Distributed Situation Awareness in Patient Flow Management: An Admission Case Study

Abstract

Managing patient flow can be an effective strategy to reduce idling hospital beds, thereby lowering the healthcare cost without sacrificing quality of care. However, improving patient flow can be a major challenge due to the complex patterns of communication across diverse hospital staff. To identify improvement opportunities, this paper investigates whether the Distributed Situation Awareness (DSA) framework can feasibly and meaningfully model Situation Awareness (SA) in patient flow. The investigation involved a case study on modeling the DSA of the admission phase in patient flow for a level 1 trauma center. A DSA model combining task, knowledge, and social networks was created, showing feasibility of the framework in depicting the distribution and transaction of knowledge across workers and information systems. Further, a true elective admission case was mapped onto the DSA model, verifying its practical merits.

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

“…The DSA three-part method helped to identify functions and knowledge/SA of the CECC as well as the government ministries and agencies pertinent in their communication. Due to the lack of access to the CECC, data elicitation only involved documentation review of published articles and public video recordings rather than internal documentation review, interviews, and observations [14], [28], [29]. Data extraction involved identifying how the CECC operates (i.e., task elements), what information or SA is generated or transmitted (i.e., knowledge elements), and which ministries and agencies are involved for each operation (i.e., social elements).…”

Quantitative Evidence Supporting Distributed Situation Awareness Model of Patient Flow Management

“…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.…”

Modeling and simulation for situation awareness distribution and transactions for intrahospital patient transports

“…Previous research revealed that patient transport efficiency can be investigated with Distributed Situation Awareness (Alhaider et al, 2018(Alhaider et al, , 2020a, a theoretical framework proposed by Stanton et al (2006) for depicting the distribution and exchange of situation awareness (SA) between agents (i.e., human and machines) in complex systems. Alhaider et al, (2020a) presented a descriptive DSA network model combining social, task, and knowledge elements of patient transport to identify deficient SA transactions between agents that appeared to be associated with re-scheduling, cancelations, and delays, thereby prolonging minimum length of the patient journeys.…”