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    Understanding variation in covid-19 reported deaths with a novel Shewhart chart application

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    Authors
    Perla, Rocco J.
    Provost, Shannon M.
    Parry, Gareth J.
    Little, Kevin
    Provost, Lloyd P.
    UMass Chan Affiliations
    Department of Population and Quantitative Health Sciences
    Document Type
    Journal Article
    Publication Date
    2020-06-26
    Keywords
    Covid-19 pandemic
    Shewhart control chart
    Statistical Process Control
    Statistical public reporting of healthcare data
    Biostatistics
    Epidemiology
    Health Services Research
    Infectious Disease
    Statistical Methodology
    Virus Diseases
    
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    Link to Full Text
    https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7337871/
    Abstract
    OBJECTIVE: Motivated by the covid-19 pandemic, we developed a novel Shewhart chart to visualize and learn from variation in reported deaths in an epidemic. CONTEXT: Without a method to understand if day-to-day variation in outcomes may be attributed to meaningful signals of change-rather than variability we would expect-care providers, improvement leaders, policy-makers, and the public will struggle to recognize if epidemic conditions are improving. METHODS: We developed a novel hybrid C-Chart and I-Chart to detect within a geographic area the start and end of exponential growth in reported deaths. Reported deaths were the unit of analysis owing to erratic reporting of cases from variability in local testing strategies. We used simulation and case studies to assess chart performance and define technical parameters. This approach also applies to other critical measures related to a pandemic when high-quality data are available. CONCLUSIONS: The hybrid chart detected the start of exponential growth and identified early signals that the growth phase was ending. During a pandemic, timely reliable signals that an epidemic is waxing or waning may have mortal implications. This novel chart offers a practical tool, accessible to system leaders and front-line teams, to visualize and learn from daily reported deaths during an epidemic. Without Shewhart charts and, more broadly, a theory of variation in our epidemiological arsenal, we lack a scientific method for real-time assessment of local conditions. Shewhart charts should become a standard method for learning from data in the context of a pandemic or epidemic.
    Source

    Perla RJ, Provost SM, Parry GJ, Little K, Provost LP. Understanding variation in covid-19 reported deaths with a novel Shewhart chart application. Int J Qual Health Care. 2020 Jun 26:mzaa069. doi: 10.1093/intqhc/mzaa069. Epub ahead of print. PMID: 32589224. Link to article on publisher's site

    DOI
    10.1093/intqhc/mzaa069
    Permanent Link to this Item
    http://hdl.handle.net/20.500.14038/27613
    PubMed ID
    32589224
    Related Resources

    Link to Article in PubMed

    ae974a485f413a2113503eed53cd6c53
    10.1093/intqhc/mzaa069
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    COVID-19 Publications by UMass Chan Authors
    Population and Quantitative Health Sciences Publications

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