TY - GEN
T1 - Challenges of health analytics utilization
T2 - 17th International Conference on Informatics, Management, and Technology in Healthcare, ICIMTH 2019
AU - Khalifa, Mohamed
PY - 2019/1/1
Y1 - 2019/1/1
N2 - The last four decades witnessed a huge progress in digitizing health information, representing an unmatched opportunity for utilizing health analytics in improving the quality of healthcare and reducing its costs. To learn more about different challenges facing the successful utilization of health analytics, a careful review of literature was conducted, and a qualitative analysis was used to explore and classify these challenges. Three main categories of challenges were identified. 1) Technological challenges; hardware, software, and data content, 2) Human challenges; knowledge, experiences, beliefs and attitudes, and end user behaviors, and 3) Organizational challenges; managerial, financial, and legal barriers to optimal utilization of health analytics. The non-technological problems seem to be harder to solve as well as more time consuming, including the existence of a specific business need and a clear vision to guide the project. In addition, health analytics should always be built with the end users in mind.
AB - The last four decades witnessed a huge progress in digitizing health information, representing an unmatched opportunity for utilizing health analytics in improving the quality of healthcare and reducing its costs. To learn more about different challenges facing the successful utilization of health analytics, a careful review of literature was conducted, and a qualitative analysis was used to explore and classify these challenges. Three main categories of challenges were identified. 1) Technological challenges; hardware, software, and data content, 2) Human challenges; knowledge, experiences, beliefs and attitudes, and end user behaviors, and 3) Organizational challenges; managerial, financial, and legal barriers to optimal utilization of health analytics. The non-technological problems seem to be harder to solve as well as more time consuming, including the existence of a specific business need and a clear vision to guide the project. In addition, health analytics should always be built with the end users in mind.
KW - Big Data
KW - Business Intelligence
KW - Health Analytics
KW - Hospitals
UR - http://www.scopus.com/inward/record.url?scp=85068558270&partnerID=8YFLogxK
U2 - 10.3233/SHTI190015
DO - 10.3233/SHTI190015
M3 - Conference proceeding contribution
C2 - 31349264
AN - SCOPUS:85068558270
SN - 9781614999867
T3 - Studies in Health Technology and Informatics
SP - 55
EP - 58
BT - Health informatics vision
A2 - Mantas, John
A2 - Hasman, Arie
A2 - Gallos, Parisis
A2 - Kolokathi, Aikaterini
A2 - Househ, Mowafa S.
A2 - Liaskos, Joseph
PB - IOS Press
CY - Amsterdam
Y2 - 5 July 2019 through 7 July 2019
ER -