Important questions still need to be clarified regarding Germany’s Hospital Care Improvement Act, which goes into effect on 1 January 2025, according to Prof. Dr. Johannes Wessling, head of the German Roentgen Society's (DRG's) working group on hospital reform.
Prof. Dr. Johannes Wessling. Image courtesy of the DRG.
“There are now fears that the detailed work on the law that is urgently needed for practical implementation will be delayed. The DRG and the radiological organizations will continue to be persistent in their involvement in the ongoing process and will do persuasive work at all political levels,” Wessling said in a statement issued on 18 December.
The new law was passed by the German parliament in November and is aimed at reorganizing the country’s health sector by cutting the number of hospitals, boosting clinics, and digitalizing bureaucracy, according to reports.
In his statement on the law, Wessling noted that it is still unclear how the federal government will finance the upcoming restructuring, as well as what the uniform quality criteria and minimum case numbers should be, as these will determine whether a clinic is assigned certain service groups with corresponding provisional remuneration.
“We are also seeking dialogue with the responsible actors in the federal states and will work towards an adequate representation of radiological services in the overall system of service groups,” he said.

















![Overview of the study design. (A) The fully automated deep learning framework was developed to estimate body composition (BC) (defined as subcutaneous adipose tissue [SAT] in liters; visceral adipose tissue [VAT] in liters; skeletal muscle [SM] in liters; SM fat fraction [SMFF] as a percentage; and intramuscular adipose tissue [IMAT] in deciliters) from MRI. The fully automated framework comprised one model (model 1) to quantify different BC measures (SAT, VAT, SM, SMFF, and IMAT) as three-dimensional (3D) measures from whole-body MRI scans. The second model (model 2) was trained to identify standardized anatomic landmarks along the craniocaudal body axis (z coordinate field), which allowed for subdividing the whole-body measures into different subregions typically examined on clinical routine MRI scans (chest, abdomen, and pelvis). (B) BC was quantified from whole-body MRI in over 66,000 individuals from two large population-based cohort studies, the UK Biobank (UKB) (36,317 individuals) and the German National Cohort (NAKO) (30,291 individuals). Bar graphs show age distribution by sex and cohort. BMI = body mass index. (C) After the performance assessment of the fully automated framework, the change in BC measures, distributions, and profiles across age decades were investigated. Age-, sex-, and height-adjusted body composition reference curves were calculated and made publicly available in a web-based z-score calculator (https://circ-ml.github.io).](https://img.auntminnieeurope.com/mindful/smg/workspaces/default/uploads/2026/05/body-comp.XgAjTfPj1W.jpg?auto=format%2Ccompress&fit=crop&h=112&q=70&w=112)