Abstract: The following relates to an improved system and method for displaying medical information. In one aspect, a root concepts circle including at least one clinical concept category is displayed. A children concept ring, which may be built based on a user-selected clinical concept category of the at least one clinical concept categories, may surround or partially surround the root concept circle. A ring fashion timeline may also be displayed, and may be built based on a user-selected clinical concept of the at least one clinical concepts.

Abstract: A computer (10) displays an information data set (22) in a viewport (30) using a first type of rendering (42) when the viewport is in a first viewport geometry space (52), and displays the information data set in the viewport using a second type of rendering (44) when the viewport is in a second viewport geometry space (54). The viewport may be resized by a user. While displaying the first type of rendering, resizing of the viewport into the second viewport geometry space is detected and in response the computer transitions to displaying the information data set using the second type of rendering. Likewise, while displaying the information data set in the viewport using the second type of rendering, resizing of the viewport into the first viewport geometry space is detected and in response the computer transitions to displaying the information data set using the first type of rendering.

Abstract: A system includes a computing system (102) a processor (104) that performs the following: establish syntactic interoperability with a plurality of healthcare data sources (114); extract health care episode concepts from the sources, including concepts from a radiology report; classify the extracted concepts into cognitive classes, wherein the cognitive classes include: observation; evaluation; instruction and action; map the classified concepts to terminologies/ontologies; create a linked list of the events, including observations, evaluations, instructions and actions, to be contextualized; reconstruct the events from the linked list using time and location to order the events in a predetermined way; receive a query, including a unique identifier; for the events; construct, in response to the query, an output in electronical format that includes the events organized according to the cognitive classes and indexed by time from the reconstructed events; and transmit the constructed output via a network to a rem

Abstract: The present disclosure pertains to modeling free-text clinical documents into a hierarchical graph-like data structure based on semantic relationships among clinical concepts present in the documents. A method comprises parsing, identifying, and annotating clinical terms within free-text clinical documents. This is accomplished by storing identified clinical terms in a concept node. The concept node is a data structure that has a set of properties to categorize stored concepts. Clinical concepts of free-text clinical documents are classified into clinical event classes. The free-text clinical documents include clinical terms that were associated with clinical concept categories. Classifying clinical concepts includes organizing clinical text-free documents into sections that describe a specific aspect of the clinical text-free documents that include one or more of clinical, technical, or administrative aspects of the documents.

Abstract: A health care performance assessment apparatus (10) includes at least one processor (16, 20, 22, 24) programmed to: collect information associated with medically-related events from a plurality of databases; group the collected information associated with medically-related events into episode of care (EOC) data structures wherein each EOC data structure contains the collected information for a single EOC treating a medical condition or providing a medical procedure to a single patient; store the EOC data structures in an EOC repository (18); group EOC data structures having a chosen commonality into at least one cohort; and calculate at least one key performance indicators (KPIs) for the cohorts. A display (2) is configured to display the KPIs for at least one selected cohort.

Abstract: A computer (10) displays an information data set (22) in a viewport (30) using a first type of rendering (42) when the viewport is in a first viewport geometry space (52), and displays the information data set in the viewport using a second type of rendering (44) when the viewport is in a second viewport geometry space (54). The viewport may be resized by a user. While displaying the first type of rendering, resizing of the viewport into the second viewport geometry space is detected and in response the computer transitions to displaying the information data set using the second type of rendering. Likewise, while displaying the information data set in the viewport using the second type of rendering, resizing of the viewport into the first viewport geometry space is detected and in response the computer transitions to displaying the information data set using the first type of rendering.

Abstract: The present disclosure pertains to modeling free-text clinical documents into a hierarchical graph-like data structure based on semantic relationships among clinical concepts present in the documents. A method comprises parsing, identifying, and annotating clinical terms within free-text clinical documents. This is accomplished by storing identified clinical terms in a concept node. The concept node is a data structure that has a set of properties to categorize stored concepts. Clinical concepts of free-text clinical documents are classified into clinical event classes. The free-text clinical documents include clinical terms that were associated with clinical concept categories. Classifying clinical concepts includes organizing clinical text-free documents into sections that describe a specific aspect of the clinical text-free documents that include one or more of clinical, technical, or administrative aspects of the documents.

Abstract: Methods and apparatus for assigning patients to hospital beds to prevent the spread of healthcare-associated infection (HAI). HAI is a major patient safety problem worldwide, affecting hundreds of millions of individuals each year. By considering probabilities that patients will acquire and/or spread infections, embodiments of the present invention can reduce the spread of HAI by selectively assigning patients to beds within healthcare institutions.

Abstract: A system and method perform the steps of retrieving clinical events for a patient; identifying the clinical events relevant to a clinical guideline for an incidental finding, wherein the incidental finding is an imaging observation tangential to the primary goal for performing an imaging exam; parsing out clinical concepts in the clinical events; clustering the clinical concepts according to the clinical guideline for the incidental finding; creating a longitudinal health patient profile by storing clustered clinical concepts for the identified clinical events relevant to the incidental finding clinical guideline; determining whether to define a new imaging finding from a current imaging exam as an incidental finding; and making follow-up recommendations for the defined incidental finding based on the longitudinal health patient profile and relevant patient clinical information.

Abstract: The following relates to an improved system and method for displaying medical information. In one aspect, a root concepts circle including at least one clinical concept category is displayed. A children concept ring, which may be built based on a user-selected clinical concept category of the at least one clinical concept categories, may surround or partially surround the root concept circle. A ring fashion timeline may also be displayed, and may be built based on a user-selected clinical concept of the at least one clinical concepts.