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Enregistrement W134178488

The Effect of Managerial Factors on the Incidence of Medical Operations: The Case of Cesarean Sections

2005· article· en· W134178488 sur OpenAlexaboutno aff
Jin‐Li Hu, Yuan-Fu Huang

Notice bibliographique

Revuenon disponible
Typearticle
Langueen
DomaineHealth Professions
ThématiqueHealth Services Management and Policy
Établissements canadiensnon disponible
Organismes subventionnairesnon disponible
Mots-clésIncentiveAgency (philosophy)PaymentSection (typography)PopulationPer capita incomePer capitaWageEconomicsDemographic economicsBusinessMedicineLabour economicsFinanceEnvironmental healthSociologyAdvertising
DOInon disponible

Résumé

récupéré en direct d'OpenAlex

High cesarean section rates in Taiwan are usually explained by medical, socio-economic, and religious reasons. This paper analyzes managerial factors determining cesarean section rates from both demand and supply sides. Taiwan's official data on cesarean section during 1992-2001 are collected. Our major empirical findings are as follows: (1) Cesarean section rates in public hospitals are significantly higher than those in private hospital. (2) Different geographic areas in Taiwan also have significantly different cesarean section rates. (3) An increase in Christian and Catholic population ratio significantly reduces its cesarean section rate, while an area increase per capita income raises an area's cesarean section rates. (4) Medical centers have the highest, regional hospitals have the medium, and district hospitals have the lowest cesarean section rates. Introduction Most existing literature explains the high cesarean section (CS) rates from the viewpoint of medical need (Taffel et al., 1987), socio-economic factors (Stafford, 1991), and religion (Lo, 2003). Managerial aspects (such as the reward system and agency problem) are often neglected. Due to the reward system for doctors, many CS operations are in fact induced demand by the doctors' incentive to increase their own income. Especially in public hospitals where the fixed wage payment is lower, a doctor may have an incentive to earn an extra pay-by-case income by operating CS. Moreover, there is an asymmetric information problem in the medical market such that it is a patient's best response to follow the doctor's advice to have a CS operation. A doctor is an agent for a patient (the principal) to take care of the latter's health. Usually a doctor has an advantage of medical knowledge over a patient. A doctor can easily take his advantage of medical knowledge to persuade a patient to have an extra medical treatment that may not be necessary but indeed will increase the doctor's income. Increasing cesarean section rates are a pandemic trend all over the world, where even according to Taiwan's official statistics, cesarean section (CS) rates on the island have remained high during the past decade (Taiwan Department of Health, 2001). For example, Taiwan's CS rate was 34.5% in 2000, which is a little bit lower than Brazil's 36.0% in 1996 (Hopkins, 2000) but is much higher than other countries' average and optimal rates (6%?16.5%). Although there are mothers-to-be who indeed need CS for medical treatment and CS does save many lives of mothers and infants, CS still presents potential hazards to mothers and infants. For example, an increase in the CS rate may not only enhance the maternal morbidity risk (Rogers, 1988), but also increase respiratory distress syndromes of newborns (De Muylder, 1993). At the same time, an increase in the CS rate also increases medical costs (Shearer, 1993). Consequently, increasing CS rates have become a global issue. Many developed countries, such as the U.S. and Canada, have engaged themselves in solving this problem. Most of the above literature on the CS decision uses questionnaire data or hospital data in a single area. The existing papers on Taiwan's CS rates not only use a questionnaire, but also study only a single hospital (Huang et al., 1997). To our knowledge, this paper is the first effort to use official and national data to study CS rates of all hospitals in Taiwan during the past decade. Both supply and demand sides make the CS decision. In following sections, we will explore the factors causing the high CS rates in Taiwan, both from the supply and demand sides. For the supply-side analysis, the associated factors taken into account in the papers are the doctor's wage system, hospital ownership, etc. For demand-side analysis, the associated factors are religion, regional per capita income, and the national heath insurance program's payment. Method Sub-grouping hospitals by characteristics There are twenty-three municipalities and counties covering the island of the Taiwan. …

Récupéré en direct depuis OpenAlex et désinversé. Les résumés ne sont pas conservés dans cette base de données : les index inversés représentent 8,6 Go des 9,3 Go de texte de la base, et le serveur dispose de 13 Go libres.

Comment cette classification a été obtenuedéplier

Prédiction distillée sur la base complète

Imitation des enseignants

Ni 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.

score de la tête « metaresearch » (Codex)0,004
score de la tête « metaresearch » (Gemma)0,001
Version: codex-gemma-dda1882f352aStatut de validation: machine_predicted_unvalidated
Catégories candidatesCharge utile insuffisante (le modèle a refusé de juger)
Catégories consensuellesaucune
DomaineSignal candidat: aucune · Signal consensuel: aucune
Devis d'étudeSignal candidat: Théorique ou conceptuel · Signal consensuel: aucune
GenreSignal candidat: Empirique · Signal consensuel: Empirique
Score de désaccord entre enseignants0,802
Score d'incertitude au seuil1,000

Scores Codex et Gemma par catégorie

CatégorieCodexGemma
Métarecherche0,0040,001
Méta-épidémiologie (sens strict)0,0000,000
Méta-épidémiologie (sens large)0,0000,000
Bibliométrie0,0000,000
Études des sciences et des technologies0,0010,000
Communication savante0,0000,000
Science ouverte0,0010,000
Intégrité de la recherche0,0000,000
Charge utile insuffisante (le modèle a refusé de juger)0,0010,000

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.

Tête enseignante Opus0,048
Tête enseignante GPT0,453
Écart entre enseignants0,405 · la distance entre les deux têtes enseignantes sur ce seul travail
Statut de validationscore_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

Classification

machine, non validée

Prédiction automatique; un appel candidat d’une seule tête enseignante, pas un consensus.

Devis d'étudeThéorique ou conceptuel
Domainenon disponible
GenreEmpirique

Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».

En bref

Citations0
Publié2005
Routes d'admission1
Résumé présentoui

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