Abstract: A healthcare system that includes a form engine configured to generate an interface specifically for individuals with differing cognitive abilities (e.g., children). The interface includes form fields and visual elements to receive health care and feedback data for storage in persistent data store. The visual elements can relate to requests for information and can also relate to responses to those requests. The visual elements are mapped to form fields. The healthcare system automatically populates field values corresponding to the form fields based on detected interactions with the visual elements at the interface.

Abstract: A healthcare information system for providing near-real or real-time contact tracing is provided comprising: a position data receiver unit configured to receive position data related to one or more entities associated with a healthcare facility; a contextual profile management unit configured to utilize received position data to generate, maintain or update one or more contextual profiles, each of the one or more contextual profiles corresponding to each of the one or more entities. Devices, systems and methods are provided related to the use of near-real or real-time contact tracing in applications including infection control, developing infection pathways, among others.

Abstract: Systems and methods for integrating data from various sources are provided, the system comprising a processor and a non-transitory computer readable storage medium storing instructions which when executed by the processor, configure the processor to filter and transform data received from one or more health care organizations by: receiving one or more data sets; developing one or more rules based upon the one or more data sets; and applying the one or more rules to the one or more data sets to detect the presence of one or more data elements.

Abstract: Embodiments described herein relate to apparatuses and methods for incident prediction alerts for transmission to a health care organization system by applying rules to data sets. Each rule may define a set of data elements linked to an incident, and a processor may detect one or more sets of data elements in the data sets. The processor may normalize the data feeds, generate rules on historical data, generate prediction alerts by applying rules to near-real time data feeds, train to update rules, validate and error check rules, remove statistical noise, generate visualizations for the data feeds, and receive input and feedback data.

Abstract: Embodiments described herein relate to apparatuses and methods for incident prediction alerts for transmission to a health care organization system by applying rules to data sets. Each rule may define a set of data elements linked to an incident, and a processor may detect one or more sets of data elements in the data sets. The processor may normalize the data feeds, generate rules on historical data, generate prediction alerts by applying rules to near-real time data feeds, train to update rules, validate and error check rules, remove statistical noise, generate visualizations for the data feeds, and receive input and feedback data.