Understanding variation in covid-19 reported deaths with a novel Shewhart chart application
UMass Chan Affiliations
Department of Population and Quantitative Health SciencesDocument Type
Journal ArticlePublication Date
2020-06-26Keywords
Covid-19 pandemicShewhart control chart
Statistical Process Control
Statistical public reporting of healthcare data
Biostatistics
Epidemiology
Health Services Research
Infectious Disease
Statistical Methodology
Virus Diseases
Metadata
Show full item recordAbstract
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/mzaa069Permanent Link to this Item
http://hdl.handle.net/20.500.14038/27613PubMed ID
32589224Related Resources
ae974a485f413a2113503eed53cd6c53
10.1093/intqhc/mzaa069