Mehr von Lordan, Grace
Mehr von Applied Economics

Export für Ihre Literaturverwaltung

Übernahme per Copy & Paste
Bibtex-Export
Endnote-Export

       

Weiterempfehlen

Bookmark and Share


Considering Endogeneity, Quality of Care and Casemix- A Hierarchical Random Parameters Approach To Measuring Efficiency For Out of Hours Primary Care Services in Ireland

[Zeitschriftenartikel]

Lordan, Grace

Zitationshinweis

Bitte beziehen Sie sich beim Zitieren dieses Dokumentes immer auf folgenden Persistent Identifier (PID):http://nbn-resolving.de/urn:nbn:de:0168-ssoar-241687

Weitere Angaben:
Abstract Modelling efficiency in healthcare with stochastic production frontier analysis can be cumbersome given that frequently outputs are multiple and exogenous. This analysis considers an approach where payroll is considered as an output in the health production function and services offered by the healthcare facility are seen as inputs. These services are generally modelled as outputs in the traditional production frontier approach. It is argued that this may be inappropriate when these services are exogenous and is even more troublesome with multiple output technology when a suitable aggregation method is not apparent. The objective of the function is then to minimise the payroll given the inputs. This approach is applied to micro panel data from primary care out of hours’ services which operate on the Island of Ireland. The model also considers approaches to the problem of controlling for heterogeneity. It deals specifically with heterogeneity associated with unobservable casemix and quality of care. These approaches are compared in terms of their statistical effect on efficiency values and their rankings as well as their theoretical merit.
Sprache Dokument Englisch
Publikationsjahr 2009
Seitenangabe S. 3411-3423
Zeitschriftentitel Applied Economics, 41 (2009) 26
DOI http://dx.doi.org/10.1080/00036840701426592
Status Postprint; begutachtet (peer reviewed)
Lizenz PEER Licence Agreement (applicable only to documents from PEER project)
top