems, 221-254, doi: 10.1016/S0165-0114(03)00089-7
PandyaD.PodofilliniL.. (2015), A method for Human Reliability Analysis in radiotherapy: Identification and characterization of influencing factors. In: Podofillini. (Eds) Safety and Reliability of Complex Engineered Systems, Taylor & Francis Group, 3096-3076, doi: 10.1201/b19094-405
19.
StantonN.A.BaberC. (2002), Error by design: methods for predicting device usability, Design Studies, 23(4), 363-384, doi: 10.1016/S0142-694X(01)00032-1
20.
WittenI.H.FrankE.HallM. A. (2011). Data mining: practical machine learning tools and techniques, Elsevier.
21.
ZaitsevaE.LevashenkoV. (2016), Construction of a Reliability Structure Function Based on Uncertain Data, IEEE Trans on Reliability, 65(4), 1710-1723, doi: 10.1109/TR.2016.2578948
22.
ZaitsevaE.KvassayM.. (2015), Estimation of a Healthcare System Based on the Importance Analysis. In: PancerzK.ZaitsevaE. (eds) Computational Intelligence, Medicine and Biology: Selected Links. Springer, 3-22, doi: 10.1007/978-3-319-16844-9_1
