Analysis of construction injury burden by type of work.
BACKGROUND
To lay groundwork for identifying patterns of injury etiology, we sought to describe injury experience associated with types of work performed at construction sites by examining workers' compensation (WC) claims for the 32,081 construction workers who built Denver International Airport (DIA).


METHODS
Injury rates and WC payment rates were calculated for 25 types of work based on claims and payroll data reported to DIA's owner-controlled insurance program according to National Council on Compensation Insurance job classifications. By linking DIA claims with corresponding lost-work-time (LWT) claims filed with Colorado's Workers' Compensation Division, we were also able to obtain and examine both total and median lost days for each type of work.


RESULTS
Injury experience varied widely among the types of construction work. Workers building elevators and conduits and installing glass, metal, or steel were at particularly high risk of both LWT and non-LWT injury. Median days lost by injured workers was highest (202 days) for driving/trucking. Median days lost for most types of work was much greater than previously reported for construction: 40 days or more for 18 of the 25 types of work analyzed. WC payment rates reflect both number and severity of injuries and were generally not significantly different from expected losses. They were, however, significantly higher than expected for driving/trucking, metal/steel installation, inspection/analysis, and elevator construction.


CONCLUSIONS
Analysis of injury data by type of work allows targeting of safety resources to high risk construction work and would be useful in prospective surveillance at large construction sites with centrally administered workers' compensation plans.
Lowery
J T
JT
Department of Preventive Medicine and Biometrics, University of Colorado Health Sciences Center, Denver, Colorado 80262, USA.
Glazner
J
J
Borgerding
J A
JA
Bondy
J
J
Lezotte
D C
DC
Kreiss
K
K
D000041:Absenteeism; D001359:Aviation; D016009:Chi-Square Distribution; D003120:Colorado / Q000453:epidemiology; D006801:Humans; D007345:Insurance Claim Review / Q000191:economics; D008669:Metallurgy / Q000706:statistics & numerical data; D018986:Motor Vehicles / Q000706:statistics & numerical data; D009784:Occupational Diseases / Q000145:classification* / Q000453:epidemiology; D009790:Occupations / Q000145:classification* / Q000706:statistics & numerical data; D011159:Population Surveillance; D011446:Prospective Studies; D012307:Risk Factors; D012449:Safety; D013232:Steel; D014942:Workers' Compensation / Q000191:economics / Q000458:organization & administration / Q000706:statistics & numerical data; D014947:Wounds and Injuries / Q000145:classification* / Q000453:epidemiology
D013232:Steel