Systems, methods, and media are provided for predicting fall risk for a post-acute care patient. Patient data for the post-acute care patient is received. Features from the patient data are extracted. The features include one or more polypharmacy features. Other features may include lab or vital features. Based on the features extracted from the patient data, a prediction of the post-acute care patient suffering a fall within the future is generated using one or more machine learning models. The one or more machine learning models may be trained using one or more of binary features, continuous features, categorical features, free-text features, or a combination thereof. An action is initiated based on the prediction of the post-acute care patient suffering a fall. The action is associated with reducing the risk of the patient fall, such adjusting the lighting in the patient's room, for example.
G16H 50/30 - ICT specially adapted for medical diagnosis, medical simulation or medical data mining; ICT specially adapted for detecting, monitoring or modelling epidemics or pandemics for individual health risk assessment
G16H 50/20 - ICT specially adapted for medical diagnosis, medical simulation or medical data mining; ICT specially adapted for detecting, monitoring or modelling epidemics or pandemics for computer-aided diagnosis, e.g. based on medical expert systems
G16H 10/60 - ICT specially adapted for the handling or processing of patient-related medical or healthcare data for patient-specific data, e.g. for electronic patient records
2.
ADVANCED SIMULATION MANAGEMENT TOOL FOR A MEDICAL RECORDS SYSTEM
Systems for testing computing devices of a medical records system using a simulated environment are provided. The simulated environment is generated by identifying transaction traffic over the network, where the transaction traffic comprises messages of different transaction types. A computing device is configured to output a simulated status by extrapolating a performance of the computing devices upon receiving a series of messages indicating the transaction types. The output of the computing device may indicate an error in the simulated environment where the performance of a computing device exceeds a performance threshold. Based on the error indication, transaction traffic can be diverted from the computing device to another computing device having performance capacity.
Methods, systems, and computer-readable media are disclosed herein that create inter-communication capabilities between servers that use technologically diverse and/or incompatible operating systems. Herein, a driver is leveraged to create these inter-communication capabilities by inserting a source server generated message into a table at the target server. The target server automatically executes code in the message and generates results therefrom. The target serer communicates the results to the source server, where the source server again leverages the driver to handle the results.
Methods, computer systems, and computer-storage medium are provided for monitoring, analyzing, and providing reports regarding direct access technologies, for example DirectAccess, VPN, or VPN-like technologies. User activity associated with DirectAccess servers can be filtered by server location to allow administrators to determine which users, and how many users, utilized or are utilizing each DirectAccess server, which can be identified by geographic locations. In some cases, this information can be used to address technical support issues or to determine which resources of an entity may be under- or over-utilized.
Hospital readmissions may be prevented. Readmission is prevented by predicting the probability of a given patient to be readmitted. The probability alone may prevent readmission by educating the patient or medical professional. The probability may be predicted during a patient stay and used to generate a workflow action item to reduce the probability, to warn, to output appropriate instructions, and/or assist in avoiding readmission. The probability may be specific to a hospital, physician group, or other entity, allowing prevention to focus on past readmission causes for the given entity.
G16H 10/60 - ICT specially adapted for the handling or processing of patient-related medical or healthcare data for patient-specific data, e.g. for electronic patient records
G06Q 10/10 - Office automation, e.g. computer aided management of electronic mail or groupware; Time management, e.g. calendars, reminders, meetings or time accounting
G16H 50/30 - ICT specially adapted for medical diagnosis, medical simulation or medical data mining; ICT specially adapted for detecting, monitoring or modelling epidemics or pandemics for individual health risk assessment
G16H 40/20 - ICT specially adapted for the management or administration of healthcare resources or facilities; ICT specially adapted for the management or operation of medical equipment or devices for the management or administration of healthcare resources or facilities, e.g. managing hospital staff or surgery rooms
G16H 50/70 - ICT specially adapted for medical diagnosis, medical simulation or medical data mining; ICT specially adapted for detecting, monitoring or modelling epidemics or pandemics for mining of medical data, e.g. analysing previous cases of other patients
6.
COMPUTER-DECISION SUPPORT FOR PREDICTING AND MANAGING NON-ADHEARANCE TO TREATMENT
Technologies are provided for identifying individuals having a risk of non-adherence to or from a prescribed treatment program; for predicting and the risk, which may be determined as a forecast over a future time span; and evaluating it to further determine or invoke specific actions to mitigate the risk or otherwise improve likelihood of compliance. A singular spectrum analysis (SSA) is utilized to analyze temporal properties of a time series determined from measured or observational data to determine an emergent pattern. Based on this pattern, a risk of non-adherence, including relapse or absconding, over a future time interval by the individual may be determined and utilized to implement an intervening action.
Technologies are provided for identifying individuals having a risk of non-adherence to or from a prescribed treatment program; for predicting and the risk, which may be determined as a forecast over a future time span; and evaluating it to further determine or invoke specific actions to mitigate the risk or otherwise improve likelihood of compliance. A singular spectrum analysis (SSA) is utilized to analyze temporal properties of a time series determined from measured or observational data to determine an emergent pattern. Based on this pattern, a risk of non-adherence, including relapse or absconding, over a future time interval by the individual may be determined and utilized to implement an intervening action.
47
G06N 7/00 - Computer systems based on specific mathematical models
G16H 10/60 - ICT specially adapted for the handling or processing of patient-related medical or healthcare data for patient-specific data, e.g. for electronic patient records
Systems, methods, and storage media are provided that are useful in a computing environment for receiving, modifying, and transforming service level information from database servers and entities in a hosted database environment. Multiple application programming interface (API) calls are made by a database observation system to request information for multiple service level indicators from database servers belonging to multiple different entities. Database observation system receives and aggregates the information for multiple service level indicators from each of the database servers belonging to multiple different entities. The database observation system provides, within a dashboard interface, the aggregated information for each of the multiple service level indicators, individual service level indicator scores, and aggregated service level indicator scores for each of the database servers for each of the multiple entities.
Methods and systems for processing of voice input to identify intents and mapped standard terminologies are provided. Using natural language processing, an intent of a voice input is identified. The intent is utilized to identify a standard terminology that maps to the intent. The standard terminology is utilized to identify information relevant to the standard terminology in a patient's electronic health record.
G10L 15/22 - Procedures used during a speech recognition process, e.g. man-machine dialog
G16H 10/60 - ICT specially adapted for the handling or processing of patient-related medical or healthcare data for patient-specific data, e.g. for electronic patient records
G10L 15/18 - Speech classification or search using natural language modelling
9.
Microbiota activity sensor and decision support tool
An improved decision support tool is provided for detecting, diagnosing, or treating human patient based on detected changes or trends in microbiota-related activity of the patient. The decision support tool determine a longitudinal pattern of relative abundances or diversity levels of microbiota, and subsequently determine the occurrence of alternations or trends, which may indicate or be related to meaningful clinical events, such as a change in condition for the patient. In one embodiment, a joint determination of statistical significance of change and trend is first detected and then utilized to determine an occurrence of clinically meaningful microbiota activity in a patient. The decision support tool may further initiate an intervening action based on a detected change or trend, such as generating an electronic notification, modifying a treatment program, providing a recommendation, automatically allocating health care resources to the patient, or automatically scheduling a consultation with a caregiver.
G16H 20/10 - ICT specially adapted for therapies or health-improving plans, e.g. for handling prescriptions, for steering therapy or for monitoring patient compliance relating to drugs or medications, e.g. for ensuring correct administration to patients
G16H 50/20 - ICT specially adapted for medical diagnosis, medical simulation or medical data mining; ICT specially adapted for detecting, monitoring or modelling epidemics or pandemics for computer-aided diagnosis, e.g. based on medical expert systems
G06F 17/17 - Function evaluation by approximation methods, e.g. interpolation or extrapolation, smoothing or least mean square method
G06F 17/18 - Complex mathematical operations for evaluating statistical data
10.
DYNAMICALLY DETERMINING RISK OF CLINICAL CONDITION
Systems, methods and computer-readable media are provided for facilitating clinical decision support and managing patient population health by health-related entities including caregivers, health care administrators, insurance providers, and patients. Embodiments of the invention provide decision support services including providing timely contextual patient information including condition risks, risk factors and relevant clinical information that are dynamically updatable; imputing missing patient information; dynamically generating assessments for obtaining additional patient information based on context; data-mining and information discovery services including discovering new knowledge; identifying or evaluating treatments or sequences of patient care actions and behaviors, and providing recommendations based on this; intelligent, adaptive decision support services including identifying critical junctures in patient care processes, such as points in time that warrant close attention by caregivers; near-real time querying across diverse health records data sources, which may use diverse clinical nomenclatures and ontologies; improved natural language processing services; and other decision support services.
G16H 50/20 - ICT specially adapted for medical diagnosis, medical simulation or medical data mining; ICT specially adapted for detecting, monitoring or modelling epidemics or pandemics for computer-aided diagnosis, e.g. based on medical expert systems
G16H 50/30 - ICT specially adapted for medical diagnosis, medical simulation or medical data mining; ICT specially adapted for detecting, monitoring or modelling epidemics or pandemics for individual health risk assessment
G16H 10/60 - ICT specially adapted for the handling or processing of patient-related medical or healthcare data for patient-specific data, e.g. for electronic patient records
11.
NATURAL LANGUAGE UNDERSTANDING OF CONVERSATIONAL SOURCES
Methods and systems for natural language processing/understanding of voice conversations are provided. Using natural language processing, a clinical condition is extracted from a voice conversation. A clinical ontology identifies clinical concepts associated with the clinical conditions. The clinical concepts are classified for documentation. The clinical concepts are searched and validated from within an individual's longitudinal record.
G16H 10/60 - ICT specially adapted for the handling or processing of patient-related medical or healthcare data for patient-specific data, e.g. for electronic patient records
12.
PHYSIOLOGIC SEVERITY OF ILLNESS SCORE FOR ACUTE CARE PATIENTS
Systems, methods, and computer storage media are provided for determining a patient's severity of illness score (pSIS) for a patient admitted to an acute care facility. Data corresponding to physiologic components is received from an electronic medical record associated with a patient admitted to an acute care healthcare facility. The physiologic components include vital sign measurements and laboratory tests. Weights are assigned to a minimum, median, and maximum measured values for each vital sign. Weights are assigned to minimum and maximum values for each laboratory test. The weights are derived based on a deviation from normal within a time period. A pSIS is determined by summing the weights. Additional data corresponding to physiologic components may be received from the electronic medical record. The additional data may be utilized to update the weights and determine a patient's updated pSIS that may be utilized to track a progress of the patient.
G16H 50/30 - ICT specially adapted for medical diagnosis, medical simulation or medical data mining; ICT specially adapted for detecting, monitoring or modelling epidemics or pandemics for individual health risk assessment
G16H 10/60 - ICT specially adapted for the handling or processing of patient-related medical or healthcare data for patient-specific data, e.g. for electronic patient records
13.
Maintaining stability of health services entities treating influenza
Systems, methods and computer-readable media are provided for determining and mitigating the aggregate loss risk associated with hospitalization for epidemic or pandemic influenza for health insurers, reinsurers, provider organizations, or public policy-makers. An accurate prediction of this risk may be provided, which may be used to determine parameters for reinsurance underwriting or for issuance and trading of catastrophe bonds (“cat bonds”) or other insurance-linked securities (ILS) and derivatives to lay off substantial amounts of such risk to capital markets investors. In particular, one embodiment uses a novel log-expit transformation of the raw data and non-parametric gradient-boosting machine-learning modeling in order to determine a high-claim right-tail risk. Some embodiments further comprise securitizing epidemic or pandemic influenza acute care health services catastrophe risk.
G16H 50/30 - ICT specially adapted for medical diagnosis, medical simulation or medical data mining; ICT specially adapted for detecting, monitoring or modelling epidemics or pandemics for individual health risk assessment
G16H 50/50 - ICT specially adapted for medical diagnosis, medical simulation or medical data mining; ICT specially adapted for detecting, monitoring or modelling epidemics or pandemics for simulation or modelling of medical disorders
G16H 50/80 - ICT specially adapted for medical diagnosis, medical simulation or medical data mining; ICT specially adapted for detecting, monitoring or modelling epidemics or pandemics for detecting, monitoring or modelling epidemics or pandemics, e.g. flu
14.
SYSTEM AND METHOD FOR PREDICTING THE IMPACT OF SOURCE CODE MODIFICATION BASED ON HISTORICAL SOURCE CODE MODIFICATIONS
Methods, systems, and computer-readable media are disclosed herein that utilizes historical changes made to files and methods in computer programming code to predict related files and methods that may be affected by current and/or future changes made to other files and methods. In aspects, when computer code for a particular method is going to be edited, other methods are identified that were changed in previous editing sessions that also included changes to the particular method. Using scoring techniques for the other methods, a recommendation is provided that details the relative strength of whether the other methods are predicted to be affected by any changes made to the computer code for the particular method that is edited.
Methods, systems, and computer-readable media are disclosed herein for a machine learning engine and rule engine that leverage historical and contextual data to intelligently identify, score, and suggest one or more documents for auto-population of a graphical user interface. The machine learning and rule engine employ vectorization and clustering technique to identify, score, and suggest the most factually accurate and contextually relevant documents as selectable candidates for electronic documentation. Further, the selection, rejection, or modification of the candidate documents are ingested by the machine learning engine and/or the rule engine to update a clustering algorithm and/or to update a relevance scoring algorithm, which are then utilized for subsequent instances.
G16H 10/60 - ICT specially adapted for the handling or processing of patient-related medical or healthcare data for patient-specific data, e.g. for electronic patient records
The technology disclosed relates to generating automated test plan scripts. Repository data associated with a test plan script is received. Source code and test plan solution data corresponding to the repository data are analyzed. For example, the repository data may be analyzed using natural language processing and static code analysis. In some embodiments, test steps of the test plan are performed to generate repository data. A suggestion of a reusable component for a particular test step or test validation is provided for one or more of the test steps. A selection of the suggestion of the reusable component for at least one of the test steps is received. An automated test plan script corresponding to the selection is generated.
Systems and methods for generating and presenting a clinical workforce management interface to assign staff in a clinical setting. The interface may present components including an aggregate patient population profile listing individual patients in a unit, the projected workload capacity the care for those patients represents, and an assignment bar depicting provider assignments for that patient over a designated time period. The interface may likewise present a provider population profile which lists available care providers in a unit, as well as their capacity ratings, skill sets, shifts, or other schedule data characterizing available clinical staff. A charge nurse or other staff manager may view and manipulate the provider-to-patient assignments, for instance by dragging and dropping visual elements to perform assignments. Compliance monitoring functions such as maintaining provider ratios may be automatically performed, and the staff manager may be alerted when ratios or criteria violate limits.
G16H 40/20 - ICT specially adapted for the management or administration of healthcare resources or facilities; ICT specially adapted for the management or operation of medical equipment or devices for the management or administration of healthcare resources or facilities, e.g. managing hospital staff or surgery rooms
G06Q 10/10 - Office automation, e.g. computer aided management of electronic mail or groupware; Time management, e.g. calendars, reminders, meetings or time accounting
G16H 40/63 - ICT specially adapted for the management or administration of healthcare resources or facilities; ICT specially adapted for the management or operation of medical equipment or devices for the operation of medical equipment or devices for local operation
G16Z 99/00 - Subject matter not provided for in other main groups of this subclass
18.
Predicting and preventing caregiver musculoskeletal injuries
Systems, methods and computer-readable media are provided for determining the modality for transferring, lifting, or repositioning (TLR) a human patient in a health care setting contexts. In some cases, a model-based recursive partitioning and Bradley-Terry regression is applied, which may be optionally parallelized so as to determine statistical associations with various factors, such as caregiver attributes, care venue, and patient attributes. One embodiment determines a Bradley-Terry regression model from the recursive partitioning which may be incorporated into a TLR selection decision-support tool or otherwise utilized to identify the optimal modality.
A61B 5/00 - Measuring for diagnostic purposes ; Identification of persons
A61G 7/00 - Beds specially adapted for nursing; Devices for lifting patients or disabled persons
G16H 50/70 - ICT specially adapted for medical diagnosis, medical simulation or medical data mining; ICT specially adapted for detecting, monitoring or modelling epidemics or pandemics for mining of medical data, e.g. analysing previous cases of other patients
19.
Clinical Integration Of Facial Recognition Processing
Embodiments herein disclose systems, methods, and computer-readable media for integrating facial recognition technology into clinical workflows. An application can manage receipt of a source image, including a face of an unidentified individual, and communicate the source image for facial recognition processing. The facial recognition processing can identify an individual and demographic information associated thereto, as well as provide information to access an electronic health record server housing one or more electronic health records. The application can access health-related data for the individual from the individual's EHR and rank the accessed information to communicate to a source device in a custom, prioritized communication.
G06V 40/16 - Human faces, e.g. facial parts, sketches or expressions
G16H 40/20 - ICT specially adapted for the management or administration of healthcare resources or facilities; ICT specially adapted for the management or operation of medical equipment or devices for the management or administration of healthcare resources or facilities, e.g. managing hospital staff or surgery rooms
G16H 10/60 - ICT specially adapted for the handling or processing of patient-related medical or healthcare data for patient-specific data, e.g. for electronic patient records
20.
SYSTEM AND METHOD FOR OPTIMIZING DESIGN, WORKFLOWS, PERFORMANCE, AND CONFIGURATIONS BASED ON DESIGN ELEMENTS
Methods, systems, and computer-readable media are disclosed herein for an application that optimizes the design element and workflow configuration of a target computer program. Generally, the application automatically displays preview images of graphical user interface in response to a user-input answer in a questionnaire, where the preview image accounts for design element and/or workflow impacts to the graphical user interface of the target computer program. The application also predicts performance indicators for target computer program that account for design element and/or workflow steps directly or indirectly selected through the user-input answers.
G06Q 10/06 - Resources, workflows, human or project management, e.g. organising, planning, scheduling or allocating time, human or machine resources; Enterprise planning; Organisational models
G06F 3/0484 - Interaction techniques based on graphical user interfaces [GUI] for the control of specific functions or operations, e.g. selecting or manipulating an object or an image, setting a parameter value or selecting a range
G06F 3/0482 - Interaction techniques based on graphical user interfaces [GUI] based on specific properties of the displayed interaction object or a metaphor-based environment, e.g. interaction with desktop elements like windows or icons, or assisted by a cursor's changing behaviour or appearance interaction with lists of selectable items, e.g. menus
21.
INTELLIGENT SCHEDULING SYSTEM AND METHODS BASED ON PATIENT SPECIFIC DATA AND CLUSTER SIMILARITY
Methods, systems, and computer-readable media are disclosed herein for intelligently identifying specific timeslots and identifying specific durations for the timeslots that can be recommended to a person seeking to make an appointment with a clinician. A scheduling module leverages real-time GPS data of the person and clustering techniques to identify the timeslots and predicted durations the person is predicted to utilize in that appointment based at least on a chief complaint and patient cohort data.
G16H 40/20 - ICT specially adapted for the management or administration of healthcare resources or facilities; ICT specially adapted for the management or operation of medical equipment or devices for the management or administration of healthcare resources or facilities, e.g. managing hospital staff or surgery rooms
G16H 10/60 - ICT specially adapted for the handling or processing of patient-related medical or healthcare data for patient-specific data, e.g. for electronic patient records
G06Q 10/10 - Office automation, e.g. computer aided management of electronic mail or groupware; Time management, e.g. calendars, reminders, meetings or time accounting
G16H 50/70 - ICT specially adapted for medical diagnosis, medical simulation or medical data mining; ICT specially adapted for detecting, monitoring or modelling epidemics or pandemics for mining of medical data, e.g. analysing previous cases of other patients
H04W 4/029 - Location-based management or tracking services
An alert optimizer subsystem for a HIT system modifies, reconciles, and/or prioritizes candidate clinical alerts. The optimized alerts may be filtered, prioritized, enriched, and/or formatted so that the alerts are more relevant and/or more actionable for a system user.
G16H 10/60 - ICT specially adapted for the handling or processing of patient-related medical or healthcare data for patient-specific data, e.g. for electronic patient records
23.
INTELLIGENT AND NEAR REAL-TIME MONITORING IN A STREAMING ENVIRONMENT
The present invention is directed to intelligent and near real-time monitoring in a streaming environment. In embodiments, a streaming platform streams raw data from raw data capture devices, where the raw data is contextually enriched using multiple information sources. A rule execution operator, integrated within the streaming platform, detects events by executing rules against the contextually enriched data. The rules applied are customizable, flexible, multivariate, and dynamically responsive to changing information. When an event is detected, an action can be instantiated in response to the event detection and/or newly derived information. The action and/or instructions for performing the action are communicated to external sources, where the action can be initiated and/or completed. Accordingly, actions are instantiated in near real time relative to the initial receipt of raw data from which the events were detected. Actions may be delayed using sophisticated temporal reasoning, in some embodiments.
Embodiments of the present disclosure relate to systems, methods, and user interfaces that generates and renders virtual environments for display using a VR system (e.g., on a display of a VR headset). Virtual reality is leveraged to create immersive experiences that enables users to experience clinical processes, train staff through new protocols, and gain empathy through a variety of complex scenarios. Initially, contextual information is initially received for an event. Based on the contextual information of the event, data collections is triggered from a clinical system and an environment system for data occurring before and after the event. Utilizing the collected data, a three dimensional modeling of a timeline of event, characters associated with the event, and dialogue corresponding to the event can be recreated. After contributing factors are identified and weighted for the event, a virtual simulation of the event can be created.
Methods, computer systems, and computer-storage medium are provided for providing clinical information for a person, such as a test result, immediately and the information automatically and immediately pushed to the ordering physicians device. A graphical representation is generated for a clinician to select clinical notification options. The received selection creates a notification to be automatically sent to one or more clinician devices. Automatic notifications reduce delay in clinician action when new clinician information is provided.
G16H 80/00 - ICT specially adapted for facilitating communication between medical practitioners or patients, e.g. for collaborative diagnosis, therapy or health monitoring
H04L 29/08 - Transmission control procedure, e.g. data link level control procedure
Technologies are provided for automatically routing service requests (e.g., trouble tickets). More particularly, embodiments of the present invention provide a real-time routing system that helps reduce the wait time on the assignment of client logged support requests. To do so, a batch job may run regularly (e.g., every 5 minutes) to identify newly logged tickets by querying a ticket database corresponding to a ticket system. The smart routing systems utilizes an iterative process to identify the most appropriate associate on the most appropriate support team for assigning the ticket. Once the appropriate associate has been identified, the client as well as the associate may be notified regarding the ticket assignment.
Systems and methods are provided for facilitating the dispensing of a medication from a dispensing station. An order is received and includes the medication and a total dosage for the medication to be dispensed. The medication is mapped to a table that stores a list of a plurality of medications that are available for dispensing at one or more dispensing stations at different physical locations. Each of the plurality of medications are stored in the table with a corresponding unit usable to formulate a dosage. A particular medication is identified in the plurality of medications in the table that corresponds to the medication of the order. The particular medication also corresponds to the total dosage based on the corresponding unit in the table associated with the particular medication. An instruction is communicated to the one or more dispensing stations to dispense the particular medication.
G16H 20/13 - ICT specially adapted for therapies or health-improving plans, e.g. for handling prescriptions, for steering therapy or for monitoring patient compliance relating to drugs or medications, e.g. for ensuring correct administration to patients delivered from dispensers
G06Q 10/08 - Logistics, e.g. warehousing, loading, distribution or shipping; Inventory or stock management, e.g. order filling, procurement or balancing against orders
Methods and systems for processing of voice input to identify intents and mapped standard terminologies are provided. Using natural language processing, an intent of a voice input is identified. The intent is utilized to identify a standard terminology that maps to the intent. The standard terminology is utilized to identify information relevant to the standard terminology in a patient's electronic health record.
G10L 15/22 - Procedures used during a speech recognition process, e.g. man-machine dialog
G16H 10/60 - ICT specially adapted for the handling or processing of patient-related medical or healthcare data for patient-specific data, e.g. for electronic patient records
G10L 15/18 - Speech classification or search using natural language modelling
G06V 40/20 - Movements or behaviour, e.g. gesture recognition
G06V 40/16 - Human faces, e.g. facial parts, sketches or expressions
29.
ENABLING THE USE OF MULITPLE PICTURE ARCHIVING COMMIUNICATION SYSTEMS BY ONE OR MORE FACILITIES ON A SHARED DOMAIN
Methods, systems, and computer-storage media are provided for utilizing multiple Picture Archiving Communication Systems (PACS) to view one more medical images by storing one or more PACS at a database within the system. Requests are received from one or more users at one or more facilities to utilize one or more PACS to view one or more medical images. After accessing the database to determine one or more PACS authorized for each facility from which a request is received, one or more users are provided with one or more PACS to view medical images associated with radiological exams and provide the necessary assessments and reports for treatment.
A catastrophe-theoretic approach is provided for predicting an occurrence of an acute inflammatory condition or event (e.g., SIRS or sepsis) for a human patient based on a time series of monitored vital signs values measured from a patient, and in some instances, for providing advanced notice to clinicians or caregivers when such an acute inflammatory event is forecasted or modifying treatment for the patient, according to the predicted likelihood. In particular, an acute inflammatory condition management system is provided for determining a likelihood of near-term future significant acute inflammation in human patients. Embodiments of the disclosure described herein may provide a forecasted risk for future significant acute inflammation within a time horizon comprising a future time interval. In one embodiment, the future time interval is from 30 min to approximately 8 hours into the future, and may be dependent on the frequency of vital signs measurements.
A61B 5/00 - Measuring for diagnostic purposes ; Identification of persons
A61B 5/0205 - Simultaneously evaluating both cardiovascular conditions and different types of body conditions, e.g. heart and respiratory condition
G16H 50/50 - ICT specially adapted for medical diagnosis, medical simulation or medical data mining; ICT specially adapted for detecting, monitoring or modelling epidemics or pandemics for simulation or modelling of medical disorders
A61B 5/08 - Measuring devices for evaluating the respiratory organs
Methods and systems for natural language processing/understanding of voice conversations are provided. Using natural language processing, a clinical condition is extracted from a voice conversation. A clinical ontology identifies clinical concepts associated with the clinical conditions. The clinical concepts are classified for documentation. The clinical concepts are searched and validated from within an individual's longitudinal record.
G10L 15/22 - Procedures used during a speech recognition process, e.g. man-machine dialog
G16H 10/60 - ICT specially adapted for the handling or processing of patient-related medical or healthcare data for patient-specific data, e.g. for electronic patient records
Methods are provided for validating theoretical improvements in the decision-support processes facilitating surveillance and monitoring of a patient's risk for developing a particular disease or condition and detecting the disease or condition. Patient information is received from a source and populated into an active risk assessment that monitors the patient's risk for developing Sepsis. At least a first and second set of actionable criteria for determining a patient's risk for developing sepsis are received. For each set of actionable criteria, it is determined that actionable criteria have been met. In some embodiments, software agents, operating in a multi-agent computing platform, perform each determination of whether actionable criteria are met. In some embodiments, in response to actionable criteria being met, a notification or alert is provided, and in some embodiments the results of the determinations of each set of actionable criteria are provided to facilitate validation of theoretical improvements.
G16H 50/30 - ICT specially adapted for medical diagnosis, medical simulation or medical data mining; ICT specially adapted for detecting, monitoring or modelling epidemics or pandemics for individual health risk assessment
33.
Intelligent touch care corresponding to a patient reporting a change in condition
Embodiments of the present disclosure relate to systems, methods, and user interfaces for providing intelligent touch care. More particularly, embodiments of the present disclosure utilizes contributing data elements in a community early warning score (CEWS) to predict touchpoint discipline and to recommend frequency, modality, and upstream transitions of care and outside service referrals for a patient in a community care setting. In response to a touch point (e.g., a change in condition or medication, a scheduled or unscheduled appointment, or a patient question), the CEWS can be utilized along with data in an EHR of a patient, data from a patient device, or data from a patient portal to initiate a follow-up (e.g., personal health question or encounter). Notification tools and scheduling functionality are provided via a user interface of the patient device to improve clinical workforce capacity, increase the number of patient touches, and encourage heightened patient engagement.
G16H 80/00 - ICT specially adapted for facilitating communication between medical practitioners or patients, e.g. for collaborative diagnosis, therapy or health monitoring
G16H 40/20 - ICT specially adapted for the management or administration of healthcare resources or facilities; ICT specially adapted for the management or operation of medical equipment or devices for the management or administration of healthcare resources or facilities, e.g. managing hospital staff or surgery rooms
G16H 10/60 - ICT specially adapted for the handling or processing of patient-related medical or healthcare data for patient-specific data, e.g. for electronic patient records
Embodiments herein disclose systems, methods, and computer-readable media for automatically transforming a code base. Using the code base as input, the code base is parsed, analyzed, and a modified code base is automatically generated. The code base may be modified by changing one or more assets in the code base based on the identification of path-to-path dependencies and/or interactions, in various embodiments. In some embodiments, the identifiers for globally exposed assets in the code base are modified to add imports or exports.
Systems and methods are provided to electronically generate an Electronic Data Interchange (EDI) 835 transmission to test an EDI 835 processing system. An EDI 835 transmission may include vast amounts of data that are input into the transmission in a unique way. If even one space is off, the EDI 835 transmission will not be correctly processed and may be kicked back by the system. This has serious consequences, as it may result in incorrect or non-recording of a payment on a claim. Unfortunately, most systems are not tested for EDI 835 processing capabilities before going live due to the time intensive nature of generating EDI 835 transmissions for testing. The present application describes one or more innovative ways to electronically generate one or more EDI 835 transmission.
G16H 40/20 - ICT specially adapted for the management or administration of healthcare resources or facilities; ICT specially adapted for the management or operation of medical equipment or devices for the management or administration of healthcare resources or facilities, e.g. managing hospital staff or surgery rooms
G06F 16/25 - Integrating or interfacing systems involving database management systems
Systems, methods and computer-readable media are provided for facilitating patient health care through automatic discovery, establishment, and statistical validation of diagnostic-signals in repositories of EMR information, identifying phenotypic diagnostic signals regarding markers or combinations or sequences of patient attributes. In an embodiment, a method includes identifying, from a dataset of health care records, a first group of patients that have one or more markers; extracting one or more diagnostic statuses that pertain to the group of patients tested with diagnostics such as whole genome sequencing (WGS) or whole exome sequencing (WES); determining one or more statistically significant differences involving frequent itemsets comprised of two or more marker combinations that occur concomitantly in members of the group; determining statistical disproportionality signals among the items and itemsets with regard to the likelihood that WGS or WES will yield a specific, actionable diagnosis; and determining membership of an individual in a diagnostic-yield subset of the group according to the individual's manifesting one or more of the identified signals.
G16H 50/20 - ICT specially adapted for medical diagnosis, medical simulation or medical data mining; ICT specially adapted for detecting, monitoring or modelling epidemics or pandemics for computer-aided diagnosis, e.g. based on medical expert systems
G16H 10/60 - ICT specially adapted for the handling or processing of patient-related medical or healthcare data for patient-specific data, e.g. for electronic patient records
G16B 20/00 - ICT specially adapted for functional genomics or proteomics, e.g. genotype-phenotype associations
A computing platform is provided to perform continuous monitoring of new genomic variants from external genomic databases and compare the new variants to genomic sequencing results for patients stored in long term cloud storage. The platform provides alerts to clinicians if a patient's genomic sequencing results match one or more of the new genomic variants.
G16B 20/20 - Allele or variant detection, e.g. single nucleotide polymorphism [SNP] detection
G06F 16/27 - Replication, distribution or synchronisation of data between databases or within a distributed database system; Distributed database system architectures therefor
G06F 16/2458 - Special types of queries, e.g. statistical queries, fuzzy queries or distributed queries
G06F 16/28 - Databases characterised by their database models, e.g. relational or object models
G16H 10/40 - ICT specially adapted for the handling or processing of patient-related medical or healthcare data for data related to laboratory analysis, e.g. patient specimen analysis
G16H 10/60 - ICT specially adapted for the handling or processing of patient-related medical or healthcare data for patient-specific data, e.g. for electronic patient records
G16H 70/60 - ICT specially adapted for the handling or processing of medical references relating to pathologies
G16H 50/70 - ICT specially adapted for medical diagnosis, medical simulation or medical data mining; ICT specially adapted for detecting, monitoring or modelling epidemics or pandemics for mining of medical data, e.g. analysing previous cases of other patients
G16H 15/00 - ICT specially adapted for medical reports, e.g. generation or transmission thereof
G16H 40/20 - ICT specially adapted for the management or administration of healthcare resources or facilities; ICT specially adapted for the management or operation of medical equipment or devices for the management or administration of healthcare resources or facilities, e.g. managing hospital staff or surgery rooms
G06Q 10/06 - Resources, workflows, human or project management, e.g. organising, planning, scheduling or allocating time, human or machine resources; Enterprise planning; Organisational models
G16B 50/30 - Data warehousing; Computing architectures
Systems, methods, and storage media useful in a computing platform to automatically generate and deploy access control list (ACL) rules for one or more firewalls in a data center are provided. The computing platform is vendor-agnostic and generates ACL rules in multiple syntaxes depending on the firewall needing updating. The platform traverses a data center mapping structure to identify one or more firewalls to be updated for a destination IP address and source IP address and automatically generates the ACL rule in the syntax for the one or more firewalls identified.
Systems, methods, and storage media useful in a healthcare computing platform to provide comprehensive safety measurement scores, and the individual safety measurements that make up the comprehensive safety measurement scores, for multiple hospitals in a geographic area and/or within a healthcare system are provided. Systems, methods, and storage media provided receive changes to individual safety measurements to model how changes to individual measurements impact the comprehensive safety measurement score for a hospital.
G16H 40/20 - ICT specially adapted for the management or administration of healthcare resources or facilities; ICT specially adapted for the management or operation of medical equipment or devices for the management or administration of healthcare resources or facilities, e.g. managing hospital staff or surgery rooms
Methods, systems, and computer-readable media are disclosed herein for Electronic Medical Record (EMR) integrated electronic case reporting. A trigger code is received from a platform. The trigger code corresponds to an infectious disease or a public health concern, such as receiving a vaccination. A patient code is also received. The patient code corresponds to information from a patient encounter. The trigger code is compared to the patient code and it is determined whether a match exists. Upon determining that the match exists, a time logic is applied for generating an electronic Initial Case Report (eICR). The time logic corresponds to the information from the patient encounter. The eICR comprising EMR data is generated.
G16H 10/60 - ICT specially adapted for the handling or processing of patient-related medical or healthcare data for patient-specific data, e.g. for electronic patient records
G16H 10/40 - ICT specially adapted for the handling or processing of patient-related medical or healthcare data for data related to laboratory analysis, e.g. patient specimen analysis
G16H 50/70 - ICT specially adapted for medical diagnosis, medical simulation or medical data mining; ICT specially adapted for detecting, monitoring or modelling epidemics or pandemics for mining of medical data, e.g. analysing previous cases of other patients
G16H 70/20 - ICT specially adapted for the handling or processing of medical references relating to practices or guidelines
G16H 70/60 - ICT specially adapted for the handling or processing of medical references relating to pathologies
G16H 40/20 - ICT specially adapted for the management or administration of healthcare resources or facilities; ICT specially adapted for the management or operation of medical equipment or devices for the management or administration of healthcare resources or facilities, e.g. managing hospital staff or surgery rooms
G06Q 10/10 - Office automation, e.g. computer aided management of electronic mail or groupware; Time management, e.g. calendars, reminders, meetings or time accounting
G16H 50/80 - ICT specially adapted for medical diagnosis, medical simulation or medical data mining; ICT specially adapted for detecting, monitoring or modelling epidemics or pandemics for detecting, monitoring or modelling epidemics or pandemics, e.g. flu
G16H 70/40 - ICT specially adapted for the handling or processing of medical references relating to drugs, e.g. their side effects or intended usage
A concept type agnostic method, system and media is provided to dynamically generate a narrative view based on the template hierarchy levels, high-level attributes of the nodes in the document template hierarchy, and end user entry is provided.
G06F 19/00 - Digital computing or data processing equipment or methods, specially adapted for specific applications (specially adapted for specific functions G06F 17/00;data processing systems or methods specially adapted for administrative, commercial, financial, managerial, supervisory or forecasting purposes G06Q;healthcare informatics G16H)
G16H 15/00 - ICT specially adapted for medical reports, e.g. generation or transmission thereof
G16H 10/60 - ICT specially adapted for the handling or processing of patient-related medical or healthcare data for patient-specific data, e.g. for electronic patient records
42.
PREDICTIVE, DIAGNOSTIC AND THERAPEUTIC APPLICATIONS OF WEARABLES FOR MENTAL HEALTH
Methods, systems, and computer-readable media are disclosed herein for predictive, diagnostic, and therapeutic applications of wearables for mental health. Information is received from at least one user device comprising a wearable device and corresponding to a user of the at least one user device. A response from the user to a validating questionnaire for a type of mental disorder or neurological disorder is received. A risk score corresponding to the type of mental disorder or neurological disorder and based at least in part on the information and the response to the validating questionnaire is determined. A determination is made as to whether the risk score is within a first predetermined range. In response to the risk score not being within the first predetermined range, a notification is automatically provided. Feedback from the wearable device is received in response to the user taking a medication prescribed after automatically providing the notification. The feedback indicates data corresponding to an activity or a behavior of the user is not within a second predetermined range. A follow up is automatically scheduled in response to receiving the feedback.
A61B 5/11 - Measuring movement of the entire body or parts thereof, e.g. head or hand tremor or mobility of a limb
A61B 5/0205 - Simultaneously evaluating both cardiovascular conditions and different types of body conditions, e.g. heart and respiratory condition
G16H 10/20 - ICT specially adapted for the handling or processing of patient-related medical or healthcare data for electronic clinical trials or questionnaires
G16H 20/70 - ICT specially adapted for therapies or health-improving plans, e.g. for handling prescriptions, for steering therapy or for monitoring patient compliance relating to mental therapies, e.g. psychological therapy or autogenous training
G16H 10/60 - ICT specially adapted for the handling or processing of patient-related medical or healthcare data for patient-specific data, e.g. for electronic patient records
43.
REGULATORY DOCUMENT ANALYSIS WITH NATURAL LANGUAGE PROCESSING
Technologies are provided for automatically comparing versions of a regulatory document and highlighting meaningful changes to each version of the regulatory document. An analysis engine accepts two inputs of a regulatory document in HTML format. One input is an original version of the regulatory document and one input is a revised version of the regulatory document. The documents are processed by the analysis engine to highlight added content as compared to the original version of the HTML content and the second document being processed to highlight removed content as compared to the revised version of the HTML content. These highlighted documents are then presented to the user.
Methods, systems, and computer-readable media are disclosed herein for intelligent service request analysis and remedy. In an aspect, a service request related to a computer system is received. Once received, natural language processing is conducted to determine at least one key term associated with the at least one service request. A machine learning algorithm is then used to determine at least one classification group for the at least one service request, wherein the classification group is associated with the remedy. A rate of success is determined for the determined remedy for the classification group. Based on the rate of success exceeding a predetermined threshold, cause the remedy to be implemented in the computer system.
G10L 15/18 - Speech classification or search using natural language modelling
G16H 10/60 - ICT specially adapted for the handling or processing of patient-related medical or healthcare data for patient-specific data, e.g. for electronic patient records
45.
Performing configuration validation to optimize system functionality
Methods, systems, and computer-storage media are provided for validating the configuration of one or more applications to be used by one or more users in a healthcare management system. Requests are received to perform a configuration validation for at least one application at a first location. Configuration file data comprising one or more requirements and configuration data for the at least one application is obtained. The configuration validation is performed by conducting a comparative analysis on the configuration file data and the configuration data. If the data is identical, then the requirements are met, and the correct version of the application is installed. If the data is not identical, then the system identifies the correct version that needs to be installed. A message is generated for the first user comprising the configuration validation outcome.
G06F 9/44 - Arrangements for executing specific programs
G06F 8/71 - Version control ; Configuration management
G16H 40/40 - ICT specially adapted for the management or administration of healthcare resources or facilities; ICT specially adapted for the management or operation of medical equipment or devices for the management of medical equipment or devices, e.g. scheduling maintenance or upgrades
Methods, systems, and computer-readable media are disclosed herein for providing objective electronic medical record (EMR) system adoption analysis. In an aspect, a subjective input and an objective input is received by a user via a user computing device. The subjective input is comprised of at least one of knowledge assessment related to an EMR system, an attitude assessment related to the EMR system, or a practice assessment related to the EMR system. The objective input is comprised of demographic data related to the user of the EMR system. A score is then calculated for the objective and subjective input, wherein calculating the score comprises applying a weight to the objective and the subjective input to determine one or more of a knowledge score, an attitude score, or a practice score. It is determined that at least one of the knowledge score, attitude score, or practice score, is below at least one predetermined threshold. And, responsive to determining this, an intervention module associated with at least one of the knowledge score, attitude score, or practice score, is automatically transmitted to the user.
G09B 7/08 - Electrically-operated teaching apparatus or devices working with questions and answers of the multiple-choice answer type, i.e. where a given question is provided with a series of answers and a choice has to be made from the answers characterised by modifying the teaching programme in response to a wrong answer, e.g. repeating the question, supplying further information
G16H 10/60 - ICT specially adapted for the handling or processing of patient-related medical or healthcare data for patient-specific data, e.g. for electronic patient records
G16H 10/20 - ICT specially adapted for the handling or processing of patient-related medical or healthcare data for electronic clinical trials or questionnaires
G16H 40/20 - ICT specially adapted for the management or administration of healthcare resources or facilities; ICT specially adapted for the management or operation of medical equipment or devices for the management or administration of healthcare resources or facilities, e.g. managing hospital staff or surgery rooms
G09B 19/00 - Teaching not covered by other main groups of this subclass
47.
RESPONDING TO REQUESTS FOR INFORMATION AND OTHER VERBAL UTTERANCES IN A HEALTHCARE FACILITY
Systems, methods, and devices are provided for responding to requests received from users in a healthcare facility, and for generating alerts based upon criticality detected in received verbal utterances. A personal assistant device (PAD) may receive a verbal request for information. The identity of the requestor may be verified and a response to the request may be received by the PAD. In some cases, prior to audibly outputting the response, it may be determined whether the response contains protected health information (PHI). Upon determining that the response contains PHI, the presence of persons other than the patient in proximity to the PAD and/or security of the location of the PAD may be evaluated prior to audibly outputting the response. Additionally, alerts having a heightened criticality may be generated when a received verbal utterance is determined to have a heightened criticality.
G16H 10/60 - ICT specially adapted for the handling or processing of patient-related medical or healthcare data for patient-specific data, e.g. for electronic patient records
Methods are provided for the surveillance and monitoring of a patient's medical care when the patient is treated at two or more medical organizations having different medical record systems. Patient information is received from a first medical organization and populated into an active risk assessment array that monitors the patient's risk for developing a particular disease or condition. Patient information is then received from a second medical organization and populated into the array. It is determined that actionable criteria have been met, and in response, a notification or alert is sent to the medical organizations indicating that the patient is at risk.
G16H 10/60 - ICT specially adapted for the handling or processing of patient-related medical or healthcare data for patient-specific data, e.g. for electronic patient records
G16H 50/20 - ICT specially adapted for medical diagnosis, medical simulation or medical data mining; ICT specially adapted for detecting, monitoring or modelling epidemics or pandemics for computer-aided diagnosis, e.g. based on medical expert systems
G16H 40/67 - ICT specially adapted for the management or administration of healthcare resources or facilities; ICT specially adapted for the management or operation of medical equipment or devices for the operation of medical equipment or devices for remote operation
49.
AUTOMATED TRANSFORMATION DOCUMENTATION OF MEDICAL DATA
Systems, methods, and storage media useful in a healthcare cloud computing platform to transform, deduplicate and store medical data from third-party databases to a patient's primary medical record in the healthcare cloud computing platform. Exemplary implementations may: load and read data from third-party databases, and determine if it is duplicative of what is in the patient's primary record. Other embodiments, provide a method for ranking medical data from two different third-party databases to determine which medical data should be written to the patient's primary medical record in the healthcare computing platform.
G06F 16/215 - Improving data quality; Data cleansing, e.g. de-duplication, removing invalid entries or correcting typographical errors
G06F 16/25 - Integrating or interfacing systems involving database management systems
G06F 16/21 - Design, administration or maintenance of databases
G16H 10/60 - ICT specially adapted for the handling or processing of patient-related medical or healthcare data for patient-specific data, e.g. for electronic patient records
50.
AUTOMATED TRANSFORMATION DOCUMENTATION OF MEDICAL DATA
Systems, methods, and storage media useful in a healthcare cloud computing platform to transform, deduplicate and store medical data from third-party databases to a patient's primary medical record in the healthcare cloud computing platform. Exemplary implementations may: load and read data from third-party databases, and determine if it is duplicative of what is in the patient's primary record. Other embodiments, provide a method for ranking medical data from two different third-party databases to determine which medical data should be written to the patient's primary medical record in the healthcare computing platform.
G16H 10/60 - ICT specially adapted for the handling or processing of patient-related medical or healthcare data for patient-specific data, e.g. for electronic patient records
Methods, systems, and computer-readable media are disclosed herein for automated identification and alerting of neurodegenerative diseases (NDD). Patient information comprising medical history information is accessed. Using the patient information, one or more risk factors and/or symptoms for a NDD are identified. Using the identified risk factors and/or symptoms, a patient with probable risk for developing the NDD is determined. A notification of the probable risk that the patient develops the NDD is provided.
G16H 50/30 - ICT specially adapted for medical diagnosis, medical simulation or medical data mining; ICT specially adapted for detecting, monitoring or modelling epidemics or pandemics for individual health risk assessment
G16H 50/20 - ICT specially adapted for medical diagnosis, medical simulation or medical data mining; ICT specially adapted for detecting, monitoring or modelling epidemics or pandemics for computer-aided diagnosis, e.g. based on medical expert systems
G16H 10/60 - ICT specially adapted for the handling or processing of patient-related medical or healthcare data for patient-specific data, e.g. for electronic patient records
52.
Optimizing Service Delivery through Partial Dependency Plots
This disclosure includes technologies for service level delivery, including for achieving various threshold satisfaction levels in delivering services. The disclosed system uses machine learning models to predict the respective importance of various variables associated with a service. Further, the disclosed system determines respective marginal contributions and respective thresholds associated with variables with high-impact for service level delivery. Subsequently, the disclosed system performs various tasks based on those thresholds to achieve various threshold satisfaction levels in delivering the service.
G06F 3/0488 - Interaction techniques based on graphical user interfaces [GUI] using specific features provided by the input device, e.g. functions controlled by the rotation of a mouse with dual sensing arrangements, or of the nature of the input device, e.g. tap gestures based on pressure sensed by a digitiser using a touch-screen or digitiser, e.g. input of commands through traced gestures
G06F 3/0482 - Interaction techniques based on graphical user interfaces [GUI] based on specific properties of the displayed interaction object or a metaphor-based environment, e.g. interaction with desktop elements like windows or icons, or assisted by a cursor's changing behaviour or appearance interaction with lists of selectable items, e.g. menus
G06F 3/01 - Input arrangements or combined input and output arrangements for interaction between user and computer
Technologies are provided for leveraging machine learning to predict the likelihood of near-future OUD for patients presenting in an emergency department. A model is trained with data corresponding to one or more of: gender, age, prior opioid use disorder diagnosis, prior opioid use disorder events, prior opioids, prior emergency department encounters, prior inpatient encounters, other medications, drug screening tests, hepatitis C tests, tobacco use questionnaires, prior results from medical tests, social history questionnaires, or other diagnoses to predict opioid use disorder risk for a population of patients. Upon receiving information available at an emergency department triage for a patient, the trained model is utilized to predict the opioid use disorder risk for the patient over a predetermined period of time. The predicted opioid use disorder risk for the patient is provided within the patient chart over the predetermined period of time and may include details corresponding to risk factors specific to the patient and risk mitigation options.
G16H 50/70 - ICT specially adapted for medical diagnosis, medical simulation or medical data mining; ICT specially adapted for detecting, monitoring or modelling epidemics or pandemics for mining of medical data, e.g. analysing previous cases of other patients
G16H 50/30 - ICT specially adapted for medical diagnosis, medical simulation or medical data mining; ICT specially adapted for detecting, monitoring or modelling epidemics or pandemics for individual health risk assessment
G16H 50/20 - ICT specially adapted for medical diagnosis, medical simulation or medical data mining; ICT specially adapted for detecting, monitoring or modelling epidemics or pandemics for computer-aided diagnosis, e.g. based on medical expert systems
G16H 20/10 - ICT specially adapted for therapies or health-improving plans, e.g. for handling prescriptions, for steering therapy or for monitoring patient compliance relating to drugs or medications, e.g. for ensuring correct administration to patients
G16H 40/20 - ICT specially adapted for the management or administration of healthcare resources or facilities; ICT specially adapted for the management or operation of medical equipment or devices for the management or administration of healthcare resources or facilities, e.g. managing hospital staff or surgery rooms
G16H 10/60 - ICT specially adapted for the handling or processing of patient-related medical or healthcare data for patient-specific data, e.g. for electronic patient records
G16H 10/40 - ICT specially adapted for the handling or processing of patient-related medical or healthcare data for data related to laboratory analysis, e.g. patient specimen analysis
G16H 10/20 - ICT specially adapted for the handling or processing of patient-related medical or healthcare data for electronic clinical trials or questionnaires
Systems, methods, and storage media useful in a healthcare cloud computing platform to transform, deduplicate and store medical data from third-party databases to a patient's primary medical record in the healthcare cloud computing platform. Exemplary implementations may: load and read data from third-party databases, and determine if it is duplicative of what is in the patient's primary record. Other embodiments, provide a method for ranking medical data from two different third-party databases to determine which medical data should be written to the patient's primary medical record in the healthcare computing platform.
G16H 15/00 - ICT specially adapted for medical reports, e.g. generation or transmission thereof
G16H 10/60 - ICT specially adapted for the handling or processing of patient-related medical or healthcare data for patient-specific data, e.g. for electronic patient records
G06F 16/215 - Improving data quality; Data cleansing, e.g. de-duplication, removing invalid entries or correcting typographical errors
G06F 16/25 - Integrating or interfacing systems involving database management systems
Methods, computer systems and computer readable media cause an infusion pump to provide a line check validation. A medical device that needs a line check validation is provided to a clinician via a graphical user interface. A selection of the medical device that needs the line check validation is received via the graphical user interface. The line check validation is automatically performed based on the selection. In aspects, the line check validation comprises establishing a first connection between a computing device associated with the graphical user interface and a second computing device associated with a patient. Further, the line check validation comprises establishing a second connection between the computing device and the medical device. As such, the medical device for the patient is automatically validated based on the first connection and the second connection.
G16H 20/17 - ICT specially adapted for therapies or health-improving plans, e.g. for handling prescriptions, for steering therapy or for monitoring patient compliance relating to drugs or medications, e.g. for ensuring correct administration to patients delivered via infusion or injection
G16H 40/63 - ICT specially adapted for the management or administration of healthcare resources or facilities; ICT specially adapted for the management or operation of medical equipment or devices for the operation of medical equipment or devices for local operation
G16H 10/60 - ICT specially adapted for the handling or processing of patient-related medical or healthcare data for patient-specific data, e.g. for electronic patient records
56.
Determining patient candidacy for epilepsy neurosurgical procedure
Systems, methods and computer-readable media are provided for identifying persons who are likely to benefit from a neurosurgical procedure, such as lobectomy, hemispherectomy, lesionectomy, callosotomy, and the like. Measured values of physiological variables may be combined via a multi-variable predictive model. In some embodiments, this may take the form of a multinomial logistic regression classifier. In other embodiments, the evidence-combining may be implemented via a neural network or support vector machine or similar machine learning or classification methods. In an embodiment, a leading indicator of near-term responsiveness to the regimen may be provided to a caregiver, such as a neurologist, and further may be integrated with case-management software and an electronic health record decision-support system.
A61B 5/05 - Detecting, measuring or recording for diagnosis by means of electric currents or magnetic fields; Measuring using microwaves or radio waves
A61B 5/00 - Measuring for diagnostic purposes ; Identification of persons
G06F 19/00 - Digital computing or data processing equipment or methods, specially adapted for specific applications (specially adapted for specific functions G06F 17/00;data processing systems or methods specially adapted for administrative, commercial, financial, managerial, supervisory or forecasting purposes G06Q;healthcare informatics G16H)
A61B 34/10 - Computer-aided planning, simulation or modelling of surgical operations
G16H 40/63 - ICT specially adapted for the management or administration of healthcare resources or facilities; ICT specially adapted for the management or operation of medical equipment or devices for the operation of medical equipment or devices for local operation
G16H 50/20 - ICT specially adapted for medical diagnosis, medical simulation or medical data mining; ICT specially adapted for detecting, monitoring or modelling epidemics or pandemics for computer-aided diagnosis, e.g. based on medical expert systems
G16H 10/60 - ICT specially adapted for the handling or processing of patient-related medical or healthcare data for patient-specific data, e.g. for electronic patient records
Methods, systems, and computer-readable media are provided for facilitating record matching and entity resolution and for enabling improvements in record linkage. A power-spectrum-based temporal pattern-specific weight may be incorporated into record linkage methods to enhance the record linkage accuracy and statistical performance. For example, in embodiments, a value-specific weight may be calculated from a population-based frequency of field-specific values and provides an opportunity to capture and measure the relative importance of specific values found in a field. A timeseries-derived Bayesian power spectrum weight may be calculated from the population-based frequency of temporal pattern-specific values in terms of intensities at various frequencies of the power spectrum computed from the timeseries, and further provides an opportunity to capture and measure the relative importance of specific sequences of care episodes.
G16H 10/60 - ICT specially adapted for the handling or processing of patient-related medical or healthcare data for patient-specific data, e.g. for electronic patient records
58.
UTILIZING MULTI-LAYER CACHING SYSTEMS FOR STORING AND DELIVERING IMAGES
Methods, systems, and computer-storage media are provided for utilizing a multi-layer caching system to provide fast and accurate diagnostic image renderings to a healthcare provider. After receiving a request to view medical image data that comprises at least one image frame, the system accesses a least recently used (LRU) memory cache and a local database to determine whether the requested medical image data is stored locally. If the medical image data is not stored locally, the system accesses a remote image storage and retrieves the medical image data requested. The medical image data is then transformed from a compressed format to a decompressed format and transmitted to a user for review. Additionally, the decompressed medical image data is stored locally at either the LRU memory cache or the local database until no longer needed.
Systems and methods are provided for evaluating an alarm condition for a monitored patient in a population of one or more patients. One or more physiological parameters pertaining to the patient, or physiological variables, are used to form a time series describing the patient status. A quantile threshold is determined for a patient. A monitor is initialized and begins generating a binary raw alarm signal. The binary signal is filtered with a low pass filter, and the filtered data is subjected to a quantile operation to determine if a particular sample exceeds the determined quantile threshold. If the quantile threshold is exceeded, then a check is performed to see if the raw binary alarm signal also indicates an alarm. If both the preliminary alarm indication and the raw binary signal indicate an alarm, then an alarm is emitted; otherwise monitoring continues.
In some examples, data associated one or more medical presentations of a person is received. A mapping that associates the data to one or more candidate diagnoses is determined. The one or more candidate diagnoses correspond to one or more possible medical conditions associated with the person. A validation score for a first candidate diagnosis, of the one or more candidate diagnoses, is generated based on a set of features associated with the person. The validation score indicates an accuracy of the candidate diagnosis. At least partially in response to the generating of the validation score, an indicator is caused to be provided at a user device. The indicator indicates the validation score.
G16H 50/20 - ICT specially adapted for medical diagnosis, medical simulation or medical data mining; ICT specially adapted for detecting, monitoring or modelling epidemics or pandemics for computer-aided diagnosis, e.g. based on medical expert systems
G16H 50/30 - ICT specially adapted for medical diagnosis, medical simulation or medical data mining; ICT specially adapted for detecting, monitoring or modelling epidemics or pandemics for individual health risk assessment
61.
METHODS AND SYSTEM FOR RECORDING USER INPUTS WHEN INTERACTING WITH A USER INTERFACE
Methods and systems are provided for collecting and recording any inputs that a user provides to an application or website while the user is interacting with the user interface. The collected information is recorded and stored either in the user's browser cache or sent back to the application backend. The storage location is determined by the application developer or website developer. The recorded data may be automatically restored when the user accesses the location where the user inputs were collected from. The user's data is stored only in the user cache or the application backend such that the data provided by the user is safe and secure.
G06F 9/455 - Emulation; Interpretation; Software simulation, e.g. virtualisation or emulation of application or operating system execution engines
G06F 16/958 - Organisation or management of web site content, e.g. publishing, maintaining pages or automatic linking
G16H 10/60 - ICT specially adapted for the handling or processing of patient-related medical or healthcare data for patient-specific data, e.g. for electronic patient records
G06F 21/62 - Protecting access to data via a platform, e.g. using keys or access control rules
G06F 9/451 - Execution arrangements for user interfaces
62.
System and method for predicting the impact of source code modification based on historical source code modifications
Methods, systems, and computer-readable media are disclosed herein that utilizes historical changes made to files and methods in computer programming code to predict related files and methods that may be affected by current and/or future changes made to other files and methods. In aspects, when computer code for a particular method is going to be edited, other methods are identified that were changed in previous editing sessions that also included changes to the particular method. Using scoring techniques for the other methods, a recommendation is provided that details the relative strength of whether the other methods are predicted to be affected by any changes made to the computer code for the particular method that is edited.
Methods, systems, and computer-readable media are disclosed herein that provide a comprehensive view that reveals all or nearly all possible method dependencies that are present in client workflows. In aspects, when computer code for a particular method is going to be edited, other methods are identified that have upstream or downstream dependencies relative to the particular method. The methods that will be affected based on the computer code editing can be presented in a user-interactive graphical user interface that facilitates exploration of upstream and downstream dependencies.
Methods, systems, and computer-readable media are disclosed herein for automatically identifying and selecting, based on machine learning model(s), one or more patient educations instructions as suggested smart recommendations for a particular patient, based on parameter matching and filtering with other patient parameters. The parameters of a current patient can be automatically matched to parameters that are associated with other patients, on a one-to-one parameter basis or based on specific combinations parameters. Based on the presence of one or more shared parameters between a current patient and other patients as well as the strength of the parameter match, one or more instructions that were provided to the other patients can be recommended for the current patient automatically. Instruction(s) selected for the current patient can then be stored in association with the parameters of the current patient and used to evaluate and make recommendations for subsequent patients.
G16H 50/20 - ICT specially adapted for medical diagnosis, medical simulation or medical data mining; ICT specially adapted for detecting, monitoring or modelling epidemics or pandemics for computer-aided diagnosis, e.g. based on medical expert systems
G16H 10/60 - ICT specially adapted for the handling or processing of patient-related medical or healthcare data for patient-specific data, e.g. for electronic patient records
G16H 50/70 - ICT specially adapted for medical diagnosis, medical simulation or medical data mining; ICT specially adapted for detecting, monitoring or modelling epidemics or pandemics for mining of medical data, e.g. analysing previous cases of other patients
G16H 40/20 - ICT specially adapted for the management or administration of healthcare resources or facilities; ICT specially adapted for the management or operation of medical equipment or devices for the management or administration of healthcare resources or facilities, e.g. managing hospital staff or surgery rooms
G16H 15/00 - ICT specially adapted for medical reports, e.g. generation or transmission thereof
Technologies are provided for providing a dashboard interface corresponding to one or more datacenter components for information originating from one or more proprietary applications. A selection of information corresponding to the one or more datacenter components is initially received. Upon receiving the selection, an application programming interface (API) call request is made, in real-time, for the information corresponding to the one or more datacenter components from the one or more proprietary applications. As the information corresponding to one or more datacenter components from the one or more proprietary applications is received, it is aggregated and provided within the dashboard interface.
Methods, systems, and computer-readable media are disclosed herein for predicting medication induced respiratory depression in patients. Herein, when indications are received for particular events being logged to a computerized clinical workflow, a query of patient's clinical record(s) is preformed to locate predetermined factors that are associated with medication induced respiratory depression. An overall value is calculated to stratify the possibility of adverse respiratory events for the patient. Warnings, detailed intervention instructions, and complete medical orders can be automatically generated and provided to a clinician and/or automatically input to the clinical workflow of the patient for performance.
G16H 50/20 - ICT specially adapted for medical diagnosis, medical simulation or medical data mining; ICT specially adapted for detecting, monitoring or modelling epidemics or pandemics for computer-aided diagnosis, e.g. based on medical expert systems
G16H 70/40 - ICT specially adapted for the handling or processing of medical references relating to drugs, e.g. their side effects or intended usage
G16H 20/10 - ICT specially adapted for therapies or health-improving plans, e.g. for handling prescriptions, for steering therapy or for monitoring patient compliance relating to drugs or medications, e.g. for ensuring correct administration to patients
G16H 10/60 - ICT specially adapted for the handling or processing of patient-related medical or healthcare data for patient-specific data, e.g. for electronic patient records
67.
AUTOMATED SUSCEPTIBILITY IDENTIFICATION AND ALERTING IN INFECTIOUS DISEASE OUTBREAKS
Methods, systems, and computer-readable media are disclosed herein for automated susceptibility identification and alerting. An occurrence of an outbreak of an infectious disease occurring at a particular time or time range and at a particular location is determined. In response to determining the occurrence of the outbreak, patient information comprising location information and medical history information is automatically scanned. Patients who are within a predetermined range of the particular location of the outbreak and who have at least one high risk factor corresponding to the outbreak are identified using the patient information. A notification to at least one of the patients who are within the predetermined range and who have the at least one high risk factor corresponding to the outbreak is provided. The notification comprises a representation of an increased risk to the outbreak.
G16H 50/80 - ICT specially adapted for medical diagnosis, medical simulation or medical data mining; ICT specially adapted for detecting, monitoring or modelling epidemics or pandemics for detecting, monitoring or modelling epidemics or pandemics, e.g. flu
G16H 50/30 - ICT specially adapted for medical diagnosis, medical simulation or medical data mining; ICT specially adapted for detecting, monitoring or modelling epidemics or pandemics for individual health risk assessment
G16H 10/60 - ICT specially adapted for the handling or processing of patient-related medical or healthcare data for patient-specific data, e.g. for electronic patient records
H04W 4/021 - Services related to particular areas, e.g. point of interest [POI] services, venue services or geofences
H04W 4/02 - Services making use of location information
Systems, methods, and storage media useful in a healthcare computing platform to build and publish an integrated medical consultation report to a patient's primary electronic medical record are provided. The integrated medical consultation report presents up-to-date objective medical factors from the patient's medical record concurrently with a subjective medical summary from an authoring clinician. The integrated medical consultation report is stored as a unique medical document in the patient's primary electronic record.
G16H 10/60 - ICT specially adapted for the handling or processing of patient-related medical or healthcare data for patient-specific data, e.g. for electronic patient records
G16H 80/00 - ICT specially adapted for facilitating communication between medical practitioners or patients, e.g. for collaborative diagnosis, therapy or health monitoring
A diagnostic and decision support technology is provided for determining the presence, identity, and/or severity of an inherited lysosomal storage disorder. In particular, a mechanism is provided to detect and classify a lysosomal storage disorder in a human patient, which utilizes a logistic regression classifier determined based on a multi-variable-composite-biomarker comprising a specific set of physiological variables of the patient. This multi-variable statistical predictive biomarker approach may be employed for identifying persons whose attributes are consistent with features or glycogen storage diseases, such as late-onset Pompe disease.
G16H 50/20 - ICT specially adapted for medical diagnosis, medical simulation or medical data mining; ICT specially adapted for detecting, monitoring or modelling epidemics or pandemics for computer-aided diagnosis, e.g. based on medical expert systems
G16B 40/00 - ICT specially adapted for biostatistics; ICT specially adapted for bioinformatics-related machine learning or data mining, e.g. knowledge discovery or pattern finding
Methods, systems, and computer-storage media are provided for generating graphical representations of audit events. A party-of-interest is represented by a central node, and one or more peripheral nodes surrounding the central node represent parties having electronic records accessed by the party-of-interest during a selected time frame. The size of the peripheral nodes represents a frequency of access of the node's respective electronic record. Each of the peripheral nodes is actionable enabling a user to view information related to the audit event.
G06F 3/04847 - Interaction techniques to control parameter settings, e.g. interaction with sliders or dials
G16H 10/60 - ICT specially adapted for the handling or processing of patient-related medical or healthcare data for patient-specific data, e.g. for electronic patient records
G06F 3/04842 - Selection of displayed objects or displayed text elements
G06F 3/04817 - Interaction techniques based on graphical user interfaces [GUI] based on specific properties of the displayed interaction object or a metaphor-based environment, e.g. interaction with desktop elements like windows or icons, or assisted by a cursor's changing behaviour or appearance using icons
71.
Gap in Care Determination Using a Generic Repository for Healthcare
By extracting clinical data of any format from respective different sources, a data repository normalized to a generic format is created. A medical domain specific language may be used to interact with the data repository for identifying cohorts and gaps in care for the respective cohorts. Any rules for finding gaps in care are converted into the medical domain specific language for determining gaps. This standardization in both the data repository and rule application may allow for a true cost and time to value solution accessible to many different medical practices.
G06F 40/40 - Processing or translation of natural language
G16H 50/20 - ICT specially adapted for medical diagnosis, medical simulation or medical data mining; ICT specially adapted for detecting, monitoring or modelling epidemics or pandemics for computer-aided diagnosis, e.g. based on medical expert systems
G16H 50/70 - ICT specially adapted for medical diagnosis, medical simulation or medical data mining; ICT specially adapted for detecting, monitoring or modelling epidemics or pandemics for mining of medical data, e.g. analysing previous cases of other patients
Methods, systems, and computer-readable media are provided for facilitating mapping of semantically similar terms between and among two or more information systems. In particular, to facilitate automatic discovery, establishment, and/or statistical validation of linkages between a plurality of different nomenclatures employed by a plurality of information systems, such as multiple electronic health record systems. In embodiments, the imputation of latent synonymy in corpora comprised of samples of historical records from each system enables automated terminology mapping between disparate systems' records, thereby establishing reliable linkages that may subsequently be utilized for realtime decision support, data mining-based research, or other valuable purposes.
G06F 16/28 - Databases characterised by their database models, e.g. relational or object models
G16H 10/60 - ICT specially adapted for the handling or processing of patient-related medical or healthcare data for patient-specific data, e.g. for electronic patient records
G16H 15/00 - ICT specially adapted for medical reports, e.g. generation or transmission thereof
A stroke detection system analyzes images of a person's face over time to detect asymmetric changes in the position of certain reference points that are consistent with sagging or drooping that may be symptomatic of a stroke or TIA. On detecting possible symptoms of a stroke or TIA, the system may alert caregivers or others, and log the event in a database. Identifying stroke symptoms automatically may enable more rapid intervention, and identifying TIA symptoms may enable diagnostic and preventative care to reduce the risk of a future stroke.
H04N 7/18 - Closed-circuit television systems, i.e. systems in which the signal is not broadcast
G16H 40/63 - ICT specially adapted for the management or administration of healthcare resources or facilities; ICT specially adapted for the management or operation of medical equipment or devices for the operation of medical equipment or devices for local operation
G16H 10/60 - ICT specially adapted for the handling or processing of patient-related medical or healthcare data for patient-specific data, e.g. for electronic patient records
H04N 13/204 - Image signal generators using stereoscopic image cameras
H04N 13/207 - Image signal generators using stereoscopic image cameras using a single 2D image sensor
G16H 40/20 - ICT specially adapted for the management or administration of healthcare resources or facilities; ICT specially adapted for the management or operation of medical equipment or devices for the management or administration of healthcare resources or facilities, e.g. managing hospital staff or surgery rooms
G06V 10/42 - Global feature extraction by analysis of the whole pattern, e.g. using frequency domain transformations or autocorrelation
G06V 10/44 - Local feature extraction by analysis of parts of the pattern, e.g. by detecting edges, contours, loops, corners, strokes or intersections; Connectivity analysis, e.g. of connected components
G06V 20/52 - Surveillance or monitoring of activities, e.g. for recognising suspicious objects
G06T 11/60 - Editing figures and text; Combining figures or text
H04N 5/232 - Devices for controlling television cameras, e.g. remote control
A61B 5/1171 - Identification of persons based on the shapes or appearances of their bodies or parts thereof
G08B 13/196 - Actuation by interference with heat, light, or radiation of shorter wavelength; Actuation by intruding sources of heat, light, or radiation of shorter wavelength using passive radiation detection systems using image scanning and comparing systems using television cameras
G16H 30/20 - ICT specially adapted for the handling or processing of medical images for handling medical images, e.g. DICOM, HL7 or PACS
G16H 15/00 - ICT specially adapted for medical reports, e.g. generation or transmission thereof
G16H 80/00 - ICT specially adapted for facilitating communication between medical practitioners or patients, e.g. for collaborative diagnosis, therapy or health monitoring
G16H 40/67 - ICT specially adapted for the management or administration of healthcare resources or facilities; ICT specially adapted for the management or operation of medical equipment or devices for the operation of medical equipment or devices for remote operation
G16H 50/30 - ICT specially adapted for medical diagnosis, medical simulation or medical data mining; ICT specially adapted for detecting, monitoring or modelling epidemics or pandemics for individual health risk assessment
G16H 20/10 - ICT specially adapted for therapies or health-improving plans, e.g. for handling prescriptions, for steering therapy or for monitoring patient compliance relating to drugs or medications, e.g. for ensuring correct administration to patients
74.
UTILIZING ARTIFICIAL INTELLIGENCE TO DETECT OBJECTS OR PATIENT SAFETY EVENTS IN A PATIENT ROOM
Methods and systems are provided for detecting objects or patient safety events in a patient room. Artificial intelligence is utilized to enhance safety issue recognition capabilities by the methods and systems. Sensors collect a series of images and depth data in a room of a patient. Data (corresponding to images and depth data of an object or patient safety event) is received from the sensors and compared to stored data to identify the object or patient safety event. The images are communicated to a central video monitoring system and a user may be prompted to confirm if the object requires learning or a patient safety event occurred (or identify the object or patient safety event) or to provide additional parameters or actions. A patient safety learning system analyzes the data and incorporates the user response to enhance safety issue recognition capabilities of the system and reduce false alerts.
Systems, methods, and computer-readable media are disclosed herein that generate a ternary tree data structure that includes multiple categories (e.g., terminologies) using dynamic array modifications that facilitate sharing of one or more nodes across categories. A plurality of different categories may be added and stored within a single ternary tree data structure such that each categories may be separately queried using the single ternary data structure.
Methods, systems, and computer-readable media are disclosed herein that provide services for automatically facilitate mobile-friendly messages containing identification-scrubbed clinical images transferred between a secure healthcare system and an external application that is accessed on a mobile device. Through the services and using minimal inputs, a scrubbed outgoing message containing patient-specific images is automatically generated and transmitted to a mobile device for a user to review. The services automatically track replies as incoming messages that can be mapped back to one patient and one patient visit using unique identifiers that ensure patient information is not shared outside the secure healthcare system. Also, the services automatically extract clinical finding from incoming messages and provide notifications containing the clinical findings to the appropriate clinician for the patient that corresponds to the reviewed images.
G16H 40/20 - ICT specially adapted for the management or administration of healthcare resources or facilities; ICT specially adapted for the management or operation of medical equipment or devices for the management or administration of healthcare resources or facilities, e.g. managing hospital staff or surgery rooms
G16H 30/40 - ICT specially adapted for the handling or processing of medical images for processing medical images, e.g. editing
G06Q 30/00 - Commerce, e.g. shopping or e-commerce
G06Q 10/10 - Office automation, e.g. computer aided management of electronic mail or groupware; Time management, e.g. calendars, reminders, meetings or time accounting
G16H 15/00 - ICT specially adapted for medical reports, e.g. generation or transmission thereof
G16H 40/67 - ICT specially adapted for the management or administration of healthcare resources or facilities; ICT specially adapted for the management or operation of medical equipment or devices for the operation of medical equipment or devices for remote operation
G06F 16/955 - Retrieval from the web using information identifiers, e.g. uniform resource locators [URL]
G06F 21/62 - Protecting access to data via a platform, e.g. using keys or access control rules
H04L 29/06 - Communication control; Communication processing characterised by a protocol
A61B 5/00 - Measuring for diagnostic purposes ; Identification of persons
77.
Generating asynchronous runtime compatibility in JavaScript applications
Methods and computer-readable media are disclosed herein for generating asynchronous runtime compatible applications from non-asynchronous applications. In embodiments, source code for the application that is not compatible with asynchronous processing is examined. The source code is parsed in order to identify unsafe functions that will cause failures of the application when processed in an asynchronous runtime. The source code corresponding to those unsafe functions is modified by adding asynchronous functions and commands to the source code and restructuring the source code. The modified source code may then be provided to an asynchronous runtime environment as the application is now compatible with asynchronous processing.
Methods, computer systems, and computer storage media are provided for facilitating claims management using planned orders. More particularly, encounter information can be synchronized with clinical system data in a revenue cycle management system so costly editing and delays can be avoided. Initially, an order for the patient during an encounter is received from a clinical system. A clinician may be prompted indicating the order cannot be completed because of a conflict. The revenue cycle management system monitors the clinical system for the missing information corresponding to the conflict. Once the missing information is received, the encounter information is synchronized with the missing information. The synchronized encounter information comprises automated edits that enable a claim corresponding to the encounter to be billable.
G16H 40/20 - ICT specially adapted for the management or administration of healthcare resources or facilities; ICT specially adapted for the management or operation of medical equipment or devices for the management or administration of healthcare resources or facilities, e.g. managing hospital staff or surgery rooms
G06Q 40/00 - Finance; Insurance; Tax strategies; Processing of corporate or income taxes
G06Q 10/10 - Office automation, e.g. computer aided management of electronic mail or groupware; Time management, e.g. calendars, reminders, meetings or time accounting
G06F 16/27 - Replication, distribution or synchronisation of data between databases or within a distributed database system; Distributed database system architectures therefor
Systems, methods and computer-readable media are provided for facilitating patient health care by providing discovery, validation, and quality assurance of nomenclatural linkages between pairs of terms or combinations of terms in databases extant on multiple different health information systems that do not share a set of unified codesets, nomenclatures, or ontologies, or that may in part rely upon unstructured free-text narrative content instead of codes or standardized tags. Embodiments discover semantic structures existing naturally in documents and records, including relationships of synonymy and polysemy between terms arising from disparate processes, and maintained by different information systems. In some embodiments, this process is facilitated by applying Latent Semantic Analysis in concert with decision-tree induction and similarity metrics. In some embodiments, data is re-mined and regression testing is applied to new mappings against an existing mapping base, thereby permitting these embodiments to “learn” ontology mappings as clinical, operational, or financial patterns evolve.
Methods, systems, and computer-readable media are disclosed herein for generating a user-interactive partogram in a graphical user interface using cloud deployment and multi-application integration.
G16H 10/60 - ICT specially adapted for the handling or processing of patient-related medical or healthcare data for patient-specific data, e.g. for electronic patient records
H04L 29/06 - Communication control; Communication processing characterised by a protocol
H04L 29/08 - Transmission control procedure, e.g. data link level control procedure
Methods, systems, and computer-readable media for a system and method are provided for assessing the value of predictive models monitoring medical conditions. Trends in an individual's medical condition are determined based on monitoring values, and the trends are associated with the actions performed in response to the monitoring values and in accordance with the predictive models. The trends may indicate that an individual's condition is improving, worsening, or remaining stable in response to the action taken. Models used for multiple conditions for an individual or for a population of individuals may be assessed in this manner to generate knowledge regarding the performance of the models based on the actions taken. This knowledge may be used to assess the value of the models in terms of the models' performance and may provide insight on way to improve the models.
G16H 50/50 - ICT specially adapted for medical diagnosis, medical simulation or medical data mining; ICT specially adapted for detecting, monitoring or modelling epidemics or pandemics for simulation or modelling of medical disorders
G16H 50/20 - ICT specially adapted for medical diagnosis, medical simulation or medical data mining; ICT specially adapted for detecting, monitoring or modelling epidemics or pandemics for computer-aided diagnosis, e.g. based on medical expert systems
G16H 50/70 - ICT specially adapted for medical diagnosis, medical simulation or medical data mining; ICT specially adapted for detecting, monitoring or modelling epidemics or pandemics for mining of medical data, e.g. analysing previous cases of other patients
82.
AUTOMATED ICON ACCESSIBILITY ASSESSMENT ALGORITHM AND TOOL
Systems, methods, and computer-readable media for providing tools to validate color contrast are provided. To do so, three discrete color check processes are performed to ensure a user is able to identify when an icon is at risk of being inaccessible by some users. A border score considers each pixel at the edge of an icon compared to the background in which it is placed. An area score considers each discrete pixel of an icon compared to the background in which it is placed. A grid score considers a subdivision of an icon compared to the background in which it is placed. Using each of these three independent process, a summative score is provided. The summative score categories the icon into a risk level. Depending on the risk level, the icon may need to be refined to ensure it becomes more accessible.
Methods, systems, and computer-readable media are disclosed herein for improved state identification and prediction in computerized queries. In an aspects, a neural network model is trained via word embedding, using a plurality of workflows having a plurality of steps as input training data. The model may be searched using a string to locate and identify semantic matches as potential results, where the potential results correspond to a specific step and/or a particular workflow. Markov chaining may also be performed, using the potential results, in order to predict one or more additional results, where the additional results correspond to a specific succeeding step within a particular workflow, in some aspects. The results and predicted steps may be displayed.
Methods, systems, and computer-readable media are disclosed herein that provide a comprehensive view that reveals all or nearly all possible method dependencies that are present in client workflows. In aspects, when computer code for a particular method is going to be edited, other methods are identified that have upstream or downstream dependencies relative to the particular method. The methods that will be affected based on the computer code editing can be presented in a user-interactive graphical user interface that facilitates exploration of upstream and downstream dependencies.
Decision support technology is provided for use with patients who may experience respiratory deterioration. A mechanism is provided to determine an indicator of a patient's probability of deterioration of respiratory functioning, which may include calculating a probability of a respiratory deterioration event in patients from whom serial digital recordings of respiratory sounds are acquired. A forecast or score representing a likelihood of deterioration may be generated and used for pulmonary disease prognosis, diagnosis, and/or determining or implementing an appropriate response action such as automatically issuing an alert or notification to a caregiver associated with the patient.
09 - Scientific and electric apparatus and instruments
42 - Scientific, technological and industrial services, research and design
Goods & Services
Computer software for use in the healthcare field, namely, for patient registration, admission discharge and transfer of patients, automating billing processes, patient accounting, submitting claims to insurance companies or other payors of healthcare services, reimbursement management, and integrating financial information. Providing online, non-downloadable software in the healthcare field, namely, providing a software platform for patient registration, admission discharge and transfer of patients, automating billing processes, patient accounting, submitting claims to insurance companies or other payors of healthcare services, reimbursement management, and integrating financial information.
09 - Scientific and electric apparatus and instruments
42 - Scientific, technological and industrial services, research and design
Goods & Services
(1) Computer software for use in the healthcare field, namely, for patient registration, admission discharge and transfer of patients, automating billing processes, patient accounting, submitting claims to insurance companies or other payors of healthcare services, reimbursement management, and integrating financial information (1) Providing online, non-downloadable software in the healthcare field, namely, providing a software platform for patient registration, admission discharge and transfer of patients, automating billing processes, patient accounting, submitting claims to insurance companies or other payors of healthcare services, reimbursement management, and integrating financial information
88.
GENERATION OF SYNTHETIC ALERTS AND UNIFIED DASHBOARD FOR VIEWING MULTIPLE LAYERS OF DATA CENTER SIMULTANEOUSLY
Systems and methods provide for automatically generating a data model that includes a first data feed conforming to industry standards where only alerts for alert triggering violations are provided. The data model further comprises a second data feed that includes both the alerts from the first data feed and a plurality of synthetic alerts for any violations that occur in a data center but do not qualify as alert triggering violations. This second data feed provides a complete picture of the performance of a data center's devices and allows for accurate analytics.
Methods and systems determine risks of deterioration of hospitalized or other monitored or cared-for patients, for example in a treatment facility such as a hospital or under home-health care. In embodiments, a warning or other instruction is issued to medical professionals to alert them that certain patients have moderate or high risk of transfer to a higher level of care or should be monitored more frequently. A medical professional can accept alerts regarding prediction of deterioration, causing a prophylactic transfer or increased monitoring, or a transfer or monitoring order can occur automatically. Data relating to all patients in a unit of a medical facility can be viewed including warnings relating to risk of transfer or deterioration, so that a medical facility can intervene prior to an event such as a cardiac event and/or plan to accommodate patients at higher levels of care or monitoring.
A61B 5/00 - Measuring for diagnostic purposes ; Identification of persons
G16H 50/20 - ICT specially adapted for medical diagnosis, medical simulation or medical data mining; ICT specially adapted for detecting, monitoring or modelling epidemics or pandemics for computer-aided diagnosis, e.g. based on medical expert systems
G16H 50/30 - ICT specially adapted for medical diagnosis, medical simulation or medical data mining; ICT specially adapted for detecting, monitoring or modelling epidemics or pandemics for individual health risk assessment
G16H 80/00 - ICT specially adapted for facilitating communication between medical practitioners or patients, e.g. for collaborative diagnosis, therapy or health monitoring
G16H 40/63 - ICT specially adapted for the management or administration of healthcare resources or facilities; ICT specially adapted for the management or operation of medical equipment or devices for the operation of medical equipment or devices for local operation
G16H 40/67 - ICT specially adapted for the management or administration of healthcare resources or facilities; ICT specially adapted for the management or operation of medical equipment or devices for the operation of medical equipment or devices for remote operation
G16H 40/20 - ICT specially adapted for the management or administration of healthcare resources or facilities; ICT specially adapted for the management or operation of medical equipment or devices for the management or administration of healthcare resources or facilities, e.g. managing hospital staff or surgery rooms
G16H 10/60 - ICT specially adapted for the handling or processing of patient-related medical or healthcare data for patient-specific data, e.g. for electronic patient records
90.
AUTOMATED WORKFLOW ACCESS BASED ON CLINICAL USER ROLE AND LOCATION
Systems, methods, computer-readable media for automating displays based on admissions, transfers, and discharges are provided. In embodiments, a location associated with a clinician is detected. A role associated with the clinician authenticated to a first device is determined. One or more applications associated with the clinician based on the location and the role is automatically launched on the first device. In embodiments, authentication requests from the clinician are received for a second device. A session associated with the one or more applications is suspended on the first device and resumed on the second device.
G06F 3/023 - Arrangements for converting discrete items of information into a coded form, e.g. arrangements for interpreting keyboard generated codes as alphanumeric codes, operand codes or instruction codes
G16H 10/60 - ICT specially adapted for the handling or processing of patient-related medical or healthcare data for patient-specific data, e.g. for electronic patient records
G16H 40/20 - ICT specially adapted for the management or administration of healthcare resources or facilities; ICT specially adapted for the management or operation of medical equipment or devices for the management or administration of healthcare resources or facilities, e.g. managing hospital staff or surgery rooms
A61B 34/10 - Computer-aided planning, simulation or modelling of surgical operations
91.
COMPUTER MODELING AND EVALUATION OF INSURANCE PRICING AND RISK
Systems, methods and computer-readable media are provided for determining a premium for a proposed insurance coverage. In various embodiments, a plurality of context variables can be defined related to proposed coverage. Based on defined context variables, historical claim events are extracted from one or more sources of claims data. Extracted historical claim events may be representative of the proposed coverage. Historical claim events can be aggregated based on a time period to form aggregated claims data per time period. The aggregated data can then be used to determine a historical volatility time series based on differences between logarithms of the aggregated claims data per time period for a plurality of time periods. Additionally or alternately, the aggregated claims data per time period can be used to determine a fit of the aggregated data to one or more distributions. The fit can be evaluated, such as based on a fit parameter, to select a distribution. A calculation can then be performed to determine a premium. If a normal distribution is selected, the historical volatility time series can be used to estimate a volatility. This estimated volatility can then be used to calculate a premium.
G16H 50/30 - ICT specially adapted for medical diagnosis, medical simulation or medical data mining; ICT specially adapted for detecting, monitoring or modelling epidemics or pandemics for individual health risk assessment
92.
Decision support system for anticipating a myocardial ischemic event
A catastrophe-theoretic approach is provided for predicting an occurrence of an ischemic myocardial event (e.g., acute myocardial infarction) for a human patient based on a time series of monitored vital signs values measured from a patient, and in some instances, for providing advanced notice to clinicians or caregivers when such an ischemic event is forecasted or modifying treatment for the patient, according to the predicted likelihood. In particular, an ischemic heart disease management system is provided for determining a likelihood of near-term future significant myocardial ischemia in persons with coronary artery disease. Embodiments of the disclosure described herein may provide a forecasted risk for future significant myocardial ischemia within a time horizon comprising a future time interval. In one embodiment, the future time interval is from 30 min to approximately 4 hours into the future, and may be dependent on the frequency of vital signs measurements.
A61B 5/02 - Measuring pulse, heart rate, blood pressure or blood flow; Combined pulse/heart-rate/blood pressure determination; Evaluating a cardiovascular condition not otherwise provided for, e.g. using combinations of techniques provided for in this group with electrocardiography; Heart catheters for measuring blood pressure
A61B 5/00 - Measuring for diagnostic purposes ; Identification of persons
A61B 5/145 - Measuring characteristics of blood in vivo, e.g. gas concentration, pH-value
A61B 5/0205 - Simultaneously evaluating both cardiovascular conditions and different types of body conditions, e.g. heart and respiratory condition
A61B 5/021 - Measuring pressure in heart or blood vessels
Methods, computer-readable storage media, and systems for visually grouping related diagnoses and/or encounter/visit data together to provide treatment providers and patients with a summarized view of a patient's treatment per condition and how that treatment has changed over time are provided. Also provided are methods, computer-readable storage media, and systems for conflating related diagnoses and/or encounter data into a visual representation that summarizes a patient's treatment per condition and provides quickly discernible insight into how such treatment has changed over time.
G16H 15/00 - ICT specially adapted for medical reports, e.g. generation or transmission thereof
G16H 70/20 - ICT specially adapted for the handling or processing of medical references relating to practices or guidelines
G16H 50/70 - ICT specially adapted for medical diagnosis, medical simulation or medical data mining; ICT specially adapted for detecting, monitoring or modelling epidemics or pandemics for mining of medical data, e.g. analysing previous cases of other patients
G16H 30/20 - ICT specially adapted for the handling or processing of medical images for handling medical images, e.g. DICOM, HL7 or PACS
A computerized method is presented for improving medical records of an individual based on received information from a device or wearable, the method comprising: retrieving from a record-keeping database medical-related information associated with the individual; retrieving from a device associated with the individual a measurable factor; determining, based at least partly on the medical-related information, that the measurable factor poses a medical risk to the individual; and communicating instructions to the record-keeping database to store, in association with the individual, information related to the medical risk. Other methods may associate a location with a medical risk. Other methods may aggregate medical information received from devices or wearables and associate it with a location. Mapping this information with regard to locations may allow early prediction of an epidemic.
G16H 10/60 - ICT specially adapted for the handling or processing of patient-related medical or healthcare data for patient-specific data, e.g. for electronic patient records
G16H 50/30 - ICT specially adapted for medical diagnosis, medical simulation or medical data mining; ICT specially adapted for detecting, monitoring or modelling epidemics or pandemics for individual health risk assessment
95.
METHODS AND SYSTEM FOR HEMORRHAGE-SPECIFIC DETERMINATIONS
Methods and a system are provided for assessing postpartum hemorrhage risk and postpartum hemorrhage stages in a clinical setting. Generally, a clinician may indicate that the mass of several bloody items, indicated in type and quantity, is to be measured using a scale. The mass of bloody items is compared to the known unused dry mass of such items in order to accurately determine the quantitative blood loss (QBL) of a patient at the bedside. The cumulative QBL can be updated by weighing additional items. Based on the cumulative QBL, the patient's vital signs, and other factors, a corresponding hemorrhage stage is identified and communicated to the clinician. Recommendations specific to the hemorrhage stage are provided to a clinician. Some recommendations are selectable actions that trigger automatic placement of medical orders and notifications to relevant medical services, such as a blood bank or anesthesia.
A61B 5/02 - Measuring pulse, heart rate, blood pressure or blood flow; Combined pulse/heart-rate/blood pressure determination; Evaluating a cardiovascular condition not otherwise provided for, e.g. using combinations of techniques provided for in this group with electrocardiography; Heart catheters for measuring blood pressure
G16H 10/60 - ICT specially adapted for the handling or processing of patient-related medical or healthcare data for patient-specific data, e.g. for electronic patient records
G16H 50/30 - ICT specially adapted for medical diagnosis, medical simulation or medical data mining; ICT specially adapted for detecting, monitoring or modelling epidemics or pandemics for individual health risk assessment
G01G 19/00 - Weighing apparatus or methods adapted for special purposes not provided for in groups
96.
VIRTUAL AUGMENTATION OF CLINICAL CARE ENVIRONMENTS
Systems and methods for employing virtual environmental augmentation in clinical care environments to enhance a clinician's in-the-moment knowledge, leverage past experiences of the clinician and others, and improve the quality of patient care are provided. Such virtual environmental augmentation may align with prior-established, evidence-based clinical processes and enhance the clinician's in-the-moment knowledge by extracting relevant data from one or more clinical sources and presenting a virtual representation of at least a portion of the extracted data (or a summary, exemplification, or interpretation thereof) in the clinician's field-of-view while the clinician is present in a clinical care environment and is utilizing an environmental augmentation device. Such environmental augmentation additionally may facilitate real-time documentation enabling more complete clinical records and ultimately improving the quality of patient care.
G16H 30/40 - ICT specially adapted for the handling or processing of medical images for processing medical images, e.g. editing
G16H 40/20 - ICT specially adapted for the management or administration of healthcare resources or facilities; ICT specially adapted for the management or operation of medical equipment or devices for the management or administration of healthcare resources or facilities, e.g. managing hospital staff or surgery rooms
G16H 30/20 - ICT specially adapted for the handling or processing of medical images for handling medical images, e.g. DICOM, HL7 or PACS
Systems and methods are provided for injury characterization including detecting matches of an individual subject's record (such as an athlete's record) with collections of other subjects records, based on serial, longitudinal patterns, for facilitating athlete health and training, preventive and rehabilitation medicine, and risk management in athletics. In an embodiment, time series are formed from information pertaining to successive longitudinal episodes of injury and the circumstances in which the injuries were incurred; calculating time-series K-nearest-neighbor clusters and distances for each such combination; determining the cluster to which a given candidate player injury record is nearest or belongs, and prescribing an injury-risk reduction intervention specific to the plurality of hazards that are characteristic of trajectories that are members of that cluster and that are deemed to be relevant to reducing or mitigating those hazards and thereby are efficacious in preventing subsequent injuries that are prevalent in that trajectory cluster.
G16H 40/20 - ICT specially adapted for the management or administration of healthcare resources or facilities; ICT specially adapted for the management or operation of medical equipment or devices for the management or administration of healthcare resources or facilities, e.g. managing hospital staff or surgery rooms
G16H 50/30 - ICT specially adapted for medical diagnosis, medical simulation or medical data mining; ICT specially adapted for detecting, monitoring or modelling epidemics or pandemics for individual health risk assessment
98.
Proximity-based mobile-device updates of electronic health records
A system, method, and computer-readable media are provided for facilitating clinical decision making, and in particular, decision making based on a third party's clinical situation by determining and providing useful, up-to-date information, such as patient-related information to a decision maker. In one embodiment, a user first identifies an information item concerning a patient. Based on that item, a set of related information items is determined and prioritized, and a reference pointer, which identifies the set of related information, is generated. The reference pointer is communicated to the user's mobile device. Subsequently, the user's mobile device requests information from the set of information items associated with the reference pointer, and provides information authorization information. Following authentication of the user's credentials, updates of information from the set of information items may be communicated to the user's mobile device as they become available.
G16H 10/65 - ICT specially adapted for the handling or processing of patient-related medical or healthcare data for patient-specific data, e.g. for electronic patient records stored on portable record carriers, e.g. on smartcards, RFID tags or CD
G16H 10/60 - ICT specially adapted for the handling or processing of patient-related medical or healthcare data for patient-specific data, e.g. for electronic patient records
G16H 40/63 - ICT specially adapted for the management or administration of healthcare resources or facilities; ICT specially adapted for the management or operation of medical equipment or devices for the operation of medical equipment or devices for local operation
G06F 21/62 - Protecting access to data via a platform, e.g. using keys or access control rules
G06F 16/90 - Information retrieval; Database structures therefor; File system structures therefor - Details of database functions independent of the retrieved data types
G06F 16/955 - Retrieval from the web using information identifiers, e.g. uniform resource locators [URL]
A stateless, on-demand semantic indexing and search service for a health information exchange is provided that anticipatorily fetches data from one or more external sources, extracts semantic concepts from textual documents, and serves an in-memory semantic search index to users to ease finding of relevant patient data across a set of distributed health record data sources. Clinicians may search for not only text, but for semantic concepts, and the search index is able to return relevant results regardless of whether the source information is located inside or outside the local electronic health record. Predictive algorithms may be incorporated to pre-fetch, semantically process and index data for patients likely to be searched in an upcoming time window. Activity indicators for clinicians and patients may be utilized to pre-fetch, semantically process, and index data.
G16H 10/60 - ICT specially adapted for the handling or processing of patient-related medical or healthcare data for patient-specific data, e.g. for electronic patient records
G06F 16/22 - Indexing; Data structures therefor; Storage structures
G06F 16/31 - Indexing; Data structures therefor; Storage structures
100.
SYSTEM AND METHOD FOR SMART SEARCHING FOR CONVERSION ACHIEVEMENT
Methods, systems and computer storage media are disclosed for providing resources to a platform issue. Embodiments describe associating educational resources and an event resource to resolve the platform issue.
G06Q 10/06 - Resources, workflows, human or project management, e.g. organising, planning, scheduling or allocating time, human or machine resources; Enterprise planning; Organisational models
G16H 10/60 - ICT specially adapted for the handling or processing of patient-related medical or healthcare data for patient-specific data, e.g. for electronic patient records
