Short- and long-term impacts of the National Essential Medicines Policy on drug availability, price, and usage in a deprived rural county in southwestern China: an interrupted time series analysis across 8 years
Notice bibliographique
Résumé
Background: China's National Essential Medicines Policy (NEMP) has been implemented for over 15 years; yet empirical evidence on its long-term impacts is lacking, particularly in remote and rural regions. This study aims to assess the short-and long-term effects of NEMP on the drug availability, price, and usage in a deprived rural county in southwestern China. Methods: A quasi-experimental design was employed, featuring a single-group pre-and-post comparison. We gathered 74,436 procurement records spanning from 2009 to 2016 from the drug warehouses of local medical institutions. Pharmaceutical data were analyzed quarterly, considering various policy and therapeutic attributes. Fisher's Drug Price Index (DPI-F) was calibrated for the retail and wholesale prices of a consistent collection of 405 medications. We conducted interrupted time-series analysis to examine the immediate and enduring impacts of NEMP's initial (commencing in January 2011) and second (starting from December 2015) stages. Results: After initiation of NEMP, the number of available essential medicines surged by 115 but subsequently faced a steady quarterly decline (-9.1) in township healthcare centers (THCs, primary care). Conversely, county hospitals (secondary care) initially saw a reduction of 40 in drug availability but later exhibited a steady increase (+4.2 per quarter) up to the second-stage NEMP. Regarding price, THCs encountered abrupt (-26.1%/-15.9% in retail/wholesale price) and sustained (-0.2%/-0.3% per quarter) price drops after NEMP. The immediate price change after NEMP in county hospitals were milder but significant in non-essential medicines, and long-term declines were also observed in all drugs. As for total sales, a significant long-term disparity emerged between THCs (+0.9% per quarter) and county hospitals (+3.3% per quarter). Following the second-stage NEMP, retail prices in county hospitals further decreased, although wholesale prices did not; however, following price upward trends were observed in both THCs and county hospitals. Lastly, the influences of NEMP varied across different therapeutical categories of medicines. Conclusion: NEMP has successfully regulated drug prices in primary and secondary healthcare facilities in remote and rural areas, both short-term and long-term. However, a remarkable disparity in medicine availability and utilization was observed between different levels of facilities over time. Continuous monitoring is essential, with increased attention needed on the uneven impacts of the policy on diverse drugs, facilities, regions, and demographics.
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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 | 0,003 | 0,000 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,001 | 0,000 |
| Bibliométrie | 0,001 | 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 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 ».