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Medical practices display power law behaviors similar to spoken languages
BACKGROUND: Medical care commonly involves the apprehension of complex patterns of patient derangements to which the practitioner responds with patterns of interventions, as opposed to single therapeutic maneuvers. This complexity renders the objective assessment of practice patterns using conventio...
Autores principales: | , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
BioMed Central
2013
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3766655/ https://www.ncbi.nlm.nih.gov/pubmed/24007376 http://dx.doi.org/10.1186/1472-6947-13-102 |
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author | Paladino, Jonathan D Crooke, Philip S Brackney, Christopher R Kaynar, A Murat Hotchkiss, John R |
author_facet | Paladino, Jonathan D Crooke, Philip S Brackney, Christopher R Kaynar, A Murat Hotchkiss, John R |
author_sort | Paladino, Jonathan D |
collection | PubMed |
description | BACKGROUND: Medical care commonly involves the apprehension of complex patterns of patient derangements to which the practitioner responds with patterns of interventions, as opposed to single therapeutic maneuvers. This complexity renders the objective assessment of practice patterns using conventional statistical approaches difficult. METHODS: Combinatorial approaches drawn from symbolic dynamics are used to encode the observed patterns of patient derangement and associated practitioner response patterns as sequences of symbols. Concatenating each patient derangement symbol with the contemporaneous practitioner response symbol creates “words” encoding the simultaneous patient derangement and provider response patterns and yields an observed vocabulary with quantifiable statistical characteristics. RESULTS: A fundamental observation in many natural languages is the existence of a power law relationship between the rank order of word usage and the absolute frequency with which particular words are uttered. We show that population level patterns of patient derangement: practitioner intervention word usage in two entirely unrelated domains of medical care display power law relationships similar to those of natural languages, and that–in one of these domains–power law behavior at the population level reflects power law behavior at the level of individual practitioners. CONCLUSIONS: Our results suggest that patterns of medical care can be approached using quantitative linguistic techniques, a finding that has implications for the assessment of expertise, machine learning identification of optimal practices, and construction of bedside decision support tools. |
format | Online Article Text |
id | pubmed-3766655 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2013 |
publisher | BioMed Central |
record_format | MEDLINE/PubMed |
spelling | pubmed-37666552013-09-12 Medical practices display power law behaviors similar to spoken languages Paladino, Jonathan D Crooke, Philip S Brackney, Christopher R Kaynar, A Murat Hotchkiss, John R BMC Med Inform Decis Mak Research Article BACKGROUND: Medical care commonly involves the apprehension of complex patterns of patient derangements to which the practitioner responds with patterns of interventions, as opposed to single therapeutic maneuvers. This complexity renders the objective assessment of practice patterns using conventional statistical approaches difficult. METHODS: Combinatorial approaches drawn from symbolic dynamics are used to encode the observed patterns of patient derangement and associated practitioner response patterns as sequences of symbols. Concatenating each patient derangement symbol with the contemporaneous practitioner response symbol creates “words” encoding the simultaneous patient derangement and provider response patterns and yields an observed vocabulary with quantifiable statistical characteristics. RESULTS: A fundamental observation in many natural languages is the existence of a power law relationship between the rank order of word usage and the absolute frequency with which particular words are uttered. We show that population level patterns of patient derangement: practitioner intervention word usage in two entirely unrelated domains of medical care display power law relationships similar to those of natural languages, and that–in one of these domains–power law behavior at the population level reflects power law behavior at the level of individual practitioners. CONCLUSIONS: Our results suggest that patterns of medical care can be approached using quantitative linguistic techniques, a finding that has implications for the assessment of expertise, machine learning identification of optimal practices, and construction of bedside decision support tools. BioMed Central 2013-09-04 /pmc/articles/PMC3766655/ /pubmed/24007376 http://dx.doi.org/10.1186/1472-6947-13-102 Text en Copyright © 2013 Paladino et al.; licensee BioMed Central Ltd. http://creativecommons.org/licenses/by/2.0 This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/2.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. |
spellingShingle | Research Article Paladino, Jonathan D Crooke, Philip S Brackney, Christopher R Kaynar, A Murat Hotchkiss, John R Medical practices display power law behaviors similar to spoken languages |
title | Medical practices display power law behaviors similar to spoken languages |
title_full | Medical practices display power law behaviors similar to spoken languages |
title_fullStr | Medical practices display power law behaviors similar to spoken languages |
title_full_unstemmed | Medical practices display power law behaviors similar to spoken languages |
title_short | Medical practices display power law behaviors similar to spoken languages |
title_sort | medical practices display power law behaviors similar to spoken languages |
topic | Research Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3766655/ https://www.ncbi.nlm.nih.gov/pubmed/24007376 http://dx.doi.org/10.1186/1472-6947-13-102 |
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