Daniel J Olsson, DO, FACOEP

Current Appointments

• Assistant Professor of Emergency Medicine

Hospital Campus

• Downtown

Clinic/Unit

• Emergency Department, Pediatrics
  Upstate University Hospital - Downtown Campus
  Google Maps & Directions
  2nd Fl., East Wing, 750 East Adams Street
  Syracuse, NY 13210
  315 464-5565
  
• Emergency Department, Adult
  Upstate University Hospital - Downtown Campus
  Google Maps & Directions
  2nd Fl., East Wing, 750 East Adams Street
  Syracuse, NY 13210
  315 464-5611
  
• Hyperbaric Medicine
  Upstate University Hospital - Downtown Campus
  Google Maps & Directions
  Rm. 1528, 750 East Adams Street
  Syracuse, NY 13210
  315 464-4910
  

Web Resources

• Professional Site

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

Specialties & Certification

• Emergency Medicine

Diseases & Conditions Treated

• Diabetes and Illness
• Diabetes and Nerve Damage
• Diabetic Foot Complications
• Medical Emergencies
• Radiatiod Proctitis

Treats

• Adults and Children

Treatments/Services

• Emergency Services

Current Hospital Privileges

• Upstate University Hospital

Web Resources

• Professional Site

Research Abstract

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