| Course | NR 538 Population Health I: Assessment and Analysis of Data |
|---|---|
| Week | 3 |
| Paper type | Indicator selection memo |
| Length | About 880 words, 1 pages |
| Format | Memo with APA 7 citations |
| School | Chamberlain University |
| Program | MSN, Population Health |
| Updated | September 2026 |
Free sample paper for NR 538 Week 3
Memorandum
To: County Health Director; copy to Area Agency on Aging Director and Ambulance Service Medical Director
From: Student Name, RN, Public Health Nurse
Date: Month Day, Year
Re: Recommended indicators for the older adult falls assessment, with reasons for the measures not recommended
Recommendation
I recommend that our assessment of serious fall risk among the county's 14,200 residents aged 65 or older track three indicators: the rate of repeat lift-assist callers, the rate of fall-related hospitalizations and the number of hip fracture hospitalizations. I recommend against three other candidates, and the reasons are set out below, because the measures we discard decide whether partners believe the ones we keep.
The Tests
Each candidate was tested against five questions. Available: is it produced for our county at least once a year? Stable: are there enough events for the number not to swing by chance from year to year? Sensitive: could a county falls program realistically change it within three to five years? Meaningful: would our partners, the Area Agency on Aging, the ambulance service and the hospital, recognize it as a measure of the problem they see? Affordable: can we obtain it without new data collection? A measure had to pass at least four tests, including stability, to be kept. County-level health measures face a particular problem with small numbers, and the County Health Rankings methods address it by combining years and suppressing unreliable estimates (Remington et al., 2015). Our stability test follows the same concern.
The Six Candidates
Table 1 summarizes the results.
Table 1
Candidate Indicators and Test Results
| Candidate | Current county value | Available | Stable | Sensitive | Meaningful | Affordable | Decision |
|---|---|---|---|---|---|---|---|
| Lift-assist callers per 1,000 older adults | 14.9 (212 people) | Yes | Yes | Uncertain | Yes | Yes | Discard |
| Repeat lift-assist callers (three or more calls) per 1,000 | 2.9 (41 people) | Yes | Moderate | Yes | Yes | Yes | Keep |
| Fall-related hospitalizations per 10,000, three-year average | 115 (about 164 a year) | Yes | Yes | Yes | Yes | Yes | Keep |
| Hip fracture hospitalizations, count per year | About 58 | Yes | Moderate | Yes, slowly | Yes | Yes | Keep |
| Fall deaths per 100,000 | About 77 (11 deaths a year) | Yes | No | No | Yes | Yes | Discard |
| Percentage of older adults reporting a fall in the past year | State estimate only | No | Yes | No | Yes | Yes | Discard |
The Three Kept
Repeat lift-assist callers. This is the most specific measure of people at immediate risk. Research from one city showed lift-assist calls clustering at a minority of addresses, with frequent returns within 30 days (Cone et al., 2013), which suggests that repeat callers are where serious falls concentrate. The measure is also the one a county program could change most directly, through home safety visits and referral to exercise programs. Its weakness is size: 41 people means that a change of five or six people moves the rate noticeably. We will report it with a count as well as a rate, and judge it over two years rather than one.
Fall-related hospitalizations. State hospital discharge data are available by county of residence each year. At about 164 a year, the number is large enough to be stable, especially as a three-year average. It captures injuries serious enough to require admission, which is the outcome a falls program most wants to prevent.
Hip fracture hospitalizations. Hip fractures are the most serious common fall injury in older adults and carry high mortality and loss of independence. They are a subset of fall hospitalizations, so the measure adds specificity rather than new coverage. It will change slowly, and we should not expect to see an effect before year three.
The Three Discarded
All lift-assist callers. The overall rate is stable and meaningful, but it is uncertain in direction. A successful outreach program might increase calls in the short term, as older adults learn that calling for help after a fall is better than lying on the floor. A rise in this measure could therefore mean either more falls or better help-seeking. We will still count lift-assist calls for operational purposes, but not as an indicator of success.
Fall deaths. The county records about 11 fall deaths a year. That rate happens to be close to the national rate of 78 per 100,000 for 2021 (Kakara et al., 2023), but with so few events, one or two additional deaths would change the rate by 10 to 20%. It fails the stability test and cannot show the effect of a program within five years.
Self-reported falls. The state behavioral risk factor survey estimates the share of older adults who report a fall, and research has found its estimates broadly comparable to other self-report surveys (Pierannunzi et al., 2013). But the survey sample is too small to produce a county estimate. A state figure cannot show whether our county's program works.
Next Steps
If you agree, I will establish baseline values for the three indicators from the last three years of data, request the hospital discharge extract from the state, and agree a reporting schedule with the ambulance service. I propose reporting the indicators to partners twice a year, each with a count, a rate and a note on what the number can and cannot show. I would welcome a discussion of the discarded measures with the Area Agency on Aging, since its staff may see value in a measure I have set aside.
References
Cone, D. C., Ahern, J., Lee, C. H., Baker, D., Murphy, T., & Bogucki, S. (2013). A descriptive study of the "lift-assist" call. Prehospital Emergency Care, 17(1), 51-56. https://doi.org/10.3109/10903127.2012.717168
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
Pierannunzi, C., Hu, S. S., & Balluz, L. (2013). A systematic review of publications assessing reliability and validity of the Behavioral Risk Factor Surveillance System (BRFSS), 2004-2011. BMC Medical Research Methodology, 13, Article 49. https://doi.org/10.1186/1471-2288-13-49
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
NR 538 Week 3 instructions, in plain terms
Selecting indicators for a population assessment is the focus. Prompts ask you to propose indicators, explain criteria for selection, identify data sources and justify your choices, often in memo form to a decision maker. List more candidates than you will keep. State your selection tests before applying them, and include stability, since small counts make county rates swing from year to year. Apply the tests to every candidate in a table. Give as much attention to the measures you discard as to those you keep, because readers trust the kept measures more when they can see why others were rejected. Note how each kept measure will be reported. Cite indicator and data quality sources in APA 7.
How this NR 538 Week 3 example is built
The memo opens with its recommendation and names the three measures it will not recommend. A section defines five tests and a rule for keeping a measure, supported by county ranking methods for handling small numbers. Table 1 shows six candidates with current values, test results and decisions. A section explains the three kept measures, including why repeat callers are specific but small and should be judged over two years. Another explains each discard: all lift-assist calls because a rise could mean better help-seeking, fall deaths because eleven a year are unstable, and a self-reported survey measure because no county estimate exists. Next steps and an invitation to discuss the discards close the memo.
Reading the NR 538 Week 3 grading rubric
Indicator memo rubrics usually reward clear recommendations, explicit selection criteria, accurate data sources, justified choices and professional memo format. Graders favor memos that apply stated tests to every candidate, including rejected ones, since that shows the choice was not arbitrary. Attention to stability for small populations demonstrates understanding of county-level data. Recognizing measures whose direction is ambiguous, such as help-seeking, shows analytic depth. Reporting counts with rates is a practical sign of statistical literacy. Evidence on data sources and national context supports the rationale. A concise memo with a table that summarizes the tests fits the audience and usually scores well on communication.
Common NR 538 Week 3 mistakes, and how to avoid them
A frequent weakness is proposing indicators without saying how they were chosen or what was rejected. Show the tests. Another is choosing measures with too few events at the county level, such as deaths, whose rates swing with one or two cases. Check stability. Students also rely on state or national survey estimates that cannot show county change. Confirm the level of the data. Avoid indicators that could rise for good reasons, unless you say how you will interpret them. Do not forget sensitivity: an indicator no program could move in five years will not show progress. Keep the memo short enough for a director to read, with the reasoning in a table.
Get a NR 538 Week 3 example written to your instructions
Send your own prompt, the rubric, and the memo template if your classroom posts one, together with the population and the sources you have been working from. A custom NR 538 example is written to your material and comes back inside 24-48h, and the first one costs nothing. Tell us which measures your instructor mentioned so the rejected column stays believable.
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 4: Trend Analysis Write-up
- NR 538 Week 5: Benchmark Comparison Brief
- NR 538 Week 6: Community Input Summary
- NR 538 Week 7: Priority Ranking Matrix
- NR 538 Week 8: Needs Assessment Report
- NR 530 Week 3: Social Determinants Map
NR 538 Week 3 questions, answered
How many indicators should the memo keep?
Fewer than most writers expect. Sections vary and some name a number in the prompt, so check yours, but a memo that keeps two or three measures it can source precisely usually outscores one that keeps eight and cites none of them by year. The kept set has to survive being carried through the remaining weeks, and every extra measure is another figure to defend later.
Is a memo allowed to reject an indicator my instructor suggested?
Yes, provided the ruling uses the same criteria as everything else in the table. Rejecting a suggested measure on a stated ground reads as independent work; rejecting it silently, or bending a criterion so it fails, reads as avoidance. If the suggestion fails only on availability, saying so plainly and naming what would be needed to use it is usually the strongest version.
Does the memo need a formal weighting system?
Rarely at this point in the term. Weighting belongs to the ranking work later, and importing it early tends to produce arithmetic nobody can explain. What the memo needs is a small set of pass or fail tests applied in the same order to every candidate, with the reasoning visible in each row. Save numeric weights for the matrix week, where the choice between problems actually happens.
Where can I find a free NR 538 Week 3 sample paper?
The six-candidate indicator memo shown above is the full NR 538 Week 3 sample, open to all readers. If your assessment concerns another problem, share the candidate measures and a memo testing and choosing among them can be prepared.
Why does the NR 538 memo explain discarded indicators?
Because readers trust the chosen measures more when they can see why others were rejected. The sample discards three measures, each with a stated reason, such as fall deaths being too few in the county to give a stable rate.