For the enormously complex healthcare system, big data is an invaluable asset with immense potential. Big data use cases in this sector are many and varied. In this post, we will limit ourselves to three, with special focus on data security.
Combating data breaches
2016 witnessed 106 major healthcare breaches, which resulted in the exposure of approximately 13.5 million records. Multiple data breaches at the same organization are all too common. Cyberattacks have become increasingly brazen, which is pretty counter-intuitive given the vast arsenal of cybersecurity solutions available today. Healthcare organizations that treat data breaches as just another IT issue risk losing trust and authority among the public. Inability to manage customer data reflects poorly on organization’ commitment to patient well-being and makes them appear callous and insensitive.
Big data is enabling organizations to analyze and control cyberattacks in ways not possible before. For instance, big data security analytics that heuristically analyzes security threats, can serve as the first line of defense against cyberattacks alongside human oversight and a powerful reporting engine. It analyzes unstructured data and extracts information that you wouldn’t have even thought of looking for.
Healthcare organizations need to apply a data perspective to security to put more effective controls in place. One approach would be to place controls around business processes that hold the most valuable and sensitive data. This can be enabled by examining data patterns and visualizing as well as effectively managing the organization’s data value chain. For organizations that cannot afford to deploy expensive security analytics software, smarter data-driven analyses can help identify processes that require the highest protection so more resources can be allocated in a targeted manner.
Gleaning insights from patient information to improve quality of care
Healthcare providers are integrating health care records across their hospitals and medical offices to build an integrated and comprehensive data hub. The goal is to leverage data at micro and macro levels, capturing insights that aid the delivery of more personalized patient experiences, improve outcomes and decrease costs.
Improving pharmaceutical R&D
Pharmaceutical companies have hastened their pace of zealously pursuing blockbuster drugs. Not every high-potential drug can provide the envisioned financial benefits. Sometimes, they come at the cost of less profitable but important drugs that are required extensively in certain parts of the world (ex : drugs for treating dengue fever in developing countries).
Big data and predictive analytics can help the pharma industry make informed assessments on which drugs have the highest probability of success, and allocate their investments more efficiently as well as responsibly.