Improving Data Surveillance Resilience Beyond COVID-19: Experiences of Primary heAlth Care quAlity Cohort In ChinA (ACACIA) Using Unannounced Standardized Patients.

We analyzed COVID-19 influences on the design, implementation, and validity of assessing the quality of primary health care using unannounced standardized patients (USPs) in China. Because of the pandemic, we crowdsourced our funding, removed tuberculosis from the USP case roster, adjusted common co...

Descripción completa

Detalles Bibliográficos
Publicado en:American Journal of Public Health Vol. 112; no. 6; pp. 913 - 923
Autores principales: Xu, Dong, Cai, Yiyuan, Wang, Xiaohui, Chen, Yaolong, Gong, Wenjie, Liao, Jing, Zhou, Jifang, Zhou, Zhongliang, Zhang, Nan, Tang, Chengxiang, Mi, Baibing, Lu, Yun, Wang, Ruixin, Zhao, Qing, He, Wenjun, Liang, Huijuan, Li, Jinghua, Pan, Jay
Formato: Artículo
Publicado: American Public Health Association Jun2022
Materias:
Acceso en línea:Ver este registro en EBSCOhost
fields @attributes:
  recordID: 1
pdfLink:
plink: https://search.ebscohost.com/login.aspx?direct=true&db=ssf&AN=157068700&site=ehost-live
header:
  @attributes:
    shortDbName: ssf
    uiTerm: 157068700
    longDbName: Social Sciences Full Text (H.W. Wilson)
    uiTag: AN
  controlInfo:
    bkinfo:
    jinfo:
      jid:
        00900036
        APH
      jtl: American Journal of Public Health
      issn: 00900036
      maglogo: N
    pubinfo:
      dt: Jun2022
      vid: 112
      iid: 6
      pid: 44
      pub: American Public Health Association
    artinfo:
      ui:
        157068700
        10.2105/ajph.2022.306779
      ppf: 913
      ppct: 10
      formats:
      tig:
        atl: Improving Data Surveillance Resilience Beyond COVID-19: Experiences of Primary heAlth Care quAlity Cohort In ChinA (ACACIA) Using Unannounced Standardized Patients.
      aug:
        au:
          Xu, Dong
          Cai, Yiyuan
          Wang, Xiaohui
          Chen, Yaolong
          Gong, Wenjie
          Liao, Jing
          Zhou, Jifang
          Zhou, Zhongliang
          Zhang, Nan
          Tang, Chengxiang
          Mi, Baibing
          Lu, Yun
          Wang, Ruixin
          Zhao, Qing
          He, Wenjun
          Liang, Huijuan
          Li, Jinghua
          Pan, Jay
      su:
        Public health surveillance
        Primary health care
        COVID-19 pandemic
        Psychological resilience
        Acquisition of data
      sug:
        subj:
          Public health surveillance
          Primary health care
          COVID-19 pandemic
          Psychological resilience
          Acquisition of data
      ab: We analyzed COVID-19 influences on the design, implementation, and validity of assessing the quality of primary health care using unannounced standardized patients (USPs) in China. Because of the pandemic, we crowdsourced our funding, removed tuberculosis from the USP case roster, adjusted common cold and asthma cases, used hybrid online–offline training for USPs, shared USPs across provinces, and strengthened ethical considerations. With those changes, we were able to conduct fieldwork despite frequent COVID-19 interruptions. Furthermore, the USP assessment tool maintained high validity in the quality checklist (criteria), USP role fidelity, checklist completion, and physician detection of USPs. Our experiences suggest that the pandemic created not only barriers but also opportunities to innovate ways to build a resilient data collection system. To build data system reliance, we recommend harnessing the power of technology for a hybrid model of remote and in-person work, learning from the sharing economy to pool strengths and optimize resources, and dedicating individual and group leadership to problem-solving and results. (Am J Public Health. 2022;112(6):913–922. https://doi.org/10.2105/AJPH.2022.306779)
      pubtype: Academic Journal
      doctype: Article
      src: R
    language: English
    refInfo:
    copyright:
      @attributes:
        flag: N
    holdings:
      @attributes:
        islocal: N