Back

Trends in Breast Pump Prescription Claims: A Nationwide Population-Based Study of Outpatient Statutory Health Insurance Billing Data in Germany, 2011 to 2024

Fischer, L.; Daudi, A. E.; Haile, Z. T.; Theurich, M. A.

2026-02-17 public and global health
10.64898/2026.02.13.26345532 medRxiv
Show abstract

ObjectiveThe objective of this analysis was to explore temporal and regional trends in breast pump prescription claims in outpatient settings in Germany, and to characterize the types of pumps covered. Study designWe conducted a nationwide secondary analysis of outpatient statutory health insurance billing data for breast pump prescriptions from 2011 to 2024, covering nearly 90% of the German population. Billing data from community pharmacies were scaled to full national coverage using regional extrapolation factors and subsequently linked with national and state-level live birth statistics to adjust for birth rates and population size across federal states. A list of breast pumps covered by German national statutory health insurance funds was queried for information on their characteristics. ResultsPrescription of electric pumps dominate outpatient statutory health insurance breast pump claims in Germany, with national statutory health insurance funds covering {euro}15.3 million for pump rentals. Manual pumps dispensed through community pharmacies accounted for {euro}27 thousand in 2024. Between 2011 and 2024, electric pump claims increased by a factor of 2.57, rising from 235.4 to 605.2 claims per 1000 infants newly enrolled in statutory health insurance (average annual growth rate 8.24%). Claims varied substantially across federal states but increased overall. ConclusionsThis is the first epidemiological analysis of statutory health insurance prescription claims for breast pumps in Germany. We found that electric breast pumps are important medical devices supporting outpatient human milk expression in Germany. Prescription claims appear to be very common and have shown an increase over the past 13 years.

Matching journals

The top 7 journals account for 50% of the predicted probability mass.

50% of probability mass above

"Similar papers" are the closest papers from that journal in the model's embedding space. They show what the match is built on, but the ranking comes mostly from a classifier over the whole training set, not from these examples alone.