Refine
Has Fulltext
- no (2)
Year of publication
- 2022 (2)
Document Type
- Article (1)
- Conference Proceeding (1)
Language
- English (2)
Is part of the Bibliography
- yes (2)
Background:
The medical care of patients with myositis is a great challenge in clinical practice. This is due to the rarity of these disease, the complexity of diagnosis and management as well as the lack of systematic analyses.
Objectives:
Therefore, the aim of this project was to obtain an overview of the current care of myositis patients in Germany and to evaluate epidemiological trends in recent years.
Methods:
In collaboration with BARMER Insurance, retrospective analysis of outpatient and inpatient data from an average of approximately 8.7 million insured patients between January 2005 and December 2019 was performed using ICD-10 codes for myositis for identification of relevant data.
In addition, a comparative analysis was performed between myositis patients and an age-matched comparison group from other populations insured by BARMER.
Results:
45,800 BARMER-insured individuals received a diagnosis of myositis during the observation period, with a relatively stable prevalence throughout. With regard to comorbidities, a significantly higher rate of cardiovascular disease as well as neoplasm was observed compared to the control group within the BARMER-insured population. In addition, myositis patients suffer more frequently from psychiatric disorders, such as depression and somatoform disorders.
However, the ICD-10 catalogue only includes the specific coding of "dermatomyositis" and "polymyositis" and thus does not allow for a sufficient analysis of all idiopathic inflammatory myopathies subtypes.
Conclusion:
The current data provide a comprehensive epidemiological analysis of myositis in Germany, highlighting the multimorbidity of myositis patients. This underlines the need for multidisciplinary management. However, the ICD-10 codes currently still in use do not allow for specific analysis of the subtypes of myositis.
The upcoming ICD-11 coding may improve future analyses in this regard.