Complex problems in health related domains (particularly in health care and occupational health) means to face several big data problems. In the context of intervention and risk assessment KOHS showed that an edge-to-edge based architecture is needed to deal with these challenges.
Edge-to-edge based architecture means – technically – that multiple computing nodes work de-centrally and connected to each other (cloud of edges). Data is acquired, processed and stored locally on each node and independently from other computing nodes but are always able to connect, share data and even distribute computing tasks.
The architecture KOHS is developing does apply this edge-to-edge approach on processes of intervention and risk assessment.
PIMEX based intervention and risk assessment (domain of occupational health)
PIMEX (PIcture-Mix-EXposure) is a method for visualising health hazards at the workplace (cf. Rosén and Lundstrom, 1987).
The approach enables the analysis of working processes and an assessment of risks, resulting in a set of measures for the purpose of workplace improvement. A priority objective is to increase employees’ awareness of health hazards by imparting knowledge about interrelations between occupational strains, exposures and their consequences on health. (cf. Kviecien et al, 2006).
The aim of a PIMEX intervention is to achieve an optimal design of a working system (mainly: the worker interacting with technical artefacts working on tasks) (cf. Kauer et al, 2006).
A systematic and anticipatory debate on occupational safety and health topics in the course of interventions forms the core of a health promoting design of work, where a key aspect is the involvement of at-risk personnel in the analysis process (participative ergonomics).
The methodical use of PIMEX has to be seen as an intervention strategy (cf. Kviecien & Wichtl 2014). The effectiveness of the methodical use of PIMEX could be confirmed from different point of views (cf. Kuhl & Dobernowsky 2011, Kauer et al. 2006, Rosén et al. 2005).
A structured and traceable proceeding in the course of a PIMEX intervention further provides a basis for an integrated management approach. By applying the PIMEX method in context of different risk domains the focus shifts to a comprehensive view on prevention.
But as different risk domains are usually handled by different experts and are under responsibility of different institutions, organizations usually lack of knowledge to integrate the tasks in context of safety and health management (and other management areas) and to interconnect the produced data.
Thus an edge-to-edge based architecture – as KOHS is developing – is helpful to enable implementing an integrated management system step by step, as well as to provide a generic big data processing approach.
Rosén, G. and Lundstrom, S. (1987): Concurrent video filming and measuring for visualization of exposure. American Industrial Hygiene Association Journal 48/8, 688-692.
Kviecien H., Wichtl M. (2006), Visualisierung von Belastungen und Beanspruchungen als Basis einer partizipativen Arbeitssystemanalyse, 52. Arbeitswissenschaftlichen Kongress der GfA, GfA-Press, Dortmund
Kauer R, Kviecien H, Wichtl M (2006) Visualizing work-related strains and exposures as a basis for participative working-system analysis, 16th World Congress on Ergonomics – IEA 2006
Kviecien H, Wichtl M (2014) Analyse und Beurteilung von Belastung und Beanspruchung – PIMEX, In: Ausbildung zur Sicherheitsfachkraft, Band 4, 6. Auflage. Wien, Bohmann-Verlag S. 569-584
Kuhl K, Dobernowsky M (2011) Application of PIMEX method: Employees are motivated to change their working conditions and optimise preventive measures; in Work 39, A Journal of Prevention, Assessment & Rehabilitation No.4
Rosén G, Andersson I-M, Walsh PT, Clark RDR., Säämänen A, Heinonen K, Riipinen H, and Pääkkönen R (2005) A Review of Video Exposure Monitoring as an Occupational Hygiene Tool, Annals of Occupational Hygiene, volume 49, British Occupational Hygiene Society