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Complexity Theory and Decision Making in Health System

Complexity Theory and Decision Making in Health System. “ I never make predictions, especially about the future.”. Sam Goldwyn Mayer. Health Care. Driving. Scheduled. Airlines. Chartered. European. Flights. Railroads. Mtn Climbing. Nuclear. Bungee Jumping. Chemical. Power.

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Complexity Theory and Decision Making in Health System

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  1. Complexity Theory and Decision Making in Health System

  2. “ I never make predictions, especially about the future.” • Sam Goldwyn Mayer

  3. Health Care Driving Scheduled Airlines Chartered European Flights Railroads Mtn Climbing Nuclear Bungee Jumping Chemical Power Manufacturing How Hazardous is Health Care Dangerous Safe 100K 10K 1K Total # of Deaths 100 10 1 1 10 100 1K 10K 100K 1M 10M # Encounters / Death

  4. Health Care as a Complex System • Health care organizations can be viewed as complex systems (Institute of Medicine 2001; Plsek and Greenhalgh 2001; Sweeney and Griffiths 2002).

  5. C A B X Effect Sufficient Cause Cluster

  6. Simple • Baking a cake is a simple problem. • Simple problems lend themselves to a recipe approach. • The process and results are generalizable; and while special skill at cooking is a plus, it is not essential for success.

  7. O ~D M K C A B X

  8. O ~D M K I X G J C A B Y

  9. O ~D M K I X G J C A B D P X Z ~A Y

  10. O ~D M K I X G J C A B D P A X Z ~A ~K Y

  11. O ~D M K T N I X V G J C ~G C A B G P D S P T Z A U X R Q Z P ~A L ~K D H Y

  12. Complicated • Sending a rocket to the moon is an example of a complicated problem. • Complicated problems are best dealt with using formulaic and expert-knowledge approaches. • The overall problem can be mechanistically broken down into component parts (booster rocket, cabin environment, navigational equipment, etc.) and assigned to teams of experts who utilize the proven methodologies of their disciplines.

  13. Complicated • Rockets are similar in important ways, meaning that success with one rocket provides reasonable assurance of success with future rockets. • When surprising events do occur, we can study these, build improvements into the system, and thus raise the probability of future success.

  14. O ~D M K ? ? ? X ? G J ? ? ? A B ? P ? S P ? Z A ? X ? ? Z ? ? ? ~K ? ? Y

  15. Complex • In contrast to simple and complicated issues, an example of a complex issue is that of raising a child. • Success in raising one child is no guarantee of success in raising another. • Past experience, coupled with advice from experts, can serve as a starting point; but we know that simply applying the formula that worked before may not lead to success, and may even lead directly to failure because of the second child’s resentment at being treated this way.

  16. Across all disciplines, at all levels, and throughout the world, health care is becoming more complex.

  17. Complex Adaptive Systems: Definition • A complex adaptive system is a collection of individual agents with freedom to act in ways that are not always totally predictable, and whose actions are interconnected so that one agent's actions changes the context for other agents.

  18. Far from Agreement Level of Agreement Decisions will have varying levels at which the entire system agree that a particular effect is desired. The Degree of Certainty Decisions are more certain when the cause and effect linkages are well known. Close to Agreement Stacey Diagram Far from certainty Close to certainty

  19. Far from Agreement Close to Agreement Stacey Diagram Where even enough hard evidence is not enough Where there is not enough hard evidence Far from certainty Close to certainty

  20. Far from Agreement Simple: Rational decision-making. Straightforward planning & control Close to Agreement Stacey Diagram Simple Far from certainty Close to certainty

  21. Far from Agreement Chaos: No discernible patterns. Disintegration & anarchy Close to Agreement Stacey Diagram Chaos Simple Far from certainty Close to certainty

  22. Far from Agreement Close to Agreement Stacey Diagram Chaos Complicated Simple Far from certainty Close to certainty

  23. Far from Agreement Close to Agreement Stacey Diagram Chaos Complicated Simple Complicated Far from certainty Close to certainty

  24. Far from Agreement Close to Agreement Stacey Diagram Zone of Complexity Far from certainty Close to certainty

  25. Far from Agreement Close to Agreement Stacey Diagram Good enough planning–minimum specification, simple rules Multiple actions Experiment and tune system plan-do-check-act Scan for patterns Political decision making Negotiation and consensus building Compromise Listen to the shadow system Use intuition, muddle through Metaphors Use complex thoughts for complex systems Judgmental decision making Mission and vision based decision making Plan and control Regulate Far from certainty Close to certainty

  26. Far from Agreement Close to Agreement What is the fate of a complex system of decisions ? Finding more cause components from already known cause clusters and discovering unknown cause clusters * * Far from certainty Close to certainty

  27. Far from Agreement Close to Agreement What is the fate of a complex system of decisions ? * Consensus building around shared Values and beliefs * Far from certainty Close to certainty

  28. Far from Agreement Close to Agreement What is the fate of a complex system of decisions ? * * Falling into chaos : Organizational Collapse, Revolutions, Death Far from certainty Close to certainty

  29. Stacey Diagram • Many organizations are existing in all areas of the matrix at different times. • Traditional management methods are effective in the Simple area. • Management methods needs to be altered in the Complicated areas - • negotiation / compromise • mission & values based

  30. Stacey Diagram • If you try to use traditional management methods (plan & control) in the Zone of Complexity, you usually get unintended and unpredictable consequences. • Complex Adaptive Systems can exist and thrive in the Zone of Complexity. • PDCA cycle is an example of management in the complex zone allowing tuning, experimenting, and good-enough planning.

  31. System Design • The distinction between these systems is obvious, but frequently not taken into account when system is designed. • When the human components respond in an unpredictable manner, they are labeled as being unreasonable or “resistant to change.” • The designer then specifies behavior in greater detail via rules, guidelines, etc.

  32. Thank You! Any Questions!

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