Function of Rule-Based Mapping withing Integrated Terminology Management

James R. Campbell, MD, and Margo Imel, RHIT, MBA/TM

Nationwide implementation of computerized patient records with decision support features is a national priority. In order to achieve this goal, a terminology architecture is required that serves granular, interactive recording of clinical data while supporting the administrative, billing, epidemiologic reporting, and research needs of the enterprise. Achieving universal access to computerized records requires support in the development of a national health information infrastructure.

The National Committee on Vital and Health Statistics (NCVHS) and the Institute of Medicine have affirmed a terminology architecture, which consists of core clinical reference terminologies mapped to the nonclinical classifications required by the healthcare enterprise. Interoperability between systems, an imperative for the EHR, demands that this core employ standard terminologies with advanced decision support features.

Historically, a lack of agreement on standards for use in healthcare systems has laid down a roadblock to this type of information technology support to physicians. According to the National Committee on Vital and Health Statistics, 2000, “If information in multiple locations is to be searched, shared, and synthesized when needed, we will need … common vocabularies for personal, clinical and public health information.”

As part of its responsibilities under the Health Insurance Portability and Accountability

Act of 1996 (HIPAA), NCVHS was called upon to “study the issues related to the adoption of uniform data standards for Patient Medical Record Information (PMRI) and the electronic exchange of such information.”1

In 2003, NCVHS identified SNOMED CT®as the general terminology for the core set of PMRI terminologies.

On September 30, 2003, the College of American Pathologists (CAP) received American National Standards Institute (ANSI) approval for the Healthcare Terminology Structure Standard. This standard specifies a standard file structure for use in distributing healthcare terminology. SNOMED CT® is distributed in this ANSI standard structure.

The Terminology Solution—SNOMED CT®

SNOMED CT®, a clinical reference terminology, is designed to capture granular detail about all aspects of clinical healthcare and allow it to be viewed from multiple perspectives. It allows coding in an EHR system at the level of detail necessary for clinical care.

SNOMED CT® terminology provides a common language that enables healthcare enterprises a consistent way of indexing, storing, retrieving, and aggregating clinic data across specialties and site of care.

Coding at a clinical level of detail facilitates reuse of data for differential diagnosis, research, and decision support and outcomes analysis. This means that data can be aggregated to match different queries without having to resort to manually compiled code lists.

What is a clinical reference terminology?

Industry experts define a reference terminology as “a set of concepts and relationships that provide a common reference point for comparisons and aggregation of data about the entire health care process, recorded by multiple different individuals, systems or institutions.”2

A clinical reference terminology is ontology of concepts and the relationships linking them. A clinical reference terminology defines the concepts in a formal and computer-processable way. As an example, the hierarchical relationships in SNOMED CT® employ the “Is a” link to identify which concepts are specializations of broader concepts. Along with other defining relationships, a network of meaning is created that is useful for computer representation and processing. When thinking about computer coded terminology and its uses, there are two key process elements that must be considered: data input and data output. In the computer world, these features are referred to as interface and references properties.

Interface and Reference Properties

Interface properties support input of data or data entry. They support the ability to find terms, enhance natural language processing and language translation. These properties organize the manner in which terms are presented to a user in a software system.

Reference properties support data output or retrieval of data. They support data aggregation, analysis, and interoperability. These properties deal with how data is accessed and manipulated based on its meaning rather than how it is displayed on a computer screen.

Through creation of definitions that are computer readable and processable, a clinical reference terminology supports reproducible transmission of patient data between information systems. It supports consistent and understandable coding of clinical concepts, and thus, is a necessary contributor to the function of EHR systems.

SNOMED CT® Mappings to ICD-9-CM

Mapping in this context is the creation of a link or translation from individual concepts within the domain of the reference terminology to the appropriate assignment in another classification scheme.

Several techniques are used to develop the SNOMED CT mappings, including mapping files, integration files, and file integration. In addition to providing individual cross

maps, the vision of SNOMED® International, a division of the College of American Pathologists, is to offer availability and re-use of information across cooperating terminologies.

First generation SNOMED to ICD-9-CM mappings have been broad in nature and limited in completeness and use. Disagreement on mapping assignments in the ICD maps arises largely from differences in understanding of the assumptions regarding context specification and management of such.

SNOMED®International is in the process of developing a second generation map that uses rule-based mapping algorithms. By design, a rule-based map supports multiple context-dependent maps to a classification. Systematic documentation of heuristics and editorial principles in the map help to create a map that is understandable and reproducible. The development of the rule-based map will provide reliable one-to-many mapping to ICD-9-CM, reducing map ambiguity and supporting semi-automated classification mapping of SNOMED CT concepts. This second generation map is designed to manage patient-level context through rule-based interaction with data in a computerized patient record and may be used to support reimbursement.

SNOMED CT mappings are designed to be integrated into a computerized patient record and are not designed to be a manual coding tool.

Use Case Development

Understanding the steps in developing a map begins with the development of the use case. The use case defines the intended use, audience, and shared understanding of the target and source—key to development of a useful and reproducible map.

Key components of a use case are as follows:

  • Business application                                      
  • Purpose (and what  is not the purpose)
  • Audience/Scenarios
  • Scope
  • Target domain
  • Source domain
  • General approach
  • Key assumptions
  • Mapping procedures and heuristics
  • Data sets (mapping categories and rule set structures)
  • Quality Plan
  • Internal review
  • External review

Defining the Map Heuristics and Guidelines

Reproducibility of a coding map requires that a clear and unambiguous editorial policy be developed. There must be sound understanding of both source and target schemes including editorial rules, conventions, structure, and purpose. Next, the editorial guide is documented; it contains a cumulative reference of assumptions and heuristics to be used in translation and interpretation of the two schemes. In the case of the SNOMED CT® to ICD-9-CM rule-based map, heuristics, guidelines, and mapping procedures have been developed that acknowledge the fundamental differences between a reference terminology and a classification in that “equivalence” is often uncertain.

Mapping Rules

Rule-based mapping uses code-level exclusions relevant to the ICD-9-CM target scheme, which are applicable to patient context. The development of a limited-set of rule acronyms that support exclusion rules by gender, age, and co-morbid diagnosis suitable for editorial management are used. The following table illustrates map rule schema (explanatory text added as information):

SNOMED CT Concept

Map Group

Map Priority

Map Category

Map Rule

Map Target

233868005 Fungal myocarditis

1

1

31

IFA myocarditis acute or subacute in bacterial disease NEC

422.0 Acute myocarditis in disease classified elsewhere

1

2

31

IFA streptococcal myocarditis

391.2 Acute rheumatic myocarditis

1

3

11

Otherwise

422.92 Septic myocarditis

2

4

12

Otherwise

117.9 Other and unspecified mycoses

Mapping Definitions

The following mapping definition developed by the CAP are utilized:

  • SNOMED CT Concept—source concept for mapping
  • Map Group—one map group is assigned for each ICD-9-CM target code
  • Map Priority—sequence number for rule processing (integer)
  • Map Rule—rule statement for map record: IFA, simple if-then rule type; PR,  poisoning rule (not shown); ECR, external cause required (not shown); GAMR, gender age map rule (not shown)
  • Map Target—ICD-9-CM code mapped for associated SNOMED concept
  • Map Category (see below)
    • Category 0: outside of ICD scope
    • Category 11: properly classified and specific for reimbursement
    • Category 12: properly classified but non-specific for reimbursement
    • Category 20: not valid as primary:  Fully classified but is referenced in the authoritative source as a manifestation code, an additional or secondary diagnosis code
    • Category 22: properly classified but not valid as primary diagnosis
    • Category 31: requires additional patient characteristics, otherwise maybe specific for reimbursement
    • Category 32: requires additional patient characteristics, maybe non-specific for reimbursement

Note: Not all categories are presented in the above illustration.

The Transition to eHIM Professionals

The introduction of the EHR, new standards for the processing and management of patient information, and the implementation of HIPPA requirements, are contributing to changing roles for HIM professionals. Meeting the challenge of these changing roles requires the HIM professional to acquire new and expanded skill sets in data management and technology.

Now is the time to develop an understanding of how SNOMED CT® interfaces with other terminologies in the management of patient data in the EHR. New jobs and roles emerging with this change in technology will only accelerate. The well positioned HIM professional will play a central part in creating and managing relationships between clinical terminologies, such as SNOMED CT® and coding schemes such as ICD-9-CM, ICD-O, and ICD-10. Now is the time to embrace the change.

Endnotes

  1. http://www.ncvhs.hhs.gov/031105lt3.pdf
  2. Spackman, KA., Campbell, KE., Cote, RA. (1997). “SNOMED RT: a reference terminology for health care,” Proceedings of the 1997 AMIA Fall Symposium, October 29, Nashville TN.

Source:
Campbell, James R.; Imel, Margo. "Function of Rule-Based Mapping withing Integrated Terminology Management." AHIMA's 77th National Convention and Exhibit Proceedings, October 2005.