Design and Implementation of Data Mining For Medical Record System

Design and Implementation of Data Mining For Medical Record System

ABSTRACT

Data mining is the extraction of hidden predictive information from large database which helps in predicting future trend and behavior thereby helping management make knowledge driven decisions.

The data mining tool designed is to aid in quick access and retrieval of patients information to avoid time wasted in retrieving of such data from hospitals data warehouse. The data mining tool was also designed to discover hidden pattern that helps in decision making by management.

Structured System Analysis and Design Methodology were used in the analysis of the existing system which also provided a guide for the design of the proposed system.

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TABLE OF CONTENTS

Approval Page………………………………………………………………..i
Certification Page…………………………………………………………… ii
Dedication……………………………………………………………………iii
Acknowledgement……………………………………………………………v
Table of Contents…………………………………………………………… vi
Abstract……………………………………………………………………… x
CHAPTER ONE
INTRODUCTION
1.1 Background of Study……………………………………………. 1
1.2 Statement of the Problem……………………………………….. 2
1.3 Objectives of Study……………………………………………… 3
1.4 Significance of Study…………………………………………… 4
1.5 Scope of Study……………………………………………………4
1.6 Limitations of Study………………………………………….. …4
1.7 Definition of related terms…………………………………….… 5
CHAPTER TWO
REVIEW OF RELATED LITERATURE
2.1 Introduction……………………………………….. ………..7
2.2 Review of related literature………………………………….11
CHAPTER THREE
SYSTEM ANALYSIS AND METHODOLOGY
3.1 System analysis…………………………………..………16
3.2 Method of data collection…………………..……………..17
3.2.1 Interviewing key officer………………………………….17
3.2.2 Observation method………………………………………18
3.2.3 Examination of document…………………………………18
3.3 Analysis of the existing system……………..……………..18
3.3.1 Organization profile chart……………………………………18
3.3.2 Advantages of the existing system…………..….………….20
3.3.3 Disadvantage of the existing system…………….………….21
3.4 Analysis of the proposed system………………….…………21
3.4.1 Justification of the proposed system…………………………22
3.5 Methodology……………………………………………………23
3.5.1 Recommended appropriate mode…………………………….24
CHAPTER FOUR
SYSTEM DESIGN AND IMPLEMENTATION
4.1 Overview of design……………………………………………25
4.2 Main menu……………………………………………………..26
4.3 Program modules specification………………………………27
4.3.1 Database design and specification……………………………27
4.3.2 Input/output specification……………………………………28
4.3.3 Input form……………………………………………………29
4.3.4 Output form…………………………………………………..31
4.3.4.1 Medical record system………………………………..32
4.4 Flowchart of the proposed solution………………………….34
4.5 Choice and justification of programming language…………..35
4.6 System requirement ………………………………………….37
4.7 Implementation plan…………………………………………..37
4.7.1 Testing…………………………………………………………38
4.7.2 Conversion…………………………………………………….39
4.7.3 Training……………………………………………………….40
4.8 Maintenance details………………………………………….40
CHAPTER FIVE
SUMMARY, RECOMMENDATIONS, CONCLUSION
5.1 Summary………………………………………………….41
5.2 Review of achievements…………………………………..42
5.3 Areas of application………………………………………..42
5.4 Suggestion for further studies………………………………42
5.5 Recommendation……………………………………………43
5.6 Conclusion…………………………………………………..43
REFERENCES……………………………………………………45

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INTRODUCTION

Data mining, is the extraction of hidden predictive information from large database, is a powerful new technology with great potential to help companies focus on the most important information in their data warehouses.

Data mining tools predict future trends and behaviors, allowing businesses to make proactive, knowledge driven decisions. The automated, prospective analysis offered by data mining move beyond the analyses of past events provided by retrospective tools typical of decision support systems.

Data mining tools can answer business questions that traditionally were too time consuming to resolve. The scour databases for hidden patterns, finding predictive information those experts may miss because it lies outside their expectations.

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REFERENCES

Akukwe, A.C., & Uzoma, J.P. (1999). A Practical Approach to Electronic Data Processing. Owerri: Cherry Ben Publisher.
Anderson, R.G. (2002). Data Processing, Information System And Technology. London: Pitman Publishing Ltd.
Commer, J.M.A. (1987). Computer Model for Sales Territory Planning Decision Services. U.S.A: American marketing Association.
Ezeano, A.N. (1993). Computer User Resistance And Misconception. Britain:Minner‟s Press.
Hill, D.W. (1978). Computer in Medical Services. London: Macdonald AndEvans.
Igwe, S.O. (2002). Introduction to Information Processing and Basic Programing”. India: Micbad Publishers.

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