1
CDA IG for Genetic Testing Reports –
Towards a Clinical Genomic Statement
Shabo A.

Abstract— Genetic tests have recently become an important
tool in clinical care that further personalizes the care processes
based on the patient's genetic profile or even individual genetic
makeup. Genetic testing methods are diverse and span from
testing for known germline mutations in the context of single-gene
disorders, to full sequencing of genes in tumor tissues looking for
somatic variations in cancer cells. Most of the genetic tests look
for genetic variations or use cytogenetic methods but there is a
growing use of gene expression testing kits in clinical care and
other genomic research techniques slowly propagate to
healthcare. The CDA Implementation Guide for Genetic Testing
Reports is an attempt to suggest a standard framework for
reports that summarize genetic testing results, targeting both
clinicians and applications.
The GTR has an extensive use of human readable content
such as background information and recommendations which
are necessary but hard to present in a definite way because of
the relatively higher level of uncertainly and sometimes
controversy of genetic testing results. This makes the narrative
somewhat fuzzy and thus difficult to structure. With regard to
the actual findings, these are represented as clinical genomic
statements as further explained in detail.
The GTR section outline is built on a single summary
section at the top, along with multiple sections describing
specific types of genetic tests (e.g., genetic variation,
cytogenetics, etc.). The summary section consists of an overall
interpretation summarizing the interpretations of each of the
specific genetic tests (see figure 1).
I. INTRODUCTION
T
he CDA [1] Implementation Guide (IG) for Genetic
Testing Reports (GTR) is being developed by the HL7
Clinical Genomics Work Group (co-sponsored by the
Structured Documents Work Group), using the OHT MDHT
tool for CDA [2]. The GTR can be used by all producers of
genetic testing reports such as genetic labs and clinical
geneticists. As a consequence of genetic testing diversity and
the constantly growing number of techniques yielding new
result formats less familiar to the receiving party (e.g.,
referring physician), it is crucial to have a report format with
emphasis on detailed but easy-to-understand interpretations of
the testing results along with concrete recommendations.
Nevertheless, background information on performed tests is
important as well to allow the receiving party to assess the test
reliability especially in relatively new tests.
The GTR is part of an attempt to bridge the gap between the
markedly different worlds of medical informatics and
bioinformatics by referencing and building on the HL7
Clinical Genomics standards [3]. These standards cope with
that gap by encapsulating raw genomic data along with the
most clinically-significant data items (so-call bubbled-up)
represented by HL7 objects possibly associated with
phenotypic information. In contrast, the GTR consists of
merely the bubbled-up information along with the displayable
information. For example, full DNA sequences of tested genes
can be encapsulated along with certain variations along these
sequences that are clinically meaningful to the patient.
Amnon Shabo (Shvo) is with the IBM Research Lab in Haifa (phone: 97254-4714070; fax: 972-4-8296116; e-mail: shabo@il.ibm.com).
Fig.1. Section Outline of the CDA IG for GTR (screen snapshot taken from
the Eclipse-based OHT MDHT tool for developing CDA IGs).
There are several design challenges in the development of
the GTR that originate in the genomic information complexity
as well as in the need to make genomic data relevant to clinical
care and more importantly readable and comprehendible to
clinicians at the point of care. The following sections describe
some of the main challenges.
II. DESIGN CHALLENGES
A. Granularity
This implementation guide copes with the challenge of how
fine grain clinical genomic data exchanged through proprietary
or HL7 Clinical Genomics messages would be represented
using the CDA model. The best example is a full sequencing
test of several genes where specific segments of each gene
were sequenced. Using existing HL7 Clinical Genomics
2
specifications (e.g., the Genetic Variation CMET) it is possible
to convey this raw genomic data set, however for the sake of a
human-readable report summarizing genetic test results, it
seems better if that messaging granularity of data will not be
modeled into the GTR, rather optionally be referenced when
needed. It is important to note that CDA R2 is limited in its
expressive power and it is the current basis of GTR. If GTR is
upgraded to CDA R3 (when R3 becomes available), then this
design decision will be revisited.
B. Clinical Genomic Statement
The challenge of the GTR's structured data is to come up
with an abstract template for a 'Clinical Genomic Statement'.
The template under ballot has, at its core, a genomic
observation (e.g., a genetic variation) along with necessary
information like time, method and performer. This observation
is then associated with the indications of making this
observation and with interpretations of that observation (see
figure 2). Following the HL7 Clinical Genomics Domain, an
important design principle is to disallow the use of the
interpretationCode attribute of the genomic observation
because it is important to have it as a separate observation
where time, method and other attributes could be different than
those of the genomic observation.
Fig. 2. The Clinical Genomic Statement main structure.
C. Universal vs. Specific Templates
Another challenge is how to define a universal
implementation guide that can accommodate the needs
described above, which could then be further refined to
specific genetic testing reports, either realm specific or
method-specific etc. The design principle currently used is to
have a Universal document template and derive specific
templates from the parent Universal one, e.g., by binding to
different codes required by each realm. It is expected to see
implementation guides derived from the Universal GTR for
geographic realms, e.g., a US Realm-specific GTR could
mandate the use of LOINC codes developed for genetic testing
results [4] and are used in the Universal spec as examples (see
figure 3). It is also foreseen to have different GTR templates
for research and pharmaceutical efforts, which follow specific
work flows unique to the sponsoring organization (e.g., a
pharma company) and the GTR needs to support it.
Fig. 3. An example of a LOINC value set utilized in GTR. These value sets
were initially developed as part of an HL7 v2 implementation guide [5].
III. INITIAL IMPLEMENTATIONS
The GTR is balloted as a Draft Standard for Trial Use and is
being experimented in several efforts, for example:
(1) In a Korean Patient Empowerment System [6] where
patients can manage their health data through a web portal, the
system can import clinical data from sources such as EHR and
PHR systems as well as from health monitoring devices and
genetic labs. The system includes healthcare services such as
the Personalized Adverse Drug Event alerts service, which
also uses pharmacogenetic knowledge-bases and combines it
with the patient clinical and genetic data. The system
maintains the clinical data in HL7 CCD instances while the
GTR is used for handling the genetic testing reports.
(2) Translational Software is a startup company that is
building a Web-based portal for ordering and interpreting
genetic tests. The portal will implement GTR for interpretive
results and to enable laboratories to deliver test results to
Electronic Medical Record systems in HL7 standards using
both narrative and structured data [7].
IV. CONCLUSION
The CDA IG for GTR is an attempt to bridge from genetic
lab messages with high-resolution genomic data, to human
readable reports consisting of both narrative and structured
entries. While the narrative accommodates the extensive
background information and fuzzy recommendations, the
structured entries represent the essential data following a
'clinical genomic statement' abstract template that can be used
by decision support applications at the point of (personalized)
care.
ACKNOWLEDGMENT
The development of the GTR is a joint effort of members of
the HL7 Clinical Genomics Work Group supported by the
entire community of HL7 as well as by the developers of the
OHT MDHT tool for CDA.
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