https://doi.org/10.1007/s00392-025-02625-4
1Universitätsklinikum Schleswig-Holstein Medizinische Klinik II / Kardiologie, Angiologie, Intensivmedizin Lübeck, Deutschland; 2Universitätsklinikum Schleswig-Holstein Klinik für Herz- und thorakale Gefäßchirurgie Lübeck, Deutschland; 3Curschmann Klinik Rehabilitationskrankenhaus für Kardiologie und Angiologie Timmendorfer Strand, Deutschland; 4Universitätsklinikum Schleswig-Holstein Klinik für Rhythmologie Lübeck, Deutschland
Purpose
Heart failure (HF) is associated with frequent rehospitalizations and increased mortality. HF networks are recommended to improve screening and management of HF patients. As the effects and clinical benefits of HF networks still remain unclear, we developed a HF network model and implemented this in North Germany with governmental support to optimize outcome of these patients.
Methods
A local multi-sectoral HF network was established first in the city of Lübeck, Germany and then for the state of Schleswig-Holstein in Northern Germany. A model of a local HF network is depicted in Figure 1A; in total 12 local pre-existing networks were connected to form a HF state network (Figure 1B). Patient trajectories through the healthcare system were analyzed from network inhospital databases to identify reasons for frequent rehospitalizations leading to a high burden in terms of resource and costs. HF coded patients in the advanced HF- and network coordinating Heart Center Lübeck were compared before (2018-2020) and after (2021-2023) network establishment.
Results
Outpatient treatment cases doubled (+101.3%), specialist and GP referrals were increased +49.7% and +17.9%, respectively (Figure 1C). HF rehospitalizations were numerically reduced (before vs. after: 20.3 vs. 17.9%; p=0.295). Elective patient referral rose for both general (+20.7%) and advanced HF cases after establishment (+40%). Analysis of treated advanced HF patients’ baseline characteristics showed earlier presentation with less deterioration (INTERMACS class before vs. after: 3.3±1.4 vs 4.4±1.9, p=0.044, cardiac index before vs. after: 1.2±0.31 vs 1.8±0.33, p<0.001). Rehospitalization of advanced HF patients within one year was high with 52.8%, dominated by cardiovascular causes (43%), followed by bleeding (21%) and infections (11%). The mortality rate in this cohort was low in the short follow-up period.
Conclusion
Changes in referral patterns and treatment cases show first positive outcome trends in this state-based HF network.
Figure 1.
A) Structure of the components of a local heart failure network model
B) Implementation and structure of a state HF network with a central network coordination
C) How the heart failure network changed the referral pattern