| Course | HCS 493 Data Analytics for Health Care Managers (HCS/493) |
|---|---|
| Week | 3 |
| Paper type | Clinical and public health data comparison |
| Length | about 1,061 words, 4 double-spaced pages plus title page and references |
| Format | APA 7 student paper |
| School | University of Phoenix |
| Program | BS in Health Administration |
| Updated | September 2026 |
Free sample paper for HCS 493 Week 3
Two Views of the Same Asthma: What a Hospital's Emergency Records and the CDC's Neighborhood Estimates Each Show a Health Care Manager, and Where They Disagree
[Student Name]
University of Phoenix
HCS/493: Data Analytics for Health Care Managers
Week 3 Assignment
[Instructor Name]
[Date]
The hospital and its visit records are composites written for a model paper; the county and census tract estimates are the real CDC PLACES figures for Allen County, Ohio, used for illustration.
The community benefit director at a composite 210-bed community hospital was preparing the hospital's required community health needs assessment. She asked the analytics team a direct question: where in the county is adult asthma worst, so the hospital can place its new respiratory therapist-led education program? The team answered from two kinds of data. The first came from the hospital's own records of emergency visits. The second came from public health estimates published for every neighborhood in the county. The answers overlapped only partly, and the reasons for the differences explain what separates clinical data from public health data.
Clinical Data
Clinical data are created in the course of caring for individual patients: diagnoses, vital signs, medications, test results and procedures recorded in the electronic health record, along with the claims sent to payers. They are detailed and timely. For this question, the team pulled every emergency visit in the past two years by an adult with a primary diagnosis of asthma, 1,284 visits by 911 patients, and grouped them by the census tract of the patient's home address.
What the Clinical Data Showed
Four tracts near the hospital, all within three miles, accounted for 38% of the visits. Rates per 1,000 adults were highest in two tracts with large public housing complexes. On the hospital's data alone, the program belonged near the hospital.
Public Health Data
Public health data describe the health of whole populations, whether or not people sought care. Sources include surveillance systems for reportable diseases, vital records, population surveys and registries. Greenlund et al. (2022) described PLACES, a federal project run with two foundation partners that produces model-based estimates of chronic disease, risk behaviors and prevention for counties and census tracts across the country by combining national survey responses with population data.
What the Public Health Data Showed
In the 2025 PLACES release, based on 2023 data, an estimated 11.1% of adults in Allen County, Ohio, had current asthma, with a 95% confidence interval of 9.9% to 12.5% (Centers for Disease Control and Prevention, 2025a). Across the county's 35 census tracts, estimates ranged from 9.8% to 14.0% (Centers for Disease Control and Prevention, 2025b). Several of the highest tracts matched the clinical data, but two high-prevalence tracts on the far side of the county from the hospital produced almost no emergency visits to it.
Why the Two Sources Disagree
The clinical data count people who had an asthma attack severe enough to seek emergency care, and who chose this hospital. Residents of those two tracts live closer to a hospital in a neighboring county and may go there, or may manage symptoms at an urgent care clinic or not at all. The public health estimates count everyone in the population, including people with well-controlled asthma who never visit an emergency department. The clinical data answer where our patients with asthma come from; the public health data answer where adults with asthma live, and a needs assessment is supposed to answer the second question.
Strengths and Limits of Clinical Data
Clinical data are specific to real encounters, include severity and outcomes and are available within days. Their limits are coverage and bias: they miss people who do not seek care or who go elsewhere, and diagnoses are recorded for billing and treatment rather than research, so coding practices affect counts. Birkhead et al. (2015) noted that electronic health records can support public health surveillance but that differences in data systems, coding and coverage require careful handling.
Strengths and Limits of Public Health Data
Public health data cover whole populations, allow comparison across places and over time and include people outside the health care system. Their limits are timeliness and precision. PLACES estimates are modeled, not counted; they rely on survey responses and population characteristics, carry confidence intervals and lag the present by two years or more. A tract estimate of 14.0% is a best estimate, not a census.
Other Public Health Sources the Team Considered
The team also looked at two other public sources. The state's hospital discharge data set, which combines inpatient and emergency records from every hospital, would capture residents who went to the neighboring county, but it is released more than a year late and at the ZIP code level rather than the tract level. Syndromic surveillance, in which hospitals send near real-time emergency visit data to the health department, tracks sudden rises in respiratory visits during wildfire smoke or high-pollen days. Yoon et al. (2017) described how syndromic surveillance grew from bioterrorism preparedness into an all-hazards tool, which is how the county health department now uses it. Each source adds a piece that neither the hospital's records nor the survey-based estimates provide.
Privacy
The hospital's visit records are protected health information under HIPAA and may be used for its own operations, including this analysis, but only in de-identified or aggregated form in a public report. Published public health estimates such as PLACES are aggregated and carry no individual identities, so they can be shared freely.
Impact on the Health Care Industry
Clinical data drive operations, quality measurement, payment and research within organizations. Public health data drive planning, policy and resource allocation across communities, and they increasingly shape hospital obligations, since needs assessments and population health contracts require organizations to look beyond their own patients. Organizations that rely on one type alone either miss the community or miss the detail.
How the Hospital Will Use Both
The needs assessment will present both maps. The education program will start in the two public housing tracts where both sources agree and add a monthly session at a clinic serving the two distant tracts, where public health data show need but clinical data show little use. The team will ask the neighboring hospital to share aggregated asthma visit counts, and it will recheck the program's reach against the next PLACES release.
Conclusion
The same condition looked different through two lenses. The hospital's clinical data showed where its asthma patients came from, in detail and in near real time. Public health data showed where adults with asthma lived, including those the hospital never saw. Each answers a different question, and the needs assessment, and the program it shaped, are better for using both.
References
Birkhead, G. S., Klompas, M., & Shah, N. R. (2015). Uses of electronic health records for public health surveillance to advance public health. Annual Review of Public Health, 36, 345-359. https://doi.org/10.1146/annurev-publhealth-031914-122747
Centers for Disease Control and Prevention. (2025a). PLACES: Local data for better health, county data, 2025 release [Data set]. https://data.cdc.gov/d/swc5-untb
Centers for Disease Control and Prevention. (2025b). PLACES: Local data for better health, census tract data, 2025 release [Data set]. https://data.cdc.gov/d/cwsq-ngmh
Greenlund, K. J., Lu, H., Wang, Y., Matthews, K. A., LeClercq, J. M., Lee, B., & Carlson, S. A. (2022). PLACES: Local data for better health. Preventing Chronic Disease, 19, Article 210459. https://doi.org/10.5888/pcd19.210459
Yoon, P. W., Ising, A. I., & Gunn, J. E. (2017). Using syndromic surveillance for all-hazards public health surveillance: Successes, challenges, and the future. Public Health Reports, 132(1_suppl), 3S-6S. https://doi.org/10.1177/0033354917708995
What the HCS 493 Week 3 instructions ask
HCS 493 Week 3 commonly asks students to explain the difference between clinical data and public health data and the impact of each on the health care industry. Students may be asked to define both types, name sources such as electronic health records, claims, registries, surveillance systems and national surveys, describe how each is collected and used and discuss their strengths, weaknesses and privacy considerations. Some prompts ask for an example of how an organization combines the two. Papers usually run two or three pages and cite peer-reviewed or agency sources. Strong papers go beyond definitions to show what each type of data can and cannot answer, use a specific condition or program as the example and explain the practical consequence for managers.
How this HCS 493 Week 3 example is built
The paper opens with a request from the hospital's community benefit director, who is preparing a needs assessment and wants to know where adult asthma is worst in the county. It shows the answer from the hospital's own emergency records, visits by patients' home neighborhood, and the answer from public health data, model-based prevalence estimates for each census tract. The two maps agree on some neighborhoods and disagree on others. Each source is described by who collects it, what it counts, its strengths and its blind spots. A section on privacy explains the rules for each. The paper closes with how the hospital will use the two sources together in its assessment and programs.
HCS 493 Week 3 grading rubric: where the points go
Faculty in the data-comparison week usually look for accurate definitions and, above all, a clear explanation of how the two kinds of data differ in purpose, collection, coverage and use. Points go to named, real sources for each type, a balanced account of strengths and limitations and an example showing the impact on decisions in health care organizations. Awareness of privacy rules and data quality earns credit. Scholarly or government sources should support the discussion. Organization, clear writing and APA style make up the remainder. Work that treats public health data as simply clinical data added up, or that lists sources with no discussion of what questions they can answer, typically falls short of the upper range.
HCS 493 Week 3 help: mistakes to avoid
A common gap in HCS 493 Week 3 is describing clinical and public health data as the same numbers at different sizes. Clinical data record care given to individual patients who sought it; public health data describe whole populations, including people who never came in. Say so plainly, and show a case where the two disagree. Another error is presenting survey or model-based estimates as exact counts; note confidence intervals and methods. Students also forget that clinical data reflect who uses a particular hospital, not the community. Mention privacy: patient-level records fall under HIPAA, while published public health estimates are usually aggregated. Use real sources by name. Finally, end with how an organization can use both together.
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HCS 493 Week 3 questions, answered
What does HCS/493 Week 3 usually ask for?
Many sections ask students to explain the difference between clinical and public health data, give examples and sources of each and discuss their impact on the health care industry.
Where can I find a free HCS 493 Week 3 sample paper?
The asthma data comparison on this page can be read in full at no charge, with notes on the side marking how each source is used. Send your own prompt and a first custom paper is free.
What is the difference between clinical data and public health data?
Clinical data come from caring for individual patients, such as health records and claims; public health data describe the health of whole populations, such as surveillance systems, vital records and surveys.
What is CDC PLACES?
A CDC project that provides model-based estimates of chronic disease measures, risk behaviors and prevention for counties, places, census tracts and ZIP code areas across the United States.
Can clinical data be used for public health surveillance?
Yes. Data from electronic health records can support surveillance, such as syndromic surveillance of emergency visits, though they cover only people who seek care at participating sites.
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