| Course | NR 538 Population Health I: Assessment and Analysis of Data |
|---|---|
| Week | 5 |
| Paper type | Benchmark comparison brief |
| Length | About 1,120 words, 3 pages |
| Format | APA 7 student paper |
| School | Chamberlain University |
| Program | MSN, Population Health |
| Updated | September 2026 |
Free sample paper for NR 538 Week 5
Benchmark Comparison Brief: Our County's Fall Hospitalization Rate Set Beside the State, the Nation's Published Figures and Five Rural Peer Counties Chosen Before the Numbers Were Seen, and Why the Peers Decide the Finding
Student Name
College of Nursing, Chamberlain University
NR 538: Population Health I: Assessment and Analysis of Data
Instructor Name
Month Day, Year
Benchmark Comparison Brief: Our County's Fall Hospitalization Rate Set Beside the State, the Nation's Published Figures and Five Rural Peer Counties Chosen Before the Numbers Were Seen, and Why the Peers Decide the Finding
The Question
Our county's fall-related hospitalization rate among residents aged 65 or older was 120.4 per 10,000 in 2025. Is that high? The answer depends entirely on what it is compared with. Two counties can hold the same number of people and share almost nothing else: one may be a retirement destination with an older population, another a farming county with a younger one, and their fall rates will differ for reasons unrelated to how well either prevents falls. This brief chooses its comparisons first, explains the choice and only then reports the finding.
Choosing the Comparisons
Three comparisons were considered. The state rate is the one most often quoted. It is available and familiar, but the state's older population is concentrated in two metropolitan areas where older adults are, on average, younger, more likely to live with family and closer to hospitals. The national figures published by federal agencies give context but are not comparable to a county hospitalization rate, since the most recent national report on falls presents self-reported falls and fall death rates rather than hospitalizations (Kakara et al., 2023). The third option is a set of peer counties: counties similar to ours on the factors most likely to affect fall rates for reasons other than prevention.
The peer approach is used by national county health ranking programs, which have developed methods for comparing counties that account for differences in size and composition (Remington et al., 2015). I chose five peers before looking at their fall rates, using four criteria: rural designation, a share of residents aged 65 or older between 21% and 27%, median household income within 15% of ours, and a hospital within the county. Twelve counties in the state and two neighboring states met all four criteria. I chose the five closest in size to ours, so that each peer's rate would rest on a similar number of events. Choosing the peers before seeing their rates was deliberate. It is easy, once the numbers are visible, to include a county that makes ours look better or to drop one that makes ours look worse, and a reader has no way to know whether that happened unless the rules are stated first. The four criteria and the list of twelve eligible counties are kept with the analysis, so that anyone who doubts the choice can check it.
The Comparison
Table 1 shows the three-year average rate, 2023 to 2025, for our county, the five peers and the state.
Table 1
Fall Hospitalization Rates, Our County, Five Peers and the State
| Comparison | Share of population aged 65 or older | Share of those aged 85 or older | Fall hospitalizations per 10,000 aged 65 or older, 2023 to 2025 |
|---|---|---|---|
| Our county | 24.5% | 13.1% | 117.1 |
| Peer county A | 23.8% | 12.4% | 109.6 |
| Peer county B | 26.2% | 14.0% | 121.3 |
| Peer county C | 22.1% | 11.2% | 98.4 |
| Peer county D | 25.0% | 13.5% | 112.8 |
| Peer county E | 21.6% | 10.9% | 103.7 |
| Peer median | 109.6 | ||
| State | 18.3% | 9.8% | 96.2 |
What the Choice of Comparison Does to the Finding
Against the state, our county's rate is about 22% higher. A report using only that comparison would conclude that our county has a serious falls problem relative to the state. Against the peer median, our rate is about 7% higher. That is still higher, but the gap is a third of what the state comparison suggests.
The last column of the table explains much of the difference. Fall risk rises steeply with age, and the share of older adults who are 85 or older varies from 10.9% in peer county E to 14.0% in peer county B. The two peers with the oldest populations, B and D, have rates close to ours; the two with the youngest, C and E, have the lowest. The state, with the youngest older population of all, has the lowest rate. The ordering is almost exactly the ordering of the oldest-old share. This is what would be expected if age structure, rather than differences in prevention, drives most of the variation. Adults aged 85 or older fall more often and are more likely to be injured when they fall, so a county with more of them will have more fall hospitalizations per older resident even if every program works equally well. Our county sits just above peer county D, which has a slightly larger oldest-old share and a slightly lower rate, which is the one place in the table where our position may deserve a closer look. Our county's position among the peers is consistent with its age structure, not clearly worse than it.
What the Brief Can and Cannot Conclude
The brief can conclude that the state comparison overstates our county's disadvantage, and that among similar counties ours is somewhat above the middle, in line with its older population. It cannot conclude that our county's falls prevention is better or worse than the peers', because the rates are crude rather than age-adjusted and differences between counties in hospital admission practices, such as whether hip fractures are transferred elsewhere, may affect the counts. Age-adjusted rates, which I have requested from the state for all six counties, will allow a fairer comparison.
Using the Comparison
The peer comparison has a practical use beyond the finding, and it may be the most useful result of the exercise. Benchmarks are often used only to rank counties, which encourages either complacency or alarm. Used as a way to find neighbors doing something different, they become a source of ideas. Peer county C has the lowest rate among the peers and a moderately old population. Its health department runs an evidence-based falls prevention exercise program across six senior centers and has done so for five years. I will contact its staff to learn how the program operates and whether they track participants' hospitalizations. A benchmark is most useful not when it ranks us but when it points to a peer doing something worth learning from.
Future reports of our county's fall indicators will show the peer median alongside our rate and will not show the state rate without the peer median beside it. That change alone will prevent the most misleading reading of our data.
References
Kakara, R., Bergen, G., Burns, E., & Stevens, M. (2023). Nonfatal and fatal falls among adults aged ≥65 years: United States, 2020-2021. MMWR. Morbidity and Mortality Weekly Report, 72(35), 938-943. https://doi.org/10.15585/mmwr.mm7235a1
Remington, P. L., Catlin, B. B., & Gennuso, K. P. (2015). The County Health Rankings: Rationale and methods. Population Health Metrics, 13, Article 11. https://doi.org/10.1186/s12963-015-0044-2
What the NR 538 Week 5 assignment asks for
Comparing your population with benchmarks is the task. Prompts usually ask you to select comparison populations, present indicator values, interpret differences and consider their implications. Choose your comparisons before looking at their values, and explain why each fits. State averages are familiar but often mismatched, especially for rural counties. Consider peers matched on factors that affect the indicator for reasons other than program quality, such as age structure. Show how the finding changes with the comparison. Look for the factor that explains the pattern. Say what the comparison cannot conclude without adjusted rates. Use peers as a source of ideas, not only a ranking. Cite benchmarking methods in APA 7.
How the NR 538 Week 5 example is put together
The brief opens by asking whether 120.4 per 10,000 is high and noting that the answer depends on the comparison. It considers the state, national reports and peer counties, and explains four peer criteria set before any rate was seen. Table 1 compares three-year rates, older population shares and oldest-old shares for the county, five peers and the state. A section shows the finding shrinking from 22% above the state to 7% above peers, and the ordering following the share aged 85 or older. Limits include crude rates and differing hospital practices. The brief ends by contacting a peer county with a senior center exercise program and changing how future reports present comparisons.
Where the points sit in the NR 538 Week 5 rubric
Benchmark brief rubrics generally reward appropriate comparison populations, clear rationale for their selection, accurate presentation of data, thoughtful interpretation and recognition of limitations. Graders favor briefs in which comparisons are chosen by stated criteria before results are seen, since that guards against selective comparison. Showing how the conclusion changes with the benchmark demonstrates critical thinking. Identifying age structure as the likely driver shows understanding of confounding. Stating what cannot be concluded without age adjustment reflects rigor. Using a peer to find a promising program shows application. A clear comparison table and citations to benchmarking methods usually secure the remaining points. Stating which comparison future reports will use, and why, shows the brief will change practice.
NR 538 Week 5 help from the desk
A frequent weakness is comparing a county only with its state, which can exaggerate or hide differences. Add matched peers. Another is choosing peers after seeing their numbers, which invites selection that flatters the result. Fix criteria first. Students also ignore age structure when comparing rates of age-related conditions. Show it. Avoid concluding that a program is better or worse from crude rates. Do not rank counties without asking what the ranking is for. Keep the peer list and criteria with the analysis so others can check. Finally, look for a peer doing something different, since a comparison that points to an idea is more useful than one that only ranks.
Get a NR 538 Week 5 example written to your instructions
Send the prompt, the rubric and the brief template your classroom uses, along with the measure you are carrying and any reference your instructor named. We build a custom NR 538 example on your own material and return it inside 24-48h, first one free. Tell us the geography you need, since that decides which references are available at all.
More NR 538 papers and MSN samples
- NR 538 Week 1: Discussion Naming a Findable Group
- NR 538 Week 2: Data Source Appraisal
- NR 538 Week 3: Indicator Selection Memo
- NR 538 Week 4: Trend Analysis Write-Up
- NR 538 Week 6: Community Input Summary
- NR 538 Week 7: Priority Ranking Matrix
- NR 538 Week 8: Needs Assessment Report
- NR 530 Week 5: Defined Population Brief
NR 538 Week 5 questions, answered
Is a national target an acceptable reference?
Often yes, and it behaves differently from a place. A published target tells you the distance to an agreed goal but nothing about whether similar populations manage it, so the strongest briefs use a target alongside a peer rather than instead of one. Whichever you use, quote the year and the body that set it, because targets are revised and an out of date one undermines the whole page.
What if my population looks better than the reference?
Write that. A brief showing your population ahead of its peers is not a failed assignment, it is a finding that changes what the assessment ends up ranking. The weak response is to hunt for a worse reference until the gap appears, which shows in the grounds paragraph immediately. The strong response keeps the reference it defended and asks what the advantage costs elsewhere.
How do I handle two sources that define the measure differently?
Flag it inside the table, not in a footnote. One row can note that the two publishers count admissions differently, or use different age ranges, and the reading then says how much of the apparent gap that might explain. Silently placing the two side by side is the version that loses marks, because the brief looks confident about a difference that may be an artifact of wording.
Where can I find a free NR 538 Week 5 sample paper?
The five-peer falls benchmark brief above is the complete NR 538 Week 5 sample, and nothing is charged for it. If you need a comparison for a different indicator or county, send us the figures and a brief with pre-chosen peers can be prepared.
How should NR 538 peer counties be chosen?
By criteria set before looking at their values, matching on factors that affect the indicator for reasons other than program quality. The sample matches on rurality, share of older residents, income and having a hospital.