Patent ID: 11955244
Assignee: OPTUM SERVICES (IRELAND) LIMITED
Field: Medical technology (Instruments)
Classification: CPC G | IPC G

Claim 0:
1. A computer-implemented method for generating a predicted risk measure for a first predictive entity, the computer-implemented method comprising:
generating, using one or more processors, by utilizing a risk determination machine learning model and based at least in part on one or more hidden features of the first predictive entity, the predicted risk measure, wherein:
(i) the risk determination machine learning model is generated based at least in part on a ground-truth risk measure for each ground-truth predictive entity in a ground-truth subset of a plurality of candidate predictive entities,
(ii) the first predictive entity is among the plurality of candidate predictive entities but is outside of the ground-truth subset,
(iii) each ground-truth predictive entity is associated with a prediction time horizon and a per-horizon historical claim set within the prediction time horizon,
(iv) each per-horizon claim count of a per-horizon claim set for a ground-truth predictive entity satisfies a per-horizon claim count threshold,
(v) each prediction time horizon for a ground-truth predictive entity is determined based at least in part on a primary event associated with the ground-truth predictive entity,
(vi) each primary event for a ground-truth predictive entity is determined based at least in part on a diagnosis timestamp for a recipient entity associated with the ground-truth predictive entity, and
(vii) each ground-truth risk measure for a ground-truth predictive entity is determined based at least in part on the per-horizon claim set for the ground-truth predictive entity; and

initiating, using the one or more processors, the performance of one or more prediction-based actions based at least in part on the predicted risk measure.