Older fallers attended to by an ambulance but not transported to hospital: a vulnerable population at high risk of future falls

Aust N Z J Public Health. 2013 Apr;37(2):179-85. doi: 10.1111/1753-6405.12037.

Abstract

Objective: This prospective cohort study describes older non-transported fallers seen by the Ambulance Service of New South Wales (ASNSW), quantifies the level of risk and identifies predictors of future falls and ambulance use.

Methods: Participants were 262 people aged 70 years or older with a fall-related ASNSW attendance who were not transported to an emergency department. They completed a questionnaire about health, medical and physical factors previously associated with falling. Falls were monitored for six months after ambulance attendance with monthly fall calendars.

Results: Participants had a high prevalence of chronic medical conditions, functional limitations and past falls. During follow-up, 145 participants (58%) experienced 488 falls. Significant predictors of falls during follow-up were three or more falls in the past year, being unable to walk more than 10 minutes without resting, and requiring assistance for personal-care activities of daily living (ADLs). Sixty-two participants (25%) required repeat, fall-related ambulance attendance during the study. Predictors of repeat ambulance use were: 3+ falls in past year, requiring assistance for personal-care ADLs and having disabling pain in past month.

Conclusions: Older, non-transported fallers seen by the ASNSW are a vulnerable population with high rates of chronic health conditions.

Implications: Onward referral for preventive interventions may reduce future falls and ambulance service calls.

Publication types

  • Research Support, Non-U.S. Gov't

MeSH terms

  • Accidental Falls / prevention & control*
  • Accidental Falls / statistics & numerical data*
  • Activities of Daily Living
  • Aged
  • Aged, 80 and over
  • Ambulances / statistics & numerical data*
  • Chronic Disease / epidemiology
  • Emergency Service, Hospital / statistics & numerical data*
  • Female
  • Follow-Up Studies
  • Hospitals
  • Humans
  • Logistic Models
  • Male
  • New South Wales / epidemiology
  • Prospective Studies
  • Referral and Consultation / statistics & numerical data*
  • Risk Factors
  • Socioeconomic Factors
  • Surveys and Questionnaires
  • Vulnerable Populations