The effect of influenza and pneumococcal vaccination in the elderly on health service utilisation and costs: a claims data-based cohort study

Background: To date, cost-effectiveness of influenza and pneumococcal vaccinations was assumed in several health economic modelling studies, but confirmation by real-world data is sparse. The aim of this study is to assess the effects on health care utilisation and costs in the elderly using real-world data on both, outpatient and inpatient care. Methods: Retrospective community-based cohort study with 138,877 individuals aged ≥ 60 years, insured in a large health insurance fund in Thuringia (Germany). We assessed health care utilisation and costs due to influenza- or pneumococcal-associated diseases, respiratory infections, and sepsis in 2015 and 2016. Individuals were classified into four groups according to their vaccination status from 2008 to 2016 (none, both, or either only influenza or pneumococcal vaccination). Inverse probability weighting based on 236 pre-treatment covariates was used to adjust for potential indication and healthy vaccinee bias. Results: Influenza vaccination appeared as cost-saving in 2016, with lower disease-related health care costs of − €178.87 [95% CI − €240.03;− €117.17] per individual (2015: − €50.02 [95% CI − €115.48;€15.44]). Cost-savings mainly resulted from hospital inpatient care, whereas higher costs occurred for outpatient care. Overall cost savings of pneumococcal vaccination were not statistically significant in both years, but disease-related outpatient care costs were lower in pneumococci-vaccinated individuals in 2015 [− €9.43; 95% CI − €17.56;− €1.30] and 2016 [− €12.93; 95% CI − €25.37;− €0.48]. Although we used complex adjustment, residual bias cannot be completely ruled out. Conclusion: Influenza and pneumococcal vaccination in the elderly can be cost-saving in selective seasons and health care divisions. As cost effects vary, interpretation of findings is partly challenging.Peer Reviewe

Structural characteristics and contractual terms of specialist palliative homecare in Germany

Background Multi-professional specialist palliative homecare (SPHC) teams care for palliative patients with complex symptoms. In Germany, the SPHC directive regulates care provision, but model contracts for each federal state are heterogeneous regarding staff requirements, cooperation with other healthcare providers, and financial reimbursement. The structural characteristics of SPHC teams also vary. Aim We provide a structured overview of the existing model contracts, as well as a nationwide assessment of SPHC teams and their structural characteristics. Furthermore, we explore whether these characteristics serve to find specifc patterns of SPHC team models, based on empirical data. Methods This study is part of the multi-methods research project “SAVOIR”, funded by the German Innovations Fund. Most model contracts are publicly available. Structural characteristics (e.g. number, professions, and affiliations of team members, and external cooperation) were assessed via an online database (“Wegweiser Hospiz- und Palliativversorgung”) based on voluntary information obtained from SPHC teams. All the data were updated by phone during the assessment process. Data were descriptively analysed regarding staff, cooperation requirements, and reimbursement schemes, while latent class analysis (LCA) was used to identify structural team models. Results Model contracts have heterogeneous contract partners and terms related to staff requirements (number and qualifications) and cooperation with other services. Fourteen reimbursement schemes were available, all combining different payment models. Of the 283 SPHC teams, 196 provided structural characteristics. Teams reported between one and 298 members (mean: 30.3, median: 18), mainly nurses and physicians, while 37.8% had a psychosocial professional as a team member. Most teams were composed of nurses and physicians employed in different settings; for example, staff was employed by the team, in private practices/nursing services, or in hospitals. Latent class analysis identified four structural team models, based on the team size, team members’ affiliation, and care organisation. Conclusion Both the contractual terms and teams’ structural characteristics vary substantially, and this must be considered when analysing patient data from SPHC. The identified patterns of team models can form a starting point from which to analyse different forms of care provision and their impact on care quality