Towards Unified Data Exchange Formats for Reporting Molecular Drug Susceptibility Testing

Authors

  • Wilfred Bonney Division of Tuberculosis Elimination, National Center for HIV/AIDS, Viral Hepatitis, STD, and TB Prevention, Centers for Disease Control and Prevention, Atlanta, GA, USA
  • Sandy F. Price Division of Tuberculosis Elimination, National Center for HIV/AIDS, Viral Hepatitis, STD, and TB Prevention, Centers for Disease Control and Prevention, Atlanta, GA, USA
  • Swapna Abhyankar LOINC and Health Data Standards, Regenstrief Institute, Inc., Indianapolis, IN, USA
  • Riki Merrick Association of Public Health Laboratories, Silver Spring, MD, USA
  • Varsha Hampole California Department of Public Health, Richmond, CA, USA
  • Tanya A. Halse Wadsworth Center, New York State Department of Health, Albany, NY, USA
  • Charles DiDonato New York State Office of Information Technology Services, Albany, NY, USA
  • Tracy Dalton Division of Tuberculosis Elimination, National Center for HIV/AIDS, Viral Hepatitis, STD, and TB Prevention, Centers for Disease Control and Prevention, Atlanta, GA, USA
  • Beverly Metchock Division of Tuberculosis Elimination, National Center for HIV/AIDS, Viral Hepatitis, STD, and TB Prevention, Centers for Disease Control and Prevention, Atlanta, GA, USA
  • Angela M. Starks Division of Tuberculosis Elimination, National Center for HIV/AIDS, Viral Hepatitis, STD, and TB Prevention, Centers for Disease Control and Prevention, Atlanta, GA, USA
  • Roque Miramontes Division of Tuberculosis Elimination, National Center for HIV/AIDS, Viral Hepatitis, STD, and TB Prevention, Centers for Disease Control and Prevention, Atlanta, GA, USA

DOI:

https://doi.org/10.5210/ojphi.v12i2.10644

Abstract

Background: With the rapid development of new advanced molecular detection methods, identification of new genetic mutations conferring pathogen resistance to an ever-growing variety of antimicrobial substances will generate massive genomic datasets for public health and clinical laboratories. Keeping up with specialized standard coding for these immense datasets will be extremely challenging. This challenge prompted our effort to create a common molecular resistance Logical Observation Identifiers Names and Codes (LOINC) panel that can be used to report any identified antimicrobial resistance pattern.

Objective: To develop and utilize a common molecular resistance LOINC panel for molecular drug susceptibility testing (DST) data exchange in the U.S. National Tuberculosis Surveillance System using California Department of Public Health (CDPH) and New York State Department of Health as pilot sites.

Methods: We developed an interface and mapped incoming molecular DST data to the common molecular resistance LOINC panel using Health Level Seven (HL7) v2.5.1 Electronic Laboratory Reporting (ELR) message specifications through the Orion Health™ Rhapsody Integration Engine v6.3.1.

Results: Both pilot sites were able to process and upload/import the standardized HL7 v2.5.1 ELR messages into their respective systems; albeit CDPH identified areas for system improvements and has focused efforts to streamline the message importation process.

Discussion: The common molecular resistance LOINC panel is designed to be generalizable across other resistance genes and ideally also applicable to other disease domains.

Conclusion: The study demonstrates that it is possible to exchange molecular DST data across the continuum of disparate healthcare information systems in integrated public health environments using the common molecular resistance LOINC panel.

Keywords: Data Exchange Formats, Electronic Laboratory Reporting, Health Information Exchange, LOINC, Health Level Seven, Public Health Surveillance.

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Published

2020-12-08

How to Cite

Bonney, W., Price, S. F., Abhyankar, S., Merrick, R., Hampole, V., Halse, T. A., … Miramontes, R. (2020). Towards Unified Data Exchange Formats for Reporting Molecular Drug Susceptibility Testing. Online Journal of Public Health Informatics, 12(2). https://doi.org/10.5210/ojphi.v12i2.10644

Issue

Vol. 12 No. 2 (2020): Online Journal of Public Health Informatics

Section

Original Articles

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