Positive Predictive Value of French Hospitalization Discharge Codes for Stroke and Transient Ischemic Attack.

Abstract:

BACKGROUND:We aimed at measuring the positive predictive value (PPV) of data in the French Hospital Medical Information Database (FHD). SUMMARY:This retrospective multicenter study included 31 hospitals from where 56 hospital stays were randomly selected among all hospitalizations for the years 2009 and 2010 with at least 1 principal diagnosis of stroke or transient ischemic attack (TIA). Three algorithms were evaluated. Algorithm 1 selected discharge abstracts with at least 1 principal diagnosis identified by one of the relevant International Classification of Diseases, 10th revision codes. Algorithm 2 selected stays with 1 principal diagnosis of the whole stay, but without the dates of the stay. Algorithm 3 took into account the kind of medical wards. The PPV of each algorithm was calculated using medical records as the reference. We found 1,669 discharge abstracts with a diagnosis of stroke among the 1,680 that were randomly selected. The neurologist's review revealed 196 false-positive cases providing a global PPV of 88.26% for algorithm 1, 89.96% for algorithm 2 and 92.74% for algorithm 3. KEY MESSAGES:It was possible to build an algorithm to optimize the FHD for stroke and TIA reporting, with a PPV at 90%. The FHD could be a good tool to measure the burden of stroke in France.

journal_name

Eur Neurol

journal_title

European neurology

authors

Giroud M,Hommel M,Benzenine E,Fauconnier J,Béjot Y,Quantin C,FRESCO Study.

doi

10.1159/000438859

subject

Has Abstract

pub_date

2015-01-01 00:00:00

pages

92-9

issue

1-2

eissn

0014-3022

issn

1421-9913

pii

000438859

journal_volume

74

pub_type

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