Aim
In view of increasing concern about a two-class system in the German health care sector, this study investigates the relevance
of health insurance schemes and other socioeconomic characteristics to the level of specialist health care provision.
Subjects and Methods
Referring to Ronald M. Andersen’s model of health care utilization and more content-based approaches, we implement a negative
binomial hurdle regression to estimate the number of specialist visits within the last 12 months. Our data source is the German
sample of the first wave of the Survey of Health, Ageing and Retirement in Europe (SHARE) in 2004.
Results
The results show that men’s number of specialist visits is markedly sensitive to predisposing and enabling factors, whereas women’s health care utilization depends less on such socioeconomic characteristics. With reference to previous
findings concerning general practitioner consultation, the assumption of a bipolar health care system providing general practitioner care primarily to the statutory insured and specialist care to the privately insured is supported
empirically as to men. Education, which is considered to be highly correlated with health lifestyles, has a positive effect
on medical health care. Every additional year of education increases by about 10% the probability of men seeking specialist
consultation. Furthermore, the results indicate an unfavorable situation for the self-employed concerning health care because
of their specific employment situation and health insurance coverage.
Discussion
The research results suggest the existence of relevant differences in the amount of specialist consultation according to health
insurance and other socioeconomic features. Further research could concentrate on the question of whether these inequalities
in utilization levels indicate overprovision or underprovision of ambulant health care. Moreover, we recommend longitudinal
research that is particularly suited to detangle age and cohort effects.
Keywords Specialist consultation - Health care utilization - Health insurance - Supply-induced demand - Hurdle regression