Increasing bystander CPR: potential of a one question telecommunicator identification algorithm

Scand J Trauma Resusc Emerg Med. 2015 May 13;23:39. doi: 10.1186/s13049-015-0115-1.


Objectives: Telecommunicators use a two-question algorithm to identify cardiac arrest: Is the individual conscious? Is the individual breathing normally? Although this approach increases arrest identification and consequently bystander CPR, the strategy does not identify all arrests and requires time to complete. We evaluated the implications of a one-question strategy that inquired only about consciousness.

Methods: We undertook a 3-month observational study of consecutive cases identified as unconscious by the telecommunicator prior to EMS arrival who were not receiving bystander CPR. We evaluated the extent that a one-question strategy could increase arrest identification and reduce the identification interval; and the trade-off whereby additional persons without arrest could potentially receive CPR.

Results: Among 679 eligible cases, 20% (n = 135) were in arrest and 80% (n = 544) were not in arrest. The two-question algorithm identified 90% (121/135) as true arrest. Of the 135 in arrest, 70% (n = 95) received compressions. The median interval from call to arrest identification was 72 seconds, with a median of 14 seconds for the breathing normally question. Using the two-question algorithm, telecommunicators incorrectly classified 30% (n = 164/544) of non-arrests as arrest. Bystanders proceeded to compressions in 16% (n = 85/544) of persons not in arrest. A one-question approach that inquired only about consciousness could potentially increase the arrest identification by 10% (14/135) and reduce the interval to compressions by a median of 14 seconds; however the strategy would potentially triple the number of non-arrest cases (544 versus 164) eligible for CPR instructions.

Conclusion: A single-question arrest identification algorithm may not achieve a favorable balance of risk and benefit.

Publication types

  • Observational Study
  • Research Support, Non-U.S. Gov't

MeSH terms

  • Algorithms*
  • Cardiopulmonary Resuscitation / methods*
  • Decision Making*
  • Emergency Medical Service Communication Systems*
  • Humans
  • Out-of-Hospital Cardiac Arrest / diagnosis*
  • Out-of-Hospital Cardiac Arrest / therapy*
  • Quality Assurance, Health Care
  • Retrospective Studies
  • Treatment Outcome
  • Unconsciousness
  • Washington