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Turning Numbers
Into Knowledge
Nate MooreMBA, CPA, FACMPE
Business Intelligence for
Medical Practices
Learning Objectives
• Describe examples of data exploration using Analysis Services
• Recognize sources of data to combine with Integration Services
• Differentiate between pulling and pushing data with Reporting Services
Business Intelligence
Business Intelligence is a set of methodologies,
processes, architectures, and technologies that
transform raw data into meaningful and useful
information used to enable more effective
strategic, tactical, and operational insights and
decision-making.
Boris Evelsonhttp://www.forrester.com/Topic+Overview+Business+Intelligence/-/E-RES39218?objectid=RES39218
Business Intelligence
Data is merely the raw material of knowledge.
New York Times
SQL Server 101
Relational database management
system from Microsoft
SQL Server 101
SQL Server 101
SQL Server 101
SQL Server 101
SQL Server 101
Learning Objective #1
Describe examples of data exploration using
Analysis Services
Analysis Services
Cubes
Measures (numbers like collection dollars or billed charges)
Dimensions (ways to categorize measures, like time, providers, and locations)
Analysis Services
Excel is a great tool
to work with cubes
Analysis Services
Pivot Table Connected to Cube
2.1 M records
Pivot Table Spreadsheet Table
500K records
Analysis Services
Pivot Table Connected to Table
Pivot Table Connected to Cube
Analysis Services
Table Cube
Pros Easier to createComplete drill down detailCan group data in Pivot Table
Easier to work with large datasetsCustom formulas (MTD, YTD) and hierarchies
Cons Much larger file sizeHarder to work with lots of data
Requires IT help to createLimited ability to drill down to detailHave to group data at cube level
Analysis Services Data Mining
Analysis Services Data Mining
Classification (discrete values)
Regression (continuous values)
Segmentation (algorithm groups)
Association (already grouped)
Sequence Analysis (future routes)
Analysis Services Data Mining
Classification (discrete values)
Will a patient show up for their appointment?
Will a patient pay their patient balance?
Will a patient respond to treatment?
Analysis Services Data Mining
Regression (continuous values)
What will a patient’s healthcare cost next year?
What will a patient’s blood pressure be?
What is the value of a new patient?
Analysis Services Data Mining
Segmentation\Clustering (algorithm groups)
Algorithm looks for patterns to define patient categories for analysis
Which patient groups are most likely to respond to a medication or a marketing program?
Analysis Services Data Mining
Association (already grouped)
Data already has a group
Look at past data to find patterns in the group (Amazon, Netflix)
Analysis Services Data Mining
Sequence Analysis (future routes)
Examine stops along a route to predict future routes
Navigation on a website
Patients receiving treatments or buying products on a schedule
Analysis Services Data Mining
Data Mining Model
Gather data
Choose a model
Randomly hold out test data (~30%)
Generate model
Evaluate model on test data
Analysis Services Data Mining
What kinds of data are already available in your PM system to
predict no shows?
Analysis Services Data Mining
Primary Insurance Zip Code
Co-Pay Day of Week
Time of Day Provider
Location No Show History
Age Gender
New vs. Established Referral Source
Days between Schedule Date and Appt Date
Analysis Services Data Mining
Decision Tree
Analysis Services Data Mining
Model Testing – Classification MatrixActual
Predicted No Show Show Total
No Show 26 23 49
Show 5,824 103,498 109,322
Total 5,850 103,521 109,371
Accurate 103,524 94.7%
Not Accurate 5,847 5.3%
Total 109,371 100.0%
Analysis Services Data Mining
Forecasts
vs.
Predictive Analytics
Analysis Services Data Mining
Predictive Analytics
Technology that learns from experience (data) to predict the future behavior of individuals in order to drive better decisions.
Eric SiegelPredictive Analytics: The Power to Predict
Who Will Click, Buy, Lie, or Die
Analysis Services Data Mining
Target using unscented lotion
and Predictive Analytics
to Predict Pregnancy
Analysis Services Data Mining
PA vs. Facts
PA vs. Changing Workflow to get Facts
Predicting the Past
Learning Objective #2
Recognize sources of data to combine with
Integration Services
Integration Services
Control Flow
Integration Services
Data Flow
Integration Services
Integration Services
Data Sources
Data Destinations
Integration Services
Control Flow Tasks
Integration Services
Data Flow Tasks
Integration Services
Use SSIS to get data into SQL Server to
take advantage of:
SSAS (cubes and date mining) and
SSRS (email and web pages)
Integration Services
PM and EHR data
Eligibility and Benefits data
Combine multiple PM systems
Learning Objective #3
Differentiate between pulling and pushing datawith Reporting Services
Reporting Services
Reporting Services
Tools to add features to SSRS web pages and
Reporting Services
Alertsvs
“Wait and Wade”
Reporting Services
Reporting Services
Reporting Services
Reporting Services
Reporting Services
You can use the same report on a webpage (pull)
or in an alert email (push) with Reporting Services
Learning Objectives
Those who do not learn from the past are condemned to repeat it.
George Santayana
Learning Objectives
• Describe examples of data exploration using Analysis Services
• Recognize sources of data to combine with Integration Services
• Differentiate between pulling and pushing data with Reporting Services
Next Steps
Understand your data with Pivot Tables
Get more data with cubes/SSIS
Alerts and web pages with SSRS
Data Mining and Predictive Analytics
Next Steps
Watch Excel Videos
Pivot Tables (Videos 1-29 and 280-330)mooresolutionsinc.com/videos.php
MGMA Connexion article on
Pivot Tablesmooresolutionsinc.com/articles.php
Join Excel UsersMGMA Community
• Login to www.mgma.com• Go to My Profile, then click on My
Subscriptions from the submenu• Choose your delivery preferences for the
communities you wish to join• Direct link
http://community.mgma.com/MGMA/MGMA/MyProfile/MySubscriptions/Default.aspx
• Excel Users is in alphabetical order
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