Harmonization of SHARPn Clinical Element Models with CDISC SHARE
Clinical Study Data Standards
Guoqian Jiang, MD, PhD
Mayo Clinic
On behalf of CDISC CEMs
Harmonization Working Group
Acknowledgement
CDISC CEMs Harmonization WG– Julie Evans, CDISC– Tom Oniki, IHC– Joey Coyle, IHC– Landen Bain, CDISC– Guoqian Jiang, Mayo Clinic– Stan Huff, IHC– Rebecca Kush, CDISC– Christopher Chute, Mayo Clinic
Introduction
The Intermountain Healthcare/GE Healthcare Clinical Element Models (CEMs) have been adopted by the SHARPn project for normalizing patient data from electronic medical records (EMRs).
To maximize the reusability of the CEMs in a variety of use cases across both clinical study and secondary use, it is necessary to build interoperability between the CEMs and existing data standards (e.g. CDISC and ISO 11179 standards).
Clinical Element Models (CEMs)
The Clinical Element Model presents a model for describing and representing detailed clinical information.
CEM defines standard data structure to capture patient data. E.g. BloodPressurePanel CEM.
CDISC Standards
CDASH - Clinical Data Acquisition Standards Harmonization SDTM - Study Data Tabulation Model
Objective
To harmonize the SHARPn CEMs with CDISC SHARE clinical study data standards.
As the starting point, we were focused on three generic domains: – Demographics– Lab Tests– Medications
MaterialsCDISC contributed templates in the three
domains in Excel spreadsheets– Demographics (DM)– Lab Tests (LB)– Concomitant Medication (CM)
And the SHARPn project provided three CEM models: – SecondaryUsePatient, – SecondaryUseLabObs – and SecondaryUseNotedDrug in XML Schema.
Methods
We formed a CSHARE CEMs Harmonization Working Group with representatives from CDISC, Intermountain Healthcare and Mayo Clinic.
We performed a panel review on each data element extracted from the CDISC templates and SHARPn CEMs.
When a consensus is achieved, a data element is classified into one of the following three context categories: Common, Clinical Study or Secondary Use.
Results
In total, we reviewed 127 data elements from the CDISC SHARE templates and 1130 data elements extracted from the SHARPn CEMs.
We identified 4 common data elements (CDEs) from the Demographics domain, 20 CDEs from the Lab Tests domain and 15 CDEs from the Medications domain.
Demographics
Lab Tests
Medications
Outstanding Issues
Differences in implementation– Dose Form (--DOSFRM)– Formulation.data.code
Data types– CDISC data types with mappings to ISO21090 (HL7?)– CEM data types are a subset of HL7 data types with
extensionValue set definition mechanism
– CDISC terminology defines standard codelists– CEM value sets rely on external terminology services (e.g.
CTS2 value set definition services)
ConclusionIn conclusion, we have identified a set of
data elements that are common to the context of both clinical study and secondary use.
We consider that the outcomes produced by this Working Group would be useful for facilitating the semantic interoperability between systems for both clinical study and secondary use.
Future works
To discuss and analyze outstanding issues– What do we do when CDISC has something we don’t
have? Do we automatically add it to the core? If not, what are our criteria for adding/not adding?
– How do we harmonize value sets? Is it ok if one or the other of us has a subset of the other? Do we create “core” value sets that are supersets of what all use cases need, just like we’re creating core models?
– What do we do about those “differences in implementation”?
– How do we see this mapping being used now?
Future works
To expand harmonization efforts to more other domains
To foster requirements on building a collaborative platform for supporting the harmonization
To author the CDISC clinical study data models using the CEM formalisms (e.g. CDL or ADL)
References
http://informatics.mayo.edu/sharp/opencem/index.php/Main_Page (csharecems/sharpn)