Can Hospital Discharge Databases Be Used to Follow Ischemic Stroke Incidence?

Abstract

Background and Purpose-Because acute ischemic strokes (ISs) are mainly hospitalized, hospital discharge data could be used to routinely follow their incidence management. We aimed to assess sensitivity and positive predictive value of the French hospital discharge database (HDD) to identify patients with acute IS using a prospective and exhaustive cohort (AVC69) of acute IS cases. Methods-A selection algorithm based on IS diagnosis coded with the International Classification of Diseases and cerebral imaging codes was used to identify all hospital stays with the primary diagnosis of IS in the HDD of the university hospitals of the Rhône area. Cases identified through HDD search were compared with IS cases identified through an exhaustive cohort study conducted in the Rhône district and confirmed on medical records review. Results-There were 465 confirmed cases of IS hospitalized in 1 of the 4 university hospitals during the study period. The HDD search identified 313 among those (true-positive cases) but missed 152 cases (false-negative cases). The sensitivity of the HDD search was 67.3% (95% confidence interval, 63.1-71.5), and the positive predictive value was 95.1% (95% confidence interval, 92.8-97.4). Additionally, HDD search retrieved 16 cases, which were not eventually IS (false positives). Sensitivity was better when patients were hospitalized in neurological departments. Conclusions-The lack of sensitivity to identify acute IS patients through HDD search does not seem to be accurate enough to validate the use of these data for incidence estimates. Efforts have to be made to improve the coding quality. Key Words: hospital discharge database ■ ischemic stroke ■ positive predictive value ■ sensitivity

Trends Over Time in the Risk of Stroke After an Incident Transient Ischemic Attack

“…Diagnostic coding for stroke has a high positive predictive value when compared with gold-standard clinical neurologist diagnosis. [22][23][24] Although diagnostic misclassification may therefore affect point incidence estimates of TIA, it is much less likely to influence our analysis of trends over time in stroke risk after TIA, or TIA rates, particularly because the same coding system was used for the study period. Notably, the yearly downward trend in the risk of stroke risk was still observed when restricted to patients receiving brain imaging during hospitalization.…”

Stroke Tracked by Administrative Coding Data

“…11 In that study, the overall sensitivity of the French HDD was higher (77%), whereas the positive predictive value was lower (69%) than the one reported by Haesebaert et al 10 Furthermore, in the same study, 10 sensitivity and positive predictive values were heterogeneous across stroke types and were higher for intracerebral hemorrhage as suggested by several previous studies.…”

“…For this reason, the concordance between administrative coding data and medical records has been scrutinized in different settings. 8,9 In the current issue of Stroke, Haesebaert et al 10 reported the results of their study designed to help us understand whether concern about the reliability of administrative coding data in stroke research is ill placed or whether such concern is justified or whether the answer lies somewhere in between the 2 poles. The study assessed the accuracy of the French hospital discharge database (HDD) to identify subjects with acute ischemic stroke.…”

“…False negatives were attributed to coding errors (coding symptoms instead of reporting a stroke diagnosis, reporting stroke as the secondary and not the primary diagnosis, and errors in codification of demographic data [nonresident patients]). A limitation of the studies by Haesebaert et al 10 and Aboa-Eboulé et al 11 is that the premise that the reviewing stroke neurologist's diagnosis (heavily influenced by the diagnosis of the treating physician) represents the gold standard is not entirely accurate.…”

“…Furthermore, although administrative coding data may improve traditional methods, any application of administrative data to stroke research requires a thorough understanding of their limitations and the willingness to interpret results with caution. Indeed, the main problem, as confirmed by the quoted studies, 10,11 relies on the accuracy of the diagnosis, the quality of included data elements, and particularly on missing data elements. Furthermore, we should consider that the personnel who apply coding are not homogenous across all countries (administrative versus physician staff), and it is not always the same person who is in charge of the patient so that the coding needs to be extrapolated from medical records.…”