Page 13 - Building Big Data Applications

Chapter 1 Big Data introduction 7

Metadata & MDM

Clinical Data
Lab Data Standard
Processing Engine Current EDW
Reports
Machine Data
UA ARCHITECTURE Analy cs
Image Data
Drug Data ELT Engine
Therapeu c Data
Financial Data New Processing
Big Data EDW
Engine Ad-Hoc
Claims Data
Reports
Social Media Data
Security & Infrastructure
FIGURE 1.1 Prototype solution flow.

insights and opportunities. We can convert research notes from doctors that have been
dormant into useable data, and create a global search database that will provide more
collaboration and offer possibilities to share genomic therapy research.
When we can provide better cures and improve the quality of care, we can manage
patient health in a more agile manner. Such a solution will be a huge step in reducing
healthcare costs and fixing a broken system.
Eventually, this integrated data can also provide lineage into producing patient
auditing systems based on insurance claims, Medicaid, and Medicare. It will also help
isolate fraud, which can be a large revenue drain, and will create the ability to predict
population-based spending based on disease information from each state. Additionally,
integrated data will help drive metrics and goals to improve efficiency and ratios.
While all of these are lofty goals, Big Data-based solution approaches will help create
a foundational step toward solving the healthcare crisis. There are several issues to
confront in the data space, such as quality of data, governance, electronic health record
(EHR) implementation, compliance, and safety and regulatory reporting. Following an
open source type of approach, if a consortium can be formed to work with the U.S.
Department of Health and Human Services, a lot of associated bureaucracy can be
minimized. More vendor-led solution developments from the private and public sectors
will help spur unified platforms that can be leveraged to create this blueprint.
Big Data Infrastructure is an interesting subject to discuss, as this forms the crux of
how to implement Big Data applications. Let us take a step back and look at enterprise
applications running across the organization.