Today’s healthcare companies are using Hadoop to build healthcare platforms that can store and analyze large data sets, consisting of billions of objects. Organizations also need to be able to search and analyze disparate data sources such as patient populations, treatment protocols, and clinical outcomes to accelerate discovery and insight.
Leading Healthcare Organization
A leading healthcare organization collects petabytes of claims and treatment data. It plans to create a new data repository service for its enterprise customers who can leverage their own customer data and run expanded set of analytics. MapR is the only distribution that delivers on the multi-tenancy needs of this company by providing volume based isolated environment with quotas and secure access for the end users.
Healthcare Applications relying on Hadoop include:
- Health information exchange - Providers need to manage and share patient electronic health care records from mixed data sources (e.g., images, treatments, demographics) among the medical provider community.
- Healthcare service quality improvements and reduce number of hospitalizations - Improve Healthcare service quality and reduce number of hospitalizations.
- Drug Safety - Healthcare professionals need to understand drug safety and toxicity (e.g. interaction between drugs).
- Drug Development - Researchers need to make the drug development process more efficient by shortening testing time and reducing time spent on drugs with a low likelihood of success in order to get revenue-generating drugs to the market more quickly.
- Personalized Medicine - Targeted genetic sequencing of patients and tumors as well as gut biomes is beginning to provide real advances in treatment selection and detailed prognosis. However, this is causing an explosion in data sizes.
- N-of-1 Studies - Massive scale data collection is enabling highly detailed empirical examination and prediction of individual patient treatment responses, allowing investigations to proceed with dramatically smaller trial populations.