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Turning Numbers. Nate Moore MBA, CPA, FACMPE. Into Knowledge. Business Intelligence f or Medical Practices. Learning Objectives. Describe examples of data exploration using Analysis Services Recognize sources of data to combine with Integration Services
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Turning Numbers Nate Moore MBA, CPA, FACMPE Into Knowledge
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 http://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
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 Spreadsheet Table 500K records Pivot Table Connected to Cube 2.1 M records
Analysis Services Pivot Table Connected to Cube Pivot Table Connected to Table
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 Decision Tree
Analysis Services Data Mining Model Testing – Classification Matrix
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 andPredictive 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 (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 data • with Reporting Services
Reporting Services • Tools to add features to SSRS web pages and email
Reporting Services • Alerts • vs • “Wait and Wade”
