Daniel J Olsson, DO, FACOEP-D
Research Programs and Affiliations
- Emergency Medicine
Education & Fellowships
- Residency: Chicago Osteopathic Medical Center, 1993
- DO: University of Health Sciences, College of Osteopathic Medicine, MO, 1989
- Internship: Lakeside Hospital, Kansas City, MO, 1989
Prehospital Emergency Medicine
Dr. Olsson's current projects and research interests include Prehospital Emergency Medicine
Specialties & Certification
- Emergency Medicine
Diseases & Conditions Treated
- Medical Emergencies
- Adults and Children
- Emergency Services
Current Hospital Privileges
- Upstate University Hospital
ResearchEmergency Department Overcrowding: Use of a computer model to predict overcrowding in “ real time “.
Olsson, D.*; Joroleman, M.; Scott, J. University Hospital; SUNY Health Science Center, Syracuse, New York, USA 13210
AIMS: Overcrowding in Emergency Departments is an ongoing and serious issue. Many departments are faced with staffing and space issues. Is it possible to predict “ the future “ by developing a computer model to determine “ real time “ needs within the Emergency Department ?
METHODS: Historical data ( EMS transports and ED visits ( length of stay, arrival times and total numbers )) was collected and reviewed. This was obtained from the area Hospital Executive Council and the regional EMS dispatch center. From this information we were able to construct a theoretical model of a patient visit. This “ model “ was then realized into a computer program written from MicrosoftÔ Visual Basic.
RESULTS: By combining fixed data ( patient rooms ) with variable data ( length of stay and EMS rates of arrival ) we were able to generate a visual display. This provides a “ real time “ or predictive color scale on the computer screen that displays patients' arrivals, rooms needed, and times of discharge. From this output, we can glean the staffing and space needs given current / fluctuating EMS transports ( as indicated by arrival rates ). Therefore, as the rates of EMS arrivals fluctuate ( such as with weather ) one can predict the varying needs of the Emergency Department.
CONCLUSIONS: By adapting an accurate computer model we can provide immediate real time information regarding ED census in an attempt to ameliorate overcrowding, decrease nursing stress and improve patient care.
Presented as an Oral Presentation during the International Conference on Emergency Medicine, Cairns, Queensland, Australia, June 2004
Faculty Profile Shortcut: http://www.upstate.edu/faculty/olssond