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Continuous Decision Improvement (CDI): Public Health Decision Making for Complex Environments
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Continuous Decision Improvement (CDI): Public HealthDecision Making for Complex Environments
Tomas J. Aragon, MD, DrPHHealth Officer, City & County of San FranciscoDirector, Population Health Division (PHD)San Francisco Department of Public Health
Adjunct Faculty, Division of EpidemiologyUC Berkeley School of Public Health
2014
Tomas J. Aragon, MD, DrPH Health Officer, City & County of San Francisco Director, Population Health Division (PHD) San Francisco Department of Public Health[10pt] Adjunct Faculty, Division of Epidemiology UC Berkeley School of Public HealthContinuous Decision Improvement (CDI): Public Health Decision Making for Complex Environments2014 1 / 25
Outline
1 Introduction
2 Continuous Decision Improvement
3 Example—CDI for self-improvement
4 Summary
Tomas J. Aragon, MD, DrPH Health Officer, City & County of San Francisco Director, Population Health Division (PHD) San Francisco Department of Public Health[10pt] Adjunct Faculty, Division of Epidemiology UC Berkeley School of Public HealthContinuous Decision Improvement (CDI): Public Health Decision Making for Complex Environments2014 2 / 25
Introduction
Overview of CDI Training Curriculum
Curriculum and tools for continuous improvement of public health decision making incomplex environmentsIncorporates public health considerations (HELLP = Health, Ethical, Legal, Logistical,Political)Incorporates understanding of dual-process model (intuition vs. deliberation)
Tomas J. Aragon, MD, DrPH Health Officer, City & County of San Francisco Director, Population Health Division (PHD) San Francisco Department of Public Health[10pt] Adjunct Faculty, Division of Epidemiology UC Berkeley School of Public HealthContinuous Decision Improvement (CDI): Public Health Decision Making for Complex Environments2014 3 / 25
Introduction
Complexity and why it matters
What is a complex system?1 A population of diverse agents, all of which are2 connected, with behaviors and actions that are3 interdependent, and that exhibit4 adaptation and learning.
Why do we care? Complex systems . . .are ambiguous, deceptive, unpredictableare difficult to direct and control (adaptive resistance)can evolve along divergent pathways (silos)can produce “tipping points” (e.g., epidemics)
Tomas J. Aragon, MD, DrPH Health Officer, City & County of San Francisco Director, Population Health Division (PHD) San Francisco Department of Public Health[10pt] Adjunct Faculty, Division of Epidemiology UC Berkeley School of Public HealthContinuous Decision Improvement (CDI): Public Health Decision Making for Complex Environments2014 4 / 25
Introduction
Mitigating and harnessing complexity
Mitigating complexityExpect the unexpected and unintended consequencesExpect and prepare to fail (avoid overconfidence)Be humble and practice humble inquiry
Harnessing complexityStrengthen cooperation by building trust and practicing humilityStrengthen decision making processes (requires trust & humility)See every failure as a learning opportunity (requires humility)Balance exploration (learning) and exploitation (execution)Design for agility, adaptability, and responsivenessDevelop/use “simple rules” that can spread
Tomas J. Aragon, MD, DrPH Health Officer, City & County of San Francisco Director, Population Health Division (PHD) San Francisco Department of Public Health[10pt] Adjunct Faculty, Division of Epidemiology UC Berkeley School of Public HealthContinuous Decision Improvement (CDI): Public Health Decision Making for Complex Environments2014 5 / 25
Introduction
What is the Dual-Process model?
DeliberationIntuition
Tomas J. Aragon, MD, DrPH Health Officer, City & County of San Francisco Director, Population Health Division (PHD) San Francisco Department of Public Health[10pt] Adjunct Faculty, Division of Epidemiology UC Berkeley School of Public HealthContinuous Decision Improvement (CDI): Public Health Decision Making for Complex Environments2014 6 / 25
Introduction
Intuition (naturalistic decision making)
Size-up Imagine Do Size-up
DefinitionFramework for studying how people make decisions and perform cognitively complex functionsin demanding, real-world situations. These include situations marked by limited time,uncertainty, high stakes, environmental constraints, unstable conditions, and varying amountsof experience.
ExamplesPanhandler approaches you on the street asking for money.Driving on city street when suddenly you hear a siren.Fighter pilots in heat of aerial battle: Observe-Orient-Decide-Act (OODA) Loop
Tomas J. Aragon, MD, DrPH Health Officer, City & County of San Francisco Director, Population Health Division (PHD) San Francisco Department of Public Health[10pt] Adjunct Faculty, Division of Epidemiology UC Berkeley School of Public HealthContinuous Decision Improvement (CDI): Public Health Decision Making for Complex Environments2014 7 / 25
Introduction
Deliberation (rational decision making)
Analyze Plan Do Re-analyse
Example: 4D Decision Processa,b (a best practice decision process)1 DEFINE Problem (values, objectives)2 DESIGN Alternatives (creative, complete)3 DECIDE Alternatives (consequences, trade-offs)4 DO (action planning)
a. Parnell GS, et al. Handbook of Decision Analysis. Wiley, 2013b. Parnell GS, et al. Decision Making in Systems Engineering and Management, 2nd Edition. Wiley, 2011
Tomas J. Aragon, MD, DrPH Health Officer, City & County of San Francisco Director, Population Health Division (PHD) San Francisco Department of Public Health[10pt] Adjunct Faculty, Division of Epidemiology UC Berkeley School of Public HealthContinuous Decision Improvement (CDI): Public Health Decision Making for Complex Environments2014 8 / 25
Introduction
Dual-process model is Intuition and Deliberation
Observe
Orient
DECIDE
Act
EnvironmentalResponse
EnvironmentalContext
DEFINE Problem(Values, Objectives)
DESIGN Alternatives(Creative, Complete)
DECIDE Alternatives(Consequences, Trade-offs)
DO (action planing)
EnvironmentalResponse
EnvironmentalContext
OODA Loop 4D Decision Process
Intuition Deliberation
Tomas J. Aragon, MD, DrPH Health Officer, City & County of San Francisco Director, Population Health Division (PHD) San Francisco Department of Public Health[10pt] Adjunct Faculty, Division of Epidemiology UC Berkeley School of Public HealthContinuous Decision Improvement (CDI): Public Health Decision Making for Complex Environments2014 9 / 25
Introduction
The 4D Decision Process in more detail
1 DEFINE problem1 Situational awareness (including HELLP: Health, Ethical, Legal, Logistical, Political)2 Clarify problem or opportunity3 Clarify frame and test assumptions4 Clarify values (What is important to us?)5 Set objectives (What do you really need to accomplish?)
2 DESIGN alternatives1 Think into the future: How did we achieve objectives?2 Brainstorm on alternatives3 Be creative and complete
3 DECIDE alternatives1 Assess consequences (consequence table)2 Consider trade-offs3 Prioritize and select alternatives
4 DO decision (implement decision)—traditionally, continuous improvement happens hereTomas J. Aragon, MD, DrPH Health Officer, City & County of San Francisco Director, Population Health Division (PHD) San Francisco Department of Public Health[10pt] Adjunct Faculty, Division of Epidemiology UC Berkeley School of Public HealthContinuous Decision Improvement (CDI): Public Health Decision Making for Complex Environments2014 10 / 25
Continuous Decision Improvement
What is Continuous Decision Improvement (CDI)?The 4D Decision Process improves decision making, but we aspire to continuously improvedecision making. That’s is continuous decision improvement!
Quality improvement (QI) in public health*A continuous effort to achieve measurable improvements in process performance to improvethe health of the community.
Continuous decision improvement (CDI) in public healthA continuous effort to achieve measurable improvements in the planning and execution ofdecision-making processes to achieve organization goals and to improve the health of thecommunity.
*Riley, Moran, Corso, et al. Defining Quality Improvement in Public Health. J Publ Health Management andPract, Jan/Feb 2010
Tomas J. Aragon, MD, DrPH Health Officer, City & County of San Francisco Director, Population Health Division (PHD) San Francisco Department of Public Health[10pt] Adjunct Faculty, Division of Epidemiology UC Berkeley School of Public HealthContinuous Decision Improvement (CDI): Public Health Decision Making for Complex Environments2014 11 / 25
Continuous Decision Improvement
What kind of decisive leader are you? should you be?
DECISIVE LEADERSHIP
SOLUTION-ORIENTEDWhat should we do?
PROCESS-ORIENTEDHow should we decide?VERSUS
Professor Michael Roberto:“Many leaders focus on finding the right solutions to problems rather than thinking carefullyabout what process they should employ to make key decisions. When confronted with a toughissue, we focus on the question, what decision should I make? We should first ask, how Ishould I go about making this decision?” (Source: The Art of Critical DecisionMaking—Course Guidebook)
Tomas J. Aragon, MD, DrPH Health Officer, City & County of San Francisco Director, Population Health Division (PHD) San Francisco Department of Public Health[10pt] Adjunct Faculty, Division of Epidemiology UC Berkeley School of Public HealthContinuous Decision Improvement (CDI): Public Health Decision Making for Complex Environments2014 12 / 25
Continuous Decision Improvement
The CDI Choice-Mobile—All aboard!Plan Decision → Decision Process → Decision Outcome
Tomas J. Aragon, MD, DrPH Health Officer, City & County of San Francisco Director, Population Health Division (PHD) San Francisco Department of Public Health[10pt] Adjunct Faculty, Division of Epidemiology UC Berkeley School of Public HealthContinuous Decision Improvement (CDI): Public Health Decision Making for Complex Environments2014 13 / 25
Continuous Decision Improvement
Continuous Decision Improvement = PDSA + 4D Decision Process
Define-Design-Decide-Do
Communication
Context
Composition
Control
Define-Design-Decide-Do
A Max Cognitive Conflict
B Min Affective Conflict
C Max Shared Understanding
D Max Commitment
E Min Resistance
Quality of Decision Process
- Decision Quality*
- Constructive Conflict (A, B)
- Comprehensive Consensus (C, D, E)
PLANManagerial Levers
DODecision Process
STUDYDecision Process
ACT (learn and improve)Frame, Alternatives, Information, Measurements, and Logical reasoning
Tomas J. Aragon, MD, DrPH Health Officer, City & County of San Francisco Director, Population Health Division (PHD) San Francisco Department of Public Health[10pt] Adjunct Faculty, Division of Epidemiology UC Berkeley School of Public HealthContinuous Decision Improvement (CDI): Public Health Decision Making for Complex Environments2014 14 / 25
Example—CDI for self-improvement
Trust is a decision (see Robert Hurley’s The Decision to Trust, 2012)
Definition of trust“Trust is the degree of confidence you have that another party can be relied on to fulfillcommitments, be fair, be transparent, and not take advantage of your vulnerability.”
FACT: Good team decision making requires cooperation.Good cooperation requires trust and humility.Extending and creating trust are decision problemsHumility improves trust building (giving and creating).
STRONG RECOMMENDATION:Learn and practice individual trust-building CDITrain team members in trust-building CDI
Tomas J. Aragon, MD, DrPH Health Officer, City & County of San Francisco Director, Population Health Division (PHD) San Francisco Department of Public Health[10pt] Adjunct Faculty, Division of Epidemiology UC Berkeley School of Public HealthContinuous Decision Improvement (CDI): Public Health Decision Making for Complex Environments2014 15 / 25
Example—CDI for self-improvement
Understanding trust as a decision problem (1/2)
Trustor Trustee
PredispositionsVulnerability
Expectation
Competent*
Commoninterests
Character(integrity)
Consequence Care(benevolence)
DECISIONto Trust?
Probability
Relational Context- Personal security- Power imbalance- Prior history
External Context- Situational security- Uncertainty
Cognitive Biases
INFLUENCEDecision to Trust?
* capable, consistent, continuously improving
Tomas J. Aragon, MD, DrPH Health Officer, City & County of San Francisco Director, Population Health Division (PHD) San Francisco Department of Public Health[10pt] Adjunct Faculty, Division of Epidemiology UC Berkeley School of Public HealthContinuous Decision Improvement (CDI): Public Health Decision Making for Complex Environments2014 16 / 25
Example—CDI for self-improvement
Understanding trust as a decision problem (2/2)
Trustor Trustee
PredispositionsVulnerability
Expectation
Competent*
Commoninterests
Character(integrity)
Consequence Care(benevolence)
DECISIONto Trust?
Probability
Relational Context- Personal security- Power imbalance- Prior history
External Context- Situational security- Uncertainty
Cognitive Biases
INFLUENCEDecision to Trust?
* capable, consistent, continuously improvingTomas J. Aragon, MD, DrPH Health Officer, City & County of San Francisco Director, Population Health Division (PHD) San Francisco Department of Public Health[10pt] Adjunct Faculty, Division of Epidemiology UC Berkeley School of Public HealthContinuous Decision Improvement (CDI): Public Health Decision Making for Complex Environments2014 17 / 25
Example—CDI for self-improvement
Scenario—Decision to give and create trust, and to practice humility
Trust is an issue whenwe expose our vulnerabilities, orwe need someone to fulfill a commitment, orwe expect a fair and transparent process when our interests are at stake.
Scenario: Self-improvement through feedbackFor my job, I need to improve my performance. One proven approach is to ask for honestfeedback from my “harshest critics.” Decision problem: From whom do I seek feedback?
CDI Humble inquiry for improvement (HIFI)Humble inquiry is “the gentle art of asking without telling.” Asking for feedback requirespracticing humility, exposing vulnerabilities (extending trust), but it also creates trust(influencing others’ confidence in you). See Edgar Schein’s Humble Inquiry (2013)
Tomas J. Aragon, MD, DrPH Health Officer, City & County of San Francisco Director, Population Health Division (PHD) San Francisco Department of Public Health[10pt] Adjunct Faculty, Division of Epidemiology UC Berkeley School of Public HealthContinuous Decision Improvement (CDI): Public Health Decision Making for Complex Environments2014 18 / 25
Example—CDI for self-improvement
Scenario: From whom do I seek feedback for improving in Task A?
1 DEFINE problem1 Situational awareness: work environment2 Clarify problem or opportunity: self-improvement through seeking feedback3 Clarify frame and test assumptions: Improving in Task A will contribute to our mission.4 Clarify values: mission-driven, self-improvement5 Set objectives:
1 maximize technical learning how to improve in Task A2 maximize receiving honest, reliable feedback3 minimize personal, unnecessary attacks4 strengthen relationships (elicit trust [confidence] in me)
2 DESIGN alternatives: generate list of names3 DECIDE alternatives: prioritize and select (consequence table)4 DO decision (use humble inquiry to elicit feedback for self-improvement)
Tomas J. Aragon, MD, DrPH Health Officer, City & County of San Francisco Director, Population Health Division (PHD) San Francisco Department of Public Health[10pt] Adjunct Faculty, Division of Epidemiology UC Berkeley School of Public HealthContinuous Decision Improvement (CDI): Public Health Decision Making for Complex Environments2014 19 / 25
Example—CDI for self-improvement
Aside: What is a consequence table?
A consequence table organizes your data:1 Objectives (column 1)2 Alternatives (Options A, B, and, C)3 Measures (cells = consequences of the alternatives on the objectives)
Tomas J. Aragon, MD, DrPH Health Officer, City & County of San Francisco Director, Population Health Division (PHD) San Francisco Department of Public Health[10pt] Adjunct Faculty, Division of Epidemiology UC Berkeley School of Public HealthContinuous Decision Improvement (CDI): Public Health Decision Making for Complex Environments2014 20 / 25
Example—CDI for self-improvement
Scenario: From whom do I seek feedback? (Consequence Table)
Objectives Sub-objectives A1 A2 A3 A4Maximize technical learning Competent (-3 to 3) 3 3 0 -3Maximize honest feedback Character (-3 to 3) 3 2 3 -3
Reliable (-3 to 3) 3 2 3 -3Minimize personal attacks Cares about me (-3 to 3) 3 0 0 -3Increase trust in me Vulnerable (-3 to 3) 0 0 -3 0
12 7 3 -12
Scale: -3 = high negative (e.g., very incompetent)-2 = medium negative-1 = low negative0 = neutral1 = low positive2 = medium positive3 = high positive (e.g. very competent)
Tomas J. Aragon, MD, DrPH Health Officer, City & County of San Francisco Director, Population Health Division (PHD) San Francisco Department of Public Health[10pt] Adjunct Faculty, Division of Epidemiology UC Berkeley School of Public HealthContinuous Decision Improvement (CDI): Public Health Decision Making for Complex Environments2014 21 / 25
Summary
Summary of Continuous Decision Improvement as a Consequence Table
Objectives Sub-objectives 4D CDIMaximize quality criteria 1 Frame Y Y
2 Alternatives Y Y3 Information Y Y4 Measurements Y Y5 Logical reasoning Y Y
Maximize constructive conflict 6 Maximize cognitive conflict Y Y7 Minimize emotional conflict Y Y
Maximize comprehensive consensus 8 Maximize shared understanding Y Y9 Maximize commitment Y Y
10 Minimize resistance Y YImprove decision planning 11 Plan-Do-Study-Act (PDSA) cycles YImprove decision process 12 Plan-Do-Study-Act (PDSA) cycles YIncludes HELLP considerations 13 Health, Ethical, Legal, Logistical, Political Y
Tomas J. Aragon, MD, DrPH Health Officer, City & County of San Francisco Director, Population Health Division (PHD) San Francisco Department of Public Health[10pt] Adjunct Faculty, Division of Epidemiology UC Berkeley School of Public HealthContinuous Decision Improvement (CDI): Public Health Decision Making for Complex Environments2014 22 / 25
Summary
Continuous Decision Improvement = PDSA + 4D Decision Process
Define-Design-Decide-Do
Communication
Context
Composition
Control
Define-Design-Decide-Do
A Max Cognitive Conflict
B Min Affective Conflict
C Max Shared Understanding
D Max Commitment
E Min Resistance
Quality of Decision Process
- Decision Quality*
- Constructive Conflict (A, B)
- Comprehensive Consensus (C, D, E)
PLANManagerial Levers
DODecision Process
STUDYDecision Process
ACT (learn and improve)Frame, Alternatives, Information, Measurements, and Logical reasoning
Tomas J. Aragon, MD, DrPH Health Officer, City & County of San Francisco Director, Population Health Division (PHD) San Francisco Department of Public Health[10pt] Adjunct Faculty, Division of Epidemiology UC Berkeley School of Public HealthContinuous Decision Improvement (CDI): Public Health Decision Making for Complex Environments2014 23 / 25
Summary
Bibliography
1 Why Great Leaders Don’t Take Yes for an Answer: Managing for Conflict and Consensus (2ndEdition), by Michael A. Roberto. Link: http://amzn.com/0133095118
2 Smart Choices: A Practical Guide to Making Better Decisions, by John S. Hammond et al. Link:http://amzn.com/0767908864
3 Handbook of Decision Analysis, by Gregory S. Parnell PhD et al. Link:http://amzn.com/1118173139
4 Decisive: How to Make Better Choices in Life and Work, by Chip Heath et al. Link:http://amzn.com/0307956393
5 The SPEED of Trust: The One Thing That Changes Everything, by Stephen M.R. Covey et al.Link: http://amzn.com/1416549005
6 The Decision to Trust: How Leaders Create High-Trust Organizations, by Robert F. Hurley. Link:http://amzn.com/1118072642
7 Humble Inquiry: The Gentle Art of Asking Instead of Telling, by Edgar H Schein. Link:http://amzn.com/1609949811
Tomas J. Aragon, MD, DrPH Health Officer, City & County of San Francisco Director, Population Health Division (PHD) San Francisco Department of Public Health[10pt] Adjunct Faculty, Division of Epidemiology UC Berkeley School of Public HealthContinuous Decision Improvement (CDI): Public Health Decision Making for Complex Environments2014 24 / 25
Summary
Acknowledgment
CDC Cooperative Agreement 5P01TP000295This project was supported by the cooperative agreement number 5P01TP000295 from theCenters for Disease Control and Prevention. Its contents are solely the responsibility of theauthors and not necessarily represent the official views of the Centers for Disease Control &Prevention.
Tomas J. Aragon, MD, DrPH Health Officer, City & County of San Francisco Director, Population Health Division (PHD) San Francisco Department of Public Health[10pt] Adjunct Faculty, Division of Epidemiology UC Berkeley School of Public HealthContinuous Decision Improvement (CDI): Public Health Decision Making for Complex Environments2014 25 / 25