Literature DB >> 17068996

A 12-year analysis of Malmquist total factor productivity in dialysis facilities.

Nick Kontodimopoulos1, Dimitris Niakas.   

Abstract

This study examined total factor productivity of dialysis facilities in Greece over a 12-year period, using nationally representative panel data. Data Envelopment Analysis (DEA) was used to compute Malmquist productivity indices, which were decomposed into technical efficiency change and technological change. The sample consisted of 73 dialysis facilities operating throughout the entire study period (1993-2004), corresponding to 97.3% and 58.9% of all facilities in the first and last study years respectively. Production variables were nursing staff and dialysis machines (inputs) and dialysis sessions (output). The DEA model was input-oriented allowing for constant returns to scale (CRS). Technical efficiency change was decomposed into scale efficiency change and variable returns to scale (VRS) "pure" technical efficiency change. Mean overall efficiency, throughout the study years, ranged from 39.6 to 63.1% with an all-time average of 56.7%, and only 2-4% of the facilities were fully efficient in each study year. Productivity indices indicated year-by-year progress or regress up to 5%, but the efficiency and technological components differed, in some cases, by as much as 30%. Although interesting subperiod effects were observed, conclusions could not be generalized for the entire study period due to alternating trends. We suggest that preliminary insight to productivity in this sector has been obtained, but particular subperiods must be isolated and further investigated.

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Year:  2006        PMID: 17068996     DOI: 10.1007/s10916-005-9005-9

Source DB:  PubMed          Journal:  J Med Syst        ISSN: 0148-5598            Impact factor:   4.920


  14 in total

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2.  Productivity and efficiency changes in primary care: a Malmquist index approach.

Authors:  A Giuffrida
Journal:  Health Care Manag Sci       Date:  1999-01

Review 3.  Non-parametric and parametric applications measuring efficiency in health care.

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5.  Reforming the reform: the Greek National Health System in transition.

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6.  The efficiency of treatment strategies of general practitioners. A Malmquist index approach.

Authors:  Matthias Staat
Journal:  Eur J Health Econ       Date:  2003-09

7.  Efficiency measurement of hemodialysis units in Greece with data envelopment analysis.

Authors:  Nick Kontodimopoulos; Dimitris Niakas
Journal:  Health Policy       Date:  2005-02       Impact factor: 2.980

8.  Longitudinal analysis of efficiency in multiple output dialysis markets.

Authors:  Hacer Ozgen; Yasar A Ozcan
Journal:  Health Care Manag Sci       Date:  2004-11

9.  The impact of health care policy initiatives on productivity.

Authors:  M Tambour
Journal:  Health Econ       Date:  1997 Jan-Feb       Impact factor: 3.046

10.  The production of dialysis by for-profit versus not-for-profit freestanding renal dialysis facilities.

Authors:  R I Griffiths; N R Powe; D J Gaskin; G F Anderson; G V de Lissovoy; P K Whelton
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  4 in total

1.  Separating managerial inefficiency from influences of the operating environment: an application in dialysis.

Authors:  Nick Kontodimopoulos; Nikolaos D Papathanasiou; Yannis Tountas; Dimitris Niakas
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2.  The impact of non-discretionary factors on DEA and SFA technical efficiency differences.

Authors:  Nick Kontodimopoulos; Nikolaos D Papathanasiou; Angeliki Flokou; Yannis Tountas; Dimitris Niakas
Journal:  J Med Syst       Date:  2010-05-07       Impact factor: 4.460

3.  Data Envelopment Analysis in the Presence of Measurement Error: Case Study from the National Database of Nursing Quality Indicators® (NDNQI®).

Authors:  Byron J Gajewski; Robert Lee; Nancy Dunton
Journal:  J Appl Stat       Date:  2012-09-18       Impact factor: 1.404

4.  A window-DEA based efficiency evaluation of the public hospital sector in Greece during the 5-year economic crisis.

Authors:  Angeliki Flokou; Vassilis Aletras; Dimitris Niakas
Journal:  PLoS One       Date:  2017-05-23       Impact factor: 3.240

  4 in total

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