11 research outputs found

    Design of a Novel Multifunction Decision Support Display for Anesthesia Care: AlertWatch® OR

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    Abstract Background This paper describes the design of a multifunction alerting display for intraoperative anesthetic care. The design was inspired by the multifunction primary flight display used in modern aviation. Results The display retrieves live data from multiple sources; the physiologic monitors, the anesthesia information management system, the laboratory values and comorbidities from patient’s problem summary list, medical history or history & physical. This information is integrated into a display composed of readily identifiable icons of organ systems, which are color coded to signify normal range, marginal range, abnormal range (by green, yellow, red respectively) and orange outlines for comorbidities/risk factors. There are dozens of text alerts, which can be presented as black text (informational), red text (important information) and red scrolling text (highest importance information). The alerts are derived from current standards in the literature and some involve complex calculations being conducted in the background. Conclusions The goal of such a system is to improve the quality and safety of anesthetic care by providing enhanced situational awareness in a fashion analogous to the “glass cockpit” and its primary flight display which has improved aviation safety.https://deepblue.lib.umich.edu/bitstream/2027.42/142347/1/12871_2018_Article_478.pd

    Additional file 2: of Design of a Novel Multifunction Decision Support Display for Anesthesia Care: AlertWatchÂŽ OR

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    List of Text Alerts. There are a total of 54 alerts. These text alerts come in three levels of severity: black text are informational, red text are important and scrolling red text require an immediate attention. (PDF 66 kb

    Design of a novel multifunction decision support/alerting system for in-patient acute care, ICU and floor (AlertWatch AC)

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    Abstract Background Multifunction surveillance alerting systems have been found to be beneficial for the operating room and labor and delivery. This paper describes a similar system developed for in-hospital acute care environments, AlertWatch Acute Care (AWAC). Results A decision support surveillance system has been developed which extracts comprehensive electronic health record (EHR) data including live data from physiologic monitors and ventilators and incorporates them into an integrated organ icon-based patient display. Live data retrieved from the hospitals network are processed by presenting scrolling median values to reduce artifacts. A total of 48 possible alerts are generated covering a broad range of critical patient care concerns. Notification is achieved by paging or texting the appropriated member of the critical care team. Alerts range from simple out of range values to more complex programing of impending Ventilator Associated Events, SOFA, qSOFA, SIRS scores and process of care reminders for the management of glucose and sepsis. As with similar systems developed for the operating room and labor and delivery, there are green, yellow, and red configurable ranges for all parameters. A census view allows surveillance of an entire unit with flashing or text to voice alerting and enables detailed information by windowing into an individual patient view including live physiologic waveforms. The system runs via web interface on desktop as well as mobile devices, with iOS native app available, for ease of communication from any location. The goal is to improve safety and adherence to standard management protocols. Conclusions AWAC is designed to provide a high level surveillance view for multi-bed hospital units with varying acuity from standard floor patients to complex ICU care. Alerts are generated by algorithms running in the background and automatically notify the selected member of the patients care team. Its value has been demonstrated for low acuity patients, further study is required to determine its effectiveness in high acuity patients.http://deepblue.lib.umich.edu/bitstream/2027.42/173425/1/12871_2021_Article_1411.pd
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