Identifying fall-related injuries in older adults using ICD-10 injury codes : Validation study of emergency department patients with and without subsequent hospitalization.

Authors

Michaela Gross, Daniel Schoene, Clemens Becker, Christoph Wasser, Gisela Büchele, Jochen Klenk, Kilian Rapp

Published in

Zeitschrift fur Gerontologie und Geriatrie. Oct 07, 2026. Epub Oct 07, 2026.

Abstract

To evaluate the burden of fall-related injuries at the population level, diagnosis-based electronic healthcare records could represent a valuable instrument. The German ICD system (ICD-10-GM) does not include the coding of falls. The aim of the study was to assess to what extent specific ICD-10 injury diagnoses, alone or in combination, are attributable to falls.
This retrospective single-center validation study analyzed routinely collected electronic healthcare records of 2256 patients aged ≥ 65 years who were treated either exclusively in the emergency department (ED sample) or in the emergency department with subsequent hospitalization (HO sample) and had an injury diagnosis (ICD-10: S00-S99, T00-T14). To determine whether the injury was caused by a fall, electronic patient records were reviewed. Positive predictive values (PPVs) of ICD codes and combinations of ICD codes for fall-related injuries were calculated (derivation phase) and the potential for statistical overfitting was assessed (validation phase).
The study included 1378 patients in the ED sample (mean age 79.8 years, 59.2% female) and 878 patients in the HO sample (mean age 82.6 years, 66.5% female). All models yielded PPVs of at least 0.9 in the HO sample and 0.8 in the ED sample. The PPVs in the validation set were closely comparable to those in the derivation set.
The ICD-10 diagnoses from routine administrative data can be used to identify fall-related injuries with a high PPV in older adults treated in the ED with or without subsequent hospitalization. Thus, ICD-10 diagnoses can be a valuable resource for monitoring secular trends and evaluating the impact of population-based fall prevention programs.

PMID:
42844418
Bibliographic data and abstract were imported from PubMed on 08 Oct 2026.

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