Abstract: Methods, systems, and computer-readable media are disclosed herein for a concurrent comparative tool for assessing multiple versions of a data model in a pre-deployment environment to ensure that any subsequently deployed version will perform than a current version of the data model. In aspects, the tool extracts observed and predictive data for various versions and comparatively evaluates the performance measures of each version. The performance measures can be validated across the versions to determine and select a leading version that has demonstrated improve technological performance and predictive accuracy. The leading version can be deployed.

Abstract: Technologies are provided for an improved classifier apparatus and processes for improving the accuracy of classification technology including example applications of such classifiers. A process includes applying clustering to variables contributing to the classification task. The clusters may be represented in a 1-dimensional, 2-dimensional, or 3-dimensional matrix that is a spatial abstraction of the interrelationships. A convolutional transformation may be applied to the matrix so as to reduce the effective dimensionality of the classification problem and improve the signal-to-noise ration. A deep learning neural network method may be applied to the transformed network to generate an improved classification model, which may be utilized by a decision support tool. One embodiment comprises a decision support tool for detecting risk of venous thrombosis and venous thromboembolism (VTE) in a patient, based on phenotype and genomics information.

Abstract: Methods, systems, and computer-readable media for rapid event voice documentation are provided herein. The rapid event voice documentation system captures verbalized orders and actions and translates that unstructured voice data to structured, usable data for documentation. The voice data captured is tagged with metadata including the name and role of the speaker, a time stamp indicating a time the data was spoken, and a clinical concept identified in the data captured. The system automatically identifies orders (e.g., medications, labs and procedures, etc.), treatments, and assessments/findings that were verbalized during the rapid event to create structured data that is usable by a health information system and ready for documentation directly into an EHR. The system provides all of the captured data including orders, assessment documentation, vital signs and measurements, performed procedures, and treatments, and who performed each, available for viewing and interaction in real time.

Abstract: Various tools are disclosed for providing assistive or augmentative means to enhance the fluency and accuracy of persons having speech disabilities. These technologies may automatically ascertain and dynamically improve the accuracy with which automatic speech recognition (ASR) systems recognize utterances of persons having impaired speech conditions. In an embodiment, digitized audio information about a speaker’s utterance is processed to determine a set of candidate words matching the utterance. From these candidate words, a set of concepts is determined using a finite state machine model. A pictogram representing each concept is identified and presented to the speaker so that the speaker may select the pictogram corresponding to the best match of his or her intended meaning associated with the utterance. An action corresponding to speaker’s selection then may be performed. For example, displaying or synthesizing speech from textual information describing the selected concept.

Abstract: Methods, computer systems, and computer storage media are provided for utilizing machine learning to verify payers and/or health plans. HIPAA transactions can be utilized to train a machine learning model to intelligently link payers and/or health plans to specific employers. Initially, transaction data is received from electronic data interchange (EDI) insurance transactions. The transaction data comprises data corresponding to a plurality of employers, a plurality of payers, and a plurality of health plans provided by the plurality of payers. A machine learning model is trained with the transaction data to build a mapping of the plurality of employers, the plurality of payers contracted with each employer of the plurality of employers, and the plurality of health plans provided by the plurality of payers for each employer of the plurality of employers. The machine learning model is utilized to verify the scan data is mapped in accordance with the mapping.

Abstract: Methods, systems, and computer-readable media are disclosed herein to provide rule-based reconciliation of records. Specifically, rules are utilized to reconcile one or more records and identify duplicates therein. Once duplicate records are identified, one or more ranking sets can be utilized to identify which of the duplicate records to write to the system.

Abstract: Various tools are disclosed for providing assistive or augmentative means to enhance the fluency and accuracy of persons having speech disabilities. These technologies may automatically ascertain and dynamically improve the accuracy with which automatic speech recognition (ASR) systems recognize utterances of persons having impaired speech conditions. In an embodiment, digitized audio information about a speaker’s utterance is processed to determine a set of candidate words matching the utterance. From these candidate words, a set of concepts is determined using a finite state machine model. A pictogram representing each concept is identified and presented to the speaker so that the speaker may select the pictogram corresponding to the best match of his or her intended meaning associated with the utterance. An action corresponding to speaker’s selection then may be performed. For example, displaying or synthesizing speech from textual information describing the selected concept.

Abstract: 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.

Abstract: 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.

Abstract: 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 patent 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.

Abstract: Computerized systems and methods are provided to intelligently and dynamically manage a data center comprising at least one server and at least one central manager. The central manager is programmed to access the at least one server on a predetermined schedule to determine whether at least one application is functioning properly by determining a functionality level. Alternatively, the central manager determines whether the at least one server is actively used by determining an activity level for the server. Based on the central manager's determinations, the system dynamically adjusts the power level of the server, resulting in reduced power consumption and a reduction in wasted resources and unnecessary processing power in the management of servers in a data center.

Abstract: 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.

Abstract: 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.

Abstract: 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.

Abstract: 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.

Abstract: An improved decision support tool is provided for detecting and treating human patients at risk for having (or developing) venous thromboembolism VTE. The tool determines a quantitative probability of VTE by utilizing a smart sensor based on a particular machine-learning model for detecting specific biomarkers determined to be related to VTE. In particular, a quantitative probability of VTE may be determined via a model based on interrelationships between multiple components of the human body's complement cascade and their coupling to coagulation processes. In one aspect, a quasi-Dirichlet distribution “mixture” relationship between total hemolytic complement (CH50) activity and complement protein C3 levels is employed as part of a smart sensor and decision support tool to provide predictive, diagnostic, and prognostic applications and for guiding prevention and treatment of acute VTE. Where the smart sensor determines a risk for VTE, then the decision support tool may initiate an intervening action.

Abstract: Systems, methods, and user interfaces infer data organization for display. An inference system learns patterns of how various healthcare items are typically grouped on a display so data can be aggregated and displayed in appropriate groupings to a clinician user. From a user perspective, it appears as though the display has been manually edited or a mapping has been created so that items are displayed in appropriate groups, even though neither editing nor mapping has been performed.

Abstract: Methods, systems, and computer-readable media are provided for routing radio-frequency identification (RFID) location data from an RFID tag reader to a record-keeping unit. A first tagging entry is received from a first record-keeping unit. The information associated with the first tagging entry is stored in a data store. A first set of location data is received, indicating that the RFID tag of the first item has been read by an RFID tag reader. It is algorithmically determined that the received location data corresponds to the first tagging entry received from the first record-keeping unit. The first set of location data is communicated to the first record-keeping unit.

Abstract: System and methods for controlling healthcare devices and systems using voice commands are presented. In some aspects a listening device may receive voice command from a person. The voice command may be translated into human readable or machine readable text via a speech-to-text service. A control component may receive the text and send device-specific instructions to a medical device associated with a patient based on the translated voice command. In response to the instructions, the medical device may take an action on a patient. Some examples of actions taken may include setting an alarm limit on a monitor actively monitoring a patient and adjusting the amount of medication delivered by an infusion pump. Because these devices may be controlled using a voice command, in some cases, no physical or manual interaction is needed with the device. As such, multiple devices may be hands-free controlled from any location.

Abstract: A computer-implemented trading platform, system, and method are provided for facilitating the trading and accounting for health quality offsets. So-called “health quality credits” related to emissions of ‘potentially avoidable complications’ (PACs) or ‘potentially avoidable mortality’ (PAMs). Emissions trading or “cap-and-trade” is an administrative approach used to control emissions that degrade public-goods assets by providing economic incentives for achieving and sustaining economically significant reductions in the emissions of pollutants that impair public goods such as clean air or health.