Occupational injuries among healthcare workers and objective workload at a tertiary hospital in Lebanon: a retrospective study - Hani Mowafi; Samar Al-Hajj; Carine J Sakr; Ghassan M Khairallah; Khalil El-Asmar; Diana Rahme (BMJ Public Health)
Background Healthcare workers (HCWs) are at an increased risk of occupational injuries due to exposure to many hazards at work. The COVID-19 pandemic exacerbated these occupational risks, particularly with hospital employees working in increasingly demanding environments. HCW shortages further increase the risk of injury to remaining HCWs who shoulder the patient load with fewer human resources. This study aims to explore trends of occupational injuries in Lebanon—a country that faced a multi-faceted healthcare crisis with a severe economic collapse, a resulting massive HCW exodus, coupled with increased workload due to the COVID-19 pandemic. This study further investigates the association between HCW injuries and objective workload measures.Methods This is a retrospective study examining incident reports completed by HCWs over 5 years (January 2018 to December 2022). The data were complemented by monthly workload measures (admissions, occupied beds, procedures, ED visits, clinic visits) and absenteeism data. Analysis was performed using linear regression models to assess the relationship between workload predictors and injury rate.Results 2291 injuries were recorded, and 22.61% were sustained by registered nurses. The mean monthly injury rate was 1.68 per 100 EFTE, with an increased yearly trend. 40.39% of injuries were due to needle-pricks. Higher injury rates were found to be positively associated with workload: with each 1000 additional procedures each month (8.8% increase), the mean injury rate increased by 0.11 (95% CI 0.04 to 0.18, p value=0.002) (6.34% increase).Conclusion HCWs sustain a high burden of occupational injuries. Understanding the socio-economic factors and the changes in workload in relation to injury trends is crucial. The study offers valuable insights into suitable staffing and workload levels and can inform policies.