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Cross-Disciplinary Consultancy to Enhance Predictions of Asthma Exacerbation Risk in Boston

This paper continues an initiative conducted by the International Society for Disease Surveillance with funding from the Defense Threat Reduction Agency to connect near-term analytical needs of public health practice with technical expertise from the global research community. The goal is to enhance...

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Autores principales: Reid, Margaret, Gunn, Julia, Shah, Snehal, Donovan, Michael, Eggo, Rosalind, Babin, Steven, Stajner, Ivanka, Rogers, Eric, Ensor, Katherine B., Raun, Loren, Levy, Jonathan I., Painter, Ian, Phipatanakul, Wanda, Yip, Fuyuen, Nath, Anjali, Streichert, Laura C., Tong, Catherine, Burkom, Howard
Formato: Online Artículo Texto
Lenguaje:English
Publicado: University of Illinois at Chicago Library 2016
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5302473/
https://www.ncbi.nlm.nih.gov/pubmed/28210420
http://dx.doi.org/10.5210/ojphi.v8i3.6902
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author Reid, Margaret
Gunn, Julia
Shah, Snehal
Donovan, Michael
Eggo, Rosalind
Babin, Steven
Stajner, Ivanka
Rogers, Eric
Ensor, Katherine B.
Raun, Loren
Levy, Jonathan I.
Painter, Ian
Phipatanakul, Wanda
Yip, Fuyuen
Nath, Anjali
Streichert, Laura C.
Tong, Catherine
Burkom, Howard
author_facet Reid, Margaret
Gunn, Julia
Shah, Snehal
Donovan, Michael
Eggo, Rosalind
Babin, Steven
Stajner, Ivanka
Rogers, Eric
Ensor, Katherine B.
Raun, Loren
Levy, Jonathan I.
Painter, Ian
Phipatanakul, Wanda
Yip, Fuyuen
Nath, Anjali
Streichert, Laura C.
Tong, Catherine
Burkom, Howard
author_sort Reid, Margaret
collection PubMed
description This paper continues an initiative conducted by the International Society for Disease Surveillance with funding from the Defense Threat Reduction Agency to connect near-term analytical needs of public health practice with technical expertise from the global research community. The goal is to enhance investigation capabilities of day-to-day population health monitors. A prior paper described the formation of consultancies for requirements analysis and dialogue regarding costs and benefits of sustainable analytic tools. Each funded consultancy targets a use case of near-term concern to practitioners. The consultancy featured here focused on improving predictions of asthma exacerbation risk in demographic and geographic subdivisions of the city of Boston, Massachusetts, USA based on the combination of known risk factors for which evidence is routinely available. A cross-disciplinary group of 28 stakeholders attended the consultancy on March 30-31, 2016 at the Boston Public Health Commission. Known asthma exacerbation risk factors are upper respiratory virus transmission, particularly in school-age children, harsh or extreme weather conditions, and poor air quality. Meteorological subject matter experts described availability and usage of data sources representing these risk factors. Modelers presented multiple analytic approaches including mechanistic models, machine learning approaches, simulation techniques, and hybrids. Health department staff and local partners discussed surveillance operations, constraints, and operational system requirements. Attendees valued the direct exchange of information among public health practitioners, system designers, and modelers. Discussion finalized design of an 8-year de-identified dataset of Boston ED patient records for modeling partners who sign a standard data use agreement.
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spelling pubmed-53024732017-02-16 Cross-Disciplinary Consultancy to Enhance Predictions of Asthma Exacerbation Risk in Boston Reid, Margaret Gunn, Julia Shah, Snehal Donovan, Michael Eggo, Rosalind Babin, Steven Stajner, Ivanka Rogers, Eric Ensor, Katherine B. Raun, Loren Levy, Jonathan I. Painter, Ian Phipatanakul, Wanda Yip, Fuyuen Nath, Anjali Streichert, Laura C. Tong, Catherine Burkom, Howard Online J Public Health Inform Research Article This paper continues an initiative conducted by the International Society for Disease Surveillance with funding from the Defense Threat Reduction Agency to connect near-term analytical needs of public health practice with technical expertise from the global research community. The goal is to enhance investigation capabilities of day-to-day population health monitors. A prior paper described the formation of consultancies for requirements analysis and dialogue regarding costs and benefits of sustainable analytic tools. Each funded consultancy targets a use case of near-term concern to practitioners. The consultancy featured here focused on improving predictions of asthma exacerbation risk in demographic and geographic subdivisions of the city of Boston, Massachusetts, USA based on the combination of known risk factors for which evidence is routinely available. A cross-disciplinary group of 28 stakeholders attended the consultancy on March 30-31, 2016 at the Boston Public Health Commission. Known asthma exacerbation risk factors are upper respiratory virus transmission, particularly in school-age children, harsh or extreme weather conditions, and poor air quality. Meteorological subject matter experts described availability and usage of data sources representing these risk factors. Modelers presented multiple analytic approaches including mechanistic models, machine learning approaches, simulation techniques, and hybrids. Health department staff and local partners discussed surveillance operations, constraints, and operational system requirements. Attendees valued the direct exchange of information among public health practitioners, system designers, and modelers. Discussion finalized design of an 8-year de-identified dataset of Boston ED patient records for modeling partners who sign a standard data use agreement. University of Illinois at Chicago Library 2016-12-28 /pmc/articles/PMC5302473/ /pubmed/28210420 http://dx.doi.org/10.5210/ojphi.v8i3.6902 Text en This is an Open Access article. Authors own copyright of their articles appearing in the Journal of Public Health Informatics. Readers may copy articles without permission of the copyright owner(s), as long as the author and OJPHI are acknowledged in the copy and the copy is used for educational, not-for-profit purposes.
spellingShingle Research Article
Reid, Margaret
Gunn, Julia
Shah, Snehal
Donovan, Michael
Eggo, Rosalind
Babin, Steven
Stajner, Ivanka
Rogers, Eric
Ensor, Katherine B.
Raun, Loren
Levy, Jonathan I.
Painter, Ian
Phipatanakul, Wanda
Yip, Fuyuen
Nath, Anjali
Streichert, Laura C.
Tong, Catherine
Burkom, Howard
Cross-Disciplinary Consultancy to Enhance Predictions of Asthma Exacerbation Risk in Boston
title Cross-Disciplinary Consultancy to Enhance Predictions of Asthma Exacerbation Risk in Boston
title_full Cross-Disciplinary Consultancy to Enhance Predictions of Asthma Exacerbation Risk in Boston
title_fullStr Cross-Disciplinary Consultancy to Enhance Predictions of Asthma Exacerbation Risk in Boston
title_full_unstemmed Cross-Disciplinary Consultancy to Enhance Predictions of Asthma Exacerbation Risk in Boston
title_short Cross-Disciplinary Consultancy to Enhance Predictions of Asthma Exacerbation Risk in Boston
title_sort cross-disciplinary consultancy to enhance predictions of asthma exacerbation risk in boston
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5302473/
https://www.ncbi.nlm.nih.gov/pubmed/28210420
http://dx.doi.org/10.5210/ojphi.v8i3.6902
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