Big Data in Healthcare: Are we getting useful insights from this avalanche of data?

The benefits of deriving useful insights from avalanche of data available everywhere cannot be overemphasized. Big Data analytics can revolutionize the healthcare industry. It can also ensure functional productivity, help forecast and suggest feedbacks to disease outbreaks, enhance clinical practice, and optimize healthcare expenditure which cuts across all stakeholders in healthcare sectors. Notwithstanding these immense capabilities available in the general application of big data; studies on derivation of useful insights from healthcare data that can enhance medical practice have received little academic attention. Therefore, this study highlighted the possibility of making very insightful healthcare outcomes with big data through a simple classification problem which classifies the tendency of individuals towards specific drugs based on personality measures. Our model though trained with less than 2000 samples and with a simple neural network architecture achieved mean accuracies of 76.87% (sd=0.0097) and 75.86% (sd=0.0123) for the 0.15 and 0.05 validation sets respectively. The relatively acceptable performance recorded by our model despite the small dataset could largely be attributed to number of attributes in our dataset. It is essential to uncover some of the many complexities in our societies in relations to healthcare; and through many machine learning architectures like the neural networks these complex relationships can be discovered