| Course | EDN 818 Innovation and Technology in Health Care |
|---|---|
| Module | Module 3 |
| Paper type | Applied theory paper |
| Length | About 1,132 words, 7 pages |
| Format | APA 7 student paper |
| School | Aspen University |
| Program | Doctor of Education |
| Updated | September 2026 |
Free sample paper for EDN 818 Module 3
Nine Units, Nine Results: Complex Adaptive Systems Theory and the Uneven Spread of a Nurse-Driven Mobility Program
Student Name
Doctor of Education Program, Aspen University
EDN 818: Innovation and Technology in Health Care
Instructor Name
Month Day, Year
Nine Units, Nine Results: Complex Adaptive Systems Theory and the Uneven Spread of a Nurse-Driven Mobility Program
Two years ago Kingsmere Regional Hospital introduced a nurse-driven early mobility program on nine adult inpatient units. Every unit got an identical protocol, identical training and one target: each eligible patient out of bed three times a day. A year later, results ranged from units where mobility had become routine and hospital-acquired functional decline had fallen, to units where the protocol was barely used. Leaders first blamed the weaker units' managers. This paper uses complex adaptive systems theory to offer a different explanation, and to redesign the program's spread on the basis of what the theory predicts.
What a Complex Adaptive System Is
A complex adaptive system is a collection of agents who act on their own understanding and whose actions change the context for one another. Plsek and Greenhalgh (2001) argued that health care organizations behave this way: clinicians respond to internal rules and mental models rather than to directives alone, their actions interact, and the system produces patterns no one designed. Such systems are embedded in larger systems, their boundaries are fuzzy, tension and paradox are normal, and small changes can have large effects while large efforts sometimes change little. Plans that assume predictable, linear cause and effect tend to disappoint.
Improvement Seen Through Complexity
Braithwaite (2018) argued that many improvement programs underperform because they treat health care as a machine to be fixed with standardized interventions, and he called for approaches that work with the system's adaptive nature: understanding local conditions, expecting variation, building on what already works and accepting that change emerges rather than being installed. The mobility program was designed in the machine tradition. It is a useful case for testing the complexity view.
What Happened on the Units
Interviews with unit managers, charge nurses, physical therapists and nursing assistants, together with the program's data, revealed patterns that the theory helps explain. The table links each feature of complex adaptive systems to what the team found.
| Feature of complex adaptive systems | What happened on the units |
|---|---|
| Agents act on internal rules | Where nurses believed mobility was physical therapy's job, the protocol was set aside |
| Interdependence | Units whose nursing assistants were included in planning mobilized more patients |
| Embedded systems | Units that shared therapists with outpatient clinics lost therapy support in the afternoons |
| Emergence | Two units invented a hallway walking chart that spread informally to a third |
| Sensitivity to small changes | A single gait belt stored in each room raised mobility on one unit more than training did |
| Tension and paradox | Fall-prevention alarms discouraged the very walking the program sought |
Why the Standard Rollout Failed
The rollout assumed that the same inputs would produce the same outputs everywhere. In a complex system, the same protocol meets different mental models, relationships, resources and competing priorities on each unit, and it is transformed by them. The weaker units were not led by weaker managers; they were systems in which the program's assumptions did not fit. On one oncology unit, for example, nurses feared that mobilizing patients with low platelet counts was unsafe, a concern the protocol had not addressed, and they reasonably declined to follow it.
Simple Rules Instead of Detailed Protocols
Complexity theory suggests that a few simple rules, applied locally, can produce complex adaptive behavior more reliably than detailed instructions. Plsek and Greenhalgh (2001) described how simple rules, minimum specifications rather than full blueprints, allow local agents to adapt while keeping a shared direction. For the mobility program, three rules might replace the 12-page protocol: every patient's mobility goal is set within 24 hours of admission; every staff member who enters the room helps the patient toward that goal; and any barrier to mobility is raised at the daily huddle.
Attractors and Feedback
Complex systems settle into patterns, sometimes called attractors, that are hard to disturb. The dominant attractor on most units was bed rest as the default, reinforced by fall alarms and by charting that recorded falls but not mobility. Changing the attractor requires changing what is noticed and rewarded. Units that succeeded made mobility visible: the hallway chart, a line in the shift report, a mobility score on the patient whiteboard. Feedback loops that report mobility alongside falls give staff reasons to act differently.
Learning From Positive Outliers
The complexity view encourages leaders to study what already works. The two units that invented the hallway chart did not follow the protocol more faithfully; they adapted it to their own routines. Their nursing assistants, not only their nurses, owned the walking rounds. These positive outliers offer more usable lessons for the weaker units than the original protocol did, because they show how the program can live in real conditions.
Diffusion as Well as Design
Research on how innovations spread in health service organizations supports the same conclusion. Greenhalgh et al. (2004) found that adoption depends on how potential adopters perceive an innovation, on the social networks that carry it, on the readiness and resources of the receiving system and on the extent to which the innovation can be adapted, or reinvented, to fit local needs. An innovation that can be reinvented spreads further than one that must be adopted whole.
A Redesigned Spread Plan
For the next year, Kingsmere will replace the uniform rollout with a plan built on these ideas. The three simple rules will replace the detailed protocol. Each unit will hold a short design session to adapt the rules to its patients, staffing and physical layout, with nursing assistants and therapists present. Staff from the two successful units will visit the others as peers, not trainers. The oncology unit will work with hematology to set safe mobility criteria for patients with low platelet counts. Fall alarm policies will be reviewed so they do not penalize walking. Each unit will track mobility and falls together and share results monthly.
Implications for Leaders
Leading in a complex system requires different habits: setting direction and a few rules rather than detailed procedures, expecting and learning from variation, paying attention to relationships and informal networks, making the desired behavior visible and adjusting as results emerge. Leaders must also resist the urge to blame individuals for outcomes that reflect how a system responds. Accountability remains, but it is directed at learning and adaptation rather than compliance alone.
Conclusion
The mobility program produced nine different results because it entered nine different systems. Complex adaptive systems theory explains the variation as the predictable result of agents with different mental models, relationships and constraints, rather than as a failure of management. Simple rules, local adaptation, visible feedback, attention to positive outliers and peer-led spread offer a better path. The same lesson applies to most improvement programs a health system will launch: design for adaptation, not uniformity.
References
Braithwaite, J. (2018). Changing how we think about healthcare improvement. BMJ, 361, Article k2014. https://doi.org/10.1136/bmj.k2014
Greenhalgh, T., Robert, G., Macfarlane, F., Bate, P., & Kyriakidou, O. (2004). Diffusion of innovations in service organizations: Systematic review and recommendations. The Milbank Quarterly, 82(4), 581-629. https://doi.org/10.1111/j.0887-378X.2004.00325.x
Plsek, P. E., & Greenhalgh, T. (2001). The challenge of complexity in health care. BMJ, 323(7313), 625-628. https://doi.org/10.1136/bmj.323.7313.625
Reading the EDN 818 Module 3 assignment instructions
Complex Adaptive System Theory is named in Aspen's description of EDN 818, and with the third module's prompt reserved for the class, this example applies the theory to an improvement program that spread unevenly. Here the task is usually to state the theory correctly, use it on a real situation from your workplace and draw conclusions a leader could act on. Choose a situation with a puzzle the theory can explain, such as variation in results or unintended consequences. Define the theory by features you can observe, then show each feature in your case. Contrast what the theory predicts with what a conventional plan assumed. End with changes to how the work should be led, not only with a statement that health care is complex.
How the EDN 818 Module 3 example is put together
The paper opens with a mobility protocol, training and target applied identically on nine units, and results that ranged from routine walking to barely any use. It defines a complex adaptive system through agents with internal rules, interdependence, embedded systems, emergence and sensitivity to small changes, and introduces the argument that improvement programs underperform when they ignore those features. A two-column table links six features to observations, from nurses who saw mobility as therapy's job to fall alarms that discouraged walking. Later sections explain why the uniform rollout failed, replace a 12-page protocol with three simple rules, discuss attractors and visible feedback, draw lessons from two units that invented a hallway walking chart, connect to research on reinvention and set out a redesigned spread plan.
EDN 818 Module 3 rubric: what earns full marks
Applied theory papers are graded on accurate explanation, convincing application, insight and practical implications. This example earns its application marks by linking each feature of the theory to a specific observation in the table, rather than describing the theory and the case separately. It cites three APA sources: Plsek and Greenhalgh's BMJ article on complexity in health care, Braithwaite's BMJ analysis of how improvement thinking needs to change, and the Greenhalgh review of how innovations spread. Reframing the weaker units' results as system responses rather than management failures shows the shift in thinking the theory is meant to produce. The redesigned spread plan turns that insight into concrete leadership actions, which graders expect in a doctoral leadership course.
EDN 818 Module 3 help: mistakes that cost marks
Many complexity papers describe the theory in abstract terms and then offer conventional recommendations that ignore it. Test yourself: would your recommendations look different if you had never read the theory? If not, rework them. Pick a case with real variation or surprise. Observe or interview people involved, since complex systems are understood from the inside. Look for positive outliers, units or teams where the change worked unexpectedly well, and ask what they did differently. Avoid treating complexity as an excuse for having no plan; simple rules and feedback are plans. If the theory's vocabulary feels slippery, a tutor can help you match each feature to an example from your own workplace before you write.
Write yours, or have the desk draft it
This paper is an original model document written by our desk, not a submitted student paper and not an official Aspen University document. Read it for the moves, then write your own to the instructions in your classroom. If you want one built to your exact prompt and rubric, the first custom sample is free and arrives in 24 to 48 hours.
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EDN 818 Module 3 questions, answered
What does EDN 818 Module 3 usually ask for?
Aspen's EDN 818 asks leaders to explore innovation in complex systems with theories such as Complex Adaptive System Theory, so applying that theory to a real change is a typical third assignment. Follow your classroom prompt.
What is a complex adaptive system in health care?
A system of people who act on their own understanding and affect one another's context, so that outcomes emerge from their interactions rather than from plans or directives alone.
What are simple rules in complexity theory?
A few minimum specifications that give shared direction while letting local teams adapt how they reach the goal, instead of a detailed protocol applied the same way everywhere.
Where can I find a free EDN 818 Module 3 sample paper?
The complete paper is above, applying complex adaptive systems theory to a mobility program with uneven results, with a table linking six features of the theory to what happened on the units.
Why do standard rollouts produce different results on different units?
Each unit has its own mental models, relationships, resources and competing demands, which transform the same protocol into different practices.