Characteristics of health IT outage and suggested risk management strategies: an analysis of historical incident reports in China.
BACKGROUND
The healthcare industry has become increasingly dependent on using information technology (IT) to manage its daily operations. Unexpected downtime of health IT systems could therefore wreak havoc and result in catastrophic consequences. Little is known, however, regarding the nature of failures of health IT.


OBJECTIVE
To analyze historical health IT outage incidents as a means to better understand health IT vulnerabilities and inform more effective prevention and emergency response strategies.


METHODS
We studied news articles and incident reports publicly available on the internet describing health IT outage events that occurred in China. The data were qualitatively analyzed using a deductive grounded theory approach based on a synthesized IT risk model developed in the domain of information systems.


RESULTS
A total of 116 distinct health IT incidents were identified. A majority of them (69.8%) occurred in the morning; over 50% caused disruptions to the patient registration and payment collection functions of the affected healthcare facilities. The outpatient practices in tertiary hospitals seem to be particularly vulnerable to IT failures. Software defects and overcapacity issues, followed by malfunctioning hardware, were among the principal causes.


CONCLUSIONS
Unexpected health IT downtime occurs more and more often with the widespread adoption of electronic systems in healthcare. Risk identification and risk assessments are essential steps to developing preventive measures. Equally important is institutionalization of contingency plans as our data show that not all failures of health IT can be predicted and thus effectively prevented. The results of this study also suggest significant future work is needed to systematize the reporting of health IT outage incidents in order to promote transparency and accountability.
Center for Medical Informatics, Peking University, Beijing, China; School of Biomedical Informatics, University of Texas Health Sciences Center at Houston, Houston, TX, USA. Electronic address: jblei@hsc.pku.edu.cn.
Jianbo
J
Lei
Center for Medical Informatics, Peking University, Beijing, China.
Pengcheng
P
Guan
Center for Medical Informatics, Peking University, Beijing, China.
Kaihua
K
Gao
Center for Medical Informatics, Peking University, Beijing, China.
Xueqin
X
Lu
Donald Bren School of Information and Computer Sciences, University of California, Irvine, CA, USA.
Yunan
Y
Chen
Center for Statistics and Informatics, Ministry of Health, China.
Yuefeng
Y
Li
Center for Statistics and Informatics, Ministry of Health, China.
Qun
Q
Meng
School of Biomedical Informatics, University of Texas Health Sciences Center at Houston, Houston, TX, USA.
Jiajie
J
Zhang
School of Biomedical Informatics, University of Texas Health Sciences Center at Houston, Houston, TX, USA.
Dean F
DF
Sittig
School of Public Health Department of Health Management and Policy, University of Michigan, Ann Arbor, MI, USA; School of Information, University of Michigan, Ann Arbor, MI, USA.
Kai
K
Zheng
D002681:China; D006801:Humans; D008490:Medical Informatics; D061214:Patient Safety; D012308:Risk Management / Q000458:organization & administration*
Accident prevention; Electronic health records; Failure prediction; Failure recovery, maintenance and self-repair; Health information system; Patient safety; Safety critical systems