DHA 731 Week 6 Resource Allocation Decisions in Population Health Example

Ten Tracts, One Grant: Allocating $1.2 Million for Chronic Disease Across Four Rural North Carolina Counties

[Student Name]

University of Phoenix

DHA/731: Population Health and Epidemiology

Week 6 Assignment

[Instructor Name]

[Date]

The health network, the grant, program costs, county requests and the allocation process are composites written for a model paper. Tract figures are real CDC PLACES 2025 release estimates for Bertie, Halifax, Hertford and Northampton counties; research findings come from the sources cited.

The region received a one-time grant of $1.2 million to reduce the burden of chronic disease over three years. Within a week, officials from each of the four counties asked for an equal share, $300,000 apiece. Their request was simple and politically comfortable. Before agreeing, the vice president asked two questions: was the request fair, and would it do the most good? This paper examines how the grant should be allocated.

Defining the Problem

The grant can fund community health workers, food programs, transportation and chronic disease education, and it must be spent within three years. The need is larger than the grant, which works out to under five dollars a year for each adult in the region. Every dollar spent in one place is a dollar not spent elsewhere, so the question is not whether to leave some needs unmet but which ones, and on what grounds.

Principles of Allocation

Ethicists have described values for allocating scarce health resources. Emanuel and colleagues named four values that recur in these debates: producing the most benefit, giving each person equal consideration, favoring those whose work helps others and helping those in the greatest need first. They put the most weight on producing benefit and treated the other values as guides to how that benefit should be pursued (Emanuel et al., 2020). Although written for scarce medical resources during a pandemic, these values apply to any limited budget.

Equal Shares

Equal shares treat counties equally but not people. Halifax County has more than twice as many adults as each of the other counties, and its tracts include most of the region's highest-need areas. An equal split would also ignore differences within counties: some tracts in every county have needs close to the state average, while others have diabetes and food insecurity rates among the highest in North Carolina. An equal split would give each Halifax resident far less than each resident elsewhere.

Allocation by Need

Allocation by need directs resources where the burden is greatest. Real tract estimates show that 10 of the 39 tracts have both diagnosed diabetes at 22% or more of adults and food insecurity at 30% or more; these tracts contain about 22,000 adults, roughly a quarter of the region's adults, and include six tracts in Halifax, two in Northampton and one each in Bertie and Hertford (Centers for Disease Control and Prevention [CDC], 2025). In the highest-need tract, 25.8% of adults have diabetes, 45.6% report food insecurity and 22.0% lack reliable transportation (CDC, 2025).

Adding Social Vulnerability

Need also includes a community's capacity to respond. Flanagan and colleagues at CDC combined fifteen census measures for each tract, covering income, age, disability, language, race, housing and access to a vehicle, into an index of how hard a disaster would hit a community and how slowly it would recover, and they tested it against what happened in Hurricane Katrina (Flanagan et al., 2011). The index's socioeconomic, household, minority status and housing measures help identify tracts where the same program will face more barriers.

Maximizing Benefit

Need alone is not enough. A dollar spent where a program is likely to work produces more health than a dollar spent where it cannot be delivered. Community health workers reach more people in tracts with dense housing than in tracts where homes are miles apart, and food programs work best where partners such as food banks and churches already operate. The team estimated cost per person reached for each program in each tract, using the pilot's experience and partners' records, and found costs up to twice as high in the most isolated tracts.

Priority to the Worst Off

Giving priority to the worst off supports concentrating resources in the ten highest-need tracts, even if a program there costs more per person. The region's values statement commits it to reducing disparities, which favors this principle. Spreading the grant evenly would feel fair to the counties and unfair to the people who need it most.

A Formula Combining Need and Benefit

The team built a simple formula. Each tract received a need score combining diabetes prevalence, food insecurity and transportation barriers, weighted equally, and a feasibility score reflecting partners and program reach. Seventy percent of the grant was allocated by need score and 30% by feasibility, applied to tracts rather than counties.

The Resulting Allocation

The formula directed about 62% of the grant to the ten high-need tracts and 38% to the remaining 29. The team tested other weights: shifting to 50% need and 50% feasibility moved about $90,000 away from the most isolated tracts, a change the advisory group rejected as contrary to the region's commitment to reducing disparities. By county, Halifax received about $560,000, Northampton $230,000, Bertie $210,000 and Hertford $200,000. Every county received resources, but in proportion to need rather than as equal shares.

A Fair Process

Data and formulas do not by themselves make an allocation legitimate. Daniels argued that limit-setting decisions are fair when they meet four conditions: publicity, meaning the reasons are public; relevance, meaning they rest on reasons fair-minded people can accept; revision and appeals, allowing decisions to be challenged and changed; and regulation, ensuring the other conditions are met (Daniels, 2000).

Applying Accountability for Reasonableness

The region published the formula, data and weights on its website and presented them at meetings in each county. A community advisory group, with residents from high-need tracts, reviewed the weights. Counties could appeal within thirty days with new data. Hertford County appealed, citing a new food pantry that improved feasibility, and its allocation was increased by $20,000, drawn from a small reserve held back for appeals. The appeal showed the process working as intended: new information changed the result, and the change was explained publicly.

Trade-Offs

The allocation accepts trade-offs openly. Some residents with high needs in lower-scoring tracts will receive less, although clinic-based services remain open to anyone who needs them. Programs in the most isolated tracts may cost more per person. And county officials who wanted equal shares may be dissatisfied. The vice president met with each county's officials to explain the formula, and three of the four accepted it once they saw their own high-need tracts identified by name. Local ownership matters: county health departments will help deliver the programs, and their support depends on understanding why the money went where it did.

Measures

Measures include people reached in each tract, cost per person reached, blood sugar control among program participants, food insecurity screening and referrals, rides provided and satisfaction of community advisory members with the process.

Conclusion

Equal shares would have been simple but would have given the least to the people with the most need. Real tract data show need concentrated in ten tracts. Ethical values support directing resources toward the worst off while seeking benefit, and a transparent process with appeals makes the allocation legitimate.

References

Centers for Disease Control and Prevention. (2025). PLACES: Local data for better health, census tract data, 2025 release [Data set]. data.cdc.gov. https://data.cdc.gov/d/cwsq-ngmh

Daniels, N. (2000). Accountability for reasonableness. BMJ, 321(7272), 1300-1301. https://doi.org/10.1136/bmj.321.7272.1300

Emanuel, E. J., Persad, G., Upshur, R., Thome, B., Parker, M., Glickman, A., Zhang, C., Boyle, C., Smith, M., & Phillips, J. P. (2020). Fair allocation of scarce medical resources in the time of Covid-19. New England Journal of Medicine, 382(21), 2049-2055. https://doi.org/10.1056/NEJMsb2005114

Flanagan, B. E., Gregory, E. W., Hallisey, E. J., Heitgerd, J. L., & Lewis, B. (2011). A social vulnerability index for disaster management. Journal of Homeland Security and Emergency Management, 8(1), Article 3. https://doi.org/10.2202/1547-7355.1792