Abstract: A clinical insight and decision support visualization tool includes a data ingestion logic module that automatically accesses, in real-time, electronic health data of a plurality of trauma patients being treated by a care team at a healthcare institution. The tool further includes a data analysis module that automatically applies at least one predictive model to analyze the processed patient data and determine a current mortality risk score value for each patient, and a user interface module that presents real-time and historical information for each trauma patient including a current mortality risk score value, a categorization of the current mortality risk score value, top contributors to the current mortality risk score value and their respective values, and a trend plot of historic mortality risk score values.

Abstract: A community vulnerability index dashboard includes a data ingestion logic module configured to automatically receive real-time and non-real-time data from a variety of sources including education agencies, law enforcement, health services agencies, healthcare agencies, medical insurance agencies, housing and transportation agencies, childcare licensing agencies, and non-emergency citywide services. The dashboard includes a data processing module that extracts and process the ingested data, and a data analysis logic module that analyzes the processed data to determine values for indicators and an overall vulnerability index value based on the values of the plurality of indicators to provide insight into the lives of residents living in a community on a block group level. The dashboard includes a data presentation dashboard interface to display an interactive choropleth map of the overall vulnerability index and indicator values on a block group level for the community of interest.

Abstract: A machine learning system for healthcare applications comprises a data ingestion pipeline configured to automatically receive patient data including stored data from an EHR database and real-time data from a plurality of data sources, the data including, EHR records, claims data, and social determinants of health data; a data processing module configured to clean, extract, and process the received patient data; at least one predictive model configured to analyze the cleaned and processed data and determine a risk score for each patient; a configuration file defining the predictive model execution parameters; a tuning module configured to adjust parameters of the predictive model, including variables, thresholds, and coefficients; a retraining module configured to make further adjustments of the predictive model to remove inherent data biases; and a dashboard and reporting module configured to present the risk score to a patient care team.

Abstract: A patient care plan system includes a repository of patient data including real-time clinical and non-clinical data that include data generated as a result of at least one treatment received by the patient provided by an outside service provider; at least one predictive model configured to analyze clinical and social factors derived from the patient's data to determine a risk score associated with the particular medical condition; a patient care plan module configured to selectively extract data from the patient's data to generate a targeted patient data summary including data that are indicative of quality metrics associated with the at least one treatment received by the patient, and organize and format the extracted data into a patient care plan; and a payment interface module configured to transmit the patient's care plan to a payor in exchange for payment for the at least one treatment received by the patient.