Understanding the effect of rurality and social risk factors on barriers to care and surgical outcomes.

了解农村和社会风险因素对护理和手术结果障碍的影响。

基本信息

  • 批准号:
    10677260
  • 负责人:
  • 金额:
    --
  • 依托单位:
  • 依托单位国家:
    美国
  • 项目类别:
  • 财政年份:
    2021
  • 资助国家:
    美国
  • 起止时间:
    2021-10-01 至 2025-03-31
  • 项目状态:
    未结题

项目摘要

Background: The Mission Act provides improved Veteran access to care both within the Veterans Administration (VA) and community systems. An underlying assumption is that faster care with more choices results in better care. However, care fragmentation is associated with increased length of stay, readmissions, and mortality. Postoperative complications and readmissions are higher in minority and low socioeconomic status (SES) patients. Low SES is also associated with frailty, one of the best predictors of 30-day postoperative complications and hospital readmissions. Despite having a profound influence on health outcomes, social risk factors are absent from risk adjustment for VA quality measures, further exacerbating disparities in minority and low SES populations. This strategy may further constrain resources to care for vulnerable populations, as many Veterans are economically disadvantaged and potentially adding avoidable costs to care delivery. Another major issue is care fragmentation. Nevertheless, the impact of non-VA care and care fragmentation is absent in performance metrics. Our goal is to identify social risk factors and levels of care fragmentation that affect surgical outcomes to inform VA quality metric policy and institutional resource allocation. We improve upon current practice by joining surgical outcomes data with 1) VA/Centers for Medicare & Medicaid Services (CMS) claims data, 2) VA fee-basis files to identify encounters outside of the VA health system and 3) using more granular proxy social risk factors and neighborhood disadvantage. Significance/Impact: Our significance is modeling surgical outcomes using social risk factors, rurality, living in a disadvantaged neighborhood and care fragmentation to identify factors contributing to health care disparities and to inform VA policy. The impact is to develop quality metrics using social risk factors and care fragmentation. HSR&D priority areas: Rural Health, Health Equity, Health Care Value and Health Care Informatics. Innovation: Joining diverse data sources to develop predictive models using both traditional parametric methods and exploratory machine learning techniques to provide clinicians and administrators with outcomes and economic analyses necessary to change institutional practices to benefit our most vulnerable Veterans. Specific Aims: Aim 1: Identify factors affecting surgical outcomes by assessing the contributions of ethnicity, race, SES, place of residence and care fragmentation to surgical complications, readmissions and mortality Hypothesis: Using ethnic/racial minority status, SES, place of residence and care fragmentation will identify important risk factors for postoperative complications, readmissions, and mortality Aim 2: Assess the impact of social risk factors and care fragmentation on hospital performance metrics for readmissions and mortality Hypothesis: Including social risk factors and care fragmentation in risk adjustment models significantly changes VA hospital performance rankings with respect to readmissions and mortality Aim 3: Determine the relationship of place of residence, care fragmentation, SES and minority status to acute and long-term VA surgical health care utilization to inform VA resource allocation Hypothesis: Low SES, rurality, care fragmentation and minority status are associated with higher VA resource utilization Methodology: Quantitative analyses using traditional parametric and exploratory machine learning techniques performed on diverse datasets to develop predictive models of surgical outcomes using care fragmentation, rurality and social risk factors risk adjusted for medical comorbidities and applied to VA quality metrics. Implementation/Next Steps: Deployment of quality metric models using social risk factors and care fragmentation within the VA system. Adjusting resource allocation to account for social risk factors.
背景:使命法案为退伍军人提供了更好的医疗服务

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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Daniel E Hall其他文献

Outcomes of Women Undergoing Noncardiac Surgery in Veterans Affairs Compared With Non-Veterans Affairs Care Settings.
退伍军人事务部与非退伍军人事务部护理机构中接受非心脏手术的女性的结果进行比较。
  • DOI:
    10.1001/jamasurg.2023.8081
  • 发表时间:
    2024
  • 期刊:
  • 影响因子:
    16.9
  • 作者:
    Elizabeth L George;Michael A. Jacobs;K. Reitz;Nader N Massarweh;A. Youk;Shipra Arya;Daniel E Hall
  • 通讯作者:
    Daniel E Hall

Daniel E Hall的其他文献

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{{ truncateString('Daniel E Hall', 18)}}的其他基金

Understanding the effect of rurality and social risk factors on barriers to care and surgical outcomes.
了解农村和社会风险因素对护理和手术结果障碍的影响。
  • 批准号:
    10431846
  • 财政年份:
    2021
  • 资助金额:
    --
  • 项目类别:
Understanding the effect of rurality and social risk factors on barriers to care and surgical outcomes.
了解农村和社会风险因素对护理和手术结果障碍的影响。
  • 批准号:
    10187736
  • 财政年份:
    2021
  • 资助金额:
    --
  • 项目类别:
Improving surgical decision-making by measuring and predicting long-term loss of independence after surgery
通过测量和预测术后长期丧失独立性来改善手术决策
  • 批准号:
    10316647
  • 财政年份:
    2021
  • 资助金额:
    --
  • 项目类别:
Pilot testing a home-based rehabilitation intervention designed to improve outcomes of frail Veterans following cardiothoracic surgery
试点测试一种家庭康复干预措施,旨在改善心胸外科手术后体弱退伍军人的预后
  • 批准号:
    9922125
  • 财政年份:
    2017
  • 资助金额:
    --
  • 项目类别:
Pilot Testing Prehabilitation Services Aimed at Improving Outcomes of Frail Veterans Following Major Abdominal Surgery
试点康复服务旨在改善体弱的退伍军人在接受重大腹部手术后的结果
  • 批准号:
    9291841
  • 财政年份:
    2017
  • 资助金额:
    --
  • 项目类别:
Describing Variation in IRB Efficiency, Quality and Procedures
描述 IRB 效率、质量和程序的变化
  • 批准号:
    8597960
  • 财政年份:
    2012
  • 资助金额:
    --
  • 项目类别:
Describing Variation in IRB Efficiency, Quality and Procedures
描述 IRB 效率、质量和程序的变化
  • 批准号:
    8279692
  • 财政年份:
    2012
  • 资助金额:
    --
  • 项目类别:

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