Literature DB >> 36239768

[Uncovering rare diseases in medical data-coding].

Tamara Martin1, Kathrin Rommel2, Carina Thomas2, Jutta Eymann3, Tanita Kretschmer4, Reinhard Berner4, Min Ae Lee-Kirsch4, Helge Hebestreit5.   

Abstract

The ICD-10-GM coding system used in the German healthcare system only captures a minority of rare disease diagnoses. Therefore, information on the incidence and prevalence of rare diseases as well as necessary (financial) resources for the expert care required for evidence-based decisions by health insurers, care providers, and politicians are lacking. Furthermore, the missing information complicates and sometimes even precludes the generation of scientific knowledge on rare diseases. Therefore, starting in 2023, all in-patient cases in Germany with a rare disease diagnosis must be coded by an ORPHAcode using the Alpha-ID-SE file.The file Alpha-ID-SE links the ICD-10-GM codes to the internationally established ORPHAcodes for rare diseases. Commercially available software tools progressively support the coding of rare diseases. In several centers for rare diseases linked to university hospitals, IT tools and procedures were established to realize a complete coding of rare diseases. These include financial incentives for the institutions providing rare disease codes, systematic queries asking for rare disease codes during the coding process, and a semi-automated coding process for all patients with a rare disease previously seen at the institution. A combination of the different approaches probably results in the most complete coding.To get the complete picture of rare disease epidemiology and care requirements, a specific and unique coding of out-patient cases is also desirable. Furthermore, a structured reporting of phenotype is required, especially for complex rare diseases and for yet undiagnosed cases.
© 2022. The Author(s).

Entities:  

Keywords:  Alpha-ID-SE; Diagnosis; Human phenotype ontology; ORPHAcode; Rare diseases

Year:  2022        PMID: 36239768     DOI: 10.1007/s00103-022-03598-9

Source DB:  PubMed          Journal:  Bundesgesundheitsblatt Gesundheitsforschung Gesundheitsschutz        ISSN: 1436-9990            Impact factor:   1.595


  5 in total

1.  Representation of rare diseases in health information systems: the Orphanet approach to serve a wide range of end users.

Authors:  Ana Rath; Annie Olry; Ferdinand Dhombres; Maja Miličić Brandt; Bruno Urbero; Segolene Ayme
Journal:  Hum Mutat       Date:  2012-04-06       Impact factor: 4.878

2.  [Improving the visibility of rare diseases in health care systems by specific routine coding].

Authors:  Magdalena María Marx; Franzisca Marie Dulas; Katja Maria Schumacher
Journal:  Bundesgesundheitsblatt Gesundheitsforschung Gesundheitsschutz       Date:  2017-05       Impact factor: 1.513

Review 3.  The human phenotype ontology.

Authors:  P N Robinson; S Mundlos
Journal:  Clin Genet       Date:  2010-02-11       Impact factor: 4.438

4.  [How Often is Rare Really Rare? A Survey on the Frequency of Rare Diseases at a University Hospital].

Authors:  Tanita Kretschmer; Adrian Danker; Olaf Müller; Angela Rösen-Wolff; Min Ae Lee-Kirsch; Reinhard Berner
Journal:  Gesundheitswesen       Date:  2021-04-15

5.  Rare diseases in ICD11: making rare diseases visible in health information systems through appropriate coding.

Authors:  Ségolène Aymé; Bertrand Bellet; Ana Rath
Journal:  Orphanet J Rare Dis       Date:  2015-03-26       Impact factor: 4.123

  5 in total

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