Coordinating SNOMED-CT and ICD-10: Getting the Most out of Electronic
Health Record Systems
by Sue Bowman, RHIA, CCS
A standard electronic health record (EHR) and
interoperable national health information infrastructure require the
use of uniform health information standards, including a common medical
language. Data must be collected and maintained in a standardized format,
using uniform definitions, in order to link data within an EHR system
or share health information between systems. The lack of standards has
been a key barrier to electronic connectivity in healthcare.
Together,
standard clinical terminologies and classifications represent a common
medical language, allowing clinical data to be effectively utilized and
shared between EHR systems. Therefore, standard clinical terminologies
and classifications, with maps to link them, must be incorporated into
EHR systems to achieve system interoperability and the benefits of a
national health information infrastructure.
Terminologies and Classifications: Distinct Purposes
Neither a clinical
terminology nor a classification can, by itself, serve all of the purposes
for which health information is currently used or will be used in the
future. Terminologies and classifications are designed for distinctly
different purposes and satisfy diverse user data requirements. Multiple
terminologies as well as classification systems are necessary to capture
and effectively use the breadth and depth of clinical data in an EHR.
Classification
systems such as ICD-9-CM, ICD-10-CM, and ICD-10-PCS group similar diseases
and procedures and organize related entities for easy retrieval. Classification
systems allow granular clinical concepts captured by a terminology to
be aggregated into manageable categories for secondary data purposes.
They are typically used for external reporting requirements or other
uses where data aggregation is advantageous, such as measuring the quality
of care, monitoring resource utilization, or processing claims for reimbursement.
Classification systems are considered “output” rather
than “input” systems and are not intended or designed for
the primary documentation of clinical care. They are inadequate in a
reference terminology role because they lack granularity and fail to
define individual clinical concepts and their relationships. Yet they
are the most common source of clinical data today, readily available
as a byproduct of the healthcare reimbursement process.
Reference terminologies
such as SNOMED-CT are “input” systems
and codify the clinical information captured in an EHR during the course
of patient care. SNOMED-CT is designed for use in electronic, not paper-based,
health record systems. The number of terms and level of detail in a reference
terminology cannot be effectively managed without automation.
Reference
terminologies are inadequate for serving the secondary purposes for which
classification systems are used because of their immense size, considerable
granularity, complex hierarchies, and lack of reporting rules. A clinical
terminology intended to support clinical care processes should not be
manipulated to meet reimbursement and other external reporting requirements,
as such manipulation would have an adverse effect on patient care, the
development and use of decision support tools, and the practice of evidence-based
medicine.
Mapping: How SNOMED and ICD Work Together
The benefits of using a reference
terminology increase exponentially if the reference terminology is linked
to modern, standard classification systems for the purpose of generating
health information necessary for statistical analysis, reimbursement,
and other secondary uses. The linkage of terms in different systems to
extract information for multiple purposes is accomplished through mapping.
Mapping
is the process of linking content from one terminology to another or
to a classification. Maps result in an expression of the relationships
between the terminologies or classification systems involved. Mapping
requires deciding how concepts in different terminologies match, are
similar, or differ. It provides a link between terminologies and classifications
in order to:
- Use data collected for one purpose for another purpose
- Retain the
value of data when migrating to newer database formats and schemas
- Avoid
entering data multiple times and the associated risk of increased cost
and errors1
Unlike coding, mapping is not specific to a particular patient
encounter. Context is not available as part of the mapping process.2
Creation of a map generally involves an automated translation software
engine. Automated maps create efficiency by minimizing duplicative
data entry and patient data integration across a wide variety of
applications.3
The development of maps between terminologies and classifications
will not eliminate administrative coding or the need for expertise in
code selection. Fully automating the process of mapping from a reference
terminology to a classification system is challenging because of the
inherent differences between a terminology and a classification.4
Maps
will standardize translation of coding systems to a certain extent and
therefore improve coding accuracy simply and efficiently. But human review
is still necessary before reporting a code resulting from a map to ensure
accuracy with regard to the context of a specific patient encounter and
compliance with applicable coding guidelines and reimbursement policies.
While maps are always subject to human review, the goal is to automate
as much of the mapping process as possible using a rules-based approach.5
As rules-based maps are developed for multiple use cases and become increasingly
sophisticated, the level of human review at the individual code level
will diminish and workplace roles will focus on the development and maintenance
(including quality control) of maps for a variety of use cases and the
development of algorithmic translation and concept representation.
Next
Steps for the 21st Century
The full value of the health information contained
in an EHR system will only be realized if both systems involved in the
map are up to date and accurately reflect the current practice of medicine.
Therefore, it makes no sense to map a robust terminology such as SNOMED-CT
to an outdated classification system such as ICD-9-CM. Continued use
of the outdated ICD-9-CM system diminishes the value of the US investment
in SNOMED-CT. The anticipated benefits of an EHR cannot be achieved
if the reference terminology employed in the EHR, such as SNOMED-CT,
is aggregated into a 30-year-old classification system, such as ICD-9-CM,
for administrative use and indexing.
The longer ICD-10 implementation
is delayed, the longer and more expensive it will be to achieve a fully
functioning EHR with the interoperability necessary for the sharing of
healthcare data. Continued use of ICD-9-CM as a medical code set standard
threatens to jeopardize the ability of the US healthcare industry to
effectively collect and use accurate, detailed healthcare data and information
for the betterment of domestic and global healthcare.
AHIMA believes the following steps are essential:
- The federal government
must initiate the regulatory process for the adoption of ICD-10-CM
and ICD-10-PCS.
- The healthcare industry must incorporate terminology
standards in its EHR development initiatives.
- Robust rules-based maps,
designed for different use cases, must be developed from SNOMED-CT
to ICD-10-CM and ICD-10-PCS to maximize the value of the clinical data
and the benefits of an EHR system.
- Such maps should be made publicly
available through the UMLS and should become a standard component of
any EHR system.
These steps are among the first the industry should
take toward maximizing the power of healthcare data and, in doing so,
building a better healthcare system for the 21st century.
Notes
- Imel, Margo, and James Campbell. “Mapping from a Clinical
Terminology to a Classification.” In AHIMA’s 75th Anniversary
National Convention and Exhibit Proceedings, October 2003.
- Ibid.
- Brouch, Kathy. “AHIMA Project Offers Insights into SNOMED,
ICD-9-CM Mapping Process.” Journal of AHIMA 74, no. 7 (2003):
52–55.
- Ibid.
- Available at the SNOMED International Web site at www.snomed.org.
Sue
Bowman (sue.bowman@ahima.org) is director of coding policy and compliance
at AHIMA.
| This article is excerpted from a white paper published in Perspectives
in HIM. To read the complete paper, see “Coordination of SNOMED-CT
and ICD-10,” available online at www.ahima.org/perspectives. |
Article citation: Bowman, Sue. "Coordinating SNOMED-CT and ICD-10: Getting the Most out of Electronic Health Record Systems." Journal of AHIMA 76, no.7 (July-August 2005): 60-61. |
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