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SCC-Planning: Using Innovations in Big Data and Technology to Address the High Rate of Infant Mortality in Greater Columbus Ohio

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
批准号:
1737560
负责人:
Raghu Machiraju
金额:
$10.0万
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
项目状态:
已结题
起止时间:
2017-09-01 至 2020-02-29

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中文摘要
翻译
俄亥俄州首府哥伦布所在的富兰克林县是美国婴儿死亡率最高的县之一,每1000名活产儿中就有8.3人死亡。正如美国医学会杂志(2016)最近的一篇文章所概述的那样,尽管我们五分之一的美元花在了医疗保健上,但美国在许多衡量人口健康的重要指标上都落后了,包括婴儿死亡率。虽然解决这些重要公共卫生问题所需的数据是可用的,但到目前为止,我们还没有看到在信息学方法方面进行足够的投资,以组合和分析这些多层次(例如,个人生活方式因素、社区特征)数据。目前的规划项目是为解决大哥伦布和全国婴儿死亡率高的问题而计划(并打算实施)这样一种方法的努力。作为最近交通部智慧城市挑战赛的获胜者,哥伦布已经制定了一项完善的计划,利用技术来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。这笔资金支持和后续赠款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,以解决产妇和婴儿健康结果不佳的风险因素。此外,通过将学生和其他受训人员纳入我们的工作,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)找出对实现最佳母婴健康构成当地障碍的数据差距及其对社区婴儿死亡的直接原因的影响;2)与社区中的主要利益攸关方和合作伙伴保持一致,以期找出可以利用技术,特别是连通性和机动性来解决障碍和加快进展的机会;以及3)利用我们的技术和内容专长,设计和实施新的干预措施,以改善母婴健康。自2014年以来,当地已经采取了许多努力来解决富兰克林县的高婴儿死亡率问题,但都无济于事。因此,迫切需要一种协调的、新颖的多学科方法。这项计划拨款的主要重点和智力贡献是与利益相关者密切合作,规划战略,以确定富兰克林县婴儿死亡率的关键因素(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。
英文摘要
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.
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Collaborative Research: Autonomous Computing Materials
  • 批准号:
    1940168
  • 项目类别:
    Continuing Grant
  • 资助金额:
    $35.66万
  • 财政年份:
    2019
  • 负责人:
    Raghu Machiraju
  • 依托单位:
Spokes: MEDIUM: MIDWEST: Collaborative: Community-Driven Data Engineering for Substance Abuse Prevention in the Rural Midwest
  • 批准号:
    1761969
  • 项目类别:
    Standard Grant
  • 资助金额:
    $65.1万
  • 财政年份:
    2018
  • 负责人:
    Raghu Machiraju
  • 依托单位:
BCSP: ABI Innovation: Collaborative Research: Predicting changes in protein activity from changes in sequence by identifying the underlying Biophysical Conditional Random Field
  • 批准号:
    1262469
  • 项目类别:
    Standard Grant
  • 资助金额:
    $41.14万
  • 财政年份:
    2014
  • 负责人:
    Raghu Machiraju
  • 依托单位:
G&V: Medium: Collaborative Research: Large Data Visualization Using An Interactive Machine Learning Framework
  • 批准号:
    1065025
  • 项目类别:
    Standard Grant
  • 资助金额:
    $54.2万
  • 财政年份:
    2011
  • 负责人:
    Raghu Machiraju
  • 依托单位:
海外基金