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

Simple statistical measures for analyzing categorical data.

C G Humble1

  • 1Department of Veterans Affairs Medical Center, Durham, NC.

Journal for Healthcare Quality : Official Publication of the National Association for Healthcare Quality
|August 6, 1994
PubMed
Summary
This summary is machine-generated.

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

From hard copy to computer integration: developing clinical indicators for quality improvement.

Journal for healthcare quality : official publication of the National Association for Healthcare Quality·1997
Same author

Dietary fiber and cardiovascular disease: a reply.

American journal of preventive medicine·1994
Same author

Dietary fiber and coronary heart disease in middle-aged hypercholesterolemic men.

American journal of preventive medicine·1993
Same author

Oats and cholesterol: the prospects for prevention of heart disease.

American journal of public health·1991
Same author

Cancer treatment protocols. Who gets chosen?

Archives of internal medicine·1988
Same author

Cigarette smoking and lung cancer in New Mexico.

The American review of respiratory disease·1988

Healthcare quality studies often track patient procedure or outcome rates. Run charts offer a nonstatistical approach, while simple epidemiological methods and the chi-square test enable statistical comparisons over time and between groups.

Area of Science:

  • Healthcare Quality Improvement
  • Epidemiology
  • Biostatistics

Background:

  • Assessing healthcare quality frequently involves monitoring patient procedure or health outcome proportions.
  • Evaluating changes in these rates over time is crucial for quality assessment.

Purpose of the Study:

  • To explain run charts as a nonstatistical method for evaluating changes in rates.
  • To present simple epidemiological methods and the chi-square test for statistically comparing rates between groups and time periods.
  • To discuss practical aspects and interpretation of these statistical methods with realistic examples.

Main Methods:

  • Utilizing run charts for nonstatistical trend evaluation.
  • Applying simple epidemiological methods for two-group rate comparisons.

Related Experiment Videos

  • Employing the chi-square test to determine the statistical significance of rate differences.

    • Main Results:

    • Run charts provide a visual, nonstatistical means to assess changes in healthcare rates.
    • Epidemiological methods and the chi-square test allow for statistically valid comparisons of rates between different groups or time points.
    • The article illustrates the practical application and interpretation of these statistical tools.

    Conclusions:

    • Both nonstatistical (run charts) and statistical (chi-square test) methods are valuable for analyzing healthcare quality data.
    • Understanding these methods aids in the effective evaluation of patient outcomes and procedure rates.
    • Practical guidance and examples are provided for implementing these analyses, with a supplementary spreadsheet available.