EMS response slower for cardiac arrest in low-income areas

It takes emergency medical services (EMS) almost four minutes longer to transport cardiac arrest patients from poor neighborhoods to the hospital versus those from high-income neighborhoods, according to a study of 2014 United States EMS data published in JAMA Network Open.

This 3.8-minute difference was calculated after adjusting for factors that would influence traffic such as urban/rural setting and time of day, noted lead author Renee Y. Hsia, MD, MSc, and colleagues.

“Our findings are particularly concerning given the time sensitivity of conditions like cardiac arrest in which the heart has ceased functioning and immediate medical care is required to restore function and circulation,” wrote Hsia, with the department of emergency medicine at the University of California, San Francisco, and coauthors.

“In fact, a recent study showed that even a 4.4-minute delay is associated with a 13% increase in 30-day mortality. This finding is similar to another landmark study performed using EMS response times and mortality, which documented a 17% increase in 1-year mortality from a 1-minute delay.”

The researchers studied 63,600 cardiac arrests from 2014 in which the victim didn’t die on scene and was transported to a hospital. Forty-eight states contributed to the data set, allowing Hsia et al. to evaluate the association between EMS times and zip code-level household incomes across the country. The highest median household income quartile ranged from $57,502 to $113,313, while the lowest ranged from $20,250 to $42,642.

The total EMS time was 37.5 minutes in high-income zip codes and 43 minutes in low-income regions. After controlling for urban zip code, day of the week and time of day, total EMS time remained 10 percent longer in the poorest areas, translating to delays of 3.8 minutes in hospital arrival.

Broken down further, that delay stemmed from:

  • 0.3 minutes longer in response time, or the time between EMS dispatch and arrival at the patient’s location.
  • 2.8 minutes longer spent on scene.
  • 0.6 minutes longer spent transporting the patient from the scene to the hospital.

“Given that whether or not a patient survives cardiac arrest can depend on a matter of minutes, even small delays in EMS response times may negatively alter patient outcomes,” the authors wrote. “Our findings are disturbing given that poorer neighborhoods have higher rates of disease and other structural disparities in health care access that further compound their risk for worse outcomes. Our study shows that these structural disparities begin as early as the initial EMS activation and the resulting services, which is an area previously more traditionally administered by public services and considered less vulnerable to market forces.”

Hsia et al. also pointed out rates of bystander CPR are typically lower in poorer neighborhoods, increasing the importance of timely EMS intervention. However, there is also a trend toward more ambulance companies becoming privately owned, for-profit entities, which may make them more likely to set up shop in wealthier areas and widen this gap.

“Because low-income patients are more dependent on EMS for hospital transport, these reductions in prehospital services likely have disproportionate, detrimental downstream influences on the poor, exacerbating rather than alleviating health disparities,” the researchers wrote.

In a related editorial, Andrew I Friedson, PhD, suggested two additional explanations for the gap in EMS times between low- and high-income zip codes. Since the data was taken in 2014, the first year the Affordable Care Act was implemented, he said there’s a chance the higher rate of insurance expansion in low-income areas compared to wealthier locations could have increased the use of ambulance services for low-acuity services and slowed down their responses to cases of cardiac arrest.  

“The study by Hsia et al. may actually be detecting disparities in ambulance system congestion owing to differences in levels of ACA insurance expansion as opposed to an effect truly driven by income disparities,” Friedson wrote. “In this case, policy might be most effective if aimed at ambulance congestion, perhaps by curbing unnecessary patient use of emergency transport.”

Similarly, Friedson noted ride-sharing services like Uber were expanding rapidly in 2014, first targeting high-income areas, and those companies may have taken some of the burden off of ambulances for nonemergency transportation to the hospital. With all of these factors in mind, Friedson said it would likely require multiple policies to shrink the income-based gap in EMS times for cardiac arrest.