TY - GEN
T1 - Identifying Clusters and Themes from Incidents Related to Health Information Technology in Medical Imaging as a Basis for Improvements in Practice
AU - Jabin, Shafiqur Rahman
AU - Magrabi, Farah
AU - Hibbert, Peter
AU - Schultz, Tim
AU - Runciman, William
PY - 2019/12
Y1 - 2019/12
N2 - Beyond identifying and counting the things that go wrong, understanding how and why they go wrong requires qualitative research, especially for low-frequency events. The purpose of this study was to identify and characterize patient safety and quality issues related to health information technology (HIT) in medical imaging by collecting and analyzing incident reports through the lens of thematic analysis. In this article, we analyze 5 clusters: Staff related issues (16%), issues with diagnosis (15%), HIT incidents that involved 'paper record' (12%), information and communication related (4%), and 'action taken' related issues (4%). Human factors involved people failing to scan forms into the computer system (consents, requests, bookings, questionnaires, assessments, treatments and prescriptions), and another 4% involved failure to enter verbally imparted information into the system (about infectious patients, cancelled cases, and the status of reports). All of these problems had their genesis in human errors and violations. Human factors were found to cause more deleterious effects than technical factors. Of three instances of deaths caused by diagnostic issues, two were triggered by human factors, missed diagnosis. However, 'staff or organizational outcome' was evenly distributed for both human and technical factors. It was therefore important to identify and characterize these incidents related to health information technology in medical imaging through the lens of thematic analysis, to provide a basis for improvements in preventing issues and improving clinical practice.
AB - Beyond identifying and counting the things that go wrong, understanding how and why they go wrong requires qualitative research, especially for low-frequency events. The purpose of this study was to identify and characterize patient safety and quality issues related to health information technology (HIT) in medical imaging by collecting and analyzing incident reports through the lens of thematic analysis. In this article, we analyze 5 clusters: Staff related issues (16%), issues with diagnosis (15%), HIT incidents that involved 'paper record' (12%), information and communication related (4%), and 'action taken' related issues (4%). Human factors involved people failing to scan forms into the computer system (consents, requests, bookings, questionnaires, assessments, treatments and prescriptions), and another 4% involved failure to enter verbally imparted information into the system (about infectious patients, cancelled cases, and the status of reports). All of these problems had their genesis in human errors and violations. Human factors were found to cause more deleterious effects than technical factors. Of three instances of deaths caused by diagnostic issues, two were triggered by human factors, missed diagnosis. However, 'staff or organizational outcome' was evenly distributed for both human and technical factors. It was therefore important to identify and characterize these incidents related to health information technology in medical imaging through the lens of thematic analysis, to provide a basis for improvements in preventing issues and improving clinical practice.
KW - health information technology
KW - incident reports
KW - medical imaging
KW - safety and quality
KW - thematic analysis
UR - http://www.scopus.com/inward/record.url?scp=85082009553&partnerID=8YFLogxK
U2 - 10.1109/IST48021.2019.9010280
DO - 10.1109/IST48021.2019.9010280
M3 - Conference contribution
AN - SCOPUS:85082009553
T3 - IST 2019 - IEEE International Conference on Imaging Systems and Techniques, Proceedings
BT - IST 2019 - IEEE International Conference on Imaging Systems and Techniques, Proceedings
PB - Institute of Electrical and Electronics Engineers
CY - Piscataway, NJ
T2 - 2019 IEEE International Conference on Imaging Systems and Techniques, IST 2019
Y2 - 8 December 2019 through 10 December 2019
ER -