Abstract:
The system of the present application includes computerized diagnostic ECG that is tailored for the EMR. The system and method of the present application provides several new approaches to the computerized ECG based on information available from the EMR through an EMR portal. Some of these information items include: Test indication and reason for performing the ECG, previous ECGs as a measure of the patient's “normal” baseline; electrolytes, and drugs known to cause cardiac toxicity/prolonged QT. Based on these inputs, the computerized ECG analysis will behave differently, including the formation of reports, the ancillary information supplied with the ECG and the interpretation itself.
Abstract:
The system and method of the present application selects and presents ECGs that are most important to the user in conjunction with a measurement trend that relates to the diagnosis and management of the abnormality. In addition, the system and method of the present application will guide the user to verify whether the ECGs selected by the computer were valid and if not guide the user through measurement trends to find 12-ECGs of significance.
Abstract:
A system for processing ECG to detect atrial fibrillation includes three software modules. A beat module is executable on a processor to receive a time series of ECG data, identify heart beats, and determine a beat AFIB value based on a timing of each identified heart beat. The beat AFIB value represents a presence or absence of AFIB based on variability in the timing of each identified heart beat. A segment module is executable to receive the time series of ECG data, divide the time series of ECG data into two or more time segments, and determine a segment AFIB value for each time segment. The segment AFIB value indicates a presence or absence of AFIB in the time segment based on whether any of a set of rhythms are identified. The AFIB detection module is executable to determine an AFIB identification value for each time segment based on the beat AFIB value during that time segment and the segment AFIB value for that time segment.
Abstract:
A system for processing ECG to detect atrial fibrillation includes three software modules. A beat module is executable on a processor to receive a time series of ECG data, identify heart beats, and determine a beat AFIB value based on a timing of each identified heart beat. The beat AFIB value represents a presence or absence of AFIB based on variability in the timing of each identified heart beat. A segment module is executable to receive the time series of ECG data, divide the time series of ECG data into two or more time segments, and determine a segment AFIB value for each time segment. The segment AFIB value indicates a presence or absence of AFIB in the time segment based on whether any of a set of rhythms are identified. The AFIB detection module is executable to determine an AFIB identification value for each time segment based on the beat AFIB value during that time segment and the segment AFIB value for that time segment.
Abstract:
Method and system for displaying measured health data are disclosed herein. An example method includes receiving configuration for a rules engine which comprises a plurality of configurable rules. Each rule defines a link to specific information in an electronic medical record (EMR) in response to the measured health data meeting one or more criteria. The method further includes receiving the measured health data for a subject; linking the measured health data to the specific information in the EMR in response to the measured health data meeting the one or more criteria based on the configured rules engine; and displaying the measured health data and the specific information in the EMR which is linked to the measured health data.
Abstract:
Techniques for rules engine referencing are described herein. The techniques may include receiving electrocardiograph (ECG) data for a subject and identifying an electronic medical record (EMR) associated with the subject. The techniques further including referencing a rules engine including multiple configurable conditions defining when specific ECG data is to be linked to the EMR, and linking the specific ECG data to the EMR if one or more of the plurality of configurable conditions are met.