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Abstract
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Virtual Pre-Conference Global Injury Prevention Showcase 2021 - Abstract Book - # 3F.001
Context Incident-reporting systems enable organisations to capture and analyse large volumes of occupational safety incidents. By counting and categorising hazard and incident reports, these systems are crucial to understanding broad organisational risk. However, these systems often ask incident 'victims' to pick from set categorical fields restricting the identification of micro-trends, local hazards and those not anticipated by the system designers. Qualitative data analysis is not a standard function of most large scale reporting systems, identifying local or unique hazards often occurs outside the reporting system relying on free-text comments. Addressing hazards in this manner is labour intensive and not often integrated into risk management pathways.
Process Cluster analysis using the freely available NODEXL software program provides means to analyse subjective incident data in a semi-quantitative manner. The data can self-categorise to form a picture of local level hazards. This presentation includes examples of this method used to analyse Workforce MSI, challenging behaviour and Mental Stress incident reports in Healthcare.
Outcomes A visual representation of qualitative incident data to inform local strategy.
A repeatable and targeted method of hazard ID.
The identification of new or unanticipated hazards and their interactions.
Local hazards to cross-reference against key areas of organisational risk.
Evidence for policy or strategy development/recombination of corrective actions.
Analysis Cluster Diagrams for Musculoskeletal injury, Mental Stress and Challenging Behaviour incidents.
Learning outcomes Understanding of qualitative analysis for strategy development.
Identifying multi-hazard interaction and associations.
Appreciation for a visual representation of hazard identification when developing in the risk-management strategy.
Language: en |