Organizing Analytics Success
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This document discusses organizing for analytics success through establishing three core systems: the analytic system, content system, and deployment system. It provides examples of activities and components for each system, such as automating data visualization in the analytic system, standardizing care delivery through shared baselines in the content system, and applying agile principles to care improvement in the deployment system. The document also includes examples of exercises and poll questions to aid discussion around each system.
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Organizing Analytics Success
- 1. 1 Session #7 – Organizing For Analytics Success Hotel Wi-Fi • HASummit14 • PW: analytics Current Session Thumbs Up Submit a Question Poll Question 1 2 3 4 App Questions? • 3 app helpers • Raise hand with mobile device • Walk to back
- 2. Session #7 Organizing for Analytics Success Holly Rimmasch Chief Clinical Officer, Health Catalyst Ms. Holly Rimmasch is Chief Clinical Officer at Health Catalyst. Prior to joining Health Catalyst, Ms. Rimmasch was an Assistant Vice President at Intermountain Healthcare and was integral in promoting integration of Clinical Operations across hospitals, ambulatory settings and managed care plans. Holly has spent the last 17 years dedicated to improving clinical care including implementation of operational best practices. Ms. Rimmasch holds a Master of Science in Adult Physiology from the University of Utah and a Bachelor of Science in Nursing from Brigham Young University. Steve Barlow Co-Founder and Senior Vice President of Client Operations, Health Catalyst Mr. Barlow is a co-founder of Health Catalyst. He oversees all technical client operations. Mr. Barlow is a founding member and former chair of the Healthcare Data Warehousing Association. He began his career in healthcare over 22 years ago at Intermountain Healthcare and acted as a member of the team that led Intermountain’s nationally recognized improvements in quality care and reductions in cost. Mr. Barlow holds a BS from the University of Utah in health education and promotion. 2
- 3. 3 Where Do We Start? 3 Cumulative % % of Total Resources Consumed for each clinical work process 50% 7 CPFs Number of Care Process Families (e.g., ischemic heart disease, pregnancy, bowel disorders, spine, heart failure) 21 CPFs 80%
- 4. 4 Effective Approach to improvement: Focus on “Better Care” Poor Outcomes Excellent 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” Strategy • Identify evidenced based “Shared Baseline” • Focus improvement effort on reducing variation by following the “Shared Baseline” • Often those performing the best make the greatest improvements Mean Focus on Best Practice Care Process Model Poor Outcomes 1 box = 100 cases in a year
- 5. 5 Internal Variation vs Resource Consumption Y- Axis = Internal Variation in Resources Consumed Bubble Size = Resources Consumed X Axis = Resources Consumed Bubble Color = Clinical Domain 1 2 3 4
- 6. Three Systems of Care Delivery Overview Standard “Measurement” Work Standard “Knowledge” Work 6 Analytic System Content System Standard “Organizational” Work Deployment System Evidence gathering & evaluating Knowledge assets (e.g. Order Sets) Starter sets Value stream maps Patient safety protocols Team Structures Roles Fingerprinting Implementation Data driven prioritization Calculations Definitions EnterpriseDataWarehouse Data visualization
- 7. Analytic System Core Activities 7 Analytic System Content System Deployment System Unlocking Data to Drive Measurements Automating the Broad Distribution of Information Discovering Patterns in Data
- 8. Strong Analytic System Weak Analytic System Understanding the question Hunting for data Gather, compiling or running Interpreting data Data distribution Strong Analytic System The majority of time is spent analyzing and interpreting data Understanding the question Hunting for data Gather, compiling or running Interpreting data Data distribution Non value-add Value-add 8
- 9. 9 Enterprise Data Model (Technology Vendors) Provider Patient Cost Encounter Less Transformation Bad Debt Diagnosis Procedure Facility Charge Employee Survey House Keeping Catha Lab Provider Census Time Keeping FINANCIAL SOURCES ADMINISTRATIVE SOURCES EMR SOURCES DEPARTMENTAL SOURCES Pt. SATISFACTION More Transformation Enforced Referential Integrity SOURCES EDW
- 10. 10 EMR SOURCES Oncology Revenue Cycle Diabetes Labor Productivity Heart Failure Regulatory Pregnancy Asthma Census DEPARTMENTAL SOURCES Pt. SATISFACTION SOURCES FINANCIAL SOURCES ADMINISTRATIVE SOURCES Redundant Data Extracts Independent Data Marts (Healthcare Point Solutions, EMRs) EDW More Transformation Less Transformation
- 11. 11 Metadata (EDW Atlas), Security and Auditing Common, linkable vocabulary Readmissions Diabetes Sepsis Financial Source Marts Administrative Source Marts Departmental Source Marts EMR Source Marts Patient Satisfaction Source Mart FINANCIAL SOURCES ADMINISTRATIVE SOURCES EMR SOURCEs DEPARTMENTAL SOURCES Pt. SATISFACTION SOURCES Adaptive Data Model More Transformation Less Transformation
- 12. Analytic System Exercise 11
- 13. The Enterprise Shopping Model Produce Meat E n t e r p r i s e S h o p p i n g M o d e l Dairy Dry Goods __ Apples __ Pears __ Tomatoes __ Carrots __ Beef __ Ham __ Chicken __ Pork __ Milk __ Eggs __ Cheese __ Cream __ Pasta __ Flour __ Sugar __ Soup __ Celery __ Banana __ Melon __ Grapes __ Turkey __ Sausage __ Lamb __ Bacon __ 2% Milk __ Half & Half __ Yogurt __ Margarine __ Baking soda __ Rice __ Beans __ B. Sugar 13
- 14. Apples Tomato Soup Flour Milk Turkey Lettuce Sugar Beans Hot dogs Banana Noodles Yogurt Your Shopping List 14
- 15. Additional Items Get eggs Buy flowers Get tires rotated Pick up dry cleaning 15
- 16. 16 Enterprise Data Model (Technology Vendors) Provider Patient Cost Encounter Less Transformation Bad Debt Diagnosis Procedure Facility Charge Employee Survey House Keeping Cath Lab Provider Census Time Keeping FINANCIAL SOURCES ADMINISTRATIVE SOURCES EMR SOURCES DEPARTMENTAL SOURCES Pt. SATISFACTION More Transformation Enforced Referential Integrity SOURCES EDW
- 17. Using a Independent Mart Shopping Model 17 https://dl.dropboxusercontent.com/u/355034/CATALYST%2090%20Second.mp4.zip
- 18. The Independent Mart Shopping Model 18 Independent Mart Shopping Model Cake Dairy Dry Goods __ ½ cup of butter __ ½ cup milk __ 2 eggs __ 1 cup white sugar __ 1 ½ cups all-purpose flour __ 2 teaspoons vanilla extract __ 1 ¾ teaspoon baking powder Trip #2 to the Store Independent Mart Shopping Model Chocolate Chip Cookies How many recipes do you need to make? Trip #1 to the Store Dairy Dry Goods __ 4 eggs __ 2 c shortening __ 1 c sugar __ 2 c brown sugar __ 2 t baking soda __ 2 t vanilla __ 1 t salt __ 4-5 c all-purpose flour __ 4 cups chocolate chips
- 19. 19 EMR SOURCES Oncology Revenue Cycle Diabetes Labor Productivity Heart Failure Regulatory Pregnancy Asthma Census DEPARTMENTAL SOURCES Pt. SATISFACTION SOURCES FINANCIAL SOURCES ADMINISTRATIVE SOURCES Redundant Data Extracts Independent Data Marts (Healthcare Point Solutions, EMRs) EDW More Transformation Less Transformation
- 20. The Adaptive Shopping Model 20 A d a p t i v e S h o p p i n g M o d e l Store: __________________________________________________ __ ______________________ __ ______________________ __ ______________________ __ ______________________ __ ______________________ __ ______________________ __ ______________________ __ ______________________ __ ______________________ __ ______________________ __ ______________________ __ ______________________ __ ______________________ __ ______________________ __ ______________________ __ ______________________ __ ______________________ __ ______________________ __ ______________________ __ ______________________ __ ______________________ __ ______________________
- 21. Shopping List Revisited 21 Additional Items Get eggs Buy flowers Get tires rotated Pick up dry cleaning Initial List And Even More Once you are home, can you make these recipes? Cake: 1 cup white sugar 1 ½ cups all-purpose flour 2 teaspoons vanilla extract 1 ¾ teaspoon baking powder ½ cup of butter ½ cup milk 2 eggs Cookies: 2 cups shortening 4 large eggs 1 cup sugar 2 cups brown sugar 2 t vanilla 1 t salt 2 t baking soda 4 cups all-purpose flour 4-5 cups chocolate chips Baking Powder •Baking Soda •Buy a new couch •Get oil change •Chocolate Chips •Buy yarn and knitting supplies •Vanilla extract •Apples •Tomato Soup •Flour •Milk •Turkey •Lettuce Sugar Beans Hot dogs Banana Noodles Yogurt
- 22. 22 Metadata (EDW Atlas), Security and Auditing Common, linkable vocabulary Readmissions Diabetes Sepsis Financial Source Marts Administrative Source Marts Departmental Source Marts EMR Source Marts Patient Satisfaction Source Mart FINANCIAL SOURCES ADMINISTRATIVE SOURCES EMR SOURCEs DEPARTMENTAL SOURCES Pt. SATISFACTION SOURCES Adaptive Data Model More Transformation Less Transformation
- 23. Poll Question #1 - Analytic 23 How would you describe your analytics and enterprise data warehousing approach? (choose the best answer that applies) a. We do not currently have a centralized analytics data repository (e.g., enterprise data warehouse- EDW) b. We have an EDW based on the enterprise data model approach c. We have an EDW based on the independent data mart approach d. We have an EDW based on the adaptive or late-binding architecture approach e. Unsure or not applicable
- 24. Content System Core Activities Defining a Clinically Driven Patient Cohort Using Evidence to Identify Three Types of Waste Standardizing Care Delivery through Shared Baselines. Analytic System Content System Deployment System 24
- 25. Strong Content System Time Measured in Weeks 25 Habit of all Front-line Clinicians at Every Facility New Clinical or Operational Best Practice Knowledge Discovered Measured in Years Strong Content System Weak Content System
- 26. Clinical Content System Components What Types of Waste are created without standard work? Ordering Waste: Populations (Heart Failure, Diabetes, etc.) Workflow Waste: Departmental Patient Injury Waste: Patient Safety How do we accelerate Evidence Integration into Care Delivery? Evidence Based Population Management Content: Outcome, process and balanced metrics related to improvement AIM statements, intervention indications, triage criteria, order sets, indications for referral, patient and provider education materials, predictive algorithms, care guidelines and protocols Evidence Based Patient Safety Content: Outcome, process and balanced metrics related to improvement AIM statements, At risk screening criteria, safety protocols, near miss and incident tracking How can data accelerate Waste Elimination? Value Stream Maps, A3s, Standard Work starter sets, Outcome, process and balanced metrics related to improvement AIM statements 26
- 27. Content System Exercise 27
- 28. 28 Find as many numbers sequentially from 1 to 50 in 20 seconds. On your mark… Get set… GO!
- 29. 1 12 18 19 22 24 25 ROUND #1 32 31 43 46 47 29
- 30. 30 Find as many numbers sequentially from 1 to 50 in 20 seconds. On your mark… Get set… GO!
- 31. 25 1 17 29 5 21 41 35 7 45 53 33 37 15 49 43 9 23 31 13 3 19 27 39 47 14 50 22 4 36 32 8 28 12 24 42 18 30 2 26 40 38 16 46 20 6 34 48 10 44 ROUND #2 31
- 32. 32 Find as many numbers sequentially from 1 to 50 in 20 seconds. On your mark… Get set… GO!
- 33. 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 START 34 33 32 31 30 29 28 27 26 25 24 23 22 21 20 19 18 17 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 END ROUND #3 33
- 34. Poll Question #2 - Content 34 Rate the level of content standardization (choose the answer that best applies) a. No standardization. Our clinicians use their best judgment based on their individual training b. We have begun to standardize some content (e.g. CPOE to implement standardized order sets – provided by our EMR vendor) We have not yet created standard content for both workflow and clinical domains across the continuum of care c. High degree of standardization, including standardized content for ambulatory and inpatient care management and utilization criteria. The same workflow and care delivery content is followed and measured regardless of what unit or facility a patient enters d. Unsure or not applicable
- 35. Deployment System Core Activities 35 Analytic System Content System Deployment System Organizing for Scalable Improvement Applying Agile Principles to Care Improvement Accelerate Root Cause Analysis by Combining Analytics and Lean Principles
- 36. Strong Deployment System 36 Weak Deployment System Baseline Performance Improvement with focused project team Inability to sustain gains over time Strong Deployment System Baseline Performance Improvement with permanent integrated teams Gains sustained over time
- 37. Population Health Hierarchy “Ordering of Care” Primary Care Care Process Families e.g., Diabetes CV Care Process Families e.g., Heart Failure W&C Care Process Families e.g., Pregnancy GI Care Process Families e.g., Lower GI Disorders Resp-iratory Care Process Families e.g., Obstructive Lung Disorders Neuro Sciences Care Process Families e.g., Spine Disorders Musculo-skeletal Care Process Families e.g., Joint Replace-ment Surgery Care Process Families e.g., Urologic Disorders General Med Care Process Families e.g., Infectious Disease Oncology Care Process Families e.g., Breast Cancer Peds Spec Care Process Families e.g., Peds CV Surg 12 Clinical Programs Cardiovascular 133 Care Process Families Heart Failure 1610 Care Processes Acute Myocardial Infarction Mental Health Care Process Families e.g., Depression 37
- 38. 38 Organization of teams Clinical and technical Provides overall governance and prioritization of initiatives SENIOR EXECUTIVE LEADERSHIP TEAM Provides steady state domain governance and oversight GUIDANCE TEAM Refines Work Group output and leads implementation CLINICAL IMPLEMENTATION TEAM Provides a forum to develop and/or refine clinical content and analytics feedback WORK GROUP Oversees data governance Supports development of clinical content and analytics feedback CONTENT AND ANALYTICS TEAM
- 39. Ranking Comparison Care Process Family Case Count Rank LOS Hours (Capacity) Rank Total Charges Rank Total Direct Cost Rank Total Direct Cost Opportunity Rank Organizational Readiness (1 to 10) 1 = most ready Trauma 9 2 2 3 3 Ischemic Heart 3 7 1 2 2 Disease Infectious Disease 6 3 3 1 1 Pregnancy 1 1 7 4 8 Heart Failure 10 8 4 5 5 Joints 11 13 8 6 16 Normal Newborn 2 6 20 24 32 GI Disorders 4 4 6 7 4 Lower Respiratory 5 5 5 8 6 39
- 40. 40 Organizational Teams Women & Children’s Clinical Program Guidance Team Pregnancy MD Lead RN SME Pregnancy SAM Knowledge Manager Gynecology MD Lead RN SME Data Architect = Subject Matter Expert = Data Capture = Data Provisioning & Visualization = Data Analysis Guidance Team Leads MD Lead Nurse Lead Application Administrator Normal Newborn MD Lead RN SME Normal Newborn SAM Gynecology SAM • Permanent Teams • Integrated Clinical and Technical members • Supports Multiple Care Process Families
- 41. Information Management 41 DATA CAPTURE • Acquire key data elements • Assure data quality • Integrate data capture into operational workflow DATA ANALYSIS • Interpret data • Discover new information in the data (data mining) • Evaluate data quality = Subject Matter Expert = Data Capture = Data Provisioning = Data Analysis DATA PROVISIONING • Move data from transactional systems into the Data Warehouse • Build visualizations for use by clinicians • Generate external reports (e.g., CMS) Knowledge Managers (Data quality, data stewardship and data interpretation) Application Administrators (optimization of source systems) Data Architects (Infrastructure, visualization, analysis, reporting)
- 42. 42 Standard “Organizational” Work Overview Kickoff AIM Statement Implementation Design Launch Approval Results Review • Mission • Cohort Discover • Data Analysis and Review • Best Practices • Building Multiple Potential AIM statements • Supplement content • Refine Cohort • Refine Metrics • Develop Draft Visualizations • Develop Recommended AIM statement #1 • Cluster Reps Obtain Front Line Input • Finalize Cohort • Develop Additional metrics based on feedback • Develop Additional Visualizations to support • PDSA cycle • Cluster Reps Obtain Front Line Input • Improvement Plan • Implementation Plan • Develop cluster rep assignments, and deliverables • Collect cluster rep feedback • Prepare Initial Results from AIM statement #1 • Summarized report for historical review • Refine, recommend AIM statement #2 Monthly Tasks and Checkpoints 7 Steps (Work Streams) 1.Gather Knowledge Assets 2.Define Cohort 3.Select AIM Statement 4.Select, Build, Refine Metrics 5.Develop Implementation Plan for Process Improvement 6. Implementation 7. Measure Progress Select Initial Metric Build and Refine Build and Refine Build and Refine
- 43. Deployment System Exercise 42
- 44. Round 1 44 1 minute to describe 1 minute to draw • Only the Clinician can talk • The Architect cannot look at the drawing (no mind reading) • The Architect can’t start drawing • Only the Architect can draw • The Clinician can only watch – no talking 11234510123456789M101234567890123456789 11234510123456789M101234567890123456789
- 45. 45
- 46. 11234510123456789M101234567890123456789 Round 2 46 2 minutes to describe and draw interactively • The Architect still cannot look at the drawing (still no mind reading capabilities ) • You can interact as much as you want • You can erase and redraw 11234510123456789M101234567890123456789
- 47. 47
- 48. Poll Question #3 - Deployment 48 How are teams organized to improve the quality of care and sustain improvements? (choose the answer that best applies) a. We have ad hoc, reactive improvement teams organized on a project basis b. Our quality department supports service lines and departments for quality and workflow improvement initiatives c. We have organized, permanent, interdisciplinary, process improvement teams. These teams permanently own the quality, cost, safety and satisfaction of their care delivery domain d. Unsure or not applicable
- 49. Poll Question #4 - Deployment 49 How do you align and prioritize improvement priorities across your organization? (choose the answer that best applies) a. We don’t have alignment of our improvement priorities. We have free form improvement that is prioritized in silos across the organization b. We have alignment of our improvement priorities within our hospital, but not across our entire enterprise c. We have a very clear prioritization and governance process for our improvement priorities, tied to our strategic plan d. Unsure or not applicable
- 50. 50 Problems with Missing Systems Information System Centric If we build it they will come. Focus on reducing information request queue. Research Centric Academic ideas with no practical application. Lots of published papers. Organization Centric NULL SET (Clinicians stop coming to meetings if evidence and measurement are both missing.) Analytic System Content System Deployment System Science Project Centric Pockets of excellence, Limited roll-out of improvements. LEAN Centric Un-sustainable Improvements. Can’t manually measure after 2 or 3 projects. Automation Centric Paved Cow Paths (Process is automated but not improved – many EMR deployments.)
- 51. Three Systems to Ignite Change Analytic System Content System Deployment System Scalable & Sustainable Outcomes Improved population health Care delivery is evidenced based, improvements in cost and quality are scalable and sustainable 51
- 52. In Summary Don’t boil the ocean! 52 All3 systemsareneeded. Analytic System Content System Analytic System • Be agile and adaptive • Enable knowledge discovery Content System • Use best practices to understand Deployment System and reduce waste Deployment System • Leadership is key • Permanent structures and processes/systemic approach • Dedicated resources
- 53. Analytic Insights Questions & A Answers 53
- 54. Session Feedback Survey 54 1. On a scale of 1-5, how satisfied were you overall with this session? 1) Not at all satisfied 2) Somewhat satisfied 3) Moderately satisfied 4) Very satisfied 5) Extremely satisfied 2. What feedback or suggestions do you have? (free form text) 3. On a scale of 1-5, what level of interest would you have for additional learning on this topic (articles, webinars, collaboration, training) 1) No interest 2) Some interest 3) Moderate interest 4) Very interested 5) Extremely interested
- 55. Upcoming Breakout Sessions 2:25 PM – 3:25 PM 9. Getting the Most Out of Your Data Analyst John Wadsworth, VP, Technical Operations Health Catalyst * This is a hands-on session 10. How to Make Analytics a Strategic, C-Level Imperative Jon Brown, VP and Associate CIO, Mission Health Gene Thomas, VP & CIO, Memorial Hospital Gulfport 11. Creating Physician Engagement Bryan Oshiro, MD, CMO, Health Catalyst Chris D. Spahr, MD, Enterprise Quality Executive, CHW 12. User Group Kickoff & New Product Roadmap Thomas D. Burton, SVP, Co-Founder, Health Catalyst Steve Barlow, SVP & Co-Founder, Health Catalyst Holly Rimmasch, Chief Clinical Officer, Health Catalyst * This is an interactive feedback session 55 Location Grand Ballroom D Grand Ballroom A Savoy Venezia
Editor's Notes
- Order – Content – Analytic - Deployment
- The first system, analytic, is the Health Catalyst core competency. This is where we standardize the way we measure things, including our calculations and definitions. It’s also where the enterprise data warehouse and data visualizations live.
- Each of the many databases on campus has reporting capabilities. There is a queue of report writing requests with each system. Report consumers are left to do th
- Your table host is handing out to each of you an Enterprise Shopping Model card that looks like this.
- Invite team members to map their shopping needs to the Enterprise Shopping Model cards just distributed. Give team members about 1 minutes to
- Let’s have a quick show of hands How many of you thought that was easy? How many were frustrated? How many gave up?
- For this next exercise you will use the Adaptive Shopping Model card being passed around.
- Now let’s walk through each of the three systems. The first system, content, involves standardizing the medical knowledge work. Even when a new study comes out and identifies best practices, it can take years for physicians to integrate the new knowledge into everyday practices. By standardizing knowledge assets, such as order sets, intervention criteria, value stream maps, and patient safety protocols, we can improve the speed at which new medical knowledge becomes everyday practice. This includes a consistent standard method for gathering evidence, evaluating that evidence, and integrating it into care delivery.
- Indicate what year the induction evidence was first communicated. Each of the many databases on campus has reporting capabilities. There is a queue of report writing requests with each system. Report consumers are left to do th
- How many of you thought this was the three? Defect Waste – easy to make an error – selecting the wrong number 3 - click for animation Workflow waste – no apparent way to work through the sequencing task.
- The first system, analytic, is the Health Catalyst core competency. This is where we standardize the way we measure things, including our calculations and definitions. It’s also where the enterprise data warehouse and data visualizations live.
- Each of the many databases on campus has reporting capabilities. There is a queue of report writing requests with each system. Report consumers are left to do th
- This time the rules are a little different.
- Improved Population Health Care delivery is evidenced based, improvements in cost and quality are scalable and sustainable Improved clinical effectiveness Reduced waste Improved patient safety By applying all of the steps of the analytic, deployment, and content systems, we can truly ignite change in throughout all systems of care delivery. And by igniting change through the analytic, deployment, and content systems, we can provide sustainable and scalable solutions that will result in improved outcomes, reduced waste, and increased patient safety.
- Follow up group participation 1Would you like to participate in a follow up group on this topic that would meet 2-3 times next year to share progress, challenges and best practices? (Yes, No)
- Follow up group participation 1Would you like to participate in a follow up group on this topic that would meet 2-3 times next year to share progress, challenges and best practices? (Yes, No)