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Emergency medical services use by stroke patients: a population-based study
American Journal of Emergency Medicine (2009) 27, 141–145
www.elsevier.com/locate/ajem
Original Contribution
Emergency medical services use by stroke patients: a population-based study☆ Opeolu Adeoye MD a,⁎, Christopher Lindsell PhD a , Joseph Broderick MD b , Kathy Alwell RN b , Edward Jauch MD a , Charles J. Moomaw PhD b , Matthew L. Flaherty MD b , Arthur Pancioli MD a , Brett Kissela MD b , Dawn Kleindorfer MD b a
Department of Emergency Medicine, University of Cincinnati, Cincinnati, OH, USA Department of Neurology, University of Cincinnati, Cincinnati, OH, USA
b
Received 7 December 2007; revised 4 February 2008; accepted 5 February 2008
Abstract Objectives: Emergency medical services (EMS) use by stroke patients varies from 38% to 65%. In an epidemiological study, we determined the proportion of stroke patients who used EMS, hypothesizing that demographics, stroke severity, stroke type, and location at stroke onset would be associated with EMS use. Methods: Stroke and transient ischemic attack patients were identified in a population of 1.3 million in the Cincinnati area in 1999. Patient charts and EMS records were abstracted by research nurses and reviewed by study physicians. The proportion of EMS users was computed. Logistic regression was used to test for associations with EMS use. Results: Of 3949 strokes, we excluded strokes/transient ischemic attacks that occurred in the hospital (n = 283), out of town (n = 10), during EMS transport (n = 2), and at unknown locations (n = 73). Patients with unknown EMS use (n = 301); those with missing estimated stroke severity (n = 174), prestroke disability (n = 78), race (n = 3), and stroke type (n = 3); and those younger than 18 years (n = 14) were also excluded. The remaining 3008 patients had a mean age of 74 years, 17% were black, and 45% were men. Emergency medical services was used by 1532 (50.9%) patients. Age, prestroke disability, stroke severity, hemorrhagic stroke, and stroke at work were associated with EMS use. Race, sex, and prior stroke were not associated with EMS use. Conclusion: Half of stroke patients used EMS in our population-based study. Older patients; those with greater prestroke disability, more severe stroke, and hemorrhagic stroke; and those having stroke at work were more likely to use EMS. © 2009 Elsevier Inc. All rights reserved.
1. Introduction Acute ischemic stroke patients treated with recombinant tissue plasminogen activator (rt-PA) are 30% more likely to ☆
Supported in part by NINDS 5R01NS030678-13. ⁎ Corresponding author. Tel.: +1 513 558 3117; fax: +1 513 558 5791. E-mail address: [email protected] (O. Adeoye).
0735-6757/$ – see front matter © 2009 Elsevier Inc. All rights reserved. doi:10.1016/j.ajem.2008.02.004
have minimal or no disability 3 months poststroke compared with those treated with placebo [1]. Unfortunately, more than 70% of ischemic stroke patients present outside the 3-hour window of rt-PA eligibility, and only 1% to 5% of all ischemic stroke patients receive rt-PA [2-7]. Prehospital delays by stroke patients in seeking treatment is a major hindrance to delivering rt-PA therapy to stroke patients [2-13].
142 Once a stroke is suspected by the lay public, the use of emergency medical services (EMS) decreases prehospital delays and increases the likelihood of therapy with rt-PA [7-13]. Use of EMS also decreases time to being seen by an emergency physician, time to computed tomography, and time to being seen by a neurologist [5-9]. It has been hypothetically estimated that if all stroke patients had a known onset time and called 911 immediately, rt-PA treatment would increase from 4.3% to 28.6% [7]. Estimates of EMS use by stroke patients vary from 38% to 65%, based mostly on clinical trials [8-12]. Because clinical trials have significant referral biases and may not represent the experience of the entire population, we sought to determine the proportion of stroke patients who used EMS within our large population of 1.3 million to identify factors associated with EMS use that could be potentially amenable to guiding educational efforts. We hypothesized that demographics, stroke severity, stroke type, and location at stroke onset would affect EMS use.
2. Methods 2.1. Greater Cincinnati/Northern Kentucky Stroke Study The Greater Cincinnati/Northern Kentucky Stroke Study (GCNKSS) is a population-based epidemiological study of stroke in blacks and whites, specifically designed to measure temporal trends in incidence and racial differences in incidence of stroke and stroke risk factor profiles. The GCNKSS study population is defined as the 1.3 million residents of the Greater Cincinnati/Northern Kentucky region, which includes 2 southern Ohio counties and 3 contiguous Northern Kentucky counties that border the Ohio River. Included in this area are 18 hospitals. Although residents of nearby counties seek care at the 18 hospitals, only residents of the 5 study area counties were included as cases. The study period was calendar year 1999. The methods of case ascertainment and data collection have been previously reported [14]. Briefly, study nurses retrospectively reviewed and abstracted the medical records of all inpatients with primary or secondary stroke-related International Classification of Diseases Ninth Version (ICD-9) discharge diagnoses (430-436) from the 18 acute care hospitals in the study region. In addition, research nurses prospectively reviewed emergency department (ED) and hospital admission logs for potentially missed cases. The study nurses also reviewed all autopsy cases where stroke was listed as the primary or secondary cause of death. Patients were identified as being from the study area based on their zip code. Once cases of stroke or transient ischemic attack (TIA) were identified, a study nurse abstracted the medical record using standardized case report forms. Abstracted data
O. Adeoye et al. included stroke symptoms, point of first health care provider contact (911/EMS, ED, primary doctor, etc), ED physical examination findings and complete vital signs, past medical and surgical history, medications before the stroke, social history/habits, diagnostic tests performed and results, treatments, and short-term outcomes. The study nurse abstracted all information and then made a determination as to whether a stroke had likely occurred. Study physicians (stroke neurologists and emergency physicians with stroke expertise) reviewed every abstract and decided if a stroke or TIA had occurred. The physicians assigned stroke location, subtype, and mechanism to each verified case based on all available information, using definitions previously reported [14,15]. For this analysis, (1) patients must have resided at home, that is, not at nursing, retirement, or group homes; (2) the stroke must have occurred outside the hospital (ie, strokes occurring during a hospital admission for another diagnosis were excluded); (3) patients must have presented to a local ED; and (4) the stroke must have occurred within the 5-county Greater Cincinnati/Northern Kentucky region. Use of EMS was defined as calling 911, not just using an ambulance for transportation to the hospital. All localities within the 5-county region use the 911 system. All 911 calls were confirmed by review of dispatch and EMS records. We excluded patients who were younger than 18 years, had unknown EMS use, and had missing data for stroke severity, prestroke disability, race, or stroke type. Stroke severity was determined using a retrospectively derived National Institutes of Health Stroke Scale (NIHSS) score. Institutional review board approval was obtained at all participating hospitals. Data were managed with SAS version 8.2 (SAS Institute), and descriptive and comparative analyses were performed using SPSS v14.0 (SPSS Inc, Chicago, IL). The theoretical model that examined whether age, race, sex, stroke type, where the stroke occurred, stroke severity, and prestroke disability would impact EMS was tested using multivariable logistic regression. The significance level and odds ratio (OR) for each predictor were used to evaluate whether the variable belongs in the theoretical model. The HosmerLemeshow goodness-of-fit statistic was used to test whether the theoretical model was a good fit to the data.
3. Results There were 3949 confirmed cases of stroke or TIA in the 5-county Greater Cincinnati/Northern Kentucky region during 1999. Of these, we excluded 283 in-hospital events, 10 events that occurred when the resident was out of town, 2 events wherein the patient developed stroke symptoms while transported by EMS for other reasons, and 73 strokes that occurred at unknown locations. We further excluded those with unknown EMS use (n = 301); those with missing estimated stroke severity (n = 174), prestroke disability (n = 78), race (n = 3), and stroke type (n = 3); and those younger
Emergency medical services use by stroke patients Table 1 Comparison of included and excluded patients for predicting EMS use
Age (y) Female Male White Black Other Unknown race Estimated NIHSS score ICH Infarct Subarachnoid hemorrhage TIA Unknown stroke type Known prior stroke or TIA Prestroke modified Rankin scale No EMS EMS Unknown EMS
Included (n = 3008)
Excluded (n = 573)
P value
74 1667 1341 2493 497 18 0 6 187 1965 68 788 0 1093
73 (0-97) 337 (58.8) 236 (41.2) 466 (81.3) 102 (17.8) 2 (0.3) 3 (0.5) 4 (0-42) 108 (18.8) 241 (42.1) 24 (4.2) 197 (34.4) 3 (0.5) 205 (35.8)
.082 .134
.798
0 (0-5)
.085
(18-99) (55.4) (44.6) (82.9) (16.5) (0.6) (0.0) (0-42) (6.2) (65.3) (2.3) (26.2) (0.0) (36.3)
0 (0-5) 1476 (49.1) 1532 (50.9) 0 (0.0)
.001
b.001 b.001
96 (16.8) b.001 176 (30.7) 301 (52.5)
Values are shown as median (range) or n (%), as appropriate.
than 18 years (n = 14). To check for exclusion bias, included patients were compared with those excluded from the model (Table 1). Notably, the included patients had slightly more severe strokes (median NIHSS score = 6) compared with the excluded patients (median NIHSS score = 4), and excluded patients had a higher proportion of intracerebral hemorrhage compared with included patients (18.8% vs 6.2%). There were 3008 confirmed cases of stroke or TIA included for the analyses. Emergency medical services was Table 2
Characteristics of patients using and not using EMS
Age Black White Other Female Male Prior stroke or TIA Prestroke mRS Estimated NIHSS score Hemorrhage Infarct TIA Stroke at home Stroke at work Other location
EMS was not used (n = 1476)
EMS was used (n = 1532)
71 (20-98) 1227 (83.1) 240 (16.3) 9 (0.6) 779 (52.8) 697 (47.2) 511 (34.6) 0 (0-5) 4 (0-42) 70 (4.7) 904 (61.2) 502 (34.0) 1352 (91.6) 44 (3.0) 80 (5.4)
77 (18-99) 1266 (82.6) 257 (16.8) 9 (0.6) 888 (58.0) 644 (942.0) 582 (38.0) 1 (0-5) 8 (0-42) 185 (12.1) 1061 (69.3) 286 (18.7) 1382 (90.2) 38 (2.5) 112 (7.4)
Values are shown as median (range) or n (%), as appropriate.
143 Table 3 Multivariable logistic regression model (ORs for use of EMS)
Age per year Black vs white Other vs white Male vs female Prior stroke Prestroke mRS per point NIHSS Hemorrhage vs TIA Infarct vs TIA Work vs home Health care facility vs home Other vs home
OR
95% Confidence interval
P value
1.028 1.018 1.064 1.019 0.977 1.140
1.021-1.035 0.817-1.269 0.382-2.962 0.866-1.198 0.824-1.158 1.083-1.201
b.0001 .8744 .9053 .8231 .7889 b.0001
1.135 3.015 0.926 1.660 1.300
1.116-1.154 2.104-4.321 0.756-1.133 1.021-2.701 0.876-1.928
b.0001 b.0001 .4532 .0411 .1925
1.111
0.602-2.051
.7353
used by 1532 (50.9%) patients. The characteristics of patients who used and did not use EMS are presented in Table 2. Use of EMS varied by type of stroke: 54% of 1965 ischemic stroke patients used EMS, whereas 72% of 255 hemorrhagic stroke patients and 36% of 788 TIA patients used EMS. Our multivariable theoretical model fit well (P = .446; Table 3). Increasing age (OR = 1.03 per year), worsening prestroke disability (OR = 1.14 per point increase in prestroke modified Rankin scale), worsening stroke severity (OR = 1.14 per point increase on the NIHSS), hemorrhagic stroke (OR = 3.015 compared with TIA), and whether the stroke occurred at work vs at home (OR = 1.66) were associated with EMS use. Race, sex, and prior stroke were not associated with EMS use.
4. Discussion The findings of this comprehensive population-based epidemiological study are consistent with those of other reports suggesting that about half of stroke patients use EMS [8-11]. Multiple factors likely play a role in stroke patients' utilization of EMS. We have previously demonstrated poor public knowledge of stroke warning signs and risk factors within our population [16]. Thus, public awareness of the urgency of stroke symptoms likely contributes to EMS use. It has also been reported that patients are more likely to use EMS if someone other than the patient noted the symptoms [9], as might occur for stroke at work, which we found predictive of EMS use. Several explanations are possible for the predictors of EMS use we identified. The elderly and those with higher prestroke disability may have caregivers available who activated EMS, whereas those with hemorrhages and severe strokes may have been more obviously symptomatic, prompting EMS activation. Hemorrhage
144 independently predicted EMS use even when controlled for severity, and our hypothesis is that this might be a symptomspecific effect (a severe headache may prompt a 911 call more than other symptoms do, such as arm numbness). We plan to conduct an analysis of arrival times by symptom in the future. Although other reports on EMS use in stroke patients have been published, no studies on how to increase EMS use are available. The Delay in Accessing Stroke Healthcare studies (DASH and DASH II) are frequently cited sources of EMS use among stroke patients [8,9]. DASH II was important in clearly demonstrating that EMS use alone decreased not just prehospital time but also response times in the ED. This is an important concept often overlooked in prehospital studies. Within the DASH studies, which were multicenter registries among selected sites, 46% of DASH and 48% of DASH II patients used EMS. Barsan et al [10] reported 47% EMS use in their multicenter study of 1159 stroke patients in an rt-PA treatment trial. Rossnagel et al [11] found that 49% of 558 confirmed stroke patients used EMS in Germany. None of these studies were conducted on a population-wide basis. All 18 hospitals in the Greater Cincinnati region have been served by an aggressive Stroke Team for close to 20 years and significant public education efforts had been initiated in the decade before the study period given the recognition that the public was largely unaware of stroke signs and symptoms [16]. Despite these concerted efforts in our region, only half of stroke patients used EMS. Wein et al [12] published a population-based evaluation of 429 rural confirmed cases of stroke or TIA that found that 38% of patients used EMS. Our higher EMS use rate may be because of study settings (urban vs rural) and/or cultural differences between the different populations being studied (black/white vs Hispanic/white). An estimated 25% of the US population resides in nonurban areas [17]. Most subjects in our study lived close to a hospital and had ready access to EMS via 911. We have previously reported a mean time from 911 call to on-scene arrival of the EMS crew of 6.5 minutes in our study area [13]. Emergency medical services units in sparsely populated areas likely have longer times between calling 911 and on-scene arrival. Patients in rural areas may be less likely to activate EMS if they expect these long delays. As such, our findings may be more applicable to an urban US population. There are conflicting reports in the literature regarding some of our findings. Wein et al [12] found no association between EMS use and sex, age, race, stroke type, or prior stroke. Barsan et al [10] found that older patients, blacks, and those with hemorrhagic strokes were more likely to use EMS, whereas location at onset was not associated with EMS use. Lacy et al [5] reported that older age and white race predicted EMS use. DASH II also found age to be predictive of EMS use [9]. A limitation of our study is that we could not identify who (ie, the patient or a witness) dialed 911 to contact EMS. The identified predictors of EMS use (older age, greater prestroke
O. Adeoye et al. disability, increasing stroke severity, and hemorrhagic stroke subtype) suggest that those patients would actually be less likely to be physically capable of dialing 911. Wein et al [12] found that only 4.3% of stroke patients using EMS called 911 themselves. Activation of EMS was mostly done by family members, paid caregivers, or coworkers. Public education specifically targeting those close to at-risk groups was proposed [12] and is strongly encouraged given our findings. Another limitation of our study is that incomplete EMS and ED records led to the exclusion of 559 patients. We found that excluded patients had a lower NIHSS score and a higher proportion of ICH. The high proportion of hemorrhagic stroke in excluded patients may have resulted in an underestimation of EMS use. On the other hand, excluded patients had less severe strokes as determined by the NIHSS and may have been less likely to use EMS, possibly leading to an overestimation of EMS use. If we included all 559 patients and assumed that none used EMS, estimated EMS use would be 43%. If we included only the 301 patients with unknown EMS use and assumed that none used EMS, we would have found that 46% of patients used EMS. Although the reasons for the findings remain unclear, the fact that too few stroke patients use EMS is demonstrated.
5. Conclusion To our knowledge, this is the largest and most comprehensive study to date that evaluates the frequency of EMS use among patients with confirmed stroke or TIA. Use of EMS to access stroke care increases the likelihood of therapy with rt-PA [7-13] and decreases time to being seen by an emergency physician, time to computed tomography, and time to being seen by a neurologist [5-9]. Our findings that half of all stroke patients used EMS are consistent with those of other published reports [8-11]. Public education specifically targeting those close to at-risk groups will likely have a positive impact on EMS use by stroke patients and increased efforts to emphasize use of 911 for all suspected strokes are needed. Future prospective studies should systematically investigate the causes of lack of EMS use and ways to increase EMS use among stroke patients.
References [1] Tissue plasminogen activator for acute ischemic stroke. The National Institute of Neurological Disorders and Stroke rt-PA Stroke Study Group. N Engl J Med 1995;333:1581-7. [2] Kleindorfer D, Kissela B, Schneider A, et al. Eligibility for recombinant tissue plasminogen activator in acute ischemic stroke: a population-based study. Stroke 2004;35:e27-9. [3] Barber PA, Zhang J, Demchuk AM, et al. Why are stroke patients excluded from TPA therapy? An analysis of patient eligibility. Neurology 2001;56:1015-20. [4] Moser DK, Kimble LP, Alberts MJ, et al. Reducing delay in seeking treatment by patients with acute coronary syndrome and stroke:
Emergency medical services use by stroke patients
[5]
[6]
[7]
[8]
[9]
[10]
a scientific statement from the American Heart Association Council on cardiovascular nursing and stroke council. Circulation 2006;114: 168-82. Lacy CR, Suh DC, Bueno M, et al. Delay in presentation and evaluation for acute stroke. Stroke Time Registry for Outcomes Knowledge and Epidemiology (S.T.R.O.K.E). Stroke 2001;32:63-9. O’Connor RE, McGraw P, Edelsohn L. Thrombolytic therapy for acute ischemic stroke: why the majority of patients remain ineligible for treatment. Ann Emerg Med 1999;33:9-14. California acute stroke pilot registry (CASPR) investigators. Prioritizing interventions to improve rates of thrombolysis for ischemic stroke. Neurology 2005;64:654-9. Rosamond DW, Gorton RA, Hinn AR, et al. Rapid response to stroke systems: the Delay in Accessing Stroke Healthcare (DASH) study. Acad Emerg Med 1998;5:45-51. Schroeder EB, Rosamond DW, Morris DL, et al. Determinants of use of emergency medical services in a population with stroke symptoms: the second Delay in Accessing Stroke Healthcare (DASH II) study. Stroke 2000;31:2591-6. Barsan WG, Brott TG, Broderick JP, et al. Time of hospital presentation in patients with acute stroke. Arch Intern Med 1993;153:2558-61.
145 [11] Rossnagel K, Jungehulsing GJ, Nolte CH, et al. Out-of-hospital delays in patients with acute stroke. Ann Emerg Med 2004;44: 476-83. [12] Wein TH, Staub L, Felberg R, et al. Activation of emergency medical services for acute stroke in a nonurban population. The TLL Temple Foundation Stroke Project. Stroke 2000;31:1925-8. [13] Kleindorfer DO, Lindsell CJ, Broderick JP, et al. Community socioeconomic status and prehospital times in acute stroke and transient ischemic attack. Do poorer patients have longer delays from 911 call to the emergency department? Stroke 2006;37:1508-13. [14] Broderick J, Brott T, Kothari R, et al. The Greater Cincinnati/Northern Kentucky Stroke Study: preliminary first-ever total incidence rates of stroke among blacks. Stroke 1998;29:415-21. [15] Special report from the National Institute of Neurological Disorders and Stroke. Classification of cerebrovascular diseases III. Stroke 1990;21:637-76. [16] Pancioli AM, Broderick J, Kothari R, et al. Public perception of stroke warning signs and knowledge of potential risk factors. JAMA 1998; 279:1288-92. [17] www.census.gov/population/censusdata. United States Bureau of the Census. Urban and Rural Population.
www.elsevier.com/locate/ajem
Original Contribution
Emergency medical services use by stroke patients: a population-based study☆ Opeolu Adeoye MD a,⁎, Christopher Lindsell PhD a , Joseph Broderick MD b , Kathy Alwell RN b , Edward Jauch MD a , Charles J. Moomaw PhD b , Matthew L. Flaherty MD b , Arthur Pancioli MD a , Brett Kissela MD b , Dawn Kleindorfer MD b a
Department of Emergency Medicine, University of Cincinnati, Cincinnati, OH, USA Department of Neurology, University of Cincinnati, Cincinnati, OH, USA
b
Received 7 December 2007; revised 4 February 2008; accepted 5 February 2008
Abstract Objectives: Emergency medical services (EMS) use by stroke patients varies from 38% to 65%. In an epidemiological study, we determined the proportion of stroke patients who used EMS, hypothesizing that demographics, stroke severity, stroke type, and location at stroke onset would be associated with EMS use. Methods: Stroke and transient ischemic attack patients were identified in a population of 1.3 million in the Cincinnati area in 1999. Patient charts and EMS records were abstracted by research nurses and reviewed by study physicians. The proportion of EMS users was computed. Logistic regression was used to test for associations with EMS use. Results: Of 3949 strokes, we excluded strokes/transient ischemic attacks that occurred in the hospital (n = 283), out of town (n = 10), during EMS transport (n = 2), and at unknown locations (n = 73). Patients with unknown EMS use (n = 301); those with missing estimated stroke severity (n = 174), prestroke disability (n = 78), race (n = 3), and stroke type (n = 3); and those younger than 18 years (n = 14) were also excluded. The remaining 3008 patients had a mean age of 74 years, 17% were black, and 45% were men. Emergency medical services was used by 1532 (50.9%) patients. Age, prestroke disability, stroke severity, hemorrhagic stroke, and stroke at work were associated with EMS use. Race, sex, and prior stroke were not associated with EMS use. Conclusion: Half of stroke patients used EMS in our population-based study. Older patients; those with greater prestroke disability, more severe stroke, and hemorrhagic stroke; and those having stroke at work were more likely to use EMS. © 2009 Elsevier Inc. All rights reserved.
1. Introduction Acute ischemic stroke patients treated with recombinant tissue plasminogen activator (rt-PA) are 30% more likely to ☆
Supported in part by NINDS 5R01NS030678-13. ⁎ Corresponding author. Tel.: +1 513 558 3117; fax: +1 513 558 5791. E-mail address: [email protected] (O. Adeoye).
0735-6757/$ – see front matter © 2009 Elsevier Inc. All rights reserved. doi:10.1016/j.ajem.2008.02.004
have minimal or no disability 3 months poststroke compared with those treated with placebo [1]. Unfortunately, more than 70% of ischemic stroke patients present outside the 3-hour window of rt-PA eligibility, and only 1% to 5% of all ischemic stroke patients receive rt-PA [2-7]. Prehospital delays by stroke patients in seeking treatment is a major hindrance to delivering rt-PA therapy to stroke patients [2-13].
142 Once a stroke is suspected by the lay public, the use of emergency medical services (EMS) decreases prehospital delays and increases the likelihood of therapy with rt-PA [7-13]. Use of EMS also decreases time to being seen by an emergency physician, time to computed tomography, and time to being seen by a neurologist [5-9]. It has been hypothetically estimated that if all stroke patients had a known onset time and called 911 immediately, rt-PA treatment would increase from 4.3% to 28.6% [7]. Estimates of EMS use by stroke patients vary from 38% to 65%, based mostly on clinical trials [8-12]. Because clinical trials have significant referral biases and may not represent the experience of the entire population, we sought to determine the proportion of stroke patients who used EMS within our large population of 1.3 million to identify factors associated with EMS use that could be potentially amenable to guiding educational efforts. We hypothesized that demographics, stroke severity, stroke type, and location at stroke onset would affect EMS use.
2. Methods 2.1. Greater Cincinnati/Northern Kentucky Stroke Study The Greater Cincinnati/Northern Kentucky Stroke Study (GCNKSS) is a population-based epidemiological study of stroke in blacks and whites, specifically designed to measure temporal trends in incidence and racial differences in incidence of stroke and stroke risk factor profiles. The GCNKSS study population is defined as the 1.3 million residents of the Greater Cincinnati/Northern Kentucky region, which includes 2 southern Ohio counties and 3 contiguous Northern Kentucky counties that border the Ohio River. Included in this area are 18 hospitals. Although residents of nearby counties seek care at the 18 hospitals, only residents of the 5 study area counties were included as cases. The study period was calendar year 1999. The methods of case ascertainment and data collection have been previously reported [14]. Briefly, study nurses retrospectively reviewed and abstracted the medical records of all inpatients with primary or secondary stroke-related International Classification of Diseases Ninth Version (ICD-9) discharge diagnoses (430-436) from the 18 acute care hospitals in the study region. In addition, research nurses prospectively reviewed emergency department (ED) and hospital admission logs for potentially missed cases. The study nurses also reviewed all autopsy cases where stroke was listed as the primary or secondary cause of death. Patients were identified as being from the study area based on their zip code. Once cases of stroke or transient ischemic attack (TIA) were identified, a study nurse abstracted the medical record using standardized case report forms. Abstracted data
O. Adeoye et al. included stroke symptoms, point of first health care provider contact (911/EMS, ED, primary doctor, etc), ED physical examination findings and complete vital signs, past medical and surgical history, medications before the stroke, social history/habits, diagnostic tests performed and results, treatments, and short-term outcomes. The study nurse abstracted all information and then made a determination as to whether a stroke had likely occurred. Study physicians (stroke neurologists and emergency physicians with stroke expertise) reviewed every abstract and decided if a stroke or TIA had occurred. The physicians assigned stroke location, subtype, and mechanism to each verified case based on all available information, using definitions previously reported [14,15]. For this analysis, (1) patients must have resided at home, that is, not at nursing, retirement, or group homes; (2) the stroke must have occurred outside the hospital (ie, strokes occurring during a hospital admission for another diagnosis were excluded); (3) patients must have presented to a local ED; and (4) the stroke must have occurred within the 5-county Greater Cincinnati/Northern Kentucky region. Use of EMS was defined as calling 911, not just using an ambulance for transportation to the hospital. All localities within the 5-county region use the 911 system. All 911 calls were confirmed by review of dispatch and EMS records. We excluded patients who were younger than 18 years, had unknown EMS use, and had missing data for stroke severity, prestroke disability, race, or stroke type. Stroke severity was determined using a retrospectively derived National Institutes of Health Stroke Scale (NIHSS) score. Institutional review board approval was obtained at all participating hospitals. Data were managed with SAS version 8.2 (SAS Institute), and descriptive and comparative analyses were performed using SPSS v14.0 (SPSS Inc, Chicago, IL). The theoretical model that examined whether age, race, sex, stroke type, where the stroke occurred, stroke severity, and prestroke disability would impact EMS was tested using multivariable logistic regression. The significance level and odds ratio (OR) for each predictor were used to evaluate whether the variable belongs in the theoretical model. The HosmerLemeshow goodness-of-fit statistic was used to test whether the theoretical model was a good fit to the data.
3. Results There were 3949 confirmed cases of stroke or TIA in the 5-county Greater Cincinnati/Northern Kentucky region during 1999. Of these, we excluded 283 in-hospital events, 10 events that occurred when the resident was out of town, 2 events wherein the patient developed stroke symptoms while transported by EMS for other reasons, and 73 strokes that occurred at unknown locations. We further excluded those with unknown EMS use (n = 301); those with missing estimated stroke severity (n = 174), prestroke disability (n = 78), race (n = 3), and stroke type (n = 3); and those younger
Emergency medical services use by stroke patients Table 1 Comparison of included and excluded patients for predicting EMS use
Age (y) Female Male White Black Other Unknown race Estimated NIHSS score ICH Infarct Subarachnoid hemorrhage TIA Unknown stroke type Known prior stroke or TIA Prestroke modified Rankin scale No EMS EMS Unknown EMS
Included (n = 3008)
Excluded (n = 573)
P value
74 1667 1341 2493 497 18 0 6 187 1965 68 788 0 1093
73 (0-97) 337 (58.8) 236 (41.2) 466 (81.3) 102 (17.8) 2 (0.3) 3 (0.5) 4 (0-42) 108 (18.8) 241 (42.1) 24 (4.2) 197 (34.4) 3 (0.5) 205 (35.8)
.082 .134
.798
0 (0-5)
.085
(18-99) (55.4) (44.6) (82.9) (16.5) (0.6) (0.0) (0-42) (6.2) (65.3) (2.3) (26.2) (0.0) (36.3)
0 (0-5) 1476 (49.1) 1532 (50.9) 0 (0.0)
.001
b.001 b.001
96 (16.8) b.001 176 (30.7) 301 (52.5)
Values are shown as median (range) or n (%), as appropriate.
than 18 years (n = 14). To check for exclusion bias, included patients were compared with those excluded from the model (Table 1). Notably, the included patients had slightly more severe strokes (median NIHSS score = 6) compared with the excluded patients (median NIHSS score = 4), and excluded patients had a higher proportion of intracerebral hemorrhage compared with included patients (18.8% vs 6.2%). There were 3008 confirmed cases of stroke or TIA included for the analyses. Emergency medical services was Table 2
Characteristics of patients using and not using EMS
Age Black White Other Female Male Prior stroke or TIA Prestroke mRS Estimated NIHSS score Hemorrhage Infarct TIA Stroke at home Stroke at work Other location
EMS was not used (n = 1476)
EMS was used (n = 1532)
71 (20-98) 1227 (83.1) 240 (16.3) 9 (0.6) 779 (52.8) 697 (47.2) 511 (34.6) 0 (0-5) 4 (0-42) 70 (4.7) 904 (61.2) 502 (34.0) 1352 (91.6) 44 (3.0) 80 (5.4)
77 (18-99) 1266 (82.6) 257 (16.8) 9 (0.6) 888 (58.0) 644 (942.0) 582 (38.0) 1 (0-5) 8 (0-42) 185 (12.1) 1061 (69.3) 286 (18.7) 1382 (90.2) 38 (2.5) 112 (7.4)
Values are shown as median (range) or n (%), as appropriate.
143 Table 3 Multivariable logistic regression model (ORs for use of EMS)
Age per year Black vs white Other vs white Male vs female Prior stroke Prestroke mRS per point NIHSS Hemorrhage vs TIA Infarct vs TIA Work vs home Health care facility vs home Other vs home
OR
95% Confidence interval
P value
1.028 1.018 1.064 1.019 0.977 1.140
1.021-1.035 0.817-1.269 0.382-2.962 0.866-1.198 0.824-1.158 1.083-1.201
b.0001 .8744 .9053 .8231 .7889 b.0001
1.135 3.015 0.926 1.660 1.300
1.116-1.154 2.104-4.321 0.756-1.133 1.021-2.701 0.876-1.928
b.0001 b.0001 .4532 .0411 .1925
1.111
0.602-2.051
.7353
used by 1532 (50.9%) patients. The characteristics of patients who used and did not use EMS are presented in Table 2. Use of EMS varied by type of stroke: 54% of 1965 ischemic stroke patients used EMS, whereas 72% of 255 hemorrhagic stroke patients and 36% of 788 TIA patients used EMS. Our multivariable theoretical model fit well (P = .446; Table 3). Increasing age (OR = 1.03 per year), worsening prestroke disability (OR = 1.14 per point increase in prestroke modified Rankin scale), worsening stroke severity (OR = 1.14 per point increase on the NIHSS), hemorrhagic stroke (OR = 3.015 compared with TIA), and whether the stroke occurred at work vs at home (OR = 1.66) were associated with EMS use. Race, sex, and prior stroke were not associated with EMS use.
4. Discussion The findings of this comprehensive population-based epidemiological study are consistent with those of other reports suggesting that about half of stroke patients use EMS [8-11]. Multiple factors likely play a role in stroke patients' utilization of EMS. We have previously demonstrated poor public knowledge of stroke warning signs and risk factors within our population [16]. Thus, public awareness of the urgency of stroke symptoms likely contributes to EMS use. It has also been reported that patients are more likely to use EMS if someone other than the patient noted the symptoms [9], as might occur for stroke at work, which we found predictive of EMS use. Several explanations are possible for the predictors of EMS use we identified. The elderly and those with higher prestroke disability may have caregivers available who activated EMS, whereas those with hemorrhages and severe strokes may have been more obviously symptomatic, prompting EMS activation. Hemorrhage
144 independently predicted EMS use even when controlled for severity, and our hypothesis is that this might be a symptomspecific effect (a severe headache may prompt a 911 call more than other symptoms do, such as arm numbness). We plan to conduct an analysis of arrival times by symptom in the future. Although other reports on EMS use in stroke patients have been published, no studies on how to increase EMS use are available. The Delay in Accessing Stroke Healthcare studies (DASH and DASH II) are frequently cited sources of EMS use among stroke patients [8,9]. DASH II was important in clearly demonstrating that EMS use alone decreased not just prehospital time but also response times in the ED. This is an important concept often overlooked in prehospital studies. Within the DASH studies, which were multicenter registries among selected sites, 46% of DASH and 48% of DASH II patients used EMS. Barsan et al [10] reported 47% EMS use in their multicenter study of 1159 stroke patients in an rt-PA treatment trial. Rossnagel et al [11] found that 49% of 558 confirmed stroke patients used EMS in Germany. None of these studies were conducted on a population-wide basis. All 18 hospitals in the Greater Cincinnati region have been served by an aggressive Stroke Team for close to 20 years and significant public education efforts had been initiated in the decade before the study period given the recognition that the public was largely unaware of stroke signs and symptoms [16]. Despite these concerted efforts in our region, only half of stroke patients used EMS. Wein et al [12] published a population-based evaluation of 429 rural confirmed cases of stroke or TIA that found that 38% of patients used EMS. Our higher EMS use rate may be because of study settings (urban vs rural) and/or cultural differences between the different populations being studied (black/white vs Hispanic/white). An estimated 25% of the US population resides in nonurban areas [17]. Most subjects in our study lived close to a hospital and had ready access to EMS via 911. We have previously reported a mean time from 911 call to on-scene arrival of the EMS crew of 6.5 minutes in our study area [13]. Emergency medical services units in sparsely populated areas likely have longer times between calling 911 and on-scene arrival. Patients in rural areas may be less likely to activate EMS if they expect these long delays. As such, our findings may be more applicable to an urban US population. There are conflicting reports in the literature regarding some of our findings. Wein et al [12] found no association between EMS use and sex, age, race, stroke type, or prior stroke. Barsan et al [10] found that older patients, blacks, and those with hemorrhagic strokes were more likely to use EMS, whereas location at onset was not associated with EMS use. Lacy et al [5] reported that older age and white race predicted EMS use. DASH II also found age to be predictive of EMS use [9]. A limitation of our study is that we could not identify who (ie, the patient or a witness) dialed 911 to contact EMS. The identified predictors of EMS use (older age, greater prestroke
O. Adeoye et al. disability, increasing stroke severity, and hemorrhagic stroke subtype) suggest that those patients would actually be less likely to be physically capable of dialing 911. Wein et al [12] found that only 4.3% of stroke patients using EMS called 911 themselves. Activation of EMS was mostly done by family members, paid caregivers, or coworkers. Public education specifically targeting those close to at-risk groups was proposed [12] and is strongly encouraged given our findings. Another limitation of our study is that incomplete EMS and ED records led to the exclusion of 559 patients. We found that excluded patients had a lower NIHSS score and a higher proportion of ICH. The high proportion of hemorrhagic stroke in excluded patients may have resulted in an underestimation of EMS use. On the other hand, excluded patients had less severe strokes as determined by the NIHSS and may have been less likely to use EMS, possibly leading to an overestimation of EMS use. If we included all 559 patients and assumed that none used EMS, estimated EMS use would be 43%. If we included only the 301 patients with unknown EMS use and assumed that none used EMS, we would have found that 46% of patients used EMS. Although the reasons for the findings remain unclear, the fact that too few stroke patients use EMS is demonstrated.
5. Conclusion To our knowledge, this is the largest and most comprehensive study to date that evaluates the frequency of EMS use among patients with confirmed stroke or TIA. Use of EMS to access stroke care increases the likelihood of therapy with rt-PA [7-13] and decreases time to being seen by an emergency physician, time to computed tomography, and time to being seen by a neurologist [5-9]. Our findings that half of all stroke patients used EMS are consistent with those of other published reports [8-11]. Public education specifically targeting those close to at-risk groups will likely have a positive impact on EMS use by stroke patients and increased efforts to emphasize use of 911 for all suspected strokes are needed. Future prospective studies should systematically investigate the causes of lack of EMS use and ways to increase EMS use among stroke patients.
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