That finding, which the study’s authors call “alarming,” may explain, at least in part, why the death rate from cardiac arrest — a sudden malfunction of the heart that stops it from beating — is so much higher among people residing in lower-income ZIP codes.
“When it comes to a cardiac arrest, every minute counts,” said Dr. Renee Hsia, the study’s lead author and a professor of emergency medicine at the University of California, San Francisco, in a released statement. “We found that emergency medical services response times were 10 percent longer in the poorest neighborhoods.”
That may not sound like a lot, but a 2017 study found that even a 4.4-minute delay in emergency services reaching someone who had experienced a cardiac arrest was associated with a 13 percent increased risk of that person dying within the next 30 days.
Where the data came from
Hsia and her colleagues decided to focus their study on cardiac arrest because it requires immediate medical attention and has a high mortality rate. By stabilizing cardiac arrest patients and transporting them to a hospital, EMS performs a crucial role in the outcome of such cases.
For the study, the researchers analyzed data on 63,600 cases of cardiac arrest in which an emergency medical services (EMS) ambulance was called and transported the patient, still alive, to a hospital. The cases occurred in 2014 and took place in 46 states, including Minnesota.
The researchers looked at four specific EMS time measures within that database: the time from the ambulance’s dispatch to its arrival at the patient’s location, from the ambulance’s arrival to its departure from the location, from the ambulance’s departure at the patient’s location to its arrival at the hospital, and the total amount of time EMS was involved with each case.
They also compared the results of those measures with time benchmarks that various systems across the country have adopted for responding to heart attacks.
The database also included the ZIP code where each cardiac arrest took place. The researchers used Census Data to determine the average household income for each of those ZIP codes and then ranked all the neighborhoods into four income groups: the top 25 percent (median incomes from about $57,000 to $113,000), the bottom 25 percent (median incomes from about $10,000 to $43,000) and two groups in between.
The wealthiest areas had a higher proportion of cardiac arrest patients who were privately insured (29 percent versus 16 percent in the low-income areas), while the poorer areas had a greater proportion of Medicaid-insured patients (38 percent versus 16 percent in the high-income areas).
After crunching all the data, Hsai and her colleagues found that EMS responses were more likely to meet national time benchmarks in high-income areas than in low-income ones. They also found that the total EMS response — from receiving the 911 call to getting the patient to the hospital — averaged 37.5 minutes in the highest-income zip codes, compared to 43 minutes in the lowest ones.
In addition, the time an ambulance spent on the scene with a patient, the time the ambulance took to transport the patient to the hospital and the total time EMS spent responding to the patient were 10 percent longer in the lowest-income ZIP codes.After adjusting for such confounding factors as urban density and time of day (to account for higher traffic and more clogged roads), the study found the EMS response in the poorest ZIP codes was an average of 3.8 minutes longer than in the wealthiest ones.
The researchers cite several possible reasons for this disparity, including the “increasing number of emergency department and hospital closures in lower-income areas.” The farther patients are from a hospital, the longer it takes for an ambulance to reach them.
The researchers also note that “the new, shifting landscape to privately owned ambulance companies may lead to a greater focus on profitability over public need, which could drive more companies to serve wealthier neighborhoods, potentially increasing total EMS time because poorer neighborhoods would have fewer ambulances and personnel to go around.”
Eliminating system-level disparities
The study comes with several caveats. It used data from only one year, and it did not take into consideration the level of health insurance coverage in the ZIP codes. Furthermore, it’s unclear how the use of Uber and other ride-sharing services to transport people to hospitals — services that were rapidly expanding in 2014 — may have impacted the study’s results.
Also, cardiac arrests account for less than 1 percent of 911 calls, so the study’s findings may not be applicable to other types of emergency medical situations.
Still, the results are consistent with at least two other studies on this topic — and with studies that have looked at other structural health-related disparities between low- and high-income neighborhoods.
“Our findings show that health care disparities exist at the system-level, including ambulance transport times,” said Hsai. “As hospital closures and the cost of health care continue to rise, we must examine how to ensure access to care for our most vulnerable.”