Abstract

Cloud-based analytics allow for inexpensive processing of large amount of data. However, processing protected health information (PHI) in cloud is a challenging task due to strict regulations (e.g., HIPAA) requiring features (e.g., data isolation) which most cloud-based platforms do not currently support in their offerings. This makes it difficult to leverage many technologies well suited to the cloud (e.g., Apache Spark)to process PHI. To address this issue, we have developed the Watson Health Cloud (WHC), a cloud-based platform for the storage and analysis of large amount of PHI. The WHC enables all the features necessary to store and process PHI, with little customization needed by the end-user. This paper describes the lessons learned from developing a cloud platform for PHI. Specifically, we discuss the architecture and implementation challenges we faced throughout development. We hope the insights gained from our experiences help others when designing frameworks and applications which process PHI.

Keywords:
Cloud computing Scalability Computer science Health care Computer security Database Operating system

Metrics

10
Cited By
2.97
FWCI (Field Weighted Citation Impact)
5
Refs
0.92
Citation Normalized Percentile
Is in top 1%
Is in top 10%

Citation History

Topics

Scientific Computing and Data Management
Social Sciences →  Decision Sciences →  Information Systems and Management
IoT and Edge/Fog Computing
Physical Sciences →  Computer Science →  Computer Networks and Communications
Cloud Data Security Solutions
Physical Sciences →  Computer Science →  Information Systems

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