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RNH Hospital Application and Data Analysis

International Journal of Research in Signal Processing, Computing & Communication System Design

Volume 5 Issue 1

Published: 2019
Author(s) Name: Puja Bharti Singh, Bhakti Khera, Vipul Bangad and Purshottam Assudani | Author(s) Affiliation: Shri Ramdeobaba College of Engineering and Management, Univ. of Nagpur, Maharashtra, India.
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Abstract

This application incorporates various factors needed for smooth working and management of RNH hospital. This hospital application allows administrator to store and manage various resources according to patients’ and doctor’s requirements. The application is developed to eliminate human efforts in managing hospital records and data manually. The system also stores the doctor’s data in a well defined manner. The doctor’s details include his name, number, experience, consultant type specialty and current doctor’s status. This app also provides the information offered by the hospital and details about health packages, data analysis and billing generation. User can also request an appointment as per his/her requirements and ask queries. This application uses the data which is collected from RNH Hospital to perform analysis: on medicines which compares Medicines (on the basis of types of Medicines); set values (Above & Below), on Hospital Growth which compares and computes average (Number of Registrations & Surgeries), on Treatments; comparing them (on the basis of Male & Females, Age Groups) by applying statistical and inferential analysis like Mean, Median, Standard deviation, T-test and Analysis of Variance (ANOVA). The application uses Android Studio as a front end, SQL Server to store it’s back end data and Morris.js using Hypertext Preprocessor (PHP) and Java Script Object Notation (JSON) to perform data analysis. The back end data includes accommodation details and related doctor’s data for effectively managing a hospital. The analyzed data is in graphical format which includes bar graph, pie-chart.

Keywords: ANOVA, Application, Data analysis, JSON, PHP, T-test.

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