Managing the data from respiratory measurements.
Clinical decisionmaking depends upon properly interpreting the significance of physiological and other clinical data. Our experience, summarized in six case studies, suggests that no one variable is sufficient for making clinical decisions. Rather, different parameters are relevant in different situations. This article summarizes two techniques for improving the effectiveness of clinical decisionmaking in the ICU using quantitative physiological monitoring data. First, mathematical modeling has been used for measuring the volume of gas in the lungs of patients receiving mechanical ventilation. The technique analyzes the transient response to oxygen change; thus it is suitable for routine use in the ICU. Second, symbolic processing has been used for interpreting the clinical significance of measured data. This symbolic processing is used for recognizing artifact in measured data, determining expected physiological meaning of measured data in different clinical situations, identifying physiological status, and identifying therapy that may be appropriate for meeting therapeutic goals or correcting physiological problems in patients in the intensive care unit.
D000368:Aged; D002245:Carbon Dioxide / Q000097:blood; D003201:Computers; D003657:Decision Making; D005260:Female; D005652:Functional Residual Capacity; D006801:Humans; D007362:Intensive Care Units; D008297:Male; D008875:Middle Aged; D008954:Models, Biological; D008991:Monitoring, Physiologic / Q000379:methods*; D010100:Oxygen / Q000097:blood; D011312:Pressure; D012123:Pulmonary Ventilation; D012119:Respiration; D012129:Respiratory Function Tests; D012131:Respiratory Insufficiency / Q000503:physiopathology*
D002245:Carbon Dioxide; D010100:Oxygen