HLTH 3100 Week 9 Resource Allocation Argument Example

Twenty Places, Sixty Applicants: An Argument for Allocating a Free Diabetes Education Program by Greatest Need, Then by Lottery

Student Name

Walden University

HLTH 3100: Ethical and Legal Issues in Healthcare

Instructor Name

Month Day, Year

Twenty Places, Sixty Applicants: An Argument for Allocating a Free Diabetes Education Program by Greatest Need, Then by Lottery

The Shortage

A rural federally qualified health center has grant funding for one cohort of a free 12-week diabetes self-management program led by a certified educator. The program has 20 places. Sixty adult patients with type 2 diabetes have asked to join after their clinicians recommended it. The program cannot be expanded this year, and the next grant cycle is uncertain. The center's administrator must decide who gets the 20 places. The scenario is invented for this assignment.

Allocation decisions are uncomfortable because any criterion ranks some people lower. This paper chooses one criterion, defends it against the obvious rivals and states clearly what it costs the people it ranks lower.

Every one of the 60 applicants would likely benefit, so whatever rule is used will turn away people with a real need.

The Rival Criteria

One influential review (Persad et al., 2009) sorts the principles behind scarce-resource decisions into families: equal treatment, which includes lotteries and taking people in order of arrival; priority to those worst off, whether by illness or by age; maximizing total benefits, such as lives saved or years gained; and promoting social usefulness. In their view, every single principle fails somewhere on its own, so a workable scheme mixes two or more. Four candidates are realistic here.

First come, first served. The first 20 applicants get places. This is simple and appears neutral, but it favors patients who heard about the program first and could respond quickly, often those with phones, flexible jobs and good contact with the clinic.

Lottery. All 60 have an equal chance. This treats applicants as equals and is hard to manipulate, but it ignores real differences in need.

Greatest expected benefit. Choose the patients most likely to improve, perhaps those with good attendance records and stable lives. This would maximize measured results but would tend to exclude patients facing the most obstacles.

Greatest need. Choose the patients whose diabetes is least controlled, measured by the most recent hemoglobin A1c, the blood test that reflects roughly the past three months of glucose control.

The Criterion Chosen: Greatest Need, Then Lottery

I propose that the 20 places go first to applicants whose most recent A1c is 9% or higher, a level commonly treated as poor control, and that a lottery decide among applicants at the same level if there are more of them than places. If fewer than 20 applicants have an A1c of 9% or higher, the remaining places are filled by lottery among the other applicants.

The reasons are three. First, the program's purpose is to reduce the harms of uncontrolled diabetes, and those harms, such as kidney disease, vision loss and amputation, fall most heavily on patients whose blood sugar is highest. Favoring the worst off directs a scarce benefit to the people with the most to lose, which is one common reading of the principle of justice in health care (Beauchamp & Childress, 2019). Second, the criterion uses a measure already in every applicant's record, so it is objective and does not require staff to judge who deserves help. Third, the lottery treats applicants with equal need as equals and removes any temptation to favor patients staff know or like.

This combination follows the advice of Persad et al. (2009) that allocation should combine principles rather than rely on one. It is also consistent with guidance developed during the COVID-19 pandemic, which emphasized maximizing benefits, giving priority to the worst off and using random selection among people with similar prognosis (Emanuel et al., 2020).

Answering the Strongest Rival

The strongest objection comes from the benefit criterion. Patients with the highest A1c may also face the hardest lives, unstable housing, shift work or depression, and may be less likely to attend all 12 sessions. Giving them the places could produce worse program results and fewer total patients helped.

There are two answers. The first is empirical: patients with higher starting A1c often have more room to improve, so even partial attendance may produce meaningful benefit. The second is about purpose: a program judged only by its average results will always be tempted to select easy patients, which reproduces the health gaps a health center exists to narrow. The center can address attendance directly, for example by offering evening sessions and transportation vouchers, rather than by excluding the patients who most need help.

Handling Dropouts and Keeping the Process Transparent

The center should also decide in advance what happens if a selected patient drops out in the first two weeks. A simple rule works: the place goes to the next applicant on the list produced by the same criterion, so that the allocation stays consistent and nobody can be moved up informally. If a patient drops out later, the place should not be refilled, because a newcomer would have missed too much of the program to benefit. Writing these rules down before selection begins protects staff from pressure and protects applicants from the suspicion that places were filled by favor. The full list, with names removed, could be kept on file so the center can show how each place was filled if anyone asks.

What the Criterion Costs

The criterion has costs, and they fall on real people. Applicants with an A1c of 8.5% will mostly be excluded, though their diabetes is also not well controlled, and some of them would benefit greatly. Applicants who applied first and waited longest will feel the system ignored their effort. And patients with well-controlled diabetes who wanted education to stay that way will almost certainly not be chosen this cycle. To reduce these costs, the center should offer the excluded applicants something: a group education session led by a nurse, written materials and first priority, by the same rules, for the next cohort. It should also explain the criterion openly to all 60 applicants, because a fair rule that is kept secret will look like favoritism.

References

Beauchamp, T. L., & Childress, J. F. (2019). Principles of biomedical ethics (8th ed.). Oxford University Press.

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

Persad, G., Wertheimer, A., & Emanuel, E. J. (2009). Principles for allocation of scarce medical interventions. The Lancet, 373(9661), 423-431. https://doi.org/10.1016/S0140-6736(09)60137-9