An Implementation Of A Repository For Healthcare Insurance Using MongoDB

Abstract

The explosive growth of unstructured data in the National Health Insurance Scheme (NHIS) in Nigeria has given rise to the lack of an appropriate data storage mechanism to house data in the Scheme. This paper x-rayed these data storage challenges with a view to implementing a storage mechanism that can handled large volume and different formats of data in the Scheme. The NHIS is currently using the paper-based, file and cabinet data storage system with some of the data stored in the form of PDF, Excel and image files on the computer system. This has led to serious challenges ranging from the loss of data, lack of appropriate data storage facilities to accommodate the data to the delay in the administration of quality care to beneficiaries of the Scheme. Also, the diversity of data with the ever-growing datasets which is also generated at very high rate has also constituted a major challenge for NHIS. This research therefore developed a computer-based data storage system using MongoDB which has full index support, replication, high availability and auto-sharding. The design was done with Enterprise Application Diagrams and implemented using Java Programming Language, MapReduce Framework and MongoDB. The study shows that there are inequities in the delivery of services within the NHIS in Nigeria due to lack of proper storage medium. This is responsible for the ineffectiveness and inefficiency of healthcare services received through the Scheme. In conclusion, this research has provided the stakeholders with access to information more easily, which will enable them to plan, evaluate, and collaborate more effectively.
 Keywords: Big Data, NHIS, Storage, MongoDB, Data, Analytics.

A Mathematical Approach to Healthcare Insurance Data Analytics

“…In most instances, waste is not considered as negligent actions by fraudsters but rather the ill use of resources. Abuse comprises actions that may directly or indirectly, bring about unnecessary costs to the healthcare insurance program, improper payment, payment for services that fail to meet professionally recognized standards of care, or medically unnecessary services [25], [28], [31], [32], [33]. Abuse consists of payment for items or services when there is no legal entitlement to that payment, and the provider has not knowingly and intentionally misrepresented facts to obtain payment [25].…”

“…Most works done in the analytics of healthcare insurance data in other countries have been in the area of combating fraud. Though other aspects like the collection of data have been fully automated and hence, there are no issues with regards to delays in the processing of the other data [24][26] [28][29] [31][32] [34]. Many works have been done in this area but none has come up with an Independent Mathematical Expressions for the analytics.…”