How to Write the Applying Epidemiology to Program Design for Chronic Disease Assignment (NURS 8310 Week 10)
A section-by-section breakdown of the 7–10 page program proposal — what goes into each required component, how epidemiologic thinking applies to program design, how to write SMART objectives that hold up to scrutiny, and where most proposals lose points before the rubric is even opened.
The NURS 8310 Week 10 assignment asks you to produce a 7–10 page program proposal that moves from epidemiologic analysis of a chronic disease to a fully designed intervention — including SMART objectives, a named planning model, data collection justification, stakeholder identification, cultural considerations, funding strategy, and marketing. That is a lot of distinct tasks crammed into one document, and the rubric scores each of them separately. Collapsing them into a single undifferentiated narrative is one of the most reliable ways to lose points across multiple criteria simultaneously. This guide walks through each required component in the order the assignment presents it, explains what the rubric is actually evaluating in each section, and identifies the structural and conceptual errors that most commonly appear in these proposals.
This guide does not write the assignment for you. It explains the logic behind each section — what epidemiologic thinking is supposed to produce, how it connects to program design, and what “excellent” looks like in rubric terms — so you can apply that thinking to your own selected chronic disease and population. The assignment gives you significant latitude in disease and population selection; that latitude is where most of the analytical work happens, and no guide can do it for you.
What This Guide Covers
What the Assignment Is Actually Testing
The assignment is not asking you to describe a chronic disease. It is asking you to demonstrate that you can use epidemiologic data to make design decisions about a health intervention. The distinction matters because students who treat this as a disease overview assignment — front-loading statistics about prevalence and mortality without connecting them to program choices — produce proposals that score in the “fair” or “poor” band even when the background information is accurate.
Every section from the disease description onward should feed forward into a design decision. The epidemiologic characteristics of person, place, and time tell you who to target, where to locate the program, and when the problem is most acute. The health outcome you select determines what data you collect and how you write your SMART objectives. The planning model you choose dictates how the proposal is organized from planning through evaluation. When these connections are visible in the writing, the rubric criterion on “strong understanding and application of program planning concepts and strategies” is satisfied at the excellent band. When they are absent — when the sections read as isolated chunks of information — that criterion drops to fair or below.
The assignment instructions specifically direct you to the CDC’s National Center for Chronic Disease Prevention and Health Promotion (NCCDPHP) website before selecting your disease. The NCCDPHP maintains current prevalence data, identified priority diseases, and links to evidence-based intervention resources. Working from this source establishes that your disease selection is grounded in national significance, which the rubric’s first criterion evaluates. The NCCDPHP is at cdc.gov/chronicdisease — use the data tables, not just the overview pages, when describing patterns in your proposal.
Section 1: Selecting Your Chronic Disease and Population
The assignment says to select a chronic disease “of professional importance to you.” That phrase is doing two things: it gives you latitude to work on something relevant to your practice area, and it signals that you should be able to explain why you selected it. The rubric criterion asks for an “accurate and concise” identification — meaning the disease is named specifically (not “cardiovascular disease” when you mean “heart failure in adults over 65”) and the population is defined with enough precision that you can actually describe their characteristics in the next section.
Vague disease-population pairings are the first structural problem in weak proposals. “Diabetes in adults” is not a population — it is a category. A defined population has geographic boundaries, demographic characteristics, and epidemiologic context. The more precisely you define your population in Section 1, the more efficiently every subsequent section can be written, because you are describing the specific patterns and designing the specific program for a specific group rather than a hypothetical general one.
Choose a Disease With Available Data
The evidence summary section (Section 5) and data collection section (Section 7) both require you to engage with existing data sources. Selecting a disease for which CDC, CMS, or state health department data exists at the population level saves significant time and produces a stronger proposal. NCCDPHP priority diseases — type 2 diabetes, heart disease, COPD, obesity, hypertension — all have deep data availability.
Define a Geographically Bounded Population
Your geographic region section needs to be substantive. A population defined at the county, metropolitan area, or specific community level allows you to cite state or local health department data and makes your program design decisions (where to locate services, which languages to use, which community partners exist) concrete and defensible.
Match the Disease to a Distinct Population Subgroup
The rubric evaluates “important characteristics of the population” — age, race/ethnicity, socioeconomic status, health literacy, insurance status, and other factors relevant to the disease. A population defined by a single demographic characteristic gives you more to work with in program design and cultural considerations than a general adult population.
Section 2: Geographic Region and Population Characteristics
This section describes where your population lives and who they are. The rubric asks for an “accurate and concise” description of both the geographic region and important characteristics of the population — 20 points, scored separately from the disease identification. That means you cannot fold these two sections together into a single paragraph. Each needs its own substantive content.
For the geographic region, describe the relevant features of the location that affect health: urban/rural classification, access to healthcare facilities, transportation infrastructure, food environment, neighborhood characteristics, and state-level policy context where relevant. For population characteristics, describe the demographic and socioeconomic profile — age distribution, racial/ethnic composition, poverty rate, insurance coverage, health literacy level, employment patterns, and any community-specific factors that affect health behavior and healthcare access. These characteristics do not exist just to fill a section; they determine who your program needs to reach and how it needs to reach them.
Census data gives you demographics. State health department data gives you disease burden. Local health department or county health rankings data gives you social determinants. A strong geographic and population section triangulates across at least two or three sources. Using only the CDC NCCDPHP overview page for this section produces a proposal that describes the national picture rather than your specific population — which the rubric will read as vague. County Health Rankings (countyhealthrankings.org) is a free, peer-reviewed resource that provides county-level data on health outcomes, behaviors, and social determinants for every county in the United States.
Section 3: Epidemiologic Characteristics — Person, Place, and Time
This is the highest-weighted descriptive section (25 points) and the one where epidemiologic thinking is most explicitly required. The assignment asks you to describe the patterns of the disease in your selected population using the three classic epidemiologic dimensions: person (who gets the disease), place (where the disease occurs), and time (when and how the disease has changed over time). These are not three independent questions — together they constitute the epidemiologic portrait of the disease in your population that justifies your program design choices.
Person
Person characteristics describe who bears the greatest burden of the disease within your population. This includes age, sex, race/ethnicity, socioeconomic status, occupation, health behaviors (smoking, physical inactivity, diet), comorbidities, and any other variables that distinguish people with higher incidence or prevalence from those with lower. The rubric’s “excellent” band requires a detailed description — not a single sentence listing demographic groups, but a substantive account of which subgroups carry disproportionate burden and why those disparities matter for program targeting.
Place
Place characteristics describe geographic variation in disease burden within or around your defined population. This includes variation between urban and rural areas, between neighborhoods within a city, between census tracts with different income levels, or between states with different policy environments. The place dimension tells you where the program needs to be physically located, which community-based organizations are relevant partners, and whether certain geographic subgroups need additional outreach.
Time
Time characteristics describe how the disease has changed — whether prevalence is rising, stable, or declining; whether there are seasonal patterns; whether a particular demographic shift has changed who is affected; and what has caused any trends you identify. The time dimension provides the epidemiologic rationale for why the program is needed now. A disease with rising incidence among a specific population subgroup makes a stronger case for urgency than one with stable or declining rates.
PERSON: Identify the highest-burden subgroups within your population by age, sex, race/ethnicity, and socioeconomic status. State the specific prevalence or incidence rates for these subgroups. Explain what the epidemiologic literature identifies as the primary risk factors that account for the disparity. Connect these to your program’s target group.
PLACE: Describe geographic variation within your defined region. Cite specific county- or zip code-level data if available. Identify areas with the highest burden and explain what structural or environmental factors drive the geographic concentration. Connect these to where your program will be delivered.
TIME: Describe the trend over the past 5–10 years for your population. State whether incidence or prevalence is rising or falling and at what rate. Identify any inflection points and their explanations. Connect the trend to the urgency of the intervention you are proposing.
Section 4: Identifying One Health Outcome to Improve
The assignment asks you to identify one health outcome — not the disease itself, but a specific, measurable result you want to improve in your population. This is a narrower and more precise task than describing the disease. For a proposal on type 2 diabetes in urban African American adults, the health outcome might be HbA1c control, diabetes-related emergency department visits, medication adherence, or participation in structured self-management education. Each of these is a distinct, measurable outcome with different implications for program design.
The health outcome you select here determines the content of multiple subsequent sections: the evidence summary needs to support why improving this outcome matters, the SMART objectives are written around this outcome, and the data collection plan describes how you will measure change in this outcome. Choosing an outcome that is too broad — “improve health in diabetic patients” — makes all of those sections harder to write with specificity, and the rubric will reflect that vagueness across multiple criteria.
Section 5: Summarizing Current Evidence
This section requires a “clear, concise, and well-organized summary of current evidence that supports the importance of improving the health outcome.” The rubric is evaluating two things simultaneously: whether the evidence is current (not relying on studies from 15 years ago when more recent data exists) and whether it directly supports the specific outcome you have selected rather than the disease generally.
Current evidence means publications within approximately the last five years for most health outcomes, using peer-reviewed sources from databases like PubMed, CINAHL, or the Cochrane Library. Nash et al. (2021) is cited in the assignment instructions and can serve as a framing reference, but a summary of current evidence requires primary research — systematic reviews, randomized controlled trials, large-scale cohort studies — that demonstrates the significance of your specific health outcome in your specific population.
The evidence summary should establish three things: that the outcome currently falls short of what it could or should be in your population (the gap), that improving the outcome produces meaningful downstream benefits (the value), and that evidence-based programs have demonstrated the capacity to improve it (the feasibility). A summary that only establishes the gap without establishing the value and feasibility of improvement is incomplete — and the rubric will mark it down accordingly. The Healthy People 2030 objectives (health.gov/healthypeople) are a citable source for establishing national benchmarks against which your population’s outcome can be compared.
Section 6: Describing the Evidence-Based Program
The assignment asks you to briefly describe the evidence-based program you are developing and explain why this approach will best fit the needs of your population. “Evidence-based” here means the program design is grounded in an intervention model or approach that has demonstrated effectiveness in the literature — not that you are replicating an existing program verbatim, but that the strategies you are using (self-management education, motivational interviewing, community health worker outreach, peer support, telehealth follow-up) have evidence behind them.
The fit justification is where the epidemiologic work from earlier sections pays off. Why this approach for this population? Because the person characteristics showed low health literacy — so a written materials-only approach would fail. Because the place characteristics showed geographic dispersion — so a community health center-based model would miss too many people. Because the time characteristics showed rapid rise in a specific age group — so the program needs to target a specific recruitment channel. These connections make the program design section score at the excellent band instead of the good or fair bands.
Section 7: Data Collection and Analysis
The assignment asks you to explain what data you would need to collect, how you would obtain and analyze it, whether you would use primary or secondary data, and to justify your choice. This is a methods section, and it is evaluated at 25 points with a specific requirement for “a strong justification for choices.” The justification is what separates excellent from good-band responses — many students describe what data they will collect without explaining why that data source is appropriate given the population, the outcome, and the program type.
Primary Data: When It Makes Sense
Primary data collection means gathering data directly from your target population — surveys, interviews, clinical measurements, direct observation. Justify primary data when secondary sources do not capture your specific outcome at the right level of granularity, when your population is not well-represented in existing datasets, or when you need baseline measures from your specific program participants before intervention begins. Describe the instrument (validated survey name, clinical protocol), sampling strategy, and analysis plan (descriptive statistics, pre-post comparison, regression).
Secondary Data: When It Makes Sense
Secondary data comes from existing sources — CDC BRFSS, Medicare/Medicaid claims, state health department surveillance systems, electronic health records, hospital discharge databases. Justify secondary data when the outcome is routinely captured in surveillance systems, when the cost and time of primary data collection exceed program resources, or when you need population-level trend data to contextualize program results. Identify the specific dataset by name, explain what variables it contains that map to your outcome, and describe how you will access it.
Many proposals describe data collection but skip data analysis — which the rubric requires (“how you would obtain and analyze it”). Describe the specific analytic approach: pre-post comparison of outcome measures, comparison to a control group or historical baseline, use of descriptive statistics to characterize the program population, or multilevel modeling if you are examining variation across sites. You do not need to describe statistical software or advanced methodology — but you do need to show that the data collected can be used to answer the question of whether the program achieved its health outcome objective.
Section 8: Writing SMART Objectives
SMART objectives — Specific, Measurable, Achievable, Relevant, Time-bound — are one of the most frequently tested and most frequently done incorrectly elements of any program proposal. The rubric requires both short-term and long-term objectives, scored at 25 points, with “poor” defined as objectives that “do not meet SMART criteria.” Every word in a SMART objective does specific work, and vague language in any element causes the objective to fail.
| SMART Element | What It Requires in the Objective | Common Error |
|---|---|---|
| Specific | Names the population, the behavior or outcome to change, and the direction of change (increase, decrease, achieve) | “Improve health outcomes” — not specific. “Reduce uncontrolled blood pressure in Hispanic adults with hypertension enrolled in the program” — specific. |
| Measurable | States how the change will be quantified — a percentage, a rate, a validated scale score, a frequency count | “Increase awareness” — not measurable. “Increase self-management knowledge scores by ≥15 points on the Diabetes Knowledge Questionnaire” — measurable. |
| Achievable | The target is realistic given available resources, time, and what the evidence base suggests is feasible for similar programs | Setting a 90% reduction in hospitalizations in 6 months when similar programs achieve 15–20% — not achievable. Grounding targets in cited comparable program outcomes resolves this. |
| Relevant | The objective directly addresses the health outcome identified in Section 4 and is consistent with the program type described in Section 6 | Writing an objective about medication adherence when the identified health outcome is emergency department visits — relevant only if you can connect them, which requires explanation. |
| Time-bound | States a specific timeframe by which the objective will be achieved (6 months from program enrollment, by end of Year 1, within 12 months of program launch) | “Eventually” or “over time” — not time-bound. “By Month 6 of program participation” — time-bound. |
SHORT-TERM (process/intermediate outcomes, typically 3–6 months): By Month 3 of the program, at least 75% of enrolled adults with type 2 diabetes will attend a minimum of 4 of 6 structured self-management education sessions, as measured by attendance logs maintained by program health educators.
LONG-TERM (clinical/health outcomes, typically 12 months or beyond): By Month 12 of the program, at least 50% of enrolled adults with type 2 diabetes who had HbA1c values ≥8% at baseline will demonstrate HbA1c values below 8%, as measured by laboratory results obtained at 12-month clinical follow-up visits.
Note: Short-term objectives typically target process outcomes (participation, knowledge, skill acquisition) because clinical outcomes take time to change. Long-term objectives target clinical or behavioral outcomes. Writing both at the clinical outcome level for a 6-month and 12-month timeframe respectively is a common error — short-term outcomes for a clinical program are almost always process outcomes.
Section 9: Stakeholder Identification
Stakeholders are individuals, groups, or organizations with a vested interest in the program — either because they will be affected by its outcomes, contribute resources to it, or be involved in implementing or overseeing it. The rubric evaluates whether you have accurately identified the relevant stakeholders at 20 points. Listing only clinical stakeholders (physicians, nurses, pharmacists) for a community-based program misses the broader stakeholder ecosystem and will score in the fair band.
For a chronic disease program at the community level, stakeholders typically include the target population and their families (primary beneficiaries), community health workers and navigators (frontline implementers), community-based organizations such as faith communities, social service agencies, and patient advocacy groups (partner organizations), healthcare systems and primary care providers (clinical partners), public health departments (regulatory and data partners), and payers including Medicaid managed care organizations or community development financial institutions (financial stakeholders). Identifying each group and briefly explaining their role in program planning — rather than simply listing names — satisfies the rubric’s “concisely identifies” standard at the excellent band.
Section 10: Program Planning Model
At 40 points, this is the highest-weighted single criterion in the rubric. It has three distinct scored components: identifying which planning model from Curley Chapter 7 you selected, justifying that selection, and explaining how you would plan, implement, and evaluate the program based on the model. A proposal that names a model without justifying it, or that justifies it without applying it to planning, implementation, and evaluation, will score in the good or fair band on this criterion alone — costing up to 15 points.
PRECEDE-PROCEED
A multi-phase model that begins with outcome assessment and works backward to identify causal factors before designing interventions. Strong choice for proposals where the behavioral and environmental determinants of the health outcome are well-described in the epidemiologic literature and can be directly connected to program strategies.
Logic Model
A visual and conceptual framework linking inputs, activities, outputs, and short- and long-term outcomes. Strong choice when the proposal needs to make the program theory of change explicit and when multiple stakeholders with different orientations need to understand the program logic. Compatible with most grant funding requirements.
PDSA Cycle
Plan-Do-Study-Act — an iterative quality improvement model. Appropriate for programs embedded within existing healthcare systems where rapid cycle testing and improvement are feasible. Less appropriate for community-based programs being designed from scratch where a more comprehensive planning framework is needed before iteration begins.
What the Planning, Implementation, and Evaluation Explanation Must Cover
- Planning: What needs assessment or community assessment steps does the model require? Which stakeholders are involved in planning and how? What data inputs inform the plan? How does your chosen model structure the planning phase specifically?
- Implementation: What does the model say about how interventions should be rolled out? What sequencing does it prescribe? How does implementation fidelity get maintained? Who is responsible for which implementation components?
- Evaluation: What types of evaluation does the model include (process, outcome, impact)? What data sources feed the evaluation? How are evaluation findings used to adjust the program? What does the model say about evaluation timing and who conducts it?
The excellent band requires that your planning, implementation, and evaluation explanation is based on the selected model — meaning the model’s specific steps, phases, or components structure your answer, not just generic program planning language that could apply to any model.
Section 11: Cultural and Ethical Considerations
The rubric asks for “relevant” cultural and ethical considerations — not an exhaustive list of every possible cultural or ethical issue, but a substantive discussion of those specific to your chosen disease, population, and program type. The word “relevant” is important: cultural considerations for a hypertension self-management program in an African American urban community are different from those for a tobacco cessation program in a rural Appalachian population, and a proposal that lists generic cultural competency principles without connecting them to the specific population and program will score in the fair band.
Cultural Considerations
Address language and literacy in program materials. Address how the disease is understood within the cultural context of the population (illness beliefs, stigma, the role of family in health decisions). Address who is a trusted messenger in the community (faith leaders, traditional healers, community health workers from the same background). Address whether any program activities are culturally incongruent and what adaptations are needed. Cite culturally adapted evidence-based programs if they exist for your population.
Ethical Considerations
Address informed consent for data collection from participants. Address privacy protections for health information. Address equity — does the program prioritize the highest-need subgroup within your population, or does it inadvertently reach those who are easier to reach rather than those who bear the greatest burden? Address any potential conflicts of interest between program funders and program design. Address power dynamics if the population is historically underserved.
Sections 12–13: Funding and Marketing
These two sections carry 10 points each — smaller than the others but still scored separately. The rubric requires an “accurate and detailed” explanation of funding and “accurate and detailed description” of marketing strategies. Detailed means more than naming a funding source or marketing channel; it means explaining why that source is appropriate for this program and this population.
Funding
Realistic funding sources for a chronic disease community program include federal grants (CDC Chronic Disease Prevention grants, HRSA community health center funding, NIH Small Business Innovation Research grants for technology-enabled programs), state health department grants, foundation grants (Robert Wood Johnson Foundation, American Heart Association, American Diabetes Association research and program grants), Medicaid value-based care contracts, and hospital community benefit funds under IRS requirements for nonprofit hospitals. Each source has eligibility requirements and funding priorities — match your program type to sources that fund that type of program, and briefly explain the match. A community-based diabetes self-management program for uninsured adults, for example, is well-aligned with HRSA community health center funding and Medicaid managed care quality improvement contracts.
Marketing
Marketing strategies should be matched to the population characteristics established in Section 2. A population with high social media engagement warrants a different channel mix than a population with limited internet access. Relevant strategies for community-based chronic disease programs include primary care provider referrals and co-location, community health worker outreach to specific neighborhoods or community settings, faith community partnerships, social service agency referrals, and targeted social media or text message campaigns for populations with smartphone access. Describe the strategy, the channel, and why it fits this specific population — not a generic marketing plan that would apply to any program.
Where Most Proposals Lose Marks
Describing a Disease Instead of a Program
Front-loading the proposal with extended disease background at the expense of the program design sections. The assignment asks for a program proposal, not a disease overview. Sections 1–5 are context; Sections 6–13 are the actual proposal content. Most of the rubric points sit in Sections 6–13.
Instead
Keep the disease description sections (person, place, time; geographic characteristics; evidence summary) concise and focused on what is needed to justify program design decisions. Every fact you include should connect to a program choice made in a later section.
SMART Objectives That Fail the Measurable Test
Writing objectives that describe activities rather than outcomes, or that are not quantified. “Participants will learn about the importance of blood pressure management” is an activity, not a SMART objective. “Participants will improve knowledge scores on the Hypertension Self-Management Scale by ≥20% from baseline by Month 3” is a SMART objective.
Instead
Test each objective against all five SMART criteria before submitting. If you cannot specify exactly how you will measure the outcome, the objective fails the measurable test. If you cannot state a specific timeframe, it fails the time-bound test. Both are rubric criteria for the “poor” band.
Naming a Planning Model Without Applying It
Writing “I selected PRECEDE-PROCEED because it is comprehensive and evidence-based” and then describing a generic planning, implementation, and evaluation process that does not reference PRECEDE-PROCEED’s specific phases. The rubric requires the explanation to be “based on the model” — which means using the model’s actual steps.
Instead
Read the model in Curley Chapter 7 before writing this section. Identify the specific phases or components of your chosen model and use them to structure your planning, implementation, and evaluation explanation. The model’s language should appear in your proposal — not just the model’s name.
Generic Cultural Considerations
Writing “the program will be culturally sensitive and use interpreters when needed” without connecting cultural considerations to the specific population characteristics described in Section 2. Generic cultural competency language without population-specific content scores in the fair band.
Instead
Refer back to the population characteristics you established in Section 2 and identify which of them create specific cultural or ethical considerations for program design. If the population has high rates of limited English proficiency, describe what that means for materials, staffing, and community partnerships — specifically.
No Justification for Data Collection Choice
Describing a data collection plan (surveys, EHR data, CDC surveillance data) without explaining why that approach is appropriate for this program, this population, and this outcome. The rubric explicitly scores justification — a description without justification is “poor” band.
Instead
For every data source or collection method you describe, add one or two sentences explaining why it is appropriate given your population (access, literacy, language), your outcome (what data source captures it best), and your program resources (what you can feasibly collect and analyze).
Falling Short of 7 Pages
Submitting a 5- or 6-page proposal when the assignment requires 7–10 pages (not including title page and references). With 13 rubric criteria, each needing substantive coverage, a proposal below the minimum length almost certainly has undersized sections. Thin treatment of the planning model section alone can lose 10+ points.
Instead
Map the page count roughly before writing. With 13 criteria across 7–10 pages (excluding title/references), each section averages 0.5–0.75 pages. Sections with higher point values (planning model at 40 pts, evidence summary at 25 pts) justify more space than sections at 10 pts.
Frequently Asked Questions
Getting the Proposal Right: What the Rubric Is Measuring
The NURS 8310 Week 10 assignment rubric distributes 300 points across 13 criteria, with the highest weight (40 points) on the program planning model section and 25 points each on several other analytical sections. The distribution signals what matters most: not the disease background, but the program design reasoning — the SMART objectives, the planning model application, the data collection justification, the cultural and ethical analysis. These are the sections where students who understand epidemiology and program planning earn the excellent band, and where students who treat this as a descriptive writing exercise consistently score lower.
The connection between epidemiologic analysis and program design decisions is what the assignment is fundamentally testing. If your person-place-time analysis reveals that the highest burden falls on a specific socioeconomic and racial/ethnic subgroup with limited healthcare access, that finding should visibly shape your program type, delivery setting, stakeholder selection, cultural considerations, and marketing strategy. When those connections are made explicit in the writing, the rubric criterion on “strong understanding and application of program planning concepts and strategies” is satisfied. When the proposal reads as a list of independent sections without internal coherence, that criterion drops — regardless of how accurate the individual sections are.
For direct support with this assignment — whether you need help structuring the proposal, developing evidence-based SMART objectives, applying a specific planning model, or writing an APA-formatted program proposal — our public health assignment writing team works specifically with population health nursing coursework and understands what the rubric requires at the excellent band.
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