Community surveillance of falls among the elderly using computerized EMS transport data

Am J Emerg Med. 1994 Jul;12(4):433-7. doi: 10.1016/0735-6757(94)90055-8.

Abstract

Because falls are common among the elderly and are associated with high morbidity and mortality, community surveillance has been recommended. The purpose of this study was to characterize the impact of falls among the elderly on emergency medical transport services (EMS) and to explore the potential for community surveillance of falls through the use of computerized EMS data. Computerized EMS data and United States census data for 1990 for persons aged > or = 65 in Forsyth County, NC, were used to produce EMS transport rates for falls and to make comparisons by age, gender, race, and residence (nursing home vs community). A fall was reported as the cause for EMS summons in 15.1% (613 of 4,058) of cases. Transport rates in 1990 for falls were 7.8 per 1,000, 25.4 per 1,000, and 58.5 per 1,000 for the age groups of 65 to 74 years, 75 to 84 years, and 85 years and older. Rates were higher for females than for males (17.1 per 1,000 v 8.1 per 1,000) and higher for whites than for African-Americans (14.3 per 1,000 v 10.3 per 1,000). Rates for nursing home residents were four times that of community residents (70.6 per 1,000 v 16.0 per 1,000). Over 50% of nursing home fallers were transported between midnight and 0400 compared with 25% of community dwellers. EMS summons for older adults reporting a fall accounts for a significant portion (15%) of all transports in this county. Computerized EMS data demonstrated patterns of falls among the elderly that are consistent with known demographic factors. The potential for using computerized EMS data as a practical means of community surveillance should be further explored.

Publication types

  • Research Support, Non-U.S. Gov't

MeSH terms

  • Accidental Falls / statistics & numerical data*
  • Age Factors
  • Aged
  • Aged, 80 and over
  • Causality
  • Databases, Factual*
  • Evaluation Studies as Topic
  • Female
  • Humans
  • Male
  • North Carolina / epidemiology
  • Population Surveillance / methods*
  • Racial Groups
  • Residence Characteristics
  • Sex Factors
  • Time Factors
  • Transportation of Patients / statistics & numerical data*