The Power of Data: Igniting, Scalable and Sustainable Change

1. The Power of Data:Igniting, Scalable and Sustainable Change John L. Haughom, MD May 2014

2. 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? http://www.healthcatalyst.com/ebooks/healthcare-transformation-healthcare-a-better-way/

3. Poll Question On a Scale of 1-5, how would you rate your organization’s ability to manage complexity? • 5 – 8% • 4 – 26% • 3 – 45% • 2 – 17% • 1 – 4%

4. Implementing an Effective System of Production in Healthcare Analyticsystem Scalable and sustainable outcomes Deploymentsystem Contentsystem

5. Analytic System Components

6. Using Data Appropriately Fear Micromanage Kill the Messenger (denial, shift blame) Filter the data (game the system) Scherkenbach’s Cycle of Fear

7. Using Data: Learning vs. Acountability • Learning • Knowledge used by care delivery organizations and improvement teams • Nourishes intrinsic motivation • Result centric • Accountability • Knowledge used by consumers, regulators, other physicians, etc. • May encourage gaming the system • Reward centric Measure, manage & improve the system Suboptimize Game the number Berwick DM, James B, Coye MJ. The connections between quality measurement and improvement. Medical Care. 2003; 41(1Supplement): 30-38.

8. Enterprise data model EDW FINANCIAL SOURCES (e.g. EPSi, Lawson, PeopleSoft) DEPARTMENTAL SOURCES (e.g. Apollo) Patient Bad Debt Provider Provider Encounter Survey ADMINISTRATIVE SOURCES (e.g. API Time Tracking) Cost Charge Census Facility House Keeping Diagnosis Procedure Employee EMR SOURCES PATIENT SATISFACTION (e.g. NRC Picker) Catha Lab Time Keeping more transformation less transformation enforced referential integrity

9. Dimensional data model Redundant data extracts FINANCIAL SOURCES (e.g. EPSi, Lawson, PeopleSoft) DEPARTMENTAL SOURCES (e.g. Apollo) Regulatory Labor Productivity Revenue Cycle ADMINISTRATIVE SOURCES (e.g. API Time Tracking) Pregnancy Oncology Asthma Heart Failure Diabetes Census EMR SOURCE PATIENT SATISFACTION SOURCES (e.g. NRC Picker) more transformation less transformation

10. Late-Binding™ Data Warehouse Metadata: EDW Atlassecurity and auditing FINANCIAL SOURCES (e.g. EPSi, Peoplesoft, Lawson) DEPARTMENTAL SOURCES (e.g. Apollo) Common, linkable Vocabulary FinancialSource Marts DepartmentalSource Marts Readmissions AdministrativeSource Marts PatientSource Marts PATIENT SATISFACTION SOURCES (e.g. NRC Picker, Press Ganey) ADMINISTRATIVE SOURCES (e.g. API Time Tracking) Diabetes Sepsis EMR Source Marts HRSource Mart EMR SOURCE Human Resources (e.g. PeopleSoft) More transformation Less transformation

11. Early versus late binding of Data DATAANALYSIS SOURCE DATA CONTENT CUSTOMIZED DATA MARTS SOURCE MARTS MATERIALS MANAGEMENT SUPPLIES SUPPLIES QlikView CLINICAL CLINICAL DISEASE REGISTRIES Microsoft Access/ODBC FINANCIAL FINANCIAL INTERNAL COMPLIANCE AND PAYER MEASURES Web applications HR HR CLINICAL EVENTS Excel OTHERS OTHERS OPERATIONAL EVENTS STATE SAS, SPSS STATE RESEASRCH REGISTRIES 5 6 1 4 ACADEMIC 2 3 Et. al EXTERNAL ACADEMIC early binding low volatility vocabulary or business rules? late binding high volatility vocabulary or business rules? Data rules and vocabulary binding points

12. Automating data gathering DATA CAPTURE • Acquire key data elements electronically • Assure data quality • Integrate data capture into workflow DATA ANALYSIS DATA PROVISIONING • Interpret data • Discover new information in the data (data mining) • Evaluate data quality • Move data from transactional systems into the data warehouse • Build visualizations for use by clinicians • Generate external reports (e.g., CMS)

13. Population Health Management Paradigm shift Inpatient Inpatient Clinic care Hospice Home Skilled nursing facility Home healthcare Outpatient Cemetery Acutecare-centric management Population-centric management

14. Population Health Management Anatomy of Healthcare Delivery Symptoms Screening & preventive Prevention and treatment knowledge assets Management of Preventive, Ambulatory, Acute Medical, Invasive & PAC Modules Health maintenance and preventive guidelines Diagnostic work-up Diagnostic algorithms Utilization management knowledge assets Diagnostic Algorithms, Triage Criteria, Referral & Intervention Indications Home(patient portal) Triage to treatment venue Triage criteria Admission order sets Admission order sets Clinic Carenon-recurrent Clinic Care chronic Invasive Medical Invasive Surgical Acute Medical IP Med-Surg Acute Medical IP ICU Indications for intervention Treatment and monitoring algorithms Indications for referral Standardized follow-up Substance selection Pre-procedure order sets Substance preparation Substance selection Supplementary order sets Invasive* subspecialist Chronic disease subspecialist Clinical supply chain management Bedside care Clinical ops procedure guidelines and patient injury prevention * To Invasive Care Processes Treatment and monitoring algorithms Procedure Post-procedure order sets Bedside care practice guidelines, risk assessment and patient injury prevention protocols, bedside care procedures, transfer and discharge protocols Post-procedure care Post-acute care order sets IP (SNF, IRF) Home health Hospice Discharge

15. Population Health Management Clinical Integration hierarchy - care process families Outpatient Inpatient SNF Home Health Hospice Home ClinicCare Hyperlipidemia Acute Myocardial Infarction(AMI) Cardiac Rehab CoronaryAtherosclerosis Percutaneous Intervention(PCI) Ischemic Heart Disease care process family Coronary Artery Bypass Graft (CABG)

16. Population Health Management Clinical Integration hierarchy - clinical programs Inpatient SNF Home Health Hospice Home ClinicCare Outpatient Cardiovascular clinical program Heart Rhythm Disorders care process family Ischemic Heart Diseasecare process family Heart Failurecare process family Vascular Disorders care process family

17. Clinical Integration hierarchy Clinical programs – ordering of care CV W&C GI Neuro Sciences Musculo-skeletal General Med Resp-iratory Primary Care Surgery Oncology Peds Spec Mental Health care process families e.g., Heart Failure care process families e.g., Pregnancy care process families e.g., Lower GI Disorders care process families e.g., Obstructive Lung Disorders care process families e.g., Spine Disorders care process families e.g., Joint Replace-ment care process families e.g., Infectious Disease care process families e.g., Diabetes care process families e.g., Urologic Disorders care process families e.g., Breast Cancer care process families e.g., Peds CV Surg care process families e.g., Depression

18. Clinical Integration constructClinical support services – delivery of care CV W&C GI Neuro Sciences Musculo-skeletal General Med Resp-iratory Primary Care Surgery Oncology Peds Spec Mental Health Care Process Families e.g., Heart Failure Care Process Families e.g., Pregnancy Care Process Families e.g., Lower GI Disorders Care Process Families e.g., Obstructive Lung Disorders Care Process Families e.g., Spine Disorders Care Process Families e.g., Joint Replace-ment Care Process Families e.g., Infectious Disease Care Process Families e.g., Diabetes Care Process Families e.g., Urologic Disorders Care Process Families e.g., Breast Cancer Care Process Families e.g., Peds CV Surg Care Process Families e.g., Depression Diagnostic Clinical Support Services (workflow models) (e.g., pathology and laboratory medicine, diagnostic radiology) Therapeutic Clinical Support Services (workflow models) (e.g., pharmacy, transfusion medicine, respiratory therapy, physical, occupational, speech therapy) Ambulatory Clinic Clinical Support Services (workflow models) (e.g., primary care clinics, chronic disease specialty clinics, subspecialty clinics) Acute Medical Clinical Support Services (workflow models) (e.g., Emergency Care, ICU/CCU/NICU/PICU, General Med-Surg) Invasive Clinical Support Services (workflow models) (Interventional Medical [e.g., cath lab, interventional radiology, GI lab, L&D, rad onc] and Surgical [e.g., amb, IP])

19. Value Stream Protocols to Help Prevent Patient Harm

20. Mapping – admin codes to clinical

21. Population Health Management Medicare FFS payments by venue – 2008-2012 Inpatient SNF LTCH/IRF Home Health Hospice Clinic Care Outpatient $ 53 Billion 4.1% $ 133 Billion 10.3% $ $ 90 Billion 6.9% $ 152 Billion 11.8% 447 Billion 34.5% $ 48 Billion 3.7% 372 Billion 28.7% $

22. Top 32 care process families account for 80% of the opportunity Inpatient per case KPA Top 10 care process families account for over 40% of the opportunity Percent of total resources consumed Care process families by resources consumed (high to low)

23. In Summary… • Organizations need a comprehensive framework to help them implement a solid strategy and foundation for the future • The Three Systems (Analytic, Deployment, Content) is an example of a comprehensive framework that can lead to future success • Use data primarily for learning rather than judgment • The late binding data model is the quickest to set up, cheapest to maintain, and most importantly, offers the flexibility required to support continuous improvement • Automating data distribution allows frontline workers to become self-service gatherers and analyzers of data • The Anatomy of Healthcare Delivery and Clinical Integration Hierarchy can help organizations focus their improvement efforts and maximize value for the investment

24. Coming Attractions (next webinar) • The Analytic System: Bringing it all together • Understanding variation and the role of SPC charts in quality improvement • A thoughtful approach to improvement • Finding meaningful patterns in the data • Demonstration of the power of modern analytical tools • We have come along way, and yes, clinicians can use these tools!

25. Poll Question • On a Scale of 1-5, how effective is your organization’s analytical strategy and capability (as described today)? • 5 – 4% • 4 – 16% • 3 – 31% • 2 – 35% • 1 – 14%

26. Poll Questions • Does your organization have a robust strategy to identify high value improvement opportunities? • 5 – 14% • 4 – 13% • 3 – 37% • 2 – 30% • 1 – 6%

27. Thank You Upcoming Educational Opportunities Data Driven Care: The Key to Accountable Care Delivery from a Physician Group Perspective • Date: May 29th • Presenter: Dr. Gary Spencer, CMO, Crystal Run Healthcare, Luke Skelly, Health Catalyst • Register at http://healthcatalyst.com/ • Accountable Care Transformation: The Four Building Blocks of Population Health Management • Date: June 4th, 2014
Presenter: Dr. David Burton, MD, Chairman, Health Catalyst • Time: 1:00 - 2:00 PM ET • Register at http://healthcatalyst.com/ • 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: http://www.healthcatalyst.com/news/healthcare-analytics-summit-2014 • For the New World of Healthcare, A Declaration of Independence Is Only the Beginning • On April 28, 2014, Dr. Daniel Craviotto, Jr. published an editorial in the Wall Street Journal, “A Doctor’s Declaration of Independence,” in which he argued that it is time to “defy healthcare mandates issued by bureaucrats not in the healing profession.” • Read Dr. Haughom’s response on how the medical profession needs to move beyond frustration and cynicism to create a vision for a better, more effective healthcare system. http://healthcatalyst.com/ For Information Contact: John.Haughom@healthcatalyst.com

28. OBJECTIVE Obtain unbiased, practical, educational advice on proven analytics solutions that really work in healthcare. The future of healthcare requires transformative thinking by committed leadership willing to forge and adopt new data-driven processes. If you count yourself among this group, then HAS ’14 is for you. MOBILE APP • Access to a mobile app that can be used for audience response and participation in real time. Group-wide and individual analytic insights will be shared throughout the summit, resulting in a more substantive, engaging experience while demonstrating the power of analytics.