Identifying a Medical Department Based on Unstructured Data: A Big Data Application in Healthcare

Author:

Bansal Veena,Poddar Abhishek,Ghosh-Roy R.

Abstract

Health is an individual’s most precious asset and healthcare is one of the vehicles for preserving it. The Indian government’s spend on healthcare system is relatively low (1.2% of GDP). Consequently, Secondary and Tertiary government healthcare centers in India (that are presumed to be of above average ratings) are always crowded. In Tertiary healthcare centers, like the All India Institute of Medical Science (AIIMS), patients are often unable to articulate their problems correctly to the healthcare center’s reception staff, so that these patients to be directed to the correct healthcare department. In this paper, we propose a system that will scan prescriptions, referral letters and medical diagnostic reports of a patient, process the input using OCR (Optical Character Recognition) engines, coupled with image processing tools, to direct the patient to the most relevant department. We have implemented and tested parts of this system wherein a patient enters his symptoms and/or provisional diagnosis; the system suggests a department based on this user input. Our system suggests the correct department 70.19% of the time. On further investigation, we found that one particular department of the hospital was over-represented. We eliminated the department from the data and performance of the system improved to 92.7%. Our system presently makes its suggestions using random forest algorithm that has been trained using two information repositories-symptoms and disease data, functional description of each medical department. It is our informed assumption that, once we have incorporated medicine information and diagnostics imaging data to train the system; and the complete medical history of the patient, performance of the system will improve further.

Publisher

MDPI AG

Subject

Information Systems

Cited by 4 articles. 订阅此论文施引文献 订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献

1. Big Data y Fog Computing aplicados al sistema de la salud;Journal TechInnovation;2023-12-01

2. Supervised Learning-Based Classifiers in Healthcare Decision-Making;Proceedings of International Conference on Computational Intelligence and Data Engineering;2020-12-21

3. Data-Driven Approach To Patient Flow Management And Resource Utilization In Urban Medical Facilities;2020 IEEE 22nd Conference on Business Informatics (CBI);2020-06

4. Big Data Analytics and Firm Performance: A Systematic Review;Information;2019-07-01

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