| Course | NURS 6451 Evaluation Methods for Health Information Technology |
|---|---|
| Week | Week 4 |
| Paper type | Evaluation design paper |
| Length | About 1,030 words, 6 pages |
| Format | APA 7 student paper |
| School | Walden University |
| Program | Master of Science in Nursing (MSN) |
| Updated | September 2026 |
Free sample paper for NURS 6451 Week 4
Choosing a Design to Answer One Question: Why a Non-Randomized Stepped-Wedge Comparison Fits the Messaging App Rollout Better Than a Pre-Post Study
Student Name
College of Nursing, Walden University
NURS 6451: Evaluation Methods for Health Information Technology
Instructor Name
Month Day, Year
Choosing a Design to Answer One Question: Why a Non-Randomized Stepped-Wedge Comparison Fits the Messaging App Rollout Better Than a Pre-Post Study
The Question the Design Must Serve
The evaluation asks one question: since pagers gave way to the messaging app across the four medical-surgical units, has the wait between a nurse sending a routine request and the responsible prescriber first acknowledging it become shorter, longer or neither? A design can only be judged against the question it serves. This one needs a comparison between pager and app periods that is not confused by everything else that changed at the hospital over the same months.
Facts That Constrain the Design
The rollout was planned before the evaluation. Go-live dates for the four units are staggered at six-week intervals, and the order was set by device delivery and training schedules, not by chance. Two units are already live. Two remain on pagers, and their go-live dates are fixed. For every message, the app logs when it left the sender, when it was opened and when the first answer came back; the paging system logs nothing beyond the fact that a page went out. Any design must therefore use prospective observation for pager periods and must accept that the order of units was not randomized.
Design 1: A Single Pre-Post Comparison, Rejected
The simplest design would compare acknowledgment intervals on all four units before go-live with intervals after. It is rejected. Anything else that changed during those months would be credited to the app: a new hospitalist schedule, the arrival of new residents, a seasonal rise in census or a separate quality project on discharge timing. Pre-post comparisons without a concurrent comparison are common in the literature on messaging tools and are the weakest design for attributing change to the system (Lopez Bernal et al., 2017). For two of our units, the pre period has already passed unmeasured, which makes the design impossible to carry out fully in any case.
Design 2: An Interrupted Time Series on Each Unit, Kept as Fallback
An interrupted time series would measure the acknowledgment interval repeatedly, for example weekly, before and after each unit's go-live, and look for a change in level or trend at the go-live point. It is stronger than a single pre-post comparison because it models the existing trend and so is less likely to mistake a gradual change for an effect of the app (Lopez Bernal et al., 2017). Its weakness is that it cannot separate the app's effect from a hospital-wide event occurring at about the same time, since each unit serves as its own control. It is kept as the fallback if the stepped-wedge comparison cannot be run as planned, and for the two units already live it is partly all that is possible.
Design 3: A Stepped-Wedge Comparison, Chosen
In a stepped-wedge design, clusters, here units, cross from the control condition to the intervention at different times, until all have crossed, and at each step the units still in the control condition act as concurrent comparisons for those that have switched (Hemming et al., 2015). Our staggered go-live already creates that structure. During the weeks when Units 3 and 4 remain on pagers and Units 1 and 2 use the app, the pager units provide a concurrent comparison; when Unit 3 switches, Unit 4 still does. The comparison protects against hospital-wide events, because an event that lengthens acknowledgment everywhere will appear in the pager units too. The design also uses the time series within each unit.
The design is non-randomized, and the paper says so plainly. Because the order was fixed by operational schedules, units that went first may differ from units that went later in ways that affect acknowledgment, such as patient mix or prescriber staffing. The claim the evaluation can support is therefore an association adjusted for time, not a randomized estimate of the app's effect. Stepped-wedge trials are usually randomized for exactly this reason (Hemming et al., 2015), and a future rollout at this hospital could randomize order if the evaluation is planned before scheduling.
What Each Result Would Mean
The design is chosen partly for how its results can be read. If acknowledgment intervals fall on each unit when it switches, while units still on pagers show no change in the same weeks, the association with the app is as strong as a non-randomized design allows. If intervals fall on switched units and on pager units alike, something hospital-wide is at work, and the app cannot take credit. If intervals rise after switching, the usability findings about the recipient directory become the first explanation to test. And if the result differs sharply between the first two units and the last two, the difference between units that were chosen to go first and those that went later becomes the finding to investigate. Writing these readings down before any data exist protects the evaluation from interpreting whatever appears as support for the app.
Threats to Validity and How They Are Handled
Selection: units differ at baseline; the analysis will compare within units over time as well as between units. History: hospital-wide events are handled by the concurrent pager units; unit-specific events, such as a manager change, will be logged. Measurement: the pager baseline comes from observation and the app period from logs, so the two may not measure identical events; the measurement plan will define acknowledgment the same way for both and will observe a sample of app-period requests to check the log definition. Hawthorne effect: staff aware of observation may respond faster; observation will run long enough on each unit for its novelty to fade.
What the Design Does Not Include
No sample size calculation is included. The number of units is fixed by the rollout, and this paper's task is to match the design to the question. A statistician will advise on the number of time points and on an analysis model that accounts for clustering and time before the analysis plan is final. Health informatics evaluation guidance recommends reporting such design choices and their limits openly (Talmon et al., 2009), and this paper is written to be the first entry in that record.
References
Hemming, K., Haines, T. P., Chilton, P. J., Girling, A. J., & Lilford, R. J. (2015). The stepped wedge cluster randomised trial: Rationale, design, analysis, and reporting. BMJ, 350, h391. https://doi.org/10.1136/bmj.h391
Lopez Bernal, J., Cummins, S., & Gasparrini, A. (2017). Interrupted time series regression for the evaluation of public health interventions: A tutorial. International Journal of Epidemiology, 46(1), 348-355. https://doi.org/10.1093/ije/dyw098
Talmon, J., Ammenwerth, E., Brender, J., de Keizer, N., Nykänen, P., & Rigby, M. (2009). STARE-HI: Statement on reporting of evaluation studies in health informatics. International Journal of Medical Informatics, 78(1), 1-9. https://doi.org/10.1016/j.ijmedinf.2008.09.002
The Walden NURS 6451 Week 4 instructions
The Week 4 prompt generally asks you to select and justify an evaluation design for your question, comparing alternatives and addressing threats to validity. Many sections expect you to consider experimental, quasi-experimental and observational options and to explain constraints of the real setting. Papers usually run three to five pages. Restate your question first, then describe the facts of the implementation that limit your options, such as schedules already set. Weigh at least two alternatives before choosing, name the main weakness of your choice plainly and describe how you will handle the principal threats to validity. If the order of implementation has already been set, say who set it and why.
How this NURS 6451 Week 4 example is built
The paper restates the question, then sets out constraints: staggered go-live dates fixed by device delivery and training, two units already live and pagers that record only sent pages. Design 1, a single pre-post comparison, is rejected with reasons. Design 2, an interrupted time series, is described with its strength and weakness and kept as fallback, citing a tutorial on time series regression. Design 3, a stepped wedge, is explained and chosen, citing a methods paper, with its non-randomized limitation stated in the same section. A section on how each result would be read, a threats section and a note on why no sample size appears close the paper.
Where the marks sit in the NURS 6451 Week 4 rubric
Design rubrics usually score alignment of design with question, consideration of alternatives, justification of the choice, treatment of threats to validity, feasibility and use of methodological sources. Alignment rewards a design that can actually answer the stated question. Alternatives earn credit when each is weighed fairly. Justification is judged on reasons tied to the setting. Threats to validity often carry significant weight and reward naming specific threats such as history, selection and measurement, with a response to each. Feasibility asks whether the design fits the real rollout. Methods sources should support design claims. Many rubrics also reward stating in advance how each possible result would be read, which guards against interpreting any result as success.
NURS 6451 Week 4 help: mistakes that cost marks
The most common loss is choosing a randomized trial that the setting could never support, or a single pre-post comparison without acknowledging its weakness. Another is naming threats to validity without saying how the design handles them. Some papers describe designs generically and never mention the real constraints. Others claim causal conclusions the design cannot support. Start from the question and the facts of the rollout, compare realistic options, state the chosen design's limit openly and write down how each possible result would be interpreted before any data exist. Also explain any missing sample size calculation rather than leaving the reader to wonder. Keep the design section tied to the real rollout.
Get a NURS 6451 Week 4 example written to your instructions
Send the Week 4 prompt and rubric with a short description of how your system is being rolled out, since staggered, single-date and pilot rollouts point to different designs. The first example costs nothing and lands in 24-48h, with the threats-to-validity table included for you to adapt.
More NURS 6451 papers and MSN samples
- NURS 6451 Week 1: Discussion post
- NURS 6451 Week 2: Evaluation question memo
- NURS 6451 Week 3: Literature matrix
- NURS 6451 Week 5: Measurement plan
- NURS 6451 Week 6: Usability analysis
- NURS 6451 Week 7: Workflow impact analysis
- NURS 6451 Week 8: Stakeholder analysis
- NURS 6451 Week 9: Discussion post
- NURS 6451 Week 10: Evaluation plan
- NURS 6451 Week 11: Reflection
- NURS 6501 Week 4: Perfusion and ventilation case study
- NURS 6441 Week 4: Work breakdown
- NURS 6512 Week 4: Focused SOAP Note
- NURS 6421 Week 4: Task analysis
NURS 6451 Week 4 questions, answered
Why not randomize which unit goes live first?
In the composite hospital, go-live order was fixed by device delivery and training schedules before anyone planned an evaluation, which is common with operational rollouts. The paper states this openly and treats the design as a non-randomized stepped wedge, with the weaker causal claim that implies. Where an organization can randomize the order, the same structure becomes stronger, and the paper notes that too.
Is an interrupted time series enough on its own?
It can be, if enough time points exist before and after go-live and nothing else hospital-wide changes at the same moment. The sample keeps it as the fallback because the stepped wedge adds concurrent comparison units, which protect against a hospital-wide event. Sections that assign a time series specifically get the analysis built around it instead.
Does the paper include a sample size calculation?
No, and it says why: the number of units is fixed by the rollout, and the paper's job at this stage is to match design to question. A statistician would advise on the number of time points and the analysis model later. If your prompt asks for power or sample considerations, the desk adds a section framed as questions for that consultation.
Where can I find a free NURS 6451 Week 4 sample paper?
The complete design paper, all three designs, the chosen stepped wedge, the result readings and the threats section, is free on this page. Design papers for other questions are available from the desk.
What is a stepped-wedge design in NURS 6451?
A design in which units switch to the new system at different times, so units still using the old system serve as concurrent comparisons. It suits staggered rollouts, and it is stronger when the order is randomized.