Abstract
The absconding behaviour of a patient or leaving the hospital against medical advice is a matter of concern as in the both situations it might create risk for the patients, the people around them and for the hospital. This study predicts various factors responsible for absconding and LAMA cases with purpose to reduce the chances of their occurrence. Various classification techniques were used for the prediction and the comparison of classifier is done on the basis of their performance. Age, gender, sponsored category, ward and doctor were observed as significant factors associated with such cases. This study will help the hospital in early detection of such patients and reduce the occurrence of these events. Thus, it will help the hospital in improving the health and saving the life of patients of such cases.
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Authors would like to thank the hospital for providing the data and helping out with the queries.
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Chaudhary, R., Garg, A., Bhadauria, M. (2018). Predictive Analytics for LAMA and Absconding Behaviour of Patient. In: Satapathy, S., Bhateja, V., Das, S. (eds) Smart Computing and Informatics . Smart Innovation, Systems and Technologies, vol 78. Springer, Singapore. https://doi.org/10.1007/978-981-10-5547-8_66
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DOI: https://doi.org/10.1007/978-981-10-5547-8_66
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