Deprivation as a fundamental cause of morbidity and reduced life expectancy: an observational study using German statutory health insurance data.

Across all developed countries, there is a steep life expectancy gradient with respect to deprivation. This paper provides a theoretical underpinning for this gradient in line with the Grossman model, indicating that deprivation affects morbidity and, consequently, life expectancy in three ways: directly from deprivation to morbidity, and indirectly through lower income and a trade-off between investments in health and social status. Using rich German claims data covering 6.3 million insured people over four years, this paper illustrates that deprivation increases morbidity and reduces life expectancy. It was estimated that highly deprived individuals had approximately two more chronic diseases and a life expectancy reduced by 15 years compared to the least deprived individuals. This mechanism of deprivation is identified as fundamental, as deprived people remain trapped in their social status, and this status results in health investment decisions that affect long-term morbidity. However, in the German setting, the income and investment paths of the effects of deprivation were of minor relevance due to the broad national coverage of its SHI system. The most important aspects of deprivation were direct effects on morbidity, which accumulate over the lifespan. In this respect, personal aspects, such as social status, were found to be three times more important than spatial aspects, such as area deprivation.

Modelling the effect of demographic change and healthcare infrastructure on the patient structure in German hospitals - a longitudinal national study based on official hospital statistics.

BACKGROUND: Effects of demographic change, such as declining birth rates and increasing individual life expectancy, require health system adjustments offering age- and needs-based care. In addition, healthcare factors can also influence health services demand. METHODS: The official German hospital statistics database with odd-numbered years between 1995 and 2011 was analysed. This is a national comprehensive database of all general hospital inpatient services delivered. Official data from hospital statistics were linked at the district level with demographic and socio-economic data as well as population figures from the official regional statistics. Panel data regression, modelling case numbers per hospital, was performed for 13 diagnosis groups that characterised the patient structure. Socio-demographic variables included age, sex, household income, and healthcare factors included bed capacity, personnel and hospital characteristics. RESULTS: The median number of annual treatments per hospital increased from 6 015 (5th and 95th percentile [670; 24 812]) in 1995 to 7 817 in 2011 (5th and 95th percentile [301; 33 651]). We developed models characterising the patient structure of health care in Germany, considering both socio-demographic and hospital factors. Demographic factors influenced case numbers across all major diagnosis groups. For example, the age groups 65-74 and 75 + influenced cerebrovascular disease case numbers (p < 0.001). Other important factors included human and material resources of hospitals or the household income of patients. Distinct differences between the models for the individual diagnosis groups were observed. CONCLUSIONS: Hospital planning should not only consider demographic change but also hospital infrastructure and socio-economic factors.

Recommendation of rotavirus vaccination and herd effect: a budget impact analysis based on German health insurance data.

The objective of this study was to assess the budget impact and health effects of introducing rotavirus (RV) vaccination in Saxony, Germany, from a health insurance perspective. Special emphasis is given to the herd effect. We analyzed direct medical and non-medical costs of RV infection for Social Health Insurance between 2007 and 2010 based on 360,000 routine data observations from the AOK PLUS for children below 5 years of age. We compared the actual annual number of RV cases (vaccination scenario) with the number derived from 2005 (no vaccination, base case scenario). The vaccination coverage rate has increased from 5% to 61% between 2007 and 2010. The number of RV cases decreased by 21% from 32,274 in 2007 to 25,614 in 2010. Based on vaccination coverage, the total cost savings per 1,000 children due to RV vaccination was estimated to be 39,686 Euros. The overall share of outpatient costs was 60%. Mean gross cost savings were expected to be 304 Euros per avoided case. The net cost savings were expected to be 19 Euros per avoided case. About 59% of total savings was due to herd protection resulting from increasing vaccine rates. The herd effect per avoided case increased with increasing vaccine coverage. Incidence of RV cases, vaccination costs and days absent from work were sensitive parameters. This retrospective analysis showed that the increase in RV vaccination coverage in Saxony has been budget neutral if not cost saving for sick funds.