Hm306 week 2

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A Practical Approach to Analyzing
Healthcare Data
Chapter 3 – Tools for Data
Organization, Analysis, and
Presentation

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Data Organization Using
Databases
• Healthcare data is complex and often multi-
dimensional
– Provider
– Patients
– Insurance companies
– Services
• Providing an organizational structure for the data can
facilitate more efficient analysis and reporting
• Database – self-describing collection of integrated
records.
– Self-describing – contains a description of its own structure
– Integrated – data elements are related to each other

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Database Vocabulary
• Tables- two dimensional arrays of data
– Rows = records
– Columns = variables or attributes
• RDMS – Relational Database Management System
– Software that is used to hold and maintain data tables and
their relationships
• SQL – Structured Query Language
– Programming language used to communicate with a
relational database
• ERD – Entity Relationship Diagram
– Diagram that shows how tables in an RDMS relate

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Small-Scale Databases
• Microsoft Access
– Relational database management system (RDMS)
– Strengths
• Approachable for inexperienced database users
• Graphical user interface (GUI)
• Built in wizards for table, query and report design
• Supports integrated forms for data collection
– Weaknesses
• Multi-user support is difficult to implement
• Database size limited to 2GB
• Most ‘classic’ Database Administrators (DBAs) do not
consider Access to be a full blown RDMS

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Hierarchy of a Relational Database
• Tables are rows and columns of values
– Envision a tab in a spreadsheet
• Fields are the columns in a spreadsheet
– In a patient database, fields may be age, gender, admission date, etc.
• Data elements or records are the rows in a spreadsheet
– In a patient database, row may represent patients or services provided to patients
• A unique row identifier in a table is called the primary key
– Cannot be duplicated within the same table
– Used to link tables together

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Entity Relationship Diagram
• Diagram that displays the relationships between tables within a RDBMS
• The key fields are identified as well as the cardinality of the relationship between the
tables
• Cardinality
– One – to – one
– One – to – many
• In Figure A.1
– PatientID is the primary key in the Patient Info table and a secondary key in the Visits table
– The cardinality of the relationship between the table is one to many.
• Each patient may have many visits

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More About Cardinality

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Data Dictionary
• Details roadmap of the database
• Should include
– Name of computer or software program that
contains the data element
– Type of data in the field
– Length of data in the field
– Edits placed on the data field
– Values allowed to be placed in the data field
– A clear definition of each value

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Structured Query Language
• SQL
• Tool to use and maintain databases
– Select data
– Update data
– Insert rows into a table
– Delete rows from a table

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SQL Example
• Retrieve the records for all patients
from Milwaukee
– SELECT PATIENT_LNAME,
PATIENT_FNAME FROM PATIENT
WHERE PATIENT_CITY = ‘Milwaukee’
• Key words in the query are in red font

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Statistical Software Packages
• Statistical Package for the Social Sciences
(SPSS)
– Menu driven program
– More suited for smaller (<1G) datasets
– May open Excel files for analysis
• Statistical Analysis System (SAS)
– Command line program
– Excellent for manipulating large datasets

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SAS Syntax
• SAS is a programming language much like
SQL
– Key words:
• Data – used to name and create a dataset
• Proc – declare which analytic procedure will be used
• Set – declare which dataset will be the subject of the
analysis
• Run – designates the end of the command and starts
the calculation
– Syntax: always end commands with a ‘;’

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Role of Excel – Data Analysis
• Data analysis
– Data analysis toolpak add-in
– Must be careful importing text data elements
that appear to be numeric
• ICD-9 codes with leading zeroes
• Variables with mixed number and alpha values
• Pivot tables are also an excellent
exploratory data analysis tool

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Graphical Displays of Data
• Types of graphical comparisons
– Group summary
– Trends or changes over time
– Relative size of groups
– Relationships between variables

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Bar Graph or Chart
• Group summary
• Comparison of counts or averages across
groups
• Two variables: admissions, age category.
– One bar for each gender

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Line Graphs or Chart
• Trends or changes over time
• Look for trends/patterns
• Should not be used for connecting unrelated points

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Pie Chart
• Compares relative size of groups
• Used to represent relative proportions of a total
• Note that this is different than a bar chart – in a pie
chart categories must be part of a bigger set or
population

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Scatter Diagrams
• Used to display the relationship between two
continuous variables
• Should not be used if either variable is categorical

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Infographics
• Conveys a message or story using a
combination of graphs and text
• Primary types:
– Cause and effect
– Chronological
– Quantitative
– Directional
– Product

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Tables versus Graphs
• Tables have several advantages over graphs such
as:
– Present more information than a graph
– Display the exact values
– Require less work to create
• Graphs also have advantages over tables such as:
– Catch the attention of the reader
– Show trends easily
– Bring out facts or relationships that stimulate thinking