1. Transition matrices model as a way to better understand and predict intra-hospital pathways of covid-19 patients
- Author
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Arnaud, Foucrier, Jules, Perrio, Johann, Grisel, Pascal, Crépey, Etienne, Gayat, Antoine, Vieillard-Baron, Frédéric, Batteux, Tobias, Gauss, Pierre, Squara, Seak-Hy, Lo, Matthias, Wargon, Romain, Hellmann, Hôpital Beaujon [AP-HP], Assistance publique - Hôpitaux de Paris (AP-HP) (AP-HP), Agence Régionale de Santé Ile-de-France [Paris] (ARS IDF), Service de santé numérique [Paris] (SESAN), Recherche en Pharmaco-épidémiologie et Recours aux Soins (REPERES), Université de Rennes (UR)-École des Hautes Études en Santé Publique [EHESP] (EHESP), Hôpital Lariboisière-Fernand-Widal [APHP], Marqueurs cardiovasculaires en situation de stress (MASCOT (UMR_S_942 / U942)), Institut National de la Santé et de la Recherche Médicale (INSERM)-Groupe Hospitalier Saint Louis - Lariboisière - Fernand Widal [Paris], Assistance publique - Hôpitaux de Paris (AP-HP) (AP-HP)-Assistance publique - Hôpitaux de Paris (AP-HP) (AP-HP)-Centre National de la Recherche Scientifique (CNRS)-Université Paris Cité (UPCité)-Université Sorbonne Paris Nord, Centre de recherche en épidémiologie et santé des populations (CESP), Université de Versailles Saint-Quentin-en-Yvelines (UVSQ)-Assistance publique - Hôpitaux de Paris (AP-HP) (AP-HP)-Hôpital Paul Brousse-Institut National de la Santé et de la Recherche Médicale (INSERM)-Université Paris-Saclay, Hôpital Ambroise Paré [AP-HP], Institut Cochin (IC UM3 (UMR 8104 / U1016)), Institut National de la Santé et de la Recherche Médicale (INSERM)-Centre National de la Recherche Scientifique (CNRS)-Université Paris Cité (UPCité), CHU Grenoble, Clinique Ambroise Paré [Centres Médico-Chirurgicaux Ambroise Pré, Pierre Cherest, Hartmann], Hôpital Delafontaine, Centre Hospitalier de Saint-Denis [Ile-de-France], Observatoire Regional des Soins Non Programmés [ïle-de-France/Saint-Denis] (ORSNP), AP-HP - Hôpital Bichat - Claude Bernard [Paris], and Jonchère, Laurent
- Subjects
Hospitalization ,[SDV] Life Sciences [q-bio] ,Intensive Care Units ,Multidisciplinary ,SARS-CoV-2 ,[SDV]Life Sciences [q-bio] ,Humans ,COVID-19 ,Hospital Mortality ,Pandemics ,Hospitals ,Retrospective Studies - Abstract
Since January 2020, the SARS-CoV-2 pandemic has severely affected hospital systems worldwide. In Europe, the first 3 epidemic waves (periods) have been the most severe in terms of number of infected and hospitalized patients. There are several descriptions of the demographic and clinical profiles of patients with COVID-19, but few studies of their hospital pathways. We used transition matrices, constructed from Markov chains, to illustrate the transition probabilities between different hospital wards for 90,834 patients between March 2020 and July 2021 managed in Paris area. We identified 3 epidemic periods (waves) during which the number of hospitalized patients was significantly high. Between the 3 periods, the main differences observed were: direct admission to ICU, from 14 to 18%, mortality from ICU, from 28 to 24%, length of stay (alive patients), from 9 to 7 days from CH and from 18 to 10 days from ICU. The proportion of patients transferred from CH to ICU remained stable. Understanding hospital pathways of patients is crucial to better monitor and anticipate the impact of SARS-CoV-2 pandemic on health system.
- Published
- 2022
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