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扩大监测范围,与社区共享数据:来自儿童保健中心疾病监测计划的定性见解。

Expanding Surveillance Toward Sharing Data with the Community: Qualitative Insights from a Childcare Center Illness Surveillance Program.

机构信息

Peter M. DeJonge, MPH, and Khalil Chedid, MD, MPH, are PhD Candidates, Department of Epidemiology; Abigail Gaughan is an Undergraduate Student; Emily T. Martin, PhD, MPH, is an Associate Professor, Department of Epidemiology; and Alison L. Miller, PhD, is an Associate Professor, Department of Health Behavior and Health Education; all at the University of Michigan School of Public Health, Ann Arbor, MI. William Gribbin, MS, is a Medical Student and Andrew N. Hashikawa, MD, MPH, is an Associate Professor, Department of Emergency Medicine and Department of Pediatrics; both at the University of Michigan Medical School, Ann Arbor, MI.

出版信息

Health Secur. 2021 May-Jun;19(3):262-270. doi: 10.1089/hs.2020.0069. Epub 2021 May 5.

Abstract

Childcare attendance is a recognized independent risk factor for pediatric infectious diseases due to the pathogen-sharing behaviors of young children and the crowded environments of childcare programs. The Michigan Child Care Related Infections Surveillance Program (MCRISP) is a novel online illness surveillance network used by community childcare centers to track disease incidence. It has been used to warn local public health departments about emerging outbreaks. The flow of data from MCRISP, however, remains largely unidirectional-from data reporter to public health researchers. With the intent to ultimately improve the system for users, we wanted to better understand how community illness data collected by MCRISP might best benefit childcare stakeholders themselves. Using a ground-up design approach, we conducted a series of focus groups among childcare directors participating in MCRISP. All primary data reporters from each of the 30 MCRISP-affiliated childcare centers were eligible to participate in the focus groups. A thematic assessment from the focus groups revealed that participants wanted surveillance system improvements that would (1) support subjective experiences with objective data, (2) assist with program decision making, (3) provide educational resources, and (4) prioritize the user's experience. Our findings support a framework by which community disease surveillance networks can move toward greater transparency and 2-way data flow. Ultimately, a more mutually beneficial surveillance system improves stakeholder engagement, provides opportunities for rapid mitigation strategies, and can help allocate timely resources in responding to emerging outbreaks and pandemics.

摘要

儿童保育出勤率是儿科传染病的公认独立危险因素,这是由于幼儿的病原体共享行为和儿童保育计划的拥挤环境所致。密歇根州儿童保育相关感染监测计划(MCRISP)是一个新颖的在线疾病监测网络,用于社区儿童保育中心跟踪疾病发病率。它已被用于向当地公共卫生部门发出有关新出现的疫情爆发的警告。然而,MCRISP 的数据流向主要是单向的,即从数据报告者到公共卫生研究人员。为了最终为用户改进系统,我们想更好地了解 MCRISP 收集的社区疾病数据如何最能使儿童保育利益相关者受益。我们采用自下而上的设计方法,在参与 MCRISP 的儿童保育主任中进行了一系列焦点小组讨论。每个参与 MCRISP 的 30 家儿童保育中心的所有主要数据报告人均有资格参加焦点小组。焦点小组的主题评估显示,参与者希望改进监测系统,以(1)支持客观数据的主观经验,(2)协助决策,(3)提供教育资源,并(4)优先考虑用户体验。我们的研究结果支持了一个框架,通过该框架,社区疾病监测网络可以朝着更大的透明度和双向数据流发展。最终,一个更互利的监测系统可以提高利益相关者的参与度,为快速缓解策略提供机会,并有助于在应对新出现的疫情和大流行时及时分配资源。

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