Title

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

UMMS Affiliation

Department of Population and Quantitative Health Sciences

Publication Date

2020-06-26

Document Type

Article

Disciplines

Biostatistics | Epidemiology | Health Services Research | Infectious Disease | Statistical Methodology | Virus Diseases

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.

Keywords

Covid-19 pandemic, Shewhart control chart, Statistical Process Control, Statistical public reporting of healthcare data

DOI of Published Version

10.1093/intqhc/mzaa069

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

Journal/Book/Conference Title

International journal for quality in health care : journal of the International Society for Quality in Health Care

Related Resources

Link to Article in PubMed

PubMed ID

32589224

Link to Full Text

Share

COinS