The Value of Risk Management The Stanford Experience Jeff Driver Chief Executive Officer The Risk Authority of the Stanford University Medical Network

Objectives: Describe what is meant by strategic risk management, value-driven enterprise clinical risk management, and return on risk strategy Learn a financially successful, translatable, and scalable approach to managing clinical risk through the Stanford example Identify risk management programmatic outcome measures and expected five year results based on the Stanford Clinical VDERM model 2

Agenda: Context: About Stanford University Medical Center CNTX Context: About Stanford University Medical Center History of Risk Management Introduction to Value-Driven Risk Management at Stanford Financial and Other Outcomes Clinical Risk Management Concluding Remarks HISTORY VDRM FIN CRM CR 3

Context: The Stanford University Medical Network CNTX Context: The Stanford University Medical Network 4

Context: Risk Management Services CNTX Context: Risk Management Services Risk Management Services 5

Agenda: Context: About Stanford University Medical Center CNTX Context: About Stanford University Medical Center History of Risk Management Introduction to Value-Driven Risk Management at Stanford Financial and Other Outcomes Clinical Risk Management Concluding Remarks HISTORY VDRM FIN CRM CR 6

The History of Risk Management The Evolution of Risk Management 1700s Modern theory of probability 1980s Medical malpractice crisis; high premiums, partial coverage 1985 - COSO 1999 IOM report; focus on patient safety 2004 COSO publishes Enterprise Risk Management Integrated Framework 2009 ISO 31000 standards released Early Risk Management Traditional Risk Management Enterprise Risk Management 1700s – Foundation laid for modern theory of probability 1955-1964 “Modern” Risk Management, self-protection, insurance 1990s Risk Management becomes a “corporate affair” 2002 Sarbanes-Oxley Act & National Patient Safety Goals (The Joint Commission) 2008 National HealthCare Quality Report Risk Management profession is in status-quo mode 2013 AIG Study “Clear need to improve patient safety to provide an ROI” 7

The History of Risk Management Early Risk Management Early Risk Management The theory of probability, an instrument for risk management, began in 1654 with a game of dice. All the risk-management tools we employ today stem from the developments between 1654 and 1754. The New Religion of Risk Management, Peter L. Bernstein, Harvard Business Review, March/April (1996): 47-51 8

The History of Risk Management Traditional Risk Management (TRM) Traditional Risk Management focuses on preventing loss through insurance and claims. Traditional Risk Management offers a fragmented view that can be reactive and not focused on business vision and strategy. Early Risk Management TRM is inadequate for the complexities of healthcare and the rapidly changing political and economic environment. Risk Management Handbook for Healthcare Organizations: The Essentials , R. Carrroll, P. Nakamura, 5th Edition, Volume 1 , 2006 9

The History of Risk Management Enterprise Risk Management (ERM) In 1992, in response to financial fraud in the 1980s, the Committee of Sponsoring Organizations of the Treadway Commission (COSO) created a process for examining risk across an entire organization to protect, create shareholder value and make good decisions.* Regulations shaped the COSO process to allow audits, rather than focus on actions to mitigate risk for all losses.** Healthcare has been slow in adopting ERM and there has been little improvement in patient safety. According to a US government report, 44% of all 2008 adverse events were preventable and 1 in 7 experienced an adverse event.*** Early Risk Management *Enterprise Risk Management Handbook For Healthcare Entities, R. Carroll, P. Nakamura, R. Rose, 2nd Edition, 2013 **The End of Enterprise Risk Management, D. Martin, M. Power, AEI-Brookings Joint Center for Regulatory Studies, 2007 *** Adverse Events in Hospitals: National Incidence Among Medicare Beneficiaries, OIG 2010 10

The History of Risk Management Data Analysis for Decision Making The use of data to make good, consistent and transparent decisions is critical to managing future strategic risk.* Pharmaceutical and energy industries have been successful using this. Some examples are: Chevron made $78 billion more** SmithKline Beecham tripled their return from 5:1 to 15:1*** *Rethinking Strategic Risk, H. Ristuccia, Risk Management, April 10, 2013 **Chevron Overcomes the Biggest Bias of All, C. Spetzler, SDG White Paper 2011 ***How Smithkline Beecham Makes Better Resource Allocation Decisions, P. Sharpe, T. Keelin, Harvard Business Review, March – April 1998 11

Agenda: Context: About Stanford University Medical Center CNTX Context: About Stanford University Medical Center History of Risk Management Introduction to Value-Driven Risk Management at Stanford Financial and Other Outcomes Clinical Risk Management Concluding Remarks HISTORY VDRM FIN CRM CR 12

Introduction to Value-Driven Clinical Risk Management at Stanford 13

Risk Management Success/Failure Spectrum Migration from Traditional Risk Management to Value-Driven Risk Management VDRM BEST BETTER BASELINE WORSE “The Merely Useless” WORST “The Worse Than Useless” Risk Management Success/Failure Spectrum Firm builds quantitative methods Inputs are validated with proven statistical methods Additional empirical measurements are used where optimal Portfolio analysis of risk/return is used Quantitative methods are used utilizing some proven components Scope of risk management expands to include more forms of risk Detailed “soft” or “scoring” methods are used or misapplied quantitative methods are used but not counted on by management May be no worse that baseline except it wastes time and money Management’s intuition drives risk assessment and mitigation strategies Formal risk management is not attempted Ineffective methods used with great confidence, even though they add error to evaluation Much effort spent on seemingly sophisticated methods but no objective, measurable evidence that they improve on intuition Methods cause erroneous decisions to be taken that would not have otherwise been made Hubbard, Douglas: The Failure of Risk Management, 2009 14

Building on Traditional and Enterprise Risk Management VDRM Building on Traditional and Enterprise Risk Management Early Risk Management VDERM uses data and decision analysis in the risk process. 15

Stanford’s Formula for Value-Driven Risk Management VDRM Stanford’s Formula for Value-Driven Risk Management FIN Financial and Other Outcomes C&L Claims and Litigation Management CRM Clinical Risk Management 5yrs/49% $ 16

Agenda: Context: About Stanford University Medical Center CNTX Context: About Stanford University Medical Center History of Risk Management Introduction to Value-Driven Risk Management at Stanford Financial and Other Outcomes Clinical Risk Management Concluding Remarks HISTORY VDRM FIN CRM CR 17

Financial and Other Outcomes 18

Risk Management Outcomes FIN Risk Management Outcomes Metric Desired Result Observed Result Comment Reporting Pattern Faster Inconclusive Average incident to report lag is one year Frequency Lower Annual reported claims dropped 29% Closing Pattern Small number of closed claims Severity Some large post-PEARL closed claims Overall Cost 49% reduction over 5 years * Reinvestments in Loss Control Programs vs. Premium Rebates and Holidays 19

Premium Benchmarks PEARL vs. University of Michigan 20% lower FIN Premium Benchmarks Aon Premium Benchmarking Study - 2012 PEARL vs. University of Michigan Premium Benchmarking Study Primary Program Seven Year Average Insurance Premium Compared to Average Insurance Premium (FN1) Premium Compared to Hospital Benchmark (FN2) Stanford Hospital 20% lower 11% lower Stanford Clinics 18% lower Lucile Packard Children’s Hospital at Stanford 13% lower 27% lower Lucile Packard Clinics 32% lower (FN1) Average insurance premium estimates were calculated using the data provided by SUMC and informal indications provided by two carriers per year. (FN2) The Aon benchmark premiums are calculated using the Aon Hospital Professional Liability and Physician Professional Liability Benchmark Analysis. 20

Agenda: Context: About Stanford University Medical Center CNTX Context: About Stanford University Medical Center History of Risk Management Introduction to Value-Driven Risk Management at Stanford Financial and Other Outcomes Clinical Risk Management Concluding Remarks HISTORY VDRM FIN CRM CR 21

Value Driven Clinical Risk Management = International Organization for Standardization ISO 31000 Risk Management Standards + Modern Decision Analysis Science CRM 22

Platform for CRM: ISO 31000 23 CRM Risk Identification Identify sources of risk, areas of impact and consequences. Risk Analysis Understanding the risk and whether it needs to be fully evaluated. Risk Evaluation Compare the level of risk established in the previous stage with the risk tolerance criteria established. Risk Treatment Modification of risk and decision on treatment option. Source: ISO 31000:2009 Relationships between the risk management principles, framework and process. 23

Platform for CRM: Simplified 24

Value Protected & Value Created CRM Platform for CRM - Simplified Five Critical Steps Value Protected & Value Created Figure out what types of future events might prevent or slow the achievement of objectives or enhance the prospects of success. 25

CRM Identify: The Model Methodology The coding of medical malpractice claims is the center of our patient safety model. CODING What sets us sets us apart from other organizations across the country is our deeply coded data, Which is at the center of our patient safety model. Allows us to look closely at patterns of vulnerabilities that start at the bedside, and Translate them into opportunities for improvements in patient safety. 26 26

Identify: Clinical Coding CRM Identify: Clinical Coding Clinical Coding Prioritizes where to focus resources Surgery, OB, ED, nursing, medication issues Frequency and volume, clinical severity, financial losses Focuses on what needs to be fixed Technical: human factors, skills, cognitive issues Communication: provider to provider, provider Identifies who is involved Physicians, nurses, residents, fellows, technicians, etc. Supports resourcing solutions; how can we make it happen Leadership buy-in, financial investment in patient safety initiatives 27

Identify: Using an Accident Causation Taxonomy CRM April 26, 2017 Identify: Using an Accident Causation Taxonomy Major Allegation (based on complaint, 1-1 ratio) Diagnosis-related events Surgical events (non-anesthesia) Medical treatment events Obstetrical events Safety & security events What (is alleged to have) happened delayed dx, missed dx, wrong dx, failure to dx skill based, retained FB, pt management post-op improper placement of C-line, improper choice of tx pregnancy, labor/fetal distress, delivery falls, enviro hazards, assaults (non-employee) Responsible Service (1 primary + secondary) Primary and secondary contributors Includes all providers in a specialty CRNA in Anesthesiology NP in OB Who was the provider/service(s) involved Emergency Service Radiology, Pathology, Nursing Medicine (Gen Med, Cardio/Hem Onc/Hospitalist…) Surgery (Gen Surg, Bariatric/Cardiac/Urology…) OB/GYN, Orthopedics, Neurosurgery Contributing Factors (RN review, multiple) Clinical judgment Clinical systems Communication Technical skill Why it (might have) happened narrow dx focus, no consults, patient monitoring scheduling, reporting results, follow up monitoring med record, informed consent, patient education improper use of equip, inexperience, poor technique How do we actually use this data to compel action? We code the major allegation – Usually do this first, as it is clearly delineated in claims files. Which tells us what is alleged to have happened. Gives us a level of detail to evaluate if it’s a Dx-Related claim, whether it’s delayed, missed, wrong or a failure… etc. We code the Responsible service (both primary and secondary) – This comes next, usually a bit more challenging to identify Which tells us which providers/services were involved If it was an ED case with a wrong diagnosis, we might also be able to And we code Contributing Factors (most exciting, most unique!) Looking at: Clinical Judgment Clinical Systems Communication Technical Skill Which gives insight into WHY it might have happened 28

Value Protected & Value Created CRM Platform for CRM - Simplified Five Critical Steps Determine which risks are most critical and how individual risks are related to each other. Value Protected & Value Created 29

Assess: Sample Risk Register CRM Assess: Sample Risk Register 30

Assess: Sample Heat Map CRM Assess: Sample Heat Map IMPACT LIKELIHOOD 31

Value Protected & Value Created CRM Platform for CRM - Simplified Five Critical Steps Evaluate outcomes and decide which risks need to be addressed Value Protected & Value Created 32

VALUE PROTECTION VALUE CREATION CRM Evaluate: Sampling of Decision Analysis Tools Utilizing decision analysis methodologies throughout the risk evaluative process expands the value proposition of risk programs. VALUE CREATION VALUE PROTECTION Value and Risk Map Probability Assessments Quantified Value Model Waterfall of Value A B C D E F 1 2 3 4 5 Tornado Diagram Strategic Decision Insights Quantified Heat Maps Dashboards/ Monitoring • uu uuuuu uuuuu uu 33

Value Protected & Value Created CRM Platform for CRM - Simplified Five Critical Steps This is where the action is. Develop and follow steps to reduce risks at the top of your list as well as steps to increase potential benefits. Value Protected & Value Created 34

Risk Assessment and Mitigation CRM Risk Assessment and Mitigation Stanford University Medical Center Risk Mitigation Strategies in Process Factors Obstetrics Neurosurgery Orthopedics SHC Nursing LPCH Nursing Clinical Judgment (38%) 6 interventions 2 interventions 4 interventions Technical Skill (26%) 3 interventions Communication (14%) 5 interventions Administration/ System issues (12%) 35

Value Protected & Value Created CRM Platform for CRM - Simplified Five Critical Steps Determine if your risk management process has been effective. Monitor the timeliness and effectiveness of the various outlined steps to reduce risks and boost gains. Value Protected & Value Created 36

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Agenda: Context: About Stanford University Medical Center CNTX Context: About Stanford University Medical Center History of Risk Management Introduction to Value-Driven Risk Management at Stanford Financial and Other Outcomes Clinical Risk Management Concluding Remarks HISTORY VDRM FIN CRM CR 38

Stanford’s Formula for Value-Driven Risk Management VDRM Stanford’s Formula for Value-Driven Risk Management FIN Financial and Other Outcomes C&L Claims and Litigation Management CRM Clinical Risk Management 5yrs/49% $ 39

The Value of Risk Management Concluding Remarks 40