Temporal trends in the accuracy of hospital diagnostic coding for identifying acute stroke: a population-based study

Introduction: Administrative hospital diagnostic coding data are increasingly being used in identifying incident and prevalent stroke cases, for outcome audit and for ‘big data’ research. Validity of administrative coding has varied in previous studies, but little is known about the temporal trends of coding accuracy, which could bias analyses. Patients and Methods: Using all incident and recurrent strokes in a population-based cohort (Oxford Vascular Study/OXVASC) with multiple sources of ascertainment as the reference, we determined the temporal trends in sensitivity and positive predictive value of hospital diagnostic codes for identifying acute stroke from 2002 to 2017. Results: Of 1883 hospitalised strokes, 1341 (71.2%) were correctly identified by coding. Sensitivity of coding improved over time for all strokes (ptrend = 0.005) and for incident cases (ptrend = 0.002). Of 1995 apparent stroke admissions identified by International Classification of Disease-10 stroke codes (I60–I68), 1588 (79.6%) used the stroke-specific codes (I60–I61/I63–I64). Positive predictive value was higher with the use of specific codes (83.2% vs. 69.2% for all codes) and highest if combined with the first admission only (88.5%), particularly during more recent time periods (2014–2017 = 90.3%). Of 2254 OXVASC incident strokes, 833 (37.0%) were not hospitalised. Sensitivity of coding increased over time for non-disabling stroke (ptrend = 0.001), but not for disabling/fatal stroke (ptrend = 0.40). Conclusions: Although accuracy of hospital diagnostic coding for identifying acute strokes improved over the last 15 years, residual insensitivity supports linkage to other sources in large epidemiological studies. Moreover, differences in the time trends of coding sensitivity in relation to stroke severity might bias studies of trends in stroke outcome if only administrative coding is used.