Abstract: Methods, systems, and computer storage media are provided for predicting a probability of acute deterioration for a specific patient. Various discrete measurements are taken regarding the patient's current health. Those measurements are used to determine a PPOD score, which is displayed for clinicians.

Abstract: A system, methods and computer-readable media are provided for the automatic identification of patients according to near-term risk of sudden kinematic injury (falling). Embodiments of the invention are directed to event prediction, risk stratification, and optimization of the assessment, communication, and decision-making to prevent falling in humans, and in one embodiment take the form of a platform for wearable, mobile, unteathered monitoring devices with embedded decision support. Thus the aim of embodiments of the present invention relates to automatically identifying persons who are at risk for falls through the use of an inexpensive, noninvasive, portable, wearable electronic device and sensors equipped with signal-processing software and statistical predictive algorithms that calculate stability-theoretic measures derived from the digital accelerometer and gyroscope timeseries acquired by the device.

Abstract: Methods, systems, and computer storage media are provided for monitoring of the internal consistency and reliability of health information about a patient that is generated by a plurality of respondents and exchanged between more than two users of systems that store and maintain such health information.

Abstract: Methods, systems, and computer storage media are provided for predicting a probability of acute deterioration for a specific patient. Various discrete measurements are taken regarding the patient's current health. Those measurements are used to determine a PPOD score, which is displayed for clinicians.

Abstract: Systems and methods are provided for aiding in the development of Business Process Model (BPM) design. A BPM Design is created by a design editor, and contains model data that describes the design. The design is stored in a datastore. Sets of measurements are derived from the model data that express measures such as complexity, maintainability, or productivity of the design. A measurement calculator derives sets of measurements based on model data from designs. A design planner accesses the datastore and makes use of measurements as an aid to BPM Design. A display generator receives measurements and processes them so that they may be displayed to a user and readily interpreted as an aid to BPM Design, development, or management.

Abstract: Systems, methods and computer-readable media are provided for automatic identification of patients according to near-term risk of ventricular arrhythmias and sudden cardiac death (SCD). Embodiments of the invention are directed to event prediction, risk stratification, and optimization of the assessment, communication, and decision-making to prevent SCD, and in one embodiment take the form of a platform for wearable, mobile, unteathered monitoring devices with embedded decision support. Thus embodiments relate to automatically identifying persons at risk for arrhythmias and SCD through the use of noninvasive, portable, wearable electronic device and sensors equipped with signal-processing software and statistical predictive algorithms that calculate stability-theoretic measures derived from the digital electrocardiogram timeseries acquired by the device.

Abstract: A system, methods and computer-readable media are provided for the automatic identification of patients according to near-term risk of sudden kinematic injury (falling). Embodiments of the invention are directed to event prediction, risk stratification, and optimization of the assessment, communication, and decision-making to prevent falling in humans, and in one embodiment take the form of a platform for wearable, mobile, unteathered monitoring devices with embedded decision support. Thus the aim of embodiments of the present invention relates to automatically identifying persons who are at risk for falls through the use of an inexpensive, noninvasive, portable, wearable electronic device and sensors equipped with signal-processing software and statistical predictive algorithms that calculate stability-theoretic measures derived from the digital accelerometer and gyroscope timeseries acquired by the device.

Abstract: A system and method for receiving medical or other database information and pregrouping and extending that data include a data enhancement layer configured to generate additional stored dimensions capturing the data and relevant attributes. Data sources such as hospitals, laboratories and others may therefore communicate their clinical data to a central warehousing facility which may assemble and extend the resulting aggregated data for data mining purposes. Varying source format and content may be conditioned and conformed to a consistent physical or logical structure. The source data may be extended and recombined into additional related dimensions, pre-associating meaningful attributes for faster querying and storage.

Abstract: An optimization methodology is employed to match vibratory inhaler devices having certain characteristics to the particular anatomical and acoustic properties of a patient's vocal tract, in order to achieve the most effective dispersion of a dry powder medicament using inspiratory effort of a user of the inhaler. In embodiments, optimization involves employing one or more measurements of acoustic frequency spectrum properties as well as one or more anatomical/geometric measurements of the structures comprising the particular patient's mouth, pharynx, and upper respiratory tract and matching a vibratory inhalation device that corresponds thereto.

Abstract: A multi-variable statistical predictive leading-indicator approach is employed for identifying newborns at risk of clinically significant hyperbilirubinemia and for determining to administer interventions to at-risk newborns. In embodiments, a multi-variable logistic regression statistical model capable of calculating a probability of clinically significant hyperbilirubinemia is generated. Using an input data set for a newborn and the multi-variable logistic regression statistical model, a probability of clinically significant hyperbilirubinemia is determined for the newborn and presented to a clinician.

Abstract: Optimal assignment of clients to client-sets, resources to resource-sets, and client-sets to resource-sets in a server farm allows for periodic re-balancing of the load as client usership and concurrent-user activity fluctuate. Unique combinations of clients are generated as candidate client-sets, and historical load measurements for clients in each candidate client-set are summed. Summed loads for the candidate client-sets are compared against available resources of resource-sets. An objective function is employed to identify optimal assignment of clients to client-sets, resources to resource-sets, and client-sets to resource-sets.

Abstract: A system and method for receiving medical or other database information and pregrouping and extending that data include a data enhancement layer configured to generate additional stored dimensions capturing the data and relevant attributes. Data sources such as hospitals, laboratories and others may therefore communicate their clinical data to a central warehousing facility which may assemble and extend the resulting aggregated data for data mining purposes. Varying source format and content may be conditioned and conformed to a consistent physical or logical structure. The source data may be extended and recombined into additional related dimensions, pre-associating meaningful attributes for faster querying and storage. Users running analytics against the resulting medical or other datamarts may therefore access a richer set of related information as well as have their queries and other operations run more efficiently.

Abstract: A method and system suitable for automated adjustment of information represented in the transaction order records from clinical information systems of hospitals, clinics, and emergency rooms, in such a manner as to accurately reflect differences in access to care. Techniques from statistical processing are combined in a method that allows for optimization of the parameters such that statistical hypothesis testing using conventional parametric tests are valid and feasible, on account of close approximation to Gaussian normal distribution. The method and system is designed so as to be robust against wide variations in population density and transportation infrastructure, as reflects remote, rural, suburban, and metropolitan environments. Once optimized, the method and system can achieve reliable performance with regard to longitudinal measurement of health access indicators, which are used in planning and managing health services.

Abstract: Methods of making and using labeled macrophages are described.

Abstract: A method and system suitable for automated surveillance of intensive care unit patients for information denoting likelihood of in-hospital survival or mortality, represented in the timeseries of scoring systems such as APACHE III. Techniques from digital signal processing and Lyapunov stability analysis are combined in a method that allows for optimization of statistical hypothesis testing that is robust against short time series of as few as five time points. Once optimized, the method and system can achieve high-sensitivity high-specificity classification of survivorship, while avoiding false-positive prediction of mortality.

Abstract: A method and system suitable for automated surveillance of intensive care unit patients for information denoting likelihood of in-hospital survival or mortality, represented in the timeseries of scoring systems such as APACHE III. Techniques from digital signal processing and Lyapunov stability analysis are combined in a method that allows for optimization of statistical hypothesis testing that is robust against short time series of as few as five time points. Once optimized, the method and system can achieve high-sensitivity high-specificity classification of survivorship, while avoiding false-positive prediction of morality.

Abstract: A method and system suitable for automated surveillance for disease detection and particularly for syndromic information represented in the transaction order records from clinical information systems of hospitals, clinics, and emergency rooms. Patient's findings and conditions expressed as order annotations may be combined with evidence recorded by physicians in a syndromic classifier software application that yields daily counts of proband cases possibly denoting the occurrence of a bioterrorist-caused illness. Techniques from digital signal processing and statistical spatiotemporal image processing are combined in a method that allows for optimization of the parameters of the signal processing and statistical hypothesis testing, prediction for planning and decision-making, and inferencing. Once optimized, the method and system can achieve high-sensitivity high-specificity detection of true occurrences of syndromic illness such as bioterrorism, while avoiding false-alarm signals.

Abstract: A method and system suitable for automated surveillance of intensive care unit patients for information denoting likelihood of in-hospital survival or mortality, represented in the timeseries of scoring systems such as APACHE III. Techniques from digital signal processing and Lyapunov stability analysis are combined in a method that allows for optimization of statistical hypothesis testing that is robust against short time series of as few as five time points. Once optimized, the method and system can achieve high-sensitivity high-specificity classification of survivorship, while avoiding false-positive prediction of mortality.

Abstract: A method and system suitable for automated adjustment of information represented in the transaction order records from clinical information systems of hospitals, clinics, and emergency rooms, in such a manner as to accurately reflect differences in access to care. Techniques from statistical processing are combined in a method that allows for optimization of the parameters such that statistical hypothesis testing using conventional parametric tests are valid and feasible, on account of close approximation to Gaussian normal distribution. The method and system is designed so as to be robust against wide variations in population density and transportation infrastructure, as reflects remote, rural, suburban, and metropolitan environments. Once optimized, the method and system can achieve reliable performance with regard to longitudinal measurement of health access indicators, which are used in planning and managing health services.

Abstract: A decision analysis method for evaluating patient candidacy for a therapeutic procedure is provided. The method includes predicting, in accordance with a predetermined quantitative predicative scoring system, the probability of an adverse effect on such patient absent such procedure where less than all of data elements used in the scoring system may be available. The method is used to predict a probability of death of a patient within a predetermined period of time and includes predicting, in accordance with a predetermined quantitative predicative scoring system. The probability of death for such patient within the predetermined period of time being determined from medical data elements of the patient where less than all of such medical data elements may be available for use by the scoring system. A method is also provided for generating a scoring system to predict a probability of death of a patient within a predetermined period of time.