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Using nonparametric conditional approach to integrate quality into efficiency analysis: empirical evidence from cardiology departments

Overview of attention for article published in Health Care Management Science, July 2016
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Title
Using nonparametric conditional approach to integrate quality into efficiency analysis: empirical evidence from cardiology departments
Published in
Health Care Management Science, July 2016
DOI 10.1007/s10729-016-9372-4
Pubmed ID
Authors

Yauheniya Varabyova, Carl Rudolf Blankart, Jonas Schreyögg

Abstract

Health care providers are under pressure to improve both efficiency and quality. The two objectives are not always mutually consistent, because achieving higher levels of quality may require additional resources. The aim of this study is to demonstrate how the nonparametric conditional approach can be used to integrate quality into the analysis of efficiency and to investigate the mechanisms through which quality enters the production process. Additionally, we explain how the conditional approach relates to other nonparametric methods that allow integrating quality into efficiency analysis and provide guidance on the selection of an appropriate methodology. We use data from 178 departments of interventional cardiology and consider three different measures of quality: patient satisfaction, standardized mortality ratio, and patient radiation exposure. Our results refute the existence of a clear trade-off between efficiency and quality. In fact, the impact of quality on the production process differs according to the utilized quality measure. Patient satisfaction does not affect the attainable frontier but does have an inverted U-shaped effect on the distribution of inefficiencies; mortality ratio negatively impacts the attainable frontier when the observed mortality more than doubles the predicted mortality; and patient radiation exposure is not associated with the production process.

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Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 43 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 43 100%

Demographic breakdown

Readers by professional status Count As %
Student > Master 8 19%
Student > Ph. D. Student 6 14%
Student > Doctoral Student 5 12%
Professor 2 5%
Researcher 2 5%
Other 2 5%
Unknown 18 42%
Readers by discipline Count As %
Economics, Econometrics and Finance 6 14%
Engineering 5 12%
Medicine and Dentistry 3 7%
Nursing and Health Professions 2 5%
Social Sciences 2 5%
Other 4 9%
Unknown 21 49%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 1. This is our high-level measure of the quality and quantity of online attention that it has received. This Attention Score, as well as the ranking and number of research outputs shown below, was calculated when the research output was last mentioned on 14 July 2016.
All research outputs
#18,465,988
of 22,880,691 outputs
Outputs from Health Care Management Science
#206
of 285 outputs
Outputs of similar age
#271,353
of 354,681 outputs
Outputs of similar age from Health Care Management Science
#3
of 4 outputs
Altmetric has tracked 22,880,691 research outputs across all sources so far. This one is in the 11th percentile – i.e., 11% of other outputs scored the same or lower than it.
So far Altmetric has tracked 285 research outputs from this source. They typically receive more attention than average, with a mean Attention Score of 7.8. This one is in the 5th percentile – i.e., 5% of its peers scored the same or lower than it.
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