Abstract: A risk-based patient monitoring system for critical care patients combines data from multiple sources to assess the current and the future risks to the patient, thereby enabling providers to review a current patient risk profile and to continuously track a clinical trajectory. A physiology observer module in the system utilizes multiple measurements to estimate Probability Density Functions (PDF) of a number of Internal State Variables (ISVs) that describe a components of the physiology relevant to the patient treatment and condition. A clinical trajectory interpreter module in the system utilizes the estimated PDFs of ISVs to identify under which probable patient states the patient can be currently categorized and assign a probability value that the patient will be in each of the identified states. The combination of patient states and their probabilities is defined as the clinical risk to the patient.

Abstract: A risk-based patient monitoring system for critical care patients combines data from multiple sources to assess the current and the future risks to the patient, thereby enabling providers to review a current patient risk profile and to continuously track a clinical trajectory. A physiology observer module in the system utilizes multiple measurements to estimate Probability Density Functions (PDF) of a number of Internal State Variables (ISVs) that describe a components of the physiology relevant to the patient treatment and condition. A clinical trajectory interpreter module in the system utilizes the estimated PDFs of ISVs to identify under which probable patient states the patient can be currently categorized and assign a probability value that the patient will be in each of the identified states. The combination of patient states and their probabilities is defined as the clinical risk to the patient.

Abstract: A system simulates a medical protocol. The system includes an application simulator configured to receive an eligibility rule and compliance rule for a medical protocol. The simulator is further configured to receive collected patient data from a plurality of patients. The collected patient data includes longitudinal patient data relating to a specific parameter collected over a period of time from one or more sensors and/or medical devices. The simulator is further configured to compare the patient data with the eligibility rule to determine when a patient was eligible for the protocol. The simulator is further configured to compare the patient data with the compliance rule to determine a historic dynamic concordance rate for the protocol. The historic dynamic concordance rate for the protocol indicates the rate at which the patient data was consistent with the compliance rule for the protocol over the period of time.

Abstract: A method creates protocols. A protocol condition object is selected from a graphical user interface displaying a plurality of different protocol condition objects. Each object is associated with at least one corresponding parameter requirement. The selected protocol condition object is displayed in a protocol sequence window of the graphical user interface. A specific parameter window related to the corresponding parameter requirement for the selected object may be displayed. The method receives a specific parameter related to the corresponding parameter requirement within the specific parameter window. A clinical protocol having a condition as a function of the received specific parameter for the selected protocol condition type is generated.

Abstract: A system determines patient eligibility for a medical protocol. The system includes a medical protocol library containing information relating to a plurality of medical protocols. The information includes eligibility rules and compliance rules for the plurality of medical protocols. The system also includes a sensor and medical device interface configured to receive patient data from one or more sensors and/or one or more medical device. The patient data relates to the eligibility rules and/or the compliance rules for at least one of the medical protocols. The system also includes a protocol eligibility module configured to determine patient eligibility for at least one of the medical protocols as a function of the received patient data. Furthermore, the system includes a user interface configured to display an indication that the patient is eligible for the protocol.

Abstract: A method determines an internal state variable. The method receives patient data and a model of an internal state variable. The internal state variable is calculated using the patient data and the model of the internal state variable. Gold standard data corresponding to the internal state variable is received. A statistical performance assessment of the model of the internal state variable is performed. The method determines whether a performance of the model of the internal state variable is above a prescribed threshold. A source of inconsistent data negatively impacting the performance of the model of the internal state variable is determined.

Abstract: A risk-based patient monitoring system for critical care patients combines data from multiple sources to assess the current and the future risks to the patient, thereby enabling providers to review a current patient risk profile and to continuously track a clinical trajectory. A physiology observer module in the system utilizes multiple measurements to estimate Probability Density Functions (PDF) of a number of Internal State Variables (ISVs) that describe components of the physiology relevant to the patient treatment and condition. A clinical trajectory interpreter module in the system utilizes the estimated PDFs of ISVs to identify under which probable patient states the patient can be currently categorized and assign a probability value that the patient will be in each of the identified states. The combination of patient states and their probabilities is defined as the clinical risk to the patient.

Abstract: A system determines patient eligibility for a medical protocol. The system includes a medical protocol library containing information relating to a plurality of medical protocols. The information includes eligibility rules and compliance rules for the plurality of medical protocols. The system also includes a sensor and medical device interface configured to receive patient data from one or more sensors and/or one or more medical device. The patient data relates to the eligibility rules and/or the compliance rules for at least one of the medical protocols. The system also includes a protocol eligibility module configured to determine patient eligibility for at least one of the medical protocols as a function of the received patient data. Furthermore, the system includes a user interface configured to display an indication that the patient is eligible for the protocol.

Abstract: Systems, methods, and computer-readable media for providing a decision support solution to medical professionals to optimize medical care through data monitoring and feedback treatment are provided herein. In another embodiment, a computer-implemented method for modeling patient outcomes resulting from treatment in a specific medical area includes receiving patient-specific data associated with a patient, determining a plurality of possible patient states under which the patient can be categorized, a current patient state under which the patient can be categorized and determining probabilities of the patient transitioning from any of the possible patient states to every other possible patient state.

Abstract: A risk-based patient monitoring system for critical care patients combines data from multiple sources to assess the current and the future risks to the patient, thereby enabling providers to review a current patient risk profile and to continuously track a clinical trajectory. A physiology observer module in the system utilizes multiple measurements to estimate Probability Density Functions (PDF) of a number of Internal State Variables (ISVs) that describe components of the physiology relevant to the patient treatment and condition. A clinical trajectory interpreter module in the system utilizes the estimated PDFs of ISVs to identify under which probable patient states the patient can be currently categorized and assign a probability value that the patient will be in each of the identified states. The combination of patient states and their probabilities is defined as the clinical risk to the patient.

Abstract: Systems, methods, and computer-readable media for providing a decision support solution to medical professionals to optimize medical care through data monitoring and feedback treatment are provided herein. In another embodiment, a computer-implemented method for modeling patient outcomes resulting from treatment in a specific medical area includes receiving patient-specific data associated with a patient, determining a plurality of possible patient states under which the patient can be categorized, a current patient state under which the patient can be categorized and determining probabilities of the patient transitioning from any of the possible patient states to every other possible patient state.

Abstract: A risk-based patient monitoring system for critical care patients combines data from multiple sources to assess the current and the future risks to the patient, thereby enabling providers to review a current patient risk profile and to continuously track a clinical trajectory. A physiology observer module in the system utilizes multiple measurements to estimate Probability Density Functions (PDF) of a number of Internal State Variables (ISVs) that describe a components of the physiology relevant to the patient treatment and condition. A clinical trajectory interpreter module in the system utilizes the estimated PDFs of ISVs to identify under which probable patient states the patient can be currently categorized and assign a probability value that the patient will be in each of the identified states. The combination of patient states and their probabilities is defined as the clinical risk to the patient.

Abstract: A risk-based patient monitoring system for critical care patients combines data from multiple sources to assess the current and the future risks to the patient, thereby enabling providers to review a current patient risk profile and to continuously track a clinical trajectory. A physiology observer module in the system utilizes multiple measurements to estimate Probability Density Functions (PDF) of a number of Internal State Variables (ISVs) that describe a components of the physiology relevant to the patient treatment and condition. A clinical trajectory interpreter module in the system utilizes the estimated PDFs of ISVs to identify under which probable patient states the patient can be currently categorized and assign a probability value that the patient will be in each of the identified states. The combination of patient states and their probabilities is defined as the clinical risk to the patient.

Abstract: A risk-based patient monitoring system for critical care patients combines data from multiple sources to assess the current and the future risks to the patient, thereby enabling providers to review a current patient risk profile and to continuously track a clinical trajectory. A physiology observer module in the system utilizes multiple measurements to estimate Probability Density Functions (PDF) of a number of Internal State Variables (ISVs) that describe a components of the physiology relevant to the patient treatment and condition. A clinical trajectory interpreter module in the system utilizes the estimated PDFs of ISVs to identify under which probable patient states the patient can be currently categorized and assign a probability value that the patient will be in each of the identified states. The combination of patient states and their probabilities is defined as the clinical risk to the patient.

Abstract: Systems and methods produce a quantitative indication of the influence, on determination of a patient's clinical risk, of one or more measurements of one or more internal state variables. Illustrative embodiments compute a reference patient's clinical risk of being in a specific patient state using measurements of measurable internal state variables, and compute alternates of the same clinical risk using alternate values for at least one of the measurements of measurable internal state variables, and determine which of the measurements of internal state variables have the greatest quantitative impact on the patient's clinical risk by comparing the reference clinical risk to the alternate clinical risks.

Abstract: A system determines patient eligibility for a medical protocol. The system includes a medical protocol library containing information relating to a plurality of medical protocols. The information includes eligibility rules and compliance rules for the plurality of medical protocols. The system also includes a sensor and medical device interface configured to receive patient data from one or more sensors and/or one or more medical device. The patient data relates to the eligibility rules and/or the compliance rules for at least one of the medical protocols. The system also includes a protocol eligibility module configured to determine patient eligibility for at least one of the medical protocols as a function of the received patient data. Furthermore, the system includes a user interface configured to display an indication that the patient is eligible for the protocol.

Abstract: A system for determining patient eligibility and compliance with a medical protocol includes a medical protocol library containing information relating to a plurality of medical protocols. The information includes eligibility rules and compliance rules for each of the plurality of medical protocols. Each compliance rule has one or more parameters. The system has a sensor and medical device interface. The received patient data relates to the eligibility rules and/or the compliance rules for at least one of the medical protocols. A protocol eligibility module is configured to determine patient eligibility as a function of the received patient data and the eligibility rules relating to the at least one protocol. A protocol compliance module is configured to determine, after the at least one patient is enrolled in an active protocol, a dynamic concordance rate of the at least one patient.

Abstract: A method displays patient eligibility and/or compliance with a medical protocol. The method provides a display showing a respective patient identifier for a plurality of patients. The method receives information relating to a plurality of medical protocols. The information includes eligibility rules and compliance rules for each of the plurality of medical protocols. The method receives patient data from one or more sensors and/or one or more medical devices. The received patient data relates to the eligibility rules and/or the compliance rules for at least one of the medical protocols. The display indicates that at least one patient is eligible for an eligible protocol, and that at least one patient is enrolled in an active protocol. A dynamic concordance rate is calculated for the at least one patient that is enrolled in the active protocol. The display indicates the dynamic concordance rate.

Abstract: A risk-based patient monitoring system for critical care patients combines data from multiple sources to assess the current and the future risks to the patient, thereby enabling providers to review a current patient risk profile and to continuously track a clinical trajectory. A physiology observer module in the system utilizes multiple measurements to estimate Probability Density Functions (PDF) of a number of Internal State Variables (ISVs) that describe a components of the physiology relevant to the patient treatment and condition. A clinical trajectory interpreter module in the system utilizes the estimated PDFs of ISVs to identify under which probable patient states the patient can be currently categorized and assign a probability value that the patient will be in each of the identified states. The combination of patient states and their probabilities is defined as the clinical risk to the patient.

Abstract: A risk-based patient monitoring system for critical care patients combines data from multiple sources to assess the current and the future risks to the patient, thereby enabling providers to review a current patient risk profile and to continuously track a clinical trajectory. A physiology observer module in the system utilizes multiple measurements to estimate Probability Density Functions (PDF) of a number of Internal State Variables (ISVs) that describe components of the physiology relevant to the patient treatment and condition. A clinical trajectory interpreter module in the system utilizes the estimated PDFs of ISVs to identify under which probable patient states the patient can be currently categorized and assign a probability value that the patient will be in each of the identified states. The combination of patient states and their probabilities is defined as the clinical risk to the patient.