Covidien LP

Kirk Hensley

Peter Doyle

Gardner Kimm

Gary Milne

This disclosure describes systems and methods for monitoring and evaluating ventilatory data to provide useful notifications and/or recommendations. Indeed, many clinicians may not easily identify or recognize data patterns and correlations indicative of certain patient conditions or the effectiveness of ventilatory treatment. Further, clinicians may not readily determine appropriate adjustments that may address certain patient conditions or the effectiveness of ventilatory treatment. Specifically, clinicians may not readily detect or recognize the occurrence of high-delivered V, during various types of ventilation. According to embodiments, a ventilator may be configured to monitor and evaluate diverse ventilatory parameters to detect an occurrence of and potential causes for high-delivered V, and may subsequently issue suitable notifications and/or recommendations. The suitable notifications and/or recommendations may further be provided in a hierarchical format such that the clinician may selectively access information regarding the high-delivered V, and/or potential causes for the high-delivered V.

Ventilator-initiated prompt regarding high delivered tidal volume

This disclosure describes systems and methods for monitoring and evaluating ventilatory parameters, analyzing those parameters and providing useful notifications and recommendations to clinicians. That is, modern ventilators monitor, evaluate, and graphically represent a myriad of ventilatory parameters. However, many clinicians may not easily identify or recognize data patterns and correlations indicative of certain patient conditions, changes in patient condition, and/or effectiveness of ventilatory treatment. Further, clinicians may not readily determine appropriate ventilatory adjustments that may address certain patient conditions and/or the effectiveness of ventilatory treatment. Specifically, clinicians may not readily detect or recognize the presence of Auto-PEEP during volume ventilation of a non-triggering patient. According to embodiments, a ventilator may be configured to monitor and evaluate diverse ventilatory parameters to detect Auto-PEEP and may issue suitable notifications and recommendations to the clinician when Auto-PEEP is implicated. The suitable notifications and recommendations may further be provided in a hierarchical format.

Ventilator-initiated prompt regarding auto-peep detection during ventilation of non-triggering patient

This disclosure describes systems and methods for monitoring and evaluating ventilatory parameters, analyzing those parameters and providing useful notifications and recommendations to clinicians. That is, modern ventilators monitor, evaluate, and graphically represent multiple ventilatory parameters. However, many clinicians may not easily recognize data patterns and correlations indicative of certain patient conditions, changes in patient condition, and/or effectiveness of ventilatory treatment. Further, clinicians may not readily determine appropriate ventilatory adjustments that may address certain patient conditions and/or the effectiveness of ventilatory treatment. Specifically, clinicians may not readily detect or recognize the presence of double triggering during ventilation. According to embodiments, a ventilator may be configured to monitor and evaluate diverse ventilatory parameters to detect double triggering and may issue notifications and recommendations suitable for a patient to the clinician when double triggering is implicated. The suitable notifications and recommendations may further be provided in a hierarchical format.

Ventilator-initiated prompt regarding detection of double triggering during a volume-control breath type

Ventilator-initiated prompt regarding detection of double triggering during ventilation

Ventilator-initiated prompt regarding Auto-PEEP detection during volume ventilation of non-triggering patient

This disclosure describes systems and methods for monitoring and evaluating ventilatory parameters, analyzing ventilatory data associated with those parameters, and providing useful notifications and/or recommendations to clinicians. Modern ventilators monitor, evaluate, and graphically represent a myriad of ventilatory parameters. However, many clinicians may not easily identify or recognize data patterns and correlations indicative of certain patient conditions, changes in patient condition, and/or effectiveness of ventilatory treatment. Further, clinicians may not readily determine appropriate ventilatory adjustments that may address certain patient conditions and/or the effectiveness of ventilatory treatment. Specifically, clinicians may not readily detect or recognize the presence of Auto-PEEP during various types of pressure ventilation. According to embodiments, a ventilator may be configured to monitor and evaluate diverse ventilatory parameters to detect Auto-PEEP and may issue suitable notifications and recommendations to the clinician when Auto-PEEP is implicated. The suitable notifications and recommendations may further be provided in a hierarchical format.

Ventilator-initiated prompt regarding auto-PEEP detection during pressure ventilation

This disclosure describes systems and methods for monitoring and evaluating ventilatory parameters, analyzing ventilatory data associated with those parameters, and providing useful notifications and/or recommendations to clinicians. Modern ventilators monitor, evaluate, and graphically represent a myriad of ventilatory parameters. However, many clinicians may not easily identify or recognize data patterns and correlations indicative of certain patient conditions, changes in patient condition, and/or effectiveness of ventilatory treatment. Further, clinicians may not readily determine appropriate ventilatory adjustments that may address certain patient conditions and/or the effectiveness of ventilatory treatment. Specifically, clinicians may not readily detect or recognize the presence of Auto-PEEP during various types of pressure ventilation of a patient exhibiting an obstructive component. According to embodiments, a ventilator may be configured to monitor and evaluate diverse ventilatory parameters to detect Auto-PEEP and may issue suitable notifications and recommendations to the clinician when Auto-PEEP is implicated.

Ventilator-initiated prompt regarding auto-PEEP detection during pressure ventilation of patient exhibiting obstructive component

This disclosure describes systems and methods for monitoring and evaluating ventilatory parameters, analyzing those parameters and providing useful notifications and recommendations to clinicians. That is, modern ventilators monitor, evaluate, and graphically represent multiple ventilatory parameters. However, many clinicians may not easily recognize data patterns and correlations indicative of certain patient conditions, changes in patient condition, and/or effectiveness of ventilatory treatment. Further, clinicians may not readily determine appropriate ventilatory adjustments that may address certain patient conditions and/or the effectiveness of ventilatory treatment. Specifically, clinicians may not readily detect or recognize the presence of Auto-PEEP during volume ventilation of a non-triggering patient exhibiting an obstructive component. According to embodiments, a ventilator may be configured to monitor and evaluate diverse ventilatory parameters to detect Auto-PEEP and may issue notifications and recommendations suitable for a non-triggering patient to the clinician when Auto-PEEP is implicated. The suitable notifications and recommendations may further be provided in a hierarchical format.

Ventilator-initiated prompt regarding auto-PEEP detection during volume ventilation of non-triggering patient exhibiting obstructive component

This disclosure describes systems and methods for monitoring and evaluating ventilatory parameters, analyzing those parameters and providing useful notifications and recommendations to clinicians. That is, modern ventilators monitor, evaluate, and graphically represent multiple ventilatory parameters. However, many clinicians may not easily recognize data patterns and correlations indicative of certain patient conditions, changes in patient condition, and/or effectiveness of ventilatory treatment. Further, clinicians may not readily determine appropriate ventilatory adjustments that may address certain patient conditions and/or the effectiveness of ventilatory treatment. Specifically, clinicians may not readily detect or recognize the presence of Auto-PEEP during volume ventilation of a triggering patient exhibiting an obstructive component. According to embodiments, a ventilator may be configured to monitor and evaluate diverse ventilatory parameters to detect Auto-PEEP and may issue notifications and recommendations suitable for a triggering patient to the clinician when Auto-PEEP is implicated. The suitable notifications and recommendations may further be provided in a hierarchical format.

Ventilator-initiated prompt regarding auto-PEEP detection during volume ventilation of triggering patient exhibiting obstructive component

This disclosure describes systems and methods for monitoring ventilatory parameters, analyzing ventilatory data associated with those parameters, and providing useful notifications and/or recommendations to clinicians. For example, many clinicians may not easily identify or recognize data patterns and correlations indicative of a fluctuation in resistance during mechanical ventilation of a patient. Furthermore, clinicians may not easily determine potential causes for the fluctuation in resistance and/or steps for mitigating the fluctuation in resistance. According to embodiments, a ventilator may be configured to monitor and evaluate diverse ventilatory parameters to detect fluctuations in resistance and may issue suitable notifications and recommendations to the clinician based on potential causes of the fluctuation, ventilatory and/or patient data, etc. The suitable notifications and recommendations may further be provided in a hierarchical format such that the clinician may selectively access information regarding the fluctuation in resistance.

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Dublin, OH, United States of America

Kirk Hensley