1. Microsoft in Healthcare
Analytics
Georgia HIMSS
Martin Sizemore
October 2, 2012

2. Perficient Recognized by Microsoft
• Microsoft Healthcare Provider Partner of the
Year award winner for the 2nd time in 3 years.
• “Perficient combines deep health industry
expertise with a high level of competency on
Microsoft technologies. The result is a set of
high value solutions that deliver value to the
world’s leading healthcare enterprises,” Steve
Aylward, general manager, US Health & Life
Sciences, Strategies & Solutions, Microsoft.
2

3. Microsoft Partner Landscape
12
Global
Systems
Top 3 in the NSI
Integrators
Category.
33 National
Systems
Integrators
500 Managed Partners
500,000 Gold Partners

4. Business Intelligence & Analytics
Healthcare organizations are going through a technology and
data revolution. Pressure from a wide range of sources are
forcing both providers and payers to look at their data and
technology investments in new and innovative ways:
– Use data to improve quality of care • Thousands of hours redirected
– Increase financial efficiency to other tasks
– Improve operational effectiveness
– Conduct innovative research • Enhanced analytics allow both
in-depth and simple analytics
– Satisfy regulatory requirements
Perficient’s expertise and experience with full life-cycle BI • Improved reporting and data
Implementations, including the following disciplines: mining capability
– BI/Information Strategy
– BI Design (User-Centered Approach)
– BI Architecture & Enterprise Security (LDAP/SSO)
– BI Implementation BI Education and Mentoring
– Data Integration / Data Warehousing
– Business Analytics and Reporting
– Portal Integration
4

5. Meriter Health Systems
• Over 3,400 employees
• Locations throughout southern Wisconsin
• MHS includes:
– Meriter Hospital, Meriter Medical Group, Meriter Medical Clinics, Meriter Home
Health, Meriter Laboratories, Meriter Foundation, Physician Plus Insurance
Corporation
• Implemented a Cost Containment Dashboard
• Integrated Clinical & Financial Systems
• Utilized Microsoft Stack
• RVU Based Compensation Reporting

6. Meriter Orthopedics Dashboard

7. Meriter Orthopedics Dashboard

8. DuPage Medical Group
• DMG is one of the largest physician-owned, multi-specialty groups
in the Midwest
• DMG has more than 300 practicing physicians, 35 medical/surgical
specialties and 40 locations
• Leveraged existing SQL Server infrastructure
• Jump started an organizational transition towards using
standardized metrics
• Encouraged “Self Service” Reporting
• Provided Advanced Reporting and Analytical Capabilities

9. DuPage Medical Reporting

11. Agenda
1. Who is Predixion and what we do?
2. Capabilities
3. Use case based demo

12. Who is Predixion?

13. Predixion’s Vision
Predixion is a Predictive Analytics software company focused on
healthcare
• Squeeze the complexity out of Predictive Analytics and Data Mining
• Enable the integration of Predictive Intelligence into all decisioning
processes.

14. Retrospective vs. Prospective
How did we do? How do we do better?
Business Intelligence Predictive Analytics
Reactionary Healthcare The ACO Model

15. Easier to Create, Share and Consume
Insight Analytics™ - Easy data prep, model build and deployment
Predictively enabled: Dashboards, Applications, Reports

16. Innovating on “Ease-of-Use”
Easier to Create
Easier to Share
Easier to Consume

17. Analyst Creates Models

18. Enabling Non-IT Users

19. Enabling Non-IT Users

20. Integrated Predictive Intelligence
Management Views
to better understand the
patient population
Clinician Views
to better predict
individual patient
outcomes
Operational Views
that integrate predictive
information into
workflows

21. Predictive Solutions in Healthcare
• Predictable Readmissions
• Chronic Condition Management
• Co-Morbidity Identification
• At Risk Patient Population Detection
• Hospital Acquired Condition
• Proactive LOS Monitoring
• Blood Supply
• Patient Satisfaction Scores

22. Use Cases
Use case name Overall goal: Use Predixion Insight to…
Preventing disease or Decrease the incidence and/or progression of disease across covered
disease progression population, improving member health and decreasing cost.
Manage population Score the probability of individual patients for developing a specific disease
health (heart disease, cancer, etc) or condition (osteoarthritis, obesity, depression)
across covered population and deploy interventions shown to mitigate that
disease process, thereby improving member health and decreasing cost.
***Predict readmission Score the probability of readmission for currently admitted patients providing
risk actionable information allowing the healthcare system to sensibly intervene to
prevent those readmissions in a cost-effective and efficient manner.
Predict high-risk Develop a screening tool that allows payor to more accurately direct newly
pregnancy risk pregnant women at risk for complicated pregnancy to appropriate high-risk
clinical setting. Specifically identify indicators for this condition to direct
appropriate interventions.
***Length of Stay (LOS) Increase the accuracy and potentially automate the LOS estimation where
estimation possible.
Outlier/anomaly Analyze various data sources to score from a probabilistic standpoint if outlying
detection data points or anomalous trends are significant and further delineate underlying
factors that are associated with those data points or trends.

23. Use Cases
Use case name Overall goal: Use Predixion Insight to…
***Overpayment Examine various data sets to determine if there is any pattern in claims data that
Detection could be accounted for by either fraud or error.
Hospital Acquired Score the probability of individual patient's developing a HAI and identify specific
Illness indicators that allow pro-active intervention to prevent this condition.
Chronic Condition Score the probability of individual patients for developing a specific disease (heart
Management disease, cancer, etc) or condition (osteoarthritis, obesity, depression) across covered
population and deploying interventions shown to mitigate that disease process,
thereby improving member health and decreasing cost.
***Fraud and Abuse Examine various data sets to determine if there is any pattern in claims data that
could be accounted for by either fraud or error.
Membership Develop probabilistic models that determine factors important to retaining
Management subscriber membership or that lead to de-enrollment. Also, develop models that
allow for proactive management of enrolled patient's health and resource utilization.
Provider Performance Develop probabilistic models that score practioners likelihood to perform desirable
Measurement actions that promote population health and/or influence appropriate resource
utilization.
***Patient Satisfaction
Scores

24. Predictive Intelligence - CMS Metrics Mapping
1: Getting Timely Care, Appointments, and Information 24: Health Acquired Conditions Composite
Patient Safety 25: Health Care Acquired Conditions: CLASBI Bundle
2: How Well Your Doctors Communicate
Patient/ 3: Helpful, Courteous, Respectful Office Staff 35: Composite (All or Nothing Scoring)
36: Hemoglobin A1c Control (<8%)
Caregiver 4: Patients' Rating of Doctor
37: Low Density Lipoprotein (LDL-C) Control in Diabetes Mellitus
Experience 5: Health Promotion and Education
6: Shared Decision Making 38: Tobacco Non Use
39: Aspirin Use
Diabetes
7: Medicare Advantage CAHPS, health Status/Functional Status
40: Hemoglobin A1c Poor Control (>9%)
8: Rate of readmissions within 30 days of discharge from an acute care hospital for assigned 41: High Blood Pressure Control in Diabetes Mellitus
ACO beneficiary population 42: Urine Screening for Microalbumin or Medical Attention for Nephropathy in
9: 30 Day Post Discharge Physician Visit Diabetic Patients
43: Dilated Eye Exam in Diabetic Patients
10: Reconciliation After Discharge from an Inpatient facility. Percentage of patients aged 65
44: Foot Exam
years and older d/c from any inpatient facility and seen within 60 days
45: Left Ventricular Function (LVF) Assessment
Transition
11: Uni-dimensional self-reported survey that measures the quality of preparation for care 46: Left Ventricular Function (LVF) Testing
Heart Failure
transitions 47: Weight Management
Care Coordination
48: Patient Education
12: Diabetes, short-term complications (AHRQ PQI #1)
At-Risk Populations
49: Beta-Blocker Therapy for Left Ventriclar Systolic Dysfunction (LVSD)
13: Uncontrolled Diabetes (AHRQ PQI #14)
14: Chronic obstructive pulmonary disease (AHRQ PQI #5) 50: Angiotensin-Converting Enzyme (ACE) Inhibitor or Angiotensin Receptor
Blocker (ARB) Therapy for Left Ventricular Systolic Dysfunction (LVSD)
15: Congestive Heart Failure (AHRQ PQI #8)
51: Warfarin Therapy for Patients with Atrial Fibrillation
16: Dehydration (AHRQ PQI #10) 52: Composite: All or Nothing Scoring
17: Bacterial pneumonia (AHRQ PQI #11) 53: Oral Antiplatelet Therapy Prescribed for Patients with CAD
18: Urinary infections (AHRQ PQI #12)
54: Drug Therapy for Lowering LDL-Cholesterol
Information System
19: % All Physicians Meetings Stage 1 HITECH Meaningful Use Requirements
55: Beta-Blocker Therapy for CAD Patients with Prior Myocardial Infection (MI)
CAD
20: % of PCPs Meeting Stage 1 HITECH Meaningful Use Requirements
56: LDL level < 100 mg/dl
21: % of PCPs Using Clinical Decision Support
22: % of PCPs who are Successful Electronic Prescribers Under the eRx Incentive Program 57: Angiotensin-Converting Enzyme (ACE) Inhibitor or Angiotensin Receptor
Blocker (ARB) Therapy for Patients with CAD and Diabetics and/or Left
23: Patient Registry Use Ventricular Systolic Dysfunction (LVSD)
26: Influenza Immunization
58: Blood Pressure Control
Preventative Health
27: Pneumococcal Vaccination Hypertension
28: Mammography Screening 59: Plan of Care
29: Colorectal Cancer Screening 60: Spirometry Evaluation
30: Cholesterol Management for Patients with Cardiovascular Conditions COPD 61: Smoking Cessation Counseling Received
62: Bronchodilator Therapy based on FEV1 Measures
31: Adult Weight Screening and Follow-up
32: Blood Pressure Measurement 63: Screening for Fall Risk;
33: Tobacco Use Assessment and Tobacco Cessation Intervention Frail Elderly 64: Osteoporosis Management in Women Who had a Fracture
34: Depression Screening 65: Monthly INR for Beneficiaries on Warfarin
Maps to Existing Solution Reuse of Existing Solution New Solution Potential New Solution

25. Identifying At-Risk Populations

26. Risk Stratification with Predixion
Total Population Low Medium High
125
925
300
500
A core ACO skillset for identifying and managing patient
populations and driving proactive healthcare

27. Know who is at risk
Lay the foundation for Preventative Healthcare

28. Adapt care plans by risk strata
Improve efficiency and drive better patient outcomes

29. “Build the model”

30. Predixion Insight Ribbon in Excel

31. Identifying Key Influencers

32. Create the Model from Excel

33. Test the Model’s Accuracy

34. Data + Probability Score

35. Create ROI Analysis in Excel

36. “Deploy the model”
the last mile of analytics

37. Predixion’s Last Mile of Analytics
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38. Predixion’s Last Mile of Analytics
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39. Predixion’s Last Mile of Analytics
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40. Predixion’s Last Mile of Analytics
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41. Predixion’s Last Mile of Analytics
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42. Predixion’s Last Mile of Analytics
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59. Thank you