Analysing factors related to slipping, stumbling, and falling accidents at work: Application of data mining methods to Finnish occupational accidents and diseases statistics database.

The utilisation of data mining methods has become common in many fields. In occupational accident analysis, however, these methods are still rarely exploited. This study applies methods of data mining (decision tree and association rules) to the Finnish national occupational accidents and diseases statistics database to analyse factors related to slipping, stumbling, and falling (SSF) accidents at work from 2006 to 2007. SSF accidents at work constitute a large proportion (22%) of all accidents at work in Finland. In addition, they are more likely to result in longer periods of incapacity for work than other workplace accidents. The most important factor influencing whether or not an accident at work is related to SSF is the specific physical activity of movement. In addition, the risk of SSF accidents at work seems to depend on the occupation and the age of the worker. The results were in line with previous research. Hence the application of data mining methods was considered successful. The results did not reveal anything unexpected though. Nevertheless, because of the capability to illustrate a large dataset and relationships between variables easily, data mining methods were seen as a useful supplementary method in analysing occupational accident data.

[1]  Olaf C Jensen,et al.  Reduction of slips, trips and falls and better comfort by using new anti-slipping boots in fishing , 2011, International journal of injury control and safety promotion.

[2]  Chia-Wen Liao,et al.  Discovery of unapparent association rules based on extracted probability , 2009, Decis. Support Syst..

[3]  Nicholas Stergiou,et al.  The effects of shoe traction and obstacle height on lower extremity coordination dynamics during walking. , 2009, Applied ergonomics.

[4]  Das Amrita,et al.  Mining Association Rules between Sets of Items in Large Databases , 2013 .

[5]  D. P. Manning,et al.  Occupational slip, trip, and fall-related injuries can the contribution of slipperiness be isolated? , 2001, Ergonomics.

[6]  Chia-Wen Liao,et al.  Data mining for occupational injuries in the Taiwan construction industry , 2008 .

[7]  Alexandre Villeminot,et al.  Combined use of association rules mining and clustering methods to find relevant links between binary rare attributes in a large data set , 2007, Comput. Stat. Data Anal..

[8]  Chia-Fen Chi,et al.  Reanalyzing occupational fatality injuries in Taiwan with a model free approach , 2003 .

[9]  Wen-Ruey Chang,et al.  Prevention of fall-related accidents , 2005 .

[10]  Wen-Ruey Chang,et al.  Evaluation of a comprehensive slip, trip and fall prevention programme for hospital employees , 2008, Ergonomics.

[11]  Heikki Mannila,et al.  Principles of Data Mining , 2001, Undergraduate Topics in Computer Science.

[12]  Tim Bentley,et al.  The role of latent and active failures in workplace slips, trips and falls: an information processing approach. , 2009, Applied ergonomics.

[13]  M S Redfern,et al.  Biomechanics of slips , 2001, Ergonomics.

[14]  M. Bevilacqua,et al.  Industrial and occupational ergonomics in the petrochemical process industry: a regression trees approach. , 2008, Accident; analysis and prevention.

[15]  Paolo Giudici,et al.  Applied Data Mining: Statistical Methods for Business and Industry , 2003 .

[16]  Filippo Emanuele Ciarapica,et al.  Classification and prediction of occupational injury risk using soft computing techniques: An Italian study , 2009 .

[17]  Wei-Chang Yeh,et al.  Using association rules and particle swarm optimization approach for part change , 2009, Expert Syst. Appl..

[18]  Li-Yen Chang,et al.  Analysis of traffic injury severity: an application of non-parametric classification tree techniques. , 2006, Accident; analysis and prevention.

[19]  Hester J Lipscomb,et al.  Injuries from slips and trips in construction. , 2006, Applied ergonomics.

[20]  Yanjun Wang,et al.  Harnessing data mining to explore incident databases. , 2006, Journal of hazardous materials.

[21]  Rajeev Motwani,et al.  Beyond market baskets: generalizing association rules to correlations , 1997, SIGMOD '97.

[22]  Chuansi Gao,et al.  A systems perspective of slip and fall accidents on icy and snowy surfaces , 2004, Ergonomics.

[23]  R. A. Haslama,et al.  Contributing factors in construction accidents , 2005 .

[24]  R. Cham,et al.  Changes in gait when anticipating slippery floors. , 2002, Gait & Posture.

[25]  Jamal Shahrabi,et al.  A New Accident Investigation Approach Based on Data Mining Techniques , 2009 .

[26]  T A Bentley,et al.  Identification of risk factors and countermeasures for slip, trip and fall accidents during the delivery of mail. , 2001, Applied ergonomics.

[27]  Ingvar Holmér,et al.  Slips and falls in a cold climate: underfoot surface, footwear design and worker preferences for preventive measures. , 2008, Applied ergonomics.

[28]  S Leclercq,et al.  Progress in understanding processes underlying occupational accidents on the level based on case studies , 2007, Ergonomics.

[29]  R. Suganya,et al.  Data Mining Concepts and Techniques , 2010 .

[30]  T. Lockhart,et al.  Nonfatal occupational injuries associated with slips and falls in the United States. , 2006, International journal of industrial ergonomics.

[31]  Chia-Fen Chi,et al.  Accident patterns and prevention measures for fatal occupational falls in the construction industry. , 2005, Applied ergonomics.

[32]  Richard Parker,et al.  Investigating slips, trips and falls in the New Zealand dairy farming sector , 2005, Ergonomics.

[33]  Ewa Menckel,et al.  Aging and occupational accidents a review of the literature of the last three decades , 1995 .

[34]  Maurizio Faccio,et al.  CLASSIFICATION OF OCCUPATIONAL INJURY CASES USING THE REGRESSION TREE APPROACH , 2006 .

[35]  S Leclercq,et al.  Systemic analysis of so-called ‘accidents on the level’ in a multi trade company , 2004, Ergonomics.

[36]  Sou-Sen Leu,et al.  Use of association rules to explore cause-effect relationships in occupational accidents in the Taiwan construction industry , 2010 .

[37]  Kristina Kemmlert,et al.  Slips, trips and falls in different work groups--with reference to age and from a preventive perspective. , 2001 .

[38]  R. McGorry,et al.  The anatomy of a slip: Kinetic and kinematic characteristics of slip and non-slip matched trials. , 2010, Applied ergonomics.