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Socioeconomic status and out-of-hospital delay
EMERGENCY MEDICAL SERVICES/EDITORIAL
Jane H. Brice, MD, MPH Donald M. Yealy, MD From the Department of Emergency Medicine, University of North Carolina–Chapel Hill, Chapel Hill, NC (Brice); and the Department of Emergency Medicine, University of Pittsburgh, Pittsburgh, PA (Yealy).
Copyright © 2003 by the American College of Emergency Physicians. 0196-0644/2003/$30.00 + 0 doi:10.1067/mem.2003.115
APRIL 2003
41:4
ANNALS OF EMERGENCY MEDICINE
Socioeconomic Status and Out-ofHospital Delay See related article, p. 481. [Ann Emerg Med. 2003;41:491-493.]
In this issue of Annals, Govindarajan and Schull1 report the results of a study examining the effect of socioeconomic status on out-of-hospital transport delays for patients with chest pain. They approach this question by dividing their emergency medical services (EMS) response area geographically into neighborhoods based on the Forward Sortation Area designation, assigning each neighborhood a socioeconomic status based on aggregate income data from the 1996 census. Neighborhoods were then grouped together into 5 income strata. The results suggest that out-of-hospital intervals for patients with chest pain were longer for low socioeconomic status neighborhoods compared with higher socioeconomic status neighborhoods. The social implications of these findings merit attention and review. First, the results must be seen in the context of the entire out-of-hospital delay interval. Second, several factors (ie, societal, system, paramedic, patient) associated with these findings must be evaluated. The authors suggest in their discussion that, compared with the 4 lower socioeconomic status strata, the highest socioeconomic status neighborhoods had a shorter system response interval (by 34 seconds) and shorter transport intervals (by 3 seconds). The authors state: “Out-of-hospital delays for patients with chest pain from lower socioeconomic status neighborhoods might be of particular concern because low socioeco-
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SOCIOECONOMIC STATUS AND OUT-OF-HOSPITAL DELAY Brice & Yealy
nomic status has been associated with an increased incidence of AMI and higher mortality, even in the outof-hospital setting, and because out-of-hospital systems tend to serve lower socioeconomic status groups disproportionately.”1 When examining Table 1 of the article, it appears that the delays occur in the middle socioeconomic status neighborhoods, not in the lowest socioeconomic status neighborhoods. The total out-ofhospital interval for the highest socioeconomic status neighborhoods was identical to that of the lowest socioeconomic status neighborhoods. Nevertheless, it does appear that the highest socioeconomic status neighborhoods, which account for only 11% of the total system volume, have shorter out-of-hospital intervals than neighborhoods with lower income levels. Therefore, the paramedics treated the rich and the poor the same but had longer intervals with the middle class. What does this mean clinically? It is clear that the longest delay interval for patients with chest pain is the interval between symptom onset and the decision to seek care, whether that be driving to the hospital or calling 911. Most patients with chest pain wait at least an hour before seeking care,2,3 and 25% wait more than 6 hours.4-6 In the face of such delay, what difference can 34 or 132 seconds make? Given this, it is clear that the “biggest bang for the buck,” at least in patients with chest pain or stroke symptoms, lies in encouraging seeking care early rather than trying to shave a few minutes off of EMS transport intervals. The importance of societal factors in the results of Govindarajan and Schull1 are unclear. The delays discovered in the data were in the response interval and the transport interval. Both of these intervals are governed by factors beyond the control of the individual paramedic. Traffic patterns in the lower socioeconomic status neighborhoods may not allow for the rapid progress or egress of ambulances. Perhaps the streets are narrower or more often lined with cars. Perhaps the neighborhoods are not easily linked with major transportation arteries. And perhaps the streets in the neighborhood are interrupted or poorly marked, making it difficult to locate the address. Lower socioeconomic status neighborhoods also contain dwellings housing multiple fam-
4 9 2
ilies beneath one roof, making it time-consuming to find the right door on which to knock. Finally, we generally do not build our hospitals in the poorest neighborhoods. Hospitals are frequently for-profit entities. They are built among the clientele they wish to attract (ie, paying customers). Thus, a longer interval to transport a patient from the site of care to the hospital may be the result of complex forces outside of an EMS unit or system’s control. System issues are also important to consider. Where were the ambulances placed? Were the ambulances in fixed locations or engaged in flexible deployment? Were they attached to other public service outposts to maximize utility for all services but perhaps to the individual detriment of the EMS needs? This simple design factor could influence the observed data yet be unrelated, or tangentially related, to the socioeconomic issues. The authors also found that sending an ambulance staffed with advanced care paramedics to the scene increased out-of-hospital delay. It appears that advanced care paramedics are a scarce resource as evidenced by the number of calls to which a primary care paramedic ambulance was sent instead. Discerning the reason why advanced care paramedic ambulances were on the scene for longer than other crew configurations warrants further investigation, but again this is not related to the stated objective—investigating the role of socioeconomic status and out-of-hospital care. It seems unlikely that individual paramedics would be able to detect or infer small differences in income. The income strata as defined by the authors encompass very small increments. For example, the median income for the lowest stratum is $15,295, and the median for the next highest stratum is $17,509. Looking at a patient or a neighborhood and being able to tell that one makes $2,214 more than the other seems improbable. The scheme devised by the authors to lump neighborhoods together takes data in aggregate and says nothing about the income level of the individual patient. Additionally, paramedics are usually not the highest-paid civil servants. In all probability, the middle socioeconomic status neighborhoods with the longest intervals
ANNALS OF EMERGENCY MEDICINE
41:4
APRIL 2003
SOCIOECONOMIC STATUS AND OUT-OF-HOSPITAL DELAY Brice & Yealy
are probably the very neighborhoods in which the paramedics live. Finally, patient factors may have influenced the results found by the authors. They discovered longer out-ofhospital intervals for the elderly (45.3 seconds for each 10 years of age) and for female patients (205.0 seconds). The majority of the delay occurred in the on-scene interval. These patients are generally more complicated, with either lengthy medical histories and extensive medication lists or vague and atypical symptoms, making it more time-consuming to ferret out the underlying problem and decide on a treatment strategy. There will always be patients who are more complicated than others and who are therefore more time-consuming. In summary, Govindarajan and Schull1 have presented a nicely executed study that raises more questions that need to be addressed. Do all out-of-hospital intervals need to be shortened? If so, how can we shorten those in need of this? How do societal factors influence the delivery of out-of-hospital care in a timely manner? What system issues affect out-of-hospital care intervals, and how can we reduce this delay to make out-of-hospital care more efficient? What tools can paramedics develop or be provided with to aid them in the delivery of care to more complicated and timeconsuming patients? Answering these questions will require sophisticated social science methodology and collaboration with professionals of disciplines such as city planners, sociologists, medical geographers, and gerontologists.
5. Yarzebski J, Goldberg RJ, Gore JM, et al. Temporal trends and factors associated with extent of delay to hospital arrival in patients with acute myocardial infarction: the Worcester Heart Attack Study. Am Heart J. 1994;128:255-263. 6. Sheifer SE, Rathore SS, Gersh BJ, et al. Time to presentation with acute myocardial infarction in the elderly. Circulation. 2000;102:1651-1656.
Reprints not available from the authors. Address for correspondence: Jane H. Brice, MD, MPH, Department of Emergency Medicine, CB #7594, University of North Carolina– Chapel Hill, Chapel Hill, NC 27599-7594.
REFERENCES 1. Govindarajan A, Schull M. Effect of socioeconomic status on out-of-hospital transport delays of patients with chest pain. Ann Emerg Med. 2003;41:481-490. 2. Herlitz J, Blohm M, Hartford M, et al. Delay time in suspected acute myocardial infarction and the importance of its modification. Clin Cardiol. 1989;12:370-374. 3. Gurwitz JH, McLaughlin TJ, Willison DJ, et al. Delayed hospital presentation in patients who have had acute myocardial infarction. Ann Intern Med. 1997;126:593-599. 4. Schmidt SB, Borsch MA. The prehospital phase of acute myocardial infarction in the era of thrombolysis. Am J Cardiol. 1990;65:1411-1415.
APRIL 2003
41:4
ANNALS OF EMERGENCY MEDICINE
4 9 3
Jane H. Brice, MD, MPH Donald M. Yealy, MD From the Department of Emergency Medicine, University of North Carolina–Chapel Hill, Chapel Hill, NC (Brice); and the Department of Emergency Medicine, University of Pittsburgh, Pittsburgh, PA (Yealy).
Copyright © 2003 by the American College of Emergency Physicians. 0196-0644/2003/$30.00 + 0 doi:10.1067/mem.2003.115
APRIL 2003
41:4
ANNALS OF EMERGENCY MEDICINE
Socioeconomic Status and Out-ofHospital Delay See related article, p. 481. [Ann Emerg Med. 2003;41:491-493.]
In this issue of Annals, Govindarajan and Schull1 report the results of a study examining the effect of socioeconomic status on out-of-hospital transport delays for patients with chest pain. They approach this question by dividing their emergency medical services (EMS) response area geographically into neighborhoods based on the Forward Sortation Area designation, assigning each neighborhood a socioeconomic status based on aggregate income data from the 1996 census. Neighborhoods were then grouped together into 5 income strata. The results suggest that out-of-hospital intervals for patients with chest pain were longer for low socioeconomic status neighborhoods compared with higher socioeconomic status neighborhoods. The social implications of these findings merit attention and review. First, the results must be seen in the context of the entire out-of-hospital delay interval. Second, several factors (ie, societal, system, paramedic, patient) associated with these findings must be evaluated. The authors suggest in their discussion that, compared with the 4 lower socioeconomic status strata, the highest socioeconomic status neighborhoods had a shorter system response interval (by 34 seconds) and shorter transport intervals (by 3 seconds). The authors state: “Out-of-hospital delays for patients with chest pain from lower socioeconomic status neighborhoods might be of particular concern because low socioeco-
4 9 1
SOCIOECONOMIC STATUS AND OUT-OF-HOSPITAL DELAY Brice & Yealy
nomic status has been associated with an increased incidence of AMI and higher mortality, even in the outof-hospital setting, and because out-of-hospital systems tend to serve lower socioeconomic status groups disproportionately.”1 When examining Table 1 of the article, it appears that the delays occur in the middle socioeconomic status neighborhoods, not in the lowest socioeconomic status neighborhoods. The total out-ofhospital interval for the highest socioeconomic status neighborhoods was identical to that of the lowest socioeconomic status neighborhoods. Nevertheless, it does appear that the highest socioeconomic status neighborhoods, which account for only 11% of the total system volume, have shorter out-of-hospital intervals than neighborhoods with lower income levels. Therefore, the paramedics treated the rich and the poor the same but had longer intervals with the middle class. What does this mean clinically? It is clear that the longest delay interval for patients with chest pain is the interval between symptom onset and the decision to seek care, whether that be driving to the hospital or calling 911. Most patients with chest pain wait at least an hour before seeking care,2,3 and 25% wait more than 6 hours.4-6 In the face of such delay, what difference can 34 or 132 seconds make? Given this, it is clear that the “biggest bang for the buck,” at least in patients with chest pain or stroke symptoms, lies in encouraging seeking care early rather than trying to shave a few minutes off of EMS transport intervals. The importance of societal factors in the results of Govindarajan and Schull1 are unclear. The delays discovered in the data were in the response interval and the transport interval. Both of these intervals are governed by factors beyond the control of the individual paramedic. Traffic patterns in the lower socioeconomic status neighborhoods may not allow for the rapid progress or egress of ambulances. Perhaps the streets are narrower or more often lined with cars. Perhaps the neighborhoods are not easily linked with major transportation arteries. And perhaps the streets in the neighborhood are interrupted or poorly marked, making it difficult to locate the address. Lower socioeconomic status neighborhoods also contain dwellings housing multiple fam-
4 9 2
ilies beneath one roof, making it time-consuming to find the right door on which to knock. Finally, we generally do not build our hospitals in the poorest neighborhoods. Hospitals are frequently for-profit entities. They are built among the clientele they wish to attract (ie, paying customers). Thus, a longer interval to transport a patient from the site of care to the hospital may be the result of complex forces outside of an EMS unit or system’s control. System issues are also important to consider. Where were the ambulances placed? Were the ambulances in fixed locations or engaged in flexible deployment? Were they attached to other public service outposts to maximize utility for all services but perhaps to the individual detriment of the EMS needs? This simple design factor could influence the observed data yet be unrelated, or tangentially related, to the socioeconomic issues. The authors also found that sending an ambulance staffed with advanced care paramedics to the scene increased out-of-hospital delay. It appears that advanced care paramedics are a scarce resource as evidenced by the number of calls to which a primary care paramedic ambulance was sent instead. Discerning the reason why advanced care paramedic ambulances were on the scene for longer than other crew configurations warrants further investigation, but again this is not related to the stated objective—investigating the role of socioeconomic status and out-of-hospital care. It seems unlikely that individual paramedics would be able to detect or infer small differences in income. The income strata as defined by the authors encompass very small increments. For example, the median income for the lowest stratum is $15,295, and the median for the next highest stratum is $17,509. Looking at a patient or a neighborhood and being able to tell that one makes $2,214 more than the other seems improbable. The scheme devised by the authors to lump neighborhoods together takes data in aggregate and says nothing about the income level of the individual patient. Additionally, paramedics are usually not the highest-paid civil servants. In all probability, the middle socioeconomic status neighborhoods with the longest intervals
ANNALS OF EMERGENCY MEDICINE
41:4
APRIL 2003
SOCIOECONOMIC STATUS AND OUT-OF-HOSPITAL DELAY Brice & Yealy
are probably the very neighborhoods in which the paramedics live. Finally, patient factors may have influenced the results found by the authors. They discovered longer out-ofhospital intervals for the elderly (45.3 seconds for each 10 years of age) and for female patients (205.0 seconds). The majority of the delay occurred in the on-scene interval. These patients are generally more complicated, with either lengthy medical histories and extensive medication lists or vague and atypical symptoms, making it more time-consuming to ferret out the underlying problem and decide on a treatment strategy. There will always be patients who are more complicated than others and who are therefore more time-consuming. In summary, Govindarajan and Schull1 have presented a nicely executed study that raises more questions that need to be addressed. Do all out-of-hospital intervals need to be shortened? If so, how can we shorten those in need of this? How do societal factors influence the delivery of out-of-hospital care in a timely manner? What system issues affect out-of-hospital care intervals, and how can we reduce this delay to make out-of-hospital care more efficient? What tools can paramedics develop or be provided with to aid them in the delivery of care to more complicated and timeconsuming patients? Answering these questions will require sophisticated social science methodology and collaboration with professionals of disciplines such as city planners, sociologists, medical geographers, and gerontologists.
5. Yarzebski J, Goldberg RJ, Gore JM, et al. Temporal trends and factors associated with extent of delay to hospital arrival in patients with acute myocardial infarction: the Worcester Heart Attack Study. Am Heart J. 1994;128:255-263. 6. Sheifer SE, Rathore SS, Gersh BJ, et al. Time to presentation with acute myocardial infarction in the elderly. Circulation. 2000;102:1651-1656.
Reprints not available from the authors. Address for correspondence: Jane H. Brice, MD, MPH, Department of Emergency Medicine, CB #7594, University of North Carolina– Chapel Hill, Chapel Hill, NC 27599-7594.
REFERENCES 1. Govindarajan A, Schull M. Effect of socioeconomic status on out-of-hospital transport delays of patients with chest pain. Ann Emerg Med. 2003;41:481-490. 2. Herlitz J, Blohm M, Hartford M, et al. Delay time in suspected acute myocardial infarction and the importance of its modification. Clin Cardiol. 1989;12:370-374. 3. Gurwitz JH, McLaughlin TJ, Willison DJ, et al. Delayed hospital presentation in patients who have had acute myocardial infarction. Ann Intern Med. 1997;126:593-599. 4. Schmidt SB, Borsch MA. The prehospital phase of acute myocardial infarction in the era of thrombolysis. Am J Cardiol. 1990;65:1411-1415.
APRIL 2003
41:4
ANNALS OF EMERGENCY MEDICINE
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