|Title||Improving Reponse to Critical Laboratory Results with Automation: Results of a Randomized Controlled Trial|
|Author(s)||Gilad J Kuperman; Jonathan M. Teich; Milenko J. Tanasijevic; Nell Ma'Luf; Eve Rittenberg; Ashish Jha, Julie Fiskio; James Winkelman; David W Bates|
|Source||JAMIA, Vol. 6, No. 6, Pages 512-522|
|Publication Date||Nov/Dec 1999|
|Abstract||Design: Prospective randomized controlled trial. |
Intervention: A computer system to detect critical conditions and automatically notify the responsible physician via the hospital's paging system.
Patients: Medical and surgical inpatients at a large academic medical center. One two-month study period for each service.
Main outcomes: Interval from when a critical result was available for review until an appropriate treatment was ordered. Secondary outcomes were the time until the critical condition resolved and the frequency of adverse events.
Methods: The alerting system looked for 12 conditions involving laboratory results and medications. For intervention patients, the covering physician was automatically notified about the presence of the results. For control patients, no automatic notification was made. Chart review was performed to determine the outcomes.
Results: After exclusions, 192 alerting situations (94 interventions, 98 controls) were analyzed. The intervention group had a 38 percent shorter median time interval until an appropriate treatment was ordered (1.0 hours vs. 1.6 hours, P = 0.003; mean 4.1 vs. 4.6 hours, P= 0.003). The time until the alerting condition was resolved was less in the intervention group, although these results did not achieve statistical significance. The impact of the intervention was more pronounced for alerts that did not meet the laboratory's critical reporting criteria. There was no significant difference between the two groups in the number of adverse events.
Conclusion: An automatic alerting system reduced the time until an appropriate treatment was ordered for patients who had critical laboratory results. Information technologies that facilitate the transmission of important patient data can potentially improve the quality of care.