BACKGROUND: Comorbidities and complications of stroke have implications for level of care and hospital resources. It is critical, therefore, that hospital morbidity data accurately reflect the prevalence of these additional diagnoses. OBJECTIVE: This study aimed to measure and describe the concordance between stroke clinicians/researchers and medical record coders when recording stroke and related diagnoses. METHOD: Diagnoses recorded prospectively, according to defined criteria by a clinical research team, were compared with the coding of stroke comorbidities and complications as per the Australian Coding Standards (ACS) from the separations of 100 inpatients from three rehabilitation facilities in South Australia. Percentage agreement, kappa coefficient, sensitivity and specificity values were calculated. RESULTS: Kappa coefficients for agreement of prospective diagnoses with coding ranged from 0.08 to 0.819. The diagnoses with the highest agreement were stroke, aspiration pneumonia (nil cases), aphasia and dysphagia. The diagnoses with the lowest agreement were apraxia, cognitive impairment, constipation and dehydration. CONCLUSION: Not all stroke comorbidities are represented accurately in hospital morbidity datasets. Education of stroke clinicians about the current ACS may clarify expectations about medical record documentation for coding purposes which in turn may result in more accurate morbidity data and therefore costings for the rehabilitation sector.
- clinical coding
- health information management