An Efficient Approach To Map LOINC Concepts To Notifiable Conditions

1. An Efficient Approach To Map LOINC Concepts To Notifiable Conditions Wei Li, MD1, Jerome I. Tokars, MD, MPH1, Nikolay Lipskiy, DrPH1, Sundak Ganesan, MD2 1. Division of emergency Response and Preparedness National Center for Public Health Informatics (NCPHI) Centers for Disease Control and Prevention (CDC) 2. SAIC Consultant to NCPHI, CDC

2. Notifiable Diseases/Conditions Surveillance for notifiable conditions traditionally includes manual reporting using written case definitions The availability of laboratory data in electronic format makes automated reporting feasible Mapping of notifiable conditions to standard vocabularies are required A table mapping notifiable diseases to LOINC (laboratory) and SNOMED (organism) codes was first made by Dianne Dwyer in later 1990s and last updated in 2004

3. Purposes of Mapping A tool to filter the messages from public health and clinical labs to identify laboratory test results of public health importance BioSense receives laboratory test results from 30 hospitals and from a large national laboratory—need to automatically identify results that MAY indicate a notifiable condition 43 pathogens that cause notifable conditions are also Category A, B, or C Bioterrorism Agents (73%) Electronic laboratory report (ELR) and interoperability A framework for the development and maintenance of a controlled vocabulary for reportable events of public health importance Developing reusable component for intelligent surveillance information system architectures Towards development of notifiable disease controlled vocabulary for Unified Medical Language System (UMLS)

4. Objective To develop a method to map Logical Observation Identifier Names and Codes (LOINC) to notifiable conditions Efficient Easy to update

5. Notifiable Diseases and Other Conditions of Public Health Importance Notifiable Diseases and Other Conditions of Public Health Importance (n=152) Reportable either nationally (n=86) or to states Active and inactive Infectious diseases, injuries, toxins

6. Event Code List: Notifiable Diseases and Other Conditions of Public Health Importance

7. Event Code List Event Code changes year to year Retire and replace Enterohemorrhagic Escherichia Coli (EHEC) O157:H7 (10560,11562, 11564) were added in 1994 but retired in 2006 Shiga toxin-producing Escherichia Coli (STEC) was added in 2006 New code Polyovirus infection, nonparalytic (10405) was added in 2007.

8. Logical Observation Identifiers Names and Codes (LOINC®)* A standard vocabulary identifies laboratory tests and clinical observations A common language for building electronic medical records Founded in 1994 and initial release in 1995 with 6,000 lab tests The latest release (v2.21) covered 48,043 terms Allow users to merge clinical results from many sources into one database for patient care, clinical research, or management.

9. LOINC to Condition Mapping Tables Component of Public Health Information Network (PHIN) Original version by Dr. Dwyer, updated by Dr. Sable Last updated by PHIN in 2004 LOINC There are 46,812 terms in the LOINC version 2.19, which revealed 11,972 new terms added (34% increase) since 2004 > 12,000 terms have been deprecated since then LOINC has changed the properties of its database and expanded its fields to 61 LOINC to Notifiable Conditions Mapping

10. List of 152 Notifiable Diseases and Other Conditions of Public Health Importance Excluded events without lab test or unknown organism Silicosis, Spinal cord injury, and Head Injury, etc Kawasaki Disease, Reye Syndrome, etc List to be mapped includes 146 conditions All nationally notifiable infectious diseases 46 Other infectious diseases 7 Toxins Determine organisms related to each disease Find Systematized Nomenclature of Medicine (SNOMED) codes for organisms Map tests for organisms/toxins to LOINC codes by 3 methods

11. Mapping Methods (continued) The Regenstrief LOINC Mapping Assistant (RELMA v3.19) was used to identify lab tests and LOINC codes associated with each organism/toxin A SAS (v9.1.3) program was developed to perform a text search of the LOINC database to find words that matched notifiable conditions or microorganisms Manual process

12. Manual process. Check the following LOINC database fields against the list of notifiable conditions Component Method Type Class Date Last Changed Map To Short Name Related Names 2 Mapping Methods (continued)

13. RELMA v3.19

14. Results: Comparison of Mapping Tables

15. Comparison of Mapping Methods

16. Text Search The text search parsing program found only 4901 LOINC 451 LOINC entries not found by text search most had a non-specific test name, e.g. Code 33700-6 (a spore identification test) is used to identify Anthrax Search field does not contain the word that used for searching, e.g. “anthrax”

18. Product: LOINC to Condition Table Data Dictionary

19. Product: LOINC to Condition Table Data Dictionary

20. Conclusions Compared with the 2004 LOINC to Condition Table, our 2007 table added >2000 entries and deleted >200. The methods we used were labor intensive but currently necessary Efforts to improve the text search method by adding additional search terms such as “spore” may enable more frequent automated updates. In the interim, the use of RELMA to identify lab tests provides an accurate and efficient semi-automated process to update the LOINC to Condition Mapping Table

21. Future Plans Update LOINC to Notifiable Conditions Mapping Table to latest LOINC version 2.21 Re-create/modify the text search program to increase accuracy Explore programs other than SAS to perform text searches Incorporate terms in the latest release of SNOMED Ultimately, use updated mapping table to improve laboratory-based surveillance