Evidence map›Paper›PMID 22998663›Full record

ArticleBMC health services research2012

Efficacy of a numerical value of a fixed-effect estimator in stochastic frontier analysis as an indicator of hospital production structure.

Hiroyuki Kawaguchi, Hideki Hashimoto, Shinya Matsuda

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Article in BMC health services research, 2012. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.

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4citing papers in PubMed
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1 · What the graph read from it

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3 · Its place in the literature

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4 citing papers in PubMed.

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4 · The record

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5 · Who and what money

Authors and funding

3 authors.

Hiroyuki KawaguchiEconomics Faculty, Seijo University, 6-1-20 Seijo, Setagaya-ku, Tokyo, Japan. kawaguchi@seijo.ac.jp
Hideki Hashimoto
Shinya Matsuda

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundThe casemix-based payment system has been adopted in many countries, although it often needs complementary adjustment taking account of each hospital's unique production structure such as teaching and research duties, and non-profit motives. It has been challenging to numerically evaluate the impact of such structural heterogeneity on production, separately of production inefficiency. The current study adopted stochastic frontier analysis and proposed a method to assess unique components of hospital production structures using a fixed-effect variable.

methodsThere were two stages of analyses in this study. In the first stage, we estimated the efficiency score from the hospital production function using a true fixed-effect model (TFEM) in stochastic frontier analysis. The use of a TFEM allowed us to differentiate the unobserved heterogeneity of individual hospitals as hospital-specific fixed effects. In the second stage, we regressed the obtained fixed-effect variable for structural components of hospitals to test whether the variable was explicitly related to the characteristics and local disadvantages of the hospitals.

resultsIn the first analysis, the estimated efficiency score was approximately 0.6. The mean value of the fixed-effect estimator was 0.784, the standard deviation was 0.137, the range was between 0.437 and 1.212. The second-stage regression confirmed that the value of the fixed effect was significantly correlated with advanced technology and local conditions of the sample hospitals.

conclusionThe obtained fixed-effect estimator may reflect hospitals' unique structures of production, considering production inefficiency. The values of fixed-effect estimators can be used as evaluation tools to improve fairness in the reimbursement system for various functions of hospitals based on casemix classification.

Indexed as

Efficiency, OrganizationalStochastic ProcessesDiagnosis-Related GroupsEnglandHospitalsHumans

Identifiers

PMID22998663
PMCPMC3583725

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