Abstract: 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.

Abstract: 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.

Abstract: 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.

Abstract: Systems, methods, and computer-readable storage media are provided for determining and ascribing clinical conditions or diagnoses to patients and provide them to a caregiver, such as attending clinicians or other appropriate health services personnel. In particular, embodiments of the disclosure determine likely phenotypic findings that are salient to the decision-making context for a current human patient, based on anticipative sequence-mining and trajectory-mining. A sequential pattern mining and sequence itemset matching system is provided for determining likely, temporally-relevant concepts that are manifested in the information that is produced during the course of a patient's care. A clinician or caregiver may be provided the sequence itemset matching by generating a list or notice. In addition or alternatively, the results may be stored in an EHR associated with the patient.

Abstract: Methods and systems for enhanced natural language processing of clinical documentation are provided. Using natural language processing, a clinical condition is extracted from unstructured data within a current electronic document. A clinical ontology identifying itemsets associated with the clinical condition is retrieved, and indicators of relevant clinical concepts, as identified from the ontology, are searched from within the patient's longitudinal record, which comprises documentation from at least a prior encounter. Based on the whether the clinical concepts are present in the patent's record, a confidence is assigned to the NLP-extracted clinical condition, and one or more actions may be performed.

Abstract: A system, method, and computer-readable media are provided for facilitating clinical decision making, and in particular, facilitating treatment of a person having congestive heart failure. The method includes the step of receiving patient information for a patient. The method also includes the steps of determining whether the patient information suggests a trigger event, and upon determining a trigger event, determining at least one goal associated with the trigger event. The method also includes the steps of selecting a first plan, from a library of plans, corresponding to the goal and executing the plan, which further includes determining a solver to determine patient conditions or recommended treatments, receiving parameters for the determined solver, and preparing patient information for the determined solver.

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 and methods are provided for quantitatively and objectively characterizing sleep architecture in normal individuals and persons with various health conditions. Embodiments of the invention facilitate characterizing temporal-pattern information of an individual's sleep, such as measured by electroencephalography (EEG), for identifying persons with abnormalities in the temporal-pattern information, sequences or durations of their stages of sleeping (“sleep architecture”), for facilitating selecting appropriate therapy or treatment, and for monitoring the effectiveness of such therapy or treatment. In one aspect, a set of time series are formed by electronically representing and storing information pertaining to brain activity, such as EEG hypnogram or sleep information, over a multi-night span.

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: Methods, computer systems, and computer readable media for transforming raw healthcare data into relevant healthcare data are provided. Transformation of raw healthcare data into relevant data is accomplished by receiving raw data from a plurality of disparate data sources, indexing the data, and mapping the data. Embodiments transform raw data into relevant data through the use of natural language processing, synonymy and ontology mapping, and adaptive knowledge processing. The relevant data is stored in a one record that includes information necessary to understand and represent that patient.

Abstract: 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.

Abstract: Methods, computer systems, and computer readable media for transforming raw healthcare data into relevant healthcare data are provided. Transformation of raw healthcare data into relevant data is accomplished by receiving raw data from a plurality of disparate data sources, indexing the data, and mapping the data. Embodiments transform raw data into relevant data through the use of natural language processing, synonymy and ontology mapping, and adaptive knowledge processing. The relevant data is stored in a one record that includes information necessary to understand and represent that patient.

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: 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 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 and methods are provided for managing treatment of children with a congenital cyanotic heart condition such as Tetralogy of Fallot (ToF) including determining predicted survival probabilities within a timeframe wherein patients await medical treatment such as surgical correction, based on amounts of a biomarker, such as BNP (brain natriuretic peptide) in serial samples of blood plasma from the subject and determining a Tetralogy of Fallot Index (TOFI®) score from the biomarker values. Some embodiments use TOFI score to determine severity and include scheduling and prioritizing medical treatment for patients based on the severity. In some embodiments, the TOFI score is calculated from a plurality of biomarker measurements, which are log-transformed and z-score transformed, by a mathematical survival predictive model, such as a Cox Proportional Hazards model.

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: A system, method, and computer-readable media are provided for facilitating clinical decision making, and in particular, facilitating treatment of a person having congestive heart failure. The method includes the step of receiving patient information for a patient. The method also includes the steps of determining whether the patient information suggests a trigger event, and upon determining a trigger event, determining at least one goal associated with the trigger event. The method also includes the steps of selecting a first plan, from a library of plans, corresponding to the goal and executing the plan, which further includes determining a solver to determine patient conditions or recommended treatments, receiving parameters for the determined solver, and preparing patient information for the determined solver.

Abstract: 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.

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.