Jove
Visualize
Contact Us
JoVE
x logofacebook logolinkedin logoyoutube logo
ABOUT JoVE
OverviewLeadershipBlogJoVE Help Center
AUTHORS
Publishing ProcessEditorial BoardScope & PoliciesPeer ReviewFAQSubmit
LIBRARIANS
TestimonialsSubscriptionsAccessResourcesLibrary Advisory BoardFAQ
RESEARCH
JoVE JournalMethods CollectionsJoVE Encyclopedia of ExperimentsArchive
EDUCATION
JoVE CoreJoVE BusinessJoVE Science EducationJoVE Lab ManualFaculty Resource CenterFaculty Site
Terms & Conditions of Use
Privacy Policy
Policies

Related Experiment Videos

Quality Improvement Feature Series Article 2: Displaying and Analyzing Quality Improvement Data.

Patrick W Brady1,2, Michael J Tchou1,2, Lilliam Ambroggio1,3

  • 1Division of Hospital Medicine, Department of Pediatrics, Cincinnati Children's Hospital Medical Center, Ohio.

Journal of the Pediatric Infectious Diseases Society
|October 18, 2017
PubMed
Summary

Related Concept Videos

You might also read

Related Articles

Articles linked to this work by shared authors, journal, and citation graph.

Sort by
Same author

Child Opportunity Index and Suicide Risk Screening Positivity in Pediatric Emergency and Urgent Care Patients Presenting Without Behavioral Health Complaints.

Pediatric emergency care·2026
Same author

Predictors of Mortality in Children Admitted With Pneumonia to a Tertiary Hospital in Ghana: A Retrospective Cohort Study.

Health science reports·2026
Same author

Putting Principles into Practice: Pediatric Trainee Experiences in Discussing and Practicing High-Value Care.

Academic pediatrics·2026
Same author

Antibody repertoire associated with clinically diverse presentations of pediatric SARS-CoV-2 infection.

Scientific reports·2026
Same author

Food insecurity and hospital resource utilization.

Journal of hospital medicine·2026
Same author

Nasogastric Hydration Utilization in Bronchiolitis, an EMO Trial Observational Substudy.

Hospital pediatrics·2026

This article explains how to best display and analyze data in quality improvement (QI) projects. It highlights the superiority of run charts over pre-post analysis for QI studies and discusses statistical process control charts.

Area of Science:

  • Healthcare Quality Improvement
  • Data Analysis in Healthcare
  • Clinical Research Methodology

Background:

  • Effective data display and analysis are crucial for successful quality improvement (QI) initiatives.
  • Traditional clinical research methods may not be optimal for the dynamic nature of QI projects.
  • Understanding the nuances of QI data analysis is essential for healthcare professionals.

Purpose of the Study:

  • To guide the optimal display and analysis of data within QI projects.
  • To differentiate QI data analysis from traditional clinical research approaches.
  • To provide practical solutions for common data challenges encountered in QI.

Main Methods:

  • Comparison of data visualization techniques, emphasizing run charts over pre-post analysis for QI.

Related Experiment Videos

  • Introduction and explanation of various statistical process control (SPC) charts relevant to QI data.
  • Discussion of strategies for addressing frequent data-related issues in QI.

    • Main Results:

    • Run charts are demonstrated as a superior method for displaying QI data over time compared to pre-post analysis.
    • Guidance is provided on selecting and utilizing appropriate SPC charts for different QI data types.
    • Practical solutions are offered for common data challenges in QI projects.

    Conclusions:

    • Time-series data visualization using run charts is recommended for QI projects.
    • Appropriate use of SPC charts enhances the analysis of QI data.
    • Addressing data challenges effectively is key to maximizing the impact of QI initiatives.