NUR 4043 Module 4 Community Health Assessment Example

Reviewed by Junia Fairbank, MSN, RN · American College of Education · Updated

The NUR 4043 Module 4 example below is a community health assessment of a composite county of 148,000 residents that identifies uninsured adults aged 45 to 64 in two census tracts as the priority population. It belongs to American College of Education NUR 4043 (NUR4043, Community Health and Vulnerable Populations) in ACE's RN to BSN. The paper draws its boundary at the county line and names four data sources with collection periods, then profiles the population with denominators and windows. It tests the staff's assumption that older adults should be the priority and sets it aside on evidence, as three measures converge on a different group. It writes a three-part community nursing diagnosis and plans an evening screening and enrollment clinic, with three measures. Sections commonly allow a real or composite community.

CourseNUR 4043 Community Health and Vulnerable Populations
ModuleModule 4
Paper typeCommunity health assessment
Length1,370 words, about 5 pages plus title and reference pages
FormatAPA 7 student paper
SchoolAmerican College of Education
ProgramRN to BSN
UpdatedOctober 2026

Free sample paper for NUR 4043 Module 4

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Community Health Assessment of Ridgeway County: Identifying Uninsured Adults Aged 45 to 64 as the Priority Population

Student Name

American College of Education

NUR4043: Community Health and Vulnerable Populations

Module 4 Assignment

Instructor Name

April 6, 2025

What this page is doingA community assessment title should name the community and the answer, not the genre. This one does both, so a reader knows before the first paragraph which population the paper ends up defending. Graders reading a stack of these can tell immediately whether the writer reached a conclusion or only gathered figures. American College of Education publishes no deliverable name for this module, so the sheet carries the line a student would type, Module 4 Assignment, with the code in ACE form and no space.
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Community Boundary and Data Sources

This assessment covers Ridgeway County, a composite Midwestern county of 148,000 residents written for teaching, so no real county, agency, employer, or resident is described here. The boundary was drawn at the county line rather than at a home health service area, because the datasets that carry the indicators below are published at county and census tract level, and a boundary that does not match the published data produces rates nobody can check. Inside that line, 12 census tracts were treated as the working sub-areas. Two of them, written here as Tract 12 and Tract 14, hold 19,400 residents between them, which is 13.1 percent of the county population.

Four data sources carry the numbers, and each one is named with its collection period so a reader can tell how old the picture is. Population, income, and coverage figures come from American Community Survey 5-year estimates covering 2018 through 2022 (U.S. Census Bureau, 2023). Chronic disease prevalence comes from model-based small-area estimates published for 2022 (Centers for Disease Control and Prevention, 2024). Preventable hospital use follows the ambulatory care sensitive conditions definition in the national prevention quality indicator set (Agency for Healthcare Research and Quality, 2023). The weighting of clinical care against social and economic factors follows the County Health Rankings model (County Health Rankings & Roadmaps, 2024). Vital statistics are pooled across five years, because annual counts in a county this size swing too far to read.

What this page is doingBoundary and sources come before data for a reason: a rate is only checkable if the reader knows the area it covers and the years it was collected. Naming four sources with their collection periods, and matching the boundary to the level at which those sources publish, is a methods move that rubrics usually reward under accuracy or use of evidence. Pooling five years of vital statistics, and saying why, shows the writer understands that small counties produce unstable annual counts.
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Population Profile and Health Indicators

Ridgeway County holds 148,000 residents. Of these, 32,560, or 22.0 percent, are aged 65 and over, and 26,300, or 17.8 percent, are under 18. Adults aged 45 to 64 number 38,500. Median household income across 2018-2022 is $54,900, and 18.4 percent of residents, which is 27,232 people, live below the federal poverty threshold. Health services inside the county consist of one 96-bed hospital, four primary care clinics, and a federally qualified health center that opens its dental suite three days out of seven. None of those sites sit inside Tract 12 or Tract 14, a fact that becomes load bearing later in this assessment.

Coverage is where the county separates from itself. Countywide, 11.2 percent of residents under 65, which is 12,930 of 115,440 people, had no health coverage across 2018-2022. In Tract 12 and Tract 14 the same measure reaches 24.6 percent. Among adults aged 45 to 64 living in those two tracts, 1,260 of 5,120 people were uninsured, and that single figure carries more of this assessment than any other number in it. The Healthy People 2030 objective of increasing the proportion of people with health insurance frames why the gap matters rather than only how wide it is (Office of Disease Prevention and Health Promotion, n.d.).

Diagnosed diabetes among adults aged 18 and over stands at 12.6 percent countywide for 2022, against a modeled state figure of 10.1 percent for the same period. High blood pressure reaches 36.2 percent of adults in that estimate. Preventable hospital stays run at 4,120 per 100,000 Medicare enrollees for 2021. Emergency department visits for conditions a clinic could treat run at 168 per 1,000 residents aged 45 to 64 in Tract 12 and Tract 14 across the 12 months ending December 2023, against 61 per 1,000 for the same age band elsewhere in the county. Every rate above is written with the population it divides by and the period it covers, because a rate without both is a rumor.

Two further indicators were pulled because they are often assumed rather than measured. Infant mortality across the pooled years 2019-2023 is 8.1 deaths per 1,000 live births, or 121 deaths among 14,900 births, and the pooled count is used because a single year in a county this size moves too much to interpret. Births to females aged 15 to 19 run at 28.4 per 1,000 across 2016-2022. Neither indicator concentrates in Tract 12 or Tract 14; both sit within a point of the county figure. That is still a finding, because it tells the assessment where the problem is not.

What this page is doingEvery figure in this section arrives with a denominator and a window, and several are given as both a percentage and a count, which lets a reader test the arithmetic. The absence of a clinic inside the two tracts is planted here and used later rather than announced twice. The last paragraph reports a null result, that infant mortality does not concentrate in those tracts, which is evidence the writer looked for a pattern instead of confirming one already chosen.
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Which Population the Data Selects

The staff conversation that began this assessment named older adults as the priority, and the reasoning was not careless: 22.0 percent of the county is 65 and over, hospital admissions are dominated by that group, and every nurse in the room had a recent case in mind. Disaggregating by age band and tract does not support the conclusion. Residents aged 65 and over hold near-universal coverage through Medicare, their preventable stay rate is high but tracks the state figure rather than exceeding it, and their attachment to a primary care clinic is the strongest of any age band in the county. Age selected them. The data did not.

The population the data selects is uninsured adults aged 45 to 64 in Tract 12 and Tract 14, which is 1,260 people out of the 5,120 in that age band and those tracts. Three separate measures converge on them. Their uninsured share is 24.6 percent against 11.2 percent countywide, their emergency department use for conditions a clinic could treat is 168 per 1,000 against 61 per 1,000 for the same ages elsewhere, and diabetes and high blood pressure estimates for both tracts sit above county figures while no primary care site stands inside either boundary. Convergence is what turns a number into a finding; one measure alone would only have raised a question.

Vulnerability here is a structural position rather than a personal characteristic, and writing it that way changes what the plan is allowed to do. This group is not at risk through motivation or ignorance. It is at risk because coverage, transport, and clinic hours line up badly for people working daytime shifts without paid leave, many of them earning too much for public coverage in jobs that offer none, a combination the coverage data makes visible without naming a single employer. That reading matches the County Health Rankings model, which sets clinical care beside social and economic factors rather than above them (County Health Rankings & Roadmaps, 2024). A plan built to teach this group about diabetes would miss the finding entirely.

What this page is doingThis is the section that separates an assessment from a data dump. The assumed population is stated fairly, with the reasoning that made it plausible, and is then set aside on evidence rather than dismissed. Three independent measures converge before the claim is made, and the paper says so, because a single indicator would justify a question and not a conclusion. Defining vulnerability as a structural position keeps the plan from drifting into education aimed at people whose barrier is coverage.
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Community Nursing Diagnosis and Targeted Plan

The community nursing diagnosis is written in the risk, population, and evidence form used in community health nursing texts (Rector & Stanley, 2022). Risk of uncontrolled chronic disease among uninsured adults aged 45 to 64 in Tract 12 and Tract 14, related to absent coverage and to the absence of any primary care site inside those tracts, as evidenced by an uninsured share of 24.6 percent against 11.2 percent countywide across 2018-2022, emergency department use of 168 per 1,000 for conditions treatable in a clinic across the 12 months ending December 2023, and adult diabetes prevalence above the county figure of 12.6 percent in both tracts for 2022.

The intervention is a nurse-run evening screening and enrollment clinic in the Tract 12 community center, open two evenings out of seven from 1700 to 2000, staffed by two registered nurses and one certified enrollment counselor. The offer is deliberately narrow: blood pressure, a point-of-care A1C, and a coverage eligibility check, because a small service that runs on schedule beats a broad one that opens and closes. The location was chosen for a bus line running until 2130 and for hours that fit daytime shifts, which is the access barrier the data identified, rather than the knowledge gap the original conversation assumed.

Evaluation rests on three measures, each with a fixed denominator. First, adults enrolled in coverage as a share of those screened and found eligible, reported monthly for 12 months. Second, the share of screened adults with a blood pressure at or above 140/90 mm Hg who attend a primary care visit within 60 days. Third, emergency department visits for conditions treatable in a clinic among residents aged 45 to 64 in the two tracts, measured against the baseline of 168 per 1,000 after four full quarters. No outcome is claimed for this plan. The assessment states what was measured, which population the measurements select, and what would count as a change.

What this page is doingThe diagnosis is written in a recognizable three-part form, and its evidence clause repeats the exact figures from earlier sections rather than paraphrasing them, so nothing new appears at the end. The intervention answers the barrier that was actually found, down to the bus schedule and the hours. Evaluation reuses the baseline measure so a later comparison stays clean, and the closing sentences claim no outcome, which is the honest position for a plan that has not yet run.
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References

Agency for Healthcare Research and Quality. (2023). AHRQ quality indicators: Prevention quality indicators. https://qualityindicators.ahrq.gov/

Centers for Disease Control and Prevention. (2024). PLACES: Local data for better health. https://www.cdc.gov/places/

County Health Rankings & Roadmaps. (2024). County health rankings model. University of Wisconsin Population Health Institute. https://www.countyhealthrankings.org/

Office of Disease Prevention and Health Promotion. (n.d.). Health care access and quality. Healthy People 2030. U.S. Department of Health and Human Services. Retrieved March 2, 2025, from https://health.gov/healthypeople/objectives-and-measures/browse-objectives/health-care-access-and-quality

Rector, C., & Stanley, M. J. (2022). Community and public health nursing: Promoting the public's health (10th ed.). Wolters Kluwer.

U.S. Census Bureau. (2023). American Community Survey 5-year estimates: 2018-2022. https://data.census.gov/

NUR 4043 Module 4 instructions, in plain terms

NUR 4043 Module 4 asks for an assessment of one defined community that ends in a community nursing diagnosis and a targeted plan. Most prompts expect the community boundary and data sources, a population profile with health indicators, identification of a vulnerable or priority population supported by data, a nursing diagnosis in a recognized form, and an intervention with evaluation measures. Many sections ask you to use public data such as the American Community Survey or County Health Rankings. Plan on five pages for a NUR 4043 community assessment, with a table. The NUR 4043 Canvas page states whether the community must be your own. Give every rate its denominator and collection period.

Inside the NUR 4043 Module 4 example

The first section draws the boundary at the county line because the indicators are published at that level, and names its four sources with collection periods. The profile section reports age structure, uninsured rates under 65, diabetes and high blood pressure against state figures, and infant mortality pooled over five years because a single year moves too much. The priority section states the staff's view that older adults should come first, with its reasoning, then shows that uninsured adults aged 45 to 64 in Tracts 12 and 14 stand out, 1,260 people with no primary care site inside the tracts. The plan section writes the diagnosis in risk, population and evidence form and proposes a nurse-run evening clinic for blood pressure, A1C and coverage checks.

Where the points sit in the NUR 4043 Module 4 rubric

Community health assessments in NUR 4043 are graded on evidence and focus. Boundary credit requires a stated boundary and named sources with dates. Profile marks reward indicators with denominators, windows and comparisons. The priority row usually counts for the most points: a population selected by converging data rather than assumption. Graders give credit for describing vulnerability as a structural position. Diagnosis marks require the three-part form with figures. Plan credit goes to an intervention that answers the barrier found, with measures and denominators. APA 7 references to public data sources account for the final marks. Marks also go to figures given as both a percentage and a count, so the arithmetic can be checked.

NUR 4043 Module 4 help from the desk

Community assessments most often choose the priority population before looking at the data. Another frequent weakness is rates without denominators or years. Students also propose interventions, such as health education, that do not answer the barrier the data show. Name your boundary and sources. Break the data by age and area. Look for measures that converge. Test the group everyone assumes. Write the diagnosis with figures. Plan an intervention that removes the barrier and say how you will measure it. If your community is a rural county, a city neighborhood or a school district, the desk can write a community health assessment for it. Pool small counts across several years before reporting a rate.

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 American College of Education 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 NUR 4043 and RN to BSN sample papers

NUR 4043 Module 4 questions, answered

How do I identify a vulnerable population from data instead of assuming one?

Break the county into age bands and tracts, then look for measures that converge. One high number raises a question; three pointing at the same group supports a claim. State the population your colleagues assumed was most at risk, test it, and report honestly when the figures send you somewhere else. That refusal is usually the strongest paragraph in the paper.

Can I use a composite community instead of a real county?

Either works if you are honest about which you used. Label a composite once, in the opening paragraph, and keep the national sources and definitions real. What a rubric checks is not the county name but whether every rate carries its denominator and time window, whether the sources are named with collection periods, and whether the plan follows the finding.

Where can I find a free NUR 4043 Module 4 sample paper?

Above, free: the community health assessment for NUR 4043 Module 4, organized as "Community Boundary and Data Sources", "Which Population the Data Selects" and "Community Nursing Diagnosis and Targeted Plan".

What is a community nursing diagnosis?

It states a health risk, the population at risk and the evidence for it, often in a risk, population and related-to form. Community health nursing texts such as Rector and Stanley describe the format.

Where can I find county health data?

The American Community Survey, County Health Rankings and the CDC PLACES project publish county and tract figures. Name each source with its collection years in your paper.