| Course | D029 Informatics for Transforming Nursing Care |
|---|---|
| Task | Task 1 |
| Paper type | Population health data analysis |
| Length | About 1,100 words, 4 pages |
| Format | APA 7 |
| School | Western Governors University (WGU) |
| Program | MSN |
| Updated | September 2026 |
Free sample paper for D029 Task 1
Population Health Data Paper: Excessive Drinking and Alcohol-Impaired Driving Deaths in a Composite Upper Midwest County
Student Name
Leavitt School of Health, Western Governors University
D029: Informatics for Transforming Nursing Care, Task 1
Course Instructor
Month Day, Year
Population Health Data Paper: Excessive Drinking and Alcohol-Impaired Driving Deaths in a Composite Upper Midwest County
The County
The county in this paper is a composite rural and small-town county in the Upper Midwest with about 48,000 residents. Its largest town has 14,000 people and a 60-bed hospital; the rest of the county is farmland, lakes and small towns connected by two-lane highways. The population is older than the state average, and tourism brings a large seasonal increase in summer. Data were gathered from the county's County Health Rankings profile, which assembles national survey, vital statistics and traffic fatality data, and compared with the state averages and the top-performing United States counties that the site reports (County Health Rankings and Roadmaps, 2025).
Population Health Data
The profile shows a county that performs near the state average on many measures but poorly on several health behaviors. The values below are illustrative for the composite county and are presented in the form County Health Rankings uses.
| Measure | County | State | Top U.S. performers |
|---|---|---|---|
| Adult smoking | 17% | 15% | 15% |
| Adult obesity | 36% | 34% | 34% |
| Excessive drinking | 27% | 24% | 15% |
| Alcohol-impaired driving deaths (share of driving deaths) | 44% | 31% | 10% |
| Uninsured adults | 7% | 6% | 6% |
| Primary care physicians (population per physician) | 2,180:1 | 1,280:1 | 1,030:1 |
| Mental health providers (population per provider) | 870:1 | 470:1 | 300:1 |
| Children in poverty | 13% | 12% | 9% |
| Injury deaths (per 100,000) | 102 | 82 | 64 |
Significance of the Data
Two patterns stand out. The first is limited access to care: the county has about half as many primary care physicians and mental health providers per resident as the state, which makes screening and early treatment harder to reach. The second, and more striking, is alcohol. Excessive drinking, defined as binge or heavy drinking, is reported by 27% of adults, higher than the state and far above the top-performing counties. More than four in ten driving deaths in the county involved alcohol, compared with three in ten statewide and one in ten in the best-performing counties. The county's injury death rate is also well above the state rate, and alcohol contributes to many of those deaths through crashes, falls and drownings on its lakes.
These findings matter because County Health Rankings is built on a model in which four groups of determinants, namely behaviors, clinical care, the physical environment and income, education and community conditions, together shape how long and how well people live. An analysis of the model found that health behaviors accounted for about 34% of the variation in health outcomes across counties, second only to social and economic factors (Hood et al., 2016). A health behavior as far out of line as this county's drinking is therefore likely to be contributing to its poorer outcomes, and it is one that nurses, clinics and communities can act on.
Health Factor Requiring Focused Attention
The health factor selected for a population health initiative is excessive drinking, with alcohol-impaired driving deaths as its most visible consequence. It is the county's largest gap from both its state and the top performers, it contributes to the high injury death rate, and effective, affordable interventions exist. It also interacts with the county's shortage of mental health providers, since unhealthy drinking often travels with depression and anxiety that go untreated when services are scarce.
From an informatics point of view, excessive drinking is also a factor the county's own systems can measure better than they do now. Neither primary care clinic records a structured alcohol screening result, so the county currently depends on survey estimates collected every few years. Building a standard screening field into the electronic health record would give the county its own quarterly data, allow the clinics to see which patients have been screened and followed up, and create the local baseline that population health work needs. The initiative is therefore as much about creating usable data as about changing behavior.
Action Plan
The plan has three parts, led by the county public health nurse in partnership with the hospital, its two primary care clinics, law enforcement and the county's substance use coalition. First, universal screening and brief intervention in primary care. National prevention guidance gives this a B grade: every adult seen in a primary care practice should be asked about drinking, and those whose answers show risky or hazardous use should be offered brief counseling (US Preventive Services Task Force, 2018). Both clinics will add a three-question screening tool to the rooming workflow in the electronic health record, with a prompt for a brief intervention and a referral pathway when needed. Nurses will be trained to deliver the brief intervention so that it does not depend on physician time the county lacks.
Second, screening and brief intervention in the hospital's emergency department for patients seen after injuries, crashes or falls, when the link between drinking and harm is most immediate. Third, a community campaign timed for summer, when tourism and lake activity peak, delivered with the coalition and the sheriff's office: messages about safe rides and boating, a partnership with bars and marinas for designated-driver incentives, and publicized sobriety checkpoints, which are an established community strategy for reducing alcohol-impaired crashes. The public health nurse will coordinate a quarterly meeting of all partners to review progress.
Monitoring and Evaluation
The plan will be monitored with the same data that identified the problem, plus local measures that change faster. Process measures, reviewed quarterly from the clinics' electronic health records, are the proportion of adult visits with a completed alcohol screen, with a target of 80% within a year, and the proportion of positive screens with a documented brief intervention, with a target of 70%. The emergency department will report the same two measures for injury visits. The coalition will track the number of partner businesses and the reach of the summer campaign.
Outcome measures will be tracked annually. County Health Rankings updates excessive drinking and alcohol-impaired driving deaths each year, but because these measures are averaged across several years and small counties have few deaths, change will appear slowly. The plan will therefore also use state crash reports for alcohol-involved crashes in the county and the hospital's count of alcohol-related emergency visits as earlier indicators. The initiative will be judged a success if screening and intervention targets are met within a year and alcohol-involved crashes fall over three summers compared with the three years before the plan began.
References
County Health Rankings and Roadmaps. (2025). County health rankings model and data. University of Wisconsin Population Health Institute. https://www.countyhealthrankings.org
Hood, C. M., Gennuso, K. P., Swain, G. R., & Catlin, B. B. (2016). County Health Rankings: Relationships between determinant factors and health outcomes. American Journal of Preventive Medicine, 50(2), 129-135. https://doi.org/10.1016/j.amepre.2015.08.024
US Preventive Services Task Force. (2018). Screening and behavioral counseling interventions to reduce unhealthy alcohol use in adolescents and adults: US Preventive Services Task Force recommendation statement. JAMA, 320(18), 1899-1909. https://doi.org/10.1001/jama.2018.16789
What the D029 Task 1 instructions ask
The first D029 task asks you to use population health data to identify a priority and plan an initiative. Most versions ask you to describe a county, present health data from a source such as County Health Rankings, explain the significance of the data, select a health factor that needs focused attention, propose an action plan and explain how progress will be tracked. Use current figures for the county you pick, or label them plainly as illustrative. The evaluator reads for data interpreted in context, a priority that follows from the data, and a plan whose measures could show change within a reasonable time.
How this D029 Task 1 example is built
The paper begins with the county's size, economy and geography. Data are presented in a table with county and state values, so differences are visible. The significance section picks out two patterns and explains what they mean for residents. The selection section explains why excessive drinking was chosen over other weak measures, citing its link to a severe outcome and the availability of effective interventions. The action plan has three parts with named partners, including screening supported by preventive services recommendations. Monitoring separates process measures, which change quickly, from outcome measures in the rankings, which change slowly, and sets a review schedule. The action plan names the county public health nurse as lead.
Where the D029 Task 1 rubric puts the marks
Evaluators score D029 Task 1 aspect by aspect as competent, approaching competence or not evident. A county description aspect checks context. A data aspect wants accurate figures from a credible source, compared with a benchmark. A significance aspect asks what the data mean for the population. A selection aspect looks for a health factor justified by the data. Action plan aspects want specific steps and partners, and a monitoring aspect asks for measures and timing. Evaluators notice whether the plan's measures could detect change. The rankings release year belongs in the citation, and the prose should read like a report to a health department. Evaluators also look for a health factor that nurses can influence, since a priority outside nursing's reach makes the action plan harder to defend.
D029 Task 1 help: what sends it back
Population data papers are returned most often when figures appear without comparison. Show state or national values beside the county's. Second, the selected factor does not follow from the data. Explain why this factor, among the weak ones, deserves attention now. Third, action plans are broad, such as promoting healthy behaviors. Name the intervention, the partners and who leads. Fourth, monitoring relies only on annual rankings that change slowly. Add local process measures that show progress sooner. Finally, cite the data source with its release year, since county rankings update annually and older figures can mislead. Keep the plan focused on one factor.
Get a D029 Task 1 example written to your instructions
Send the Task 1 instructions and template from your D029 course of study, plus the county you have chosen. We write a custom population health data paper to those exact aspects and return it in 24-48h. The first custom sample is free.
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D029 Task 1 questions, answered
Which county should I use for D029 Task 1?
Your instructions decide, and many versions ask for the county where you live or work. Use the County Health Rankings profile for that county and compare it with your state and with the top-performing counties the site reports.
How many health factors should the D029 paper focus on?
Summarize the key findings across the profile, then choose at least one factor that clearly needs attention and build the action plan around it. Focusing on one factor usually produces a stronger plan than trying to address several.
What happens if my D029 Task 1 comes back as not competent?
You revise the parts the evaluator names and resubmit. Returns usually concern data without comparison or an evaluation plan without measures, and both are fixed in a paragraph.
Which county should I use for D029 Task 1?
Follow your instructions; many students choose their home or work county because they can interpret its data with local knowledge. The sample uses a composite Upper Midwest county to show the method.
Where can I find a free D029 Task 1 sample paper?
The whole data paper, table and action plan included, is published above with notes. Name your county and send the D029 instructions for a first tailored data paper at no charge.