Big Data in Healthcare

The use of big data in healthcare can help aids in the provision of more efficient operations and insights. The healthcare industry is facing several challenges including the outbreak of new diseases and the need to maintain optimal operational efficiency. Big data ensures the provision of advanced patient care. Electronic health records play a crucial role in collecting medical and demographic data like clinical data, lab test, medical conditions, and diagnoses that aids in the provision of quality care. Big data also improves operational efficiency. Healthcare organizations use big data as a component of their business intelligence strategy of examining historical patient admission rates and to assess the efficiency of the staff. This can help reduce healthcare cost offer better care through predictive analytics. Additionally, big data help find a cure for diseases. Some medications tend to work for some people but not for others. Big data helps uncover unknown correlations, hidden insights, and patterns, by looking at large data sets.

The use of big data in healthcare also has some challenges. One of them is the uncertainty of data management. It encourages the use of an extensive range of patient data management frameworks and tools whose designs supports analytical and operational processing. Additionally, the process of data transmission, access, and delivery of the information from a wide range of sources can result in the loss of privacy of patient information. This may interfere with the patient’s privacy.

From research, one of the strategies that can be used to mitigate the risk of using big data in healthcare effectively is to develop centralized identity management. This solution would help secure big data environments by offering access controls, user-level auditing, and privilege management. This would ensure that the data is managed correctly and patient private data are not interfered with.