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.
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.
Authors: Patrick Blin; Caroline Dureau-Pournin; Yves Cottin; Jacques Bénichou; Patrick Mismetti; Abdelilah Abouelfath; Regis Lassalle; Cécile Droz; Nicholas Moore Journal: Br J Clin Pharmacol Date: 2018-12-16 Impact factor: 4.335
Authors: Luisa Ibáñez; Mònica Sabaté; Xavier Vidal; Elena Ballarin; Marietta Rottenkolber; Sven Schmiedl; Andreas Heeke; Consuelo Huerta; Elisa Martin Merino; Dolores Montero; Luz María Leon-Muñoz; Christiane Gasse; Nicholas Moore; Cécile Droz; Régis Lassalle; Mia Aakjaer; Morten Andersen; Marie Louise De Bruin; Rolf Groenwold; Hendrika A van den Ham; Patrick Souverein; Olaf Klungel; Helga Gardarsdottir Journal: Br J Clin Pharmacol Date: 2019-09-04 Impact factor: 4.335
Authors: Nicolas H Thurin; Pauline Bosco-Levy; Patrick Blin; Magali Rouyer; Jérémy Jové; Stéphanie Lamarque; Séverine Lignot; Régis Lassalle; Abdelilah Abouelfath; Emmanuelle Bignon; Pauline Diez; Marine Gross-Goupil; Michel Soulié; Mathieu Roumiguié; Sylvestre Le Moulec; Marc Debouverie; Bruno Brochet; Francis Guillemin; Céline Louapre; Elisabeth Maillart; Olivier Heinzlef; Nicholas Moore; Cécile Droz-Perroteau Journal: BMC Med Res Methodol Date: 2021-05-01 Impact factor: 4.615