Using Distributed Data over HBase in Big Data Analytics Platform for Clinical Services

Table 1

Big Data applications related to clinical services [11–13, 18].

Clinical services	Healthcare Applications
R&D	(i) Targeted R&D pipeline in drugs and devices, clinical trial design, and patient recruitment to better match treatments to individual patients, thus reducing trial and failures and speeding new treatments to market, follow on indications, and discover adverse effects before products reach the market
Public health	(i) Targeted vaccines, e.g., choosing the annual influenza strains; (ii) Identify needs, provide services, and predict patients at risk to prevent crises, especially for the benefit of populations
Evidence-based medicine	(i) Combine and analyze a variety of structured and unstructured data-EMRs, financial and operational data, clinical data, and genomic data to match treatments with outcomes, predict patients at risk for disease or readmission, and provide more efficient care
Genomic analytics	(i) Make genomic analysis a part of the regular medical care decision process and the growing patient medical record
Device/remote monitors	(i) Capture and analyze in real-time large volumes of fast-moving data from in-hospital and in-home devices, for safety monitoring and adverse prediction
Patient profile analytics	(i) Identify individuals who would benefit from proactive care or lifestyle changes, for example, those patients at risk of developing a specific disease (e.g., diabetes) who would benefit from preventive care