Utilization prediction for helicopter emergency medical services

• Published in: Annals of emergency medicine Vol. 16; no. 4; pp. 391 - 398
• Main Authors: Maclone, A.R., Wilcox, David E
• Format: Journal Article Conference Proceeding
• Language: English
• Published: New York, NY Mosby, Inc 01.04.1987; Elsevier
• Subjects: Aircraft; Anesthesia. Intensive care medicine. Transfusions. Cell therapy and gene therapy; Biological and medical sciences; Emergency and intensive care: techniques, logistics; EMS, helicopter, prediction of use; Forecasting; Health Services Needs and Demand - trends; Health Services Research - trends; helicopter, EMS, prediction of use; Humans; Intensive care medicine; Intensive care unit. Emergency transport systems. Emergency, hospital ward; Massachusetts; Medical sciences; Rural Population; Transportation of Patients; United States; United States; Massachusetts; EMS, helicopter, prediction of use; helicopter, EMS, prediction of use; Human; Mobile unit; Helicopter; Emergency; Resuscitation; Emergency care mobile unit
• ISSN: 0196-0644; 1097-6760
• DOI: 10.1016/S0196-0644(87)80357-8

As the number of helicopter emergency medical services (HEMS) programs continues to expand rapidly, the need for an accurate, readily obtainable, inexpensive method of utilization prediction for these services has become apparent. Accurate volume and case mix prediction for these services are increasingly important as financial constraints become more severe. All previous methods of utilization prediction based on experiences of individual services or accident statistics have been either inaccurate, costly, or difficult to obtain in a relatively short period of time. Prediction of HEMS utilization requires consideration of many significant, simultaneous factors, in addition to patient needs based on population statistics. Through use of a survey of all hospital-based helicopter emergency service programs and published census data, this study analyzed factors relating to helicopter program volume and case mix, providing insight as to why previous methods utilizing total population were inaccurate. A more accurate yet simple and inexpensive method of utilization prediction for HEMS was developed.