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A Practical Guide to Performance Improvement: Data Collection and Analysis
Author(s) -
Dawson Anthony
Publication year - 2019
Publication title -
aorn journal
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.222
H-Index - 43
eISSN - 1878-0369
pISSN - 0001-2092
DOI - 10.1002/aorn.12673
Subject(s) - data collection , computer science , process (computing) , outcome (game theory) , data science , process management , engineering , statistics , operating system , mathematics , mathematical economics
This article discusses performance improvement ( PI ) data collection processes and the various tools that can be used to analyze and display data through the duration of a PI project. It describes the importance of data, how to determine the required amount of data, how to collect and analyze data, and in what format data should be presented. Personnel involved with PI projects may need to use various data collection methods and tools to ensure an effective project with a successful outcome. This article includes examples of how PI project team members can implement various data collection and analysis tools. After reviewing this article, the reader should have a better understanding of this part of the PI process.