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Publication Type : Conference Paper
Publisher : Proceedings of the International Conference on Inventive Communication and Computational Technologies, ICICCT 2017
Source : Proceedings of the International Conference on Inventive Communication and Computational Technologies, ICICCT 2017, Institute of Electrical and Electronics Engineers Inc., p.318-322 (2017)
ISBN : 9781509052974
Keywords : Data mining, Diagnosis, Effective utilization of resources, Health care, Healthcare process, Hospital information systems, Hospitals, Miners, Physical resources, Process Discovery, Process enhancements, Process mining, Productive process, PROM, Statistical tests
Campus : Mysuru
School : School of Arts and Sciences
Year : 2017
Abstract : The main aim of a hospital is to provide an effective and efficient environment for the patient which supports effective utilization of resources for the diagnostic center which reduces the complexity of diagnosis process. In order to do so it is necessary to have an accurate view of care flows under consideration. In this paper we apply process mining techniques to obtain meaningful knowledge about this flows, e.g., to discover typical paths proceeded by particular group of symptoms that create a disease of a patient. In this paper lab test dataset is considered as a baseline scenario where in productive process models are created and checked for the efficiency using inductive visual miner algorithm. In order to do so we extracted relevant event logs from hospital information system in that we have taken diagnosis of lab test logs using ProM framework. Using inductive visual miner we are able to generate a soundness model for a health sector. The result shows how the process mining can be used to provide new insight that simplifies upgrading of existing health care flows and give insight about how it can be improved. © 2017 IEEE.
Cite this Research Publication : Ganesha K., Soundarya M., and Supriya K. V., “The best fit process model for the utilization of the physical resources in hospitals by applying inductive visual miner”, in Proceedings of the International Conference on Inventive Communication and Computational Technologies, ICICCT 2017, 2017, pp. 318-322.