1. © 2010 Health Information Management: Concepts, Principles, and Practice Chapter 5: Data and Information Management

2. © 2010 From Data to Information Data = raw facts stored as characters, words, symbols, measurements, statistics Information = processed data Knowledge = information combined with experience and context

3. © 2010 Knowledge Two types of knowledge o Explicit Easily communicated and stored o Procedure manuals, clinical guidelines o Tacit Not easily communicated or stored o Employee knowledge and experience

4. © 2010 Joint Commission IM Model Managing information is an active, planned activity Four types of information o Patient specific o Aggregate o Comparative o Knowledge-based

5. © 2010 Joint Commission IM Model Needs assessment Planning and designing Capturing and reporting Processing and analyzing Storing and retrieving Disseminated and displayed

6. © 2010 Basic Principles of Information Management Information management o Treat information as an essential organizational resource o Obtain top executive support for IS planning and management o Develop an IS strategic vision and plan

7. © 2010 Basic Principles of Information Management (continued) Health information management planning o The value of information lies in its application to decision making within the organization. o Quality data are the foundation of quality information. o Integration of systems enhances IS quality and efficiency. o Information users must be involved in defining needs and designing information systems.

8. © 2010 MRI Health Care Documentation Information Capture Report Generation

9. © 2010 Data Quality Standards MRI Principles of Health Care Documentation AHIMA Data Quality Model

10. © 2010 AHIMA Characteristics of Data Quality Characteristics of data quality o Accuracy o Accessibility o Comprehensiveness o Consistency o Currency o Definition o Granularity o Precision o Relevancy o Timeliness

11. © 2010 Database Design and Management Database life cycle (DBLC) o Initial study o Design o Implementation o Testing and evaluation o Operation o Maintenance and evaluation

12. © 2010 Database Design and Management Types of databases o Relational o Object-oriented Advantages of relational databases o Structural independence o Conceptual simplicity o Ease of design, implementation, management, and use o Ad hoc query capability o Powerful database management system

13. © 2010 Database Design and Management Object-oriented databases: more applications in the future Data models: link between “real” things about which data/information are to be collected and maintained and the actual database structure

14. © 2010 Database Design and Management Levels of data models o Conceptual data model o Logical data model: entity relationship diagram (ERD), unified modeling language (UML) o Physical data model Entity relationship diagram o Entity o Attributes o Relationships: one to one, one to many, many to many

15. © 2010 Data Dictionaries Data dictionary: a descriptive list of the data elements to be collected in an information system or database, the purpose of which is to ensure consistency of usage Types of data dictionaries o DBMS data dictionary o Organization-wide data dictionary Development of data dictionaries o Define the scope of the project o Determine the makeup of the project team o Set priorities o Learn from the experience of others

16. © 2010 Quality Management Roles Database administrator Data administrator Data resource manager Data Analyst

17. © 2010 Data Integrity Data integrity: assurance that data have only been accessed or modified by individuals authorized to do so Data integrity constraints o Data type o Legal values o Data format o Key constraints

18. © 2010 Data Security Authorization management: protecting the security and privacy of the data in a database –User access control –Usage monitoring User access control –Defines each user of the database –Defines user groups –Assigns access privileges User monitoring: audit trails

19. © 2010 Data Display and Presentation Ideal Graphs… (Tufte, 2001) –show the data. –induce the viewer to think about the substance rather than the methodology, graphic design, the technology, or other things. –avoid distorting what the data have to say. –present many numbers in a small space. –make large data sets coherent. –encourage the eye to compare different pieces of data. –reveal the data at several levels of detail. –serve a reasonably clear purpose. –are closely integrated with the statistical and verbal descriptions of the data set.

20. © 2010 Data Display and Presentation Steps to follow for designing and giving presentations (Mills, 2007) –Define your purpose –Profile your audience –Map your structure –Add drama and impact –Rehearse until perfect –Deliver with style –Review and revise

21. © 2010 Optimize PowerPoint Strategies to optimize the impact of a PowerPoint presentation o Align PowerPoint with the way the brain works – use both visual and verbal channels o Segment your story into bites o Make clear to your viewer the location and direction of the presentation o Use visuals to persuade o Purge all but essential text and audiovisual effects o Dice and sequence complex visuals