Big data accessibility issues for key medical personnel

Healthcare systems rely on vast data repositories serving a variety of purposes which include business functions and patient medical records. With recent advances in big data analytics, the latent value for all this data has become more apparent yet operational use has lagged behind. Healthcare operations suffer from multiple and complex issues making harnessing the potential of big data more important than ever. This article describes use of the ArchiMate® modeling language to adopt an organizational architecture language for the purpose of building a model for personalization of healthcare-related big data. This model describes how data can be made accessible to healthcare professionals in a way that allows clinicians to generate clinical, operational, and managerial value from the data with minimal involvement of additional data professionals. The article concludes with a case study proof-of-concept demonstrating the value of the approach and suggestions for implementation.