Roadmap Step 3: Storing and refining data
Storing and refining data in healthcare organizations
How should we clean and organize our data? What is data modelling? How can we use data analytics in our hospital? How do we ensure data quality?
Data Quality Assurance (DQA)
Meaningful analysis of health facility data requires insights into the quality of the data; yet the quality of Routine Health Information Systems (RHIS) data is an ongoing challenge in many contexts. It is why, WHO has produced the Data Quality Assurance (DQA) toolkit.
Download the toolkit
Statistical process in healthcare
In this recorded webinar, YEL alumni discuss statistical processes in their healthcare organizations. Find out more about using control charts to make decisions and management protocols in this webinar.
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How to build an effective healthcare data analytics program in hospitals
Watch colleagues from our sponsor Vizient discussing how to build an effective clinical analytics program that identifies areas for performance improvement to help deliver quality patient care, lower hospital costs and inform supply chain decisions.
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Enhancing systemwide quality control
Read how Vizient has supported Novant Health to unify its health data from disparate data silos. Novant Health has standardized safety and quality control rankings across its medical system.
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Making data count
NHS England and NHS Improvement show how statistical process control is supporting NHS staff to better analyse data. Take a look at this guide, along with real life examples of how Trusts are using data most effectively.
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Do you manage your organization with reliable data?
Don't miss out on this blog from Pia Seppänen, Development Manager at Wellbeing Services County of Pirkanmaa, Finland. She addresses questions such as "What can we do to strengthen the production of reliable data in our organizations?" and shares insights about decision making in healthcare organizations and the importance of producing reliable data.
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