{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,6,17]],"date-time":"2026-06-17T01:31:51Z","timestamp":1781659911114,"version":"3.54.5"},"reference-count":25,"publisher":"Georg Thieme Verlag KG","issue":"02","funder":[{"name":"ROCHE Pharma AG"},{"name":"Research Grant"},{"name":"Rudlof-Marx-Stiftung"},{"name":"Research grant"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Hamostaseologie"],"published-print":{"date-parts":[[2026,4]]},"abstract":"<jats:title>Abstract<\/jats:title>\n                  <jats:p>Claims data are increasingly discussed to evaluate health care for rare diseases (resource consumption, outcomes and costs). Using haemophilia A (HA) as a use case, this analysis aimed to generate evidence for the aforementioned information using German Statutory Health Insurance (SHI) claims data. Claims data (2017\u20132019) from the German SHI \u2018AOK Bayern - Die Gesundheitskasse\u2019 were used. Patients with ICD-10-GM codes D66 and HA medication were included in descriptive analyses. Severity levels were categorized according to HA medication consumption. In total, 257 patients were identified: mild HA, 104 patients (mean age: 40.0 years; SD: 22.9); moderate HA, 17 patients, (51.2 years; SD: 24.5); severe HA, 128 patients, (34.2 years; SD: 18.5). There were eight patients categorized with inhibitors (37.8 years; SD: 29.6). Psychotherapy was reported among 28.8% (mild) to 32.8% (severe) of patients. Joint disease was documented for 46.2% (mild) to 61.7% (severe) of patients. Mean direct costs per patient per year were 1.34\u00d7 for mild, 11\u00d7 for moderate, 81\u00d7 higher for severe HA patients and 223\u00d7 higher for inhibitor patients than the mean annual expenditure per AOK Bayern insurant (2019). German SHI data provide comprehensive information. The patient burden in HA is significant with respect to joint disease and psychological stress regardless of the HA severity level. The cost of HA care for patients is high. Large cost ranges suggest that the individual situation of a patient must be considered when interpreting costs. The main limitation of SHI data analysis for HA was the lack of granularity of ICD codes.<\/jats:p>","DOI":"10.1055\/a-2276-4871","type":"journal-article","created":{"date-parts":[[2024,7,1]],"date-time":"2024-07-01T19:19:23Z","timestamp":1719861563000},"page":"117-126","source":"Crossref","is-referenced-by-count":2,"title":["Can German Health Insurance Claims Data Fill Information Gaps in Rare Chronic Diseases: Use Case of Haemophilia A"],"prefix":"10.1055","volume":"46","author":[{"ORCID":"https:\/\/orcid.org\/0009-0002-2441-5545","authenticated-orcid":false,"given":"Vanessa","family":"Kratzer","sequence":"additional","affiliation":[{"name":"Institute for Medical Information Processing, Biometry, and Epidemiology - IBE, Ludwig Maximilian University of Munich, Munich, Germany"},{"name":"Comprehensive Cancer Center, CCC M\u00fcnchen LMU, Munich, Germany"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Verena","family":"R\u00f6lz","sequence":"additional","affiliation":[{"name":"Institute for Medical Information Processing, Biometry, and Epidemiology - IBE, Ludwig Maximilian University of Munich, Munich, Germany"},{"name":"Pettenkofer School of Public Health, Munich, Germany"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Christoph","family":"Bidlingmaier","sequence":"additional","affiliation":[{"name":"Kinderklinik und Kinderpoliklinik im Dr. von Haunerschen Kinderspital, Ludwig Maximilian University Hospital, Munich, Germany"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Robert","family":"Klamroth","sequence":"additional","affiliation":[{"name":"Vivantes Klinikum im Friedrichshain, Klinik f\u00fcr Innere Medizin Angiologie und H\u00e4mostaseologie, Berlin, Germany"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Jochen","family":"Behringer","sequence":"additional","affiliation":[{"name":"AOK Bayern - Die Gesundheitskasse Bereich Exzellenzzentrum Analytik u. Daten Fachbereich Datengovernance, AOK Bayern, M\u00fcnchen, Germany"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-4703-2355","authenticated-orcid":false,"given":"Anja","family":"Schramm","sequence":"additional","affiliation":[{"name":"AOK Bayern - Die Gesundheitskasse Bereich Exzellenzzentrum Analytik u. 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