We have long recognized that triage systems designed for access maximization may have different algorithms for what to do with a case than those designed for poverty minimization, as those deployed by community-based advocacy organizations might choose to develop.
One factor that might be taken into account in such a poverty minimization algorithm might be the risk that the failure to provide services would result in a person falling deeper into poverty, or that the provision of services might result in removing someone from poverty. Moreover, both long and short term risk might be considered.
Now there comes a tool that, while using only the factors of race, education, marital status and age, is designed to help calculate the risk of being in poverty in the short, medium, or long term. The tool is described by its developers here. Maybe one day it might be converted into an API (applications programming interface) that would show the risk of falling into poverty for people being served by various agencies or systems, to the extent desirable and appropriate.
The current tool, while far from a triage tool, or even anything like the complex kind of predictor that might be needed for a triage component, already highlights the long term possibilities of data to take such factors into account and to make decisions based on inputing those factors into algorithms. The tool may also help us think about the complexities and difficulties that such systems would raise.