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LTIFR Calculator

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About the calculator


The Lost Time Injury frequency rate (LTIFR) measures the number of lost-time injuries per million hours worked during a single financial year. A lost-time injury is one that resulted in time lost from work of one day/shift or more. This includes injuries resulting in fatality or permanent disability.

LTIFRs are useful for drawing conclusions about the factors that contribute to lost productivity, including inadequate injury prevention. However, they should not be used to evaluate WHS performance.

Calculating LTIFR

The formula to calculate an LTIFR is:

Lost time injuries in financial year / Hours worked in financial year x 1,000,000

Example:

In 2022, a mining company experienced 5 lost time injuries. Three of the injured employees were away from work for two days, one for three days, and one for a whole week.

The company has a workforce of 1,000 employees. During 2022, total hours worked by all employees was 1,950,000 hours.

To calculate the company's LTIFR:
  • Number of people who lost time from work for one shift or more: 5
  • Total hours worked (for all company employees) during the year: 1,950,000 hours

Use the Formula:

LTIFR=(Number of lost time injuriesTotal hours worked)×1,000,000\text{LTIFR} = \left( \frac{\text{Number of lost time injuries}}{\text{Total hours worked}} \right) \times 1,000,000


LTIFR=(51,950,000)×1,000,000=2.56\text{LTIFR} = \left( \frac{5}{1,950,000} \right) \times 1,000,000 = 2.56



So, the LTIFR for the mining company in 2022 is 2.56. If we were to compare it to an industry standard, let's say the average mining industry rate is 4.2, then the company's LTIFR of 2.56 is below the industry average.

In summary:
  • Number of lost time injuries during the year: 5
  • Hours worked during the year: 1,950,000
  • LTIFR = 2.56

Limitations of LTIFRs

  • LTIFs are intended as a guide only and should be interpreted carefully.
  • LTIFRs are not recommended for small businesses, where changes to the number of injuries or workers' compensation claims are likely to result in a LTIFR that is much larger or smaller than expected.

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