| Course | EDN 820 Evidence-Based Practice and Quality Improvement |
|---|---|
| Module | Module 5 |
| Paper type | Method selection paper |
| Length | About 1,032 words, 6 pages |
| Format | APA 7 student paper |
| School | Aspen University |
| Program | Doctor of Education |
| Updated | September 2026 |
Free sample paper for EDN 820 Module 5
Matching the Method to the Problem: Choosing How to Improve Perioperative Temperature Management
Student Name
Doctor of Education Program, Aspen University
EDN 820: Evidence-Based Practice and Quality Improvement
Instructor Name
Month Day, Year
Matching the Method to the Problem: Choosing How to Improve Perioperative Temperature Management
Allerton Community Hospital's process is stable, and it leaves about 22% of eligible patients colder than 36 degrees Celsius when they reach recovery, most often older patients in long orthopedic cases. The evidence supports prewarming. The perioperative team must now choose how to improve. Leaders at Allerton have used Lean in the emergency department and Six Sigma in the laboratory, and some expect one of those to be used again. This paper describes the problem's characteristics, compares three approaches, the Model for Improvement, Lean methods and Six Sigma, against them and explains the choice.
What Kind of Problem Is This?
The problem has four characteristics that matter for method choice. The solution is largely known: prewarming and consistent intraoperative warming. The main challenge is reliable delivery in a busy holding area and operating room, which involves several departments and many people. The outcome occurs often enough, about 45 times a month, to show change within weeks. And the team needs to learn quickly how the change works in Allerton's conditions, where the appraisal identified uncertainties about case length, space and measurement.
Three Methods
The Model for Improvement, developed by Associates in Process Improvement and promoted widely in health care, poses three questions, about the aim, the evidence that a change helped and the changes worth trying, and then tries changes out in quick plan-do-study-act cycles. Lean focuses on flow and the removal of waste, and suits problems of delay, crowding and wasted effort. Six Sigma focuses on reducing defects and variation through detailed statistical analysis, and suits processes where errors are rare and causes are unknown.
Comparing the Methods
The table rates each method against the project's needs.
| Project need | Model for Improvement | Lean | Six Sigma |
|---|---|---|---|
| Solution largely known; need reliable delivery | Strong fit: tests how to implement | Partial fit: redesigns flow | Weak fit: built to find unknown causes |
| Frequent outcome, quick feedback | Strong fit: monthly or weekly data guide cycles | Moderate | Moderate; strength lies in rare defects |
| Many departments and roles | Strong fit: small tests build buy-in | Strong fit: engages frontline staff | Moderate: often expert-led |
| Need to learn local conditions | Strong fit: prediction and study each cycle | Moderate | Moderate |
| Holding area crowding and flow | Moderate | Strong fit | Weak |
The Evidence on PDSA in Practice
The Model for Improvement is popular, but it is often done badly. In a systematic review of published improvement work, Taylor et al. (2014) reviewed 73 articles that reported PDSA work: under a fifth showed a series of linked cycles, and among the 47 examined closely, just 7 used numerical data gathered at least monthly to steer their cycles. Many projects called a single implementation a PDSA cycle. The method's value depends on features that are frequently skipped: explicit predictions, small initial tests, iteration and regular data.
The Choice
The team will use the Model for Improvement as its main method, because the problem is one of reliably implementing a known practice in a complex setting, with an outcome frequent enough for rapid learning. Because holding area flow is one of the main barriers, the team will borrow Lean tools, a process map of the patient's path from registration to the operating room and a simple time study of the holding area, to design the changes it tests. Six Sigma's statistical depth is not needed for a problem whose causes are largely understood.
The Three Questions for Allerton
For Allerton, the three questions become concrete. What are we trying to accomplish? Bring the rate of cold arrivals in recovery down from 22% to 10% within six months. How will we know a change is an improvement? Through a run chart of the outcome, process measures of prewarming and intraoperative warming, and balancing measures such as first-case start times. What changes can we make? Start prewarming during the preoperative interview, use warming gowns connected before patients arrive, and continue warming without interruption into the operating room, among others to be tested.
Using the Method Well
To avoid the shortcomings Taylor et al. (2014) documented, the team will write a prediction before every cycle, start each change with one nurse and a few patients, document each cycle's plan, results and decision, run several linked cycles rather than one, and review data weekly on a run chart, using the rules Perla et al. (2011) describe for detecting signals of change. The project will be written up following SQUIRE 2.0, which asks authors to describe the context, the interventions and their evolution, the measures and the results in enough detail for others to learn from them (Ogrinc et al., 2016).
What the Choice Does Not Mean
Choosing the Model for Improvement does not mean rejecting Lean or Six Sigma. If the project revealed a rare but serious defect with unclear causes, such as occasional burns from warming devices, Six Sigma tools would be appropriate. If holding area delays proved to be the main barrier, a larger Lean redesign might follow. The point is to match the method to the problem as it is understood now and to change methods if the problem turns out to be different.
What the Method Requires
The Model for Improvement is inexpensive in equipment but not in attention. It needs a team that meets briefly every week, a data analyst able to produce run charts on a regular schedule, a sponsor who can remove barriers across departments, and front-line staff given time to test changes rather than simply told to adopt them. Allerton's chief of anesthesia has agreed to sponsor the project, the quality department has assigned an analyst for four hours a week, and the perioperative manager has arranged coverage so holding area nurses can attend the weekly huddle.
Conclusion
Allerton's hypothermia problem is a problem of implementing known practice reliably across several departments, with frequent outcomes that allow rapid learning. The Model for Improvement fits those characteristics best, supplemented by Lean tools for flow. The evidence that PDSA is often applied poorly shapes how the team will use it: with predictions, small tests, iteration and frequent data. The choice follows the problem, which is the principle any improvement leader should apply.
References
Ogrinc, G., Davies, L., Goodman, D., Batalden, P., Davidoff, F., & Stevens, D. (2016). SQUIRE 2.0 (Standards for QUality Improvement Reporting Excellence): Revised publication guidelines from a detailed consensus process. BMJ Quality & Safety, 25(12), 986-992. https://doi.org/10.1136/bmjqs-2015-004411
Perla, R. J., Provost, L. P., & Murray, S. K. (2011). The run chart: A simple analytical tool for learning from variation in healthcare processes. BMJ Quality & Safety, 20(1), 46-51. https://doi.org/10.1136/bmjqs.2009.037895
Taylor, M. J., McNicholas, C., Nicolay, C., Darzi, A., Bell, D., & Reed, J. E. (2014). Systematic review of the application of the plan-do-study-act method to improve quality in healthcare. BMJ Quality & Safety, 23(4), 290-298. https://doi.org/10.1136/bmjqs-2013-001862
Reading the EDN 820 Module 5 assignment instructions
EDN 820, as Aspen describes it, equips health professionals with improvement tools, and choosing among them is a decision leaders face on every project. The fifth module's prompt is not public, so this example chooses an improvement method for a problem the course has been following. Describe the problem's characteristics that affect method choice: whether the solution is known, how often the outcome occurs, how many departments are involved and how much must be learned locally. Explain what each candidate method is designed to do. Compare the methods against the problem's needs, ideally in a table. Use evidence about how methods are applied in practice, not only how they are meant to work. State your choice, what you will borrow from other methods and what resources the choice requires.
How this EDN 820 Module 5 example is built
The paper starts with the hospital's habit of reusing whatever method worked last time. It describes the hypothermia problem through four characteristics, then summarizes the Model for Improvement, Lean and Six Sigma. A four-column table rates each against five needs, from reliable delivery of a known practice to holding area crowding. A section reports that fewer than 20% of 73 published PDSA projects documented iterative cycles. The choice follows: the Model for Improvement, with a Lean process map and time study for the holding area. The three questions are then written for this project, with an aim of 10%. Sections on applying the method well, the time and people it requires, and when Lean or Six Sigma would become the better tool close the paper.
Where the marks sit in the EDN 820 Module 5 rubric
Method selection papers earn credit for accurate descriptions, a comparison grounded in the problem, use of evidence and a justified choice. This example compares methods against needs drawn from the hospital's own data rather than general strengths, which is the reasoning instructors look for. Its three APA sources are a BMJ Quality and Safety systematic review of how PDSA cycles are applied, a guide to run charts from the same journal and the SQUIRE 2.0 reporting guidelines. The evidence on poorly executed PDSA cycles is turned into concrete commitments, such as written predictions and weekly data, which shows the method will be used properly. Explaining when another method would be better keeps the choice open to revision, a mark of mature judgment.
EDN 820 Module 5 help from the desk
Students often pick the method they know best and justify it afterward. Describe the problem first, then compare methods against it. Another weakness is describing methods as ideals without acknowledging how they are actually used; the evidence on PDSA shows common shortcuts to avoid. Be specific about what you will borrow from other methods and why. Write the Model for Improvement's three questions for your own project, with numbers. Name the resources the method needs, such as an analyst and meeting time. Keep the table honest; no method is best at everything. If the differences between the methods still seem vague, a tutor can walk you through one example project in each so you can see how they differ in practice.
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 820 Module 3: Appraising Evidence for Applicability
- EDN 820 Module 4: Reading Patient Outcome Data
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- EDN 820 Module 7: Plan-Do-Study-Act Cycles
- EDN 820 Module 8: Evaluating Improvement Results
- EDN 812 Module 6: Root Cause Analysis of a Sentinel Event
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EDN 820 Module 5 questions, answered
What does EDN 820 Module 5 usually ask for?
Aspen's EDN 820 gives professionals tools for quality improvement, so choosing and justifying an improvement method for a specific problem is a typical fifth assignment. Follow your classroom prompt.
What are the three questions of the Model for Improvement?
What are we trying to accomplish, how will we know that a change is an improvement, and what changes can we make that will result in improvement.
When is Six Sigma a better choice than PDSA?
When defects are rare, their causes are unknown and detailed statistical analysis is needed to find them, rather than when a known practice needs reliable implementation.
Where can I find a free EDN 820 Module 5 sample paper?
The example is posted above in full: a comparison of the Model for Improvement, Lean and Six Sigma for a hypothermia project, with a table rating each against the project's needs.
Why are PDSA cycles often done poorly?
A systematic review found that most published projects did not document iterative cycles, predictions or frequent data, treating a single rollout as a cycle.