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The BASIC trial: Improving implementation of evidence-based approaches and surveillance to prevent bacterial transmission and infection

The BASIC trial: Improving implementation of evidence-based approaches and surveillance to prevent bacterial transmission and infection
BASIC 试验:改进循证方法和监测的实施,以防止细菌传播和感染
批准号:
10434139
负责人:
Jeremiah R Brown
金额:
$80.55万
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
项目状态:
未结题
起止时间:
2021-06-17 至 2026-05-31

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中文摘要
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英文摘要
We propose to establish a best practice for implementation of a multifaceted approach designed to attenuate perioperative ESKAPE (Enterococcus, S. aureus, Klebsiella, Acinetobacter, Pseudomonas, Enterobacter spp.) transmission and associated surgical site infection (SSI) development. Perioperative ESKAPE transmission (inoculum) contributes to the development of surgical site infections (SSIs) which affect 3-5% of patients undergoing surgery. SSIs increase patient morbidity, prolong hospitalization, increase the risk of intensive care unit admission, and increase the risk of death 2-fold. ESKAPE pathogens are particularly problematic. Sustained reductions in epidemiologically-related, perioperative S. aureus transmission events achieved via a multi-faceted approach including surveillance feedback optimization resulted in substantial SSI reductions (88% decrease). An evidence-based approach for attenuation of the perioperative bacterial inoculum2 must integrate improvements in provider hand hygiene, intravascular catheter design/handling, environmental cleaning/organization, and patient decolonization. In this application, we propose a type 1 hybrid effectiveness-implementation using a 2x2 factorial cluster-randomized design guided by RE-AIM. We aim to identify a best practice for addressing the perioperative ESKAPE inoculum. We will examine the relative effectiveness of increased site awareness and commitment to generating improvements via technical assistance (TA), team coaching implementation of an evidence-based set of interventions (EBIP), and TA or EBIP with ESKAPE transmission surveillance feedback. Our strong preliminary data from a randomized trial implementing a multifaceted program with surveillance has demonstrated substantial and statistically significant reductions in transmission of S. aureus and 90-day SSIs and recently reproduced our randomized trial findings in an additional external site. Therefore, our prior research strongly suggests that the proposed research should be done and justifies scaling up to dissemination and implementation. Our exceptional multidisciplinary team is well equipped to successfully complete the proposed trial and aims. In the proposed trial guided by RE-AIM, we will advance scientific knowledge and inform future dissemination and implementation by investigating how best to scale-up an already successful multifaceted approach to national dissemination through either TA or EBIP with or without surveillance. We will conduct a rigorous cost- effectiveness analysis including evaluation of net cost savings. The proposed trial guided by RE-AIM (Aim 1), the addition of 1-year follow-up for sustainability (Aim 2), and cost-effectiveness analysis (Aim 3) will provide the essential scientific knowledge to adopters and organizers to be able to reproduce the most effective delivery method of our interventions to their local setting in addition to informing our investigative team which approach to scale-up to reach national dissemination.
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The BASIC trial: Improving implementation of evidence-based approaches and surveillance to prevent bacterial transmission and infection
  • 批准号:
    10618922
  • 项目类别:
  • 资助金额:
    $80.01万
  • 财政年份:
    2021
  • 负责人:
    Jeremiah R Brown
  • 依托单位:
The BASIC trial: Improving implementation of evidence-based approaches and surveillance to prevent bacterial transmission and infection
  • 批准号:
    10316780
  • 项目类别:
  • 资助金额:
    $84.31万
  • 财政年份:
    2021
  • 负责人:
    Jeremiah R Brown
  • 依托单位:
DeepCOPD: Development and Implementation of Deep Learning to Predict and Prevent COPD Health Care Encounters
  • 批准号:
    10542393
  • 项目类别:
  • 资助金额:
    $74.16万
  • 财政年份:
    2021
  • 负责人:
    Jeremiah R Brown
  • 依托单位:
DeepCOPD: Development and Implementation of Deep Learning to Predict and Prevent COPD Health Care Encounters
  • 批准号:
    10382949
  • 项目类别:
  • 资助金额:
    $78.69万
  • 财政年份:
    2021
  • 负责人:
    Jeremiah R Brown
  • 依托单位:
海外基金