Skip to main page content
U.S. flag

An official website of the United States government

Dot gov

The .gov means it’s official.
Federal government websites often end in .gov or .mil. Before sharing sensitive information, make sure you’re on a federal government site.

Https

The site is secure.
The https:// ensures that you are connecting to the official website and that any information you provide is encrypted and transmitted securely.

Access keys NCBI Homepage MyNCBI Homepage Main Content Main Navigation
. 2018 Jan;60(1):55-73.
doi: 10.1097/JOM.0000000000001162.

Applying Machine Learning to Workers' Compensation Data to Identify Industry-Specific Ergonomic and Safety Prevention Priorities: Ohio, 2001 to 2011

Alysha R Meyers  1 , Ibraheem S Al-Tarawneh, Steven J Wurzelbacher, P Timothy Bushnell, Michael P Lampl, Jennifer L Bell, Stephen J Bertke, David C Robins, Chih-Yu Tseng, Chia Wei, Jill A Raudabaugh, Teresa M Schnorr
Affiliations

Applying Machine Learning to Workers' Compensation Data to Identify Industry-Specific Ergonomic and Safety Prevention Priorities: Ohio, 2001 to 2011

Alysha R Meyers et al. J Occup Environ Med. 2018 Jan.

Abstract

Objective: This study leveraged a state workers' compensation claims database and machine learning techniques to target prevention efforts by injury causation and industry.

Methods: Injury causation auto-coding methods were developed to code more than 1.2 million Ohio Bureau of Workers' Compensation claims for this study. Industry groups were ranked for soft-tissue musculoskeletal claims that may have been preventable with biomechanical ergonomic (ERGO) or slip/trip/fall (STF) interventions.

Results: On the basis of the average of claim count and rate ranks for more than 200 industry groups, Skilled Nursing Facilities (ERGO) and General Freight Trucking (STF) were the highest risk for lost-time claims (>7 days).

Conclusion: This study created a third, major causation-specific U.S. occupational injury surveillance system. These findings are being used to focus prevention resources on specific occupational injury types in specific industry groups, especially in Ohio. Other state bureaus or insurers may use similar methods.

PubMed Disclaimer

Conflict of interest statement

The authors have no conflicts of interest.

Figures

FIGURE 1
FIGURE 1
(A–C) Yearly claim rates per 100 estimated FTEyears for the five largest NORA sectors by intervention category, for lost-time claims, 2001–2011: (A) ERGO, Ergonomic intervention category that includes BLS-defined work-related musculoskeletal disorders caused by ergonomic hazards; (B) STF, slip, trip, or fall intervention category; and (C) OTH, other intervention category. Notes: Rates current as of February 2017. Services sector, Services (except Public Safety); Trade sector, Wholesale Trade/Retail Trade; Healthcare sector, Healthcare and Social Assistance; lost-time claims, 8 or more days away from work.
FIGURE 2
FIGURE 2
High-priority NAICS industry groups (four-digit codes) for lost-time ERGO claims for the top 25 by Prevention Index rankings and top 10 by claim rates, 2001–2011. Note: Data current as of February 2017. Bubble size is based on the estimated number of FTE-years. Lost-time claims, 8 or more days away from work. ERGO, Ergonomic intervention category (includes BLS-defined work-related musculoskeletal disorders caused by ergonomic hazards).
FIGURE 3
FIGURE 3
High-priority NAICS industry groups (four-digit codes) for lost-time STF claims for the top 25 by Prevention Index rankings and top 10 by claim rates, 2001– 2011. Note: Data current as of February 2017. Bubble size is based on the estimated number of FTE-years. Lost-time claims, 8 or more days away from work. STF, Slip, trip, or fall intervention category.
FIGURE 4
FIGURE 4
High-priority NAICS industry groups (four-digit codes) for lost-time OTH claims for the top 25 by Prevention Index rankings and top 10 by claim rates, 2001–2011. Note: Data current as of February 2017. Bubble size is based on the estimated number of FTE-years. Lost-time claims, 8 or more days away from work. OTH, Other intervention category.
FIGURE 5
FIGURE 5
(A–F) Box-plot charts* of the distribution of industry (five-digit NAICS) claim rates per 100 estimated FTE-years per NORA† sector for the five largest NORA sectors, aggregated for the time period 2001–2011, presented by intervention category and claim type: (A) ERGOlost-time, (B) ERGOtotal, (C) STFlost-time, (D) STFtotal, (E) OTHlost-time, (F) OTHtotal. Notes: The Ergonomic intervention category includes BLS-defined work-related musculoskeletal disorders caused by ergonomic hazards. Data current as of February 2017. FTE, full-time equivalent employee (2000 hours/year); Healthcare sector, Healthcare and Social Assistance; lost-time claims, 8 or more days away from work; NORA, National Occupational Research Agenda; OTH, all other; Services sector, Services (except Public Safety); STF, slip, trip or fall; Transportation sector, Transportation, Warehousing, Utilities; Trade sector, Wholesale Trade/Retail Trade. *Box plots lower whisker, minimum rate; bar, interquartile range where the dark shade, the 25th percentile to median and light shade, median to 75th percentile; upper whisker, maximum rate, except the Services Total claims maximum rates for ERGO (23.66) and STF (10.85), and the Manufacturing Total claims rate for OTH (15.0, for Ferrous Metal Foundries, NAICS = 33151) are not shown. Both extreme Services sector outliers were for Dance Companies, NAICS = 71112. †Among privately owned employers in Ohio with single and multiple locations.
See this image and copyright information in PMC

Similar articles

See all similar articles

Cited by

See all "Cited by" articles

References

    1. Bureau of Labor Statistics. Bureau of Labor Statistics News Release, USDL-11–1612. Washington, DC: U.S. Department of Labor; 2015. Nonfatal Occupational Injuries and Illnesses Requiring Days Away from Work, 2014; p. 31.
    1. Liberty Mutual Research Institute for Safety. 2016 Liberty Mutual Workplace Safety Index. Hopkinton, MA: 2016. p. 2.
    1. Bureau of Labor Statistics. Table 6. Percent Distribution of Nonfatal Occupational Injuries and Illnesses Involving Days Away from Work 1 by Selected Injury or Illness Characteristics and Major Industry Sector. Private Industry; Ohio: 2014. 2015. Available at: https://www.bwc.ohio.gov/employer/programs/safety/soii/StatsArchive3.asp. Accessed 14, 2017.
    1. Bureau of Labor Statistics. Occupational Injuries and Illnesses: Characteristics Data (CS) Washington, DC: U.S. Department of Labor; 2015. Nonfatal Cases Involving Days Away From Work: Selected Characteristics by Detailed Industry by Detailed Event or Exposure with Falls, Slips, Trips, All U.S., All Workers, Private industry, (2011–2014)
    1. Bureau of Labor Statistics. Table 1. Number of Nonfatal Occupational Injuries and Illnesses Involving Days Away from Work by Industry and Selected Natures of Injury or Illness, All United States, Private Industry, 2014. Washington, DC: U.S. Department of Labor; 2015.

Publication types