Making Effective Decisions in Times of Uncertainty and Change: What Boards Need to Know

Transcription

1 Making Effective Decisions in Times of Uncertainty and Change: What Boards Need to Know 1 Introductions Pam Arlotto President & CEO Maestro Strategies 34 year track record as a healthcare industry consultant, thought leader and entrepreneur Consulting clients include: regional clinical integration networks, leading healthcare providers, software and services providers, health information exchanges, certification agencies and associations Frequent speaker and author, HIMSS all time best selling series on HIT Return on Investment, winner HFM article of year, featured NPR & Wall Street Journal Fellow and Past National President of HIMSS Board member of the Georgia Tech Foundation and former Board member The Wallace H. Coulter Department of Biomedical Engineering at the Georgia Institute of Technology & Emory University School of Medicine and faculty of UAB Healthcare Informatics program. She also serves on Advisory Boards for several privately held healthcare companies 2 1

2 Introductions Susan Irby Practice Leader Business Intelligence Over 28 years serving healthcare in the provider arena as well as consultant to the industry BI Practice Leader fro Maestro, working with clients to develop and execute strategies around strategic decision making and Business Intelligence Industry pioneer in Decision Support at Alta Bates (Sutter Health) Contributor to HIT Return on Investment series and developer of Maestro s ROI Toolkit Former adjunct faculty member at UAB Healthcare IT, lecturing in decision support 3 About Maestro Orchestrating Change Maestro Strategies combines strategic and operational insight with deep understanding of advanced information technologies and analytic tools to help our healthcare clients execute strategic priorities and accelerate value creation 4 2

3 9/9/2014 Topics Set the Stage Change and Complexity Discuss a Decision Making Framework Review the Board s Role Example: Emergency Department, A Healthcare Microcosm Understanding new decision making tools business intelligence & analytics Creating a BI Strategy 5 Critical Success Factors 5 Innovate Transform Change 2014 Maestro Strategies, LLC Page 6 3

4 Transformation of the Business Model Our careers, dreams and strategic plans are pinned to this graph The next era will be a messy transitional phase that will kill any organization whose leaders get the mix wrong As reimbursement changes (and this is happening very quickly), we are all beginners again. This will require different skill sets, different mind sets and different business models Source: Joe Flower, Healthcare Futurist to VHA Georgia Trustee Institute, May Transformation of the Business Model The Healthcare Industry is Simultaneously Creating scale through consolidation, mergers, employment of physicians and new collaboratives Redesigning primary care Rethinking service lines to include new coordinated care models with internal and external partners Developing care protocols to standardize the delivery of care Focusing on performance, reducing cost, improving access and enhancing outcomes Implementing electronic health records and other advanced information technologies Incorporating wellness, prevention and chronic disease management strategies and practices Defining new patient experiences and becoming patient centered Accepting risk and accountability for the management of population health 8 4

5 Transformation of the Business Model IDN Owned Assets Continuum of Care Preventative & Clinical Services Hospital Post Acute & Other RX, DME & Other Volume to Value Implications Clinic & Physician Practices Emergency & Urgent Care** Ambulatory & Outpatient Care Acute Care LTAC, LTC & SNF Blurring Lines Between Payers & Providers Hospice Home Health Retail Care DME, RX Different Accountabilities & Risks Patient referred to IDN by non IDN PCP Testing Ordered Rehab Ordered Rise of Integrated Care Management ACOs, PCMHs, Narrow Networks, & Bundled Payment Structures Increased Vertical & Horizontal Consolidation Affiliated/NonAffiliated Continuum of Care Retail Healthcare & Consumer Preventative & Clinical Services Hospital Post Acute & Other RX, DME & Other Choice Clinic & Physician Practices Emergency & Urgent Care** Ambulatory & Outpatient Care Acute Care LTAC, LTC & SNF Cost Reduction & Variation Home Health Retail Elimination DME, RX Hospice Care 9 Transformation of the Business Model Chuck Lauer, Former Publisher of Modern Healthcare and an Author, Public Speaker and Career Coach I speak to at least one healthcare CEO every day and I have to tell you: From coast to coast, I am seeing something akin to panic right now. Highly experienced, talented and smart leaders, who used to move ahead of the curve, seem completely paralyzed..many of them are holding off on making any major decisions about the future. That is a mistake. As a healthcare executive, you have to deal with a lot of the unanswered questions ahead..you need to be preparing your institution for the future, because the future will come sooner than you think. 10 5

6 The Reality. Each healthcare organization is at a different point in their journey, and has unique challenges, problems to solve, opportunities for change and decisions to make Accountable Care Population Health Management, Risk Management, Innovation Clinical Integration Hospital/physician alignment, Care Coordination/standardization & Analytics Consolidation Mergers, Acquisitions, Shared Services, & Partnerships 11 The Reality. Continuously sensing changes in market forces and responding with incremental improvements in current business model while simultaneously anticipating radical changes in industry dynamics and responding with new or breakthrough business models Source: The Agile Enterprise,

7 13 15 Years Ago. Newspaper leaders knew dramatic change was underway but didn t rethink their model Newspapers were comfortable as monopoly or oligopoly businesses allowing for plodding decisions Newspaper company IT infrastructure was expensive and rigid, while it allowed plodding decisions Newspaper companies bought up other newspaper chains and took on huge debt Capital investment in printing presses was a barrier to entry allowing for newspaper company dominance Source: David Chase, Forbes, 2012 Musicians sell directly to their fans, retailers to their customers, filmmakers to their viewers, product producers to consumers via downloadable physical products 14 7

8 Healthcare s Decision Making Culture Struggling with the pace of change Combining the expert decision making culture of physicians with the consensus based decision making culture of hospitals Limited organizational capacity for managing change/transformation High risk aversion Current management driven hierarchies are about control, stabilization and efficiency Limited sense of urgency for change Uncertainty creates self protection behaviors 15 Healthcare s Decision Making Culture While the opportunities are massive, what s the biggest obstacle to healthcare transformers? It s the preservatives the incumbent healthcare players. That is, the preservatives are trying to protect the status quo, rather than focusing on how to sincerely address the Triple Aim (improve outcomes, reduce cost, improve patient experience. Source: David Chase, Forbes,

9 Healthcare s Decision Making Culture Transforming from siloed hierarchical decision making model is described as running a marathon while having a heart-lung transplant. Vertical process and infrastructure silos must evolve to collaborative decision making structures while maintaining day-to-day operations Source: The Agile Enterprise, 2005 Embrace the high velocity of change Establish a single minded focus on the patient and unrelenting pursuit of value Minimize the action needed to achieve value Reduce time to value

10 The Cynefin (ku-nev-in) Decision Making Framework Complex Complicated Unordered CE Many competing ideas Experimentation Emerging Practices Unknown Unknowns Chaotic disorder C E Analysis, Experts Good Practices Known Unknowns Simple Ordered C E Many decisions to make and no time to think Novel Practices Unknowables C = E SOP Best Practice Known Knowns Source: HBR, Snowden and Boone, The Cynefin (ku-nev-in) Framework Stable, with Complex consistent cause and Complicated effect relationships The right answer CE is self evident and undisputed C E Defined Many best competing practice ideas Analysis Experimentation Experts All parties Unknown share Unknowns common understanding Known Unknowns Limited change Chaotic C E Many decisions to make and no time to think Unknowables disorder Simple C = E SOP Best Practice Known Knowns Source: HBR, Snowden and Boone,

11 21 Insert illustrative allusion We are not following a linear design We are creating a model and then using the next three phases to pressure test it Simple Decision-Making Style Sense-Categorize-Respond Command and control Past experience, training and previous success drives perspective Decisions are easily delegated Automation of functions is straightforward Frequent communication is not necessary Source: HBR, Snowden and Boone,

12 The Cynefin (ku-nev-in) Framework Complex CE Many competing ideas Experimentation Unknown Unknowns Complicated C E Analysis, Experts Good Practices Known Unknowns disorder Clear cause and effect relationships, not everyone can Chaotic Simple see Contains multiple C E right answers or options C = E Need Many data, decisions expertise to make and analysis Best Practice and no time to think SOP Unknowables Known Knowns Source: HBR, Snowden and Boone, Readmission Reduction No silver bullet 24 12

13 Insert illustrative allusion We are not following a linear design We are creating a model and then using the next three phases to pressure test it Complicated Decision-Making Style Sense-Analyze-Respond Detailed planning and teamwork External and internal subject matter experts Analysis of data Listen to conflicting advice Cost-Benefit to finding right decision Targeted communication Source: HBR, Snowden and Boone, The Cynefin (ku-nev-in) Framework Complex CE Many competing ideas Experimentation Emerging Practices Unknown Unknowns disorder Complicated C E Analysis Experts Known Unknowns Relationships between cause and effect are unclear Chaotic Simple Patterns must emerge Experimentation, C E trial and error C = E Many decisions to make Best Practice Major change and no time to think SOP Unknowables Known Knowns Source: HBR, Snowden and Boone,

14 27 Insert illustrative allusion We are not following a linear design We are creating a model and then using the next three phases to pressure test it Complex Decision Making Style Probe-Sense-Respond Recognize- unpredictability and flux are the norm Emerging practices and experimentation Frequent interaction and communication Be open to idea generation Most businesses have shifted here Source: HBR, Snowden and Boone,

15 The Cynefin (ku-nev-in) Framework No relationships Complex between cause Complicated and effect Search for right answers is pointless CE C E Many Out-of-control competing and ideas turbulent Analysis Too Experimentation much to do, many decisions to Experts make and no time to Unknown Unknowns Known Unknowns think Chaotic C E Many decisions to make and no time to think Novel Practices Unknowables disorder Simple C = E Best Practice SOP Known Knowns Source: HBR, Snowden and Boone,

16 Walgreens became the first-ever chain retailer to announce that it would become a direct provider of primary care services --- an easilyaccessible medical home for millions of Americans suffering from chronic conditions that require preventative or ongoing care. Source: ThinkProgress, April 4, Insert illustrative allusion We are not following a linear design We are creating a model and then using the next three phases to pressure test it Chaotic Decision Making Style Act-Sense-Respond Act to restore order, staunch the bleeding, command and control No time to ask for input Look for what works instead of seeking the right answers Clear, direct, broadcast communications Source: HBR, Snowden and Boone,

17 Insert illustrative allusion We are not following a linear design We are creating a model and then using the next three phases to pressure test it Innovation Decision Making Style Act-Sense-Respond Innovation Disruptive change feels chaotic Risk averse, complex organizations will work to reverse the impact of disruption Innovation must be managed through a separate and unique process Source: HBR, Snowden and Boone, The Cynefin (ku-nev-in) Decision Making Framework Complex CE Many competing ideas Experimentation Unknown Unknowns Complicated C E Analysis Experts Known Unknowns Chaotic disorder Command and control style Simple C E Many decisions to make and no time to think Unknowables C = E Best Practice SOP Known Knowns Source: HBR, Snowden and Boone,

18 35 The Cynefin (ku-nev-in) Decision Making Framework Complex Complicated Unordered Chaotic disorder Simple Ordered Source: HBR, Snowden and Boone,

19 Take-Aways for Board Members Multiple decision making styles are necessary Most healthcare leaders are trained in right sided decision making, left sided requirements often create anxiety Leadership (Inspiration, Creativity & Change) is required of left sided decisions Adept leaders will learn to identify the type of decision that is needed and modify their own behaviors and decision making approach Complex decisions will require new tools, methods and information Boards will need to modify decision making structures to become more agile and responsive to decision types

20 Information Driven Decision Making Enterprise Performance Improvement Population Health Management 39 What is Business Intelligence? Business Intelligence (BI) refers to the strategies, skills, processes, technologies, applications and practices used to support decision making and consists of: A disciplined process system that collects, integrates, analyses and presents business information to support better business decision making An ecosystem where decision makers receive information that is reliable, secure, consistent, understandable, easily manipulated and timely...facilitating more informed decision making Information Enabled Decisions Right Time Right Information Right Format 40 20

21 Why Analytics? It Changes the 80/20 Rule Without Analytics With Analytics 20% Analysis 80% Data Gathering 40% Action! 20% Data Gathering 40% Analysis Return on Investment For some individuals, the data gathering workload may be reduced from weeks to minutes. What actions would they be enabled to take? 41 The Universe of Healthcare Data In the past, organizations have focused on data inside the four walls of the hospital. Now we must use data from a variety of sources and setting to get a true picture of what is happening to patients and populations. Source: Health Care DataWorks 42 21

22 Where Are We Today The Typical Health System Thousands of Hours of Manual Labor Nursing ICU ED Dashboard Dashboard Dashboard CBO Dashboard Surgery Dashboard VBP Dashboard Reports Access Departmental Analytics Initiatives Manual & Semi-Manual DM Essbase Hyperion Diver Cerner Insight Cognos Invision Ad hoc Signature Ad hoc Crimson Surgery Compass Lawson TSI Premier Lab Cerner eclinical Invision Signature ERP Surgery Kronos Morrissey Vision VisionW Prism Source: Health Care DataWorks 43 Maestro s BI Success Dimensions Maestro has identified five BI Success Dimensions or critical success factors. Key questions we help you answer include: What are the enterprise business drivers for Analytics? How are strategic and operational decisions made today? What will need to change? How will data assets be optimized across the Enterprise? Who coordinates BI initiatives? What kinds of talent are needed? Do we have an integrated, logical infrastructure? What systems, applications and tools are needed? Architecture, Technology & Tools Leadership, Organization & Skill Sets Enterprise BI Vision & Strategic Direction BI Success Dimensions Data Governance & Data Stewardship Decision Making Culture & Readiness 44 22

23 Maestro Closes the Gaps in Maturity Capable Analytically competent posess tools and use analytics, but have not systematized analytics as part of strategy execution Leader Use analytics across the enterprise imbedded in the fabric of management; analytics and data are a strategic asset and a competitive advantage Aspiring Appreciate the value of analytics, but are struggling with evolving to an analytic organization Localized Analytics and reporting exist in some pockets of the organization; data are in silos Beginner Not data driven and rely mostly on gut feel to make decisions. Organization not asking analytics questions or lacks data to answer them 45 Sample Progression Beginner to Leader Q4 Q1 Q2 Q3 Q4 Q1 Q2 Q3 Q4 Q1 Q2 Q3 Q4 Q1 Q2 Q3 Q4 Q1 Q2 Q3 Strategy Aspiring Capable Leader Culture Localized Aspiring Capable Leader Data Stewardship Beginner Localized Aspiring Capable Organization Localized Aspiring Capable Leader Technology Beginner Localized Aspiring Capable Leader 46 23

24 Success Dimension: Enterprise BI Vision & Strategic Direction As organizations move from volume-based to value-based reimbursement, Business Intelligence and Analytics will support execution of key strategies by providing descriptive, predictive and prescriptive analytics to enhance decision making Capable Beginner Pilot Projects Operational Reporting Localized Service Line/Portfolio Analysis Evaluate physician/provider productivity Provide cost/utilization analysis by patient Evaluate physician/provider profitability Aspiring Effective tracking and reporting of referrals Initial analysis and modeling of outcomes-based reimbursement Adherence to pathways & protocols Contract and risk analysis Data mining ondemand, ad-hoc Self-serve Health Analytics Understand true cost of services with granularity Model effects of change in practice patterns Model effects of changes in market share, population growth, population demographics, etc. Understand use of/capabilities to leverage assets Risk identification and stratification Year 1 Year 2 Year 3 Year 4 Leader Import external data to better understand market needs and opportunities Population Health Management Analyze data to Tell the Value Story Support detailed analysis of the population Year 5 47 Success Dimension: Decision Making Culture & Readiness Complicated problems can be solved with Little Data - Retrospective - Descriptive Complex problems need Business Intelligence and Analytics (BI) - Near Real-Time - Predictive Chaotic problems need Big Data, combined with Predictive and Prescriptive Analytics - Innovative - Disruptive - Iterative 48 24

25 Success Dimension: Data Governance & Data Stewardship Strategic Level Executive & Strategic Oversight, Program Prioritization and Sponsorship Program Management Level Functional Level Data Program Administration & Steering Committee. Responsible for coordination, communication & facilitation of Program components, initiatives and value across the enterprise. Data stewards or analysts assigned to key functional units. Responsible for consistent definition and use across functional units. Operating Unit Level Data definers, users and producers who use data as part of their jobs. 49 Success Dimension: Leadership, Organization & Skill Sets Today Tomorrow Vision Decentralized No one manages or coordinates. Efforts spread across organization Centralized One department manages all activities Hub & Spoke Cross functional team in central position supports local efforts Dandelion Multiple hub & spoke, Many divisions or related Organizations Holistic Everyone uses BI consistently 50 25

26 Success Dimension: Architecture, Technology & Tools Multiple Options EMR, Revenue Cycle, ERP vendors Build your own from scratch Point solutions Build with generic, reusable enterprise healthcare data model Many new healthcare players Wild Wild West 51 How to Execute on Strategy? Demonstration Project Establish a test and respond fast culture through demonstration projects. Why? Demonstrating BI Capabilities & Investments Required through a Demonstration Project will allow you to: Avoid over- committing resources and dollars Understand the work required to clean up data, integrate systems, make data stewardship decisions and set priorities Integrate with other methods: PM, LSS, Costing, Change Management, etc. Define metrics and measure for maximum impact Produce results while building out enterprise capabilities Demonstration Projects Reduce Chaos 52 26

27 How to Execute on Strategy? BI is NOT an IT Project IT Project: the future is defined at beginning of project and a plan is developed Analytics Project: the future is discovered during the project and is iterative Define the need Budget for technology Action: Define the future Define the question Vendor evaluation Funding Knowledge Data Implementation Information 53 Page 53 Take-Aways for Board Members Analytics is not an IT project Invest in analytics capabilities to support informationdriven decision making Analytics capabilities will be evolutionary, not revolutionary Effort will be required to build trust in the quality of data Move towards an enterprise center of gravity around analytics to enable information-driven decision making permeate the culture 54 27

28 Yesterday, Today and Tomorrow Walmart took 40 years to get their data warehouse to 400 terabytes Facebook probably generates that every 4 days Less than 1% of today s available data is analyzed Data is expected to grow 50x in next decade Big data offers $300 billion in value to healthcare 55 Maestro Strategies is a nationally recognized healthcare management consulting firm. Our team offers an unparalleled track record covering over twenty-five years in healthcare decision support, business intelligence, informatics and analytics. Our team includes: Pioneers in development of financial and clinical decision support systems CIOs, Enterprise BI Directors, Physician Executives, Professional Services and Vendor Executives with responsibility for Financial and Clinical BI and Decision Support Researchers who focus on the BI & Analytics Market Founded in 1989, Maestro Strategies works with prominent providers including Integrated Delivery Networks, Ambulatory Clinics, Academic Medical Centers and Regional Health Networks to transition from volume to value. Clients also include Health Information Exchanges, Payors, Suppliers to the market and Business Coalitions Questions or Comments: Pam Arlotto parlotto@maestrostrategies.com x101 Speaking/Retreats for Boards & Leadership Teams 56 28