Evaluation of a pilot cooperative medical scheme in rural China: impact on gender patterns of health care utilization and prescription practices
Notice bibliographique
Résumé
BACKGROUND: In 2003 the Chinese government introduced voluntary cooperative medical schemes (CMS), soon to be in place throughout rural China. Families who chose to enroll do so as a single unit and nothing is known about any differential effect of these new schemes on family members. This study evaluates the impact of one pilot CMS in Anhui Province on health care use by girls aged less than 5 years and women 65 years or older, and on the pattern and cost of prescriptions. METHODS: Health care records were extracted covering a 10 year period, before, during and after the pilot CMS in 4 townships, one with the intervention and 3 comparison townships without. The impact of the intervention on the age and gender distribution of patients presenting for health care and on the prescription of certain drugs was assessed by logistic regression. The cost of prescriptions before, during and after the intervention period was also assessed. RESULTS: 203,058 registration and 643,588 prescription records were identified. During the intervention there was a reduced likelihood overall that a patient was female (OR = 0.92: 95%CI 0.87-0.97) at the intervention site. Girls aged < 5 years had an increased likelihood of health care (OR = 1.41: 95%CI 1.23-1.59) during the CMS, but women ≥ 65 years were relatively disadvantaged (OR = 0.84: 95%CI 0.75-0.95). The use of antibiotics and systemic steroids increased disproportionately at the intervention site for patients ≥ 5 years. Prescription costs at the township hospital also increased at the intervention site, particularly for older men. CONCLUSIONS: This evaluation suggests that all family members did not benefit equally from the pilot CMS and that women ≥ 65 years may be disadvantaged by the newly available reimbursements of health care costs through the CMS. It points to the need, in future evaluations, to use individuals rather than families as the unit of analysis, in order to determine whether such health care inequalities are wide-spread and persistent or are reduced in the longer term. The results also support earlier concerns about the influence of new funding resources on prescription practices and the need for regulation of for-profit prescribing.
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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 | 0,010 | 0,001 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,001 | 0,000 |
| Bibliométrie | 0,000 | 0,000 |
| 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 ».