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Implementation and evaluation of an integrated computerized asthma management system in a pediatric emergency
Judith W Dexheimer1, Thomas J Abramo2, Donald H Arnold3
1Division of Emergency Medicine, Cincinnati Children's, United States; Division of Biomedical Informatics, Cincinnati Children's, United States.
Insights
A computerized asthma management system in a pediatric emergency department did not decrease time to disposition decision. This asthma care system did not impact hospital admission rates or length of stay.
Area of Science:
- Pediatric Emergency Medicine
- Health Informatics
- Clinical Decision Support Systems
Background:
- Asthma exacerbations require timely and evidence-based care in pediatric emergency departments.
- Integrating national asthma guidelines into clinical workflows can improve patient management.
- Computerized systems offer potential for standardizing care and improving efficiency.
Purpose of the Study:
- To evaluate the impact of a computerized asthma management system, including a Bayesian network for patient identification, on the time to disposition decision in a pediatric ED.
- To determine if workflow-integrated technology improves efficiency in managing pediatric asthma exacerbations.
Main Methods:
- A prospective, randomized controlled trial was conducted in a pediatric emergency department.
- Patients aged 2-18 with suspected asthma exacerbations were identified by a Bayesian network and randomized to intervention or standard care.
- The intervention group received computer-driven asthma management, including triage scoring and guideline-compliant order sets.
Main Results:
- The Bayesian network identified 1339 patients with asthma exacerbations (positive predictive value 69.9%).
- No significant difference was found in the median time to disposition decision between the intervention (228 min) and control (223 min) groups (p=0.362).
- Hospital admission rates and emergency department length of stay remained similar between the groups.
Conclusions:
- The implemented computerized asthma management system did not reduce the time to disposition decision.
- The system did not negatively impact patient flow, admission rates, or overall length of stay.
- While not improving decision time, the system integrated information systems to support clinical communication.
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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