PATIENT SAFETY PROCESSOR

• US 20130268291A1
• Filed: 03/15/2013
• Published: 10/10/2013
• Est. Priority Date: 05/17/2001
• Status: Active Grant

• Current Assignee: Lawrence A. Lynn
• Original Assignee: Lawrence A. Lynn
• Inventors: Lynn, Lawrence A., Lynn, Eric N.
• Granted Patent: US 10,032,526 B2
• Time in Patent Office: Days
• US Class Current: 705/2
• CPC Class Codes: G16H 10/60 for patient-specific data, e.g. for electronic patient records
• CPC Class Codes: G16H 15/00 ICT specially adapted for medical reports, e.g. generation or transmission thereof
• CPC Class Codes: G16H 30/20 for handling medical images, e.g. DICOM, HL7 or PACS
• CPC Class Codes: G16H 30/40 for processing medical images, e.g. editing
• CPC Class Codes: G16H 40/60 for the operation of medical equipment or devices
• CPC Class Codes: G16H 50/20 for computer-aided diagnosis, e.g. based on medical expert systems
• CPC Class Codes: G16H 50/50 for simulation or modelling of medical disorders
• CPC Class Codes: G16H 50/70 for mining of medical data, e.g. analysing previous cases of other patients
• CPC Class Codes: H04N 9/87 Regeneration of colour television signals H04N9/80 takes precedence

Abstract

A processor-based system for analyzing physiologic data and medical care is provided wherein the patient data is analyzed to construct images that are representative of a patient'"'"'s condition. The processor provides a self-modulating analysis, which is responsive to the occurrence of additional data items to increase the information contained in the images. Identifications of modes of physiologic failure by the analysis of the generated images provides for earlier recognition and intervention and improved protocolization of testing and treatment.

Claims

1. A hospital monitoring system comprising:

a database comprising an electronic medical record repository of data wherein the electronic medical record repository of data contains data of a plurality of patients in at least one hospital; and

a processor programmed to search the database for at least one complex cascade pattern within the data of the plurality of patients and to identify one or more patients whose physiologic data is used to generate the at least one complex cascade pattern, wherein said complex cascade pattern is a pathophysiologically linked series of changes in physiologic parameters in a particular patient wherein the number of pathophysiologically linked changes per unit time increase over time along at least a portion of the cascade pattern.

2. The hospital monitoring system of claim 1, comprising an alarm processor programmed to provide an automatic alarm upon the detection of the complex cascade pattern.

3. The hospital monitoring system of claim 1, wherein the complex cascade pattern comprises at least one of sepsis, severe sepsis, and septic shock, microcirculatory failure, and shock.

4. The hospital monitoring system of claim 1, further programmed to determine at least one characteristic of the complex cascade pattern, the characteristic comprising at least one of a severity of the complex cascade pattern, a duration of the complex cascade pattern, a time of onset of the complex cascade pattern, a timing relationship of the complex cascade pattern to other events or another complex cascade pattern, a time of termination of the complex cascade pattern, components of the complex cascade pattern, a state of evolution of the complex cascade pattern, a length of stay subsequent to, or in association with the complex cascade pattern, or treatments associated with the complex cascade pattern, said length of stay being of the patient associated with the complex cascade pattern.

5. The hospital monitoring system of claim 4, wherein the at least one characteristic of the complex cascade pattern is defined by at least one of;

a number of changes in physiologic parameters which comprise the complex cascade pattern, a severity of the changes in physiologic parameters, a number of systems affected by the complex cascade pattern, or a presence, number and/or severity of failure of compensation in response to changes in physiologic parameters associated with the complex cascade pattern.

6. The hospital monitoring system of claim 1, wherein the processor is further programmed to determine the rate of growth of the complex cascade pattern by at least one of the increase in number and/or severity of new changes in physiologic parameters being added per unit time, the increase number of systems affected, or the increase number of changes in physiologic parameters present in different systems.

7. The hospital monitoring system of claim 1, wherein the electronic medical record repository of data comprises data from a plurality of hospitals, and wherein the processor is programmed to identify the patients whose physiologic data is used to generate complex cascade patterns and the hospital in which they are located.

8. A patient data processing system comprising a processor programmed to:

convert the electronic medical records of at least one hospital into sequential and timed changes comprised of at least positive changes and negative changes of both the physiologic parameters and the laboratory data, automatically output a display of the detected complex cascade pattern as an image, automatically output a warning indicating the detection of the complex cascade pattern and the identification of the patient whose physiologic data is used to generate the complex cascade pattern, track the growth or decline of the complex cascade pattern and output an indication to a user indicative of growth or decline, wherein said complex cascade pattern is a pathophysiologically linked series of changes in physiologic parameters in a particular patient, and wherein growth and decline represent an increase and a decrease in the number of pathophysiologically linked changes in physiologic parameters per unit time in the complex cascade pattern, respectively.

9. The patient data processing system of claim 8, wherein the complex cascade pattern represents physiologic failure.

10. The patient data processing system of claim 8, wherein the complex cascade pattern comprises at least one of sepsis, severe sepsis, septic shock, and microcirculatory failure, or shock.

11. The patient data processing system of claim 8, wherein the processor comprises instructions for determining and outputting to the user an indication of the type of the complex cascade pattern detected.

12. The patient data processing system of claim 8, wherein the processor comprises instructions for determining and outputting to the user at least an indication of the timing and type of the changes along the complex cascade pattern.

13. The patient data processing system of claim 8, wherein the processor comprises instructions for determining and outputting to the user at least an indication of the length of the complex cascade pattern.

14. The patient data processing system of claim 8, wherein the processor comprises instructions for detecting the onset of therapy and for determining and outputting to the user at least an indication of timing of therapy in relation to said linked series of changes in physiologic parameters of the complex cascade pattern.

15. A patient data processing system for processing electronic medical records of a hospital, comprising a processor programmed to:

generate datasets of at least a portion of a plurality of patients in the hospital, including at least data relating to the physiologic state and/or care of each patient;

convert the datasets, including at least the monitored datasets and laboratory datasets into parallel and overlapping time series;

identify occurrences comprising inflammatory occurrences, metabolic occurrences, volumetric occurrences, hemodynamic occurrences, therapy occurrences, hematologic occurrences, or respiratory occurrences;

identify the timing of the occurrences;

identify at least one relational pattern of occurrences along a plurality of time series, wherein said relational pattern of occurrences is indicative of sepsis for a particular patient; and

output an alarm when the sepsis is detected.