Welcome to the Library Research & QI Center
Analyze Data & Prepare Findings page
When analyzing data is is important to be aware of and avoid bias.
How to Avoid Bias in Scientific Test - Stile Education, Dec. 7, 2020.
Recommend: turn cc on if you can't use sound.
Surveys are susceptible to data collection errors and bias as well.
Proper data collection begins at the project design phase. Good project design can help avoid common data errors in sample, selection, size, response rate and other factors that will ultimately affect the quality of the research and results you produce.
Common data collection errors (bias):
Selection of proper data collection and analysis tools can also aid in effective outcomes. Some of the resources available for HonorHealth researchers (contact your program director for more information):
The Analytic Services team provides reporting, visualization, management, and governance of data that supports, but is not limited to, operations, clinical care, patient experience, quality improvement, and patient safety activities. The team also extracts and manages data from a variety of sources but primarily the Epic Clarity database, Epic Caboodle data warehouse, and Midas database.