NLM Scrubber: NLM s Software Application to De-identify Clinical Text Documents
| Status: | Enrolling by invitation |
|---|---|
| Healthy: | No |
| Age Range: | Any - 127 |
| Updated: | 8/11/2018 |
| Start Date: | June 9, 2016 |
| End Date: | January 1, 2027 |
NLM Scrubber: NLM's Software Application to De-identify Clinical Text Documents
Background: Electronic health records contain a vast amount of data about diseases and
treatments. Researchers could use this data to test their ideas, but they would need to use
records from more than just their own group of patients. But access to those records is
restricted to ensure patient privacy.
U.S. National Library of Medicine (NLM) has created a computer tool called NLM Scrubber. This
program recognizes and deletes personal information from health records. The researchers who
developed this program now need access to the original records. This will allow them to see
how well the program removes personal information from patient records and how they can make
it more accurate.
Objectives:
To find ways to improve clinical text de-identification.
Eligibility:
No new participants. Researchers will review data that have already been collected.
Design:
Researchers will collect a random sample of reports. These will be from different doctors in
different fields.
Researchers will manually remove personal information from the records.
Researchers will also automatically remove personal information from original records using
NLM-Scrubber.
Researchers will compare the results of the computer program versus the manual changes. They
will note when the program has not been removing personal information correctly. They will
also note when the program has been deleting nonpersonal health information incorrectly.
Researchers will use the results to revise the program. They will keep testing it until the
de-identification process is complete.
treatments. Researchers could use this data to test their ideas, but they would need to use
records from more than just their own group of patients. But access to those records is
restricted to ensure patient privacy.
U.S. National Library of Medicine (NLM) has created a computer tool called NLM Scrubber. This
program recognizes and deletes personal information from health records. The researchers who
developed this program now need access to the original records. This will allow them to see
how well the program removes personal information from patient records and how they can make
it more accurate.
Objectives:
To find ways to improve clinical text de-identification.
Eligibility:
No new participants. Researchers will review data that have already been collected.
Design:
Researchers will collect a random sample of reports. These will be from different doctors in
different fields.
Researchers will manually remove personal information from the records.
Researchers will also automatically remove personal information from original records using
NLM-Scrubber.
Researchers will compare the results of the computer program versus the manual changes. They
will note when the program has not been removing personal information correctly. They will
also note when the program has been deleting nonpersonal health information incorrectly.
Researchers will use the results to revise the program. They will keep testing it until the
de-identification process is complete.
This study is about the quality assessment, improvement, and monitoring of an automatic
clinical text de-identification software application called NLM Scrubber, which has been
developed at the National Library of Medicine (NLM). The application has been developed so
that clinical reports can be used in secondary scientific studies (i.e., for secondary use)
without breaching patient privacy. Research on methods for protecting patient privacy and on
the development of NLM Scrubber have been conducted by following the guidelines of and in
compliance with HIPAA and the Privacy Act.
In order to further develop and improve NLM Scrubber and assess its de-identification
performance effectively, the investigators require the original / unredacted samples from all
potential clinical report types and sources. To this end, NLM investigators have been
collaborating with entities within NIH, namely, NIH Clinical Center, BTRIS, and NCI as well
as outside entities, Kentucky State Registry administered by University of Kentucky and
researchers from the University of Pittsburgh, who stated their interest in integrating NLM
Scrubber to their application called Text Information Extraction System. These entities
collect samples of various types of clinical reports for assessing and improving NLM Scrubber
performance. However we also need access to the original data in order to assess
potential problems and improve the accuracy of NLM Scrubber.
clinical text de-identification software application called NLM Scrubber, which has been
developed at the National Library of Medicine (NLM). The application has been developed so
that clinical reports can be used in secondary scientific studies (i.e., for secondary use)
without breaching patient privacy. Research on methods for protecting patient privacy and on
the development of NLM Scrubber have been conducted by following the guidelines of and in
compliance with HIPAA and the Privacy Act.
In order to further develop and improve NLM Scrubber and assess its de-identification
performance effectively, the investigators require the original / unredacted samples from all
potential clinical report types and sources. To this end, NLM investigators have been
collaborating with entities within NIH, namely, NIH Clinical Center, BTRIS, and NCI as well
as outside entities, Kentucky State Registry administered by University of Kentucky and
researchers from the University of Pittsburgh, who stated their interest in integrating NLM
Scrubber to their application called Text Information Extraction System. These entities
collect samples of various types of clinical reports for assessing and improving NLM Scrubber
performance. However we also need access to the original data in order to assess
potential problems and improve the accuracy of NLM Scrubber.
- No new participant enrollment. Researchers will review data that have already been
collected.
We found this trial at
1
site
Click here to add this to my saved trials
