Distributed situation awareness: a health-system approach to assessing and designing patient flow management

Quantitative Evidence Supporting Distributed Situation Awareness Model of Patient Flow Management

“…The proportion of delayed, canceled, and repeated service requests and their reasons indicates that the deficient distribution and transmission of SA identified by the DSA network model is a likely cause of the operational inefficiencies that can hinder patient flow. The results thus provide preliminary empirical, quantitative evidence for the qualitative DSA network model of patient flow management in a major healthcare center (Alhaider et al, 2020), thereby providing support for the DSA theoretical framework. The DSA network model and the results of this study collectively inform CTaC that communication protocols should be improved for the cleaning and transport staff to receive accurate status of the patient and/or the room (i.e., SA) at the time of dispatch and the operational metrics of services delayed, repeated, or canceled for management staff to assess the protocol changes.…”

“…This occurs because the initial cleaning request lacks the accurate information about patient conditions or room status that dictate the required type of cleaning. Our recent DSA modelling effort (Alhaider et al, 2020) qualitatively indicates that deficient SA distribution is commonly associated with repeated room cleaning and patient transport in CTaC. Thus, quantitative verification of such inefficiencies could be invaluable for affirming the merits of the DSA framework and improving patient flow at Carilion Clinic.…”

“…The DSA network model reveals the communication and coordination between agents (i.e., human and machine) and situation awareness (SA) exchange between them for patient flow management (Alhaider et al, 2020(Alhaider et al, , 2018. For example, Figure 1 presents a DSA network model depicting the room cleaning process after patient discharge.…”

“…Carilion Clinic, a level I trauma center in Roanoke, VA., has established a patient flow command centerthe Carilion Transfer and Communications Center that led to $1.5 million annual cost savings (Davenport et al, 2018;Morris & Carter, 2015). As the knowledge of how CTaC improves patient flow could be invaluable for other health centers, we adopted the Distributed Situation Awareness (DSA; Stanton et al, 2006; also see Lau & Boring, 2017) framework to study who (social), how (task), and what (knowledge) is necessary to manage patient flow, resulting in a network model (Alhaider et al, 2020) that reveals the necessary information exchanges to manage patient flow.…”

Resilience to the COVID-19 Pandemic: A Distributed Situation Awareness Perspective

“…DSA models can describe who, how, and what in CECC operations central to controlling COVID-19. Amongst other applications (e.g., [27]), DSA modeling has successfully illustrated the social/who, task/how, and knowledge/what element of a command center for patient flow management, thereby highlighting its strengths and weaknesses in the communication and coordination [27]. Thus, DSA model of the CECC outlining the social, task, and knowledge elements in managing the epidemic should provide insights into effective design of provisionary command center.…”