Engineering Scalable, Secure, Multi-Tenant Cloud for Healthcare Data
| Autor: | Daniel J. Dean, Anca Sailer, Senthil Bakthavachalam, Paul R. Bastide, Kirk A. Beaty, Yichong Yu, Rohit Ranchal, Yaoping Ruan, Shakil M. Khan, Yu Gu |
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| Rok vydání: | 2017 |
| Předmět: |
0301 basic medicine
Cloud computing security Computer science business.industry Process (engineering) Cloud computing Computer security computer.software_genre Data science Personalization 03 medical and health sciences 030104 developmental biology Analytics Spark (mathematics) Scalability business computer Protected health information |
| Zdroj: | SERVICES |
| DOI: | 10.1109/services.2017.13 |
| Popis: | 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., dataisolation) which most cloud-based platforms do not currentlysupport in their offerings. This makes it difficult to leveragemany technologies well suited to the cloud (e.g., Apache Spark)to process PHI. To address this issue, we have developedthe Watson Health Cloud (WHC), a cloud-based platformfor the storage and analysis of large amount of PHI. TheWHC enables all the features necessary to store and processPHI, with little customization needed by the end-user. Thispaper describes the lessons learned from developing a cloudplatform for PHI. Specifically, we discuss the architecture andimplementation challenges we faced throughout development. We hope the insights gained from our experiences help otherswhen designing frameworks and applications which processPHI. |
| Databáze: | OpenAIRE |
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