Centralized hospital monitoring system for automatically detecting upper airway instability and for preventing and aborting adverse drug reactions

• US 20060195041A1
• Filed: 03/07/2006
• Published: 08/31/2006
• Est. Priority Date: 05/17/2002
• Status: Abandoned Application

• Current Assignee: Eric N Lynn, Lawrence A. Lynn
• Original Assignee: Eric N Lynn, Lawrence A. Lynn
• Inventors: Lynn, Eric N., Lynn, Lawrence A.
• Application Number:
  US11/369,355
• Publication Number:
  US 20060195041A1
• Time in Patent Office: Days
• US Class Current: 600/538
• CPC Class Codes: A61B 5/002 Monitoring the patient using a local or closed circuit, e.g. in a room or building A61B5/0017 takes precedence
• CPC Class Codes: A61B 5/412 Detecting or monitoring sepsis
• CPC Class Codes: A61B 5/4818 Sleep apnoea
• CPC Class Codes: G16H 20/17 delivered via infusion or injection
• CPC Class Codes: G16H 40/67 for remote operation

Abstract

A system and method for the automatic diagnosis of obstructive sleep apnea in a centralized hospital critical care monitoring system for the monitoring of a plurality of patients in at least one of a critical care, step down, and cardiac ward by telemetry. The system includes a central processor having a display, and a plurality of telemetry unit for mounting with patients, each of the telemetry units has a plurality of sensors for connection with each patient, the telemetry unit is capable of the transmission of multiple signals derived from the sensors to the central processor, in one preferred embodiment the method comprising steps of programming the system to analyze the signals and to automatically identify the presence and severity of obstructive sleep apnea and to provide an indication of the identification.

Claims

1. A processor-based method of determining specific factors related to the expense associated with a complex process, the process including a plurality of dynamic components defined by a plurality of dynamic measurable parameters, the method comprising:

repetitively measuring at least a first parameter to derive at least one time series of the first parameters being indicative of at least a first component of the process;

processing the time series of the first parameter to derive a first time series of objects derived from fragments of the time series of the first parameter, the objects comprising first parameters objects;

storing the first time series objects in at least one of a relational database, an objects database, and an objects relational database;

deriving at least a second time series of expense values, the expense values being associated with the process, the objects comprising expense objects;

processing the time series of expense values to derive a second time series of objects derived from fragments of the time series of expense values;

storing the second time series of objects in a relational database, an objects database, and an objects relational database; and

comparing the first time series with the second time series to determine a dynamic relationship between the first parameters objects and the expense objects.

2. The method of claim 1, further including steps of:

repetitively measuring at least a second parameter to derive at least a second time series of the second parameter, the second parameter being indicative of at least a second component of the process;

processing the time series of the second parameter to derive a third time series of objects derived from fragments of the time series of the second parameter;

storing the third time series objects with the first parameter objects and the expense objects is the at least one of a relational database, an objects database, and an objects relational database;

comparing the time series of the first parameter objects to the time series of the second parameter objects to identify an occurrence of a dynamic pattern of interaction between the first parameter and the second parameter; and

comparing the time series of the expense objects to the occurrence to determine a relationship between the expense objects and the occurrence.

3. The method recited in claim 2, wherein the occurrence comprises a dynamic interaction between airflow and oxygen saturation.

4. The method recited in claim 2, wherein the occurrence comprises a cluster indicative of upper airway instability.

5. The method recited in claim 2, wherein the second parameter is a physiologic parameter.

6. The method recited in claim 1, wherein the process is a pathophysiologic process and the first parameter is a physiologic parameter.

7. The method recited in claim 1, wherein the process is a pathophysiologic process and the first parameter is a physiologic parameter.

8. The method recited in claim 1, wherein the recited acts are performed by a processor that comprises a portion of a patient monitor.

9. A method for the automatic diagnosis of obstructive sleep apnea in a centralized hospital critical care monitoring system for the monitoring of a plurality of patients in at least one of a critical care, step down, and cardiac ward by telemetry, the system including a central processor having a display, and a plurality of telemetry units for mounting with the patients, each of the telemetry units having a plurality of sensors for connection with each the patient, each the sensors transmitting a plurality of signals to the central unit, the method comprising:

analyzing the signals to automatically identify at least one of the presence and severity of obstructive sleep apnea; and

outputting an indication when at least one of the presence and severity of obstructive sleep apnea is identified.

10. A method of increasing at least one of hospital and physician net revenue, and improving the efficiency of the diagnosis of sleep apnea, the method comprising steps of:

disposing, in at least one of a critical care, step down, and cardiac ward, a centralized hospital critical care monitoring system for the monitoring of a plurality of patients by telemetry, the monitoring system including a central processor having a display, and a plurality of telemetry units for mounting with the patients, each of the telemetry units having a plurality of sensors for connection with each the patient, each the sensors transmitting a plurality of signals to the central unit;

employing the system to analyze the signals and to automatically identify the presence and severity of obstructive sleep apnea; and

providing an indication when at least one of the presence and severity of obstructive sleep apnea is identified.

11. The method recited in claim 10, comprising:

disposing a positive pressure delivery system adjacent to a nose of at least one of the plurality of patients, the positive pressure delivery system being in connection with the monitoring system; and

automatically adjusting positive pressure through the delivery system based on the signals.

12. A method for identifying individuals with sleep apnea in a population of hospital patients, the method comprising:

employing a centralized hospital monitoring system to detect patterns indicative of at least one of apneas and hypopneas, as a part of routine hospital monitoring of the patients;

employing the centralized hospital monitoring system to count a number of detected patterns indicative of the at least one of apneas and hypopneas detected per individual patient; and

providing an output indicative of the number of the at least one of apneas and hypopneas detected per individual patient.

13. The method recited in claim 12, comprising:

communicating with an intravenous infusion system to prevent a progression of an identified upper airway instability by limiting infusion of a narcotic.

14. The method recited in claim 12, comprising:

determining the number of patterns indicative of the at least one of apneas and hypopneas detected per individual patient per unit of time.

15. The method recited in claim 14, wherein the unit of time comprises an hour.

16. A method for providing case finding of individuals with the obstructive sleep apnea disease in a population of hospitalized patients being routinely monitored by a centralized hospital monitoring system, the method comprising:

employing the centralized hospital monitoring system to identify a subset of the population who have obstructive sleep apnea; and

providing an output indicative of the presence of the obstructive sleep apnea disease so that the population is routinely screened for the obstructive sleep apnea disease as part of routine monitoring in the hospital.

17. A method for facilitating case finding of individuals with obstructive sleep apnea disease in a population of hospitalized patients being routinely monitored by a centralized hospital monitoring system, the method comprising:

employing the centralized hospital monitoring system to detect at least one pattern indicative of the obstructive sleep apnea disease; and

providing an output in response to the detection so that the population can be routinely screened for the obstructive sleep apnea disease when routinely monitored in the hospital.

18. The method of claim 17, wherein:

the at least one pattern comprises a plurality of reciprocations; and

the centralized hospital monitoring system is adapted to quantify the number of the plurality of reciprocations.

19. A method for facilitating case finding of individuals with obstructive sleep apnea disease in a population of postoperative patients being routinely monitored by a centralized hospital monitoring system, the method comprising:

employing the centralized hospital monitoring system to detect at least one pattern indicative of the obstructive sleep apnea disease; and

providing an output in response to the detection so that the population can be routinely screened for the obstructive sleep apnea disease when routinely monitored in the hospital for complications of surgery.

20. The method of claim 19 wherein:

the at least one pattern comprises a plurality of reciprocations; and

the centralized hospital monitoring system is adapted to quantify the number of reciprocations.

21. A method for facilitating case finding of individuals with obstructive sleep apnea disease in a population of heart patients being routinely monitored by a centralized hospital monitoring system during a hospitalization for heart disease, the method comprising:

employing the centralized hospital monitoring system to detect at least one pattern indicative of the obstructive sleep apnea disease; and

providing an output in response to the detection so that the population can be routinely screened for the obstructive sleep apnea disease when routinely monitored in the hospital for complications of heart disease.

22. The method of claim 21, wherein:

the at least one pattern comprises a plurality of reciprocations; and

the centralized hospital monitoring system is adapted to quantify the number of the plurality of reciprocations.

23. A method for providing case finding of individuals with the obstructive sleep apnea disease in a population of hospitalized patients being routinely monitored by a centralized hospital monitoring system, the method comprising the steps of:

programming the centralized hospital monitoring system to detect which of the patients have the obstructive sleep apnea disease; and

programming the centralized hospital monitoring system to provide an output indicative of the presence of the obstructive sleep apnea disease so that the population is routinely screened for the obstructive sleep apnea disease when routinely monitored in the hospital.

24. A method for facilitating case finding of individuals with obstructive sleep apnea disease in a population of hospitalized patients being routinely monitored by a centralized hospital monitoring system, the method comprising:

programming the centralized hospital monitoring system to detect at least one pattern indicative of the obstructive sleep apnea disease; and

programming the centralized hospital monitoring system to provide an output in response to the detection so that the population can be routinely screened for the obstructive sleep apnea disease when routinely monitored in the hospital.

25. The method of claim 24, wherein:

the at least one pattern comprises a plurality of reciprocations; and

the centralized hospital monitoring system is adapted to quantify a number of the plurality of reciprocations.

26. A centralized monitoring system adapted to detect obstructive sleep apnea, comprising:

at least one receiver adapted to collect a signal from each of a corresponding plurality of patients, each signal representative of a physiological characteristic of a respective one of the plurality of patients; and

a processor that is adapted to;

receive the plurality of signals from the receiver and to analyze each of the plurality of signals to promptly identify a plurality of threshold events indicative of an occurrence of a corresponding plurality of adverse physiologic events and to alarm in response to the threshold events; and

detect an occurrence of a pattern that indicates at least one of the presence and severity of obstructive sleep apnea.

27. A method for the automatic detection of sleep apnea, the method comprising:

disposing a centralized hospital critical care monitoring system for the monitoring by telemetry of a plurality of patients in at least one of a critical care ward, a hospital ward, and a post-operative ward, the centralized hospital critical care monitoring system including a central processor connected to a display, and a plurality of telemetry units for mounting with the plurality of patients, each of the telemetry units having a plurality of sensors for connection with each of the plurality of patients, each of the telemetry units transmitting a plurality of signals to the central processor;

analyzing each of the plurality of signals to promptly identify a plurality of threshold events indicative of an occurrence of a corresponding plurality of adverse physiologic events;

generating an alarm if at least one of the threshold events is identified;

analyzing the signals to—

automatically identify at least one of the presence and severity of adult sleep apnea; and

outputting—

an indication responsive to the identified adult sleep apnea.

28. A sleep apnea detection system for use in a hospital centralized monitoring system, the hospital centralized monitoring system adapted to receive data corresponding to a plurality of signals, each signal representative of a physiological characteristic of a respective one of a plurality of patients, the hospital centralized monitoring system adapted to provide an alarm if at least one of the signals is indicative of an adverse condition of a corresponding one of the plurality of patients, the sleep apnea detection system comprising:

a processor that is adapted to;

retrieve data corresponding to the plurality of signals already received by the hospital centralized monitoring system, and

analyze the retrieved data to detect an occurrence of a pattern that indicates at least one of the presence and severity of sleep apnea; and

a device that outputs an indication responsive to the identified sleep apnea.

29. A tangible machine-readable medium comprising:

code adapted to retrieve data corresponding to a plurality of signals already received by a hospital centralized monitoring system, each signal representative of a physiological characteristic of a respective one of a plurality of patients, the hospital centralized monitoring system adapted to provide an alarm if at least one of the signals is indicative of an adverse condition of the corresponding one of the plurality of patients;

code adapted to analyze the retrieved data to detect an occurrence of a pattern that

indicates at least one of the presence and severity of sleep apnea; and

code adapted to output an indication responsive to the identified sleep apnea.