What degree of work overload is likely to cause increased sickness absenteeism among nurses? Evidence from the RAFAELA patient classification system.
OBJECTIVE
This paper reports a study examining whether nurses' work overload is associated with increased sick leave and quantifying the loss of working days from work overload.


BACKGROUND
The RAFAELA patient classification system indicates nursing care intensity in relation to an optimum and is one of the few validated monitoring instruments of patient-associated workload among nurses. However, it is not clear whether work overload is a risk factor for increased sickness absenteeism, an important occupational problem in health care.


METHODS
An observational cohort study was carried out with 877 nurses, 31 wards and five Finnish hospitals. Patient-associated workload scores from the RAFAELA system were based on a 6-month monitoring period in 2004. Records of 12-month self certified (1-3 days) and medically certified (>3 days) periods of sick leave in the same year were obtained from employers' registers.


RESULTS
The mean workload was 9% (sd = 8%) above the optimum. There was a linear trend between increasing workload and increasing sick leave (P < or = 0.006). Among nurses with workload > or =30% above the optimum the rate of self certified periods of sick leave was 1.44 (95% CI 1.13-1.83) times higher than among those with an optimum workload. The corresponding rate ratio for medically certified sick leave was 1.49 (1.10-2.03). These excess rates of sickness absence resulted in 12 extra sick leave days per person-year.


CONCLUSIONS
Measuring nurses' workload may be an important part of strategic human resource management of nurses to reduce sick leave among nurses.
Rauhala
Auvo
A
Vaasa Hospital District, Vaasa, Finland.
Kivimäki
Mika
M
Fagerström
Lisbeth
L
Elovainio
Marko
M
Virtanen
Marianna
M
Vahtera
Jussi
J
Rainio
Anna-Kaisa
AK
Ojaniemi
Kati
K
Kinnunen
Juha
J
D000041:Absenteeism; D000328:Adult; D015331:Cohort Studies; D005260:Female; D005387:Finland; D006801:Humans; D008297:Male; D008875:Middle Aged; D009741:Nursing Staff, Hospital / Q000458:organization & administration*; D010562:Personnel Staffing and Scheduling Information Systems; D018582:Sick Leave / Q000706:statistics & numerical data*; D016526:Workload