NSG 323 Unit 5 community assessment example

Reviewed by Cecily Vandenberg, MSN, RN Herzing University True APA form Annotated

This NSG 323 Unit 5 community assessment example examines uncontrolled hypertension among adults aged 45 to 64 in a composite rural county and closes on a population level nursing diagnosis. Herzing NSG 323, Community and Public Health Nursing, has RN to BSN students study one population through real rates, and this sample begins with the population and its boundary in Fairmont County, 214,000 residents with 52,300 adults in the age group. A windshield survey shows grocery stores 14 to 22 miles from eastern townships. Four rates follow, each with its denominator and window: 40 per 100 adults seen carry a hypertension diagnosis, half of those are controlled, 411 emergency visits per 100,000 residents and a stroke death rate near 44.9. The diagnosis section states the problem in population form and explains why two other diagnoses were set aside. About 1,300 words.

CourseNSG 323 Community and Public Health Nursing
UnitUnit 5
Paper typeCommunity assessment
LengthAbout 1,320 words, 7 pages
FormatAPA 7 student paper
SchoolHerzing University
ProgramRN to BSN
UpdatedOctober 2026

Free sample paper for NSG 323 Unit 5

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Uncontrolled Hypertension Among Adults Aged 45-64 in a Composite Rural County: A Population Assessment

Student Name

Department of Nursing, Herzing University

NSG 323: Community and Public Health Nursing

Unit 5 Assignment

Instructor Name

Month Day, Year

What this page is doingThe title names the condition, the age band, the setting, and the genre, so a reader knows within one line that this is a population assessment and not a disease overview. Age bands earn credit in community work because a rate without a population attached cannot be acted on. The block carries the course line and the unit line the classroom expects, and it makes no claim to a grade or to an official name for the work, since a model document holds neither.
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The Population, the Boundary, and What the Drive Shows

I work as a registered nurse in an outpatient clinic serving a mixed rural and small city population, and the county described here is a composite. Its name, its borders, its clinics, and every figure below are assembled from ordinary community practice so that no employer, no site, no colleague, and no patient can be identified from this paper. The composite is called Fairmont County: 214,000 residents by the most recent annual estimate, spread across one small city of about 61,000 and eleven townships. Adults aged 45 to 64 number 52,300 of those 214,000 residents, or 24 of every 100 people in the county, and that age group is the population this paper assesses.

A windshield survey at midday shows what the figures later confirm. Three full service grocery stores serve the whole county, two of them inside the city limits, and housing in the eastern townships sits 14 to 22 miles from the nearest one. Eleven fast food outlets line the two mile commercial strip on the north side. One fixed bus route runs every 45 minutes and stops at 6:30 in the evening, which matters because four of the county's five primary care sites close their clinic hours at 5:00. Nine pharmacies operate countywide and seven of them are in the city. Sidewalks run continuously downtown and are absent along the county roads where most township housing stands.

The county is not short of assets, and an assessment that lists only deficits misreads it. Two congregations run blood pressure checks after services on the first Sunday of every month, the senior center opens a walking group at 8:00 on alternate mornings, and the extension office already reaches farm households the clinic never sees. The assessment that follows treats health outcomes as the product of health behaviors, clinical care, social and economic conditions, and the physical environment, weighted as the county rankings model weights them (University of Wisconsin Population Health Institute, 2024). That model is the reason the drive comes before the data rather than after it.

What this page is doingThe privacy boundary is stated once, in the first three lines, and then dropped rather than repeated. The windshield survey comes before any figure, which is what a community assessment rubric usually rewards under observation, and the details chosen are the ones that later explain the numbers: grocery distance, bus times, clinic closing hours. Naming assets alongside deficits protects the paper from the deficit framing that costs points in this course more often than any calculation error.
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Rates, Each With Its Denominator and Its Window

Four figures describe the problem, and each is reported with what it was divided by and the period it covers. In the composite clinic records for the 12 months ending in June, 3,560 of 8,900 adults aged 45 to 64 seen at least once carried a diagnosis of hypertension, which is 40 per 100 adults seen in that period. Of those 3,560 diagnosed adults, the most recent recorded blood pressure was at or below 140/90 for 1,780, which is 50 per 100 diagnosed adults across the same 12 months. The denominators differ, and confusing them is the commonest error in a community paper: the first is adults seen, the second is adults already diagnosed.

The other two figures come from countywide counts rather than clinic records. Emergency department visits carrying a primary diagnosis of hypertensive urgency numbered 880 across the same 12 months, which is 411 visits per 100,000 residents in one year on a base of 214,000. Stroke deaths numbered 96 in that year, a crude rate of 44.9 deaths per 100,000 residents. That last comparison is weaker than it looks. The national figure usually quoted beside it is age adjusted, and this composite county is older than the country as a whole, so a crude local rate sitting above a national age adjusted rate raises a question rather than settling one (Centers for Disease Control and Prevention, 2024b).

Set against national data, the control figure is the finding that carries. About 48 of every 100 adults in the United States have hypertension, and only about 22 of every 100 adults with hypertension have it controlled, measured in national survey data collected across 2017 to 2018 (Centers for Disease Control and Prevention, 2024a). The county's 50 per 100 looks better than that until the measurement is compared: the national figure counts adults whose hypertension has never been diagnosed, while the local one counts only adults already in the clinic records. The honest reading is that 1,780 adults in this county held a diagnosis and an uncontrolled pressure in a single 12 month period, and the county has no count at all for those never seen.

Two conditions sit underneath the control figure. Distance is the first, since township residents travel 14 to 22 miles to a grocery store and a similar distance to a clinic, on the one bus route that stops before evening clinic hours would help them. Interval is the second. Screening standards call for confirmation of a raised reading outside the office before treatment starts, and for regular rechecking afterward, which turns into a transport problem rather than a clinical one in a county shaped like this one (U.S. Preventive Services Task Force, 2021). Blood pressure control also remains among the national heart disease and stroke objectives, which fixes the direction of travel here (Office of Disease Prevention and Health Promotion, n.d.).

What this page is doingEvery rate here is written as a count over a denominator across a period, so each one can be recalculated by a reader. The sheet also does something most papers skip: it says which comparison is unsound and why, when a crude local rate is set beside an age adjusted national one. Admitting that the local control figure counts a different group than the national figure is the move that turns data reporting into analysis, and it costs nothing to state.
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From These Findings to a Population Level Nursing Diagnosis

A population level nursing diagnosis names the population, the state to be changed, the conditions producing it, and the data showing it (Anderson & McFarlane, 2019). Stated in that form, the diagnosis for this composite county reads: risk for ineffective self management of hypertension among adults aged 45 to 64 in Fairmont County, related to distance from primary care and pharmacy services, transport that ends before evening clinic hours, and long intervals between blood pressure rechecks, as evidenced by 1,780 of 3,560 diagnosed adults recorded at or below 140/90 across 12 months, 411 emergency department visits per 100,000 residents for hypertensive urgency in the same year, and a crude stroke mortality of 44.9 deaths per 100,000 residents.

Two other diagnoses were considered and set aside for stated reasons. Deficient community health knowledge was rejected because nothing collected here measures knowledge, and the blood pressure checks at two congregations plus the reach of the extension office argue that information already moves through this county. Ineffective community coping was rejected as too broad to be measured by anything this assessment gathered. A diagnosis a community cannot measure is a sentence, not a plan. The retained diagnosis was kept because each of its three evidence clauses already carries a counting rule and a denominator, so the same figures can be counted again in a year and the diagnosis can be shown to be wrong.

That commits this assessment to one measurable outcome rather than a list of intentions: within 12 months, the proportion of diagnosed adults aged 45 to 64 recorded at or below 140/90 rises from 50 per 100 to 60 per 100, counted on the same records with the same denominator. What the assessment cannot do is assign a cause, since it is descriptive and drawn from a composite. What it does is state where a public health nurse would look next, which is the eastern townships, the hours after 5:00, and the interval between recheck visits. A real county would need its own counts before one sentence of this applied to it.

What this page is doingThe diagnosis is written in full three part form, with the population named, the related conditions listed, and the evidence quoted as figures already given earlier in the paper. Two competing diagnoses are then rejected with reasons, which shows selection rather than assertion. Closing on a single measurable outcome, on the same denominator used at baseline, gives the diagnosis something to be judged against and gives a grader a clear place to award the synthesis marks.
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References

Anderson, E. T., & McFarlane, J. (2019). Community as partner: Theory and practice in nursing (8th ed.). Wolters Kluwer.

Centers for Disease Control and Prevention. (2024a). High blood pressure facts. U.S. Department of Health and Human Services. https://www.cdc.gov/high-blood-pressure/data-research/facts-stats/

Centers for Disease Control and Prevention. (2024b). Underlying cause of death, 1999-2022 [Data set]. CDC WONDER. https://wonder.cdc.gov/ucd-icd10.html

Office of Disease Prevention and Health Promotion. (n.d.). Heart disease and stroke. Healthy People 2030, U.S. Department of Health and Human Services. https://health.gov/healthypeople/objectives-and-data/browse-objectives/heart-disease-and-stroke

U.S. Preventive Services Task Force. (2021). Hypertension in adults: Screening. https://www.uspreventiveservicestaskforce.org/uspstf/recommendation/hypertension-in-adults-screening

University of Wisconsin Population Health Institute. (2024). County health rankings and roadmaps: 2024 national findings report. https://www.countyhealthrankings.org

NSG 323 Unit 5 instructions, in plain terms

Unit 5 asks you to complete a community assessment for a defined population and write a population level nursing diagnosis. Expect to define the population and its boundary, describe what a windshield survey shows, report rates with their denominators and time windows, and state a diagnosis naming the population, the problem, the causes and the evidence. Students often ask where community rates come from if employer data cannot be used. County health rankings, CDC data and state vital statistics are public. Keep denominators straight, since adults seen and adults diagnosed are different bases. Write the diagnosis for a population, not a patient. Explain any diagnosis you considered and rejected.

Inside the NSG 323 Unit 5 example

The paper begins with the nurse's role, then defines the composite county, its residents and the target age group. The windshield survey describes distances to grocery stores and clinics, fast food density and transport limits. The rates section reports four figures, each followed by what it was divided by and the period it covers, and warns against mixing denominators. The diagnosis section uses a community-as-partner format to state risk for ineffective self-management of hypertension related to distance, transport and long gaps between blood pressure checks, as evidenced by the four rates. It explains why knowledge deficit and another diagnosis were set aside. References follow.

Where the points sit in the NSG 323 Unit 5 rubric

Herzing's rubric for a community assessment typically covers the population and boundary, data collection, rates, analysis and the nursing diagnosis. Rates reported with clear denominators and windows draw the most points, since they are what make a population claim checkable. Population points reward a defined age group and geography. Data criteria look for a windshield survey and public sources. Analysis credit goes to linking conditions, such as distance and transport, to outcomes. Diagnosis points reward the population, problem, causes and evidence in one statement. Rejected diagnoses explained are often credited. Anderson and McFarlane's Community as Partner, CDC hypertension data, USPSTF screening guidance and County Health Rankings support the paper.

Common NSG 323 Unit 5 mistakes, and how to avoid them

Community assessments in NSG 323 Unit 5 often come up short by reporting percentages without saying what they were divided by. Another frequent problem is mixing adults seen with adults diagnosed. Students often write a diagnosis for an individual rather than a population. The windshield survey is skipped or generic. Causes are assumed rather than shown in the data. Data sources are employer records that cannot be shared. Rejected diagnoses are not discussed. Time windows are missing, so a reader cannot tell whether a rate covers one month or five years. Assets in the community, such as churches or a mobile clinic, are left out. Finally, carry every rate with its base, because graders reward an assessment a public health team could use to plan its next step.

Write yours, or have the desk draft it

This paper is an original model document written by our desk, not a submitted student paper and not an official Herzing University document. Read it for the moves, then write your own to the instructions in your classroom. If you want one built to your exact prompt and rubric, the first custom sample is free and arrives in 24 to 48 hours.

More NSG 323 papers and RN-to-BSN samples

NSG 323 Unit 5 questions, answered

What does the NSG 323 Unit 5 assignment usually ask for?

In many sections this unit sits where community data gets applied, so the work is commonly an assessment of one population in one defined area, closing on a population level nursing diagnosis. Your classroom's instructions and rubric decide the exact form, including whether a windshield survey, an interview with a key informant, or a data table is expected alongside the prose.

How do I write a nursing diagnosis for a population instead of a patient?

Keep the three part structure and change the subject. Name the population and the defined area, state the health state at risk, list the community conditions related to it, and give the evidence as rates with denominators rather than as symptoms. If the evidence clause cannot be recounted in a year, the diagnosis is not yet measurable.

Where do community health rates come from if I cannot use my employer's data?

Use public sources and a composite setting, as this paper does. County level counts are published through CDC WONDER and the county rankings program, and national comparisons come from CDC surveillance and Healthy People objectives. Build the local figures as a realistic composite, label them as such once, and keep every denominator visible so the arithmetic stays checkable.

Where can I find a free NSG 323 Unit 5 sample paper?

Read the complete NSG 323 Unit 5 community assessment here at no charge, uncontrolled hypertension in a rural county with rates, denominators and a population nursing diagnosis. Ask for a custom community assessment.

How do you write a population level nursing diagnosis?

Name the population, the health problem, the conditions producing it and the data showing it, for example risk for ineffective self-management related to distance from care, as evidenced by county rates. This sample does that.