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

2. 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

3. 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

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

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

6. 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

7. The History of Risk Management
The Evolution of Risk Management
1700s Modern theory of probability
1980s Medical malpractice crisis; high premiums, partial coverage COSO
1999
IOM report; focus on patient safety
2004
COSO publishes Enterprise Risk Management Integrated Framework
2009
ISO standards released
Early Risk Management
Traditional Risk Management
Enterprise Risk Management
1700s – Foundation laid for modern theory of probability
“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

8. 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

9. 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

10. 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

11. 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

12. 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

13. Introduction to Value-Driven Clinical Risk Management at Stanford13

14. 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

15. 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

16. 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

17. 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

18. Financial and Other Outcomes18

19. 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

20. Premium Benchmarks PEARL vs. University of Michigan 20% lower
FIN
Premium Benchmarks
Aon Premium Benchmarking Study
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

21. 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

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

23. 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

24. Platform for CRM: Simplified24

25. 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

26. 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

27. 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

28. 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

29. 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

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

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

32. 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

33. 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 •
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34. 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

35. 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

36. 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

37. 37

38. 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

39. 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

40. The Value of Risk Management
Concluding Remarks 40