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

[Stuart Shulman]

Simone,

DiscoverText has a redaction engine tailored to FOIA request processing by
the government. It has not been tailored to the full 18 identifiers you
mention, however, we would be happy to work with your team to better
develop the tool for this use case.

~Stu

Stu Shulman <https://twitter.com/StuartWShulman>
Amherst Regional High School, CoachMA Olympic Development Program
(ODP), Assistant Coach
Region I ODP, ID Camp Staff



On Wed, May 17, 2017 at 3:06 PM, Orlowski, Simone K. <
SORLOWSKI at mgh.harvard.edu> wrote:

> 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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