One of the lessons learnt from the first Gulf War of 1990 was that health information must be captured in a machine computable manner and it must be globally available.

The Military Health System developed an Electronic Health Record (EHR) family of systems that captures standardized, computable patient data in Garrison (the base) and Theater( where the action is).

The volume of clinical encounters captured electronically
was:

1.       More than 135 million for Garrison outpatient

2.       More than 3 million for Theater outpatient

3.       67% of Department of Defense’s inpatient beds at 30 sites

Post adoption opinion of EHRs brings to light that increased interoperability and more complete patient records would increase the EHR potential substantially. Core clinical data can be reinforced with images, voice transcripts and procedural videos. As data continues to pile up, Big Data and Analytics is the obvious solution for actionable intelligence.

NiyamIT’s proven track record of implementing Big Data clusters to process peta byte scale data, gives a definitive edge to manage complex EHR records. Our strategy of working with Data Partitions based on regions for FEMA, can be applied to EHR/EMR records to enable faster delivery of information.

Big data architecture paradigms are classified into two models, the traditional batch processing and real-time processing. The most popular technologies representing these are Hadoop with MapR and Storm. The use of Lambda architecture combines these two models of data processing to achieve the best of both worlds for fast and large scale processing.

Our solutions are based on the key drivers of Speed, Reliability, Usability, Efficiency, Interoperability, and Health record completeness.

Author: Shweta Katre

Sources: Office of the Chief Information Officer, Military Health Systems www.health.mil

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