>> Jon McKeeby: Common Data Elements, Part 2 of 4.
Again, my name is Jon Walter McKeeby.
I'm the chief information officer
at the Clinical Center of the NIH.
And we utilize common data elements
to share data across clinical research.
So, this is the second part of the series.
So, we're going to review NIH
Data Management and Sharing Policy.
Under the Data Management and Sharing Policy,
NIH expects that investigators and institutes plan and budget
for the management and sharing of data.
All researchers need to submit a data management
sharing plan for review when applying for funding.
Comply with the approved data management sharing plan.
Individual NIH Institute Centers
and Offices may have additional policies and expectations,
and we identify a link for those policies.
CDEs can be a part of a compliant data management
and sharing plan.
They should be. They allow the sharing to occur.
Using Common data elements can be part of an effective plan
for managing and sharing data. According to the policy,
NIH encourages researchers to use common data elements
in order to improve accuracy, consistency,
and interoperability among data sets within various areas
of health and disease research.
We provided links here on Office of Intramural Research Guidance,
as well as Office of Intramural Data Management
and Sharing Plan Template.
They state that researchers must describe
what Common data elements will be used in their project
and to justify if common data elements will not be used.
Common data element usage at NIH.
Some institutes and centers have had mature
common data element programs for years.
Examples are the clinical center, BTRIS,
which is the repository for the intramural program
at the NIH of all the clinical research data.
And then NINDS has common data elements
across domains of different diseases.
And we'll talk about that.
NLM has been involved with common data element since 2012.
NLM encourages the adoption of common data elements across NIH.
There's an NIH common data element taskforce,
and there's an NIH common data elements repository.
And we'll review all these items in the next set of slides.
So BTRIS is the NIH Intramural Research Program
research clinical data warehouse.
We've had data since 1976 in different databases,
different systems, in our original EHR,
which was referred to as MIS, our original laboratory system.
And so, we have all this data and we want to utilize it.
So, we developed a terminology to allow this.
So, the BTRIS common data element is referred to as RED,
the Research Entity Dictionary.
BTRIS allows bidirectional exchange of data
between clinical and I.C. research systems.
Medical record number is the key identifier
to identify a patient.
We have self-service as well as assisted data curation,
and we facilitate data exchange with research collaborators.
We provide data from BTRIS to multiple clinical systems
utilizing the common data elements
that are specific to our research entities dictionary.
And so BTRIS, we have multiple systems that feed
our data repository referred to as BTRIS.
We provide the data through extractions,
our self-service as well as we produce
reports specific to request.
And so, this is the services that BTRIS provides.
BTRIS is based on the research entities dictionary
referred to as RED.
It allows ensure operability across NIHIC systems.
Allows multiple classifications and hierarchies to coexist.
And it allows tests to be defined across years,
names, type of test. And so, a glucose ordered in MIS
if it's following the same reference range,
following the same instruments, glucose and CRIS --
which is our current HER --
various types of ordering the glucose
would be all identified as the same test.
Below is the RED web search.
So, you can search for specific items and know the values.
And by clicking it, then you can find values
across the entire repository that fit that item.
So, this is an example of common data
elements specific for NIH Intramural Program.