Earplugs and eye masks at night on one composite ICU arrive with their measure fixed, a delirium p-chart and run rule, in the practice change proposal NU504 often sets for Unit 9. Searches like "nu 504 unit 9 assignment example", "nu504 unit 9 sample" and "nu504 unit 9 example" land here.
Practice Change Proposal: A Nine-Month Monitored Pilot of Nightly Earplugs and Eye Masks on a 16-Bed Mixed ICU, With the Measure Fixed Before the Change
[Student Name]
Purdue University Global
NU504: Scientific and Analytic Approaches to Advanced Evidence-Based Practice
Unit 9 Assignment
[Instructor Name]
[Date]
The unit, its baseline figures and the chart limits are composite; the evidence cited is published.
Summary
This proposal asks unit leadership to approve a nine-month pilot in which every patient who can wear them is offered foam earplugs and a contoured eye mask each night. The evidence supports the pilot but not certainty: pooled studies associate earplugs with a lower risk of delirium, at low certainty, and perceived sleep improves more reliably than delirium does (Hu, Jiang, Chen, et al., 2015; Litton et al., 2016). The proposal is sized to that evidence. It adds a cheap, low-risk practice and measures it well enough to know whether it helped here.
The Practice
At [2200], the night nurse offers earplugs and an eye mask to every patient with a Richmond Agitation-Sedation Scale score of -3 or lighter, explains them in one sentence, and fits them if the patient agrees. The offer is repeated at the [0200] check if the patient removed them. Refusal is documented as a choice, not a failure. Earplugs and masks are removed for any assessment, procedure or family visit, and never used when a patient cannot remove them and cannot signal distress. The practice sits alongside the unit's existing sedation and mobility practices rather than replacing them.
Measurement
Outcome measure: the monthly proportion of assessed patients with any positive CAM-ICU during their stay, where the denominator is patients assessed at least once. The CAM-ICU is used because it is validated for ventilated and nonverbal patients (Ely et al., 2001).
Process measure: the proportion of eligible patients wearing both aids at the [0200] check.
Balancing measures: unplanned removal of lines or tubes, and falls, each per 1,000 patient-days.
Baseline and limits. The unit's twelve baseline months give a center line of about 30 percent, with about [50] assessed patients a month. With that denominator, the p-chart's three-sigma limits run from roughly 11 to 49 percent. A single good month therefore proves nothing: a month at 20 percent would sit inside the limits and could be chance alone. The proposal states now how a real shift will be recognized: eight consecutive months below the center line. If the true rate fell to 20 percent, each month would have about a 96 percent chance of falling below 30 percent, and eight in a row would occur about seven times in ten, so the rule is likely, but not certain, to detect an effect of that size within the pilot.
Detection bias. Bedside nurses will know who wore the aids, and the CAM-ICU involves judgment. Each month, a second trained assessor who does not know the patient's aid use will repeat the CAM-ICU on [ten] randomly chosen patients, and agreement will be reported alongside the chart.
Resources and Training
Supplies: foam earplugs and contoured eye masks, about [$1.50] per patient-night. Training: a fifteen-minute huddle for each night shift on the offer script, contraindications and documentation, and a CAM-ICU refresher for the second assessors. Documentation: one flowsheet row for offered, accepted, refused or removed. Time: the offer adds about two minutes per patient at [2200].
Adherence
Adherence will be reported monthly, because it is the most likely point of failure. Nearly a third of the intervention group in a French trial took the earplugs out before morning (Demoule et al., 2017). A process measure well below 60 percent after the first two months will prompt a short round of patient interviews on why the aids are removed, and a revised offer.
Stopping Rule
The pilot will stop early if the balancing measures signal harm: a rise in unplanned device removals or falls above the upper control limit in any month, reviewed by the unit's quality nurse and medical director before restarting.
Who Is Involved
The night charge nurses lead the offer and the huddles, since the practice lives on their shift. The unit educator trains the second assessors and runs the monthly agreement check. The quality nurse builds and posts the p-chart, and the practice council reviews it each month in its regular meeting, so no new committee is needed. Families will be told about the pilot through a short brief approved by the family advisory council, and patients who are able will be asked each morning whether they kept the aids in and why, which feeds the adherence measure.
Evaluation and Decision
At nine months, the practice council will review the outcome chart, the second-assessor agreement, adherence and the balancing measures. If the run rule is met and the balancing measures are stable, the council will recommend making the practice standard and continuing the chart. If not, the council will report the result honestly, including a null result, since the evidence the proposal rests on is of low certainty and a null local result would be useful information.
References
Demoule, A., Carreira, S., Lavault, S., Pallanca, O., Morawiec, E., Mayaux, J., Arnulf, I., & Similowski, T. (2017). Impact of earplugs and eye mask on sleep in critically ill patients: A prospective randomized study. Critical Care, 21(1), 284. https://doi.org/10.1186/s13054-017-1865-0
Ely, E. W., Inouye, S. K., Bernard, G. R., Gordon, S., Francis, J., May, L., Truman, B., Speroff, T., Gautam, S., Margolin, R., Hart, R. P., & Dittus, R. (2001). Delirium in mechanically ventilated patients: Validity and reliability of the confusion assessment method for the intensive care unit (CAM-ICU). JAMA, 286(21), 2703-2710. https://doi.org/10.1001/jama.286.21.2703
Hu, R.-F., Jiang, X.-Y., Chen, J., Zeng, Z., Chen, X. Y., Li, Y., Huining, X., Evans, D. J., & Wang, S. (2015). Non-pharmacological interventions for sleep promotion in the intensive care unit. Cochrane Database of Systematic Reviews, 2015(10), CD008808. https://doi.org/10.1002/14651858.CD008808.pub2
Litton, E., Carnegie, V., Elliott, R., & Webb, S. A. R. (2016). The efficacy of earplugs as a sleep hygiene strategy for reducing delirium in the ICU: A systematic review and meta-analysis. Critical Care Medicine, 44(5), 992-999. https://doi.org/10.1097/CCM.0000000000001557
How this NU504 Unit 9 example is structured
Measurement is argued before logistics, because the course's standing question is what a number can bear. The outcome is defined precisely, any positive CAM-ICU among patients assessed at least once, reported monthly. With about 50 assessed patients a month and a baseline near 30 percent, the p-chart's three-sigma limits run from roughly 11 to 49 percent, so the proposal states in advance that a single good month proves nothing and that a shift will be recognized by eight consecutive months below the center line, which a true fall to 20 percent would likely meet within the pilot. Detection bias is handled with a monthly blinded second assessor, adherence has its own trigger, and a stopping rule names falls and device removals as the balancing signals.
Get an NU504 Unit 9 example written to your instructions
Name the change you want to propose and the outcome you would track, then attach the Unit 9 instructions, the rubric and your earlier synthesis. The proposal returns with the measure defined, numerator and denominator alike, the chart and decision rule stated in advance, and a pilot sized to the evidence. Free first custom sample in 24-48h. The paper above is an original model document written by our desk, not a submitted student paper and not an official Purdue University Global document.
NU504 Unit 9 questions, answered
What is a p-chart, and why use one instead of a significance test?
A p-chart plots a proportion over time, such as the monthly share of patients with delirium, against a center line and control limits calculated from the data. It suits unit-level monitoring because it shows whether variation is ordinary or signals real change, using agreed rules. A single before-and-after significance test ignores trends and month-to-month noise that the chart makes visible.
Why decide the measure before the pilot starts?
Because choosing it afterward lets the result shape the question. Fixing the outcome definition, denominator, chart and decision rule in advance means the pilot can fail visibly, which is what makes a success believable. Instructors in analytic courses tend to look for exactly this prespecification, since it mirrors how trials register their primary outcome before enrolling anyone.
Can a proposal recommend a change when certainty is low?
It can recommend a monitored trial of the change, which is different from recommending adoption. Low certainty means the true effect may differ substantially from the estimate, so the honest proposal pairs the change with measurement strong enough to show whether it helps locally. Low-risk, low-cost interventions are the usual candidates for that approach; risky or expensive ones typically need stronger evidence first.