Searching the clinical fitness landscape.

Widespread unexplained variations in clinical practices and patient outcomes suggest major opportunities for improving the quality and safety of medical care. However, there is little consensus regarding how to best identify and disseminate healthcare improvements and a dearth of theory to guide the...

Descripción completa

Guardado en:

Detalles Bibliográficos
Autores principales:	Margaret J Eppstein, Jeffrey D Horbar, Jeffrey S Buzas, Stuart A Kauffman
Formato:	article
Lenguaje:	EN
Publicado:	Public Library of Science (PLoS) 2012
Materias:	Medicine R Science Q
Acceso en línea:	https://doaj.org/article/af8c6fdebb494ed79e0690fa5f885a2c
Etiquetas:	Agregar Etiqueta Sin Etiquetas, Sea el primero en etiquetar este registro!

id	oai:doaj.org-article:af8c6fdebb494ed79e0690fa5f885a2c
record_format	dspace
spelling	oai:doaj.org-article:af8c6fdebb494ed79e0690fa5f885a2c2021-11-18T08:08:39ZSearching the clinical fitness landscape.1932-620310.1371/journal.pone.0049901https://doaj.org/article/af8c6fdebb494ed79e0690fa5f885a2c2012-01-01T00:00:00Zhttps://www.ncbi.nlm.nih.gov/pmc/articles/pmid/23166791/?tool=EBIhttps://doaj.org/toc/1932-6203Widespread unexplained variations in clinical practices and patient outcomes suggest major opportunities for improving the quality and safety of medical care. However, there is little consensus regarding how to best identify and disseminate healthcare improvements and a dearth of theory to guide the debate. Many consider multicenter randomized controlled trials to be the gold standard of evidence-based medicine, although results are often inconclusive or may not be generally applicable due to differences in the contexts within which care is provided. Increasingly, others advocate the use "quality improvement collaboratives", in which multi-institutional teams share information to identify potentially better practices that are subsequently evaluated in the local contexts of specific institutions, but there is concern that such collaborative learning approaches lack the statistical rigor of randomized trials. Using an agent-based model, we show how and why a collaborative learning approach almost invariably leads to greater improvements in expected patient outcomes than more traditional approaches in searching simulated clinical fitness landscapes. This is due to a combination of greater statistical power and more context-dependent evaluation of treatments, especially in complex terrains where some combinations of practices may interact in affecting outcomes. The results of our simulations are consistent with observed limitations of randomized controlled trials and provide important insights into probable reasons for effectiveness of quality improvement collaboratives in the complex socio-technical environments of healthcare institutions. Our approach illustrates how modeling the evolution of medical practice as search on a clinical fitness landscape can aid in identifying and understanding strategies for improving the quality and safety of medical care.Margaret J EppsteinJeffrey D HorbarJeffrey S BuzasStuart A KauffmanPublic Library of Science (PLoS)articleMedicineRScienceQENPLoS ONE, Vol 7, Iss 11, p e49901 (2012)
institution	DOAJ
collection	DOAJ
language	EN
topic	Medicine R Science Q
spellingShingle	Medicine R Science Q Margaret J Eppstein Jeffrey D Horbar Jeffrey S Buzas Stuart A Kauffman Searching the clinical fitness landscape.
description	Widespread unexplained variations in clinical practices and patient outcomes suggest major opportunities for improving the quality and safety of medical care. However, there is little consensus regarding how to best identify and disseminate healthcare improvements and a dearth of theory to guide the debate. Many consider multicenter randomized controlled trials to be the gold standard of evidence-based medicine, although results are often inconclusive or may not be generally applicable due to differences in the contexts within which care is provided. Increasingly, others advocate the use "quality improvement collaboratives", in which multi-institutional teams share information to identify potentially better practices that are subsequently evaluated in the local contexts of specific institutions, but there is concern that such collaborative learning approaches lack the statistical rigor of randomized trials. Using an agent-based model, we show how and why a collaborative learning approach almost invariably leads to greater improvements in expected patient outcomes than more traditional approaches in searching simulated clinical fitness landscapes. This is due to a combination of greater statistical power and more context-dependent evaluation of treatments, especially in complex terrains where some combinations of practices may interact in affecting outcomes. The results of our simulations are consistent with observed limitations of randomized controlled trials and provide important insights into probable reasons for effectiveness of quality improvement collaboratives in the complex socio-technical environments of healthcare institutions. Our approach illustrates how modeling the evolution of medical practice as search on a clinical fitness landscape can aid in identifying and understanding strategies for improving the quality and safety of medical care.
format	article
author	Margaret J Eppstein Jeffrey D Horbar Jeffrey S Buzas Stuart A Kauffman
author_facet	Margaret J Eppstein Jeffrey D Horbar Jeffrey S Buzas Stuart A Kauffman
author_sort	Margaret J Eppstein
title	Searching the clinical fitness landscape.
title_short	Searching the clinical fitness landscape.
title_full	Searching the clinical fitness landscape.
title_fullStr	Searching the clinical fitness landscape.
title_full_unstemmed	Searching the clinical fitness landscape.
title_sort	searching the clinical fitness landscape.
publisher	Public Library of Science (PLoS)
publishDate	2012
url	https://doaj.org/article/af8c6fdebb494ed79e0690fa5f885a2c
work_keys_str_mv	AT margaretjeppstein searchingtheclinicalfitnesslandscape AT jeffreydhorbar searchingtheclinicalfitnesslandscape AT jeffreysbuzas searchingtheclinicalfitnesslandscape AT stuartakauffman searchingtheclinicalfitnesslandscape
_version_	1718422187584520192

Searching the clinical fitness landscape.

Ejemplares similares