Abstract: The invention discloses a system configured for assessing performance data, the system comprising a memory comprising instruction data representing a set of instructions; and a processor configured to communicate with the memory and to execute the set of instructions. The set of instructions, when executed by the processor, cause the processor to: acquire a plurality of performance data records associated with a performance indicator; classify each performance data record according to the performance indicator; identify a plurality of variables in the performance data records that contribute to the classifications; determine, based on the plurality of variables, a plurality of observations relating to the performance indicator and at least one variable of the plurality of variables; and deliver the plurality of observations for presentation to a user. A method is also disclosed.

Abstract: The invention discloses a system configured for assessing performance data, the system comprising a memory comprising instruction data representing a set of instructions; and a processor configured to communicate with the memory and to execute the set of instructions. The set of instructions, when executed by the processor, cause the processor to: acquire a plurality of performance data records associated with a performance indicator; classify each performance data record according to the performance indicator; identify a plurality of variables in the performance data records that contribute to the classifications; determine, based on the plurality of variables, a plurality of observations relating to the performance indicator and at least one variable of the plurality of variables; and deliver the plurality of observations for presentation to a user. A method is also disclosed.

Abstract: An electronic clinical decision support (CDS) device executes (54) clinical decision rules (8) using a computer (10, 12) to generate predicted values of clinical conclusions (58) for a current patient based on values for the current patient of preconditions of the clinical decision rules (52). The rules are also executed (36) to generate predicted values of the clinical conclusions (38) for past patients based on values for the past patients of the preconditions (32) retrieved from an Electronic Medical Record (EMR) (20). Rule summary scores (42) are generated (40) based on comparisons of “ground truth” values of the clinical conclusions (34) for the past patients retrieved from the EMR with the predicted values of the clinical conclusions for the past patients. A display (14) shows the predicted values of the clinical conclusions and the corresponding applied rules for the current patient ranked at least in part by the rule summary scores.