National patient registers are a key tool in healthcare planning by monitoring the frequency of various diseases and treatments, thereby providing patient data to support hospital statistics and enable financial calculations [1]. Furthermore, the national registries are increasingly being used for population-based research [2]. To guarantee a meaningful use and interpretation of data from the clinical quality databases, knowledge of data validity is essential.

Data validity in registers include coverage, completeness of patient diagnoses and other recorded variables, and correctness of the recorded data [2].

The Danish National Patient Registry (DNPR) has nationwide coverage since all hospitals are reimbursed by the government when patient data are recorded to the registry [3, 4]. The diagnosis completeness for conditions that should lead to a hospital encounter is assumed to be high owing to the free universal Danish healthcare system [5]. Assessment of data correctness is an ongoing task, which requires frequent validation [6].

A limited number of studies have validated orthopaedic diagnoses from the DNPR [3, 7-10]. In 2006, Lass et al. reported a positive predictive value (PPV) of 86% for all orthopaedic diagnoses imported to the DNPR in a two-week time period [7]. In 2020, Hjelholt et al. studied the validation of hip fracture diagnoses from the DNPR and reported PPVs ranging from 83% to 92% depending on the anatomical location of the proximal femur [8]. This shows that the accuracy of registered diagnoses to the DNPR may vary by fracture location, which may also be the case for humerus fractures.

To our knowledge, no validation study exists on fracture diagnoses of the humerus in the DNPR. The purpose of this study was to validate the humeral fracture diagnoses for adults in the DNPR by estimating the PPV.