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CAREER: Incorporating Patient Heterogeneity and Choice into Predictive Models of Health and Economic Outcomes

CAREER: Incorporating Patient Heterogeneity and Choice into Predictive Models of Health and Economic Outcomes
职业:将患者异质性和选择纳入健康和经济结果的预测模型中
批准号:
1433602
负责人:
Maria Mayorga
金额:
$15.54万
依托单位国家:
美国
项目类别:
Standard Grant
财政年份:
2013
资助国家:
美国
项目状态:
已结题
起止时间:
2013-09-01 至 2017-05-31

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英文摘要
This Faculty Early Career Development (CAREER) Program award investigates how to obtain better predictions of the effectiveness of population-level health interventions. The research strategy is to create consumer choice models that incorporate patient heterogeneity into predictive models of health and economic outcomes. The patient plays a key role in conditions that are chronic and not immediately life threatening, but that in the long term can be harmful through associated co-morbidities. This research builds on collaborations with health sciences experts to take an interdisciplinary approach. Consumer choice models will be transformed into models for patient choice. This allows for individual patient preferences to be considered (e.g., time-preferences, willingness-to-pay for treatment) which may depend on socio-demographic patient attributes. These new patient choice models will be embedded into predictive models of health outcomes (smoking cessation and maternal drinking) and long term treatment effectiveness studies will be conducted at the population level. The educational plan includes advising and mentoring activities that work with discovery-oriented "creative inquiry" projects involving multi-level student teams.If successful, the results of this research will allow health science experts to move from efficacy to effectiveness characterization by explicitly considering individual patient preferences. These new models may also be used in predictive health models of other policy-relevant issues. Ultimately, the inclusion of patient choice will result in more accurate estimates of treatment effectiveness and more accurate predictions of health and economic outcomes. This allows policy makers to choose the most efficient intervention strategies, with a richer information set than can be provided by clinical trials alone. Middle school students studying in technology programs will be introduced to the field of industrial engineering and engage with undergraduate research teams. Graduate students will mentor participating undergraduates, resulting in a pipeline of students who will be prepared to undertake technical careers in the healthcare service industry and in academia.
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RAPID/Collaborative Research: Defining a Performance Measurement Framework for Spontaneous Volunteer Management Systems in Post-Disaster Relief
  • 批准号:
    1901699
  • 项目类别:
    Standard Grant
  • 资助金额:
    $1.14万
  • 财政年份:
    2018
  • 负责人:
    Maria Mayorga
  • 依托单位:
RAPID/Collaborative Research: Field Study of Volunteer Convergence in Post-Disaster Relief
  • 批准号:
    1760193
  • 项目类别:
    Standard Grant
  • 资助金额:
    $3.2万
  • 财政年份:
    2017
  • 负责人:
    Maria Mayorga
  • 依托单位:
CAREER: Incorporating Patient Heterogeneity and Choice into Predictive Models of Health and Economic Outcomes
  • 批准号:
    1150732
  • 项目类别:
    Standard Grant
  • 资助金额:
    $40.0万
  • 财政年份:
    2012
  • 负责人:
    Maria Mayorga
  • 依托单位:
海外基金