HLTH 5623 Module 4 Epidemiologic Rate Analysis Example

Rising Pediatric Asthma Emergency Visits in a Four-ZIP Service Area: Rate Selection, a Matched Case-Control Analysis, and the System Response

[Author Name]

Master of Health Administration Program, American College of Education

HLTH5623 Epidemiology and Public Health for Healthcare Administrators

Module 4 Assignment

[Faculty Name]

August 11, 2026

Model document written for teaching. The health system, its service area and all figures are a composite; no real organization, community or patient is described.

The Problem, the Denominator and the Measure

Metro Health Partners is a composite two-hospital system serving four adjacent ZIP codes with a resident population of 186,000, of whom 48,300 are under 18. Between July 2024 and June 2026 the two emergency departments recorded 1,152 visits carrying a primary diagnosis of asthma among children aged 2 to 17, a condition that remains one of the most common chronic diseases of childhood nationally (Centers for Disease Control and Prevention, 2024). The raw count had already reached the operations committee, where the conversation was about overnight staffing on the pediatric side of the department. A count cannot answer what the board actually asked, which was whether the system serves a population that is getting sicker or simply a population that has grown.

The measure selected is an age-specific emergency visit rate: asthma visits among children aged 2 to 17 divided by the mid-period population in that age band, expressed per 1,000 children per year. Across the 24-month window that is 1,152 visits over roughly 96,600 child-years, or 11.9 per 1,000 per year, against a state figure near 7.4 for the same ages. A rate rather than a count puts a denominator under the number so two service areas of different size can be compared at all (Friis & Sellers, 2021). An age-specific rate rather than a crude one prevents a service area with an unusually young population from appearing sicker than it is. Diagnosed prevalence is a different measure answering a different question, and both belong in the report.

A utilization rate measures contact with the system, not disease. It rises when asthma control is poor, and it also rises when primary care is hard to reach, when the only pediatric clinic closes at five, or when a family has no transportation after hours. The Agency for Healthcare Research and Quality (2023) counts pediatric asthma admissions as an indicator of ambulatory access for that reason. Stratification is what keeps the interpretation honest. By ZIP code the rate ranged from 7.1 to 19.4 per 1,000, by age it concentrated in the 2 to 5 band, and by payer, 71 percent of visits carried Medicaid coverage against 46 percent of the area pediatric population. A single system-wide number would have hidden all three patterns, and every one of them points at a different decision.

Study Design and What It Supports

Moving from description to association called for a design, and the analysis used a matched case-control study drawn from the system's own records. Cases were the 486 children with at least one asthma emergency visit in the 12 months ending June 2026. Controls were 972 children carrying a persistent asthma diagnosis with no emergency visit in the same window, matched two to one on age band and ZIP code. The exposure of interest was a gap in controller therapy, defined as no inhaled corticosteroid fill in the 90 days before the index date. A case-control design fits this question because the outcome is uncommon at the level of an individual child, the exposure data already sit in pharmacy claims, and a trial that withheld controller therapy would be neither ethical nor necessary (Centers for Disease Control and Prevention, 2021).

Among cases, 61 percent had no controller fill in the prior 90 days, against 39 percent of matched controls, giving an odds ratio of 2.4 with a 95 percent confidence interval of 1.9 to 3.1. Housing age, used as a rough proxy for indoor allergen exposure, showed a weaker association that did not hold once ZIP matching was applied. The interval matters to an administrator as much as the point estimate does: it excludes 1.0, so chance alone is an unlikely explanation, and its width tells the board how precisely the effect is known. An odds ratio is not a risk ratio, and this analysis cannot promise that closing the fill gap will cut visits by any stated percentage.

Three limits belong in the report before a decision rests on it. Claims data misclassify, because a filled prescription is not a taken dose and a child with pharmacy coverage outside the system appears as a gap that is not a gap. Selection is uneven, since controls were drawn from paneled patients who are by definition already connected to care. Confounding by severity is the hardest of the three, because the sickest children may both miss fills and reach the emergency department for reasons that travel together. Matching handled age and geography; it did not handle severity, and the honest conclusion is an association strong enough to act on and too fragile to call a cause.

What the System Would Do About the Finding

The finding names one lever the system already controls, which makes the first decision operational rather than clinical. Pharmacy analytics would produce a monthly gap list of every paneled child with persistent asthma and no controller fill inside 90 days, routed to the pediatric care management team instead of to the emergency department. At current volumes that list runs near 340 children a month, which two care managers can work at roughly eight contacts a day. The second decision is a standing discharge rule: any child leaving either emergency department with an asthma diagnosis goes home with a controller prescription, a spacer and a follow-up appointment inside seven days, booked before discharge rather than promised at it.

Results would be tracked with a measure payers already recognize. The asthma medication ratio reports the share of children whose controller fills make up at least half of total asthma medication fills (National Committee for Quality Assurance, 2024), and it moves earlier than utilization does, which makes it usable as a leading signal. The Centers for Medicare and Medicaid Services (2024) already collects that measure from state Medicaid programs, so the system will be judged on it either way. The pediatric emergency visit rate stays the outcome measure, reported quarterly, stratified by the same ZIP and payer cuts that produced the finding, with the 7.4 state figure as the external comparison rather than an internal average. A balancing view is needed as well: if emergency visits fall while admissions from the emergency department climb, the system has moved the problem rather than solved it.

Two care management positions, spacers and a modest data build come to roughly $210,000 a year, which the finance committee would weigh against avoidable emergency and inpatient spending concentrated in a Medicaid population. Part of the work sits outside the system entirely, in housing quality and school inhaler policy, and community benefit dollars are the honest instrument there rather than clinical operations. The decision should be revisited if the controller gap narrows with no movement in the visit rate, because that pattern would suggest the association was carrying severity rather than adherence, and the system would then need a different measure and a different design.

References

Agency for Healthcare Research and Quality. (2023). Pediatric quality indicators technical specifications: Asthma admission rate. U.S. Department of Health and Human Services. https://qualityindicators.ahrq.gov/measures/pdi_resources

Centers for Disease Control and Prevention. (2021). Principles of epidemiology in public health practice (3rd ed.). U.S. Department of Health and Human Services. https://www.cdc.gov/csels/dsepd/ss1978/index.html

Centers for Disease Control and Prevention. (2024). Most recent national asthma data. U.S. Department of Health and Human Services. https://www.cdc.gov/asthma/most_recent_national_asthma_data.htm

Centers for Medicare & Medicaid Services. (2024). Quality of care performance measurement: Child health care quality measures. U.S. Department of Health and Human Services. https://www.medicaid.gov/medicaid/quality-of-care/index.html

Friis, R. H., & Sellers, T. A. (2021). Epidemiology for public health practice (6th ed.). Jones & Bartlett Learning.

National Committee for Quality Assurance. (2024). Asthma medication ratio. https://www.ncqa.org/hedis/measures/asthma-medication-ratio/