Abstract: Methods, systems, and apparatus, including computer programs encoded on a computer storage medium, for a computing system that identifies information about a trial program. The information is related to healthcare data for a subset of providers. The system identifies a provider based on analysis of the information and the healthcare data and provides trial program criteria for analysis at a provider system. The provider system has access to healthcare data for subjects that interact with the provider. The computing system generates data indicating a result of screening each subject by analyzing the trial program criteria against healthcare data for each subject and receives data for a selection of a subject from the provider system. The selection is determined using screening data for the subject. A referral network of the system provides the screening data for access and analysis at an investigator system.

Abstract: Methods, apparatus, systems and articles of manufacture are disclosed to manage care pathways and associated resources. An example apparatus includes a system monitor to coordinate a patient data analyzer and a care pathway processor to at least: identify a first patient record associated with a first care pathway; and identify a second patient record that is not on the first care pathway but should be on the first care pathway. The example apparatus includes a graphical user interface including information regarding, in a first area, the first patient record associated with the first care pathway and, in a second area, the second patient record that should be associated with the first care pathway.

Abstract: A document requesting unit (150) and a document suggestion unit is provided. The document requesting unit is configured for retrieving documents to assist a first user in a first clinical task on patient data of a first patient, the document requesting unit (150) comprising a context builder (157) configured to determine a first context (142) based on a description of the first clinical task and/or the patient data of the first patient, a database unit (152) configured to retrieve a document (122) selected by the user from an electronic document database (120), and a tagging unit (156) configured to tag the selected document (122) with the first context to enable a document suggestion unit (250) to suggest the selected document (122) during a second clinical task on patient data of a second patient.

Abstract: Methods, apparatus, and systems are disclosed to improve selection of medical treatment. An example apparatus includes a user interface to receive health information for a patient and a data analyzer to access historical patient information stored in a database, and determine a condition based on comparing historical patient information stored in a database to the health information for the patient. The example apparatus includes a machine learning engine to recommend a treatment plan, including: a data analytic algorithm server to determine success rates of the treatment plan for the condition; and a model generator to generate a patient model, wherein the patient model predicts effects of the treatment plan. The example apparatus includes a communications interface to facilitate scheduling an appointment with a clinician.

Abstract: Systems and methods for automatically populating a post-operative report of a surgical procedure are disclosed. A system may include at least one processor configured to implement a method including receiving an identifier of a patient, an identifier of a healthcare provider, and surgical footage of a surgical procedure performed on the patient. The method may include analyzing frames of the surgical footage to identify phases of the surgical procedure based on interactions between medical instruments and biological structures and, based on the interactions, associate a name with each phase. The method may include determining a beginning of each phase and associating a time marker with the beginning of each phase. The method may include populating a post-operative report with the patient identifier, the names of the phases, and time markers associated with the phases in a manner that enables the health care provider to alter the post-operative report.

Abstract: Generally discussed herein are systems, apparatuses, and methods that relate to altering patient care and increasing the efficacy of medical diagnostics. A standard deviation of deltas (SDD) plot of analyte measurements can provide insights into the medical diagnostics. One or more SDD plots can be used to help diagnose a patient and alter a patient's care depending on the relation of the patient's own SDD plot characteristics relative to the one or more SDD plots. Any or all of the analysis can be automated, such as to reduce human interaction with process.

Abstract: Mechanisms are provided for determining values to associate with medical conditions of a patient. A patient assessment is received that comprises a natural language question and a corresponding answer, about a patient, provided in response to the question. Cognitive natural language processing is performed on the patient assessment to extract features from the natural language question and corresponding answer. The extracted features are evaluated within a context of a pre-existing electronic medical record of the patient. A value for a medical condition of the patient is determined based on results of the evaluation and stored in the electronic medical record for the patient.

Abstract: Patient treatment may be optimized using Recurrent Neural Network (RNN) based state simulation and Reinforcement learning (RL) techniques to simulate future states and actions. A RNN state simulator and a RL action generator may be trained using patient data such as historical states and actions. The RL action generator may be optimized by applying the RNN state simulator to simulating future states and applying the RL action generator to generate recommended actions based on the simulated future states. This process may be iteratively performed until a computational convergence is reached by the RL action generator which may indicate that the RL action generator has been optimized. A patient state may be fed into the optimized RL action generator to generate an optimal recommended treatment action.

Abstract: A medical classification code modeling system and method that generates visual maps in response to user queries, where the visual maps represent combinations of modifiers of an interface terminology that, taken together, map to medical classification code elements. The system and method may present multiple visual maps on the same display to permit visual analysis of multiple mapping revisions or versions. The system and method further may integrate into an electronic health record such that the user's ultimate selection of a mapping results in the corresponding medical classification code being inserted into the record of a patient at an appropriate location, such as on the patient's problem list.

Abstract: A computer-implemented method may be provided for analyzing and disseminating medical information. The method may include steps performed by one or more processors including, receiving a plurality of patient medical data; aggregating the plurality of patient medical data, wherein access to patient private health information is restricted; receiving a query for medical information; analyzing the aggregated medical data based on the query; producing a result of the query based on the analyzing of the aggregated medical data; and transmitting the result of the query.

Abstract: A system for facilitating interoperability among health care modules includes an interface configured to receive a first electronic record from a first health care module. The first electronic record has a first data structure. The system also includes a processor communicatively coupled to the interface. The processor is configured to analyze the first electronic record having the first data structure, and, based on the analysis, extract a portion of data from the first electronic record. The processor further creates a second electronic record using the portion of data from the first electronic record, where the second electronic record has a second data structure. The second data structure is configured to be compatible with a second health care module. The interface is further configured to transmit the second electronic record for display to the second health care module.

Abstract: Described herein are systems and methods for generating health or risk parameter reference intervals for use in healthcare or any other application of risk/attribute measurement. The reference intervals generated by the systems and methods described herein are based on direct analysis and evidence-based models of human and/or other living organism data from a population of individuals including shared feature(s) and outcome data such as vital status. The direct analysis and evidence-based models of human and/or other living organisms data utilize shared common risk parameter feature(s) and outcome data and identify relationships of two or more health or risk parameters relative to one another. These methods also apply to the measurement of risk and/or other attributes of any living organism or nonliving objects.

Abstract: Systems and methods for communicating orthodontic treatment information are disclosed herein. The methods may include methods of delivering an informational resource corresponding to an orthodontic treatment instruction to a patient of an orthodontist, and optionally to a caretaker of the patient and a dentist of the patient. The methods may further include delivering receipt information to the orthodontist and/or the caretaker, wherein the receipt information is indicative of an interaction between the patient and the informational resource. The systems may include electronic devices and interfaces associated with the orthodontist, the patient, the caretaker, and the dentist that may facilitate the communication methods.

Abstract: A method of processing EEG data. The EEG data for a user is received at a server from one or more EEG input devices. The EEG data from the user is characterized utilizing the server to generate the characterized data. The characterized data is categorized utilizing the server. The characterized data is analyzed to generate analyzed data. The analysis includes at least comparing the analyzed data against control data. A service response is generated utilizing the server to process the analyzed data.

Abstract: The present disclosure relates to a patient centric system and platform that enables a customized analysis of a patient's health conditions for assessing appropriateness of an ordered treatment. In one aspect, patient centric analysis platform includes memory having computer-readable instructions stored therein and one or more processors. The one or more processors configured to execute the computer-readable instructions to receive, from a terminal, patient identifying information of a patient; receive, from the terminal, an initial treatment order for the patient; retrieve patient specific information and treatment specific information; generate a numerical assessment of the initial treatment order based on the patient specific information and the treatment specific information, the numerical assessment indicating a safety level of the initial treatment order; and communicate the numerical assessment to the terminal.

Abstract: A computer-assisted method to timely provide notifications of treatments, the method including receiving de-identified longitudinal medical records, receiving notification data, identifying anonymized patients that received the treatment, identifying notifications for the treatment that were received by the recipients, determining, for each of the identified notifications, whether the recipient is an anonymized patient identified as having received the treatment, determining, for each of the identified notifications for the treatment determined to be received by a recipient that is an anonymized patient identified as having received the treatment, a time relationship between the time when the treatment was received by the anonymized patient and the time that the notification was received by the recipient that is the anonymized patient, and determining, for each of the anonymized patients that received the treatment, associations between one or more time relationships for notifications received by the anonymiz

Abstract: Embodiments include method, systems and computer program products for providing medication-related feedback. Aspects include receiving medication information for a patient. Aspects also include receiving a biological, behavioral, or environmental output from a sensor. Aspects also include determining, based upon the biological, behavioral, or environmental output and the medication information for the patient, whether a medication dose is needed. Aspects also include, based on a determination that the medication dose is needed, generating an alert.

Abstract: This disclosure relates to an automated and comprehensive communications and monitoring platform that enables conditions to be monitored at one or more sites, and which includes a set of tools for preventing, mitigating and/or remediating occurrences of unfavorable conditions, such as hazardous biological/chemical conditions or device failures at the sites. Historical data aggregated by the platform is utilized to predict occurrences of hazardous or unfavorable conditions. Automated remediation actions are triggered to cure or prevent the occurrences of the hazardous or unfavorable conditions.

Abstract: Various embodiments of the present disclosure comprise methods, apparatus, systems and software for use in implementing acceptance and commitment therapy (ACT). The methods include notifying or reminding users to track completion of exercises, and to track and/or monitor awareness of urges and the number of times the user allows urges to pass. Also, physical sensors can be employed to help monitor the user's detrimental behaviors and to send notifications or reminders to the user to perform exercises or track urges.

Abstract: An optimization system optimizes groups of providers for a given population of users. The optimization system includes various engines such as a source interface engine, selection engine, and group score engine. The source interface engine receives information to be used in constrained optimization from server computers and stores the information in databases. The selection engine selects groups of providers from a set of all available providers. The group score engine generates a score for each group of providers. The selection engine continues to iteratively select groups of providers to minimize the generated score. The selection engine can use hard constraints, for example, requiring that a certain type of provider be included in all selected groups, or soft constraints, for example, requiring that a certain number of providers be included based on a size of the given population.