Citation

Min J, Gurka KK, Kalesan B, Bian J, Prosperi M. Am. J. Public Health 2019; ePub(ePub): ePub.

Affiliation

Jae Min, Kelly K. Gurka, and Mattia Prosperi are with the Department of Epidemiology, University of Florida, Gainesville. Bindu Kalesan is with the Department of Medicine, Boston University, Boston, MA. Jiang Bian is with the Department of Health Outcomes and Biomedical Informatics, University of Florida.

Copyright

(Copyright © 2019, American Public Health Association)

DOI

10.2105/AJPH.2019.305306

PMID

31622141

Abstract

Current injury surveillance systems in the United States, including the National Electronic Injury Surveillance System (NEISS), are unable to draw reliable subnational and subannual incidence estimates.Compared with the International Classification of Diseases (ICD), the clinical ontology system currently used widely in health care, NEISS's coding structure lacks specificity and consistency. In parallel, the quality of ICD codes depends on accurate and complete documentation by health care providers and skillful translation into ICD codes in electronic health care data. Additionally, there is no national mandate to collect external cause of injury data.Electronic health care data, such as health records and claims, with updated codes and uniform adherence to recommendations for coding external cause of injury, have the potential to be used for a more robust and timely surveillance of injury to accurately and reliably reflect the injury burden in the United States. (Am J Public Health. Published online ahead of print October 17, 2019: e1-e5. doi:10.2105/AJPH.2019.305306).

Language: en