[Participant structure and economic benefit of prevention bonus programmes in company health insurance funds].
OBJECTIVE
This study investigates differences in sex, age, and educational level between participants and non-participants of prevention bonus programmes. The differences in the utilisation of drugs, hospital care, and sickness absence before the start of the programmes between these groups are also shown. Finally the economic benefit of the health insurance funds attributed to these programmes is estimated.


METHODS
Data from some 5.2 million insured subjects of 74 company health insurance funds in Germany were linked to information on enrollment into a prevention bonus programme anonymously. In a descriptive analysis the differences in the sociodemographic patterns between both groups are shown as well as the differences in costs to the health insurances in the three sectors mentioned above. The benefit to the health insurance funds is estimated by means of an analysis of covariance.


RESULTS
Prevention bonus programmes yields an annual benefit of at least 129 euro per participant. Men aged 40 and older and women aged 30 and older are more likely to opt into such a programme. The same is true for persons with a higher educational level. There are only few differences in health-care utilisation between the participants and non-participants of the programmes before enrollment. Only 1.4% of all insured persons participated in the programmes.


CONCLUSIONS
There is at least a short-term gain to both involved parties: the insured and the health insurance funds. The programmes are not dominated by deadweight effects. Long-term effects and effectiveness of prevention bonus programmes still have to be investigated.
Friedrichs
M
M
Institut für Prävention und Gesundheitsförderung an der Universität Duisburg-Essen, Team Gesundheit GmbH Essen, Frankfurt am Main. friedrichs@ipg-uni-essen.de
Friedel
H
H
Bödeker
W
W
D003362:Cost-Benefit Analysis; D004649:Employee Incentive Plans / Q000191:economics* / Q000706:statistics & numerical data*; D005260:Female; D005858:Germany; D015438:Health Behavior; D006293:Health Promotion / Q000191:economics* / Q000706:statistics & numerical data*; D006801:Humans; D007221:Industry / Q000191:economics*; D019458:Insurance Coverage / Q000191:economics* / Q000706:statistics & numerical data*; D008297:Male; D011314:Preventive Health Services / Q000191:economics / Q000706:statistics & numerical data; D012052:Reimbursement, Incentive / Q000191:economics / Q000706:statistics & numerical data