System and method for facilitating observation of monitored physiologic data

Abstract

Present embodiments are directed to a system and method capable of detecting and graphically indicating physiologic patterns in patient data. For example, present embodiments may include a monitoring system that includes a monitor capable of receiving input relating to patient physiological parameters and providing indications or alarms related to oxygen saturation declines and oxygen desaturation patterns associated with sleep apnea. Present embodiments may include methods and systems for mediating between alarms and other indicators associated with oxygen desaturation and ventilatory instability.

What is claimed is: 
     
         1 . A computer-implemented method of evaluating a condition of a patient, the method comprising:
 receiving data from a sensor associated with one or more physiological parameters of the patient;   activating a pattern monitoring function that operates on the data; and   adjusting a tolerance of a desaturation monitoring function that operates on the data when:
 the pattern monitoring function is activated, and 
 the tolerance does not meet a predetermined criterion. 
   
     
     
         2 . The computer-implemented method of  claim 1 , wherein adjusting the tolerance of a desaturation monitoring function comprises increasing the tolerance. 
     
     
         3 . The computer-implemented method of  claim 1 , wherein the predetermined criterion is an alarm limit, and wherein the desaturation monitoring function comprises triggering an alarm when an oxygen desaturation reaches the alarm limit. 
     
     
         4 . The computer-implemented method of  claim 1 , wherein, when activated, the pattern monitoring function comprises:
 detecting a reciprocation in the received data; and   qualifying the reciprocations as indicative of apnea.   
     
     
         5 . The computer-implemented method of  claim 3 , wherein detecting a reciprocation comprises detecting a reciprocation using an adaptive window. 
     
     
         6 . The computer-implemented method of  claim 4 , wherein qualifying the reciprocation comprises:
 calculating one or more metrics associated with the reciprocation;   comparing the one or more metrics with one or more respective limits; and   qualifying the reciprocation based at least in part on the comparison.   
     
     
         7 . The computer-implemented method of  claim 6 , wherein the one or more metrics comprise one or more of fall slope, magnitude, slope ratio, and path length ratio. 
     
     
         8 . The computer-implemented method of  claim 6 , wherein qualifying the reciprocation further comprises qualifying the reciprocation based at least in part on a linear qualification function. 
     
     
         9 . The computer-implemented method of  claim 8 , wherein the linear qualification function is determined based at least in part on a least squares analysis. 
     
     
         10 . The computer-implemented method of  claim 4 , further comprising determining a saturation pattern detection index based at least in part on a magnitude and variability of a qualified reciprocation. 
     
     
         11 . The computer-implemented method of  claim 10 , further comprising determining a frequency of qualified reciprocations, wherein the saturation pattern detection index is determined when the frequency reaches a minimum threshold. 
     
     
         12 . A system of evaluating a condition of a patient, the system comprising processing equipment configured for:
 receiving data from a sensor associated with one or more physiological parameters of the patient;   activating a pattern monitoring function that operates on the data; and   adjusting a tolerance of a desaturation monitoring function that operates on the data when:
 the pattern monitoring function is activated, and 
 the tolerance does not meet a predetermined criterion. 
   
     
     
         13 . The system of  claim 12 , wherein the processing equipment is further configured for increasing the tolerance. 
     
     
         14 . The system of  claim 12 , wherein the processing equipment is further configured for:
 detecting a reciprocation in the received data; and   qualifying the reciprocations as indicative of apnea.   
     
     
         15 . The system of  claim 12 , wherein the predetermined criterion is an alarm limit, and wherein then processing equipment is further configured for triggering an alarm when an oxygen desaturation reaches the alarm limit. 
     
     
         16 . A computer-implemented method of evaluating a condition of a patient, the method comprising:
 receiving physiological data from a sensor, wherein the physiological data is associated with one or more physiological parameters;   determining whether a desaturation monitoring function is active, wherein the desaturation monitoring function detects oxygen desaturation events in the received physiological data;   activating, when the desaturation monitoring function is active, a saturation pattern monitoring function, wherein the saturation pattern monitoring function identifies an oxygen saturation pattern;   determining, in response to the activation of the pattern monitoring function, whether an alarm limit of the desaturation monitoring function is associated with a minimum tolerance;   adjusting the alarm limit of the desaturation monitoring function when the alarm limit is not associated with a minimum tolerance.   
     
     
         17 . The computer-implemented method of  claim 16 , wherein adjusting the alarm limit of the desaturation monitoring function comprises increasing the alarm limit based at least in part on a maximum tolerance. 
     
     
         18 . The computer-implemented method of  claim 16  wherein, when activated, the pattern monitoring function comprises determining a saturation pattern detection index based at least in part on the identified oxygen saturation pattern. 
     
     
         19 . The computer-implemented method of  claim 18 , wherein saturation pattern detection index is based at least in part on an identified oxygen saturation pattern that is indicative of a frequency of oxygen desaturation events, and wherein the alarm limit of the desaturation monitoring function is not associated with a frequency of oxygen desaturation events. 
     
     
         20 . The computer-implemented method of  claim 19 , wherein the identified oxygen saturation pattern is indicative of ventilatory instability of the patient, and wherein the saturation pattern detection index is indicative of the severity of the ventilatory instability.