Efficiency of hospitals in COVID-19 era: a case study of an affected country
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Notice bibliographique
Résumé
BACKGROUND: The COVID-19 pandemic has affected all aspects of human life and society and has damaged the global economy. Health systems and hospitals were not exempted from this situation. The performance of hospitals during the COVID-19 pandemic was affected by policies related to the pandemic and other factors. This study aimed to investigate hospital performance indicators such as admissions and revenue. METHODS: The medical records of patients with selected orthopedic and general surgical diseases were studied in two government hospitals in the capital city of Urmia in the second quarter of 2019, with the same period in 2020. Data were extracted based on the number of medical records, including length of stay, hospitalization type, sex, age, insurance, number of deaths, and readmissions from the medical records department. Payment amounts were collected from the revenue department and Hospital Information System. Two performance indicators, two result indicators, and two control indicators were used. Mean disease-specific revenue, total revenue, length of stay, and bed occupancy rate were calculated for both periods. Data were analyzed using SPSS (version 16) and the Mann-Whitney statistical test. RESULTS: 2140 cases were studied in the two disease groups. An increase was observed in the number of hospitalizations and average length of stay during the pandemic. The mean disease-specific revenue in the quarter of 2020 was higher than in 2019. However, total revenue decreased, and the difference in the mean of total revenue was significant for the two years (P = 0.00) in teaching center. The number of readmissions remained unchanged throughout in the pandemic. The number of deaths due to general surgery diseases in 2020 compared to the same period in 2019 was associated with a relative increase. CONCLUSIONS: The COVID-19 pandemic increased the slope of health care costs. The analysis of the studied variables as performance, result, and control indicators showed that hospitalization rate, bed occupancy rate, and total revenue followed a similar and decreasing pattern in the selected hospitals during the COVID-19 pandemic. Hospitals should adopt appropriate strategies so that, in conditions identical to the COVID-19 pandemic, their performance is accompanied by proper management of resources, efficiency, and minimal reduction in revenue.
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Prédiction distillée sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Apprise à partir de 10 348 étiquettes directes de Codex et de 10 348 étiquettes directes de Gemma. Le mode candidate est l'union des têtes enseignantes seuillées; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont ni des étiquettes humaines ni des étiquettes directes de modèles de pointe.
Scores Codex et Gemma par catégorie
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,001 | 0,001 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,000 | 0,001 |
| Études des sciences et des technologies | 0,000 | 0,000 |
| Communication savante | 0,000 | 0,000 |
| Science ouverte | 0,000 | 0,000 |
| Intégrité de la recherche | 0,000 | 0,000 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,000 | 0,000 |
Scores machine (provisoires)
Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.
Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.
score_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découle