Skip Navigation LinksHome > April 2014 - Volume 44 - Issue 4 > It’s All About Flow in a Complex Adaptive System
Journal of Nursing Administration:
doi: 10.1097/NNA.0000000000000056
Departments: Managing Organizational Complexity

It’s All About Flow in a Complex Adaptive System

Clancy, Thomas R. PhD, MBA, RN, FAAN

Free Access
Article Outline
Collapse Box

Author Information

Author Affiliation: Clinical Professor and Assistant Dean, School of Nursing, The University of Minnesota, Minneapolis.

The author declares no conflicts of interest.

Correspondence: Dr Clancy, School of Nursing, The University of Minnesota, 5-140 Weaver-Densord Hall, 308 Harvard St SE, Minneapolis, MN 55455 (clanc027@umn.edu).

Collapse Box

Abstract

As systems evolve over time, their natural tendency is to become increasingly more complex. Studies in the field of complex systems have generated new perspectives on the application of management strategies in health systems. Much of this research appears as a natural extension of the cross-disciplinary field of systems theory. In this article, I discuss the Constructal Law and its impact on nurse workflow.

Have you ever wondered why trees look the way they do? If it was by accident, then no 2 trees would look the same. Yet, although there are many different types of trees, they all have similar design features. There is a trunk and then a series of branches, with the thickest near the base and the remainder tapering off as you go higher. Further, if you look close enough, you will see a branching pattern running across all trees, which is “self similar.”1 Self similar means that the branching pattern is the same at all scales; a small portion of the tree looks about the same as the entire tree. In fact, the branching pattern present in trees is just 1 example of design in nature. Rivers, lightning strikes, the shape of snow flakes, and even human beings all share similar design characteristics that are the result of one common goal, and that is to improve flow.

Figure. No caption a...
Image Tools

All systems, whether they are trees, rivers, or humans, have currents that flow through them. Oxygen and blood flow through animate systems such as trees or humans, whereas water and electricity flow in currents through inanimate systems such as rivers or lightening. Without flow, systems stagnate and eventually cease to exist. Put another way, movement is life. Thus, all systems, to survive, evolve in a direction that improves their access to designs that improve the flow of currents through them. The branching pattern in trees is not accidental. Rather the configuration of branches is the result of evolution and the search for optimal designs to transport water and oxygen from the ground back to the atmosphere. This treelike branching pattern is so efficient it is also seen in other structures such as river basins, the human respiratory system, computer networks, and road systems.

Back to Top | Article Outline

The Constructal Law

The evidence that all systems spontaneously evolve in a direction that improves their flow is so pervasive that scientists are now investigating whether this is a fundamental law of physics. In their book, Design in Nature: How the Constructal Law Governs Evolution in Biology, Physics, Technology, and Social Organization, Bejan and Zane2 describe the principles underlying this idea as the Constructal Law. The Constructal Law states, “For a finite flow system to persist in time (to live), its configuration must evolve in such a way that provides easier access to the currents that flow through it.”2(p3) Constructal Law predicts that given the freedom to change, systems will generate better and better configurations so that the currents within them may flow more easily. This law holds true not only for natural systems but for all systems including those developed by man.

The implications of the Constructal Law are important for all systems including those that involve nursing. In healthcare, for example, we can see the Constructal Law in action by observing the flow of patients through hospitals over time. Using hospital length of stay (LOS) as a measure of flow, the LOS in US hospitals has declined from 11.4 to 6.3 days between the years 1975 and 2008.3 What drove this dramatic change? Traditional fee-for-service reimbursement models were no longer financially sustainable, and implementation of the prospective payment system in the 1980s aligned payment incentives in a way that forced hospitals to implement systems that improved patient flow and reduced LOS.4 Hospitals were not mandated to change, but spontaneously did so to survive.

Back to Top | Article Outline

It’s All About Flow: Long and Fast, Short and Slow

Although a reduction in LOS confirms that patient flow in health systems has improved, it does not explain how. Like the formation of rivulets of water from rain that evolve into channels that further facilitate flow, successful health systems continuously create designs that improve the flow of patients. According to the Constructal Law, the currents that persist are those that facilitate movement throughout the entire system, regardless of the type. Reductions in LOS resulted not only from improvements in hospital processes but from changes in flow through the entire continuum of care. For example, prior to the 20th century, the majority of healthcare took place in the home.4 Physicians and other providers made house visits, and thus the flow of patients throughout the system was “short and slow.” Short meant that patients did not have to travel far (they remained in their homes), and slow meant that access to healthcare providers was limited by the distance they had to travel (sometimes days). In the same manner, the evolution of rivers and streams begins with falling rain seeping into the ground (slow movement) and then saturating the surface of it (short distance). When the surface of the ground becomes saturated, raindrops spontaneously combine, and channels begin to form, streams emerge, and flow is improved.

Healthcare systems follow a similar evolution of flow as river basins. As the US population increased over time, large metropolitan areas emerged, transportation improved, technology advanced, and the demand for medical services outpaced the supply of providers. No longer feasible to provide home visits, medical clinic and hospital systems emerged, and like raindrops combining and forming rivers, patients were channeled to clinics and hospitals for care. These new pathways called “fast and long” further improved the flow of patients. Fast signified that more patients could be seen per unit of time because care was centralized in clinic or hospital systems, and long meant that patients traveled farther (than their home) for care. Finally, when patients were discharged from hospitals or clinics, they returned to slow (transitional care, nursing home, home health, and so forth) and short (close to home) flow just as a river fans out into a treelike delta.

A key concept in optimizing flow is that the time currents spend in slow and short flow must equal the time spent in fast and long flow. In river systems, the amount of time water spends seeping into the ground and in small tributaries (short and slow) must equal the time it spends flowing in the main channels of the river (fast and long). The same can be said for human circulatory systems; the time blood spends flowing through capillaries (slow and short) must equal the time it spends in the large vessels such as the aorta (fast and long). Although flow through a single capillary is slower than in a large blood vessel, total blood flow is maintained through thousands of branching tributaries in the capillary system. And not surprising, these tributaries form the same branching pattern as rivers, trees, and other natural structures. If an imbalance between short and slow/long and fast develops, then flow backs up, as can be seen in heart failure or floods.

Optimizing the flow of patients through a health system follows the same concept as natural systems. Length of stay in hospitals, for example, is optimized when the total time all patients spend in fast and long systems (clinics and hospitals) is the same as that in slow and short systems (subacute and home care). When there is an imbalance caused by delays, flow is improved by spreading these “imperfections” throughout the system. For instance, the build out of ambulatory facilities (surgical centers, imaging centers, and urgent care centers), like tributaries in a river basin, redistributed services originally in hospitals and spread them throughout the system. This ultimately improved flow.

Back to Top | Article Outline

Flow Is Life

The critical concept to understand is that any system, whether natural or manmade, will continuously evolve toward configurations that improve flow. That is because movement, whether it is patients, information, or other, is the lifeblood of organizations. Without it, organizations cannot survive. Just look at your own work environment. How many initiatives are focused right now on reducing LOS, waiting room time, turnaround time, documentation time, results reporting time, call-light answering time, accounts receivable time, and so forth? We are already seeing the next configuration of flow designs evolving with the build out of virtual visits through telehealth and patient engagement systems. These systems improve fast and long flow by providing electronic access to care instantly (fast) but at a distance (long). Again, flow is improved by spreading imperfections (delays) throughout the system.

Patterns to optimize flow occur at all scales and are characteristic of complex adaptive systems. Scaling means that flow patterns are similar at all levels of the system. For instance, the branching pattern seen in 1 small section of a river looks very similar to the entire river itself; it is a scaled-down version of the whole. Natural structures such as river systems, trees, and the human circulatory system all share a common scaling characteristic called a power law. Often referred to as the Pareto effect (or 80/20 rule), a power law describes the frequency of an event as a power of some attribute of that event.5 For example, the frequency of smaller tributaries (an attribute) branching from larger ones in rivers remains constant at all scales. This scaling rule results in about 80% of the channels being small (slow and short) and 20% being large (long and fast). The same would hold for trees; 80% of branches are small, whereas 20% are large. The occurrence of a power law indicates there is a hidden order in the design of flow systems, and the direction of that design is toward configurations that optimize flow.

Back to Top | Article Outline

Design in Nature and the Evolution of Nurse Workflow

Scaling patterns indicative of complex adaptive systems also show up in manmade systems including healthcare. Length of stay, waiting room delays, and interarrival times of hospital admissions have all been shown to exhibit power law distributions. Whereas river systems, over thousands of years, have optimized their flow through a complex balance between the environmental topography and channel width, depth, and number of tributaries, health system designs are constantly evolving, enabled through advances in technology. There is a continuous “tug-of-war” between balancing slow and short flow with fast and long flow at all scales. For example, in hospitals, the number of patients with a long LOS (slow) in critical care areas (short proximity to nurses) must be offset by patients with short LOS (fast) moving quickly through the hospital (long). Otherwise, delays emerge that slow hospital admissions, transfers, and discharges and increase LOS.

If patients are the currents that flow through health systems, then what role do nurses and other health providers play? According to the Constructal Law, the evolution of configurations that optimize flow migrates toward a Pareto effect.2 If this were true, then 80% of a nurse’s time would be spent moving from one location to another in short bursts, whereas the remainder would be spent in 1 location. In fact, this was recently confirmed through a series of studies conducted on nurse mobility.6-10 Utilizing time and motion studies in an acute care setting, Cornell et al6,10 found that nurses, regardless of unit type, frequently move from 1 location to another in short bursts interspersed with occasional long periods in 1 location. The frequency of these movements, when plotted against time, shows a power law pattern similar to that of rivers, trees, and other natural structures. In other words, nurses represent the branching pattern of trees or rivers (long and fast/short and slow) to facilitate the flow of patients. Nurses are flow facilitators.

For anyone who has observed nurses working in a busy clinical setting, the findings of Cornell et al10 are not surprising. A typical nurse’s day is punctuated with short bursts of unanticipated events and interruptions, leaving little time at the patient’s bedside. And as systems become increasingly complex with advances in technology, the growing number of events, tasks, and duties nurses attend to branches out in a treelike manner. Each new branch represents another activity, and to maintain patient flow, nurses hop from 1 branch to the next in shorter and shorter bursts. Ironically, this is completely at odds with what clinical nurses and patients want, more time at the bedside and less time jumping from 1 activity to the next. Thus, improvements in patient flow do not necessarily translate to improvements in nurse and patient satisfaction: and in fact, may paradoxically contribute to lower hospital reimbursement if they negatively impact patient experience scores on pay-for-performance programs such as Medicare’s Hospital Consumer Assessment of Healthcare Providers and Systems Survey.11

Back to Top | Article Outline

Conclusion

If we use the analogy of a river, the branching pattern of nurses’ workflow is increasing at an alarming rate. Currents of information from electronic health records, real-time patient tracking monitors, electronic dashboards, mobile sensing devices, and so forth are dramatically increasing the complexity of workflow configurations for nurses.12 Globally, at the health system level, the evolution of designs that improve patient flow may be readily apparent. The recent emergence of accountable care organizations is 1 example of how patient flow can be improved through better coordination of services system-wide. However, at the patient care level, individual nurses in the health system may simply see these changes as increased complexity, resulting in less time with their patients.

If the Constructal Law2 is true, then nurse administrators face a challenging future. Pressure to improve patient flow across the continuum will continue as new technology enables it. And, like water flowing around rocks in a stream, nurses are ingenious at finding ways to maintain patient flow in the face of barriers. Unfortunately, these strategies are often workarounds for poor design configurations and increase the workload on nurses. To truly design systems that optimize patient and nurse workflow, we will again need to turn to nature. In the next article, we will explore the concept of antifragility and its potential for designing better healthcare systems.

Back to Top | Article Outline

References

1. Holt T. Complexity for Clinicians. San Francisco, CA: Radcliffe Publishing; 2004.

2. Bejan A, Zane JP. Design in Nature: How the Constructal Law Governs Evolution in Biology, Physics, Technology, and Social Organization. New York, NY: Doubleday; 2012.

3. National Center for Health Statistics. Health, United States, 2012: With Special Feature on Emergency Care. Hyattsville, MD; 2013.

4. Star P. The Social Transformation of American Medicine: The Rise of a Sovereign Profession and the Making of a Vast Industry. New York: Basic Books; 1984.

5. Lindberg C, Nash S, Lindberg C. On the Edge: Nursing in the Age of Complexity. Bordentown, NJ: Plexus Press; 2008.

6. Cornell P, Herrin-Griffith D, Keim C, et al. Transforming nursing workflow, part 1: the chaotic nature of nurse activities. J Nurse Adm. 2010; 40 (9): 366–373.

7. Cornell P, Riordan M, Herrin-Grittith D. Transforming nursing workflow, part 2: the impact of technology on nurse activities. J Nurse Adm. 2010; 40 (10): 432–439.

8. Vardaman J, Cornell P, Clancy T. Complexity and change in nurse workflows. J Nurs Adm. 2012; 42 (2): 78–82.

9. West B, Clancy T. Flash crashes bursts and black swans. J Nurs Adm. 2010; 40 (11): 456–459.

10. Cornell P, Clancy T, Vardaman J. Ward warriors: the complex nature of nurse mobility. J Nurs Adm. 2013; 43 (11): 557–561.

11. Hospital Consumer Assessment of Healthcare Providers and Systems Web site. http://www.hcahpsonline.org/home.aspx. Accessed on January 13, 2014.

12. Smith M, Saunders R, Stuckhardt L, McGinnis M. Best Care at Lower Cost: The Path to Continuously Learning for Health Care in America. Washington, DC: Institute of Medicine, National Academies Press; 2012.

© 2014 Wolters Kluwer Health | Lippincott Williams & Wilkins

 

Login