Statistical Analysis And Forecasting Report Using Aadhar Card

Abstract

Aadhar controlled Statistical Medical report and Decision project starts with fine data collection from all departments in a hospital and can be extended to every hospital without any change in the project. Data is the backbone of any report so entering data/cleaning data and maintaining them up to standard is critical part in this work. In this project, the Patients, Doctors, Pharmacy, Emergency, Roomdetails, Nurse, Attender, Ambulance, Driver and in/out patient data were observed. Here the best intelligent data structure for this project was designed by connecting each table by their unique field and also will have all possible patients flow in a hospital like emergency inpatient to outpatient etc. The project and the data have been designed in such a way to give all possible statistical and analytical report in different format like summary/detail/graph with states. Data has been collected independently in each department and all data will be interconnected through AADHAR(as a key). All the information about the hospitals was collected in a particular city and then using SAS technology, we are able to create thousands of reports from this datasets. This project is unique in a way to apply this in to other departments like transport, municipal, judiciary etc. with minimal changes and also can be scalable to apply this in to bigger data like collection of data for a state or country.

Keywords: AADHAR information, Data Analysis, SAS technology.

Introduction

Human data analysis is characterized by a deep and short-range investigation based on their experienced “cases”, whereas one of the most distinguished features of computer based data analysis is to enable us to understand from the different viewpoints by using “cross-sectional” search. It is expected that the intelligent reuse of data in the hospital information system provides to grasp all the characteristics of university hospital and to acquire objective knowledge about how the hospital management should be and what kind of medical care should be served in the university hospital. In this paper, several exploratory data analysis techniques were applied to the data extracted from hospital information systems.

The results show several interesting cases, which suggests that the reuse of stored data will give a powerful tool to support a long-period management of a university hospital. This project provides full automation and streamlines the important modules of Patient identification, Staff allocation, Doctor details, Ambulance details, Room details and other important details in hospital in a report manner. Gathering user requirement is one of the most critical tasks in almost every project development. Complete requirements of the user cannot be perceived at a given point of time. The reason is that they evolve with time, mostly they are observed after the system deployment. This evolutionary nature of user’s requirements poses difficulties in almost every phase of software development process of any project.

International Journal of Engineering & Technology this project gives an approach to overcome this problem. This project mainly concentrates on the data collected in a city through various departments like Municipal office, Hospital, Motor vehicle department, Universities, Public welfare departments etc. All the data collected independently from each department will be interconnected through AADHAR(as a key). In this paper, all the information about hospitals in a particular city was collected and then using SAS technology, created thousands of reports from this datasets.

Background

Hospital Information System: On the other hand, clinical information has been stored electronically as a Hospital Information System (HIS). The database stores all the data related with medical actions, including accounting information, laboratory examination, treatment details and patient records described by medical staffs. Incident or accident reports are not exception: they are also stored in HIS as clinical data. Thus, this system can be a cyberspace in a hospital where all the results of medical actions are stored with temporal information. This work can be viewed as distributed large-scale and multimodal spatiotemporal databases. Thus, dealing with cyberspace in a hospital will be a new challenging problem in hospital administration, and of course spatiotemporal data mining plays a central role in this challenge.

Basic Order

For example, prescription can be viewed as order from a doctor to a pharmacist and prescription order is executed as follows.

1. Outpatient Clinic
2. A prescription given from a doctor to a patient
3. The patient bring it to medical payment department
4. The patient bring it to pharmaceutical department
5. Execution of order in pharmacist office
6. Delivery of prescribed medication
7. Payment

The second to fourth steps can be viewed as information propagation: thus, if we transmit the prescription through the network, all the departments involved in this order can easily share the information and execute the order immediately. This also means that all the results of the prescription process are stored in HIS. These sharing and storing processes can be easily stored as a database by using conventional IT and DB technologies: thus, HIS can also be viewed as cyberspace of medical actions. Cardinalities: Binary Relationship A binary relationship in the ER diagram is shown below.

International Journal of Engineering & Technology

Analysis of hospital data

Objective

The objectives of this research is to investigate what kind of knowledge can be extracted by statistical methods from the datasets stored in the hospital information system, especially useful for future hospital management and decision support.

Method: Data Analysis

Descriptive statistics, exploratory data analysis and statistical tests were applied to the dataset extracted only from the discharge summaries for the analysis of patient basic information (gender, age and occupation), outcome and the number of the days in hospitals and diseases, including their chronological trends. The discharge summaries were analyzed by descriptive statistics, exploratory data analysis, statistical tests, regression analysis and generalized linear model. SAS was used for these analyses.

Modules

List of Modules

Module description gives the detailed information about the module and its supported components which is accessible in different manners. It also gives the clear cut working study of the whole project. The project comprises of few modules where the process is implemented step by step.

Extraction Transformation and Loading(ETL)

In this module, the data entered in text file or excel will be loaded using SAS ETL process into SAS Table/Dataset. The process of extracting data from source systems and bringing it into the data warehouse is commonly called ETL, which stands for extraction, transformation, and loading. ETL is short for extract, transform, load three database functions that are combined into one tool to pull data out of one database and place it into another database. Extract is the process of reading data from a database.

Data Cleaning

Process In this module, the collected data has been identified and inconsistent data can be correlated and comparing with missing and non-missing data for the identification. Data entered by staff in each department may not be accurate and can have lot of misleading information. This will be cleaned and standardized and loaded into SAS datasets.

Report Creation

Cleaned data from SAS datasets will be created into summary graph or detailed reports based on the request from each department.

Conclusion

In this proposed work, several exploratory data analysis techniques was applied to the data extracted from hospital information systems. The results show several interesting parts, which suggests that the reuse of stored data will give a powerful tool to support a long-period management of a hospital. The results obtained above also show the possibility that combination of data from discharge summaries and data from accounting information system enables us to discuss the profitability of the hospital in a quantitative way and provides us a basic tool for the management analysis of a hospital. Using this information system, some future results also has been predicted. The results are given in report format. There are three types of reports created which includes Summary report, detailed report and Graph report.