The epidemiology of emergency medical services use by older adults: an analysis of the National Hospital Ambulatory Medical Care Survey.
OBJECTIVE
To characterize older adult emergency department (ED) visits arriving by emergency medical services (EMS) and to identify factors associated with those patient visits.


METHODS
A secondary analysis of the ED component of the 1997-2000 National Hospital Ambulatory Medical Care Survey using logistic regression analyses was conducted. The dependent variable was the modes of arrival (EMS vs. not EMS) to the ED. Independent variables were grouped into four domains: demographic, clinical, system, and service characteristics.


RESULTS
Between 1997 and 2000, 38% of EMS responses were for patients aged 65 years and older. During that period, 62.2 million older adult ED patient visits occurred; 38% arrived via EMS. The average rate of EMS utilization by older adults was 167/1,000 population per year, more than four times the rate for younger patients (39/1,000 population). Fifty-three percent of EMS responses with transport to an ED for older adults resulted in hospital admission. Factors found to be associated with EMS mode of arrival included demographic (older age and urban residence), clinical (need for more rapid care and circulatory system illnesses), and service (need for procedures).


CONCLUSIONS
Older adults account for a large proportion of EMS responses and use EMS at a disproportionately high rate. As the older adult population grows, EMS systems must prepare for the increased volume of older adults by making changes in training, operations, and equipment.
Shah
Manish N
MN
Department of Emergency Medicine, University of Rochester School of Medicine & Dentistry, Rochester, NY, USA. manish.shah@rochester.edu
Bazarian
Jeffrey J
JJ
Lerner
E Brooke
EB
Fairbanks
Rollin J
RJ
Barker
William H
WH
Auinger
Peggy
P
Friedman
Bruce
B
D017677:Age Distribution; D000368:Aged; D000369:Aged, 80 and over; D003430:Cross-Sectional Studies; D004632:Emergency Medical Services / Q000706:statistics & numerical data*; D005260:Female; D005853:Geriatrics; D006801:Humans; D016015:Logistic Models; D008297:Male; D011336:Probability; D014481:United States