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

Douglas A Colquhoun; Ryan P Davis; Theodore T Tremper; Jenny J Mace; Jan M Gombert; William D Sheldon; Joseph J Connolly; Justin F Adams; Kevin K Tremper

doi:10.1186/s12871-021-01411-9

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

BMC Anesthesiol. 2021 Jul 24;21(1):196. doi: 10.1186/s12871-021-01411-9.

Authors

Douglas A Colquhoun¹, Ryan P Davis¹, Theodore T Tremper^{1

2}, Jenny J Mace¹, Jan M Gombert², William D Sheldon², Joseph J Connolly², Justin F Adams², Kevin K Tremper³

Affiliations

¹ Department of Anesthesiology, University of Michigan, 1500 E. Medical Center Drive, Ann Arbor, MI, 48109, USA.
² AlertWatch Headquarters, 330 E. Liberty Street, Ann Arbor, MI, 48104, USA.
³ Department of Anesthesiology, University of Michigan, 1500 E. Medical Center Drive, Ann Arbor, MI, 48109, USA. ktremper@umich.edu.

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.

Keywords: Acute Care; Decision Support; EHR; ICU; Inpatient Medicine; Monitoring; Surveillance.

MeSH terms

Algorithms
Critical Care / methods*
Decision Support Systems, Clinical / instrumentation*
Delivery Rooms / organization & administration
Electronic Health Records
Hospital Information Systems*
Humans
Intensive Care Units / organization & administration
Monitoring, Physiologic / instrumentation
Monitoring, Physiologic / methods
Operating Rooms / organization & administration
Patient Care / methods*
Software