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Using data to improve public health: COVID-19 secondment

Using data to improve public health: COVID-19 secondment
利用数据改善公共卫生:COVID-19 借调
批准号:
MR/W02148X/1
负责人:
Dominik Piehlmaier
金额:
$12.49万
依托单位:
依托单位国家:
英国
项目类别:
Fellowship
财政年份:
2021
资助国家:
英国
项目状态:
已结题
起止时间:
2021 至 --

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中文摘要
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英文摘要
Patients' willingness to seek treatment from their local general practitioner (GP) or healthcare system is instrumental in delivering adequate care. It is one of the National Health Service's (NHS) core missions to improve public health and well-being. Delayed treatment has been associated with higher overall healthcare costs and poor health outcomes. The COVID-19 (C19) pandemic had a profound impact on both the healthcare system as well as on patients. However, the impact of C19 on public willingness to seek timely treatment remains critically understudied. The secondment will be used to shed light on this aspect by analysing fully anonymised patient data within OpenSAFELY. Given the heavily redacted nature of the data, proxies need to be used to illustrate healthcare seeking behaviour. Specifically, healthcare seeking behaviour from patients who suffer from acute pain are observed between the time the first national lockdown was introduced and after all restrictions had been lifted. It is hypothesized that medical treatment to alleviate pain was delayed during all national lockdown episodes due to public health interventions that aimed to protect the NHS from collapsing. Similarly, it is assumed that, on average, delayed medical treatment for these specific priority access cases (i.e., acute pain patients) continue to persist even after all protective public health measures had been lifted. In other words, it is hypothesized that some patients do not seek treatment for pain relief as fast as they would have prior to the pandemic. Competing explanations for delayed treatment are tested. The aim is to identify relevant sociodemographic groups that would benefit from targeted campaigns to increase their tendency to seek timely treatment.
期刊论文(2)
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会议论文
DOI: 10.1136/bmjment-2023-300842
发表时间: 2023-08
期刊: BMJ MENTAL HEALTH
影响因子: --
作者: [McElroy, Eoin, Herrett, Emily, Patel, Kishan, Piehlmaier, Dominik M., Di Gessa, Giorgio, Huggins, Charlotte, Green, Michael J., Kwong, Alex S. F., Thompson, Ellen J., Zhu, Jingmin, Mansfield, Kathryn E., Silverwood, Richard J., Mansfield, Rosie, Maddock, Jane, Mathur, Rohini, Costello, Ruth E., Matthews, Anthony, Tazare, John, Henderson, Alasdair, Wing, Kevin, Bridges, Lucy, Bacon, Sebastian, Mehrkar, Amir, Shaw, Richard John, Wels, Jacques, Katikireddi, Srinivasa Vittal, Chaturvedi, Nish, Tomlinson, Laurie A., Patalay, Praveetha]
通讯作者: Patalay, Praveetha
Ethnic differences in the indirect impacts of the COVID-19 pandemic on clinical monitoring and hospitalisations for non-COVID conditions in England: An observational cohort study using OpenSAFELY
COVID-19 大流行对英格兰非 COVID 疾病临床监测和住院治疗的间接影响的种族差异:使用 OpenSAFELY 进行的一项观察性队列研究
DOI: 10.1101/2023.01.04.23284174
发表时间: 2023
期刊:
影响因子: --
作者: [Costello R]
通讯作者: Costello R
国内基金
海外基金
Scalable Learning and Optimization: High-dimensional Models and Online Decision-Making Strategies for Big Data Analysis
Data-driven Recommendation System Construction of an Online Medical Platform Based on the Fusion of Information
复杂数据下半参数转换模型及其在老年慢性病发展中的应用研究
  • 批准号:
    72101261
  • 项目类别:
    青年科学基金项目(C类)
  • 资助金额:
    30.0万元
  • 批准年份:
    2021
  • 负责人:
    孙韬
  • 依托单位:
Development of a Linear Stochastic Model for Wind Field Reconstruction from Limited Measurement Data
  • 批准号:
    --
  • 项目类别:
    --
  • 资助金额:
    40万元
  • 批准年份:
    2020
  • 负责人:
    Vikrant Gupta
  • 依托单位: