NR 717 Week 3 Epidemiologic Profile Example

Concepts in Population Health Outcomes & Health Policy Chamberlain University Free custom sample in 24 to 48h

An epidemiologic profile that does the arithmetic correctly and then converts it into expected spending is worked through in this NR 717 Week 3 sample paper. Chamberlain NR 717 (NR-717), Concepts in Population Health Outcomes & Health Policy, has Doctor of Nursing Practice (DNP) students calculate burden measures and carry them into money. The sample computes incidence of hypertensive disorders at 12.0 per 100 deliveries, a 5.4 per 100 hypertension readmission rate and a severe maternal morbidity rate ratio of 6.8, each with its working and a plain-language reading. It gives intervals for small counts, then converts the profile in five labeled steps into about $192,600 of expected Medicaid spending.

CourseNR 717 Concepts in Population Health Outcomes & Health Policy
Week3
Paper typeEpidemiologic profile
LengthAbout 1,100 words, 5 pages
FormatAPA 7 student paper
SchoolChamberlain University
ProgramDoctor of Nursing Practice (DNP)
UpdatedOctober 2026

Free sample paper for NR 717 Week 3

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Epidemiologic Profile of Hypertensive Disorders of Pregnancy at Riverbend Health, Converted Step by Step Into Expected Cases, Visits and Dollars

Student Name

College of Nursing, Chamberlain University

NR 717: Concepts in Population Health Outcomes & Health Policy

Instructor Name

Month Day, Year

What this page is doingThe title names both halves of the work, the epidemiology and its conversion into money, which is what this course adds to an epidemiology exercise.
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Epidemiologic Profile of Hypertensive Disorders of Pregnancy at Riverbend Health, Converted Step by Step Into Expected Cases, Visits and Dollars

The Cohort and the Single Denominator

Every measure in this profile uses the same cohort: 4,180 delivery hospitalizations at Riverbend Health in the most recent complete fiscal year. Where a measure applies to a subgroup, such as the 502 patients discharged with a hypertensive disorder of pregnancy, the subgroup is named and its size given, so a reader can always trace a figure back to the 4,180. Delivery hospitalizations are used rather than live births because they count each pregnancy once and come from the same discharge records as the numerators (Centers for Disease Control and Prevention, 2024).

The Measures, With Working Shown

Cumulative incidence of hypertensive disorders of pregnancy = 502 patients with the diagnosis at discharge divided by 4,180 delivery hospitalizations, times 100 = 12.0 per 100 deliveries. In plain terms, about one delivering patient in eight left the hospital with a pregnancy-related blood pressure disorder.

Prevalence of chronic hypertension at delivery = 209 patients with hypertension recorded before pregnancy divided by 4,180, times 100 = 5.0 per 100 deliveries. This is prevalence, not incidence, because the condition existed before the pregnancy began; it describes how many patients arrived already carrying it.

Incidence of readmission for hypertension within 42 days, among patients with a hypertensive disorder = 27 readmissions divided by 502 patients, times 100 = 5.4 per 100. Roughly one patient in nineteen with the diagnosis came back to the hospital for blood pressure within six weeks.

Incidence of emergency department visits within 42 days, among the same patients = 77 visits divided by 502, times 100 = 15.3 visits per 100 patients.

What this page is doingEach measure is written as numerator, denominator and multiplier, followed by a sentence a non-specialist could repeat, so both the arithmetic and its meaning can be checked.
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Severe Maternal Morbidity by Hypertensive Status

Excluding transfusion-only cases, severe maternal morbidity occurred in 14 of the 502 patients with a hypertensive disorder, 278.9 per 10,000, and in 15 of the 3,678 without one, 40.8 per 10,000. The rate ratio is 6.8: patients with a hypertensive disorder were nearly seven times as likely to experience severe morbidity during the delivery admission. The reference group is named, patients without a hypertensive disorder in the same cohort, because a rate ratio means nothing without one.

How Firm the Numbers Are

The small counts limit what can be said. The 27 hypertension readmissions give an exact 95% interval of about 18 to 39 events, so the true readmission rate in this population could plausibly lie between about 3.5 and 7.8 per 100. The 14 severe morbidity cases among patients with a hypertensive disorder are fewer still, and the rate ratio of 6.8 should be read as large rather than as precise. One year of data from one system cannot support claims to a decimal place, and the figures below carry ranges for that reason. For counts this small, an exact Poisson interval is the appropriate way to express uncertainty, since the usual normal approximation becomes unreliable when events number in the tens (Celentano & Szklo, 2019). In practice this means a year in which readmissions fall from 27 to 20 would not, on its own, show that anything had changed; it would sit comfortably inside the range this year's figure already allows. Any program evaluated against these numbers needs either more than one year of data or an outcome with more events, such as the blood pressure check itself.

What this page is doingTranslating the interval into what a later year would need to show protects the profile from being used to claim success on noise.
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The Conversion, Step by Labeled Step

Each step below converts one quantity into the next, and each is labeled as an observed figure, a forecast or an assumption.

Step 1, forecast: the system expects 4,250 deliveries next year. At the observed incidence of 12.0 per 100, that is about 510 patients with a hypertensive disorder.

Step 2, observed share: 60.0% of patients with a hypertensive disorder last year, 301 of 502, were Medicaid-financed. Applied to 510, that is about 306 Medicaid-financed patients.

Step 3, observed rates: at 5.4 readmissions and 15.3 emergency visits per 100 patients, the 306 would be expected to have about 16.5 hypertension readmissions and 47 emergency visits within 42 days.

Step 4, observed payments: at the plans' average payments of $9,450 per readmission and $780 per emergency visit, that is about $155,900 for readmissions and $36,700 for emergency visits, roughly $192,600 a year in Medicaid spending on the short-term consequences of postpartum hypertension in this one system.

Step 5, range: using the interval from the readmission rate, 3.5 to 7.8 per 100, readmission spending could lie between about $101,000 and $226,000.

Table 1

Converting the Profile Into Expected Medicaid Spending, Next Fiscal Year

StepQuantityBasisResult
1Patients with a hypertensive disorderForecast deliveries times 12.0 per 100510
2Medicaid-financed patientsTimes 60.0%306
3Readmissions; emergency visitsTimes 5.4 and 15.3 per 10016.5; 47
4Medicaid spendingTimes $9,450 and $780About $192,600
5Readmission spending rangeReadmission rate 3.5 to 7.8 per 100About $101,000 to $226,000

Note. Note. Steps 2 to 4 use last year's observed shares, rates and average payments; step 1 uses the system's delivery forecast.

What this page is doingLabeling every conversion step as observed, forecast or assumed lets a budget reader see exactly which numbers are measured and which are bets.
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Limits Tied to These Numbers

The readmission and emergency counts include only Riverbend's own facilities, so patients who went elsewhere are missing and the true burden is higher. The diagnosis codes for hypertensive disorders depend on documentation at discharge, and a patient who developed postpartum preeclampsia after an uncomplicated delivery is counted in the readmissions but not in the 502, which slightly inflates the readmission rate among diagnosed patients. And the average payments are for the system's two largest plans; a third, smaller plan pays about 8% less per readmission.

Where a Dollar Goes Furthest

At about $160 per patient, remote blood pressure monitoring for all 510 expected patients would cost about $81,600. The guidance it would deliver, a blood pressure check in the first ten days for patients with a hypertensive disorder, is already the recommended standard (American College of Obstetricians and Gynecologists, 2018). On the conversion above, the program would need to prevent roughly half of the expected Medicaid hypertension readmissions to pay for itself on readmissions alone, which is a stated assumption, not a finding. The cleaner argument is that the money currently spent arrives after the harm, in the emergency department and on the ward, while the same money spent in the first ten days could reach every patient at risk.

References

American College of Obstetricians and Gynecologists. (2018). ACOG Committee Opinion No. 736: Optimizing postpartum care. Obstetrics & Gynecology, 131(5), e140-e150. https://doi.org/10.1097/AOG.0000000000002633

Celentano, D. D., & Szklo, M. (2019). Gordis epidemiology (6th ed.). Elsevier.

Centers for Disease Control and Prevention. (2024). Severe maternal morbidity in the United States. U.S. Department of Health and Human Services. https://www.cdc.gov/reproductivehealth/maternalinfanthealth/severematernalmorbidity.html

The Chamberlain NR 717 Week 3 instructions

Use one denominator for every measure and name any subgroup as a share of it. Calculate each measure with the numerator, denominator, multiplier and period visible, and follow each with an interpretation a non-specialist could repeat aloud. Keep incidence and prevalence separate and use each where it answers the question. When you compare rates, name the reference group. Be honest about precision: small counts need intervals, and a result should not be reported to more decimal places than the data support. Then convert the burden into money step by step: a prevalence or incidence into expected cases in a defined population, expected cases into visits or admissions at a stated rate, and those into spending at a stated payment. Label each step as observed, forecast or assumed. Tie limits to these numbers and say where a dollar goes furthest.

Inside the NR 717 Week 3 example

The sample explains why delivery hospitalizations are the denominator and keeps 4,180 throughout. Four measures are worked line by line, each followed by a plain sentence such as one patient in eight leaving with a pregnancy-related blood pressure disorder. Chronic hypertension is labeled as prevalence because it predates pregnancy. Severe morbidity is compared between patients with and without a hypertensive disorder, giving 278.9 against 40.8 per 10,000. A precision section uses an exact interval for 27 readmissions and explains that a fall to 20 would not show change. The conversion moves from a forecast of 4,250 deliveries through Medicaid share, rates and average payments to about $192,600, with a range for readmission spending, and a table repeats each step. Limits and a cost comparison close the paper.

Reading the NR 717 Week 3 grading rubric

The predictable loss is a profile that stops at the arithmetic, correct but thinly interpreted, with nothing about what the burden costs anyone. It would pass an epidemiology course and underperform this one. Next is a conversion done silently, where cases become dollars through ratios the reader never sees. Marks are also lost when denominators change between measures, when rates are compared with no reference group, when precision is claimed that small counts cannot support and when prevalence is used where incidence was the question. Generic limitations cost points as well. Profiles score well when each conversion step is labeled and checkable and when the paper says where spending would do the most good.

NR 717 Week 3 help: mistakes that cost points

The conversion from rates to dollars is where most profiles go quiet, because each step needs a figure and a label. Send us your population, your counts and whatever payment or cost data you have, and we can help you work each measure with its denominator, write a plain-language reading, set intervals for small counts and lay out the conversion so every step is marked as observed, forecast or assumed. We can also help you tie limits to your own numbers. The data and the conclusions are drawn from your own setting.

Get a NR 717 Week 3 example written to your instructions

Send the Week 3 instructions with the worksheet or heading set your section supplies, plus the condition and the population you are profiling, and a custom example is written into that format and returned inside 24 to 48 hours. The first one is free. The judgment about where effort belongs remains yours.

More NR 717 papers and DNP samples

NR 717 Week 3 questions, answered

Am I expected to produce cost figures myself?

You are expected to show a defensible chain rather than to perform a costing study. A published average cost per admission, applied to an admission count you derived from your own rates, with both moves sourced, is what this level asks for. The version that draws a comment is the total appearing with no route back to any of the figures standing behind it.

What if the surveillance data for my population is thin?

Say what it supports and what it does not, then calculate only that far. Small area estimates, suppressed cells and modeled figures are ordinary in this work, and a write-up distinguishing a measurement from an estimate reads as competent. Producing a confident rate that the underlying counts cannot carry is the error graders in this course look for first.

How much epidemiology theory belongs in the write-up?

Enough to justify the measures chosen and no more. Explaining why incidence answers your question when prevalence would not is worth the space, while reproducing the definition of both is not, since your instructor wrote them. The length freed up belongs in the conversion and the closing judgment, where a doctoral rubric puts most of its weight.

Where can I find a free NR 717 Week 3 sample paper?

This page holds the complete epidemiologic profile of hypertensive disorders of pregnancy, with its step-by-step conversion into expected spending.

Why does the NR 717 Week 3 sample label each conversion step?

So a budget reader can see which figures were measured, which were forecast and which were assumed, and challenge the right one.