Abstract: In one embodiment, a computer-implemented method, comprising: receiving information from plural patients, the information from each of the plural patients comprising one or more items recorded over a predefined period of time; formatting the items for use in a machine learning algorithm, wherein the formatting comprises: associating each of the one or more items with a respective word; forming a sentence for each of the plural patients from the words; and transforming the sentences for the plural patients into a numerical matrix, wherein the matrix comprises one row per patient and one column per word, each word weighted by occurrence; training models according to the machine learning algorithm based on the formatted items of the plural patients; determining if a first patient should have a hierarchical condition category code by applying one or more formatted items of the first patient to the trained models; and providing a notification of any suspect hierarchical condition category codes based on the applic

Abstract: In one embodiment, a quality measure analysis system that visually presents a quality measure as a tree structure where anomalies inpatient care or processes are indicated to a user at one or more nodes of the tree to trigger additional investigation.