Managing and Predicting the Number of Health Insurance Claims in Ghana Based on Big Data and Time Series Analysis: A Case Study of Kumasi Metropolis, Ghana

Abstract

This study seeks to improve the process of managing and securing personal information (name, age, place of residence, telephone number, disease and so on) of the National Health Insurance Scheme (NHIS) subscribers of Ghana. Data was collected from the National Health Insurance Authority (NHIA) in Kumasi, Ghana on claims dating from 2010 to 2016. Big data methodology and Seasonal Auto Regressive Integrated Moving Average (SARIMA)  model was used to study and analyze the trend of health insurance claims and its future prediction claims.Our result showed an overall decrease in the number of claims from 2010 to 2016 and revealed that, the NHIA is faced with challenges in handling claims submitted to it by its clientele. An increasing trend was predicted from 2017 to 2022based on the model. Henceforth, the challenges of NHIA from the results of our study are attributable to inflated claims by clientele. NHIA efficiency can be improved by establishing a system that validates and controls claims.