1. Turning Numbers Into Knowledge Nate Moore MBA, CPA, FACMPE

2. Business Intelligence for Medical Practices

3. 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

4. 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

5. Business Intelligence Data is merely the raw material of knowledge. New York Times

6. SQL Server 101 Relational database management system from Microsoft

7. SQL Server 101

12. Learning Objective #1 Describe examples of data exploration using Analysis Services

13. Cubes Measures (numbers like collection dollars or billed charges) Dimensions (ways to categorize measures, like time, providers, and locations)

14. Analysis Services Excel is a great tool to work with cubes

15. Analysis Services Pivot Table Connected to Cube 2.1 M records Pivot Table Spreadsheet Table 500K records

16. Analysis Services Pivot Table Connected to Table Pivot Table Connected to Cube

17. 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

18. Analysis Services Data Mining

19. Classification (discrete values) Regression (continuous values) Segmentation (algorithm groups) Association (already grouped) Sequence Analysis (future routes)

20. 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?

21. 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?

22. 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?

23. Analysis Services Data Mining Association (already grouped) Data already has a group Look at past data to find patterns in the group (Amazon, Netflix)

24. 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

25. 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

26. Analysis Services Data Mining What kinds of data are already available in your PM system to predict no shows?

27. 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

28. Analysis Services Data Mining Decision Tree

29. Analysis Services Data Mining Model Testing – Classification Matrix Actual PredictedNo ShowShowTotal No Show 26 23 49 Show 5,824 103,498 109,322 Total 5,850 103,521 109,371 Accurate 103,52494.7% Not Accurate 5,8475.3% Total 109,371100.0%

30. Analysis Services Data Mining Forecasts vs. Predictive Analytics

31. 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

32. Analysis Services Data Mining Target using unscented lotion and Predictive Analytics to Predict Pregnancy

33. Analysis Services Data Mining PA vs. Facts PA vs. Changing Workflow to get Facts Predicting the Past

34. Learning Objective #2 Recognize sources of data to combine with Integration Services

35. Integration Services Control Flow

36. Integration Services Data Flow

37. Integration Services

38. Data Sources Data Destinations

39. Integration Services Control Flow Tasks

40. Integration Services Data Flow Tasks

41. 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)

42. Integration Services PM and EHR data Eligibility and Benefits data Combine multiple PM systems

43. Learning Objective #3 Differentiate between pulling and pushing data with Reporting Services

44. Reporting Services

45. Tools to add features to SSRS web pages and email

46. Reporting Services Alerts vs “Wait and Wade”

47. Reporting Services

51. You can use the same report on a webpage (pull) or in an alert email (push) with Reporting Services

52. Learning Objectives Those who do not learn from the past are condemned to repeat it. George Santayana

53. 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

54. 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

55. Next Steps Watch Excel Videos Pivot Tables (Videos 1-29 and 280-330) mooresolutionsinc.com/videos.php MGMA Connexion article on Pivot Tables mooresolutionsinc.com/articles.php

56. Join Excel Users MGMA Community Login to www.mgma.comwww.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 http://community.mgma.com/MGMA/MGMA/MyProfile/MySubscriptions/Default.aspx Excel Users is in alphabetical order

57. MooreSolutionsInc.com Nate Moore PivotTableGuy