The second stage of NR-702C is where the problem stops being described and starts being measured. The written task is a problem statement with a defensible local number inside it: what the operational definition is, where the data came from, what window it covers, and how the site's performance compares with what the evidence and the benchmark say it should be. At 256 practicum hours the term can support a genuine baseline pull rather than a borrowed benchmark, and a committee will expect that. Clinical hours, hour logs, site forms and mentor evaluations are your own record and are never drafted, reconstructed or estimated with help. Your section may print this as NR 702C or NR702C; it is the same course. Chamberlain publishes no syllabi outside Canvas. The placement here is our teaching judgment from the course's catalog arc; your section's rubric decides what your week actually asks.
What NR-702C Week 2 asks for
Consider a 400-bed community hospital where the emergency department believes its sepsis bundle compliance is poor. Everyone on the unit says so. Nobody can say by how much, against what definition, over which months, or whether the shortfall lives in lactate timing, antibiotic timing or fluid volume. That gap between shared belief and stated number is the entire work of a second-stage project document.
A doctoral problem statement has four moving parts and they have to appear in this order or the argument leaks. First, the practice that evidence supports, stated as a settled expectation. Second, the local performance against that expectation, quantified. Third, the consequence of the difference in terms the organization already tracks. Fourth, the reason the gap persists, which is where the systems reasoning starts and where most students stop early.
The measurement layer is graded harder than students expect because it is the layer a committee can check. If your operational definition is loose, the number underneath it means nothing, and every later section built on it inherits the weakness. A number without a definition is decoration. A number with a definition, a denominator, a source system and a date range is an argument.
The hour reality shapes what you can claim here. A 256-hour term realistically supports going into the source data yourself with an analyst, understanding how the field is populated, and discovering the counting quirks that make a report disagree with the unit's lived experience. That discovery is often the most doctoral paragraph in the whole document, because it explains why the organization has been arguing about a number for two years.
What this manual does not touch
Practicum hours, the hour log, encounter counts, site paperwork and preceptor or mentor evaluations belong to you and to the people who verify them. Nothing in this manual helps compose, reconstruct or estimate any of that. The written layer is what a manual can teach: how to define a measure, how to present a baseline honestly, how to argue from a number to a cause.
Where your writing draws on what you saw in a real department, the material must be de-identified before it becomes prose. Report at the level of the unit, the shift, the process step or the month. Do not name patients, do not carry dates of service, do not include any detail that would let a reader identify an individual encounter. Aggregate data is both the compliant currency and the persuasive one.
The NR-702C Week 2 method, step by step
Six moves for building a problem statement that a committee can verify.
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Write the operational definition before you write the number
Numerator, denominator, inclusion criteria, exclusion criteria, and the clock. When does the window start, what event stops it, and who decides. Two departments arguing about compliance are almost always using two different clocks.
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Trace the number back to the field it comes from
Which system, which report, which field, populated by whom and at what point in the workflow. If a timestamp is entered retrospectively at the end of a shift, your measure is partly a documentation measure, and the document should say so.
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Choose a comparison your reader already accepts
A published benchmark, a system target, a prior period on the same unit, or a peer unit inside the same organization. Say which one and why. A comparison the organization does not recognize turns a finding into an opinion.
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Show the gap over time rather than at a point
A single quarter can be noise. Several consecutive months make a pattern, and a pattern is what justifies a project rather than a conversation. If you only have a point, say it is a point.
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Convert the gap into organizational consequence
Excess length of stay, avoidable transfers, rework, overtime, regulatory exposure, or harm events. Use the units your finance and quality departments use, because the reader deciding whether this project gets support thinks in those units.
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Give at least two candidate causes and say how you will tell them apart
Knowledge, workflow design, staffing, technology, accountability. A problem statement that names one cause has quietly become a solution statement, and the later evidence stage loses its purpose.
A layout and word budget for a measured problem statement
Our frame for a data-anchored problem section, sized for roughly 1,800 to 2,200 words. This is our own outline rather than anything the university issues, and your week's rubric outranks it wherever they disagree.
| Section | What belongs in it | Word target |
|---|---|---|
| The expected practice | What settled evidence and professional guidance say should happen, stated as an expectation rather than as a discovery. | 200 to 240 |
| Operational definition | Numerator, denominator, inclusions, exclusions, the clock, and who or what records each element. | 180 to 220 |
| Local performance | The baseline with counts and denominators, the source system, the window, and any known limits of the extract. | 250 to 300 |
| Comparison and trend | The benchmark or prior period chosen, why it is the right comparator, and how the gap behaves across months. | 220 to 260 |
| Consequence | What the gap costs in the organization's own units, with the arithmetic shown rather than asserted. | 240 to 290 |
| Candidate causes | Two or three plausible drivers, each with the observation or data that would confirm or eliminate it. | 250 to 300 |
| Data limitations | What the extract cannot see, stated before a reader finds it, and what that means for interpretation. | 140 to 180 |
Evidence craft for baseline writing
Counts before percentages, always. Write that 212 of 671 qualifying encounters met the timing standard across five months, then give the proportion. A percentage without its base hides sample size, and a committee reading a small denominator behind a confident percentage will discount the whole section.
Name the extract and its date. A report pulled in one month and a report pulled in the next rarely agree, because retrospective documentation keeps landing. Say when you pulled it and whether the window is closed, and you preempt the most common challenge in a review meeting.
Separate what happened from what was documented. These are different variables and nursing data conflates them constantly. If the measure depends on a field completed after the fact, the honest sentence is that the baseline reflects documented performance, and that distinction may itself be part of the problem.
Attribute benchmarks to the body that publishes them, with a year. Targets move. A benchmark quoted without an issuing organization and an edition is a claim about the present made from an unknown date, and doctoral graders check.
Keep causal language out of a descriptive section. Associated with, coincided with, was observed alongside. The word caused belongs after you have evidence that supports it, and in a baseline section you almost never do.
Five mistakes that cost points in this week's territory
- Borrowing a national statistic as the local baseline. A published rate describes a population you did not sample. It sets the expectation; it cannot be your site's performance.
- An undefined measure. Compliance, timely, appropriate and adherence are all words that need a numerator, a denominator and a clock before they mean anything.
- One month of data presented as a trend. A single point is a snapshot. Calling it a trend invites the one question you cannot answer in a defense.
- Consequence written as adjectives. Significant burden and poor outcomes are placeholders. Excess days, transfers, rework hours and events are consequences.
- Skipping data limitations. Every extract has blind spots. Naming them first is credibility; letting a reviewer find them is a scoring event.
Before you submit
- The operational definition appears before the first number does
- Every rate carries its numerator and denominator
- The source system, report name and extract date are stated
- The comparator is named and justified, not assumed
- Consequence is expressed in units the organization already tracks
- At least two candidate causes appear, each with a way to test it
- No patient-level detail appears anywhere in the document
Writing the NR-702C problem statement?
Send the rubric and whatever baseline material you have out of Canvas. A premium original draft comes back in 24 to 48 hours with the measure defined, the numbers presented with their bases and the causal language kept honest, and revisions run until the grade lands. Hours, logs and evaluations stay entirely yours.