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Updated: Mar 31, 2026

A Method of Trigonometric Modelling of Seasonal Variation Demonstrated with Multiple Sclerosis Relapse Data
Published on: December 9, 2015
[Seasonal distribution of clinical case codes (DOC study)]
N von Dercks1, R Melz2, P Hepp3
1Klinik und Poliklinik für Unfall-, Wiederherstellungs- und Plastische Chirurgie, Universitätsklinikum Leipzig, Liebigstraße 20, 04103, Leipzig, Deutschland. nikolaus.vondercks@medizin.uni-leipzig.de.
Objectives:
The German diagnosis-related groups remuneration system (G-DRG) was implemented in 2004 and patient-related diagnoses and procedures lead to allocation to specific DRGs. This system includes several codes, such as case mix (CM), case mix index (CMI) and number of cases. Seasonal distribution of these codes as well as distribution of diagnoses and DRGs may lead to logistical consequences for clinical management.
Methods:
From 2004 to 2013 all the main diagnoses and DRGs for inpatients were recorded. Monthly and seasonal distributions were analyzed using ANOVA.
Results:
The average monthly number of cases was 265 ± 25 cases, the average CM was 388.50 ± 51.75 and the average CMI was 1.46 ± 0.15 with no significant seasonal differences (p > 0.1). Concussion was the most frequently occurring main diagnosis (3739 cases) followed by fractures of the humeral head (699). Significant distribution differences could be shown for humeral head fractures in monthly (p = 0.018) and seasonal comparisons (p = 0.006) with a maximum in winter. Radius (p = 0.01) and ankle fractures (p ≤ 0.001) also occurred most frequently in winter. Non-bony lesions of the shoulder were significantly less in spring (p = 0.04). The DRGs showed no evidence of a monthly or seasonal clustering (p > 0.1).
Conclusion:
The significant clustering of injuries in specific months and seasons should lead to logistic consequences (e.g. operating room slots, availability of nursing and anesthesia staff). For a needs assessment the analysis of main diagnoses is more appropriate than DRGs.
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