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

Crossover Experiments01:16

Crossover Experiments

Crossover experiments, also called the repeated-measurements design, is a study design in which all experimental units are exposed to all treatments in different periods. Crossover experiments are generally used in psychology, the pharmaceutical industry, agriculture, and medicine.
Crossover designs are performed even with smaller sample sizes since the samples can act as their controls. These are better than simple randomized trials since patients are exposed to all the treatments.
Bioequivalence Experimental Study Designs: Repeated Measures, Cross-Over, Carry-Over, and Latin Square Designs01:15

Bioequivalence Experimental Study Designs: Repeated Measures, Cross-Over, Carry-Over, and Latin Square Designs

Bioequivalence experimental study designs play a pivotal role in testing the effectiveness of various treatments. Key among these are the repeated measures, cross-over, carry-over, and Latin square designs. In the repeated measures design, each subject receives all treatments, allowing for temporal comparisons. This type of design is useful in reducing variability but requires careful planning to avoid bias.The cross-over design, an economical method, involves sequential administration of...
Bioavailability Study Design: Single Versus Multiple Dose Studies01:11

Bioavailability Study Design: Single Versus Multiple Dose Studies

Bioavailability studies are essential for understanding how a drug is absorbed, distributed, metabolized, and excreted in the body. These studies assess the extent and rate at which the active pharmaceutical agent becomes available at the site of action. The design of bioavailability studies can involve single-dose or multiple-dose regimens, each with distinct advantages and limitations.Single-dose studies are the preferred approach due to their simplicity and reduced drug exposure for...
Study Design in Statistics01:15

Study Design in Statistics

A study design is a set of techniques that allow a researcher to collect and analyze data from different variables defined for a specific research problem. Statistics is commonly for effective study design and more robust experiments,
Does aspirin reduce the risk of heart attacks? Is one brand of fertilizer more effective at growing roses than another? Is fatigue as dangerous to a driver as the influence of alcohol? Questions like these are answered using randomized experiments with proper...
Bioavailability Study Design: Healthy Subjects Versus Patients01:15

Bioavailability Study Design: Healthy Subjects Versus Patients

Bioavailability studies are essential for evaluating a drug's therapeutic efficacy and understanding its absorption patterns under various physiological conditions. Conducting such studies on target patient populations provides more relevant data by simulating real-world disease states. However, practical challenges often necessitate the use of young, healthy adult volunteers as study subjects.Patients may exhibit altered drug absorption patterns due to the effects of the disease itself,...
Study Designs in Epidemiology01:20

Study Designs in Epidemiology

Epidemiological study designs are fundamental tools for investigating the distribution, determinants, and control of health conditions in populations. They help researchers understand the relationships between exposures and outcomes, and they broadly fall into two categories: "observational" and "experimental" studies.
Observational studies are those where the researcher does not intervene but rather observes natural variations. They include cross-sectional, cohort, and case-control studies.

You might also read

Related Articles

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

Sort by
Same author

Evaluation of structured training in osteotomy and splitting for BSSO using a 3D-printed mandibular model.

BMC medical education·2026
Same author

KlimaNot-Effects of Climate Change on Emergency and Acute Care: Protocol for a Multicenter, Registry-Based Observational Cohort Study.

JMIR research protocols·2026
Same author

What determines the success of AI voice-cloned speech? Prosodic and acoustic evidence on three TTS systems.

Phonetica·2026
Same author

Early but not late time-restricted eating improves an actigraphy-estimated sleep quality in women with overweight or obesity: secondary analysis of the crossover ChronoFast trial.

Frontiers in nutrition·2026
Same author

Extending Interoperable Emergency Department Data: Standards-Based Design and Evaluation in AKTIN.

Studies in health technology and informatics·2026
Same author

From Fragmentation to Transparency: Exploring and Mapping the Landscape of Medical Registries in Germany.

Studies in health technology and informatics·2026

Related Experiment Videos

Small cause - big effect: improvement in interface design results in improved data quality - a multicenter crossover

Janko Ahlbrandt1, Michael Henrich, Bernd A Hartmann

  • 1Justus-Liebig-University Giessen, Giessen, Germany.

Studies in Health Technology and Informatics
|August 10, 2012
PubMed
Summary

Improving anesthesia documentation quality is crucial for patient safety. Small graphical user interface (GUI) enhancements significantly boosted correctly documented anesthesia tracers from 42% to 65% in a German study.

Related Experiment Videos

Area of Science:

  • Medical Informatics
  • Health Services Research
  • Quality Improvement

Background:

  • The introduction of the core data set for anesthesia version 3.0 in Germany aimed to enhance external quality assurance.
  • Initial documentation rates for surgical tracer procedures were found to be low when compared to separate procedure data (OPS-Codes).
  • The graphical user interface (GUI) of the documentation software was identified as a barrier, contravening dialogue principles (EN ISO 9241-110).

Purpose of the Study:

  • To assess the impact of GUI improvements on the accuracy of anesthesia documentation.
  • To evaluate the effectiveness of software modifications in a real-world clinical setting.
  • To investigate the relationship between GUI usability and data quality in clinical documentation systems.

Main Methods:

  • A crossover study was conducted across a university hospital and a municipal hospital chain (five hospitals).
  • Small, usability-focused improvements were made to the GUI in collaboration with the software manufacturer.
  • Data from 34,610 anesthesia procedures were analyzed before and after software implementation.

Main Results:

  • Correctly documented anesthesia tracers significantly improved from 42% to 65% (p<0.001) across all study sites and procedures.
  • Improvements were observed for most surgical tracer procedures at all participating hospitals.
  • The study demonstrated a substantial positive effect of minor GUI changes on data quality.

Conclusions:

  • Minor GUI modifications can significantly enhance the quality of clinical documentation and data accuracy.
  • The study raises questions about the suitability of highly flexible, parameterized systems for achieving optimal usability.
  • Future research should focus on balancing expert-designed GUIs with administrative flexibility in clinical documentation systems.