TY  - GEN
AB  - Modern hospitals are increasingly complex entities comprising healthcare teams, working in parallel, to provide care for hospitalized patients. The team’s goal of providing 
excellent clinical care to patients is highly dependent upon each team member’s ability to communicate efficiently and effectively. Unfortunately, as teams and facilities grow in 
size and complexity, communication, which was once predominantly face-to-face, is increasingly complex and difficult. This project was conceived to build the foundation for future work in this domain, by 1) creating a robust and flexible data pipeline to clean and transform data from a secure text messaging database into network models which will enable 2) utilizing network-specific analysis to (a) identify the characteristics of the inpatient communication network, (b) understand key users and roles within the communication network, and (c) help understand vulnerable users and populations and the impact of emerging automated messaging systems on the communication network of a hospital system.
AD  - Oregon Health and Science University
AU  - Hagedorn, Philip
DA  - 2018
DO  - 10.6083/EA8V6P
DO  - DOI
ID  - 3133
KW  - Text Messaging
KW  - Inpatients
KW  - Patient Care Team
KW  - care quality
L1  - https://digitalcollections.ohsu.edu/record/3133/files/4097_etd.pdf
L2  - https://digitalcollections.ohsu.edu/record/3133/files/4097_etd.pdf
L4  - https://digitalcollections.ohsu.edu/record/3133/files/4097_etd.pdf
LA  - eng
LK  - https://digitalcollections.ohsu.edu/record/3133/files/4097_etd.pdf
N2  - Modern hospitals are increasingly complex entities comprising healthcare teams, working in parallel, to provide care for hospitalized patients. The team’s goal of providing 
excellent clinical care to patients is highly dependent upon each team member’s ability to communicate efficiently and effectively. Unfortunately, as teams and facilities grow in 
size and complexity, communication, which was once predominantly face-to-face, is increasingly complex and difficult. This project was conceived to build the foundation for future work in this domain, by 1) creating a robust and flexible data pipeline to clean and transform data from a secure text messaging database into network models which will enable 2) utilizing network-specific analysis to (a) identify the characteristics of the inpatient communication network, (b) understand key users and roles within the communication network, and (c) help understand vulnerable users and populations and the impact of emerging automated messaging systems on the communication network of a hospital system.
PB  - Oregon Health and Science University
PY  - 2018
T1  - Inpatient communication networks: leveraging secure text-messaging platforms to gain insight into inpatient communication systems
TI  - Inpatient communication networks: leveraging secure text-messaging platforms to gain insight into inpatient communication systems
UR  - https://digitalcollections.ohsu.edu/record/3133/files/4097_etd.pdf
Y1  - 2018
ER  -