| Course | NR 643 Informatics Nurse Specialist Concluding Graduate Experience II |
|---|---|
| Week | 3 |
| Paper type | Adoption evidence write-up |
| Length | About 1,120 words, 5 pages |
| Format | APA 7 student paper |
| School | Chamberlain University |
| Program | MSN, Nursing Informatics |
| Updated | October 2026 |
Free sample paper for NR 643 Week 3
Adoption Evidence Write-Up: The PRN Reassessment Task on 4 West Reported as a Ladder, From Tasks Shown to Nurses Returning Week After Week
Student Name
College of Nursing, Chamberlain University
NR 643: Informatics Nurse Specialist Concluding Graduate Experience II
Instructor Name
Month Day, Year
Adoption Evidence Write-Up: The PRN Reassessment Task on 4 West Reported as a Ladder, From Tasks Shown to Nurses Returning Week After Week
The Population
Registered nurses on the 4 West assignment list who administered one or more listed doses between 15 February and 28 March 2027: 58. Removed: three superusers who tested the build and the student, who works on the unit. The analyst never gave a dose and was not in the population. Counted population: 54 nurses, including 9 float and agency nurses.
Source for every count below: the task completion log in the record, exported weekly by the clinical documentation analyst, and the staff assignment list for 4 West. Task counts include all tasks created on the unit; nurse counts exclude the four removed.
The Ladder
| Rung | What it shows | Count | Population |
|---|---|---|---|
| 1. Task shown | The record created a task | 1,507 tasks | All listed doses scanned on 4 West |
| 2. Task opened | A nurse clicked the task | 1,104 of 1,507 (73%) | Tasks |
| 2a. Distinct users who opened a task | Reach | 49 of 54 nurses (91%) | Nurses |
| 3. Task completed from the task | The nurse opened the task and filed the row | 896 of 1,507 (59%) | Tasks |
| 4. Same nurse returning | A nurse who completed a task in weeks 1 to 3 completed one again in weeks 4 to 6 | 41 of 46 (89%) | Nurses who completed one in weeks 1 to 3 |
Each rung is a different claim. A task shown says only that the build fired. An opened task says someone looked. A completed task says someone reached the end of the action. A nurse returning in a later week says something about habit, and it is the only rung that does.
Of the 1,507 tasks, 31 fired for doses later recorded as "Held" or "Refused," the known trigger difference. All 31 were dismissed with "Dose not given." Without them, 1,476 tasks were for given doses.
What Happened to Every Task
| Outcome | Tasks |
|---|---|
| Completed after opening the task | 896 |
| Completed by filing the row directly from the flowsheet, task never opened | 122 |
| Dismissed with a reason | 141, of which 31 "Dose not given" |
| Expired at end of shift with no value filed | 348 |
| Total | 1,507 |
The 122 completed without opening the task matter: the nurse went to the right row unprompted, perhaps because the task was visible on the list. Together with the 896, 1,018 tasks ended with a value in the Pain Reassessment row.
The Shape, Week by Week
| Week from 15 February | Tasks | Opened | Opened share |
|---|---|---|---|
| 1 | 252 | 161 | 64% |
| 2 | 249 | 177 | 71% |
| 3 | 251 | 188 | 75% |
| 4 | 248 | 188 | 76% |
| 5 | 254 | 188 | 74% |
| 6 | 253 | 202 | 80% |
Opening rose over the first three weeks and then held between 74% and 80%. There is no sign of the early rise fading by week 6, though six weeks is too short to say it will not.
Evidence Pointing the Other Way
Nights. Tasks created between 19:00 and 07:00 were opened 58% of the time, against 81% on days. Night nurses carry more patients, and two said in passing that they clear the list at the end of the shift.
Float and agency nurses. Of the 9, 4 opened a task; their completed share was under 30%. They were not at the go-live huddles and received only the tip sheet.
Two nurses said they dismiss tasks in bulk at the start of a shift to clear the list. The dismissal log shows 23 dismissals with reason "Other" within two minutes of each other on four occasions, consistent with that account.
The 348 expired tasks, 23% of the total, are the largest single outcome after completion. Some of these doses may have been reassessed and filed in the routine row or a note, which the companion measure will show.
Alert research shows acceptance falls as workload and repetition rise (Ancker et al., 2017), and the night pattern fits that.
Workarounds Seen in the Log
The bulk dismissals are a workaround of a familiar kind: when a list grows faster than a nurse can work it, people find ways to clear it (Koppel et al., 2008). The log cannot say whether those patients were reassessed.
What the Ladder Does Not Show
Whether reassessments were done at the bedside, and whether the values filed were accurate. The task log measures interaction with the build, not care.
How the Counts Were Checked
The analyst's export and the student's tally of the ladder were compared for weeks 1 and 2 by the clinical informatics manager, who found one difference: a task counted as completed that had been completed by a superuser covering the patient, who was removed from the population. Tasks completed by removed users stay in the task counts but not in the nurse counts, which the tables reflect. Reach, adoption and maintenance are separate claims in implementation research (Proctor et al., 2011), and the ladder keeps them apart.
What the Numbers Mean for Float and Night Staff
The two groups with the lowest use are the two that the go-live plan reached least. Float and agency nurses missed the huddles and met the task cold. Night nurses had no superuser on shift. Both gaps are about how the change was introduced, not about the build itself, and both have simple remedies already started. A second reading of the ladder after the remedies, in the sustainment period, will show whether they worked. If night use stays low after the huddle reminders, the next step would be to ask night nurses directly what gets in the way, rather than adding another prompt.
Comparison With the Plan
The project plan expected that tasks would be opened about two times in three. The observed 73% is slightly better. It expected little difference between shifts; the 23-point gap between days and nights was not foreseen.
What This Means for the Criterion
Use is broad, with 91% of nurses opening at least one task, and returning, at 89% of early completers. That is consistent with the build being used enough to move the outcome. Whether it did is the results summary's question.
Implications Already Acted On
The tip sheet was added to the float pool's orientation folder on 10 March, and the night charge nurses were asked to mention the task at the 19:00 huddle for two weeks. These changes fall inside the measurement window and will be noted in the results summary.
References
Ancker, J. S., Edwards, A., Nosal, S., Hauser, D., Mauer, E., & Kaushal, R. (2017). Effects of workload, work complexity, and repeated alerts on alert fatigue in a clinical decision support system. BMC Medical Informatics and Decision Making, 17, Article 36. https://doi.org/10.1186/s12911-017-0430-8
Koppel, R., Wetterneck, T., Telles, J. L., & Karsh, B.-T. (2008). Workarounds to barcode medication administration systems: Their occurrences, causes, and threats to patient safety. Journal of the American Medical Informatics Association, 15(4), 408-423. https://doi.org/10.1197/jamia.M2616
Proctor, E., Silmere, H., Raghavan, R., Hovmand, P., Aarons, G., Bunger, A., Griffey, R., & Hensley, M. (2011). Outcomes for implementation research: Conceptual distinctions, measurement challenges, and research agenda. Administration and Policy in Mental Health and Mental Health Services Research, 38(2), 65-76. https://doi.org/10.1007/s10488-010-0319-7
What the NR 643 Week 3 assignment asks for
Report use as a ladder rather than a single number, because each rung makes a different claim: a screen or task shown, distinct users reached, a completed action and the same user returning in a later week. Say which rung each figure stands on. Take builders and superusers out of every count and state the exclusion. Give each count its population, since a count without a denominator cannot be judged. Show the shape across weeks, because early enthusiasm can fade or build. Keep any evidence that points the other way, such as a shift or group with low use or signs of bulk dismissal. Say how the counts were checked and what the ladder cannot show about care itself.
How the NR 643 Week 3 example is put together
The sample's population is 58 nurses less four removed, leaving 54 including 9 float and agency nurses. The ladder runs from 1,507 tasks shown to 1,104 opened, 49 of 54 nurses reached, 896 completed from the task and 41 of 46 early completers returning. A second table accounts for every task: completed from the task, completed directly, dismissed and expired. Weekly opening rises from 64% to 80%. Nights at 58% against 81% on days, low use among float nurses and bulk dismissals are reported as contrary evidence. A manager's check of two weeks of counts found one difference. Remedies for float and night staff are noted as falling inside the window.
Reading the NR 643 Week 3 grading rubric
Adoption write-ups lose most when they report a single figure, such as clicks or logins, as if it showed habit. Next is a count that includes the build team and superusers, who can account for much of the early traffic. Counts without populations, such as 1,100 tasks opened, cannot be judged. Many write-ups give one total for the whole period and hide whether use is fading. Evidence pointing the other way, such as a shift with much lower use, is often left out to keep the story tidy. Write-ups that never say what the log cannot show, such as whether care was delivered, claim more than usage data can support. Write-ups that never explain how the counts were checked leave the reader to take every figure on trust.
Common NR 643 Week 3 mistakes, and how to avoid them
Usage logs are rich but easy to misread, and a single impressive number is tempting. We can help you lay out a ladder of rungs, define your population and remove the builders from every count. We can also help you show the weekly shape and write up the evidence that points the other way. The data come from your build, and the reading of them is yours. A second reader can also check that every count carries its population and that nobody who built or taught the change has slipped back into the totals.
Get a NR 643 Week 3 example written to your instructions
Send the Week 3 instructions as your section words them, the rubric, and whatever usage figures you have been able to pull, along with the name of the report they came out of. A custom example write-up is built around those figures and returned inside 24-48h. The first one is free.
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NR 643 Week 3 questions, answered
The record shows hardly anybody used it. Is that a failed assignment?
No. A low figure is a finding about something specific: an access right never granted, a link sitting three screens away from where the work happens, training that reached one shift, or a build that solves a problem nobody has at eleven at night. Write-ups tracing a small number back to one of those score better than write-ups reporting a large one.
Can staff be asked whether they used it?
Asked answers are useful as explanation and weak as measurement. People overstate use in good faith, and a form returned by twelve of forty tells you about those twelve. The stronger arrangement puts the recorded figure first and uses what people said to explain its shape, which is a different job from proving the shape exists.
How is the usage report identified?
By name, version, the parameters set when it ran, the date range and the person who ran it. Reports with similar names count different things, and one of them will be rebuilt while your project is live. Recording those five details is what lets an instructor, a successor, or you in three months produce the same figure twice.
Where can I find a free NR 643 Week 3 sample paper?
You can read the whole adoption write-up, ladder and weekly figures included, right here.
Why does the NR 643 Week 3 write-up use a ladder instead of one number?
A task shown, opened, completed or used again in a later week each says something different, and only returning use says anything about habit.