BIG DATA ANALYTICS: NIGERIAN HEALTH SECTOR

ABSTRACT

 

The study “Big Data Analytics: Nigerian Health Sector Approach was aimed to examine the health sector if they are using big data analystics in day-to-day activities. The objective of this study was to know whether big data analytics in Nigerian health sector is been implemented or available. The continuous advances in today’s digital universe and integration of computing into virtually every facet of human life are no doubt making the concept of Big Data a ubiquitous paradigm for deploying novel technologies/applications hitherto not practicable by conventional methods. Big Data, a general term for the massive amount of digital data being generated from different sources, extremely large, structured / unstructured too complex for analysis through conventional relational database techniques. It is estimated that 2.5 quintillion bytes of data is added each day of which approximately 90% is unstructured. This Big Data offers new opportunities for discovery, value creation, and rich business intelligence for decision support in any organization. Nigeria as a country is steadily moving towards digitizing some of the government departments, scheme and services in Federal, State and Local government levels. Due to increase in digital literacy of the people and availability of data intensive network access that is emerging, the need for use of big data applications is on the increase. Interestingly, gathering and processing of vast amounts of data is not new to humanity. What is new is the speed at which one can process a complex data and extracting actionable business intelligence or big insight from data. Volume, Variety and Velocity are characteristics nature of big data that need careful choice of relevant technology and framework to handle. Big Data is therefore redefining the landscape of data management, from extract, transform, and load, or ETL processes to new technologies (such as Hadoop) for cleansing and organizing unstructured data in Big-Data applications, bringing up challenges of complexity, security, and risks as well as a need for new technology skills for analytics. In this paper, the model that illustrates how analytics of Big Data can result in the transformation of the government by increased efficiency and effectiveness in the health sector with citizen engagement in decision-making will be discussed.

 

 

 

 

 

 

TABLE OF CONTENTS

Pages

Title page                                                                                                    i

Approval                                                                                                    ii

Certification                                                                                                         iii

Dedication                                                                                                  iv

Acknowledgement                                                                                                v

Abstract                                                                                                      vi

Table of contents                                                                                        vii

 

CHAPTER ONE: INTRODUCTION                                                      1

1.1     Background of study                                                                        1

1.2     Statement of the Problems                                                                5

1.3     Aims/Objectives                                                                                6

1.4     Significant of the Study                                                                    6

1.5     Scope of the study                                                                                      7

1.6     Operational definition of terms                                                                  7

 

CHAPTER TWO: LITERATURE REVIEW                                         9

2.1     Concept of Big Data Analytics                                                                   9

2.2     Characteristics of Big Data.                                                              15

2.3     Big Data in Nigeria                                                                          18

2.4     Big Data Analytics – (Preventing Medication Errors)                   36

2.5     Identifying High-Risk Patients                                                                 37

2.6     Reducing hospital costs and wait times                                           37

2.7     Preventing security breaches and fraud                                         38

2.8     Enhancing patient engagement and outcomes                               41

2.9     Widespread use of electronic health records                                               42

2.10   Healthcare Crime Investigation Approaches                                               42

2.11   Nigerian National Health Insurance Scheme                                               48

2.12   Theoretical Framework                                                                     50

 

CHAPTER THREE: METHODOLOGY                                                         55

 

CHAPTER FOUR: DATA ANALYSIS                                                   64

4.1     Detailed Analysis of Organizations in Health Sector                        64

4.2     Summary Analysis of Organizations in Health Sector                      67

4.3     Implications of Study                                                                       68

 

CHAPTER FIVE: SUMMARY, CONCLUSION AND

RECOMMENDATIONS                                                                          71

5.1     Summary                                                                                          71

5.2     Conclusion                                                                                        72

5.3     Recommendations                                                                                      75

References                                                                                         77