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 Concept Videos

Quality Control01:05

Quality Control

4.0K
Quality control is one of the three cyclical quality assurance activities that help keep a system under statistical control. Typical quality control activities include creating quality control charts, conducting proficiency testing, and documenting and archiving results.
Quality control helps track data, visualize trends, and identify variations, making it easier to detect deviations that may affect the accuracy of an analysis. One way to do this is by generating a quality control chart, which...
4.0K
Ratio Level of Measurement00:54

Ratio Level of Measurement

21.9K
The way a set of data is measured is called its level of measurement. Correct statistical procedures depend on a researcher being familiar with levels of measurement. For analysis, data are classified into four levels of measurement—nominal, ordinal, interval, and ratio.
A set of data measured using the ratio scale takes care of the ratio problem and provides complete information. Ratio scale data are like interval scale data, except they have a zero point and ratios can be calculated....
21.9K
Statistical Analysis: Overview01:11

Statistical Analysis: Overview

16.7K
When we take repeated measurements on the same or replicated samples, we will observe inconsistencies in the magnitude. These inconsistencies are called errors. To categorize and characterize these results and their errors, the researcher can use statistical analysis to determine the quality of the measurements and/or suitability of the methods.
One of the most commonly used statistical quantifiers is the mean, which is the ratio between the sum of the numerical values of all results and the...
16.7K
Quality Assurance01:19

Quality Assurance

3.7K
Quality assurance is the overarching term used to describe the activities employed to ensure the proper performance of a system. These activities can be classified into three categories: quality control, quality assessment, and internal corrective measures. Typically, these activities work cyclically: quality control is performed before and during the analysis, while quality assessment occurs during and after the investigation. Internal corrective measures are implemented based on the findings...
3.7K
Ordinal Level of Measurement00:55

Ordinal Level of Measurement

35.6K
The way a set of data is measured is called its level of measurement. Correct statistical procedures depend on a researcher being familiar with levels of measurement. For analysis, data are classified into four levels of measurement—nominal, ordinal, interval, and ratio.
Data measured using an ordinal scale are similar to nominal scale data, but there is one major difference. The ordinal scale data can be ordered. An example of ordinal scale data is a list of the top five national parks...
35.6K
Nominal Level of Measurement00:56

Nominal Level of Measurement

40.6K
The way a set of data is measured is called its level of measurement. Correct statistical procedures depend on a researcher being familiar with levels of measurement. Not every statistical operation can be used with every set of data. For analysis, data are classified into four levels of measurement—nominal, ordinal, interval, and ratio.
The data that cannot be measured but can be grouped into categories fall under the nominal level of measurement. Data that is measured using a nominal...
40.6K

You might also read

Related Articles

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

Sort by
Same authorSame journal

Surgical Management of Malignant Eyelid Tumors: A Retrospective Analysis over 10 Years of Surgical Treatment in 1443 Consecutive Cases.

Klinische Monatsblatter fur Augenheilkunde·2026
Same author

Dysregulated Intraocular Pressure in Acanthamoeba Keratitis: Clinical Associations, Therapy, and Prognosis.

Microorganisms·2026
Same author

Impact of Wearing a Face Mask on the Reliability of Standard Automated Perimetry in Glaucoma Patients and Suspects: a Retrospective Longitudinal Study.

Klinische Monatsblatter fur Augenheilkunde·2026
Same author

Integration of Mechanical Testing, In Vivo Optical Coherence Elastography and Personalized Finite Element Modeling to Predict Geometrical Outcomes of Corneal Cross-Linking.

Annals of biomedical engineering·2026
Same author

Enhancing Corneal Donation Through Hospital Collaborations in Germany: A 21-Year Perspective.

Cornea·2026
Same author

Trends in 18 years of keratoplasty in Europe: insights from the European Eye Bank Association's data.

The British journal of ophthalmology·2026

Related Experiment Video

Updated: Feb 28, 2026

Assessment of Child Anthropometry in a Large Epidemiologic Study
09:36

Assessment of Child Anthropometry in a Large Epidemiologic Study

Published on: February 2, 2017

28.0K

[Measurement of Quality with Routine Data].

Stefan J Lang1, Robert Rilk2, Alida Friederike Müller2

  • 1Klinik für Augenheilkunde, Universitätsklinikum Freiburg, Medizinische Fakultät, Albert-Ludwigs-Universität Freiburg im Breisgau.

Klinische Monatsblatter Fur Augenheilkunde
|June 10, 2017
PubMed
Summary

Hospitals can measure healthcare quality using routine data and specific indicators. Implementing an electronic patient guidance system reduced waiting times in one outpatient department, demonstrating continuous quality improvement.

More Related Videos

Conducting Respiratory Oscillometry in an Outpatient Setting
14:49

Conducting Respiratory Oscillometry in an Outpatient Setting

Published on: April 8, 2022

8.7K
Simulation of a Scaled Assembly Process with Collaboration of a Robotic Arm and Monitoring through a Vision System for Quality Control
05:47

Simulation of a Scaled Assembly Process with Collaboration of a Robotic Arm and Monitoring through a Vision System for Quality Control

Published on: August 29, 2025

497

Related Experiment Videos

Last Updated: Feb 28, 2026

Assessment of Child Anthropometry in a Large Epidemiologic Study
09:36

Assessment of Child Anthropometry in a Large Epidemiologic Study

Published on: February 2, 2017

28.0K
Conducting Respiratory Oscillometry in an Outpatient Setting
14:49

Conducting Respiratory Oscillometry in an Outpatient Setting

Published on: April 8, 2022

8.7K
Simulation of a Scaled Assembly Process with Collaboration of a Robotic Arm and Monitoring through a Vision System for Quality Control
05:47

Simulation of a Scaled Assembly Process with Collaboration of a Robotic Arm and Monitoring through a Vision System for Quality Control

Published on: August 29, 2025

497

Area of Science:

  • Healthcare Management
  • Health Informatics
  • Quality Improvement

Background:

  • Growing interest in healthcare quality measurement globally.
  • Mandatory external quality assurance and internal quality management systems for German hospitals.
  • Routine data sources like ICD codes and treatment documentation offer potential for quality assessment.

Purpose of the Study:

  • To explore the use of routine data for quality measurement in healthcare.
  • To identify suitable quality indicators for interpreting routine data.
  • To assess the impact of an electronic patient guidance system on waiting times.

Main Methods:

  • Utilizing routine data, including ICD system and treatment documentation.
  • Selecting and analyzing quality indicators such as complications, surgical objectives, procedures, and waiting times.
  • Evaluating the effect of an electronic patient guidance system on outpatient waiting times.

Main Results:

  • Routine data can be used for continuous, long-term quality measurement.
  • Quality improvement measures can be easily monitored and verified.
  • Increased use of an electronic patient guidance system correlated with decreased waiting times in an outpatient setting.

Conclusions:

  • Routine data provides a feasible method for ongoing healthcare quality assessment.
  • Quality indicators derived from routine data facilitate the evaluation of interventions.
  • Electronic patient guidance systems show promise in reducing healthcare waiting times and improving efficiency.