Direct costs of community-acquired pneumonia for hospitalized children in Shanghai, China from 2018 to 2020: a cross-sectional analysis
Notice bibliographique
Résumé
Background: Community-acquired pneumonia (CAP) is an acute respiratory infection with a high clinical and economic burden. Clarifying the burden is important for health policy making. However, there is inadequate data on the economic burden of childhood CAP in China. In this study, the direct disease burden of CAP in children was analyzed using city-level data. Methods: A cross-sectional study of the direct costs of CAP for hospitalized children aged 28 days to 18 years old in Shanghai from January 2018 to December 2020 was performed. Information, including the hospitalization costs from the first page of the children’s hospitalized medical records, was obtained. The direct costs included medical services, diagnostics, medications, and medical supplies. The continuous variables with non-normal distributions are expressed as the median (interquartile range). Comparisons between groups were performed using the Kruskal-Wallis H test. The enumeration data are expressed as the number (percentage), and comparisons between groups were performed using the χ2 test. Results: A total of 59 hospitals and 63,614 hospitalized CAP patients were included in this study. Significantly fewer patients were discharged in 2020 than 2018 and 2019 (6,662, 27,943, and 29,009, respectively, P<0.001). Among the patients, 27,741 patients (43.6%) were covered by social medical insurance, 13,509 (21.2%) by commercial health insurance, and 22,364 (35.2%) were self-paying. The annual total direct costs for 2018, 2019, and 2020 were 118.553, 140.865, and 40.064 million Chinese Yuan (CNY), respectively. The average direct costs per hospital stay due to pediatric CAP in Shanghai was 4,707.83 CNY in 2018, a sum that accounted for 7.3% and 16.7% of the per capita disposable income in Shanghai and China in 2018, respectively. The total costs of the group aged <1 year were significantly higher than those of the other age groups (6,271.1 vs. 3,244.3~4,610.7 CNY, P<0.001). The total costs of severe cases were significantly higher than those of non-severe cases (5,200.6 vs. 3,170.4 CNY, P<0.001). The median duration of hospital stay was 6.0 days (5.0, 8.0). Conclusions: CAP hospitalization continues to represent a high clinical and economic burden in Shanghai, China. Specialized hospitals, severe cases, and the length of hospital stay were positively correlated with inpatient costs.
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Comment cette classification a été obtenuedéplier
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 | 0,000 | 0,000 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,001 | 0,003 |
| 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 découleClassification
machine, non validéePrédiction automatique; un appel candidat d’une seule tête enseignante, pas un consensus.
Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».