Measurement and sources of overall and input inefficiencies: Evidences and implications in hospital services

Andrew Chen, Yuhchang Hwang, Benjamin Shao

Research output: Contribution to journalArticle

66 Citations (Scopus)

Abstract

Traditional data envelopment analysis (DEA) focuses exclusively on measuring the overall efficiency of a decision making unit (DMU). Yet, variables that have explanatory power for the overall operational inefficiency of a DMU may not necessarily be the same as those that affect its individual input inefficiencies. On many occasions, variables that explain the overall inefficiency of a DMU can be inconsistent or incongruent with those that cause its individual input inefficiencies. Therefore, we conjecture that an overall inefficiency score alone may have limited value for decision making since such a process requires fine-tuning and adjustments of specific input factors of the DMU in order to maximize its overall efficiency. In this paper, the utilization and financial data of a set of hospitals in California is used to empirically test the above conjecture. Our study has several important contributions and practical implications. First, we fine-tune previous efficiency measures on hospitals by refining input and output measures. Second, with variables on organization, management, demographics, and market competition, we identify specific factors associated with a hospital's overall operational inefficiency. More importantly, by decomposing the overall DEA operational inefficiency score into different individual input inefficiencies (including slacks), we further identify specific variables that cause individual input inefficiency. Third, significant differences are observed among factors of the overall inefficiency and individual input inefficiencies. These findings have important implications for identifying congruent factors for performance standard setting and evaluation; it also provides invaluable information for guiding effective resource allocation and better decision making for improving hospital operational efficiency.

Original languageEnglish (US)
Pages (from-to)447-468
Number of pages22
JournalEuropean Journal of Operational Research
Volume161
Issue number2
DOIs
StatePublished - Mar 1 2005

Fingerprint

Decision making
Decision Making
decision making
evidence
Data envelopment analysis
Unit
Data Envelopment Analysis
efficiency
data analysis
Financial Data
Congruent
performance standard
cause
Inconsistent
Resource Allocation
Refining
Resource allocation
Evidence
Inefficiency
Hospital services

Keywords

  • Data envelopment analysis
  • Decision analysis
  • Health services
  • Productivity and competition

ASJC Scopus subject areas

  • Information Systems and Management
  • Management Science and Operations Research
  • Statistics, Probability and Uncertainty
  • Applied Mathematics
  • Modeling and Simulation
  • Transportation

Cite this

Measurement and sources of overall and input inefficiencies : Evidences and implications in hospital services. / Chen, Andrew; Hwang, Yuhchang; Shao, Benjamin.

In: European Journal of Operational Research, Vol. 161, No. 2, 01.03.2005, p. 447-468.

Research output: Contribution to journalArticle

@article{68cf5f8e403a4eb58d7203bd729337bb,
title = "Measurement and sources of overall and input inefficiencies: Evidences and implications in hospital services",
abstract = "Traditional data envelopment analysis (DEA) focuses exclusively on measuring the overall efficiency of a decision making unit (DMU). Yet, variables that have explanatory power for the overall operational inefficiency of a DMU may not necessarily be the same as those that affect its individual input inefficiencies. On many occasions, variables that explain the overall inefficiency of a DMU can be inconsistent or incongruent with those that cause its individual input inefficiencies. Therefore, we conjecture that an overall inefficiency score alone may have limited value for decision making since such a process requires fine-tuning and adjustments of specific input factors of the DMU in order to maximize its overall efficiency. In this paper, the utilization and financial data of a set of hospitals in California is used to empirically test the above conjecture. Our study has several important contributions and practical implications. First, we fine-tune previous efficiency measures on hospitals by refining input and output measures. Second, with variables on organization, management, demographics, and market competition, we identify specific factors associated with a hospital's overall operational inefficiency. More importantly, by decomposing the overall DEA operational inefficiency score into different individual input inefficiencies (including slacks), we further identify specific variables that cause individual input inefficiency. Third, significant differences are observed among factors of the overall inefficiency and individual input inefficiencies. These findings have important implications for identifying congruent factors for performance standard setting and evaluation; it also provides invaluable information for guiding effective resource allocation and better decision making for improving hospital operational efficiency.",
keywords = "Data envelopment analysis, Decision analysis, Health services, Productivity and competition",
author = "Andrew Chen and Yuhchang Hwang and Benjamin Shao",
year = "2005",
month = "3",
day = "1",
doi = "10.1016/j.ejor.2003.09.017",
language = "English (US)",
volume = "161",
pages = "447--468",
journal = "European Journal of Operational Research",
issn = "0377-2217",
publisher = "Elsevier",
number = "2",

}

TY - JOUR

T1 - Measurement and sources of overall and input inefficiencies

T2 - Evidences and implications in hospital services

AU - Chen, Andrew

AU - Hwang, Yuhchang

AU - Shao, Benjamin

PY - 2005/3/1

Y1 - 2005/3/1

N2 - Traditional data envelopment analysis (DEA) focuses exclusively on measuring the overall efficiency of a decision making unit (DMU). Yet, variables that have explanatory power for the overall operational inefficiency of a DMU may not necessarily be the same as those that affect its individual input inefficiencies. On many occasions, variables that explain the overall inefficiency of a DMU can be inconsistent or incongruent with those that cause its individual input inefficiencies. Therefore, we conjecture that an overall inefficiency score alone may have limited value for decision making since such a process requires fine-tuning and adjustments of specific input factors of the DMU in order to maximize its overall efficiency. In this paper, the utilization and financial data of a set of hospitals in California is used to empirically test the above conjecture. Our study has several important contributions and practical implications. First, we fine-tune previous efficiency measures on hospitals by refining input and output measures. Second, with variables on organization, management, demographics, and market competition, we identify specific factors associated with a hospital's overall operational inefficiency. More importantly, by decomposing the overall DEA operational inefficiency score into different individual input inefficiencies (including slacks), we further identify specific variables that cause individual input inefficiency. Third, significant differences are observed among factors of the overall inefficiency and individual input inefficiencies. These findings have important implications for identifying congruent factors for performance standard setting and evaluation; it also provides invaluable information for guiding effective resource allocation and better decision making for improving hospital operational efficiency.

AB - Traditional data envelopment analysis (DEA) focuses exclusively on measuring the overall efficiency of a decision making unit (DMU). Yet, variables that have explanatory power for the overall operational inefficiency of a DMU may not necessarily be the same as those that affect its individual input inefficiencies. On many occasions, variables that explain the overall inefficiency of a DMU can be inconsistent or incongruent with those that cause its individual input inefficiencies. Therefore, we conjecture that an overall inefficiency score alone may have limited value for decision making since such a process requires fine-tuning and adjustments of specific input factors of the DMU in order to maximize its overall efficiency. In this paper, the utilization and financial data of a set of hospitals in California is used to empirically test the above conjecture. Our study has several important contributions and practical implications. First, we fine-tune previous efficiency measures on hospitals by refining input and output measures. Second, with variables on organization, management, demographics, and market competition, we identify specific factors associated with a hospital's overall operational inefficiency. More importantly, by decomposing the overall DEA operational inefficiency score into different individual input inefficiencies (including slacks), we further identify specific variables that cause individual input inefficiency. Third, significant differences are observed among factors of the overall inefficiency and individual input inefficiencies. These findings have important implications for identifying congruent factors for performance standard setting and evaluation; it also provides invaluable information for guiding effective resource allocation and better decision making for improving hospital operational efficiency.

KW - Data envelopment analysis

KW - Decision analysis

KW - Health services

KW - Productivity and competition

UR - http://www.scopus.com/inward/record.url?scp=5444247837&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=5444247837&partnerID=8YFLogxK

U2 - 10.1016/j.ejor.2003.09.017

DO - 10.1016/j.ejor.2003.09.017

M3 - Article

AN - SCOPUS:5444247837

VL - 161

SP - 447

EP - 468

JO - European Journal of Operational Research

JF - European Journal of Operational Research

SN - 0377-2217

IS - 2

ER -