Open AccessInjury Burden in the United States: Accurate, Reliable, and Timely Surveillance Using Electronic Health Care Data
Author(s) -
Jae Min,
Kelly K. Gurka,
Bindu Kalesan,
Jiang Bian,
Mattia Prosperi
Publication year - 2019
Publication title -
american journal of public health
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 2.284
H-Index - 264
eISSN - 1541-0048
pISSN - 0090-0036
DOI - 10.2105/ajph.2019.305306
Subject(s) - medicine , medical emergency , health care , occupational safety and health , documentation , poison control , injury prevention , environmental health , public health surveillance , public health , coding (social sciences) , external cause , medline , computer science , nursing , political science , statistics , mathematics , pathology , law , programming language
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.