EMS Response Time in Low- vs High-Income Neighborhoods

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Patients from the poorest neighborhoods experienced longer ambulance response and transport times for out-of-hospital cardiac arrest.
Patients from the poorest neighborhoods experienced longer ambulance response and transport times for out-of-hospital cardiac arrest.

Patients from the poorest neighborhoods experienced longer ambulance response and transport times for out-of-hospital cardiac arrest encounters compared with benchmarks adopted by national EMS agencies, according to a review published in JAMA Network Open.

The investigators of this retrospective cross-sectional study analyzed ambulance 9-1-1 response data for out-of-hospital cardiac arrest from 46 US state repositories. The study sample included 63,600 patients with cardiac arrest encounters, including 37,550 (59%) patients from high-income areas and 8192 (12.9%) from low-income areas. Data were extracted from the National Emergency Medical Services Information System (NEMSIS).

Negative binomial regressions models were used to evaluate the association between ZIP code–level income and EMS response time, on-scene time, transport time, and total EMS time. The investigators performed sensitivity analyses to control for variables including patient demographics, health insurance status, urbanicity, and time of day. The mean length of response time in minutes for the lowest and highest income quartiles were then compared with the same EMS benchmarks set for responding to cardiac arrest calls in less than 4, 8, and 15 minutes.

Analyzing the patient characteristics in high-income areas vs low-income areas showed greater proportions of white patients (70.1% vs 62.2%; P <.001); men (58.8% vs 54.1%; P <.001); privately insured patients (29.4% vs 15.9%; P <.001); uninsured patients (15.3% vs 7.9%; P <.001) in high-income areas and a greater proportion of Medicaid-insured patients (38.3% vs 15.8%; P <.001) in low-income areas.

Comparing total EMS time (including response time, on-scene time, and transport time), the highest income quartile by ZIP code had a mean time of 37.5 minutes±13.6), while the lowest income quartile had a mean time of 43 minutes±18.8). Controlling for urban ZIP code, weekday, and time of day, low-income areas had a 10% (95% CI, 9%-11%; P <.001) longer total EMS time than high-income areas, which translated into a difference of 3.8 minutes.

Only 31.4% of cardiac arrest EMS activations in high-income ZIP codes and 30.0% in low-income ZIP codes reached the incident scene within 4 minutes. However, a higher proportion of EMS responses in high-income vs low-income areas met the national 8-minute (78.1% vs 72.4%; P <.001) and 15-minute (96.7% vs 92.7%; P <.001) benchmarks.

Limitations to the study included the NEMSIS registry, which is confined to EMS activations and not individual patient calls, and multiple 9-1-1 calls that may be associated with the same patient. Furthermore, EMS performance metrics, as well as the benchmarks used in this study, are not nationally standardized and organization guidelines may vary; other factors, such as ride-sharing services, may drive disparities. Less than 1% of 9-1-1 calls are for cardiac arrests, meaning the results of this study may not necessarily be generalized to other types of time-sensitive 9-1-1 calls.

“Given that whether or not a patients survives cardiac arrest can depend on a matter of minutes, even small delays in EMS response times may negatively alter patient outcomes,” the researchers concluded. “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. Understanding where gaps exist can help guide improvements in policies and develop interventions to address prehospital care disparities and ultimately disparities in patient outcomes.”

Reference                    

Hsia RY, Huang D, Mann NC, et al. A US national study of the association between income and ambulance response time in cardiac arrest [published online November 30, 2018]. JAMA Network Open. doi: 10.1001/jamanetworkopen.2018.5202

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