Early cost prediction and risk identification

A system comprising:

• a training module configured to build, based on a set of historical training data for a set of training members, a trained configurable predictive pipeline;
• a feature identification module configured to identify, based on empirical testing of the set of historical training data, a set of member-level features;
• a prediction module configured to generate, using the trained configurable predictive pipeline and a set of historical test data for the set of testing members, a set of predictive data for each member in the set of testing members, wherein the predictive data comprise predictions for each of the set of member-level features;
• and
• a reporting module configured to:
• generate, for the set of predictive data for each member in the set of testing members, a predictive report, wherein the predictive report comprises the set of predictive data and a set of explanations, and wherein the set of explanations provides details for each prediction in the report.

A computer program product comprising a computer readable storage medium having program instructions embodied therewith, wherein the computer readable storage medium is not a transitory signal per se, the program instructions executable by a processor to cause the processor to perform a method comprising:

• building, based on a set of historical training data for a set of training members, a trained configurable predictive pipeline;
• identifying, based on empirical testing of the set of historical training data, a set of member-level features;
• generating, using the trained configurable predictive pipeline and a set of historical test data for the set of testing members, a set of predictive data for each member in the set of testing members;
• and
• generating, for the set of predictive data for each member, a predictive report, wherein the predictive report comprises the set of predictive data and a set of explanations, and wherein the set of explanations provides details for each prediction in the report.

A computer-implemented method for generating predictive healthcare cost data, the method comprising:

• identifying, based on empirical testing of a set of historical patient training data for a set of training members, a set of member-level features;
• generating, using a trained configurable predictive healthcare cost pipeline and a set of historical patient test data for a set of testing members in a testing set, a set of predictive data for each member in the set of testing members;
• and
• generating, for the set of predictive data for each member, a predictive report, wherein the predictive report comprises a set of medical risk factors, a predictive risk score, and a set of predictive costs.

A system for generating predictive healthcare cost data comprising:

• a computer readable storage medium with program instructions stored thereon;
• and
• one or more processors configured to execute the program instructions to perform a method comprising:
• building, based on a set of historical patient training data for a set of training members, a trained configurable predictive healthcare cost pipeline, wherein the set of training members are a set of members enrolled in a particular health insurance program;
• identifying, based on empirical testing of the set of historical patient training data for the set of training members, a set of member-level features;
• generating, using the trained configurable predictive healthcare cost pipeline and a set of historical patient test data for a set of testing members in a testing set, a set of predictive data for each member in the set of testing members;
• and
• generating, for the set of predictive data for each member, a predictive report, wherein the predictive report comprises at set of medical risk factors, a predictive risk score, and a set of predictive costs.