Editor’s Note: We’re pleased to present a paper by two members of the Special Task Force on Reshaping the System of Survival for Sudden Cardiac Arrest (SCA) that challenges our way of thinking about out-of-hospital cardiac arrest survival. Although how we respond to SCA has changed over the past few years and we’ve worked hard to save the lives of thousands of cardiac arrest patients, the fact remains that the national SCA survival rate in the U.S. continues to be low–around 8%. The Task Force, headquartered at the University of Pennsylvania, is studying this with a team of individuals representing many fields, including patient care, research, education, administration, engineering, medical writing, medical direction, disaster medicine, EMS, nursing and organizational dynamics.
This isn’t a typical article. The authors describe the problem of SCA survival from a perspective that is different from how many in EMS think about, describe, and manage the problem of SCA survival.
Don’t expect many answers in this first article. We ask you to assist the Task Force by participating in the CPR Design Project on their wesite (www.organizationaldynamics.upenn.edu/survival) and /or by sending feedback, comments and suggestions to the authors at sca-dynamics@sas.upenn.edu. We strongly recommend that you take an active role in the discussion/process. SCA survival is everyone’s problem. Your input is important.
At a special session of the 2008 Emergency Cardiovascular Care Update Conference in Las Vegas, we posed two questions: Why does the national SCA survival rate continue to be low despite more than 40 years of expenditure of energy and resources? Are we doing the “right” things?
At the conference we presented a new framework for thinking about SCA survival that was drawn from organization and management science and is used to understand complex problems and to improve organizational survival. We believe the framework and strategies used to prolong the life of an organization can also be used to prolong the life of a person.
We were motivated to address these questions in part because of data from the Resuscitation Outcomes Consortium.(1) Based on evaluations from more than 20,520 cases of out-of-hospital cardiac arrests from 10 locations in the U.S. and Canada that covered a population of approximately 21.4 million people, the 2008 paper reported an overall SCA survival rate of 4.6%. Likewise, a 2010 report published in the American Heart Association journal Circulation noted that a review of 30 years of published research showed “only 7.6 percent of victims survive an out-of-hospital cardiac arrest, a number that has not changed significantly in almost 30 years.”(2) Although recognizing that a few communities have much higher survival rates, most populated areas don’t reach these levels. To support our thinking we established a cross-disciplinary discussion and working group: the Special Task Force on Reframing the System of Survival for Sudden Cardiac Arrest.(3)
What Kind of Problem is SCA Survival?
When confronted with large and difficult problems, it’s helpful to begin by asking what kind of problem has been presented because the approach should match the type of problem. Using the wrong strategy for the type of problem, even if applied properly, can lead to serious unintended consequences, which can waste resources, prolong the problem or make it worse. In organization and management science, this error is referred to as doing the wrong thing righter.(4)
One way to decide on the best approach is to examine the circumstances of the type of problem, which can vary from simple and orderly to complex to chaotic(5,6) In an orderly environment, cause and effect relationships are clear and a “right” strategy and answer to a problem can be selected and implemented based on evidence-based data. The development of the scientific method, the concept of evidence-based medicine, and the search for root causes are based on assumptions of solving a controlled problem in an orderly and mostly predictable environment.
For an orderly problem, we often use a mechanistic and reductionist perspective, such as the “whole problem is equal to the sum of its parts.” This means that our mindset or approach to thinking is to treat the problem like a mechanical device, breaking it down into an even smaller collection of sub-problems and parts to understand how each works, just as we would for a mechanical device that wasn’t operating properly. To solve a complicated problem, we may search for the root cause and replace or fix whatever is broken, and then reassemble the new or improved parts into the whole.
Historically, we’ve broken the problem of SCA survival down into four parts: Early access, early CPR, early defibrillation, and early advanced care. In addition, a mathematical formula has been developed to show how the parts add up to survival.(7)
We’ve then broken down the four parts into smaller parts. For example, we’ve made changes to the CPR manikins, moving from lifelike full-body manikins to small, simple torso devices. We’ve also made changes to CPR procedures, reducing the original mantra of “responsiveness, airway, breathing, circulation” to hands-only compressions. We’ve expected that improving each part will improve the whole, which means increased SCA survival.
The analytic scientist argues that SCA survival is low because one or more constituent parts is broken or defective, and if we identify and fix or improve each, then overall performance and survival will be improved. The analytic approach also holds that the problem and the circumstances that surround it are sufficiently stable and orderly such that a solution is “knowable.” Dr. Mickey Eisenberg offers an example of this when he deconstructs the four parts of the chain of survival into 50 “known or speculative” factors affecting SCA survival.(8)
He noted that if we had a perfect understanding of all 50 of these factors and their respective influences on survival, and if we perfectly understood whatever factors are yet to be identified, we could construct a formula giving the exact likelihood than any particular patient would survive a cardiac arrest.(8) (p. 115)
This way of thinking where we focus on improving individual parts is how we’ve been trying to increase SCA survival for the past 30 years. Yet, overall improvement has barely changed, other than in a handful of communities. Why? Are most of us not working hard enough (a motivation problem)? Are we not intelligent or skillful enough (an ability problem)? Are we not providing enough resources (a money, people, or time problem)? Or are we adequately motivated, intelligent, rigorous, and creative in our resource allocation but using the wrong kind of approach for this type of problem?
Another Way to Think
When organizations are studied, we find that in most cases the difficult problems within and between them have circumstances that are complex and/or chaotic. And we also find that the best practices used for one management problem or in one organization or community often do not work in another–and may have unintended effects on other problems–largely because of the diversity of interests among people and groups within organizations and communities, which results in conflict and confusion.
In organizations, people and groups are not and cannot be thought of as mechanical parts. An AED brought to the scene and applied will perform as it was intended; it cannot “decide” not to become attached to a patient’s chest or to not begin after being activated. But a bystander even previously trained can forget or decide not to use an available AED due to many reasons including distraction, fear and confusion.
The behavior of people, whether in a lay or official role, is variable. People decide to follow or fail to follow guidelines and policies, and perform actions depending on their personal and professional interests and goals, and often at the moment of choice. And when a problem involves many people and organizations, the outcomes can be enormously complex and variable. Communities, organizations, and the people within them may in some circumstances act in ways that are orderly, but much of the time our social and organizational environment is better described as a kaleidoscope of variety.
Applying the concept of evidence-based where actions are selected only after reliable and valid testing has taken place is appropriate when the environment is relatively orderly as in laboratory science and medicine. But this approach is much more challenging when the problem contains much variability and social complexity.(9) Some well-structured organizational problems may be managed by reduction to an algorithm, but many others are complex or chaotic where it is difficult to identify any sense of regularity or predictability.
When a problem is organizationally complex, such as with SCA survival, we should assume the mindset or approach that the “whole problem (with all of its complexity and variability) is greater than the sum of the parts.” And consequently, a problem such as SCA survival cannot be fully understood or solved by reducing it only to the sum of links in a chain of survival. The problem is better understood as the interaction of many parts, some of which are not obvious. Indeed, a complex organizational problem has much more variability that must be accounted for.
Therefore, in order to understand the SCA survival problem, we must also include the people and groups who interact, are interdependent, and who have varying social and work obligations, personalities, and cultures. These issues are not “noise” or artifact that gets in the way of merely calling for help or quickly doing CPR or responding to a scene. Rather, it is these and other forces that together drive choices and create performance and ultimately survival. Organizational problems cannot be fully understood in mechanistic and additive ways. If we only try to use analysis to understand or to solve a complex organizational problem– if the problem is broken down into smaller parts in search of a solutionits meaning and our ability to solve it can be lost. This approach may result in temporary changes, but the problem will continue.
We believe that we need to also think about SCA survival as a complex system problem and use an approach referred to as “synthesis,” a word that means to combine objects or ideas into a complex whole. A synthesis thought process focuses on the patterns, meanings, and relationships among the parts and on the whole system rather than the parts individually. In a complex system problem, the goal is not to identify and solve the problems or to focus on the parts. Instead, the goal is to understand how the system’s inherent design prevents the desired outcomes from being realized and then to redesign the system so that the problem is eliminated or dissolved.
Complex organizational problems have been studied in management science for more than 50 years and the problem type is called by colorful names including a wicked problem and a mess.(10,11) A wicked problem has been described as one with incomplete, contradictory, and changing requirements.(12) Solutions to wicked problems are often difficult to recognize because of complex interdependencies of the parts, and a solution to one part of a wicked problem often creates or reveals another more complex problem. A problem whose solution requires large groups of individuals to change their mindsets and behaviors is likely to be a wicked problem. Examples of this type of problem have been observed in education, healthcare, pandemic influenza, homeland security, and international drug trafficking. In our opinion, the problem of SCA survival is a wicked problem; it is a mess.
If we continue to treat SCA survival as a problem in an orderly context, and if we only use mechanistic approaches based on analysis to improve each of the individual parts, we believe that we will continue to show only limited success. Improvement is most likely to occur in those few communities where the culture and leadership are well-established and powerful and where there is a high level of imposed structure and order such as in some corporate settings, particularly in the Las Vegas casinos.(13) It is important that we continue to study these examples in order to learn how to extend lessons learned to other locations, but we also believe that we need to use a second approach.
For communities and organizations that are less ordered, where there is more conflict among people and groups, more complexity and interactions, and where changes are more common (i.e., most U.S. communities), we should examine SCA survival as a complex multi-organization system. We should formulate the problem using systems thinking as a mindset and we should use synthesis. We believe that the few notable communities that have demonstrated significantly higher survival rates are using this approach.
What is the Ideal System?
In a 1984 paper published in JEMS, we attempted to solve the problem of SCA survival by assuming it was a simple problem in an orderly environment.(14) We described how to reach the quantitatively best possible or optimal solution by improving the individual links of what later was called the chain of survival: early access, early CPR, early defibrillation, and early advanced care. We argued that if our recommendations were followed – using checklists to be sure behaviors were completed–then the outcome would be an “ideal system” and SCA survival would improve. However, we made the “wrong thing righter” error described earlier: We presented an analytic strategy to solve a complex system problem.
Many people use the word “system” without clearly describing its meaning. In science, including organization and management science, a system is a whole which contains a group of interdependent parts that work together toward the same purpose or purposes, and which functions because of the interactions among the parts rather than working independently. An important characteristic of any system is that it always possesses critical or essential properties that none of the parts can manage alone.
For example, the SCA survival system includes all the organizations, groups, people, technologies, resources, and activities associated with surviving a sudden cardiac arrest. Indeed, it is the many interactions and differences in power between lay and professional providers, as well as the professional health and safety societies, educational and training organizations, equipment manufacturers and distributors, national and local media, available technology, local and community EMS and healthcare systems, and many other people and groups that interact to co-produce survival. Reducing survival only to chain links fails to appreciate the rich variability, interconnectivity, and importance of these forces. We cannot adequately understand or treat this complex organizational survival system if we only examine or improve the individual parts.
The analytic approach has focused on independent improvements of accessing EMS, improving the availability of delivering CPR, applying and using an AED, and ensuring that advanced medical care is provided. Such improvement efforts should be supported and be continued, but they are not enough. We should also use a system approach to search for ways to make the interactions among these parts more integrated and to locate other forces in the environment that also affect survival. Consider two examples.
First, suppose an AED device when started immediately opened a telephone line that connected both to an EMS dispatcher qualified to provide audio CPR instruction, and to another professional within a designated medical center who could provide coordination for arrival and transition of EMS to the medical center.
The lay responder could have immediate two-way communication, guidance, feedback and support, and would become immediately integrated with the other members of the EMS system of which each lay person is a part. Each lay responder would no longer be merely one who must perform independently which is often psychologically and physically foreign and “scary” territory, so to speak, and who “hands-off” to the next link. Rather, the lay responder and other responders in the SCA survival system would be co-involved and could be informed and supported in real time about how each member of the organizational response system was contributing to SCA survival.
Second, consider the effect of continuously improving one part of the chain of survival without full consideration of its interdependencies with other parts. This is the problem of “sub-optimizing” described by management scientist W. E. Deming.(15) As the sophistication and competencies of EMS responders continue to improve–an important and valuable outcome to be sure–what are the effects on lay responders and workplaces in the community? One unintended outcome could be the belief by these people and groups that their own preparation for SCA is less important or necessary because of the excellent EMS responders who are located “so close” to home or workplace.
In his 1968 book, The Systems Approach, Churchman reminded us that when there is a predominantly accepted thesis or way of understanding something, we should continue to study it in order to gain full understanding.(16) But we should also present a challenge based on different assumptions and which give rise to different outcomes. When the accepted way and the challenge are considered together they lead to a fuller understanding of both propositions.
Our argument is that the tremendous work being carried out across the globe to improve each of the parts that contribute to SCA survival must continue. But, we must challenge this with additional and new ways to think about survival particularly since the overall performance of our current system is unacceptably poor. Reframing SCA survival as a system problem, using a system approach to thinking, and using system methodologies for improving performance, we believe, has merit.
We argue that SCA survival has additional opportunities for improvement when it can be better understood if viewed as a complex system with changing technologies, and involving many people, groups, and organizations with their own interests. Focusing only on a generic chain or on improvements within individual groups of organizations as if these are independent parts, fails to improve the SCA system as a whole.
Our interdisciplinary academic and practice Task Force at Penn and colleagues across the US have been successfully applying systems thinking to complex problems in healthcare, education, government, and business for more than 30 years, and it is from this perspective and based on our collective experience that we are continuing to conduct our inquiry and research.(17—25)
Join Us
On JEMS.com, we will describe how to apply a systems methodology to complex problems and how the outcomes of using this kind of methodology have transformed and sustained organizations. We also describe how we can apply system change methods to the SCA Survival problem.
But we need your help and your input. We want to involve JEMS readers and so we encourage you to contact us with your opinions about this first article by telling us why you agree or disagree. We also want your help as a participant in the system change process. To send feedback about this article, e-mail: sca-dynamics@sas.upenn.edu. To participate directly, click the “Design the ideal adult CPR course experience” link on the Task Force website: www.organizationaldynamics.upenn.edu/survival.
Larry M. Starr, PhD, has been involved in the study of emergency care practice and education for more than 30 years. He has written about organization development and change, leadership, moral development, stress, personality, emergency oxygen equipment, CPR, and he is the author of the ACOEM Position Statement on AEDs in the Occupational Setting. He is director and Academic Chair of Organizational Dynamics graduate studies at the University of Pennsylvania (www.organizationaldynamics.upenn.edu/starr).
Allan Braslow, PhD, has been involved in the study of emergency care practice and education for more than 30 years including R&D education scientist under contract with USDOT/NHTSA/EMS, the American Heart Association, American Red Cross and National Safety Council, and has also served as Research Dissemination Expert at the Federal Agency for Healthcare Research and Quality. He is a leader in the research and development of CPR education including demonstrating the value of a video-based self-instructional system. He is a Visiting Scholar in Organizational Dynamics graduate studies at the University of Pennsylvania (www.organizationaldynamics.upenn.edu/braslow).
References
1. Nichol G, Thomas E, Callaway CW, et al. Regional Variation in Out-of-Hospital Cardiac Arrest Incidence and Outcome, JAMA, 2008;300(12):1423—1431.
2. Sasson C, Rogers MA, Dahl J & Kellermann AL. Predictors of Survival from Out-of-Hospital Cardiac Arrest: A Systematic Review and Meta-Analysis. Circ. 2010;3:63—81. Available at: http://circoutcomes.ahajournals.org/cgi/content/abstract/3/1/63. Summary also available at: http://ohsonline.com/articles/2009/12/05/report-outofhospital-cardiac-arrest-survival-rate-unchanged-in-30-years.aspx.
3. Special Task Group for Reshaping the System of Survival for Sudden Cardiac Arrest. Available at: www.organizationaldynamics.upenn.edu/survival.
4. Ackoff, RL. The systems revolution, Long Range Planning. 1974;7:2—5.
5. Snowden DJ & Boone ME. A Leader’s Framework for Decision Making. Harvard Business Review, November 2007. Available at: http://hbr.org/2007/11/a-leaders-framework-for-decision-making/ar/1?referral=00269&cm_sp=endeca-_-spotlight-_-link.
6. Boisot M & McKelvey B. Integrating modernist and postmodernist perspectives on organizations: A complexity science bridge. Academy of Management Review. 2010;35(3):415-433.
7. Larsen MP, Eisenberg MS, Cummins RO, et al. Predicting survival from out-of-hospital cardiac arrest: A graphic model. Ann Emerg Med. 1993;22(11):1652—1658.
8. Eisenberg MS. Resuscitate! How Your Community Can Improve Survival from Sudden Cardiac Arrest. Seattle: University of Washington Press, 2009.
9. Rousseau DM. Is there such a thing as evidence-based management? Academy of Management Review. 2006;31(2):256—260.
10.Conklin EJ. Wicked problems and social complexity. In, Dialogue Mappings: Building Shared Understanding of Wicked Problems, CogNexus Institute, 2010. Chapter available at:www.cognexus.org/wpf/wickedproblems.pdf.
10. Ackoff RL. The art and science of mess management. Interfaces. 1981;11(1):20—26.
11. Rittel H & Webber M. Dilemmas in a General Theory of Planning. Policy Sciences. 1973;4:155—169.
12. Valenzuela TD, Roe DJ Nichol G, et al. Outcomes of rapid defibrillation by security officers after cardiac arrest in casinos. NEJM. 2000;343:1206—1209.
13. Starr LM & Waymaster S. The ideal system. JEMS. 1984;9(10):34—38.
14. Deming WE. The New Economics for Industry, Government & Education. Cambridge: Massachusetts Institute of Technology Center for Advanced Engineering Study, 1993.
15. Churchman CW. The Systems Approach. Dell Publishing, N.Y., 1968.
16. Schyve PM. Systems Thinking and Patient Safety. In Advances in Patient Safety: From Research to Implementation, Volume 2 Concepts and Methodology.Agency for Healthcare Research and Quality. Available at: www.ahrq.gov/qual/advances/.
17. Golden BR & Martin RL Aligning the stars: Using systems thinking to (re)design Canadian healthcare. Healthcare Quarterly.2004;7(4):34—42. Available at www.longwoods.com/content/16803.
18. Farmer P. On the need for “Systems Thinking” in Health Care. Health & Medicine. Oct. 7, 2009. Available at http://bigthink.com/ideas/16769.
19. Ackoff RL & Greenberg D. Turning Learning Right Side Up: Putting Education Back on Track. Upper Saddle River, N.J.: Wharton School Publishing, 2008.
20. Pourdehnad J & Hebb A. Redesigning the academy of vocal arts. Systems, Reserach and Behavioral Science. 2002;19:331—338.
21. University of Alabama Huntsville creates new Center for Systems Studies. Available at www.uah.edu/systemstudies/.
22. Jacques ML. Transformation and Redesign at the White House Communications Agency. Quality Management Journal. 1999;6(3).
23. Magidson J & Brandyberry G. Putting Customers in “Wish Mode.” Harvard Business Review. 2001. Available at: http://hbr.org/2001/09/putting-customers-in-the-wish-mode/ar/1.
24. Ackoff Rl, Magidson J & Addison, HJ. Idealized Design. Upper Saddle River, N.J.: Wharton School Publishing, 2006.
