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Health Information Management:

Concepts, Principles, and Practice

Chapter 5: Data and Information Management

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From Data to Information

• Data = raw facts stored as characters, words, symbols, measurements, statistics

• Information = processed data• Knowledge = information combined with experience

and context

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Knowledge

• Two types of knowledgeo Explicit

• Easily communicated and storedo Procedure manuals, clinical guidelines

o Tacit• Not easily communicated or stored

o Employee knowledge and experience

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Joint Commission IM Model

• Managing information is an active, planned activity

• Four types of informationo Patient specificoAggregateo ComparativeoKnowledge-based

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Joint Commission IM Model

• Needs assessment

• Planning and designing

• Capturing and reporting

• Processing and analyzing

• Storing and retrieving

• Disseminated and displayed

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Basic Principles of Information Management

• Information managemento Treat information as an essential organizational resourceo Obtain top executive support for IS planning and

managemento Develop an IS strategic vision and plan

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Basic Principles of Information Management (continued)

• Health information management planningo 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.

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MRI Health Care Documentation

• Information Capture

• Report Generation

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Data Quality Standards

• MRI Principles of Health Care Documentation

• AHIMA Data Quality Model

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AHIMA Characteristics of Data Quality• Characteristics of data quality

o Accuracyo Accessibilityo Comprehensivenesso Consistencyo Currencyo Definitiono Granularityo Precisiono Relevancyo Timeliness

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Database Design and Management

• Database life cycle (DBLC)o Initial studyo Designo Implementationo Testing and evaluationo Operationo Maintenance and evaluation

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Database Design and Management

• Types of databaseso Relationalo Object-oriented

• Advantages of relational databaseso Structural independenceo Conceptual simplicityo Ease of design, implementation, management, and useo Ad hoc query capabilityo Powerful database management system

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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

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Database Design and Management

• Levels of data modelso Conceptual data modelo Logical data model: entity relationship diagram

(ERD), unified modeling language (UML)o Physical data model

• Entity relationship diagramo Entityo Attributeso Relationships: one to one, one to many, many to

many

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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 dictionarieso DBMS data dictionaryo Organization-wide data dictionary

• Development of data dictionarieso Define the scope of the projecto Determine the makeup of the project teamo Set prioritieso Learn from the experience of others

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Quality Management Roles

• Database administrator • Data administrator• Data resource manager• Data Analyst

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Data Integrity

• Data integrity: assurance that data have only been accessed or modified by individuals authorized to do so

• Data integrity constraintso Data typeo Legal valueso Data formato Key constraints

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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

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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.

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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

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Optimize PowerPoint

• Strategies to optimize the impact of a PowerPoint presentationo Align PowerPoint with the way the brain works – use both

visual and verbal channelso Segment your story into biteso Make clear to your viewer the location and direction of the

presentationo Use visuals to persuadeo Purge all but essential text and audiovisual effectso Dice and sequence complex visuals