TY - JOUR
T1 - Implementation and evaluation of an integrated computerized asthma management system in a pediatric emergency department
T2 - A randomized clinical trial
AU - Dexheimer, Judith W.
AU - Abramo, Thomas J.
AU - Arnold, Donald H.
AU - Johnson, Kevin
AU - Shyr, Yu
AU - Ye, Fei
AU - Fan, Kang Hsien
AU - Patel, Neal
AU - Aronsky, Dominik
N1 - Funding Information:
This work was supported by NIH LM 009747-01 (Dr Dexheimer, Dr Aronsky) and NHLBI K23 HL80005 (Dr Arnold). The first author was supported by a Training Grant from the NLM ( T15 LM 007450-03 ).
Publisher Copyright:
© 2014.
PY - 2014/11/1
Y1 - 2014/11/1
N2 - Objective: The use of evidence-based guidelines can improve the care for asthma patients. We implemented a computerized asthma management system in a pediatric emergency department (ED) to integrate national guidelines. Our objective was to determine whether patient eligibility identification by a probabilistic disease detection system (Bayesian network) combined with an asthma management system embedded in the workflow decreases time to disposition decision. Methods: We performed a prospective, randomized controlled trial in an urban, tertiary care pediatric ED. All patients 2-18 years of age presenting to the ED between October 2010 and February 2011 were screened for inclusion by the disease detection system. Patients identified to have an asthma exacerbation were randomized to intervention or control. For intervention patients, asthma management was computer-driven and workflow-integrated including computer-based asthma scoring in triage, and time-driven display of asthma-related reminders for re-scoring on the electronic patient status board combined with guideline-compliant order sets. Control patients received standard asthma management. The primary outcome measure was the time from triage to disposition decision. Results: The Bayesian network identified 1339 patients with asthma exacerbations, of which 788 had an asthma diagnosis determined by an ED physician-established reference standard (positive predictive value 69.9%). The median time to disposition decision did not differ among the intervention (228 min; IQR = (141, 326)) and control group (223 min; IQR = (129, 316)); (p= 0.362). The hospital admission rate was unchanged between intervention (25%) and control groups (26%); (p= 0.867). ED length of stay did not differ among intervention (262 min; IQR = (165, 410)) and control group (247 min; IQR = (163, 379)); (p= 0.818). Conclusions: The control and intervention groups were similar in regards to time to disposition; the computerized management system did not add additional wait time. The time to disposition decision did not change; however the management system integrated several different information systems to support clinicians' communication.
AB - Objective: The use of evidence-based guidelines can improve the care for asthma patients. We implemented a computerized asthma management system in a pediatric emergency department (ED) to integrate national guidelines. Our objective was to determine whether patient eligibility identification by a probabilistic disease detection system (Bayesian network) combined with an asthma management system embedded in the workflow decreases time to disposition decision. Methods: We performed a prospective, randomized controlled trial in an urban, tertiary care pediatric ED. All patients 2-18 years of age presenting to the ED between October 2010 and February 2011 were screened for inclusion by the disease detection system. Patients identified to have an asthma exacerbation were randomized to intervention or control. For intervention patients, asthma management was computer-driven and workflow-integrated including computer-based asthma scoring in triage, and time-driven display of asthma-related reminders for re-scoring on the electronic patient status board combined with guideline-compliant order sets. Control patients received standard asthma management. The primary outcome measure was the time from triage to disposition decision. Results: The Bayesian network identified 1339 patients with asthma exacerbations, of which 788 had an asthma diagnosis determined by an ED physician-established reference standard (positive predictive value 69.9%). The median time to disposition decision did not differ among the intervention (228 min; IQR = (141, 326)) and control group (223 min; IQR = (129, 316)); (p= 0.362). The hospital admission rate was unchanged between intervention (25%) and control groups (26%); (p= 0.867). ED length of stay did not differ among intervention (262 min; IQR = (165, 410)) and control group (247 min; IQR = (163, 379)); (p= 0.818). Conclusions: The control and intervention groups were similar in regards to time to disposition; the computerized management system did not add additional wait time. The time to disposition decision did not change; however the management system integrated several different information systems to support clinicians' communication.
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U2 - 10.1016/j.ijmedinf.2014.07.008
DO - 10.1016/j.ijmedinf.2014.07.008
M3 - Article
C2 - 25174321
AN - SCOPUS:84908068918
SN - 1386-5056
VL - 83
SP - 805
EP - 813
JO - International Journal of Medical Informatics
JF - International Journal of Medical Informatics
IS - 11
ER -