# Presentation: 037627

## Implementation of National Standards (LOINC, SNOMED) for Electronic Reporting of Laboratory Results: BioSense Experience

- Nikolay Lipskiy1, DrPH, MS, MBA; Jerome I. Tokars1, MD, MPH; Stephen Benoit1, MD, MPH, Roseanne English1 and Sundak Ganesan2, MD
*CDC, 1-National Center for Public Health Informatics, Division of Emergency Preparedness and Response; 2- National Center for Public Health Informatics, Division of Informatics  Shared Services*

- The findings and conclusions in this report are those of the author(s) and do not necessarily represent the
- official positions of the Centers for Disease Control and Prevention** **

## Outline

- Background/purpose
- Data sources
- Transmission of data
- Processing and use of data at CDC
- Use of standard test codes (LOINC)
- Use of standard result codes (SNOMED)
- Conclusions and recommendations for implementing standards

## Background

- The BioSense system receives data from >400 non-federal hospitals, including 50 that send microbiology laboratory tests and results and from a national laboratory.
- Before transmission to CDC, local test codes are mapped to LOINC codes and local result codes to SNOMED.
-  At CDC, SNOMED and LOINC codes are mapped to notifiable conditions using updated versions of standard mapping tables

## Objectives

- Describe the laboratory surveillance component of BioSense
- Review laboratories’ practices for reporting microbiology results
- Describe the implementation of national standards for reporting laboratory tests and results
- Based on BioSense laboratory experience, identify possible improvement activities for the implementation of standards

## Methods: Data sources

- Data sources
- Hospital laboratories (n=50)
- Approximately 34,000 orders are received per day
- Linked to other BioSense data via a random number patient identifier
- National laboratory
- Approximately 160,000 test orders per day from more 80,000 providers, primarily outpatient physicians and small group practices
- These results are unlinked to other data on individual patients
- Not included in this presentation

## Data Sources: Hospital Laboratories Reporting to BioSense

**Data Sources: Hospital Laboratories**** ****Reporting to BioSense**

## Methods: Data Transmission

- Data transmission: laboratory data sent to CDC via the Public Health Information Network Messaging System (PHINMS) using HL7 2.5 messages.
- PHIN Messaging Standard “Electronic Laboratory Message, ORU^R01”, v.2.5.1. was implemented
- BioSense data transmission standards were developed:
-      - BioSense Data Messaging Guide
-      - BioSense Mapping Tool

## Methods: Data Processing and Analysis

- Analyzed microbiology laboratory data from >599,000 patients during January 2007 and August 2008 from 50 hospital laboratories.
- Evaluated the results of mapping of local codes to standard
- Laboratory tests (Logical Observation Identifiers Names and Codes, LOINC)
- Laboratory results (The Systematized Nomenclature of Medicine, Clinical Terms, SNOMED CT)
- Used RELMA (Regenstrief Institute, 2007) for validation of LOINC codes and CliniClue browser (Clinical Information Consultancy, 2008) for validation of SNOMED CT codes

## Data Processing: Process Flow

**Data Processing: Process Flow**

## Data Processing and Analysis: SNOMED to Notifiable Conditions Table—Modified for BioSense

**Data Processing and Analysis: SNOMED to Notifiable Conditions Table—Modified for BioSense**

- Includes SNOMED codes for 162 conditions, including notifiable conditions and other pathogens of interest (e.g., influenza, RSV, MRSA)

**Example of conditions included in table**

## Tracking Notifiable Diseases Using Local Codes Mapped to Standard SNOMED Codes (Pilot Project)

**BioSense maps positive results from laboratories that implemented local or standard result test codes**

**Tracking Notifiable Diseases Using Local Codes Mapped to Standard SNOMED Codes (Pilot Project)**

## Using Text String Results (Pilot Project)

**Using Text String Results (Pilot Project)**

**BioSense tracks about 20 of the most important notifiable diseases using natural language processing (NLP) methods**

## All hospital laboratories use local codes which are mapped to standard codes at the source
1,874 local ordered tests were mapped to 586 LOINC (ratio1:3.5).
 Major causes of a reduction of codes: 
Labs use different local codes/names for the same standard procedure
Problems with translation of local codes to LOINC
Problems with mapping

- 1,874 local ordered tests were mapped to 586 LOINC (ratio1:3.5).
-  Major causes of a reduction of codes:
- Labs use different local codes/names for the same standard procedure
- Problems with translation of local codes to LOINC
- Problems with mapping

**Mapping of Local Codes to Standard LOINC—Ordered Tests**

## Mapping of Local Codes to Standard LOINC—Ordered Tests

**Examples of problems with ordered panels of tests.**

**Mapping of Local Codes to Standard LOINC—Ordered Tests**

## Mapping of Ordered Tests to Other

**31.3% of local codes are not mapped to LOINC or mapped as “Other”**
**Examples of problems with direct mapping to LOINC**** ****of ordered test names.**

- Local test order Legionella PCR does not have exact match in the LOINC coding system

## Mapping of Local Codes to Standard LOINC—Resulted Tests

- All hospital laboratories use local codes which are mapped to standard (LOINC) codes at the source
- Result test names tend to be more detailed than ordered tests; there were 2,505 unique local result test names vs. 1,874 ordered tests
- The resulted test name is different in 41.3% of tests and conveys more specific information

## Mapping of Local Codes to Standard LOINC—Resulted Tests

**Example. Translation of a local ordered microbial susceptibility test into resulted tests**

**Resulted test names frequently convey more specific information than ordered tests**

## Mapping of Local Codes to Standard LOINC—Resulted Tests

**Example. **
**Local result codes/descriptions used by different hospitals  for a standard (LOINC) test procedure 13317-3, “Staphylococcus aureus.methicillin resistant isolate:ACnc:Pt:XXX:Ord:Organism specific culture**** “**

**Mapping of Local Codes to Standard LOINC—Resulted Tests**

## Susceptibility Test Results

** ****31 of 50 labs (62.0%) use local result codes for antimicrobial susceptibility.  These are mapped to standard (LOINC) codes**

**Example**

## Use of LOINC Codes for Recognizing Notifiable Diseases

**Use of LOINC Codes for Recognizing Notifiable Diseases**

- Almost 19% of LOINC codes are “Other” (local tests can not be directly mapped to LOINC)
- LOINC codes describe general routine procedures  based on cultures (i.e., blood culture, urine culture etc.)
-  For tracking notifiable diseases, in most cases LOINC test names are not specific enough w/o additional information
-  There are situations when laboratories use two-fold descriptors of positive results: they describe properties of microorganism using SNOMED codes not specific  to a microorganism  (such  as “Heavy growth”, “Positive” etc.) ; also, they use specific LOINC codes to describe a microorganism; for these situations LOINC codes are very useful for tracking of microorganisms

**Ten most frequent LOINC codes comprise almost 67% of test results**

## SNOMED-CT for Reporting Laboratory Test Results

**Local organism codes**

**Yes**
**66% (33)**

**No**
**34% (17)**

**Yes**
**97% (32)**

**No**
**3% (1)**

**Local susceptibility codes**

**Yes**
**20% (10)**

**No**
**80% (40)**

**Mapped to SNOMED**

**Mapped to SNOMED**

**Yes**
**100% (10)**

## Overcoming Obstacles In Implementing SNOMED-CT Codes For Reporting of Laboratory Test Results

**Implementation of natural  language**
** ****processing (NLP)  techniques**
**Promotion of standard codes**

**Improvement of LOINC-SNOMED**
** ****mapping  tables**
**Collaboration with partners**
** ****to promote reporting standards**

**Acquiring local mapping  tables**
**Contacting data vendors**
**Certification of sites**
**Working with CSTE and on development **
**of ELR documents**

## Approach to Mapping Lab Criteria to Standard Codes

| NNDSS | Disease | Laboratory
Criteria | Sub-Code | LOINC (TBD) |
| --- | --- | --- | --- | --- |
| 10020 | Brucellosis | Isolation of Brucella spp. from a clinical specimen, or  | 10020-1 |  |
|  |  | Fourfold or greater rise in Brucella agglutination titer between acute- and convalescent-phase serum specimens obtained greater than or equal to 2 weeks apart and studied at the same laboratory, or  | 10020-2 |  |
|  |  | Demonstration by immunofluorescence of Brucella spp. in a clinical specimen  | 10020-3 |  |

**Notes:**
Working on improvement of electronic laboratory reporting criteria for notifiable diseases.
Brucellosis (example). Re-mapping existing case definition into machine readable

## Problems with Reporting Local Codes for Results Other Than Cultures

**>42,000 laboratory test codes (LOINC) mapped by PHIN VADS to 12,000 organism codes (SNOMED)**
**>12,900 LOINC tests for antibodies, antigens and DNA (27%); most have no corresponding local test codes and therefore could not be mapped to SNOMED codes. **
**Currently the BioSense data feed contains 840 microorganism-related SNOMED codes**

## Overcoming Obstacles in Implementation of SNOMED-CT Codes for Reporting Laboratory Test Results

**Development of local data dictionaries/SNOMED mapping tables (also, similar tables for LOINC)**
**Example. Fragment of a local data dictionary that was successfully mapped to SNOMED**

## Implementation of National Standards (LOINC, SNOMED) for Electronic Reporting of Laboratory Results: Next Steps

**Working with CDC, CSTE and other partners on development of qualitative and quantitative laboratory indicators for recognition of notifiable diseases under public health surveillance**

**      ****2. Strengthening cross-linkages between national guidelines for electronic reporting of notifiable diseases**

## Conclusions

**Our analyses highlight the challenges of mapping local microbiology laboratory data to standard vocabularies**
** ****BioSense experience may help as strategies for case recognition of notifiable diseases are being developed**
** ****To make case definitions, vocabularies, and messaging standards work in concert:**
**Further development of electronic laboratory criteria for notifiable diseases**
**Use of standard codes locally, or more accurate mapping of local codes to standard**
**Development of new LOINC and SNOMED codes where needed**

## Questions?

**Nikolay Lipskiy, e-mail 770-883-3207**

**Thank you**