Related Experiment Video

Updated: Jan 6, 2026

Performing Data Mining And Integrative Analysis Of Biomarker in Breast Cancer Using Multiple Publicly Accessible Databases
07:41

Performing Data Mining And Integrative Analysis Of Biomarker in Breast Cancer Using Multiple Publicly Accessible Databases

Published on: May 17, 2019

9.4K

Identifying Patterns and Meanings Across the AANA Foundation Closed Claim Dataset Using Thematic Analysis Methods

Mary Golinski1

  • 1is an assistant professor in the School of Nursing at Oakland University in Rochester, Michigan. She also is the assistant program director for the Oakland University-Beaumont Graduate Program of Nurse Anesthesia. Dr Golinski practices clinical anesthesia at Detroit Receiving Hospital, the level 1 trauma center of the Detroit Medical Center, Detroit, Michigan. She has been a member of the AANA Foundation Closed Claim Research Team since its inception in 1995.

AANA Journal
|October 2, 2019
PubMed

Keywords:
Adverse eventsclosed claimsnurse anesthesiapatient safetythematic analysis

More Related Videos

Identification of Disease-related Spatial Covariance Patterns using Neuroimaging Data14:27

Identification of Disease-related Spatial Covariance Patterns using Neuroimaging Data

Published on: June 26, 2013

16.1K
Basics of Multivariate Analysis in Neuroimaging Data06:35

Basics of Multivariate Analysis in Neuroimaging Data

Published on: July 24, 2010

17.3K

Related Concept Videos

Statistical Methods to Analyze Parametric Data: ANOVA01:12

Statistical Methods to Analyze Parametric Data: ANOVA

Analysis of Variance, or ANOVA, is a powerful statistical technique used to analyze parametric data, primarily in research and experimental studies. It's designed to compare the means of two or more groups, assisting researchers in identifying any significant differences between these group means. There are two main types of ANOVA based on the complexity of the analysis: one-way and two-way.
One-way ANOVA is applied when a single independent variable or factor is scrutinized. It compares...
1.5K
Statistical Analysis: Overview01:11

Statistical Analysis: Overview

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...
14.0K
Methods of Documentation IV: Focus Charting01:26

Methods of Documentation IV: Focus Charting

Focus Charting, also known as the focus charting system or "focus documentation," is a systematic documentation approach used in healthcare to organize patient information in medical records.
It typically involves three columns for recording information:
1.6K
One-Way ANOVA01:18

One-Way ANOVA

One-way ANOVA analyzes more than three samples categorized by one factor. For example, it can compare the average mileage of sports bikes. Here, the data is categorized by one factor - the company. However, one-way ANOVA cannot be used to simultaneously compare the sample mean of three or more samples categorized by two factors. An example of two factors would be sports bikes from different companies driven in different terrains, such as a desert or snowy landscape. Here, two-way ANOVA is used...
11.8K
Two-Way ANOVA01:17

Two-Way ANOVA

The two-way ANOVA is an extension of the one-way ANOVA. It is a statistical test performed on three or more samples categorized by two factors - a row factor and a column factor. Ronald Fischer mentioned it in 1925 in his book 'Statistical Methods for Researchers.'
The two-way ANOVA analysis initially begins by stating the null hypothesis that there is an interaction effect between the two factors of a dataset. This effect can be visualized using line segments formed by joining the...
3.3K
Cancer Survival Analysis01:21

Cancer Survival Analysis

Cancer survival analysis focuses on quantifying and interpreting the time from a key starting point, such as diagnosis or the initiation of treatment, to a specific endpoint, such as remission or death. This analysis provides critical insights into treatment effectiveness and factors that influence patient outcomes, helping to shape clinical decisions and guide prognostic evaluations. A cornerstone of oncology research, survival analysis tackles the challenges of skewed, non-normally...
624