Evidence map›Paper›PMID 28210420›Full record

ArticleOnline journal of public health informatics2016

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

Margaret Reid, Julia Gunn, Snehal Shah, Michael Donovan, Rosalind Eggo, Steven Babin, Ivanka Stajner, Eric Rogers, Katherine B Ensor, Loren Raun and 8 more

Abstract read
In one paragraph

Article in Online journal of public health informatics, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

2 citing papers in PubMed.

  1. Article
  2. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

18 authors.

Margaret ReidBoston Public Health Commission, Boston, MA.
Julia GunnBoston Public Health Commission, Boston, MA.
Snehal ShahBoston Public Health Commission, Boston, MA; Boston University School of Medicine, Dept. of Pediatrics, Boston, MA.
Michael DonovanBoston Public Health Commission, Boston, MA.
Rosalind EggoLondon School of Hygiene & Tropical Medicine.
Steven BabinJohns Hopkins University Applied Physics Laboratory, Laurel, MD.
Ivanka StajnerNational Oceanographic and Atmospheric Administration, National Weather Service.
Eric RogersNational Oceanographic and Atmospheric Administration, National Weather Service.
Katherine B EnsorDepartment of Statistics, Rice University, Houston, TX.
Loren RaunDepartment of Statistics, Rice University, Houston, TX.
Jonathan I LevyBoston University School of Public Health, Dept. of Environmental Health, Boston, MA.
Ian PainterUniversity of Washington School of Public Health, Dept. of Health Services, Seattle, WA.
Wanda PhipatanakulBoston Children's Hospital, Harvard Medical School, Boston, MA.
Fuyuen YipCenters for Disease Control and Prevention, National Center for Environmental Health, Division of Environmental Hazards and Health Effects, Atlanta, GA.
Anjali NathBoston Public Health Commission, Boston, MA.
Laura C StreichertInternational Society for Disease Surveillance, Boston, MA.
Catherine TongInternational Society for Disease Surveillance, Boston, MA.
Howard BurkomJohns Hopkins University Applied Physics Laboratory, Laurel, MD.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

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.

Indexed as

asthma exacerbationasthma surveillanceenvironmental risk factorpredictive model

Identifiers

PMID28210420
PMCPMC5302473

What OpenQuestion holds

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Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.