Analysis of Human Error in Healthcare Industry: an Indian Perspective
R. K. A. Bhalaji1, S. Bathrinath2, S. Saravanasankar3
1R. K. A. Bhalaji, Department of Mechancical Engineering, Kalasalingam Academy of Research and Education College, Krishnankoil (Tamil Nadu), India.
2S. Bathrinath, Department of Mechancical Engineering, Kalasalingam Academy of Research and Education College, Krishnankoil (Tamil Nadu), India.
3S. Saravanasankar, Department of Mechancical Engineering, Kalasalingam Academy of Research and Education College, Krishnankoil (Tamil Nadu), India.
Manuscript received on 27 November 2019 | Revised Manuscript received on 16 December 2019 | Manuscript Published on 31 December 2019 | PP: 157-162 | Volume-8 Issue-4S2 December 2019 | Retrieval Number: D10341292S219/2019©BEIESP | DOI: 10.35940/ijrte.D1034.1284S219
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© The Authors. Blue Eyes Intelligence Engineering and Sciences Publication (BEIESP). This is an open access article under the CC-BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/)
Abstract: In healthcare sector, employing human knowledge, on a larger scale, in the decision making process in identifying the risk sources is very common, and often the human error in the process results in adverse effects of unrecognized risks. Hence, the impact of human error in employing the human knowledge remains a major problem. To minimize the human error a fuzzy based risk assessment method using Ranked Risk Breakdown Structure (RRBS) model is proposed in this work. The proposed method is able to rank the risk resources on the basis of a risk score generating mechanism based on the probability of occurrence of risk and outcome of the risk. By recognizing the high ranking risk resources, that is, the risk drivers at higher levels of seriousness/severity, this fuzzy based methodology nullify the existing common human errors. The proposed methodology is validated with the actual past data of one decade period, the occurrence of risk and its effect in a healthcare industry situated in an urban city of India. The results of the experimentation reveal that the proposed methodology can be successfully implemented in all other industries in healthcare sector to minimize the human error in risk recognition. The suggested model is helpful for industrial managers/practitioners to tackle risk factors related with complex works.
Keywords: Fuzzy Set, Risk Assessment, RRBS.
Scope of the Article: Industrial Engineering