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  • DKFZ Publication Database  (2)
  • 1
    Abstract: OBJECTIVE: To investigate factors affecting willingness to pay (WTP) for health insurance of older adults in a longitudinal setting in Germany. DATA SOURCES: Survey data from a cohort study in Saarland, Germany, from 2008-2010 and 2011-2014 (n1 = 3,124; n2 = 2,761) were used. STUDY DESIGN: Panel data were taken at two points from an observational, prospective cohort study. DATA COLLECTION: WTP estimates were derived using a contingent valuation method with a payment card. Participants provided data on sociodemographics, lifestyle factors, morbidity, and health care utilization. PRINCIPAL FINDINGS: Fixed effects regression models showed higher individual health care costs to increase WTP, which in particular could be found for members of private health insurance. Changes in income and morbidity did not affect WTP among members of social health insurance, whereas these predictors affected WTP among members of private health insurance. CONCLUSIONS: The fact that individual health care costs affected WTP positively might indicate that demanding (expensive) health care services raises the awareness of the benefits of health insurance. Thus, measures to increase WTP in old age should target at improving transparency of the value of health insurances at the moment when individual health care utilization and corresponding costs are still relatively low.
    Type of Publication: Journal article published
    PubMed ID: 27324300
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  • 2
    Abstract: Background: To analyze the association of health care costs with predisposing, enabling, and need factors, as defined by Andersen's behavioral model of health care utilization, in the German elderly population. Methods: Using a cross-sectional design, cost data of 3,124 participants aged 57-84 years in the 8 year follow up of the ESTHER cohort study were analyzed. Health care utilization in a 3-month period was assessed retrospectively through an interview conducted by trained study physicians at respondents' homes. Unit costs were applied to calculate health care costs from the societal perspective. Socio-demographic and health-related variables were categorized as predisposing, enabling, or need factors as defined by the Andersen model. Multimorbidity was measured by the Cumulative Illness Rating Scale for Geriatrics (CIRS-G). Mental health status was measured by the SF-12 mental component summary (MCS) score. Sector-specific costs were analyzed by means of multiple Tobit regression models. Results: Mean total costs per respondent were 889 [sic] for the 3-month period. The CIRS-G score and the SF-12 MCS score representing the need factor in the Andersen model were consistently associated with total, inpatient, outpatient and nursing costs. Among the predisposing factors, age was positively associated with outpatient costs, nursing costs, and total costs, and the BMI was associated with outpatient costs. Conclusions: Multimorbidity and mental health status, both reflecting the need factor in the Andersen model, were the dominant predictors of health care costs. Predisposing and enabling factors had comparatively little impact on health care costs, possibly due to the characteristics of the German social health insurance system. Overall, the variables used in the Andersen model explained only little of the total variance in health care costs.
    Type of Publication: Journal article published
    PubMed ID: 24524754
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