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Emergency department factors associated with survival after sudden cardiac arrest
Resuscitation 84 (2013) 292–297
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Clinical paper
Emergency department factors associated with survival after sudden cardiac arrest夽 Nicholas J. Johnson a,∗ , Rama A. Salhi b , Benjamin S. Abella a,c , Robert W. Neumar a,c , David F. Gaieski a,c , Brendan G. Carr a,b a
Department of Emergency Medicine, Perelman School of Medicine, University of Pennsylvania, United States Department of Epidemiology and Biostatistics, Perelman School of Medicine, University of Pennsylvania, United States c Center for Resuscitation Science, Department of Emergency Medicine, Perelman School of Medicine, University of PennsylvaniaUnited States b
a r t i c l e
i n f o
Article history: Received 11 June 2012 Received in revised form 13 October 2012 Accepted 15 October 2012 Keywords: Cardiac arrest Regionalization Cardiac resuscitation centers
a b s t r a c t Background: Sudden cardiac arrest (SCA) is a leading cause of death in the US. Recent innovations in postarrest care have been demonstrated to increase survival. However, little is known about the impact of emergency department (ED) and hospital characteristics on survival to hospital admission and ultimate outcome. Objective: We sought to describe the incidence of SCA presenting to the ED and to identify ED and hospital characteristics associated with survival to hospital admission. Methods: We identified patients with diagnoses of atraumatic cardiac arrest or ventricular fibrillation (ICD-9 427.5 or 427.41) in the 2007 Nationwide Emergency Department Sample (NEDS), a nationally representative estimate of all ED admissions in the United States. We defined SCA as cardiac arrest in the out-of-hospital or ED settings. We used the NEDS sample design to generate nationally representative estimates of the incidence of SCA that presents to EDs. We performed unadjusted and adjusted analyses to examine the relation between patient, ED, and hospital characteristics and outcome using logistic regression. Our primary outcome was survival to hospital admission. Survival to hospital discharge was a secondary outcome. Data are presented as odds ratios (OR) with 95% confidence intervals (CI). Results: Of the 966 hospitals in the NEDS, 933 (96.6%) reported at least one SCA and were included in the analysis. We identified 38,593 cases of cardiac arrest representing an estimated 174,982 cases nationally. Overall ED SCA survival to hospital admission was 26.2% and survival to discharge was 15.7%. Greater survival to admission was seen in teaching hospitals (OR 1.3 95% CI 1.1–1.5, p = 0.001), hospitals with ≥20,000 annual ED visits (OR 1.3 95% CI 1.1–1.6, p = 0.003), and hospitals with percutaneous coronary intervention capability (OR 1.6 95% CI 1.4–1.8, p < 0.001). Higher SCA volume (>40 annually) was associated with lower survival overall (OR 0.7 95% 0.6–0.9, p = 0.010), but not when transferred patients were excluded from the analysis (OR 0.8 95% CI 0.6–1.1, p = 0.116). Conclusions: An estimated 175,000 cases of SCA present to or occur in US EDs each year. Percutaneous coronary intervention capability, ED volume, and teaching status were associated with higher survival to hospital admission. Emergency departments with higher annual SCA volume had lower survival rates, possibly because they transfer fewer patients. An improved understanding of the contribution of ED care to survival following SCA may be useful in advancing our understanding of how best to organize a system of care to ensure optimal outcomes for patients with SCA. © 2012 Elsevier Ireland Ltd. All rights reserved.
1. Introduction
夽 A Spanish translated version of the summary of this article appears as Appendix in the final online version at http://dx.doi.org/10.1016/j.resuscitation.2012.10.013. ∗ Corresponding author at: Department of Emergency Medicine, University of Pennsylvania, 3400 Spruce Street, Philadelphia, PA 19104, United States. Tel.: +1 2156626698. E-mail addresses: [email protected], [email protected] (N.J. Johnson). 0300-9572/$ – see front matter © 2012 Elsevier Ireland Ltd. All rights reserved. http://dx.doi.org/10.1016/j.resuscitation.2012.10.013
Sudden cardiac arrest (SCA) is a leading cause of death in the United States. Estimates of the annual incidence of out-of-hospital SCA, range from 300,000 to 350,000 each year.1 Outcomes remain poor for out-of-hospital SCA patients, with a median survival to hospital discharge of approximately 7.8% and significant regional variability.2 Advances including early defibrillation, high quality cardiopulmonary resuscitation (CPR), and improvements in the Advanced
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Cardiac Life Support algorithm have led to increased rates of ROSC among patients with treated SCA.3–5 In addition, there has been growing recognition of a post-cardiac arrest syndrome, characterized by a specific constellation of pathologies. A number of interventions during this post-arrest period, including therapeutic hypothermia, hemodynamic optimization, and percutaneous coronary intervention (PCI) have been shown to improve survival.6–11 Despite studies demonstrating their feasibility and benefit, most modalities of post-cardiac arrest care are infrequently implemented.12,13 Largely due to variability in both SCA survival and implementation of post-arrest care, the AHA and other groups have proposed that centers with expertise in caring for SCA patients preferentially receive them in a regionalized system of post-cardiac arrest care.14–16 Although regionalized care has not been proven for cardiac arrest, early efforts are promising, and benefits have been seen for other acute medical conditions.4,17 The concept of regionalization is rooted in the US trauma system, in which a significant survival benefit has been demonstrated for injured patients treated at specialized centers.18–21 Similar systems have been proposed and implemented for other disease states such as acute coronary syndrome and stroke.22–24 Efforts to develop cardiac resuscitation centers (CRCs) and regionalize post-cardiac arrest care are already underway, and a credentialing system was recently developed by the AHA.14–16,25 A comprehensive system of post-arrest care, which includes among many interventions a policy allowing EMS personnel to selectively transport cardiac arrest patients to CRCs, has been implemented in Arizona and associated with improved outcomes.4,17 It remains unclear, however, which hospital factors are associated with improved outcomes for patients with sudden cardiac arrest. A prior study by our group demonstrated significant variability in cardiac arrest survival among hospitals, with improved survival in centers that treat a higher volume of cardiac arrest patients in their intensive care units.26 Others have shown variable association between hospital-level factors and SCA survival.27–29 This study will examine ED and hospital factors associated with survival to admission in SCA. We hypothesized that large, urban, academic hospitals with higher SCA volumes will have better survival to hospital admission than smaller, rural, low SCA volume hospitals.
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an ED disposition of “routine discharge” or “unknown”, and those with a concomitant diagnosis of injury were excluded. Injury was defined using ICD 9-CM codes 800.00–904.99, 925.00–929.99, and 950.00–957.99, excluding late effects (ICD-9 905.00–909.99), superficial injuries (910.00–919.99), contusions (920.00–924.99), effects of foreign body (930.00–939.99), early complications of trauma (958.00–958.99), or other/unspecified injury (959.00–959.99). Only hospitals with at least one non-injury related SCA case were included in our analyses. This study was approved by the institutional review board of the University of Pennsylvania with waiver of informed consent. 2.2. Variables A facility was defined as having a cardiac catheterization lab with PCI capability if >5 PCI procedure codes (ICD-9-CM 36.00–36.06, 36.09, and 00.66) were present over the course of the year. This definition of >5 PCIs performed per year has been used before to define hospitals capable of performing revascularization for patients with acute myocardial infarction.30 We acknowledge that this definition does not guarantee the availability of a PCI lab that is available around the clock to perform emergent PCI. Other hospital characteristics of interest included location [defined by Urban Influence Codes – metropolitan, micropolitan (non-metropolitan regions with >10,000 people), rural, and nonurban residential], region (defined by United States census region), teaching status, trauma center level, ED volume, and cardiac arrest volume. Emergency department volume and cardiac arrest volume were initially grouped into categorical variables, in increments of 10,000 annual ED visits and 20 annual cardiac arrest cases, respectively. ED volume and cardiac arrest volume variables were then further categorized as binary variables (ED volume ≥ 20,000 and CA volume ≥ 40) to derive more parsimonious estimates. Cut-points for the binary variables were determined using survival trends observed in the categorical variables. In the case of cardiac arrest volume, our cut point was consistent with previous literature. Although no prior work has examined cardiac arrest survival trends by ED volume, previous work has also suggested a cardiac arrest volume cut-point of 40–50 cases annually is associated with greater survival.26,27 2.3. Outcomes
2. Methods 2.1. Selection of study subjects Data were obtained from the Nationwide Emergency Department Sample (NEDS). The NEDS is the largest all-payer database in the United States and was developed, maintained, and made available through the Healthcare Cost & Utilization Project (HCUP) of the Agency for Healthcare Research and Quality. The NEDS is constructed annually using records from State Emergency Department Databases and State Inpatient Databases. In 2007, the year used for this study, information from 966 hospitals in 27 states was included. Hospitals are selected using a stratified probability sample based on hospital characteristics and are weighted to allow for the calculation of nationally representative estimates. Sampling strata include region of the country, teaching status, trauma center designation, hospital ownership type (i.e. public, for-profit, or not-for-profit), and location. All patients who presented to a participating ED were included in the NEDS. We defined sudden cardiac arrest (SCA) as cardiac arrest in the out-of-hospital or ED settings. SCA cases were defined as a primary or secondary ED diagnosis of cardiac arrest (ICD 9-CM 427.5) or ventricular fibrillation (ICD 9-CM 427.41). Patients less than 18 years of age, those with
We describe the magnitude and distribution of SCA cases presenting to EDs in the US. The primary outcome in our analyses examining hospital factors was survival to hospital admission. As a secondary outcome, we examined survival to hospital discharge. 2.4. Data analyses We used the hospital and individual-level weights provided by HCUP to account for the sampling design of the NEDS and to generate nationally representative estimates. The data were analyzed using statistical packages (SAS version 9.3, SAS Institute, Inc., Cary, NC and Stata version 12.0, Stata Corp, College Station, TX). Analyses were performed using generalized estimating equations with robust Huber–White confidence intervals to account for clustering by center. Data are presented as odds ratios (OR) with 95% confidence intervals (CI). We conducted two post hoc sensitivity analyses. Because of potential of differential rates of transfers between hospitals treating >40 and ≤40 SCA cases per year, we performed a sensitivity analysis excluding transferred patients. Because there is no consistent definition of a “PCI capable hospital” in the literature, we performed a second sensitivity analysis to examine whether
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substituting different PCI cut-points (greater than 15, 25, 50, and 100 PCIs per year) would affect survival in our multivariate model.
Table 2 Descriptive statistics (data presented as weighted percentages unless otherwise noted).
3. Results 3.1. Characteristics of hospitals and study subjects Hospital and patient characteristics are displayed in Tables 1 and 2. Of the 966 hospitals included in the NEDS, 933 (96.6%) documented at least one case of cardiac arrest in 2007, representing 4637 hospitals nationally. Of these hospitals, 74.2% admitted at least one cardiac arrest patient from the ED. In total, 38,593 cases of cardiac arrest were identified, representing an estimated 174,982 cases of SCA that present to or occur in EDs nationally. A total of 8008 patients were excluded (1786 [age < 18], 4296 [discharged from the ED or unknown], and 1926 [injury]). Hospitals that did not report at least one case of cardiac arrest case were most often non-metropolitan, located in the Midwest, and reported low (≤10,000) annual ED visits (Table 1). Of the patients included in this analysis, 26.2% survived to hospital admission. Of those who initially survived to be admitted, 40.2% of patients died after admission, resulting in an overall survival to hospital discharge of 15.7%. Patients surviving to be admitted were younger, more likely to be female, and less likely to be admitted on a weekend when compared to patients who died in the ED, though
Table 1 Hospital characteristics (data presented as weighted percentages unless otherwise noted).
Rurality Metropolitan Micropolitan/rural Region Northeast Midwest South West Hospital control Government, Nonfederal, Public Private Collapsed (Government or Private) Teaching status Metropolitan Non-teaching Metropolitan Teaching Non-Metropolitan Trauma center level Non-Trauma Trauma Center (Level 1, 2, 3) ED volume <10,000 10,000–20,000 20,000–30,000 30,000–40,000 40,000–50,000 50,000–60,000 60,000–70,000 70,000–80,000 >80,000 Cardiac arrest volume ≤20 21–40 41–60 61–80 81–100 >100 PCI available
Included hospitals (n = 933)
Excluded hospitals (n = 33)
58.9 41.1
35.9 64.1
13.4 28.8 39.7 18.2
5.5 45.8 16.7 32.0
17.1 42.8 40.1
44.2 23.0 32.8
42.5 16.5 41.1
11.5 24.3 64.1
83.1 16.9
86.7 13.3
25.6 20.7 16.0 14.1 8.4 6.7 3.0 1.3 4.1
69.9 5.8 5.5 5.1 2.8 8.1 2.9 0.0 0.0 N/A
35.9 22.7 16.0 10.4 6.1 8.9 30.2
N/A
Age (mean, SD) Female Weekend admission Rurality Metropolitan Micropolitan/rural Region Northeast Midwest South West Hospital control Government, Nonfederal, Public Private Collapsed (Government or Private) Teaching status Metropolitan Non-teaching Metropolitan Teaching Non-Metropolitan Trauma center level Non-Trauma Trauma Center (Level 1, 2, 3) ED volume <10000 10000–20000 20000–30000 30000–40000 40000–50000 50000–60000 60000–70000 70000–80000 >80000 Cardiac arrest volume ≤20 21–40 41–60 61–80 81–100 >100 PCI capability Capable Not capable
Survived to admission
Died preadmission
Overall
65.1 (15.7) 40.3 28.4
66.0 (17.3) 38.8 29.7
65.7 (16.9) 39.2 29.4
82.6 17.4
80.6 19.4
81.1 18.9
15.5 27.4 37.8 19.4
19.1 22.2 40.3 18.5
18.1 23.5 39.6 18.7
7.2 30.9 61.9
7.8 34.5 57.7
7.6 33.6 58.8
45.0 37.6 17.4
49.5 31.1 19.4
48.4 32.7 18.9
64.1 35.9
70.5 29.5
68.8 31.2
5.0 10.4 15.0 17.5 13.9 13.4 6.9 3.5 14.6
5.7 11.6 15.3 19.5 12.0 12.8 7.3 2.5 13.3
5.5 11.3 15.2 19.0 12.5 13.0 7.2 2.7 13.6
8.2 16.5 18.2 16.9 11.8 28.5
8.2 15.1 18.5 15.5 13.3 29.4
8.2 15.5 18.5 15.8 12.9 29.2
63.1 37.9
53.1 46.9
55.7 44.3
these differences were small and unlikely to be clinically significant (Table 2). Additionally, patients who survived to be admitted were more likely to be seen at hospitals with an annual ED volume ≥20,000, in metropolitan areas, and with PCI capabilities. Among hospitals with 40 or fewer SCA cases annually, 13.1% of patients were transferred, while hospitals with greater 40 SCA cases transferred only 2.7% of cases annually. 3.2. Individual characteristics Among patient characteristics, only female gender was associated with greater survival to hospital admission in adjusted multivariate analysis (OR 1.1 95% CI 1.0–1.1, p = 0.002 [Table 3]). Age greater than 55 years was not associated with worse outcome. 3.3. Regional characteristics Greater survival was seen in hospitals in the Midwest (OR 1.4, 95% CI 1.2–1.7, p < 0.001) and West (OR 1.3, 95% CI 1.1–1.5, p = 0.005) regions. Survival at rural or micropolitan (non-metropolitan area with at least 10,000 people or more) hospitals did not differ significantly when compared with metropolitan hospitals.
N.J. Johnson et al. / Resuscitation 84 (2013) 292–297 Table 3 Adjusted association between hospital characteristics and ED survival.
Individual characteristics Age ≤55 >55 Female Hospital characteristics Region Northeast Midwest South West Rurality Metropolitan Micropolitan/Rural Teaching status Metropolitan Non-teaching Metropolitan Teaching ED volume <10,000 10,000–20,000 20,000–30,000 30,000–40,000 40,000–50,000 50,000–60,000 60,000–70,000 70,000–80,000 >80,000 Cardiac arrest volume ≤20 21–40 41–60 61–80 81–100 >100 PCI capability Not capable Capable
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4. Discussion
OR (95% CI)
p-Value
Ref 1.0 (0.9–1.0) 1.1 (1.0–1.1)
– 0.683 0.002
Ref 1.4 (1.2–1.7) 1.2 (1.0–1.4) 1.3 (1.1–1.5)
– <0.001 0.057 0.005
Ref 1.0 (0.9–1.1)
– 0.980
Ref 1.3 (1.1–1.5)
– 0.001
Ref 1.2 (1.0–1.5) 1.5 (1.1–2.0) 1.5 (1.1–2.0) 1.9 (1.4–2.7) 1.7 (1.3–2.4) 1.5 (1.0–2.2) 2.2 (1.3–3.6) 2.1 (1.4–3.1)
– 0.099 0.004 0.013 <0.001 0.001 0.030 0.003 <0.001
Ref 0.8 (0.7–1.0) 0.7 (0.5–0.9) 0.6 (0.4–0.8) 0.5 (0.3–0.6) 0.4 (0.3–0.5)
– 0.062 0.001 <0.001 <0.001 <0.001
Ref 1.6 (1.4–1.8)
– <0.001
3.4. Hospital characteristics Greater survival to admission was seen in hospitals with teaching status (OR 1.3 95% CI 1.1–1.5, p = 0.001), and PCI capability (OR 1.6 95% CI 1.4–1.8, p < 0.001, [Table 3]). Annual ED visits ≥20,000 (OR 1.3 95% CI 1.1–1.6, p = 0.003) was also associated with higher survival. Higher SCA volume (defined as >40 cardiac arrests annually) was associated with lower survival (OR 0.7 95% 0.6–0.9, p = 0.010). 3.5. Sensitivity analyses Because of potential of differential rates of transfers between hospitals treating >40 and ≤40 SCA cases per year, we performed a post hoc sensitivity analysis excluding transferred patients. These patients were transferred out of EDs to inpatient settings at another hospital. These patients were counted as “survivors” by the transferring ED. A small subset of these patients may have been transferred to another ED, where they may have been counted as a survivor or a death for the receiving ED. After excluding patients who were transferred, the relationship between ED SCA cardiac arrest volume and survival was no longer significant (OR 0.8 95% CI 0.6–1.1, p = 0.116). We performed a second sensitivity analysis to examine whether different PCI cut-points (greater than 15, 25, 50, and 100 PCIs per year) would affect our results. We found no significant difference in the odds of survival when these cut-points were substituted for greater than 5 PCIs per year in our multivariate model (data not shown).
In this study, we sought to describe the incidence of SCA presenting to EDs in the US and to identify ED factors associated with higher survival to hospital admission. We found that a number of factors including ED volume, teaching status, and PCI capability were associated with higher survival to hospital admission among patients with SCA. We previously demonstrated significant variability for cardiac arrest patients who survived to be admitted to the hospital, and in this analysis we sought to determine whether ED factors contributed to differential survival to hospital admission.26 A number of studies have attempted to elucidate hospital factors associated with cardiac arrest mortality with widely variable results. A retrospective study in a single county by Liu et al. found that only nurse-to-bed ratio was significantly associated with in-hospital cardiac arrest mortality.29 A large, multicenter, multinational prospective study found no independent associations between OHCA survival to discharge and hospital characteristics.27 Previous studies have also demonstrated a variable relationship between cardiac arrest volume and survival. A recent study demonstrated improved outcomes in Korea among patients with OHCA transported to higher volume centers.31 An analysis of a prehospital registry in Melbourne, Australia found no association between OHCA volume and outcome.32 A recent analysis of the Cardiac Arrest Registry to Enhance Survival (CARES) did not find improved outcomes at higher volume OHCA centers.33 In our previous work we identified a strong association between hospital survival and treatment in an intensive care unit treating many patients with cardiac arrest.28 The association between cardiac arrest volume and survival to admission in the current analysis was less straightforward. We found that higher SCA volumes were associated with lower survival to hospital admission. This may reflect the effect of transfers as more patients were transferred out of lower SCA volume centers (counted as “survivors”) who may have gone on to die in transit or at higher SCA volume centers. In fact, our sensitivity analysis excluding transfers demonstrated that the association between ED SCA volume and lower survival disappeared after transferred patients were excluded. It is also possible that high volume EDs, which tend to be located in more urban locations, receive more patients with CPR in progress who never achieve ROSC. It has also been previously demonstrated that ED crowding is associated with poor outcomes for a variety of time-sensitive emergency conditions.34,35 Perhaps higher volume EDs experience more crowding which impacts care for SCA patients or results in premature termination of resuscitation. It may be that, given the complexity of cardiac arrest care, factors such as use of therapeutic hypothermia and goal-directed resuscitation, may exert greater influence on survival than SCA volume. These modalities of post-arrest care are variably implemented, and it is unclear whether hospitals with higher SCA volume utilize them more consistently.12 Others have contended that individual provider factors and experience might be more important predictors of patient outcome than facility volume.33 Prior work in the surgical literature demonstrated that individual surgeons with low procedural volume had higher rates of mortality even when their facility volumes were high.36 Perhaps in our study, especially because many of the high volume hospitals are likely teaching facilities, provider experience exerts a greater effect than hospital volume. The volume–outcome relationship, established in the surgical literature and proven for a variety of medical conditions, has become a major component the argument in favor of regionalized care.26,28,37–39 Hospitals that perform larger numbers of certain surgical procedures, such as coronary artery bypass and have been
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found to have better outcomes than lower volume centers.39,40 Many, including the American Heart Association, have advocated for the development of regional systems of care for SCA built around CRCs.14–16 Efforts to regionalize cardiac arrest care are underway, and a credentialing system for CRCs was recently released by the AHA.41–44 Our data, showing worse outcomes at high volume centers, suggest that volume alone is an inadequate criterion by which to designate centers that should preferentially care for patients with sudden cardiac arrest. Future efforts should focus on better understanding the relative importance of the many components of a system of care for cardiac arrest. Since our data comes from the NEDS, an ED sample, it is likely that some of the patients with ICD codes for cardiac arrest or ventricular fibrillation that most patients had their events in the outof-hospital setting, but some likely suffered cardiac arrest in the ED. Among inpatients who have suffered cardiac arrest, almost 11% of patients have their original event in the ED.45 Patients with cardiac arrest in the ED likely have higher survival than those who suffer out-of-hospital cardiac arrest (OHCA), which may explain why our study’s overall survival of 15.7% is higher than survival rates seen in OHCA studies.2,46 It is also likely that the overall survival in our study is higher because we did not include patients who are pronounced dead by paramedics and are never transported to the ED. Although a nationally representative sample of patients with SCA treated in EDs, because of the inclusion of ED arrests and the exclusion of patients not transported to the hospital after out of hospital cardiac arrest, our estimates likely do not accurately estimate the number of out-of-hospital cardiac arrests in the US annually. Our analysis is subject to a number of limitations. This is a retrospective study of administrative data, and thus is subject to the limitations of all retrospective studies. Because of limitations in our dataset, we were unable to determine if a patient was transferred from one ED to another ED. A live, post-arrest patient may have been transferred from one ED (where he was counted as a survivor) to another ED where he died, and similarly some survivors may have been counted twice. Because the NEDS is a large national sample and the numbers of ED-to-ED cardiac arrest transfers are likely low, we believe this was probably a rare event but a limitation nonetheless. Selection of patients for our study relied on ICD coding. Variability in coding practices among individuals and institutions may have influenced our results. Finally, since this is a large nationwide sample, there may be significant heterogeneity in the care provided both in the field and at receiving hospitals. We cannot comment on which aspects of patient care most affected survival. 5. Conclusion Nearly 175,000 cases of SCA present to or occur in EDs in the US each year. Percutaneous coronary intervention capability, ED volume, and teaching status were associated with higher survival to hospital admission. Emergency departments with higher annual SCA volume had lower survival rates, possibly because they transfer fewer patients. An improved understanding of the contribution of ED care to survival following SCA may be useful in advancing our understanding of how best to organize a system of care to ensure optimal outcomes for patients with SCA. Conflict of interest statement Nicholas Johnson and Rama Salhi have no disclosures. Benjamin Abella receives research funding from the National Institutes of Health, Philips, MedTronic Foundation, and the Doris Duke Foundation. He receives speaking honoraria from Medivance and provides advisory for Heartsine Corporation. Robert Neumar has no disclosures. David Gaieski receives research support and consulting fees from Stryker. Brendan Carr receives research funding from
Centers for Disease Control and Prevention, National Institutes of Health, Agency for Healthcare Research and Quality, and the American Heart Association.
Appendix A. Supplementary data Supplementary data associated with this article can be found, in the online version, at http://dx.doi.org/10.1016/j.resuscitation. 2012.10.013.
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N.J. Johnson et al. / Resuscitation 84 (2013) 292–297 24. Edwards JM, Carr BG. Improving patient outcomes from acute cardiovascular events through regionalized systems of care. Hosp Pract (Minneap) 2012;38:54–62. 25. American Heart Association Mission Lifeline. Available at: [accessed June 05.06.12]. 26. Carr BG, Kahn JM, Merchant RM, et al. Inter-hospital variability in post-cardiac arrest mortality. Resuscitation 2009;80:30–4. 27. Callaway CW, Schmicker R, Kampmeyer M, et al. Receiving hospital characteristics associated with survival after out-of-hospital cardiac arrest. Resuscitation 2010;81:524–9. 28. Carr BG, Goyal M, Band RA, et al. A national analysis of the relationship between hospital factors and post-cardiac arrest mortality. Intensive Care Med 2009;35:505–11. 29. Liu JM, Yang Q, Pirrallo RG, et al. Hospital variability of out-of-hospital cardiac arrest survival. Prehosp Emerg Care 2008;12:339–46. 30. Iwashyna TJ, Kahn JM, Hayward RA, et al. Interhospital transfers among Medicare beneficiaries admitted for acute myocardial infarction at nonrevascularization hospitals. Circ Cardiovasc Qual Outcomes 2010;3:468–75. 31. Cha WC, Lee SC, Shin SD, et al. Regionalisation of out-of-hospital cardiac arrest care for patients without prehospital return of spontaneous circulation. Resuscitation 2012;83:1338–42. 32. Stub D, Smith K, Bray JE, et al. Hospital characteristics are associated with patient outcomes following out-of-hospital cardiac arrest. Heart 2012;97: 1489–94. 33. Cudnik MT, Sasson C, Rea TD, et al. Increasing hospital volume is not associated with improved survival in out of hospital cardiac arrest of cardiac etiology. Resuscitation 2012;83:862–8. 34. Pines JM, Pollack Jr CV, Diercks DB, et al. The association between emergency department crowding and adverse cardiovascular outcomes in patients with chest pain. Acad Emerg Med 2009;16:617–25.
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35. Chatterjee P, Cucchiara BL, Lazarciuc N, et al. Emergency department crowding and time to care in patients with acute stroke. Stroke 2011;42:1074–80. 36. Birkmeyer JD, Stukel TA, Siewers AE, et al. Surgeon volume and operative mortality in the United States. N Engl J Med 2003;349:2117–27. 37. Luft HS, Bunker JP, Enthoven AC. Should operations be regionalized? The empirical relation between surgical volume and mortality. N Engl J Med 1979;301:1364–9. 38. Thiemann DR, Coresh J, Oetgen WJ, et al. The association between hospital volume and survival after acute myocardial infarction in elderly patients [see comment]. N Engl J Med 1999;340:1640–8. 39. Peterson ED, Coombs LP, DeLong ER, et al. Procedural volume as a marker of quality for CABG surgery. JAMA 2004;291:195–201. 40. Hannan EL, Wu C, Walford G, et al. Volume–outcome relationships for percutaneous coronary interventions in the stent era. Circulation 2005;112: 1171–9. 41. Donnino MW, Rittenberger JC, Gaieski D, et al. The development and implementation of cardiac arrest centers. Resuscitation 2011;82:974–8. 42. Mechem CC, Goodloe JM, Richmond NJ, et al. Resuscitation center designation: recommendations for emergency medical services practices. Prehosp Emerg Care 2010;14:51–61. 43. HeartRescue Project. Available at: [accessed December, 2011]. 44. Association AH. Available at: [accessed 05.06.2012]. 45. Peberdy MA, Ornato JP, Larkin GL, et al. Survival from in-hospital cardiac arrest during nights and weekends. JAMA 2008;299:785–92. 46. McNally B, Robb R, Mehta M, et al. Out-of-hospital cardiac arrest surveillance—Cardiac Arrest Registry to Enhance Survival (CARES), United States, October 1, 2005–December 31, 2010. MMWR Surveill Summ 2011;60:1–19.
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Clinical paper
Emergency department factors associated with survival after sudden cardiac arrest夽 Nicholas J. Johnson a,∗ , Rama A. Salhi b , Benjamin S. Abella a,c , Robert W. Neumar a,c , David F. Gaieski a,c , Brendan G. Carr a,b a
Department of Emergency Medicine, Perelman School of Medicine, University of Pennsylvania, United States Department of Epidemiology and Biostatistics, Perelman School of Medicine, University of Pennsylvania, United States c Center for Resuscitation Science, Department of Emergency Medicine, Perelman School of Medicine, University of PennsylvaniaUnited States b
a r t i c l e
i n f o
Article history: Received 11 June 2012 Received in revised form 13 October 2012 Accepted 15 October 2012 Keywords: Cardiac arrest Regionalization Cardiac resuscitation centers
a b s t r a c t Background: Sudden cardiac arrest (SCA) is a leading cause of death in the US. Recent innovations in postarrest care have been demonstrated to increase survival. However, little is known about the impact of emergency department (ED) and hospital characteristics on survival to hospital admission and ultimate outcome. Objective: We sought to describe the incidence of SCA presenting to the ED and to identify ED and hospital characteristics associated with survival to hospital admission. Methods: We identified patients with diagnoses of atraumatic cardiac arrest or ventricular fibrillation (ICD-9 427.5 or 427.41) in the 2007 Nationwide Emergency Department Sample (NEDS), a nationally representative estimate of all ED admissions in the United States. We defined SCA as cardiac arrest in the out-of-hospital or ED settings. We used the NEDS sample design to generate nationally representative estimates of the incidence of SCA that presents to EDs. We performed unadjusted and adjusted analyses to examine the relation between patient, ED, and hospital characteristics and outcome using logistic regression. Our primary outcome was survival to hospital admission. Survival to hospital discharge was a secondary outcome. Data are presented as odds ratios (OR) with 95% confidence intervals (CI). Results: Of the 966 hospitals in the NEDS, 933 (96.6%) reported at least one SCA and were included in the analysis. We identified 38,593 cases of cardiac arrest representing an estimated 174,982 cases nationally. Overall ED SCA survival to hospital admission was 26.2% and survival to discharge was 15.7%. Greater survival to admission was seen in teaching hospitals (OR 1.3 95% CI 1.1–1.5, p = 0.001), hospitals with ≥20,000 annual ED visits (OR 1.3 95% CI 1.1–1.6, p = 0.003), and hospitals with percutaneous coronary intervention capability (OR 1.6 95% CI 1.4–1.8, p < 0.001). Higher SCA volume (>40 annually) was associated with lower survival overall (OR 0.7 95% 0.6–0.9, p = 0.010), but not when transferred patients were excluded from the analysis (OR 0.8 95% CI 0.6–1.1, p = 0.116). Conclusions: An estimated 175,000 cases of SCA present to or occur in US EDs each year. Percutaneous coronary intervention capability, ED volume, and teaching status were associated with higher survival to hospital admission. Emergency departments with higher annual SCA volume had lower survival rates, possibly because they transfer fewer patients. An improved understanding of the contribution of ED care to survival following SCA may be useful in advancing our understanding of how best to organize a system of care to ensure optimal outcomes for patients with SCA. © 2012 Elsevier Ireland Ltd. All rights reserved.
1. Introduction
夽 A Spanish translated version of the summary of this article appears as Appendix in the final online version at http://dx.doi.org/10.1016/j.resuscitation.2012.10.013. ∗ Corresponding author at: Department of Emergency Medicine, University of Pennsylvania, 3400 Spruce Street, Philadelphia, PA 19104, United States. Tel.: +1 2156626698. E-mail addresses: [email protected], [email protected] (N.J. Johnson). 0300-9572/$ – see front matter © 2012 Elsevier Ireland Ltd. All rights reserved. http://dx.doi.org/10.1016/j.resuscitation.2012.10.013
Sudden cardiac arrest (SCA) is a leading cause of death in the United States. Estimates of the annual incidence of out-of-hospital SCA, range from 300,000 to 350,000 each year.1 Outcomes remain poor for out-of-hospital SCA patients, with a median survival to hospital discharge of approximately 7.8% and significant regional variability.2 Advances including early defibrillation, high quality cardiopulmonary resuscitation (CPR), and improvements in the Advanced
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Cardiac Life Support algorithm have led to increased rates of ROSC among patients with treated SCA.3–5 In addition, there has been growing recognition of a post-cardiac arrest syndrome, characterized by a specific constellation of pathologies. A number of interventions during this post-arrest period, including therapeutic hypothermia, hemodynamic optimization, and percutaneous coronary intervention (PCI) have been shown to improve survival.6–11 Despite studies demonstrating their feasibility and benefit, most modalities of post-cardiac arrest care are infrequently implemented.12,13 Largely due to variability in both SCA survival and implementation of post-arrest care, the AHA and other groups have proposed that centers with expertise in caring for SCA patients preferentially receive them in a regionalized system of post-cardiac arrest care.14–16 Although regionalized care has not been proven for cardiac arrest, early efforts are promising, and benefits have been seen for other acute medical conditions.4,17 The concept of regionalization is rooted in the US trauma system, in which a significant survival benefit has been demonstrated for injured patients treated at specialized centers.18–21 Similar systems have been proposed and implemented for other disease states such as acute coronary syndrome and stroke.22–24 Efforts to develop cardiac resuscitation centers (CRCs) and regionalize post-cardiac arrest care are already underway, and a credentialing system was recently developed by the AHA.14–16,25 A comprehensive system of post-arrest care, which includes among many interventions a policy allowing EMS personnel to selectively transport cardiac arrest patients to CRCs, has been implemented in Arizona and associated with improved outcomes.4,17 It remains unclear, however, which hospital factors are associated with improved outcomes for patients with sudden cardiac arrest. A prior study by our group demonstrated significant variability in cardiac arrest survival among hospitals, with improved survival in centers that treat a higher volume of cardiac arrest patients in their intensive care units.26 Others have shown variable association between hospital-level factors and SCA survival.27–29 This study will examine ED and hospital factors associated with survival to admission in SCA. We hypothesized that large, urban, academic hospitals with higher SCA volumes will have better survival to hospital admission than smaller, rural, low SCA volume hospitals.
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an ED disposition of “routine discharge” or “unknown”, and those with a concomitant diagnosis of injury were excluded. Injury was defined using ICD 9-CM codes 800.00–904.99, 925.00–929.99, and 950.00–957.99, excluding late effects (ICD-9 905.00–909.99), superficial injuries (910.00–919.99), contusions (920.00–924.99), effects of foreign body (930.00–939.99), early complications of trauma (958.00–958.99), or other/unspecified injury (959.00–959.99). Only hospitals with at least one non-injury related SCA case were included in our analyses. This study was approved by the institutional review board of the University of Pennsylvania with waiver of informed consent. 2.2. Variables A facility was defined as having a cardiac catheterization lab with PCI capability if >5 PCI procedure codes (ICD-9-CM 36.00–36.06, 36.09, and 00.66) were present over the course of the year. This definition of >5 PCIs performed per year has been used before to define hospitals capable of performing revascularization for patients with acute myocardial infarction.30 We acknowledge that this definition does not guarantee the availability of a PCI lab that is available around the clock to perform emergent PCI. Other hospital characteristics of interest included location [defined by Urban Influence Codes – metropolitan, micropolitan (non-metropolitan regions with >10,000 people), rural, and nonurban residential], region (defined by United States census region), teaching status, trauma center level, ED volume, and cardiac arrest volume. Emergency department volume and cardiac arrest volume were initially grouped into categorical variables, in increments of 10,000 annual ED visits and 20 annual cardiac arrest cases, respectively. ED volume and cardiac arrest volume variables were then further categorized as binary variables (ED volume ≥ 20,000 and CA volume ≥ 40) to derive more parsimonious estimates. Cut-points for the binary variables were determined using survival trends observed in the categorical variables. In the case of cardiac arrest volume, our cut point was consistent with previous literature. Although no prior work has examined cardiac arrest survival trends by ED volume, previous work has also suggested a cardiac arrest volume cut-point of 40–50 cases annually is associated with greater survival.26,27 2.3. Outcomes
2. Methods 2.1. Selection of study subjects Data were obtained from the Nationwide Emergency Department Sample (NEDS). The NEDS is the largest all-payer database in the United States and was developed, maintained, and made available through the Healthcare Cost & Utilization Project (HCUP) of the Agency for Healthcare Research and Quality. The NEDS is constructed annually using records from State Emergency Department Databases and State Inpatient Databases. In 2007, the year used for this study, information from 966 hospitals in 27 states was included. Hospitals are selected using a stratified probability sample based on hospital characteristics and are weighted to allow for the calculation of nationally representative estimates. Sampling strata include region of the country, teaching status, trauma center designation, hospital ownership type (i.e. public, for-profit, or not-for-profit), and location. All patients who presented to a participating ED were included in the NEDS. We defined sudden cardiac arrest (SCA) as cardiac arrest in the out-of-hospital or ED settings. SCA cases were defined as a primary or secondary ED diagnosis of cardiac arrest (ICD 9-CM 427.5) or ventricular fibrillation (ICD 9-CM 427.41). Patients less than 18 years of age, those with
We describe the magnitude and distribution of SCA cases presenting to EDs in the US. The primary outcome in our analyses examining hospital factors was survival to hospital admission. As a secondary outcome, we examined survival to hospital discharge. 2.4. Data analyses We used the hospital and individual-level weights provided by HCUP to account for the sampling design of the NEDS and to generate nationally representative estimates. The data were analyzed using statistical packages (SAS version 9.3, SAS Institute, Inc., Cary, NC and Stata version 12.0, Stata Corp, College Station, TX). Analyses were performed using generalized estimating equations with robust Huber–White confidence intervals to account for clustering by center. Data are presented as odds ratios (OR) with 95% confidence intervals (CI). We conducted two post hoc sensitivity analyses. Because of potential of differential rates of transfers between hospitals treating >40 and ≤40 SCA cases per year, we performed a sensitivity analysis excluding transferred patients. Because there is no consistent definition of a “PCI capable hospital” in the literature, we performed a second sensitivity analysis to examine whether
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substituting different PCI cut-points (greater than 15, 25, 50, and 100 PCIs per year) would affect survival in our multivariate model.
Table 2 Descriptive statistics (data presented as weighted percentages unless otherwise noted).
3. Results 3.1. Characteristics of hospitals and study subjects Hospital and patient characteristics are displayed in Tables 1 and 2. Of the 966 hospitals included in the NEDS, 933 (96.6%) documented at least one case of cardiac arrest in 2007, representing 4637 hospitals nationally. Of these hospitals, 74.2% admitted at least one cardiac arrest patient from the ED. In total, 38,593 cases of cardiac arrest were identified, representing an estimated 174,982 cases of SCA that present to or occur in EDs nationally. A total of 8008 patients were excluded (1786 [age < 18], 4296 [discharged from the ED or unknown], and 1926 [injury]). Hospitals that did not report at least one case of cardiac arrest case were most often non-metropolitan, located in the Midwest, and reported low (≤10,000) annual ED visits (Table 1). Of the patients included in this analysis, 26.2% survived to hospital admission. Of those who initially survived to be admitted, 40.2% of patients died after admission, resulting in an overall survival to hospital discharge of 15.7%. Patients surviving to be admitted were younger, more likely to be female, and less likely to be admitted on a weekend when compared to patients who died in the ED, though
Table 1 Hospital characteristics (data presented as weighted percentages unless otherwise noted).
Rurality Metropolitan Micropolitan/rural Region Northeast Midwest South West Hospital control Government, Nonfederal, Public Private Collapsed (Government or Private) Teaching status Metropolitan Non-teaching Metropolitan Teaching Non-Metropolitan Trauma center level Non-Trauma Trauma Center (Level 1, 2, 3) ED volume <10,000 10,000–20,000 20,000–30,000 30,000–40,000 40,000–50,000 50,000–60,000 60,000–70,000 70,000–80,000 >80,000 Cardiac arrest volume ≤20 21–40 41–60 61–80 81–100 >100 PCI available
Included hospitals (n = 933)
Excluded hospitals (n = 33)
58.9 41.1
35.9 64.1
13.4 28.8 39.7 18.2
5.5 45.8 16.7 32.0
17.1 42.8 40.1
44.2 23.0 32.8
42.5 16.5 41.1
11.5 24.3 64.1
83.1 16.9
86.7 13.3
25.6 20.7 16.0 14.1 8.4 6.7 3.0 1.3 4.1
69.9 5.8 5.5 5.1 2.8 8.1 2.9 0.0 0.0 N/A
35.9 22.7 16.0 10.4 6.1 8.9 30.2
N/A
Age (mean, SD) Female Weekend admission Rurality Metropolitan Micropolitan/rural Region Northeast Midwest South West Hospital control Government, Nonfederal, Public Private Collapsed (Government or Private) Teaching status Metropolitan Non-teaching Metropolitan Teaching Non-Metropolitan Trauma center level Non-Trauma Trauma Center (Level 1, 2, 3) ED volume <10000 10000–20000 20000–30000 30000–40000 40000–50000 50000–60000 60000–70000 70000–80000 >80000 Cardiac arrest volume ≤20 21–40 41–60 61–80 81–100 >100 PCI capability Capable Not capable
Survived to admission
Died preadmission
Overall
65.1 (15.7) 40.3 28.4
66.0 (17.3) 38.8 29.7
65.7 (16.9) 39.2 29.4
82.6 17.4
80.6 19.4
81.1 18.9
15.5 27.4 37.8 19.4
19.1 22.2 40.3 18.5
18.1 23.5 39.6 18.7
7.2 30.9 61.9
7.8 34.5 57.7
7.6 33.6 58.8
45.0 37.6 17.4
49.5 31.1 19.4
48.4 32.7 18.9
64.1 35.9
70.5 29.5
68.8 31.2
5.0 10.4 15.0 17.5 13.9 13.4 6.9 3.5 14.6
5.7 11.6 15.3 19.5 12.0 12.8 7.3 2.5 13.3
5.5 11.3 15.2 19.0 12.5 13.0 7.2 2.7 13.6
8.2 16.5 18.2 16.9 11.8 28.5
8.2 15.1 18.5 15.5 13.3 29.4
8.2 15.5 18.5 15.8 12.9 29.2
63.1 37.9
53.1 46.9
55.7 44.3
these differences were small and unlikely to be clinically significant (Table 2). Additionally, patients who survived to be admitted were more likely to be seen at hospitals with an annual ED volume ≥20,000, in metropolitan areas, and with PCI capabilities. Among hospitals with 40 or fewer SCA cases annually, 13.1% of patients were transferred, while hospitals with greater 40 SCA cases transferred only 2.7% of cases annually. 3.2. Individual characteristics Among patient characteristics, only female gender was associated with greater survival to hospital admission in adjusted multivariate analysis (OR 1.1 95% CI 1.0–1.1, p = 0.002 [Table 3]). Age greater than 55 years was not associated with worse outcome. 3.3. Regional characteristics Greater survival was seen in hospitals in the Midwest (OR 1.4, 95% CI 1.2–1.7, p < 0.001) and West (OR 1.3, 95% CI 1.1–1.5, p = 0.005) regions. Survival at rural or micropolitan (non-metropolitan area with at least 10,000 people or more) hospitals did not differ significantly when compared with metropolitan hospitals.
N.J. Johnson et al. / Resuscitation 84 (2013) 292–297 Table 3 Adjusted association between hospital characteristics and ED survival.
Individual characteristics Age ≤55 >55 Female Hospital characteristics Region Northeast Midwest South West Rurality Metropolitan Micropolitan/Rural Teaching status Metropolitan Non-teaching Metropolitan Teaching ED volume <10,000 10,000–20,000 20,000–30,000 30,000–40,000 40,000–50,000 50,000–60,000 60,000–70,000 70,000–80,000 >80,000 Cardiac arrest volume ≤20 21–40 41–60 61–80 81–100 >100 PCI capability Not capable Capable
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4. Discussion
OR (95% CI)
p-Value
Ref 1.0 (0.9–1.0) 1.1 (1.0–1.1)
– 0.683 0.002
Ref 1.4 (1.2–1.7) 1.2 (1.0–1.4) 1.3 (1.1–1.5)
– <0.001 0.057 0.005
Ref 1.0 (0.9–1.1)
– 0.980
Ref 1.3 (1.1–1.5)
– 0.001
Ref 1.2 (1.0–1.5) 1.5 (1.1–2.0) 1.5 (1.1–2.0) 1.9 (1.4–2.7) 1.7 (1.3–2.4) 1.5 (1.0–2.2) 2.2 (1.3–3.6) 2.1 (1.4–3.1)
– 0.099 0.004 0.013 <0.001 0.001 0.030 0.003 <0.001
Ref 0.8 (0.7–1.0) 0.7 (0.5–0.9) 0.6 (0.4–0.8) 0.5 (0.3–0.6) 0.4 (0.3–0.5)
– 0.062 0.001 <0.001 <0.001 <0.001
Ref 1.6 (1.4–1.8)
– <0.001
3.4. Hospital characteristics Greater survival to admission was seen in hospitals with teaching status (OR 1.3 95% CI 1.1–1.5, p = 0.001), and PCI capability (OR 1.6 95% CI 1.4–1.8, p < 0.001, [Table 3]). Annual ED visits ≥20,000 (OR 1.3 95% CI 1.1–1.6, p = 0.003) was also associated with higher survival. Higher SCA volume (defined as >40 cardiac arrests annually) was associated with lower survival (OR 0.7 95% 0.6–0.9, p = 0.010). 3.5. Sensitivity analyses Because of potential of differential rates of transfers between hospitals treating >40 and ≤40 SCA cases per year, we performed a post hoc sensitivity analysis excluding transferred patients. These patients were transferred out of EDs to inpatient settings at another hospital. These patients were counted as “survivors” by the transferring ED. A small subset of these patients may have been transferred to another ED, where they may have been counted as a survivor or a death for the receiving ED. After excluding patients who were transferred, the relationship between ED SCA cardiac arrest volume and survival was no longer significant (OR 0.8 95% CI 0.6–1.1, p = 0.116). We performed a second sensitivity analysis to examine whether different PCI cut-points (greater than 15, 25, 50, and 100 PCIs per year) would affect our results. We found no significant difference in the odds of survival when these cut-points were substituted for greater than 5 PCIs per year in our multivariate model (data not shown).
In this study, we sought to describe the incidence of SCA presenting to EDs in the US and to identify ED factors associated with higher survival to hospital admission. We found that a number of factors including ED volume, teaching status, and PCI capability were associated with higher survival to hospital admission among patients with SCA. We previously demonstrated significant variability for cardiac arrest patients who survived to be admitted to the hospital, and in this analysis we sought to determine whether ED factors contributed to differential survival to hospital admission.26 A number of studies have attempted to elucidate hospital factors associated with cardiac arrest mortality with widely variable results. A retrospective study in a single county by Liu et al. found that only nurse-to-bed ratio was significantly associated with in-hospital cardiac arrest mortality.29 A large, multicenter, multinational prospective study found no independent associations between OHCA survival to discharge and hospital characteristics.27 Previous studies have also demonstrated a variable relationship between cardiac arrest volume and survival. A recent study demonstrated improved outcomes in Korea among patients with OHCA transported to higher volume centers.31 An analysis of a prehospital registry in Melbourne, Australia found no association between OHCA volume and outcome.32 A recent analysis of the Cardiac Arrest Registry to Enhance Survival (CARES) did not find improved outcomes at higher volume OHCA centers.33 In our previous work we identified a strong association between hospital survival and treatment in an intensive care unit treating many patients with cardiac arrest.28 The association between cardiac arrest volume and survival to admission in the current analysis was less straightforward. We found that higher SCA volumes were associated with lower survival to hospital admission. This may reflect the effect of transfers as more patients were transferred out of lower SCA volume centers (counted as “survivors”) who may have gone on to die in transit or at higher SCA volume centers. In fact, our sensitivity analysis excluding transfers demonstrated that the association between ED SCA volume and lower survival disappeared after transferred patients were excluded. It is also possible that high volume EDs, which tend to be located in more urban locations, receive more patients with CPR in progress who never achieve ROSC. It has also been previously demonstrated that ED crowding is associated with poor outcomes for a variety of time-sensitive emergency conditions.34,35 Perhaps higher volume EDs experience more crowding which impacts care for SCA patients or results in premature termination of resuscitation. It may be that, given the complexity of cardiac arrest care, factors such as use of therapeutic hypothermia and goal-directed resuscitation, may exert greater influence on survival than SCA volume. These modalities of post-arrest care are variably implemented, and it is unclear whether hospitals with higher SCA volume utilize them more consistently.12 Others have contended that individual provider factors and experience might be more important predictors of patient outcome than facility volume.33 Prior work in the surgical literature demonstrated that individual surgeons with low procedural volume had higher rates of mortality even when their facility volumes were high.36 Perhaps in our study, especially because many of the high volume hospitals are likely teaching facilities, provider experience exerts a greater effect than hospital volume. The volume–outcome relationship, established in the surgical literature and proven for a variety of medical conditions, has become a major component the argument in favor of regionalized care.26,28,37–39 Hospitals that perform larger numbers of certain surgical procedures, such as coronary artery bypass and have been
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found to have better outcomes than lower volume centers.39,40 Many, including the American Heart Association, have advocated for the development of regional systems of care for SCA built around CRCs.14–16 Efforts to regionalize cardiac arrest care are underway, and a credentialing system for CRCs was recently released by the AHA.41–44 Our data, showing worse outcomes at high volume centers, suggest that volume alone is an inadequate criterion by which to designate centers that should preferentially care for patients with sudden cardiac arrest. Future efforts should focus on better understanding the relative importance of the many components of a system of care for cardiac arrest. Since our data comes from the NEDS, an ED sample, it is likely that some of the patients with ICD codes for cardiac arrest or ventricular fibrillation that most patients had their events in the outof-hospital setting, but some likely suffered cardiac arrest in the ED. Among inpatients who have suffered cardiac arrest, almost 11% of patients have their original event in the ED.45 Patients with cardiac arrest in the ED likely have higher survival than those who suffer out-of-hospital cardiac arrest (OHCA), which may explain why our study’s overall survival of 15.7% is higher than survival rates seen in OHCA studies.2,46 It is also likely that the overall survival in our study is higher because we did not include patients who are pronounced dead by paramedics and are never transported to the ED. Although a nationally representative sample of patients with SCA treated in EDs, because of the inclusion of ED arrests and the exclusion of patients not transported to the hospital after out of hospital cardiac arrest, our estimates likely do not accurately estimate the number of out-of-hospital cardiac arrests in the US annually. Our analysis is subject to a number of limitations. This is a retrospective study of administrative data, and thus is subject to the limitations of all retrospective studies. Because of limitations in our dataset, we were unable to determine if a patient was transferred from one ED to another ED. A live, post-arrest patient may have been transferred from one ED (where he was counted as a survivor) to another ED where he died, and similarly some survivors may have been counted twice. Because the NEDS is a large national sample and the numbers of ED-to-ED cardiac arrest transfers are likely low, we believe this was probably a rare event but a limitation nonetheless. Selection of patients for our study relied on ICD coding. Variability in coding practices among individuals and institutions may have influenced our results. Finally, since this is a large nationwide sample, there may be significant heterogeneity in the care provided both in the field and at receiving hospitals. We cannot comment on which aspects of patient care most affected survival. 5. Conclusion Nearly 175,000 cases of SCA present to or occur in EDs in the US each year. Percutaneous coronary intervention capability, ED volume, and teaching status were associated with higher survival to hospital admission. Emergency departments with higher annual SCA volume had lower survival rates, possibly because they transfer fewer patients. An improved understanding of the contribution of ED care to survival following SCA may be useful in advancing our understanding of how best to organize a system of care to ensure optimal outcomes for patients with SCA. Conflict of interest statement Nicholas Johnson and Rama Salhi have no disclosures. Benjamin Abella receives research funding from the National Institutes of Health, Philips, MedTronic Foundation, and the Doris Duke Foundation. He receives speaking honoraria from Medivance and provides advisory for Heartsine Corporation. Robert Neumar has no disclosures. David Gaieski receives research support and consulting fees from Stryker. Brendan Carr receives research funding from
Centers for Disease Control and Prevention, National Institutes of Health, Agency for Healthcare Research and Quality, and the American Heart Association.
Appendix A. Supplementary data Supplementary data associated with this article can be found, in the online version, at http://dx.doi.org/10.1016/j.resuscitation. 2012.10.013.
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