Turning Numbers Into Knowledge Nate Moore MBA, 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 Evelson

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

Learning Objective #1 Describe examples of data exploration using 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 TableCube ProsEasier to create Complete drill down detail Can group data in Pivot Table Easier to work with large datasets Custom formulas (MTD, YTD) and hierarchies ConsMuch larger file size Harder to work with lots of data Requires IT help to create Limited ability to drill down to detail Have to group data at cube level

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 InsuranceZip Code Co-PayDay of Week Time of DayProvider LocationNo Show History AgeGender New vs. EstablishedReferral Source Days between Schedule Date and Appt Date

Analysis Services Data Mining Decision Tree

Analysis Services Data Mining Model Testing – Classification Matrix Actual PredictedNo ShowShowTotal No Show Show 5, , ,322 Total 5, , ,371 Accurate 103, % Not Accurate 5,8475.3% Total 109, %

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 Siegel Predictive 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

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 ( 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 data with Reporting Services

Reporting Services

Tools to add features to SSRS web pages and

Reporting Services Alerts vs “Wait and Wade”

Reporting Services

You can use the same report on a webpage (pull) or in an alert (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 ) mooresolutionsinc.com/videos.php MGMA Connexion article on Pivot Tables mooresolutionsinc.com/articles.php

Join Excel Users MGMA Community Login to 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 Excel Users is in alphabetical order

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