The Role of Response Time in EMS Performance

Several months ago, Rob Lawrence of the Richmond Ambulance Authority started a thread on the High Performance EMS Group of LinkedIn by asking “So what does the phrase ‘High Performance EMS’ mean to you?�? This innocent sounding question sparked immediate debate even within the small group at that time. Benjamin Podsiadlo of AMR quickly tied the quality of EMS performance to “experience�? and “outcomes�? stating further that “response time is not an evidence based factor in ALS performance.�? He later backed up his assertion by writing that “the catch 22 of pushing the workforce to be responsible and accountable drivers while simultaneously achieving narrow response time goals to the vast majority incidents that have no medical need for such high speed driving is also a bizarre and irresponsible contradiction.�? This is a point that even Lawrence admits could foster the “mentality of ‘arrive on time and the patient dies – good outcome, arrive late and the patient lives – bad outcome’�? that has already been affecting common sense both in the UK and increasingly in the US since NFPA 1710 set response time standards several years ago.

While there were other good comments, I would like to focus on the specific assertion that measuring response time (a well established practice today such as at Huron Valley Ambulance’s public web Performance Dashboard) is not an “evidence-based�? practice. There are many specific accounts of individual lives saved that I have heard mentioned by different agencies, but I will concede that the plural of “anecdote�? is not “data�?. However, one of the best stories of response time saving lives was made on February 9 when Richard Sposa of Jersey City Medical Center EMS discussed an interesting finding in a recent webcast. The chart reproduced here shows a correlation between

response time and the Return of Spontaneous Circulation (ROSC). This unexpected finding clearly traced an upward trend of ROSC with the decline in Average Response Time for Priority 1 Calls graphed quarterly from the beginning of 2005 to the end of 2007. This is a verified statistical trend (Mount Sinai Hospital reviewed these findings) and I suggest you click to view the graph in full detail. This shows not just living anecdotes, but a statistical increase patients with restored heartbeats.

Many things about our business can and should be questioned, but this is exactly the sort of evidence I would like to see investigated at other services. Can what Jersey City Medical Center is experiencing be reproduced elsewhere? And probably more importantly, does fast response necessarily mean “high speed driving�??

The point of System Status Management (SSM) is that ambulances can be effectively pre-positioned through scientific statistical forecasting in order to reduce the time of a response even without driving faster to the call.  Zoll Software Solutions, as an example, considers the elimination of inefficiencies to be a core component for closing the loop on your dispatch process and is even offering free medical equipment to customers who use this technology to improve their system. One customer who has done this already with Zoll technology is Grand Rapids who was also featured in the following FOX News video on Predicting Where your Next Emergency will Happen.

If you believe that knowing where your next calls are likely to come from in time to allow you to safely prepare for that response, the science is available today. You just need to be able to integrate that knowledge into your process.