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Standardized Nursing Languages

The American Nurses Association (ANA) has recognized thirteen standardized languages for use in health care, and we have placed most of them here. Click on the images to visit their respective sites and learn more about them!

ANA Recognized Terminologies and Data Element Sets

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The Committee for Nursing Practice Information Infrastructure (CNPII of the American Nurses Association (ANA) has recognized thirteen standardized languages, one of which has been retired. Two are minimum data sets, seven are nursing specific, and two are interdisciplinary. The table below outlines these standardized languages.

 

Setting Where Developed

Content

Data Element Sets

1. NMDS
Nursing Minimum Data Set
Currently Recognized

All Nursing Clinical Data Elements

2. NMMDS
Nursing Management Minimum Data Set
Currently Recognized

All Settings Nursing Administrative Data Elements
Interface Terminologies

3. CCC
Clinical Care Classification
Currently Recognized

Home Care Diagnoses, Interventions, and Outcomes

4. ICNP®
International Classification of Nursing Practice
Currently Recognized

All Nursing Diagnoses, Interventions, and Outcomes

5. NANDA
NANDA International
Currently Recognized

All Nursing Diagnoses

6.NIC
Nursing Intervention Classification
Currently Recognized

All Nursing Interventions

7. NOC
Nursing Outcome Classification
Currently Recognized

All Nursing Outcomes

8. OMAHA SYSTEM
Omaha System
Currently Recognized

Home Care, Public Health, and Community Diagnoses, Interventions, and Outcomes

9. PCDS
Patient Care Data Set
Retired

Acute Care Diagnoses, Interventions, and Outcomes

10. PNDS
Perioperative Nursing Data Set
Currently Recognized

Perioperative Diagnoses, Interventions and Outcomes
Multidisciplinary Terminologies

11. ABCCodes
ABC Codes
Currently Recognized

Nursing and Other Interventions

12. LOINC®
Logical Observation Identifiers Names and Codes
Currently Recognized

Nursing and Other Outcome and Assessments
13. SNOMED CT
Systematic Nomenclature of Medicine Clinical Terms
Currently Recognized
Nursing and Other Diagnoses, Interventions, and Outcomes

 

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Relationships Among ANA Recognized Data Element Sets And Terminologies

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There are many instances of relationships among the recognized terminologies and data element sets. Examples include: 
  • terminologies being used together 
  • one terminology being integrated into another terminology, and 
  • a terminology providing a response set for at data element within a data set. 

The table below provides a simple rendering of the existence of relationships among the recognized terminologies and data element sets. 

"●" Indicates a relationship between column and row entities. 

Example: the "●" in row 3. CCC and column 1. NMDS shows a relationship exists between the Nursing Minimum Data Set and Clinical Care Classification. 

 

 

1.
NMDS

2.
NMMDS

3.
CCC
4.
ICNP®
5.
NANDA
6.
NIC
7.
NOC
8.
OMAHA
9.
PCDS
retired
10.
PNDS
11.
ABC
12.
LOINC®
13.
SNOMED
CT
Data Element Sets
1. NMDS Nursing Minimum Data Set

2. NMMDS Nursing Management Minimum Data Set

 

 

 

 

 

 

 

 

 

 

 

 

 

Interface Terminologies
3. CCC Clinical Care Classification                  
4. ICNP® International Classification of Nursing Practice                      
5.NANDA NANDA International                
6.NIC Nursing Intervention Classification                
7. NOC Nursing Outcome Classification                
8. OMAHA Omaha Home Health Care System                      
9. PCDS (Retired) Patient Care Data Set                          
10. PNDS Perioperative Nursing Data Set                    
Multidisciplinary Terminologies
11. ABC Alternative Billing Codes                    
12. (LOINC®) Logical Observation Identifiers Names and Codes                      
13. SNOMED CT Systematic Nomenclature of Medicine Clinical Terms            

Standardized Nursing Language: What Does It Mean for Nursing Practice?

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Click on image to read the full article
Marjorie A. Rutherford, RN, MA

Abstract

Use of a standardized nursing language for documentation of nursing care is vital both to the nursing profession and to the bedside/direct care nurse. The purpose of this article is to provide examples of the usefulness of standardized languages to direct care/bedside nurses. Currently, the American Nurses Association has approved thirteen standardized languages that support nursing practice, only ten of which are considered languages specific to nursing care. The purpose of this article is to offer a definition of standardized language in nursing, to describe how standardized nursing languages are applied in the clinical setting, and to explain the benefits of standardizing nursing languages. These benefits include: better communication among nurses and other health care providers, increased visibility of nursing interventions, improved patient care, enhanced data collection to evaluate nursing care outcomes, greater adherence to standards of care, and facilitated assessment of nursing competency. Implications of standardized language for nursing education, research, and administration are also presented.


Coordination of SNOMED-CT and ICD-10: Getting the Most out of Electronic Health Record Systems

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Click on image to read the full article
by Sue Bowman, RHIA, CCS, director of coding policy and compliance, AHIMA 
Perspectives in Health Information Management Spring 2005 (May 26, 2005)

Executive Summary

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. 

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. 

Classification systems such as ICD-9-CM, ICD-10-CM, and ICD-10-PCS group together similar diseases and procedures and organize related entities for easy retrieval. 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.

They 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. The benefits of using a reference terminology such as SNOMED-CT increase exponentially if the reference terminology is linked to modern, standard classification systems for the purpose of generating health information necessary for secondary uses such as statistical and epidemiological analyses, external reporting requirements, measuring quality of care, monitoring resource utilization, and processing claims for reimbursement. The linkage of terms in different systems to extract information for multiple purposes is accomplished through mapping.

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. 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 their 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 in order to maximize the value of the clinical data and the benefits of an EHR system. 
  • These maps should be made publicly available through the Unified Medical Language System 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.