Stéphanie Polazzi
Biographic Data
| ID | 5536879 |
|---|---|
| NAME | Stéphanie Polazzi |
| GIVEN NAMES | Stéphanie |
| FAMILY NAME | Polazzi |
| SIGNATURE | POLAZZI S |
| AFFILIATIONS | Hospices Civils de Lyon |
| ORCID | 0000-0003-4622-7983 |
| VERIFIED | No |
| TOTAL WORKS | 3 |
| TOTAL CITATIONS | 0 |
| AUTHOR COUNT | 3 |
| EDITOR COUNT | 0 |
| FIRST PUBLICATION YEAR | 2013 |
| LATEST PUBLICATION YEAR | 2024 |
| H-INDEX | 0 |
Length of Stay Prediction With Standardized Hospital Data From Acute and Emergency Care Using a Deep Neural Network
OBJECTIVE: Length of stay (LOS) is an important metric for the organization and scheduling of care activities. This study sought to propose a LOS prediction method based on deep learning using widely available administrative data from acute and emergency care and compare it with other methods. PATIENTS AND METHODS: All admissions between January 1, 2011 and December 31, 2019, at 6 university hospitals of the Hospices Civils de Lyon metropolis wer…
Combining the Hospital Frailty Risk Score With the Charlson and Elixhauser Multimorbidity Indices to Identify Older Patients at Risk of Poor Outcomes in Acute Care
OBJECTIVE: The Hospital Frailty Risk Score (HFRS) can be applied to medico-administrative datasets to determine the risks of 30-day mortality and long length of stay (LOS) in hospitalized older patients. The objective of this study was to compare the HFRS with Charlson and Elixhauser comorbidity indices, used separately or combined. DESIGN: A retrospective analysis of the French medical information database. The HFRS, Charlson index, and Elixhaus…
Temporal Variation in Surgical Mortality Within French Hospitals
BACKGROUND: Surgical mortality varies widely across hospitals, but the degree of temporal variation within individual hospitals remains unexplored and may reflect unsafe care. OBJECTIVES: To add a longitudinal dimension to large-scale profiling efforts for interpreting surgical mortality variations over time within individual hospitals. DESIGN: Longitudinal analysis of the French nationwide hospital database using statistical process control meth…
No prominent works on this page.
Temporal Variation in Surgical Mortality Within French Hospitals
BACKGROUND: Surgical mortality varies widely across hospitals, but the degree of temporal variation within individual hospitals remains unexplored and may reflect unsafe care. OBJECTIVES: To add a longitudinal dimension to large-scale profiling efforts for interpreting surgical mortality variations over time within individual hospitals. DESIGN: Longitudinal analysis of the French nationwide hospital database using statistical process control meth…
Length of Stay Prediction With Standardized Hospital Data From Acute and Emergency Care Using a Deep Neural Network
OBJECTIVE: Length of stay (LOS) is an important metric for the organization and scheduling of care activities. This study sought to propose a LOS prediction method based on deep learning using widely available administrative data from acute and emergency care and compare it with other methods. PATIENTS AND METHODS: All admissions between January 1, 2011 and December 31, 2019, at 6 university hospitals of the Hospices Civils de Lyon metropolis wer…
Combining the Hospital Frailty Risk Score With the Charlson and Elixhauser Multimorbidity Indices to Identify Older Patients at Risk of Poor Outcomes in Acute Care
OBJECTIVE: The Hospital Frailty Risk Score (HFRS) can be applied to medico-administrative datasets to determine the risks of 30-day mortality and long length of stay (LOS) in hospitalized older patients. The objective of this study was to compare the HFRS with Charlson and Elixhauser comorbidity indices, used separately or combined. DESIGN: A retrospective analysis of the French medical information database. The HFRS, Charlson index, and Elixhaus…
Emergency Medicine (3 works) · Emergency Medicine (3 works) · Internal Medicine (3 works) · Internal Medicine (3 works) · Medicine (3 works) · Sepsis Diagnosis and Treatment (3 works) · Demography (2 works) · Healthcare Operations and Scheduling Optimization (2 works) · Logistic regression (2 works) · Medical emergency (2 works)