C/hca, Inc.

Hca Holdings, Inc.

Jonathan Perlin

William Michael Gregg

Jim Najib Jirjis

Thomas Andrew Doyle

Paul Martin Paslick

Edmund Stephen Jackson

Christian Krayer

Paul Brient

Sarah Hume Buta

Erin S Jospe

Umesh P Phirke

Karl Bradley Kehler

Deborah Reiner

Christopher Wobensmith

Victoria Weaver

Alan Scott

Paul Currie

Ravi S Chari

Vincent Doyle, Iii

Steven V Manoukian

Wesley Boles

Christopher Mason

Jane Englebright

Brian Freeman

Victoria Samples

David Fowler

Milind Madhukar Borkar

Stephanie Fulbright

Gabriel O Perez

Michael A Houston

Jeffrey Cuthbert

Eric Matt

Amit Chaudhri

William Dan Roberts

Mitchel Davis

Jody Miller

Leslie Werhane

Whitney Staub-Juergens

Tabatha Cooper

Willie Ford

Aaron Montlary

Sammie Mosier

Robert Rochford

Bryan Sisk

Todd Shafer

Clarence Robert Foster

David Wedemeyer

Jeffrey Scott Smith

In some examples, systems, methods, and devices are described that generate contextual suggestions for patients. Generation of the contextual suggestions is triggered by certain events performed by a medical professional with respect to a patient (e.g., updating a patient record). The contextual suggestions are related to addressing health conditions of the patient and represent tasks or considerations which the medical professional should be made aware. The contextual suggestions are generated in a way that is considerate of patient context, medical professional context, and contexts of similar patients. The contextual suggestions can be presented to the medical professional for selection and execution.

Contextual assessment of current conditions

In some examples, unstructured data is evaluated using a natural language processing model to output a set of subjective indicators. These subjective indicators are scored using a predictive model to determine whether a dependent user has or is likely to develop a particular condition such as a cellular abnormality.

Signal processing for making predictive determinations

Systems, methods, and machine-readable media to orchestrate process-performing resources and process protocols particularized to individual resources and loads are provided. Data changes in the data streams may be detected and identified. Data items from the data streams may be aggregated. Protocols that include parameter constraints according to specifications of process performance and/or operation performance may be identified. Operation-performing resources may be modeled with metrics being a function of protocols and consolidated data portions. A composite may be created that specifies a configuration a subsystem. The composite may be transmitted, and allocation of operation-performing resources to perform the defined process in accordance with the selected protocols may be controlled.

Systems and methods for multi-tier resource and subsystem orchestration and adaptation

In some examples, user models are generated to represent experience of users with respect to their roles. Models that represent conditions are also generated. As part of generating a support element for a particular user, a triggering event is detected (e.g., an update to a user record), a condition is identified, a condition model and a user model are compared to identify a condition preparedness score. This score is used to generate the support element, which is shared with a user device of the user.

Data derived user behavior modeling

A method and system for initiating message listening and routing message content to authorized user devices is disclosed. For a second user device to receive notifications regarding records of a first user, the second user device provides information identifying the first user to a notification service. The notification service verifies the identifying information. The notification service initiates one or more listeners to listen for messages flowing over a messaging bus that are relating to the first user. Once a message is identified, at least a portion of the message is used to generate a notification that may be sent to the second user device.

Providing notifications to authorized users

In some examples, authorized user profiles and generic models are generated using historical interaction data of authorized users. The authorized user profiles provide an experience profile for authorized users. The generic models are data models used to model authorized user actions. The authorized user profiles and generic models are used to generate support elements. The support elements are presented to authorized users and feedback is collected. Based on the feedback, the authorized user profiles and generic models are updated.

Authorized user modeling for decision support

Systems, methods, and machine-readable media to orchestrate process-performing resources are disclosed. Collected data items may correspond to assignments of process-performing resources, and device interactions or data changes that correspond to process or operation performances, conditions of loads. Data items may be processed to identify and map data portions to process-performing resources. Content nodes may be created and linked in a network of content nodes configured according to a computational model that comprises hierarchical orderings of the content nodes using a network data structure. A graphical representation may be formatted to represent the network data structure of the content nodes linked in the network. Metrics of resource performance corresponding to content nodes may be determined. The computational model may be trained using the metrics to create an adapted computational model. Adapted content nodes may be created according to the adapted computational model.

Systems and methods for multi-tier network adaptation and resource orchestration

In some examples, structured and unstructured data is evaluated using one or more predictive models to determine whether a dependent user is at risk for a certain condition. In other examples, structured and unstructured data is evaluated using one or more predictive models to determine a contact plan for contacting dependent users regarding follow-up appointments related to release of the dependent user.

Data processing for making predictive determinations

Growing community of inventors

Nashville, TN, United States of America

Jonathan Perlin