NU 655 Unit 2 local health data audit example

Foundations of Public Health Nursing Herzing University Free custom sample in 24 to 48h

This NU 655 Unit 2 local health data audit example gathers nine indicators for about 1,350 children under three in a composite rural county and checks where each number came from. Herzing NU 655 asks public health nursing students to question data before planning with it. It states the purpose, then lists the indicators with source, period described, year released and denominator. A section shows that every figure describes a period ended before release, some long before. Another explains how denominators differ, such as registry coverage counting every child ever entered. With about 450 births a year, single-year rates for preterm birth swing by chance, so the state pools years. A final section says which comparisons can bear weight, noting that national coverage comes from a household survey with a different method. About 560 words.

CourseNU 655 Foundations of Public Health Nursing
UnitUnit 2
Paper typeLocal health data audit
LengthAbout 560 words, 5 pages
FormatAPA 7 student paper
SchoolHerzing University
ProgramMSN Public Health Nursing
UpdatedOctober 2026

Free sample paper for NU 655 Unit 2

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Local Health Data Audit: Nine Indicators for Children Under Three in a Rural County, and Where Each Number Came From

Student Name

Department of Nursing, Herzing University

NU 655: Foundations of Public Health Nursing

Instructor Name

January 29, 2026

What this page is doingThe title promises the source behind each number, which is the point of an audit. A figure without its publisher, period, geography, and denominator cannot be compared with anything, and the audit's value lies in showing which figures can bear weight.
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Local Health Data Audit: Nine Indicators for Children Under Three in a Rural County, and Where Each Number Came From

Purpose

Before planning any work for the composite rural county's roughly 1,350 children under three, I gathered the indicators available for this population and recorded, for each, who published it, what period it describes, what geography it covers, what its denominator is, and what limits its use. The values are those found for this composite county; the sources and their characteristics are real types of data a county public health nurse would use.

The Indicators

Each indicator is shown with its source details.

IndicatorValuePublisherPeriod describedGeographyDenominatorMain limitation
Live births452State vital recordsCalendar 2023County of mother's residenceNot applicableReleased 18 months after the year ends
Preterm births10.8%State vital records2021 to 2023 combinedCounty1,362 live birthsThree years combined because single-year numbers are small
Low birth weight8.1%State vital records2021 to 2023 combinedCounty1,362 live birthsSame as above
Infant deaths4 deaths, rate not publishedState vital records2019 to 2023CountyAbout 2,250 birthsToo few deaths for a reliable rate
Combined 7-vaccine series complete by 24 months58%State immunization registryChildren born in 2022, assessed in 2024Registry address in countyChildren in registry with a county addressDenominator includes children who moved away
Six or more well-child visits by 15 months, Medicaid children51%State Medicaid agency quality report2023County of enrollmentContinuously enrolled Medicaid childrenExcludes children who lost coverage during the year
Children under 5 in poverty24%, margin of error 7 pointsCensus Bureau, American Community Survey 5-year estimates2019 to 2023CountySurvey sampleWide margin of error in a small county
Children under 6 without health insurance5%, margin of error 3 pointsCensus Bureau, American Community Survey 5-year estimates2019 to 2023CountySurvey sampleWide margin of error
Infants enrolled in WICAbout 60%State WIC programFiscal year 2024County WIC officeEstimated county infantsDenominator estimated from births

Period Described Versus Year Released

Every figure describes a period that ended before the data were released, sometimes long before. The birth data describe 2023; the census estimates describe five years of survey responses averaged together, from 2019 to 2023, so a change in child poverty after a factory closed in 2022 would appear only partly and gradually. When these figures are presented to the board of health, each will carry its period, not the year of the report it came from, so that no one mistakes 2019 to 2023 poverty for current poverty.

Denominators

The denominators differ in ways that change the meaning of the figures. The vaccination coverage figure uses every child in the registry with a county address, including children whose families moved away but whose records were never updated; those children appear unvaccinated in the county because their later doses were given elsewhere. The true coverage of children actually living in the county is therefore probably somewhat higher than 58%, though how much higher is unknown. The well-child visit measure counts only children continuously enrolled in Medicaid, excluding those who lost and regained coverage, who are likely to be the children with the most disrupted care. The two measures cannot be combined into a single picture of how well children are served.

What this page is doingThe commentary examines who is inside each denominator and which way the choice pushes the figure. Two indicators that look like they describe the same children often count different children, and a reader cannot tell unless the audit says so.
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Small Numbers and Uncertainty

With about 450 births a year, single-year rates for preterm birth and low birth weight would swing widely by chance; the state combines three years for that reason. Infant deaths are too few for any rate to be meaningful, and the state does not publish one; four deaths in five years should prompt individual case review, not rate comparison. The census estimates carry wide margins of error: child poverty of 24% plus or minus 7 points means the true value could plausibly lie anywhere from 17% to 31%, and the county should not be ranked against its neighbors on that basis (U.S. Census Bureau, 2020).

Comparisons and What Can Bear Weight

National vaccination coverage is estimated from a household survey with provider record checks, a different method from the state registry (Hill et al., 2023), so the county's registry figure should be compared with the state's registry figure for the same birth cohort, not with the national survey estimate. Of the nine indicators, the registry coverage figure, used with its denominator problem stated, and the three-year birth outcome figures are strong enough to guide planning. The poverty and insurance estimates describe context but are too uncertain for tracking change. The next step is a registry clean-up of children who have moved, which would make the coverage figure more accurate and is itself an assessment task (Centers for Disease Control and Prevention [CDC], 2012).

References

Centers for Disease Control and Prevention. (2012). Principles of epidemiology in public health practice: An introduction to applied epidemiology and biostatistics (3rd ed.). U.S. Department of Health and Human Services.

Hill, H. A., Yankey, D., Elam-Evans, L. D., Chen, M., & Singleton, J. A. (2023). Vaccination coverage by age 24 months among children born in 2019 and 2020: National Immunization Survey-Child, United States, 2020-2022. MMWR Morbidity and Mortality Weekly Report, 72(44), 1190-1196.

U.S. Census Bureau. (2020). Understanding and using American Community Survey data: What all data users need to know. U.S. Government Publishing Office.

Reading the NU 655 Unit 2 instructions

Unit 2 asks you to audit the local data available for a population before using it to plan. Expect to list indicators, record each one's source, period, release date and denominator, assess limitations such as small numbers and data lag, and judge which comparisons are valid. Many versions ask what to do when local data are sparse. Check whether your section expects a specific number of indicators. State and county health department reports, immunization registries, vital records and the American Community Survey are common sources. Treat every figure as a claim to check rather than a fact. Small populations make single-year rates unreliable, so look for pooled years or confidence intervals. Comparisons across sources with different methods need caution.

Inside the NU 655 Unit 2 example

The audit opens with a short purpose statement explaining why data must be checked before planning. A table lists nine indicators with their source details, which is the core of the document. A section on period versus release explains data lag with specific examples, such as birth data two years old at release. The denominators section shows how the same word, coverage, can mean different things depending on who is counted. The small numbers section uses the county's birth count to show why pooled rates are needed. The comparisons section judges which figures can be set beside state or national ones, and which cannot, because methods differ. Short explanations follow every judgment, which keeps the audit analytical.

Where the points sit in the NU 655 Unit 2 rubric

Herzing's rubric for a data audit typically covers the selection of indicators, documentation of sources, assessment of data quality, attention to denominators and small numbers, valid comparisons and writing. Documentation is read closely, and every indicator needs its source, period, release date and denominator for the top band. Selection points reward indicators relevant to the population. Quality criteria look for lag, coverage and method limits named specifically. Small numbers and denominators often earn their own credit. Comparison points go to judgments about which figures can be compared and why. Presentation covers a readable table. CDC's Principles of Epidemiology and the Hill vaccination coverage report appear in the APA 7 list.

NU 655 Unit 2 help: mistakes that cost points

Data audits in Unit 2 usually lose points by listing figures without sources, periods or denominators. Another frequent problem is treating the release year as the year the data describe. Students often compare county figures with national ones without noting different methods. Small numbers are ignored, so a single-year rate is taken at face value. Denominators are assumed to be the same across sources. The audit stops at listing, with no judgment about what the data can support. Finally, record where each number came from in enough detail for someone to find it again, because graders check whether a figure can be traced, and untraceable numbers weaken every later unit.

Get a NU 655 Unit 2 example written to your instructions

Send the Unit 2 instructions and the rubric from your NU 655 classroom, together with the area and the indicators to be audited. We write a custom example with the row structure built, provenance fields specified, comparability handled honestly and the missing indicators listed. Figures for your own area stay yours to enter. First custom sample free, returned in 24 to 48 hours.

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NU 655 Unit 2 questions, answered

Where do local figures usually come from?

State and county health department reports, federal survey and vital statistics releases, and the data pages many hospitals publish for their service areas. Whatever the source, record the publishing body, the collection period and the geography with the number itself. A figure carried into a paper without those three things is unusable to anyone who wants to build on it, including you next term.

What if the area publishes almost nothing?

That is a finding worth stating rather than a problem to hide. Say which indicators are unavailable at the level you need, use the smallest geography that does publish, and be explicit that the figure describes a wider area than the population you are addressing. Substituting a national estimate and letting it stand as a local figure is the error that costs most credit.

Can I use figures from my clinical site?

Only with permission and only where they are genuinely shareable, and even then consider whether they belong in a submitted file. Aggregate published data serves the same purpose without the exposure. Anything you collected yourself, including counts from a placement, is yours to handle under whatever agreement covers it, and it should never be reproduced in an example written by somebody else.

Where can I find a free NU 655 Unit 2 sample paper?

Read the complete NU 655 Unit 2 local data audit here at no charge, nine indicators with sources, lag, denominators and valid comparisons. A custom audit can examine the data for your own population and area.

Why do small populations need pooled health data?

With few events, a rate can swing widely from year to year by chance. This sample's county has about 450 births a year, so preterm birth and low birth weight rates are pooled across several years to give a more stable figure.