The effect of hospital mergers on long-term sickness absence among hospital employees: a fixed effects multivariate regression analysis using panel data.
BACKGROUND
Hospitals are merging to become more cost-effective. Mergers are often complex and difficult processes with variable outcomes. The aim of this study was to analyze the effect of mergers on long-term sickness absence among hospital employees.


METHODS
Long-term sickness absence was analyzed among hospital employees (N = 107 209) in 57 hospitals involved in 23 mergers in Norway between 2000 and 2009. Variation in long-term sickness absence was explained through a fixed effects multivariate regression analysis using panel data with years-since-merger as the independent variable.


RESULTS
We found a significant but modest effect of mergers on long-term sickness absence in the year of the merger, and in years 2, 3 and 4; analyzed by gender there was a significant effect for women, also for these years, but only in year 4 for men. However, men are less represented among the hospital workforce; this could explain the lack of significance.


CONCLUSIONS
Mergers has a significant effect on employee health that should be taken into consideration when deciding to merge hospitals. This study illustrates the importance of analyzing the effects of mergers over several years and the need for more detailed analyses of merger processes and of the changes that may occur as a result of such mergers.
Department of Health Management and Health Economics, Institute of Health and Society, Faculty of Medicine, University of Oslo, Forskningsveien 3a, 0373 Oslo, Norway. l.e.kjekshus@medisin.uio.no.
Lars Erik
LE
Kjekshus
Vilde Hoff
VH
Bernstrøm
Espen
E
Dahl
Thomas
T
Lorentzen
D000293:Adolescent; D000328:Adult; D000368:Aged; D005260:Female; D006273:Health Facility Merger / Q000706:statistics & numerical data*; D006801:Humans; D008297:Male; D008875:Middle Aged; D009664:Norway / Q000453:epidemiology; D010456:Peptides, Cyclic; D010564:Personnel, Hospital / Q000523:psychology / Q000706:statistics & numerical data*; D012737:Sex Factors; D018582:Sick Leave / Q000706:statistics & numerical data*; D055815:Young Adult
D010456:Peptides, Cyclic; C480605:cyclo(cysteinyl(3)-phenylalanyl(6)-phenylalanyl(7)-tryptophyl(8)-lysyl(9)-threonyl(10)-phenylalanyl(11)-cysteinyl(14))