As the number of enrollments in Connect for Health has come in lower than expectations some of the focus has shifted to the future sustainability of the organization. While some initial projections released last week show that even on the reduced enrollment figures there may not cause a dramatic increase in the administrative fees charged to carriers.
More problematic is the lack of dynamism in the projections. A lower enrollment number implies a higher admin fee. However, the higher admin fee is not reflected in a higher premium in the lower enrollment scenario which raises the question of whether the lower enrollment projection captures the possibility of death spiral at the lower enrollment leads to increasing admin fee leading to lower enrollments.
More importantly, the fixed operational and technical budget are never varied. One of the most important questions facing the current board is what types of projects should be green lighted to increase enrollment and decrease cost. Without some linkage between costs and enrollments it implies that enrollment is completely out of management’s hands.
The lack of modeling around the link between costs and enrollments also sidesteps difficult but important questions around the more fundamental nature of Connect for Health. What is a realistic customer acquisition cost Connect for Health? What is the customer retention cost for eligibility redetermination and re-enrollment? What happens if the cost of outreach or customer acquisition for a substantial number of eligible consumers is too high for what is seen as an acceptable revenue basis?
In many cases it is not the projection but the modeling that leads to the projection that are the key value of projection. This modeling leads to key assumptions that initially be hidden. The modeling also creates a great opportunity to build in early feedback cycles that enable a management team to alter outcomes.
Over the next few weeks I’ll be building some of the more detailed modeling to create more complete Connect for Health sustainability projection.