title: When healthcare workers get sick: exploring sickness absenteeism in British Columbia, Canada.
abstract: OBJECTIVE
  To determine the demographic and work characteristics of healthcare workers who were more likely to take sickness absences from work in British Columbia, Canada.
  
  
  METHODS
  Payroll data were analyzed for three health regions. Sickness absence rates were determined per person-year and then compared across demographic and work characteristics using multivariate Poisson regression models. The direct costs to the employer due to sickness absences were also estimated.
  
  
  RESULTS
  Female, older, full-time workers, long-term care workers and those with a lower hourly wage were more likely to take sickness absences and had similar trends with respect to the costs due to sickness absence. For occupations, licensed practical nurses, care aides and facility support workers had higher rates of sickness absence. Registered nurses, and those workers paid high hourly wages were associated with highest sickness related costs.
  
  
  CONCLUSIONS
  It is important to understand the demographic and work characteristics of those workers who are more likely to take sickness absences in order to make sure that they are not experiencing additional hazards at work or facing detrimental workplace conditions. Policy makers need to establish healthy, safe and in turn more productive workplaces. Further research is needed on how interventions can reduce sickness absence.
authors.affiliation: Occupational Health and Safety Agency for Healthcare, BC, Vancouver, BC, Canada.
authors.forename: Erin
authors.initials: E
authors.lastname: Gorman
authors.forename: Shicheng
authors.initials: S
authors.lastname: Yu
authors.forename: Hasanat
authors.initials: H
authors.lastname: Alamgir
mesh_terms: D000328:Adult; D001955:British Columbia; D017281:Cost of Illness; D003430:Cross-Sectional Studies; D005260:Female; D006282:Health Personnel / Q000706:statistics & numerical data; D006801:Humans; D008297:Male; D008875:Middle Aged; D015999:Multivariate Analysis; D016012:Poisson Distribution; D012044:Regression Analysis; D012307:Risk Factors; D018582:Sick Leave / Q000706:statistics & numerical data*