© 2014 Health Catalyst Follow Us on Twitter #TimeforAnalytics © 2014 Health Catalyst Proprietary and ConfidentialFollow Us on Twitter #TimeforAnalytics John L. Haughom, MD June 2014 The Analytic System: Finding Patterns in the Data

© 2014 Health Catalyst Follow Us on Twitter #TimeforAnalytics Healthcare: The Way It Should Be Part One – Forces Driving Transformation Chapter One – Forces Defining and Shaping the Current State of U.S. Healthcare Chapter Two – Present and Future Challenges Facing U.S. Healthcare Part Two – Laying the Foundation for Improvement and Sustainable Change What will it take to successfully ride the transformational wave? Part Three – Looking into the Future What will it take to successfully ride the transformational wave? 2 Available for FREE download at:

© 2014 Health Catalyst Follow Us on Twitter #TimeforAnalytics Implementing an Effective System of Production in Healthcare Analytic system Content system Deployment system Scalable and sustainable outcomes

© 2014 Health Catalyst Follow Us on Twitter #TimeforAnalytics Analytic System Components 4

© 2014 Health Catalyst Follow Us on Twitter #TimeforAnalytics Metadata: EDW Atlas security and auditing Common, linkable Vocabulary Financial Source Marts Administrative Source Marts Departmental Source Marts Patient Source Marts EMR Source Marts HR Source Mart Diabetes Sepsis Readmissions Less transformationMore transformation FINANCIAL SOURCES (e.g. EPSi, Peoplesoft, Lawson) ADMINISTRATIVE SOURCES (e.g. API Time Tracking) ADMINISTRATIVE SOURCES (e.g. API Time Tracking) EMR SOURCE DEPARTMENTAL SOURCES (e.g. Apollo) PATIENT SATISFACTION SOURCES (e.g. NRC Picker, Press Ganey) PATIENT SATISFACTION SOURCES (e.g. NRC Picker, Press Ganey) Human Resources (e.g. PeopleSoft) Human Resources (e.g. PeopleSoft) Late-Binding™ Data Warehouse

© 2014 Health Catalyst Follow Us on Twitter #TimeforAnalytics6 Population Health Management Clinical Integration hierarchy - care process families Hyperlipidemia Acute Myocardial Infarction (AMI) Percutaneous Intervention (PCI) Coronary Artery Bypass Graft (CABG) Cardiac Rehab Ischemic Heart Disease care process family Home Outpatient Clinic CareInpatientSNFHome HealthHospice Coronary Atherosclerosis

© 2014 Health Catalyst Follow Us on Twitter #TimeforAnalytics Population Health Management Clinical Integration hierarchy - clinical programs Vascular Disorders care process family Heart Rhythm Disorders care process family Heart Failure care process family Ischemic Heart Disease care process family Cardiovascular clinical program HomeOutpatientClinic CareInpatientSNFHome HealthHospice

© 2014 Health Catalyst Follow Us on Twitter #TimeforAnalytics 8 Clinical Integration hierarchy Clinical programs – ordering of care Primary Care careprocessfamiliese.g.,Diabetes CVCV careprocessfamiliese.g., Heart Failure W&CW&C careprocessfamiliese.g.,Pregnancy GIGI careprocessfamiliese.g., Lower GILower GIDisorders Resp- iratory careprocessfamiliese.g., Obstructive Lung Disorders Neuro Sciences careprocessfamiliese.g., Spine Disorders Musculo- skeletal careprocessfamiliese.g.,Joint Replace- ment SurgerySurgery careprocessfamiliese.g., Urologic Disorders GeneralMedGeneralMed careprocessfamiliese.g., Infectious Disease OncologyOncology careprocessfamiliese.g.,BreastCancer Peds Spec careprocessfamiliese.g.,Peds CV SurgCV Surg Mental Health careprocessfamiliese.g.,Depression

© 2014 Health Catalyst Follow Us on Twitter #TimeforAnalytics Linking the three systems Clinical Integration hierarchy

© 2014 Health Catalyst Follow Us on Twitter #TimeforAnalytics Top 10 care process families account for over 40% of the opportunity Top 32 care process families account for 80% of the opportunity Care process families by resources consumed (high to low) Percent of total resources consumed Inpatient per case KPA

© 2014 Health Catalyst Follow Us on Twitter #TimeforAnalytics Frequency distribution with control limits 0.5% 99% 2.33 std. devs. Number of times observed (Number, rate, percentage, proportion) Value observed Defect Within specifications Upper control limit Lower control limit Centerline Spread

© 2014 Health Catalyst Follow Us on Twitter #TimeforAnalytics Variation in a process is due to Random causes (common causes) Assignable causes (special causes) The Causes of Variation

© 2014 Health Catalyst Follow Us on Twitter #TimeforAnalytics ConditionAcceptable INR range DVT/Pulmonary Embolus Atrial Fibrillation Anterior Myocardial Infarction (AMI) Valve Replacement A Clinical Example Frequency distributions and control limits are common in healthcare

© 2014 Health Catalyst Follow Us on Twitter #TimeforAnalytics Statistical process control chart (How a process behaves over time) Values Observed Time The further a point moves off the center line the higher the probability it is not random variation and the greater the probability you can identify an assignable cause. Centerline Clinical process XYZ Lower control limit Assignable (special cause) variation Random (common cause) variation Upper control limit Title

© 2014 Health Catalyst Follow Us on Twitter #TimeforAnalytics Process improvement Uses of control charts Quality Time Unstable process worse better Control limits Assignable variation suggesting an unstable process Stable process Process capability Random variation suggesting a stable process Improvement

© 2014 Health Catalyst Follow Us on Twitter #TimeforAnalytics Approach to improvement # of cases # of Cases Option 1: Punish the outliers Mean Focus on minimum standard metric Excellent outcomesPoor outcomes Excellent outcomes Poor outcomes 1 box = 100 cases in a year Current condition Significant volume Significant variation Punish the outliers

© 2014 Health Catalyst Follow Us on Twitter #TimeforAnalytics Approach to improvement Excellent outcomesPoor outcomes # of Cases Current condition Significant volume Significant variation Excellent outcomes # of Cases Option 2: Identify best practice “Narrow the curve and shift it to the right” Mean Focus on best practice care process model Poor outcomes 1 box = 100 cases in a year Focus on better care

© 2014 Health Catalyst Follow Us on Twitter #TimeforAnalytics Excellent outcomesPoor outcomes # of Cases Excellent outcomes # of Cases Poor outcomes Variability High Low Resource consumption LowHigh Improvement Approach - Prioritization 18

© 2014 Health Catalyst Follow Us on Twitter #TimeforAnalytics A Demonstration Demonstrating the power of modern analytics… …Finding Meaningful Patterns in your data 19

© 2014 Health Catalyst Follow Us on Twitter #TimeforAnalytics What Does Health Catalyst Do? ● Enterprise Data Warehouse “single source of truth” ● Library of data acquisition adapters ● Metadata repository ● Auditing and access control ● Supports a variety of analytic applications ‒ Health Catalyst ‒ Client developed 20 Platform

© 2014 Health Catalyst Follow Us on Twitter #TimeforAnalytics What Does Health Catalyst Do? ● Reports & Dashboards ● Ad-hoc query ● Registries ● Quality measures ● Population health ● Data mining ● Clinical improvement ● Workflow analysis ● Modeling and predictive analytics 21 Applications Platform

© 2014 Health Catalyst Follow Us on Twitter #TimeforAnalytics What Does Health Catalyst Do? Installation ● Configuration ● Data Architecture Improvement ● Project Management ● Clinical Improvement ● “Lean” Process Improvement 22 Applications Services Platform

© 2014 Health Catalyst Follow Us on Twitter #TimeforAnalytics Application Families 23 Foundational Applications Discovery ApplicationsDiscovery ApplicationsAdvanced ApplicationsAdvanced Applications Provide deep insights into evidence-based metrics that drive improvement in quality and cost reduction through managing populations, workflows, and patient injury prevention. Encourage broad use of the data warehouse by presenting dashboards, reports, and basic registries across clinical and departmental areas. Allow users to discover patterns and trends within the data that inform prioritization, inspire new hypotheses, and define populations for management.

© 2014 Health Catalyst Follow Us on Twitter #TimeforAnalytics Demos 24 Discovery ApplicationsDiscovery Applications Foundational ApplicationsFoundational Applications Advanced Applications`Advanced Applications` Population Suites e.g., Ischemic Heart Disease Workflow / Operational Suites e.g., Acute Medical Patient Injury Prevention Suites e.g., Infection Prevention Patient Injury Prevention Modules e.g., CAUTI, CLABSI, SSI Workflow/Operational Modules e.g., ICU, MedSurg, Emergency Population Modules e.g., CABG, Stent, AMI Labor Management Explorer Rev Cycle Explorer Patient Satisfaction Explorer General Ledger Explorer Readmission Explorer Population Explorer Patient Flow Explorer Practice Management Explorer Suite Financial Management Explorer CAFE—Comparative Analytics Framework and Exchange—across Healthcare Systems and National Benchmarks EDIT—Executive Dashboard Integration Tool (Key Performance Indicator editable collage from all app categories) Key Process Analysis (KPA) Cohort Builder Comorbidity Analyzer Payment Model Analyzer Readmission Predictor Patient Flight Plan Predictor ACO Explorer Suite Metric Correlation Analyzer Regulatory Explorer Attribution Modeler

© 2014 Health Catalyst Follow Us on Twitter #TimeforAnalytics25 Demo 1: Key Process Analysis (KPA). Identify areas of greatest opportunity for quality improvement and savings Demo 2: Population Explorer. Identify potential risk by understanding relative size of disease populations and risk profiles Demo 3: Heart Failure. Achieving quality improvement and cost reductions by directing targeted interventions to high-risk patients Demo 4: Community Care. Monitoring high-risk patients in primary care to prevent expensive acute treatment Demos: How Analytics Drive Improvement & Savings

© 2014 Health Catalyst Follow Us on Twitter #TimeforAnalytics Dr. J. 15 Cases $15,000 Avg. Cost Per Case Mean Cost per Case = $10,000 $5,000 x 15 cases = $75,000 opportunity Total Opportunity = $75,000 Total Opportunity = $175,000 $4,000 x 25 cases = $100,000 opportunity Total Opportunity = $500,000 Total Opportunity = $1,200,000 Cost Per Case, Vascular Procedures KPA: Measuring Opportunity Using provider variation to calculate the potential financial impact of improving and standardizing care processes

© 2014 Health Catalyst Follow Us on Twitter #TimeforAnalytics Poll Questions 2. Does your organization effectively engage front line clinicians in improvement projects where they routinely analyze care processes to eliminate inappropriate variation and improve processes over time? 91 Respondents a. 5 – Definitely – 19% b. 4 – 22% c. 3 – 26% d. 2 – 25% e. 1 – Not at all – 8% 27

© 2014 Health Catalyst Follow Us on Twitter #TimeforAnalytics28 Demo 1: Key Process Analysis (KPA). Identify areas of greatest opportunity for quality improvement and savings Demo 2: Population Explorer. Identify potential risk by understanding relative size of disease populations and risk profiles Demo 3: Heart Failure. Achieving quality improvement and cost reductions by directing targeted interventions to high-risk patients Demo 4: Community Care. Monitoring high-risk patients in primary care to prevent expensive acute treatment Demos: How Analytics Drive Shared Savings

© 2014 Health Catalyst Follow Us on Twitter #TimeforAnalytics In Summary… A good Analytic System that unlocks your data, automates its distribution and makes it easy to see important patterns in the data is necessary to support meaningful and sustainable improvement. The data model on which your EDW is based matters. A Clinical Integration Hierarchy can help you organize how you think about and manage health care delivery. Differentiating random variation from assignable or “special cause” variation is important in healthcare and in improvement. Good use of your data can help guide you in an effort to maximize improvement and value for the investment. 29

© 2014 Health Catalyst Follow Us on Twitter #TimeforAnalytics Poll Question 3. Using our discussion of an Analytic System as a guide, on a Scale of 1-5, how effective is your organization’s analytical strategy and capability? 78 Respondents a. 5 – Very Effective – 9% b. 4 – 15% c. 3 – 35% d. 2 – 25% e. 1 – Very Limited – 15% 30

© 2014 Health Catalyst Follow Us on Twitter #TimeforAnalytics Thank You Upcoming Educational Opportunities Late-Binding Data Warehousing: An Update on the Fastest Growing Trend in Healthcare Analytics Date: July 10 th Presenter: Dale Sanders, Senior Vice President, Health Catalyst Register at Healthcare Analytics Summit Join top healthcare professionals for a high-powered analytics summit using analytics to drive an engaging experience with renowned leaders who are on the cutting edge of healthcare using data-driven methods to improve care and reduce costs. Date: September 24th-25th Location: Salt Lake City, Utah Save the Date: For Information Contact: