Estimation of agricultural and logging injury incidence in Maine using electronic administrative data sets

J Agromedicine. 2015;20(2):195-204. doi: 10.1080/1059924X.2015.1009668.

Abstract

Agriculture and forestry rank among industries with the highest rates of occupational fatality and injury. Establishing a nonfatal injury surveillance system is a top priority in the National Occupational Research Agenda. Recently, new sources of data such as Pre-Hospital Care Reports (PCRs) and hospitalization data have transitioned to electronic databases. Using narrative free text and location codes from Maine PCRs, along with International Classification of Diseases (ICD)-9 External Cause of Injury Codes (E-codes) in Maine hospital data, researchers are designing a surveillance system to track farm and forestry injury that utilizes electronic match-merging of the two data sources. For 2008, PCR records produced a total of 104 true agricultural cases. Of these, 66 (63%) were identified from the keyword/visual inspection process alone, 25 (24%) were identified by the farm checkbox only, and the remaining 13 (13%) by both methods. For the 150 unique injury events found in hospitalization data, 146 had the initial episode of care documented in only one of the three hospital files. The emergency department (ED) file had the largest number of these (123/146 = 84.2%), followed by the outpatient file (12/146 = 8.2%) and the inpatient file (11/146 = 7.5%). Of the 250 unique agricultural injuries identified (100 PCR only + 146 hospital only + 4 from both), 66 (26%) would not have been identified without free text review of PCR narrative. The false-positive rate (97.14%) keyword searches underscores that without visual inspection, it is not an effective strategy. Both sources of data (PCR and hospital data) need to be used in a continued surveillance system.

Keywords: Agriculture; electronic databases; forestry; injury surveillance.

Publication types

  • Research Support, U.S. Gov't, P.H.S.

MeSH terms

  • Accidents, Occupational / statistics & numerical data*
  • Agriculture / statistics & numerical data*
  • Emergency Service, Hospital / statistics & numerical data
  • Forestry / statistics & numerical data*
  • Hospitals / statistics & numerical data
  • Maine / epidemiology
  • Wounds and Injuries / epidemiology