Objectives: To examine the validity of routinely collected data in identifying hip fractures (HFs) and to identify factors associated with incorrect coding.
Method: In a prospective cohort study between January 2014 and June 2016, HFs were identified using physician diagnosis and diagnostic imaging and were recorded in a Registry. Records of HFs in the health information exchange (HIE) were identified using International Statistical Classification of Diseases and Related Health Problems, Tenth Revision, Australian Modification/Australian Classification of Health Interventions/Australian Coding Standards codes. New HFs were estimated by episode of care, hospital admission and with an algorithm. Data from the HIE and the Registry were compared.
Results: The number of HFs as the principal diagnosis (PD) recorded by episode (864) was higher than by admission (743), by algorithm (711) and in the Registry (638). The sensitivity was high for all methods (90-93%) but the positive predictive value was lower for episode (68%) than for admission (80%) or algorithm (81%). The number of HFs with surgery recorded in the PD by episode (639), algorithm (630) and in the Registry (623) was similar but higher than by admission (589). The episode and algorithm methods also had higher sensitivity (91-92%) than the admission method (84%) for HFs with surgery. Factors associated with coding errors included subsequent HF, long hospital stay, intracapsular fracture, younger age, male, HF without surgery and death in hospital.
Conclusions: When it is not practical to use the algorithm for regular monitoring of HFs, using PD by admission to estimate total HFs and PD by episode in combination with a procedure code to estimate HFs with surgery can produce robust estimations.
Keywords: ICD-10-AM; clinical coding; data linkage; data quality; hospital records.