Literature DB >> 28032261

Identifying congestion levels, sources and determinants on intensive care units: the Portuguese case.

Diogo Ferreira1, Rui Cunha Marques2.   

Abstract

Healthcare systems are facing a resources scarcity so they must be efficiently managed. On the other hand, it is commonly accepted that the higher the consumed resources, the higher the hospital production, although this is not true in practice. Congestion on inputs is an economic concept dealing with such situation and it is defined as the decreasing of outputs due to some resources overuse. This scenario gets worse when inpatients' high severity requires a strict and effective resources management, as happens in Intensive Care Units (ICU). The present paper employs a set of nonparametric models to evaluate congestion levels, sources and determinants in Portuguese Intensive Care Units. Nonparametric models based on Data Envelopment Analysis are employed to assess both radial and non-radial (in)efficiency levels and sources. The environment adjustment models and bootstrapping are used to correct possible bias, to remove the deterministic nature of nonparametric models and to get a statistical background on results. Considerable inefficiency and congestion levels were identified, as well as the congestion determinants, including the ICU specialty and complexity, the hospital differentiation degree and population demography. Both the costs associated with staff and the length of stay are the main sources of (weak) congestion in ICUs. ICUs management shall make some efforts towards resource allocation to prevent the congestion effect. Those efforts shall, in general, be focused on costs with staff and hospital days, although these congestion sources may vary across hospitals and ICU services, once several congestion determinants were identified.

Keywords:  Bootstrap; Congestion; Data Envelopment Analysis; Environment adjustment; Intensive Care Units

Mesh:

Year:  2016        PMID: 28032261     DOI: 10.1007/s10729-016-9387-x

Source DB:  PubMed          Journal:  Health Care Manag Sci        ISSN: 1386-9620


  21 in total

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5.  Congestion analysis to evaluate the efficiency and appropriateness of hospitals in Sicily.

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Journal:  Health Policy       Date:  2014-12-22       Impact factor: 2.980

6.  Should inpatients be adjusted by their complexity and severity for efficiency assessment? Evidence from Portugal.

Authors:  Diogo Cunha Ferreira; Rui Cunha Marques
Journal:  Health Care Manag Sci       Date:  2014-06-03

7.  A national study of the efficiency of hospitals in urban markets.

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Journal:  Health Serv Res       Date:  1993-02       Impact factor: 3.402

8.  Benchmarking urban acute care hospitals: efficiency and quality perspectives.

Authors:  Preethy Nayar; Yasar A Ozcan; Fang Yu; Anh T Nguyen
Journal:  Health Care Manage Rev       Date:  2013 Apr-Jun

9.  Hospital quality, efficiency, and input slack differentials.

Authors:  Vivian G Valdmanis; Michael D Rosko; Ryan L Mutter
Journal:  Health Serv Res       Date:  2008-09-08       Impact factor: 3.402

10.  Output congestion leads to compromised care in Peruvian public hospital neonatal units.

Authors:  Alejandro Arrieta; Jorge Guillén
Journal:  Health Care Manag Sci       Date:  2015-10-09
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  2 in total

1.  Using data envelopment analysis to perform benchmarking in intensive care units.

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Journal:  PLoS One       Date:  2021-11-18       Impact factor: 3.240

Review 2.  The Core of Healthcare Efficiency: A Comprehensive Bibliometric Review on Frontier Analysis of Hospitals.

Authors:  Thyago Celso Cavalcante Nepomuceno; Luca Piubello Orsini; Victor Diogho Heuer de Carvalho; Thiago Poleto; Chiara Leardini
Journal:  Healthcare (Basel)       Date:  2022-07-15
  2 in total

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