Artikel
Rare Diseases in German University Medicine – a Comparison with National Case Statistics
Suche in Medline nach
Autoren
Veröffentlicht: | 24. September 2021 |
---|
Gliederung
Text
Introduction: With 263-446 million patients affected worldwide, rare diseases are a global health challenge [1]. As early diagnosis and adequate treatment are often difficult, rare diseases require specialized care. In Germany, care for rare disease patients is often provided at specialized centers (“Zentren für Seltene Erkrankungen”), typically located at university hospitals. University hospitals can therefore be assumed to have a higher number of rare disease cases than other, non-university hospitals.
Methods: To test this hypothesis and quantify the potentially higher number of rare disease cases in university medicine, we performed a simple, exploratory study that compares the proportion of inpatient cases with a main diagnosis of a rare disease in six German university hospitals with the proportion in a national case statistic across all German hospitals (approx. 2,000 hospitals, including university hospitals). These national cases statistics are publicly available from the the Federal Statistical Office (“Statistisches Bundesamt”, Destatis) [2]. The rare diseases included in the analysis were based on a study by the institute of the association of statutory health insurance physicians (“Zentralinstitut für die kassenärztliche Versorgung”) and comprised rare diseases with an unambiguous code in the International Statistical Classification of Diseases and Related Health Problems, 10th revision, German Modification (ICD-10-GM), excluding rare infectious diseases and tumors [3].
Results: Investigating 77 rare diseases coded with 143 ICD-10 codes, we found that the proportion of rare diseases was 3.14 times higher in the university hospitals than in the nationwide case statistic: Of 334,596 inpatient cases in 2019 in the six university hospitals, 3,095 cases had a rare disease ICD-10 code (925.0 per 100,000 cases) compared with 19,854,842 inpatient cases and 58,524 rare disease cases (294.8 per 100,000) in the nationwide case statistics. This pattern was consistent across different ICD-10 chapters, with ratios between case numbers ranging from 2.01 for diseases of the nervous system to 6.28 for diseases of the skin and subcutaneous tissue.
Discussion: In accordance with our hypothesis, we found that the proportion of rare disease cases was around three times higher in university hospitals than expected from national case statistics. Note that our study has several limitations. First, for more reliable estimates, a larger number of rare diseases needs to be studied. This requires a better documentation of rare diseases beyond the relatively coarse ICD-10 codes (for example, by using Orpha codes [4] or the human phenotype ontology [5]). Second, we analyzed data from only six of 36 German university hospitals, and our analysis did not take into account variability across hospitals. Furthermore, the comparison dataset of all German hospitals includes the university hospitals, possibly reducing the observable effect size. Last, university hospitals differ in many aspects from other hospitals (e.g., hospital size or location) and these factors were not controlled in the study.
Conclusion: Our exploratory study provides a first indication that German university hospitals have a significantly higher number of rare disease cases than average German hospitals. However, this difference remains to be quantified more reliably in more elaborate studies with access to better data.
The authors declare that they have no competing interests.
The authors declare that an ethics committee vote is not required.
References
- 1.
- Wakap SN, Lambert DM, Olry A, Rodwell C, Gueydan C, Lanneau V, et al. Estimating cumulative point prevalence of rare diseases: analysis of the Orphanet database. Eur J Hum Genet. 2020;28:165-173. DOI: 10.1038/s41431-019-0508-0
- 2.
- Destatis. Tiefgegliederte Diagnosedaten der Krankenhauspatientinnen und -patienten (Datensatzstruktur) 2019. Available from: https://www.destatis.de/DE/Themen/Gesellschaft-Umwelt/Gesundheit/Krankenhaeuser/Publikationen/Downloads-Krankenhaeuser/tiefgegliederte-diagnosedaten-5231301197015.html
- 3.
- Schulz M, Wandrey M, Hering R, Schulz M, Bätzing-Feigenbaum J. Prävalenz seltener Erkrankungen in der ambulanten Versorgung in Deutschland im Zeitraum 2008 bis 2011. Versorgungsatlas-Bericht 15/13. Berlin: Zentralinstitut für die kassenärztliche Versorgung in Deutschland (Zi); 2015.
- 4.
- Orphanet. Available from: https://www.orpha.net
- 5.
- Robinson PN, Köhler S, Bauer S, Seelow D, Horn D, Mundlos S. The human phenotype ontology: a tool for annotating and analyzing human hereditary disease. Am J Hum Genet. 2008;83:610-615. DOI: 10.1016/j.ajhg.2008.09.017