A PHP Error was encountered

Severity: Warning

Message: file_get_contents(https://...@gmail.com&api_key=61f08fa0b96a73de8c900d749fcb997acc09): Failed to open stream: HTTP request failed! HTTP/1.1 429 Too Many Requests

Filename: helpers/my_audit_helper.php

Line Number: 143

Backtrace:

File: /var/www/html/application/helpers/my_audit_helper.php
Line: 143
Function: file_get_contents

File: /var/www/html/application/helpers/my_audit_helper.php
Line: 209
Function: simplexml_load_file_from_url

File: /var/www/html/application/helpers/my_audit_helper.php
Line: 3098
Function: getPubMedXML

File: /var/www/html/application/controllers/Detail.php
Line: 574
Function: pubMedSearch_Global

File: /var/www/html/application/controllers/Detail.php
Line: 488
Function: pubMedGetRelatedKeyword

File: /var/www/html/index.php
Line: 316
Function: require_once

A PHP Error was encountered

Severity: Warning

Message: Attempt to read property "Count" on bool

Filename: helpers/my_audit_helper.php

Line Number: 3100

Backtrace:

File: /var/www/html/application/helpers/my_audit_helper.php
Line: 3100
Function: _error_handler

File: /var/www/html/application/controllers/Detail.php
Line: 574
Function: pubMedSearch_Global

File: /var/www/html/application/controllers/Detail.php
Line: 488
Function: pubMedGetRelatedKeyword

File: /var/www/html/index.php
Line: 316
Function: require_once

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

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

J Occup Environ Med

National Institute for Occupational Safety and Health, Division of Surveillance, Hazard Evaluations, and Field Studies, Center for Workers' Compensation Studies, Cincinnati, Ohio (Drs Meyers, Wurzelbacher, Ms Tseng); Ohio Bureau of Workers' Compensation, Division of Safety and Hygiene, Pickerington, Ohio (Dr Al-Tarawneh, Mr Lampl, Mr Robins); National Institute for Occupational Safety and Health, Office of the Director, Economic Research Support Office, Cincinnati, Ohio (Dr Bushnell); National Institute for Occupational Safety and Health, Division of Safety Research, Morgantown, West Virginia (Dr Bell); National Institute for Occupational Safety and Health, Division of Surveillance, Hazard Evaluations, and Field Studies, Cincinnati, Ohio (Dr Bertke, Ms Raudabaugh, Dr Schnorr); Taiwan Centers for Disease Control, Taipei City, Taiwan (Dr Wei).

Published: January 2018

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.

Download full-text PDF

Source
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC5868484PMC
http://dx.doi.org/10.1097/JOM.0000000000001162DOI Listing

Publication Analysis

Top Keywords

workers' compensation
12
industry groups
12
machine learning
8
compensation claims
8
injury causation
8
occupational injury
8
applying machine
4
learning workers'
4
compensation data
4
data identify
4

Similar Publications

Want AI Summaries of new PubMed Abstracts delivered to your In-box?

Enter search terms and have AI summaries delivered each week - change queries or unsubscribe any time!