Microsoft in Healthcare
      Analytics
    Georgia HIMSS
     Martin Sizemore
     October 2, 2012
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
Microsoft Partner Landscape


                               12
                             Global
                            Systems
Top 3 in the NSI
                           Integrators
   Category.
                         33 National
                          Systems
                         Integrators

                   500 Managed Partners


                   500,000 Gold Partners
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
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
Meriter Orthopedics Dashboard
Meriter Orthopedics Dashboard
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
DuPage Medical Reporting
Agenda




1. Who is Predixion and what we do?
2. Capabilities
3. Use case based demo
Who is Predixion?
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.
Retrospective vs. Prospective

How did we do?            How do we do better?


  Business Intelligence       Predictive Analytics




Reactionary Healthcare       The ACO Model
Easier to Create, Share and Consume

Insight Analytics™ - Easy data prep, model build and deployment




   Predictively enabled: Dashboards, Applications, Reports
Innovating on “Ease-of-Use”

   Easier to Create


        Easier to Share


            Easier to Consume
Analyst Creates Models
Enabling Non-IT Users
Enabling Non-IT Users
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
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
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.
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
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
Identifying At-Risk Populations
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
Know who is at risk




Lay the foundation for Preventative Healthcare
Adapt care plans by risk strata




Improve efficiency and drive better patient outcomes
“Build the model”
Predixion Insight Ribbon in Excel
Identifying Key Influencers
Create the Model from Excel
Test the Model’s Accuracy
Data + Probability Score
Create ROI Analysis in Excel
“Deploy the model”
the last mile of analytics
Predixion’s Last Mile of Analytics




                               37
Predixion’s Last Mile of Analytics




                               38
Predixion’s Last Mile of Analytics




                               39
Predixion’s Last Mile of Analytics




                               40
Predixion’s Last Mile of Analytics




                               41
Predixion’s Last Mile of Analytics




                               42
Thank you

Microsoft in Healthcare Analytics Georgia HIMSS

  • 1.
    Microsoft in Healthcare Analytics Georgia HIMSS Martin Sizemore October 2, 2012
  • 2.
    Perficient Recognized byMicrosoft • 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.
  • 7.
  • 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.
  • 11.
    Agenda 1. Who isPredixion and what we do? 2. Capabilities 3. Use case based demo
  • 12.
  • 13.
    Predixion’s Vision Predixion isa 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 Howdid 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.
  • 18.
  • 19.
  • 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 inHealthcare • 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 casename 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 casename 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.
  • 26.
    Risk Stratification withPredixion 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 isat risk Lay the foundation for Preventative Healthcare
  • 28.
    Adapt care plansby risk strata Improve efficiency and drive better patient outcomes
  • 29.
  • 30.
  • 31.
  • 32.
    Create the Modelfrom Excel
  • 33.
  • 34.
  • 35.
  • 36.
    “Deploy the model” thelast mile of analytics
  • 37.
    Predixion’s Last Mileof Analytics 37
  • 38.
    Predixion’s Last Mileof Analytics 38
  • 39.
    Predixion’s Last Mileof Analytics 39
  • 40.
    Predixion’s Last Mileof Analytics 40
  • 41.
    Predixion’s Last Mileof Analytics 41
  • 42.
    Predixion’s Last Mileof Analytics 42
  • 59.

Editor's Notes

  • #7 Executive view Ability to AnalyzeAvg In Room Surgeon time across physicians for the same proceduresCost information by Hospital unitTotal PO cost by vendors of Ortho componentsReimbursement vs. Total PO Cost by Hospital
  • #8 Physican ViewTotal PO cost by vendors of Ortho componentsAvg In Room Surgeon Time vs. Case Count over timeAvg PO Cost Per Case by ProvidersPO Cost as a % Of Reimbursement , Private vs. Govt InsuranceSelf – service, drill into details built in functionality of PerformancePoint
  • #10 Can easily analyze data in familiar tools like In this case, viewing Internal Referral RatesCan show trends and key KPIs on dashboards that are made accessible through the browserEncounter CountsBilled ChargesInternal Referral RateUnique Patient Counts
  • #14 We are a PA software company focused on HealthcareOrange county – SalesRedmond – DevelopmentFounded by a team of highly successful Software executives Vision – remove barriers to PA and fill a gap in healthcare
  • #15 While understanding the past is a critical part of a healthcare system’s BI strategy, far too few organizations dedicate their precious resources to proven technologies such as data mining and predictive analytics to help drive improved outcomes throughout the system.  These technologies have been around for decades and their ability to drive notable ROI for all segments of the system are very well established.As the old saying goes, we manage what we measure, so you’’ve seen where that’s taken so far .. Trying to drive forward while looking out the rear window. How can we do better? Use data and predictive analytics to steer our course for the future.Core Metrics – Length of Stay, complication rate, Resource utilization, etcInstead we can Predict the risk for our population for certain high-dollar diseases, commonly associated co-morbidities, prescribe individualized therapeutic regimens based on analysis of data that now predict what will best achieve wellness
  • #22 Some of the CMS measured ACO outcomes:Predictable ReadmissionsChronic Condition ManagementCo-Morbidity IdentificationAt Risk Patient Population DetectionHospital Acquired Condition Proactive LOS MonitoringBlood Supply Patient Satisfaction Scores
  • #23 The next two slides are some use cases we have in-development or have deployed to other clients. The nice thing about predictive analytics is if you have a data source you can use it to identify a better way to do things.
  • #24 We’ve had some great successes. One item I added to the bottom was Patient Satisfaction Scores. Hospitals care about these numbers, a lot of the hospitals I work with have to publicly report and they have score cards on them. With this type of data you could identify key influencers to help affect process improvement.