1. Copyright ©2009 by Pearson Education, Inc. Upper Saddle River, New Jersey 07458 All rights reserved. Handbook of Informatics for Nurses and Healthcare Professionals, Fourth Edition Toni Lee Hebda and Patricia Czar Lec 3 361

2. Copyright ©2009 by Pearson Education, Inc. Upper Saddle River, New Jersey 07458 All rights reserved. Handbook of Informatics for Nurses and Healthcare Professionals, Fourth Edition Toni Lee Hebda and Patricia Czar Key Concepts Data: Building blocks in the formation of knowledge Data integrity: Ability to collect, store, and retrieve correct, complete, current data so it will be available to authorized users when needed Faulty or incomplete data gives rise to poor quality information and poor decisions

3. Copyright ©2009 by Pearson Education, Inc. Upper Saddle River, New Jersey 07458 All rights reserved. Handbook of Informatics for Nurses and Healthcare Professionals, Fourth Edition Toni Lee Hebda and Patricia Czar Ensuring Correct Data Collection and Entry Input errors decrease data quality ↓ input errors –Educate staff –System checks –Data verification

4. Copyright ©2009 by Pearson Education, Inc. Upper Saddle River, New Jersey 07458 All rights reserved. Handbook of Informatics for Nurses and Healthcare Professionals, Fourth Edition Toni Lee Hebda and Patricia Czar Educate Staff Staff who understand proper use of system and the significance of poor quality data make fewer errors

5. Copyright ©2009 by Pearson Education, Inc. Upper Saddle River, New Jersey 07458 All rights reserved. Handbook of Informatics for Nurses and Healthcare Professionals, Fourth Edition Toni Lee Hebda and Patricia Czar System Checks Mechanism provided by the computer system to prompt users to complete a task, verify information: – Data cleansing software at point of entry – Forcing users to complete “required” fields to progress – Alerting users of duplicate entries – Generating reports of actions that have not been completed

6. Copyright ©2009 by Pearson Education, Inc. Upper Saddle River, New Jersey 07458 All rights reserved. Handbook of Informatics for Nurses and Healthcare Professionals, Fourth Edition Toni Lee Hebda and Patricia Czar Data Verification Client verification that data is accurate –Verbally –On screen review –Printout review

7. Copyright ©2009 by Pearson Education, Inc. Upper Saddle River, New Jersey 07458 All rights reserved. Handbook of Informatics for Nurses and Healthcare Professionals, Fourth Edition Toni Lee Hebda and Patricia Czar Data Management Process of controlling the collection, storage, retrieval, and use of data to optimize accuracy and utility while safeguarding integrity Also known as business intelligence (BI)

8. Copyright ©2009 by Pearson Education, Inc. Upper Saddle River, New Jersey 07458 All rights reserved. Handbook of Informatics for Nurses and Healthcare Professionals, Fourth Edition Toni Lee Hebda and Patricia Czar Data Management Levels Entry level System analysts Programmers Database administrator (DBA)

9. Copyright ©2009 by Pearson Education, Inc. Upper Saddle River, New Jersey 07458 All rights reserved. Handbook of Informatics for Nurses and Healthcare Professionals, Fourth Edition Toni Lee Hebda and Patricia Czar Data Warehouse Repository for storing data from several different databases so that it can be combined and manipulated to provide answers to complex analytic questions

10. Copyright ©2009 by Pearson Education, Inc. Upper Saddle River, New Jersey 07458 All rights reserved. Handbook of Informatics for Nurses and Healthcare Professionals, Fourth Edition Toni Lee Hebda and Patricia Czar Data Storage Online storage –Provides access to current data –Rapid, using high-speed hard disk drives or storage space on the network Offline storage –For data that are needed less frequently, or for long-term data storage of old client records –Can be done on any secondary storage device

11. Copyright ©2009 by Pearson Education, Inc. Upper Saddle River, New Jersey 07458 All rights reserved. Handbook of Informatics for Nurses and Healthcare Professionals, Fourth Edition Toni Lee Hebda and Patricia Czar Data Retrieval Process that allows the user to access previously collected, stored data

12. Copyright ©2009 by Pearson Education, Inc. Upper Saddle River, New Jersey 07458 All rights reserved. Handbook of Informatics for Nurses and Healthcare Professionals, Fourth Edition Toni Lee Hebda and Patricia Czar Data Exchange Growing expectation that information collected in one facility will be available to another

13. Copyright ©2009 by Pearson Education, Inc. Upper Saddle River, New Jersey 07458 All rights reserved. Handbook of Informatics for Nurses and Healthcare Professionals, Fourth Edition Toni Lee Hebda and Patricia Czar Data Cleansing Procedure that uses software to improve the quality of data to ensure that it is accurate enough for use in data mining and warehousing

14. Copyright ©2009 by Pearson Education, Inc. Upper Saddle River, New Jersey 07458 All rights reserved. Handbook of Informatics for Nurses and Healthcare Professionals, Fourth Edition Toni Lee Hebda and Patricia Czar Data Disposal Physical destruction –Secure disposal of documents –Shredding –Destroy storage media Software destruction –Overwrite data

15. Copyright ©2009 by Pearson Education, Inc. Upper Saddle River, New Jersey 07458 All rights reserved. Handbook of Informatics for Nurses and Healthcare Professionals, Fourth Edition Toni Lee Hebda and Patricia Czar Quality Information Timely Precise Accurate Rapidly and easily available Clear Reliable

16. Copyright ©2009 by Pearson Education, Inc. Upper Saddle River, New Jersey 07458 All rights reserved. Handbook of Informatics for Nurses and Healthcare Professionals, Fourth Edition Toni Lee Hebda and Patricia Czar Data Mining Technique that uses software to look for hidden patterns and relationships in large groups of data It is used to identify standardized treatments for specific diseases

17. Copyright ©2009 by Pearson Education, Inc. Upper Saddle River, New Jersey 07458 All rights reserved. Handbook of Informatics for Nurses and Healthcare Professionals, Fourth Edition Toni Lee Hebda and Patricia Czar The Future The adoption of standard data exchange models and increased interoperability will provide access to additional databases Data mining will become commonplace facilitating research and evidence-based practice