Unscheduled-return-visits after an emergency department (ED) attendance and clinical link between both visits in patients aged 75 years and over: a prospective observational study
| Autor: | Michel Ranaivoson, Enrique Casalino, Laurent Pereira, Luisa Colosi, Romain Hellmann, Mathias Wargon, Christophe Choquet, Anne Perozziello, Gaëlle Juillien |
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| Jazyk: | angličtina |
| Rok vydání: | 2015 |
| Předmět: |
Male
medicine.medical_specialty Multivariate analysis Time Factors lcsh:Medicine 030204 cardiovascular system & hematology Logistic regression Patient Readmission 03 medical and health sciences 0302 clinical medicine Patient Admission medicine Humans 030212 general & internal medicine Prospective Studies Prospective cohort study lcsh:Science Aged Proportional Hazards Models Geriatrics Aged 80 and over Multidisciplinary Proportional hazards model business.industry lcsh:R Emergency department Triage Patient Discharge 3. Good health Logistic Models Emergency medicine Observational study Female lcsh:Q France business Emergency Service Hospital Research Article |
| Zdroj: | PLoS ONE, Vol 10, Iss 4, p e0123803 (2015) PLoS ONE |
| ISSN: | 1932-6203 |
| Popis: | Background Predictors of unscheduled return visits (URV), best time-frame to evaluate URV rate and clinical relationship between both visits have not yet been determined for the elderly following an ED visit. Methods We conducted a prospective-observational study including 11,521 patients aged ≥75-years and discharged from ED (5,368 patients (53.5%)) or hospitalized after ED visit (6,153 patients). Logistic Regression and time-to-failure analyses including Cox proportional model were performed. Results Mean time to URV was 17 days; 72-hour, 30-day and 90-day URV rates were 1.8%, 6.1% and 10% respectively. Multivariate analysis indicates that care-pathway and final disposition decisions were significantly associated with a 30-day URV. Thus, we evaluated predictors of 30-day URV rates among non-admitted and hospitalized patient groups. By using the Cox model we found that, for non-admitted patients, triage acuity and diagnostic category and, for hospitalized patients, that visit time (day, night) and diagnostic categories were significant predictors (p |
| Databáze: | OpenAIRE |
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