EMERGENCY RESPONSE SERVICES: Mortality – The Case of Cardiac Arrest 7

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Also in contrast to the results on TIME_TO_SCENE, we see that the patient insurance mix affects the time it takes to transport patients to the hospital. Relative to Medicare patients (the majority of our sample), Medicaid patients have shorter transport times. This may partly reflect the fact that Medicaid patients are more likely to reside in the urban areas of their counties (though rural areas of Pennsylvania have Medicaid patients as well). It may also reflect a lack of patient choice: better insured patients may travel longer to get to a better hospital. Privately insured patients tend to travel longer, although this result is somewhat weaker. In addition to the possibility that these patients choose to travel to better hospitals, an alternative explanation is that their insurance policies make some hospitals more desirable than others. For example, patients may anticipate financial penalties from receiving treatment from a hospital which is not affiliated with their health plan.

Having characterized the “intermediate inputs” to patient outcomes, we can now turn to assess the impact of 911 and hospital type on the probability of dying from a cardiac incident requiring ambulance transportation (Figure 4 and Table 9). We begin with a simple reduced-form regression of mortality on 911 as well as the controls from Tables 6-8. We do not find strong effects of 911 on mortality. There are several potential explanations for this result. One is that mortality rates are fairly low, and there are simply not enough deaths in the No 911 and Basic 911 counties to uncover the effects. Another possibility is that unobserved heterogeneity across counties confounds the effects of response time (although our results are robust to a variety of county-level control variables). We do see that mortality is decreasing in the number of hospitals per mile and the income of a county, while it is increasing in the crime rate and it police expenditures.