scholarly journals Quantitative Evidence Supporting Distributed Situation Awareness Model of Patient Flow Management

Author(s):  
Abdulrahman A. Alhaider ◽  
Nathan Lau ◽  
Paul B. Davenport ◽  
Melanie K. Morris
Ergonomics ◽  
2020 ◽  
Vol 63 (6) ◽  
pp. 682-709
Author(s):  
Abdulrahman A. Alhaider ◽  
Nathan Lau ◽  
Paul B. Davenport ◽  
Melanie K. Morris

2016 ◽  
Vol 16 (6) ◽  
pp. e25-e26
Author(s):  
Tolu Adebanjo ◽  
Natalie Villafranco ◽  
Nicole Hannemann ◽  
Kimberly Lehecka ◽  
Michelle Lyn ◽  
...  

2018 ◽  
Vol 22 (2) ◽  
pp. 287-303 ◽  
Author(s):  
Jaime González ◽  
Juan-Carlos Ferrer ◽  
Alejandro Cataldo ◽  
Luis Rojas

2020 ◽  
Vol 196 (12) ◽  
pp. 1080-1085
Author(s):  
Dennis Akuamoa-Boateng ◽  
Simone Wegen ◽  
Justin Ferdinandus ◽  
Regina Marksteder ◽  
Christian Baues ◽  
...  

Abstract Purpose The described work aimed to avoid cancellations of indispensable treatments by implementing active patient flow management practices and optimizing infrastructure utilization in the radiation oncology department of a large university hospital and regional COVID-19 treatment center close to the first German SARS-CoV‑2 hotspot region Heinsberg in order to prevent nosocomial infections in patients and personnel during the pandemic. Patients and methods The study comprised year-to-date intervention analyses of in- and outpatient key procedures, machine occupancy, and no-show rates in calendar weeks 12 to 19 of 2019 and 2020 to evaluate effects of active patient flow management while monitoring nosocomial COVID-19 infections. Results Active patient flow management helped to maintain first-visit appointment compliance above 85.5%. A slight appointment reduction of 10.3% daily (p = 0.004) could still significantly increase downstream planning CT scheduling (p = 0.00001) and performance (p = 0.0001), resulting in an absolute 20.1% (p = 0.009) increment of CT performance while avoiding overbooking practices. Daily treatment start was significantly increased by an absolute value of 18.5% (p = 0.026). Hypofractionation and acceleration were significantly increased (p = 0.0043). Integrating strict testing guidelines, a distancing regimen for staff and patients, hygiene regulations, and precise appointment scheduling, no SARS-CoV‑2 infection in 164 tested radiation oncology service inpatients was observed. Conclusion In times of reduced medical infrastructure capacities and resources, controlling infrastructural time per patient as well as optimizing facility utilization and personnel workload during treatment evaluation, planning, and irradiation can help to improve appointment compliance and quality management. Avoiding recurrent and preventable exposure to healthcare infrastructure has potential health benefits and might avert cross infections during the pandemic. Active patient flow management in high-risk COVID-19 regions can help Radiation Oncologists to continue and initiate treatments safely, instead of cancelling and deferring indicated therapies.


Nurse Leader ◽  
2009 ◽  
Vol 7 (1) ◽  
pp. 26-31
Author(s):  
Marty Enriquez ◽  
Marjorie Sisson ◽  
Ann Kirby ◽  
Neera Gupta

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