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A New Strategy to Evaluate Technical Efficiency in Hospitals Using Homogeneous Groups of Casemix

Overview of attention for article published in Journal of Medical Systems, February 2016
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Title
A New Strategy to Evaluate Technical Efficiency in Hospitals Using Homogeneous Groups of Casemix
Published in
Journal of Medical Systems, February 2016
DOI 10.1007/s10916-016-0458-9
Pubmed ID
Authors

Manuel Villalobos-Cid, Max Chacón, Pedro Zitko, Mario Inostroza-Ponta

Abstract

The public health system has restricted economic resources. Because of that, it is necessary to know how the resources are being used and if they are properly distributed. Several works have applied classical approaches based in Data Envelopment Analysis (DEA) and Stochastic Frontier Analysis (SFA) for this purpose. However, if we have hospitals with different casemix, this is not the best approach. In order to avoid biases in the comparisons, other works have recommended the use of hospital production data corrected by the weights from Diagnosis Related Groups (DRGs), to adjust the casemix of hospitals. However, not all countries have this tool fully implemented, which limits the efficiency evaluation. This paper proposes a new approach for evaluating the efficiency of hospitals. It uses a graph-based clustering algorithm to find groups of hospitals that have similar production profiles. Then, DEA is used to evaluate the technical efficiency of each group. The proposed approach is tested using the production data from 2014 of 193 Chilean public hospitals. The results allowed to identify different performance profiles of each group, that differs from other studies that employs data from partially implemented DRGs. Our results are able to deliver a better description of the resource management of the different groups of hospitals. We have created a website with the results ( bioinformatic.diinf.usach.cl/publichealth ). Data can be requested to the authors.

Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 79 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 79 100%

Demographic breakdown

Readers by professional status Count As %
Researcher 13 16%
Student > Master 12 15%
Student > Bachelor 7 9%
Student > Doctoral Student 5 6%
Student > Ph. D. Student 5 6%
Other 17 22%
Unknown 20 25%
Readers by discipline Count As %
Medicine and Dentistry 21 27%
Economics, Econometrics and Finance 10 13%
Business, Management and Accounting 7 9%
Computer Science 5 6%
Social Sciences 4 5%
Other 9 11%
Unknown 23 29%
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 02 November 2016.
All research outputs
#20,351,881
of 22,899,952 outputs
Outputs from Journal of Medical Systems
#1,006
of 1,154 outputs
Outputs of similar age
#339,797
of 403,284 outputs
Outputs of similar age from Journal of Medical Systems
#21
of 25 outputs
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