Real-time automated paging and decision support for critical laboratory abnormalities. Etchells, E., Adhikari, N. K J, Wu, R., Cheung, M., Quan, S., Mraz, R., Wong, B., Pinto, R., Mehta, R., Morra, D., Fowler, R., Sibbald, W., Abrams, H., & Rossos, P. G BMJ quality & safety, 20(11):924–930, November, 2011.
doi  abstract   bibtex   
BACKGROUND: For patients with critical laboratory abnormalities, timely clinical alerts with decision support could improve management and reduce adverse events. METHODS: The authors developed a real-time clinical alerting system for critical laboratory abnormalities. The system sent alerts to physicians as text messages to a smartphone or alphanumeric pager. Decision support was available via smartphone or hospital intranet. The authors evaluated the system in a prospective controlled stepped-wedge study with blinded outcome assessment in general internal medicine units at two academic hospitals. The outcomes were the proportion of potential clinical actions that were actually completed in response to the alert, and adverse events (worsening of condition or complications related to treatment of the condition). RESULTS: The authors evaluated 498 laboratory conditions on 271 patients. Overall, only 50% of potential clinical actions were carried out, and there were adverse clinical events within 48 h for 36% of the laboratory conditions. The median (IQR) proportion of potential clinical actions that were actually completed was 50% (33-75%) with alerting system on and 50% (33-100%) with alerting system off (p=0.94, Wilcoxon rank sum test). When the alerting system was on (n=164 alerts) there were 67 adverse events within 48 h of the alerts (42%). When the alerting system was off (n=334 alerts), there were 112 adverse events within 48 h (33%; difference: 9% higher with alerting system on, p=0.06). CONCLUSIONS: The provision of real-time clinical alerts and decision support for critical laboratory abnormalities did not improve clinical management or decrease adverse events.
@article{etchells_real-time_2011,
	title = {Real-time automated paging and decision support for critical laboratory abnormalities},
	volume = {20},
	issn = {2044-5423},
	doi = {10.1136/bmjqs.2010.051110},
	abstract = {BACKGROUND: For patients with critical laboratory abnormalities, timely clinical alerts with decision support could improve management and reduce adverse events.
METHODS: The authors developed a real-time clinical alerting system for critical laboratory abnormalities. The system sent alerts to physicians as text messages to a smartphone or alphanumeric pager. Decision support was available via smartphone or hospital intranet. The authors evaluated the system in a prospective controlled stepped-wedge study with blinded outcome assessment in general internal medicine units at two academic hospitals. The outcomes were the proportion of potential clinical actions that were actually completed in response to the alert, and adverse events (worsening of condition or complications related to treatment of the condition).
RESULTS: The authors evaluated 498 laboratory conditions on 271 patients. Overall, only 50\% of potential clinical actions were carried out, and there were adverse clinical events within 48 h for 36\% of the laboratory conditions. The median (IQR) proportion of potential clinical actions that were actually completed was 50\% (33-75\%) with alerting system on and 50\% (33-100\%) with alerting system off (p=0.94, Wilcoxon rank sum test). When the alerting system was on (n=164 alerts) there were 67 adverse events within 48 h of the alerts (42\%). When the alerting system was off (n=334 alerts), there were 112 adverse events within 48 h (33\%; difference: 9\% higher with alerting system on, p=0.06).
CONCLUSIONS: The provision of real-time clinical alerts and decision support for critical laboratory abnormalities did not improve clinical management or decrease adverse events.},
	language = {eng},
	number = {11},
	journal = {BMJ quality \& safety},
	author = {Etchells, Edward and Adhikari, Neill K J and Wu, Robert and Cheung, Mark and Quan, Sherman and Mraz, Richard and Wong, Brian and Pinto, Ruxandra and Mehta, Rajin and Morra, Dante and Fowler, Robert and Sibbald, William and Abrams, Howard and Rossos, Peter G},
	month = nov,
	year = {2011},
	pmid = {21725046},
	keywords = {Aged, Aged, 80 and over, Automation, Clinical Laboratory Information Systems, Communication, Decision Support Systems, Clinical, Diagnosis, Computer-Assisted, Female, Humans, Male, Middle Aged, Prospective Studies},
	pages = {924--930}
}
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