SCC-Planning: Using Innovations in Big Data and Technology to Address the High Rate of Infant Mortality in Greater Columbus Ohio
SCC-Planning:利用大数据和技术创新解决俄亥俄州大哥伦布市婴儿死亡率高的问题
基本信息
- 批准号:1737560
- 负责人:
- 金额:$ 10万
- 依托单位:
- 依托单位国家:美国
- 项目类别:Standard Grant
- 财政年份:2017
- 资助国家:美国
- 起止时间:2017-09-01 至 2020-02-29
- 项目状态:已结题
- 来源:
- 关键词:
项目摘要
Franklin County, Ohio, home of the state's capital at Columbus, has one of the highest infant mortality rates in the country at 8.3 deaths per 1,000 live births. As outlined in a recent article in the Journal of the American Medical Association (2016), the U.S. lags behind in many important measures of population health, including infant mortality, despite the fact that one-fifth of our dollars are spent on healthcare. While the data needed to address these important public health problems are available, to date we have not seen adequate investment in informatics approaches to combine and analyze these multilevel (e.g., individual lifestyle factors, neighborhood characteristics) data. The current planning project represents an effort to plan (with an intent to implement) just such an approach to address the high rate of infant mortality in Greater Columbus and nationwide. As the recent winner of the Department of Transportation's Smart Cities Challenge, Columbus already has a well-developed plan to employ technology to improve local transportation options, which is anticipated to ameliorate some contributing factors such as lack of access prenatal and other health care. The financial support from this and follow-up grants will permit us to expand that effort and leverage technological advances to further identify and design interventions to address risk factors for poor maternal and infant health outcomes. Further, by including students and other trainees in our work, we will be training the next generation of scientists to develop innovative solutions to address complex societal problems. The objectives of this one-year planning project are to: 1) identify data gaps that present local barriers to achieving optimal maternal and infant health and their effect on proximate causes of infant mortality in the community; 2) align with key stakeholders and partners in the community with a goal to identify opportunities where technology, especially connectivity and mobility, could be leveraged to address barriers and speed-up progress; and 3) utilize our technological and content expertise to design and implement novel interventions for improving maternal and infant health. Since 2014 there have been a number of local efforts to address Franklin County's high rate of infant mortality to no avail. As such, there is a dire need for a coordinated novel multidisciplinary approach. The primary focus and intellectual contribution of this planning grant is to work closely with stakeholders to plan strategies to identify the key contributors of infant mortality in Franklin County (i.e., likely specific social determinants of health) and to develop novel interventions driven by innovations in BIGDATA technology.
俄亥俄州的富兰克林县是该州首府哥伦布的所在地,是全国婴儿死亡率最高的县之一,每1,000名活产婴儿中有8.3人死亡。 正如《美国医学会杂志》(Journal of the American Medical Association,2016)最近的一篇文章所概述的那样,美国在许多重要的人口健康指标上落后,包括婴儿死亡率,尽管我们五分之一的美元花在医疗保健上。 虽然解决这些重要的公共卫生问题所需的数据是可用的,但到目前为止,我们还没有看到对信息学方法的充分投资,以联合收割机和分析这些多层次(例如,个人生活方式因素、邻里特征)数据。目前的规划项目代表了一种努力,即规划(意图实施)这样一种方法,以解决大哥伦布和全国范围内的婴儿死亡率高的问题。 作为交通部智能城市挑战赛的最近赢家,哥伦布已经制定了一项完善的计划,利用技术改善当地的交通选择,预计这将改善一些促成因素,如缺乏产前和其他医疗保健。 这笔赠款和后续赠款的财政支持将使我们能够扩大这一努力,并利用技术进步进一步确定和设计干预措施,以解决孕产妇和婴儿健康结果不佳的风险因素。此外,通过让学生和其他受训人员参与我们的工作,我们将培训下一代科学家,以开发创新的解决方案来解决复杂的社会问题。 这一为期一年的规划项目的目标是:1)确定阻碍实现最佳母婴健康的地方障碍及其对社区婴儿死亡近因的影响的数据差距; 2)与社区的主要利益攸关方和合作伙伴保持一致,目标是确定可以利用技术,特别是连通性和流动性来克服障碍和加快进展的机会; 3)利用我们的技术和内容专业知识,设计和实施新的干预措施,以改善孕产妇和婴儿的健康。自2014年以来,当地为解决富兰克林县婴儿死亡率高的问题做出了许多努力,但都无济于事。因此,迫切需要一种协调的新的多学科方法。这项规划赠款的主要重点和智力贡献是与利益攸关方密切合作,规划战略,以确定富兰克林县婴儿死亡率的主要因素(即,可能是健康的特定社会决定因素),并开发由BIGDATA技术创新驱动的新干预措施。
项目成果
期刊论文数量(0)
专著数量(0)
科研奖励数量(0)
会议论文数量(0)
专利数量(0)
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Raghu Machiraju其他文献
Raghu Machiraju的其他文献
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{{ truncateString('Raghu Machiraju', 18)}}的其他基金
Collaborative Research: Autonomous Computing Materials
合作研究:自主计算材料
- 批准号:
1940168 - 财政年份:2019
- 资助金额:
$ 10万 - 项目类别:
Continuing Grant
Spokes: MEDIUM: MIDWEST: Collaborative: Community-Driven Data Engineering for Substance Abuse Prevention in the Rural Midwest
辐条:媒介:中西部:协作:社区驱动的数据工程,用于中西部农村地区的药物滥用预防
- 批准号:
1761969 - 财政年份:2018
- 资助金额:
$ 10万 - 项目类别:
Standard Grant
BCSP: ABI Innovation: Collaborative Research: Predicting changes in protein activity from changes in sequence by identifying the underlying Biophysical Conditional Random Field
BCSP:ABI 创新:协作研究:通过识别潜在的生物物理条件随机场,根据序列变化预测蛋白质活性的变化
- 批准号:
1262469 - 财政年份:2014
- 资助金额:
$ 10万 - 项目类别:
Standard Grant
G&V: Medium: Collaborative Research: Large Data Visualization Using An Interactive Machine Learning Framework
G
- 批准号:
1065025 - 财政年份:2011
- 资助金额:
$ 10万 - 项目类别:
Standard Grant
SOFTWARE: Framework for Mining Large and Complex Scientific Datasets
软件:挖掘大型复杂科学数据集的框架
- 批准号:
0234273 - 财政年份:2003
- 资助金额:
$ 10万 - 项目类别:
Continuing Grant
ITR/NGS: A Framework for Discovery, Exploration and Analysis of Evolutionary Simulation Data (DEAS)
ITR/NGS:进化模拟数据发现、探索和分析的框架 (DEAS)
- 批准号:
0326386 - 财政年份:2003
- 资助金额:
$ 10万 - 项目类别:
Continuing Grant
CAREER: On the Assessment of Volume Rendering Algorithms in Visual Computing
职业:视觉计算中体积渲染算法的评估
- 批准号:
0196242 - 财政年份:2000
- 资助金额:
$ 10万 - 项目类别:
Continuing grant
CAREER: On the Assessment of Volume Rendering Algorithms in Visual Computing
职业:视觉计算中体积渲染算法的评估
- 批准号:
9734483 - 财政年份:1998
- 资助金额:
$ 10万 - 项目类别:
Continuing Grant
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