| Course | NR 538 Population Health I: Assessment and Analysis of Data |
|---|---|
| Week | 1 |
| Paper type | Discussion post with two replies |
| Length | About 590 words |
| Format | Discussion post with APA 7 citations |
| School | Chamberlain University |
| Program | MSN, Population Health |
| Updated | September 2026 |
Free sample paper for NR 538 Week 1
Week 1 Discussion: Initial Post
Older Adults Who Called for a Lift and Stayed Home: Choosing a Population That Already Sits in One County File, the Ambulance Service's Patient Care Records
The Group
I am a public health nurse in a rural Midwestern county of about 58,000 people, a quarter of whom are 65 or older. For this course, I want to assess older adults at risk of serious falls. That is too broad to assess. Every older adult is at some risk, and no file lists them by it. So I have narrowed the group to one that already exists in a record: county residents aged 65 or older who called the county ambulance service in the last year because they had fallen and could not get up, were helped up by the crew and were not taken to the hospital. The ambulance service calls these lift assists.
The group is small enough to name and specific enough to matter. In 2025, the service recorded 318 lift-assist calls for 212 different residents aged 65 or older. Forty-one of them called three or more times.
Why This File
A population that cannot be found in any existing file can only be described, not assessed. The ambulance service's electronic patient care records hold every lift-assist call with the address, age, time, what the crew found and whether the person was transported. The records exist because the service must document every response, and they have been kept in the same electronic system for four years. I can obtain a de-identified extract through the county's data agreement.
Lift-assist calls matter because a person who falls and cannot get up is signaling weakness, balance problems or an unsafe home, and many will fall again with injury. Nationally, more than a quarter of adults aged 65 or older reported falling in the previous year, and falls killed tens of thousands of older adults in a single year (Kakara et al., 2023). Those figures describe a population no county can list. The lift-assist file gives our county a list of people who have already shown the risk, before most of them are injured.
Who the File Misses
The file misses older adults who fall and are helped up by family, who lie on the floor without calling or who go straight to the emergency department by car. It also misses residents of the county's two assisted living facilities, whose staff handle most falls without calling the ambulance. The file is a list of people whose falls reached one service, not a list of all fallers. I will need a second source, probably hospital discharge data for fall injuries, to see what the ambulance file does not.
Question for the group: Which file already holds your population's members, and who does it leave out?
Reply to Lorena
Lorena, you chose adolescents who vape. I wonder which file lists them. A school survey estimates how many vape but does not name them, so you could describe the group but not reach its members. Would students referred to a school nurse or a cessation program be a findable subset, even if smaller?
Reply to Ahmed
Ahmed, your group, adults with diabetes enrolled in one clinic, is findable in the clinic's registry. I wonder about the adults who stopped coming. Registries often keep inactive patients for a year or two and then drop them, which would remove the people most in need of outreach. Does your clinic's registry show when a patient was last seen?
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
Reading the NR 538 Week 1 instructions
This opening forum usually has you identify a population whose health you want to assess and explain how you would find data about it. Prompts ask for the group, its health concern, the data that describe it and a tie to what the readings say about assessment. Narrow the group until a specific existing file would hold its members, because a group that appears in no record can be described but not assessed. Name the file and say who keeps it and why. Give a count if you can. Then say who the file misses, since every record captures only the people who reached its owner. Cite a source that places your concern in context, and reply to two classmates by asking where their groups are listed.
How the NR 538 Week 1 example is put together
The post starts with the county, its older population and the realization that all older adults at risk of falls cannot be assessed. It narrows the group to residents who called for a lift assist and were not transported, with counts for the year and for repeat callers. A second section explains the ambulance service's records, what they hold and how they can be obtained, and uses national fall figures to show why lift-assist callers matter. A third section names who the file leaves out, from family-assisted falls to assisted living residents, and plans a second source. Replies ask a classmate how vaping adolescents could be found in a file and another whether a clinic registry drops inactive patients.
NR 538 Week 1 rubric: what full points look like
The discussion rubric for this week generally rewards a clearly defined population, identification of relevant data sources, understanding of their limits, a tie to course concepts and thoughtful peer responses. The best-scoring posts are those in which the population can be located in a named record, since that shows the difference between assessing and describing. Giving counts drawn from the source demonstrates engagement with data. Naming who the source misses shows critical appraisal early in the course. National data that frame the local concern support the scholarly criterion when cited correctly. Replies score best when they test whether a classmate's group can actually be found. Professional writing and on-time posting complete the grade.
NR 538 Week 1 help from the desk
A frequent weakness is choosing a population so broad, such as all older adults or all adolescents, that no file lists its members. Narrow it until a record does. Another is naming a survey that estimates prevalence but contains no names, then planning to reach individuals. Be clear which kind of data you have. Students also forget to say who a source misses, which leaves the assessment looking more complete than it is. Avoid identifying individuals or small groups in a public post. Keep the post focused on the group and its data rather than on interventions, which come later in the course. In replies, ask where the classmate's group is listed and who that list leaves out.
Get a NR 538 Week 1 example written to your instructions
Send us the prompt for your own week, the rubric if your classroom posts one, and the population you have in mind. A custom NR 538 example is written to your instructions and returned inside 24-48h, and the first one is free. If your population sits in a file your employer owns, describe it to us rather than sending the extract.
More NR 538 papers and MSN samples
- 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 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 1: Discussion on Choosing a Population
NR 538 Week 1 questions, answered
Does the population have to be one I work with?
Sections rarely require that, though writing about a group you already see makes the file question easier to answer honestly. What the rubric usually rewards is a population bounded tightly enough that one existing list could plausibly contain most of its members. A group chosen for interest alone tends to strand the writer by Week 3, when indicators have to be found for it.
How many sources should a first post cite?
One named file carried properly beats four citations listed. The post that earns marks describes a single source well enough that a classmate could guess its columns, then adds a published figure only if it says something the file cannot. Reference style is set by your own classroom, so check the prompt, but the count of sources is rarely the thing being marked in week one.
Is it acceptable to say the data on my population is poor?
Yes, and saying so precisely is worth more than finding a better number. Poor in what direction is the markable version: who is missed, in which years, because of which collection method. A vague complaint that records are incomplete reads as an excuse, while a stated undercount with a named cause reads as analysis and sets up the appraisal in the following week.
Where can I find a free NR 538 Week 1 sample paper?
This page reproduces the lift-assist post and both replies as the NR 538 Week 1 sample, with no sign-up or fee. If your population is different, tell us about it and a post that finds it in an existing file can be drafted.
How narrow should the NR 538 Week 1 population be?
Narrow enough that an existing record lists its members. The sample moves from all older adults at risk of falls to residents with lift-assist calls, a group of 212 people found in the ambulance service's records.