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

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dc.citation.articleNumbere199
dc.citation.issueNumber3
dc.citation.journalTitleOnline Journal of Public Health Informatics
dc.citation.volumeNumber8
dc.contributor.authorReid, Margaret
dc.contributor.authorGunn, Julia
dc.contributor.authorShah, Snehal
dc.contributor.authorDonovan, Michael
dc.contributor.authorEggo, Rosalind
dc.contributor.authorBabin, Steven
dc.contributor.authorStajner, Ivanka
dc.contributor.authorRogers, Eric
dc.contributor.authorEnsor, Katherine B.
dc.contributor.authorRaun, Loren
dc.contributor.authorLevy, Jonathan I.
dc.contributor.authorPainter, Ian
dc.contributor.authorPhipatanakul, Wanda
dc.contributor.authorYip, Fuyuen
dc.contributor.authorNath, Anjali
dc.contributor.authorStreichert, Laura
dc.contributor.authorTong, Catherine
dc.contributor.authorBurkom, Howard
dc.date.accessioned2017-01-30T17:29:31Z
dc.date.available2017-01-30T17:29:31Z
dc.date.issued2016
dc.description.abstractThis 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 (BPHC). 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.
dc.identifier.citationReid, Margaret, Gunn, Julia, Shah, Snehal, et al.. "Cross-Disciplinary Consultancy to Enhance Predictions of Asthma Exacerbation Risk in Boston." <i>Online Journal of Public Health Informatics,</i> 8, no. 3 (2016) Health Policy and Administration Division UIC School of Public Health: http://dx.doi.org/10.5210/ojphi.v8i3.6902.
dc.identifier.doihttp://dx.doi.org/10.5210/ojphi.v8i3.6902
dc.identifier.urihttps://hdl.handle.net/1911/93811
dc.language.isoeng
dc.publisherHealth Policy and Administration Division UIC School of Public Health
dc.rightsArticle is made available in accordance with the publisher's policy and may be subject to US copyright law. Please refer to the publisher's site for terms of use.
dc.subject.keywordasthma exacerbation
dc.subject.keywordpredictive model
dc.subject.keywordenvironmental risk factor
dc.subject.keywordasthma surveillance
dc.titleCross-Disciplinary Consultancy to Enhance Predictions of Asthma Exacerbation Risk in Boston
dc.typeJournal article
dc.type.dcmiText
dc.type.publicationpublisher version
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