- Title Information
- Title
- Enabling use of high performance computing for secure processing of protected health information
- Name:
Personal
- Name Part
- Bill, Robert
- Role
- Role Term:
Text (marcrelator)
- author
- Name:
Personal
- Name Part
- Melton, Genevieve B.
- Role
- Role Term:
Text (marcrelator)
- author
- Name:
Personal
- Name Part
- Gottschalk, Bart
- Role
- Role Term:
Text (marcrelator)
- author
- Name:
Personal
- Name Part
- Ring, Andrew
- Role
- Role Term:
Text (marcrelator)
- author
- Name:
Personal
- Name Part
- Dale, Justin L.
- Role
- Role Term:
Text (marcrelator)
- author
- Name:
Personal
- Name Part
- Viñals, Jorge
- Role
- Role Term:
Text (marcrelator)
- author
- Name:
Personal
- Name Part
- Lamblin, Anne-Francoise
- Role
- Role Term:
Text (marcrelator)
- author
- Name:
Personal
- Name Part
- Pakhomov, Serguei
- Role
- Role Term:
Text (marcrelator)
- author
- Type of Resource
- text
- Genre (Local)
- podium abstracts
- Origin Information
- Date Created
(keyDate="yes", encoding="w3cdtf")
- 2015
- Language
- Language Term:
Code (ISO639-2B)
- eng
- Note
(displayLabel="Source")
- Electronic Health Record
- Note
(displayLabel="Method")
- Natural Language Processing
- Abstract
- Analyzing large clinical note collections using natural language processing (NLP) requires computational resources in excess of that typically available internal to academic health centers. External high performance computing (HPC) center have sufficient resources; however, strict HIPAA compliance requirements limit their use for processing Protected Health Information (PHI). We have developed a protocol for using HPC resources while minimizing security risks to PHI by using encrypted tunnels, ensuring that PHI data is never written to shared disk space, and by isolating PHI processing from other users. Formal independent evaluation confirmed the protocol poses minimal risk to PHI and is compliant with HIPAA. This protocol and approach can significantly expand the ability of medical centers to leverage computationally intensive processing securely and cost-effectively.
- Note:
funding
- This research was supported by Agency for Healthcare Research & Quality grant (#R01HS022085) (GM) and National Institutes of Health (#R01LM011364 (GM), #R01GM102282 (SP) and #8UL1TR000114 (Blazer))
- Note
- Podium abstract from the 2015 AMIA Annual Symposium
- Related Item:
Host
(displayLabel="Published in")
- Title Information
- Title
- AMIA Joint Summits on Translational Science Proceedings
- Origin Information
- Date Created
- 2015
- Date Created
(keyDate="yes", encoding="w3cdtf")
- 2015
- Physical Description
- Extent
- p. 244-245
- Access Condition:
use and reproduction
(href="https://creativecommons.org/licenses/by-nc/4.0/")
- This work is licensed under a
Creative Commons Attribution-NonCommercial 4.0 International License
- Access Condition:
logo
(href="https://i.creativecommons.org/l/by-nc/4.0/88x31.png")