[Air-L] Can Nvivo be used to removed PHI from free text?

Orlowski, Simone K. SORLOWSKI at mgh.harvard.edu
Wed May 17 12:06:56 PDT 2017


Hi all,

Our team is conducting a retrospective study involving electronic medical records (EMR) data and we are trying to identify tools that can help us automate the removal of PHI from unstructured text data.

By “unstructured data” we mean free narrative text containing many possible points of interest, as opposed to structured variable tables with rows and columns. The note text is itself in a structured table, however, with the following columns: patient ID, date, note subject, note text. These notes contain medical information about patients: nurses’ notes, physician notes, discharge summaries, specialty reports, etc.

We need to de-identify our data using the “Safe harbor” method: removal of 18 identifiers recommended by HIPAA, including names, dates, contact information, ages >89, ID numbers, etc. of patients or relatives, employers, or household members of patients, as well as device identifiers, serial numbers, and policy numbers.

We are wondering if Nvivo is capable of locating these particular types of data within text, and either remove or replace the found data. We then would like to export the de-identified data in its table format (i.e. columns: patient ID, date, notes subject, [now de-identified] note text.

Any help or ideas would be much appreciated! Thank you in advance.

Simone


Simone K. Orlowski, PhD
Research Fellow, User Centered Design
Connected Health Innovation | Partners Healthcare
25 New Chardon Street, Suite 300
Boston, MA 02114
SORLOWSKI at mgh.harvard.edu
Tel: (617) 643-9951
www.partners.org/connectedhealth<applewebdata://0FA5F0C5-81C4-4329-977A-26B32175AC51/www.partners.org/connectedhealth>




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