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

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.