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
Boston Public Health Commission, Boston, MA.
Boston Public Health Commission, Boston, MA; Boston University School of Medicine, Dept. of Pediatrics, Boston, MA.
Online J Public Health Inform. 2016 Dec 28;8(3):e199. doi: 10.5210/ojphi.v8i3.6902. eCollection 2016.
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.
本文延续了由国际疾病监测协会发起的一项倡议,该倡议由国防威胁降低局提供资金,旨在将公共卫生实践的近期分析需求与全球研究界的技术专长联系起来。目标是提高日常人群健康监测人员的调查能力。之前的一篇论文描述了为需求分析以及关于可持续分析工具成本和效益的对话而组建咨询团队的情况。每个获得资助的咨询团队都针对从业者近期关注的一个用例。此处介绍的咨询团队专注于基于常规可得证据的已知风险因素组合,改进对美国马萨诸塞州波士顿市人口和地理细分区域内哮喘加重风险的预测。2016年3月30日至31日,一个由28名利益相关者组成的跨学科团队在波士顿公共卫生委员会参加了此次咨询活动。已知的哮喘加重风险因素包括上呼吸道病毒传播,尤其是在学龄儿童中、恶劣或极端天气条件以及空气质量差。气象主题专家介绍了代表这些风险因素的数据源的可用性和使用情况。建模人员展示了多种分析方法,包括机理模型、机器学习方法、模拟技术以及混合方法。卫生部门工作人员和当地合作伙伴讨论了监测操作、限制因素以及操作系统要求。与会者重视公共卫生从业者、系统设计师和建模人员之间的直接信息交流。讨论最终确定了一个为期8年的波士顿急诊患者记录去识别数据集的设计,供签署标准数据使用协议的建模合作伙伴使用。