Identification of high-risk communities for unattended out-of-hospital cardiac arrests using GIS.

Improving survival rates for out of hospital cardiac arrest (OHCA) at the neighborhood level is increasingly seen as priority in US cities. Since wide disparities exist in OHCA rates at the neighborhood level, it is necessary to locate neighborhoods where people are at elevated risk for cardiac arrest and target these for educational outreach and other mitigation strategies. This paper describes a GIS-based methodology that was used to identify communities with high risk for cardiac arrests in Franklin County, Ohio during the period 2004-2009. Prior work in this area used a single criterion, i.e., the density of OHCA events, to define the high-risk areas, and a single analytical technique, i.e., kernel density analysis, to identify the high-risk communities. In this paper, two criteria are used to identify the high-risk communities, the rate of OHCA incidents and the level of bystander CPR participation. We also used Local Moran's I combined with traditional map overlay techniques to add robustness to the methodology for identifying high-risk communities for OHCA. Based on the criteria established for this study, we successfully identified several communities that were at higher risk for OHCA than neighboring communities. These communities had incidence rates of OHCA that were significantly higher than neighboring communities and bystander rates that were significantly lower than neighboring communities. Other risk factors for OHCA were also high in the selected communities. The methodology employed in this study provides for a measurement conceptualization of OHCA clusters that is much broader than what has been previously offered. It is also statistically reliable and can be easily executed using a GIS.

Poisson cluster analysis of cardiac arrest incidence in Columbus, Ohio.

BACKGROUND: Scarce resources in disease prevention and emergency medical services (EMS) need to be focused on high-risk areas of out-of-hospital cardiac arrest (OHCA). OBJECTIVE: Cluster analysis using geographic information systems (GISs) was used to find these high-risk areas and test potential predictive variables. METHODS: This was a retrospective cohort analysis of EMS-treated adults with OHCAs occurring in Columbus, Ohio, from April 1, 2004, through March 31, 2009. The OHCAs were aggregated to census tracts and incidence rates were calculated based on their adult populations. Poisson cluster analysis determined significant clusters of high-risk census tracts. Both census tract-level and case-level characteristics were tested for association with high-risk areas by multivariate logistic regression. RESULTS: A total of 2,037 eligible OHCAs occurred within the city limits during the study period. The mean incidence rate was 0.85 OHCAs/1,000 population/year. There were five significant geographic clusters with 76 high-risk census tracts out of the total of 245 census tracts. In the case-level analysis, being in a high-risk cluster was associated with a slightly younger age (-3 years, adjusted odds ratio [OR] 0.99, 95% confidence interval [CI] 0.99-1.00), not being white, non-Hispanic (OR 0.54, 95% CI 0.45-0.64), cardiac arrest occurring at home (OR 1.53, 95% CI 1.23-1.71), and not receiving bystander cardiopulmonary resuscitation (CPR) (OR 0.77, 95% CI 0.62-0.96), but with higher survival to hospital discharge (OR 1.78, 95% CI 1.30-2.46). In the census tract-level analysis, high-risk census tracts were also associated with a slightly lower average age (-0.1 years, OR 1.14, 95% CI 1.06-1.22) and a lower proportion of white, non-Hispanic patients (-0.298, OR 0.04, 95% CI 0.01-0.19), but also a lower proportion of high-school graduates (-0.184, OR 0.00, 95% CI 0.00-0.00). CONCLUSIONS: This analysis identified high-risk census tracts and associated census tract-level and case-level characteristics that can be used to target public education efforts to prevent OHCA and to mitigate its occurrence with CPR and automated external defibrillator training. In addition, EMS resources can be redeployed to minimize response times to these census tracts.

Surrogate markers of transport distance for out-of-hospital cardiac arrest patients.

BACKGROUND: Transport of out-of-hospital cardiac arrest (OHCA) patients expeditiously to appropriately equipped hospitals is of paramount importance. OBJECTIVE: We sought to test the correlation of the centroids of geographic units with the actual transport distance for OHCA patients in order to determine the most appropriate surrogate marker of location for future planning, protocol development, and research projects. METHODS: This was a prospective, observational analysis of OHCA events in Portland, Oregon. Using geographic information systems (GISs), the locations of OHCA events and receiving hospitals were identified and geocoded for visual inspection and analysis. Transport distance was calculated via network transport distance and Euclidean distance from multiple surrogate markers of location (centroids of ZIP code, census tract, census block group, and census block). Actual distance from the location of the event was then compared with these surrogate markers to determine the accuracy of alternative markers of OHCA location. RESULTS: Two hundred seventy patients had location data recorded, 163 of whom were transported to a hospital for further care. The median transport distance was 5.17 miles. The transport distance of OHCA patients from the centroid of the census block had the best correlation (R(2) = 0.99) with actual transport distance, whereas the use of the centroid of ZIP codes as a surrogate location had the lowest correlation (R(2) = 0.21). CONCLUSIONS: The use of centroids of census blocks via network distance is a valid surrogate for actual location of an OHCA event when calculating transport distance.

Prehospital factors associated with mortality in injured air medical patients.

BACKGROUND: Air medical transport provides rapid transport to definitive care. Overtriage and the expense and risk of transport may offset survival benefits. OBJECTIVE: We assessed the ability of prehospital factors to predict resource need for helicopter-transported patients. METHODS: We performed a prospective, observational cohort analysis of injured scene patients taken to one of two level I trauma centers from October 2009 to September 2010. Variables analyzed included patient demographics, diagnoses, and clinical outcomes (in-hospital mortality, emergent surgery within 24 hours, blood transfusion within 24 hours, and intensive care unit [ICU] admission ≥24 hours, as well as a combined outcome of all clinical outcomes). Prehospital variables were prospectively obtained from air medical providers at the time of transport and included past medical history, mechanism of injury, and clinical factors. We compared those variables with and without the outcomes of interest via χ(2) analysis and the Kruskal-Wallis test, where appropriate. Multivariate logistic regression identified factors associated with outcomes of interest with the intent of developing a clinical prediction tool. RESULTS: Five hundred fifty-seven patients were transported during the study period. The majority of the patients were male (67%) and white (95%) and had an injury that occurred in a rural location (58%). Most injuries were blunt (97%), and patients had a median Injury Severity Score (ISS) of 9. The overall mortality was 4%; 48% of the patients had one of the four outcomes. The most common reasons for requesting air transport were motor vehicle collision (MVC) with high-risk mechanism (18%), MVC at a speed greater than 20 mph (18%), Glasgow Coma Scale score (GCS) less than 14 (15%), and loss of consciousness (LOC) greater than 5 minutes (15%). Factors associated with mortality were age greater than 44 years, GCS less than 14, systolic blood pressure (SBP) less than 90 mmHg, and flail chest. This model had 100% sensitivity and 50% specificity and missed no deaths. The combined endpoint of all four outcomes (death, receipt of blood, surgery, ICU admission) included intubation by emergency medical services, two or more fractures of the humerus/femur, presence of a neurovascular injury, a crush injury to the head, failure to localize to pain on examination, GCS less than 14, or the presence of a penetrating head injury. This model had a sensitivity of 57% (53%-61%) and a specificity of 78% (75%-87%). CONCLUSIONS: Very few prehospital criteria were associated with clinically important outcomes in helicopter-transported patients. Evidence-based guidelines for the most appropriate utilization of air medical transport need to be further evaluated and developed for injured patients.

Part 6: electrical therapies: automated external defibrillators, defibrillation, cardioversion, and pacing: 2010 American Heart Association Guidelines for Cardiopulmonary Resuscitation and Emergency Cardiovascular Care.

The recommendations for electrical therapies described in this section are designed to improve survival from SCA and life-threatening arrhythmias. Whenever defibrillation is attempted, rescuers must coordinate high-quality CPR with defibrillation to minimize interruptions in chest compressions and to ensure immediate resumption of chest compressions after shock delivery. The high first-shock efficacy of newer biphasic defibrillators led to the recommendation of single shocks plus immediate CPR instead of 3-shock sequences that were recommended prior to 2005 to treat VF. Further data are needed to refine recommendations for energy levels for defibrillation and cardioversion using biphasic waveforms.

Rocuronium versus succinylcholine in air medical rapid-sequence intubation.

BACKGROUND: It is not known how rocuronium compares with succinylcholine in its effect on intubation success during air medical rapid-sequence intubation (RSI). OBJECTIVE: To examine the impact of succinylcholine use on the odds of successful prehospital intubation. METHODS: We performed a retrospective analysis of a critical care transport service administrative database containing patient encounters from 2004 to 2008. Rotor transports of patients ≥ 18 years old, requiring airway management (intubation or backup airway: laryngeal mask airway, Combitube, or cricothyrotomy), and receiving either rocuronium or succinylcholine were included in the analysis. Patients receiving both drugs were excluded. Multiple imputation was used to account for records that were missing data elements. A propensity score based on patient and encounter characteristics was calculated to control for the effect of clinical factors on the choice of drug by air medical personnel. Logistic regression was used to assess the impact of succinylcholine use on the odds of first-attempt intubation. Ordinal logistic regression was used to assess the impact of succinylcholine on the number of attempts required to intubate (1, 2, or ≥ 3 or backup airway). RESULTS: A total of 1,045 patients met the criteria for analysis; 761 (73%) were male, and the median age was 41 years (interquartile range 26-56). Eight hundred seventy-six (84%) were transported from the scene, and 484 (46%) received succinylcholine. Six hundred twelve (59%) were intubated on the first attempt, 322 (31%) required two attempts, 69 required three or more attempts (7%), and 42 required a backup airway (4%). After propensity score adjustment, succinylcholine was associated with a higher incidence of first-attempt intubation (odds ratio 1.4, 95% CI 1.1-1.8), as well as improved odds for requiring fewer attempts to intubate (odds ratio 1.5, 95% CI 1.2-1.9), as compared with rocuronium. CONCLUSIONS: Rapid-sequence intubation was more successful with fewer attempts in patients intubated by air medical crews with succinylcholine as opposed to rocuronium. Prospective, randomized studies are needed to confirm these findings and to explore the impact of succinylcholine on the outcomes of air medical-transported patients. Key words: airway management; critical care; emergency medical services; neuromuscular blockade; succinylcholine; rocuronium; rapid-sequence intubation; intubation; air medical transport.

The impact of rapid sequence intubation on trauma patient mortality in attempted prehospital intubation.

BACKGROUND: Rapid sequence intubation (RSI) has been instituted in some prehospital settings to improve the success of endotracheal intubation (ETI); whether RSI improves outcomes is unclear. OBJECTIVES: We sought to determine if trauma patients intubated with RSI in the prehospital setting had better survival compared to those intubated without RSI. METHODS: Retrospective cohort analysis. We analyzed all injured adults (aged >or= 15 years) meeting state trauma system criteria, having a prehospital ETI attempt, and transported from the scene (19 counties) to one of the two state Level 1 trauma centers from 2000-2005. To adjust for the non-random selection of patients for field RSI, we built a propensity score from 15 important confounders, including demographics, injury severity, blood transfusion, surgical procedures, comorbidities, alcohol use, transport mode, injury mechanism, and initial field physiologic values. A propensity-adjusted multivariable logistic regression model (outcome = in-hospital mortality), with a time-based variable for system-wide implementation of changes in airway management, was used to test the association between RSI-ETI and mortality. RESULTS: There were 877 consecutive trauma patients who had prehospital ETI during this period and were included in the analysis. Of these, 496 (57%) had RSI-ETI. In univariate analyses, those with RSI-ETI had less severe injuries, better prehospital physiology (i.e., higher Glasgow Coma Scale score and blood pressure), fewer operations, fewer blood transfusions, and lower unadjusted mortality than those intubated without RSI. However, in the propensity-adjusted model, there was no statistical difference in mortality between the two groups (odds ratio 0.74, 95% confidence interval 0.52-1.06). CONCLUSIONS: Patients selected for RSI-ETI were less seriously injured, with better prognostic factors than intubated patients for whom RSI was not used. After adjusting for these differences, use of prehospital RSI-ETI was not associated with improved survival.

Level I versus Level II trauma centers: an outcomes-based assessment.

OBJECTIVE: Trauma centers improve outcomes compared with nontrauma centers, although the relative benefit of different levels of major trauma centers (Level I vs. Level II hospitals) remains unclear. We sought to determine whether there was a difference in the patient outcome in trauma victims taken to Level I versus Level II trauma centers. METHODS: A multicenter, retrospective cohort analysis of all patients with trauma (>15 years), meeting State of Ohio trauma criteria, transported directly from the scene to a Level I or a Level II hospital (27 centers) between January 2003 and December 2006. Propensity score adjustment was used to adjust for nonrandom selection of hospital destination (I vs. II) and included age, emergency medical services (EMS) Glasgow Coma Score, comorbidities, EMS systolic blood pressure, injury type, injury severity, EMS procedures, emergency department procedures, gender, insurance status, and race. A propensity-adjusted multivariable logistic regression model was used to test the association between trauma center level and patient outcomes. Outcomes included in-hospital mortality and discharge destination (skilled nursing facility, rehabilitation center, home). RESULTS: A total of 18,103 patients were included in the analysis; 10,070 (56%) were transported to a Level I center. Patients taken to Level I centers had more severe injuries, more penetrating injuries, more complications, yet similar unadjusted mortality compared with Level II centers. In adjusted analyses, patients taken to Level I hospitals had improved survival compared with Level II centers (odds ratio [OR] 0.75, 95% confidence interval [CI] 0.56-0.98). Similar results were seen when restricting the analyses to patients with serious injuries (Injury Severity Score > 15; EMS Glasgow Coma Score < 9). Patients treated at Level I hospitals were more likely to be discharged home (OR 1.14, 95% CI 1.05-1.25), or a rehabilitation center or skilled nursing facility (OR 1.39, 95% CI 1.27-1.52). CONCLUSIONS: Patients taken to Level I centers had improved survival and better functional outcomes compared with injured persons taken to Level II hospitals.

Distance impacts mortality in trauma patients with an intubation attempt.

OBJECTIVE: Out-of-hospital endotracheal intubation (OOH-ETI) has been associated with adverse outcomes; whether transport distance changes this relationship is unclear. We sought to determine whether patients injured farther from the hospital benefit more from OOH-ETI than those injured closer. METHODS: We performed a retrospective cohort analysis of trauma patients > 14 years old transported to two Level 1 trauma centers and surviving to admission from 2000 to 2003. We used probabilistically linked geographic data to calculate transport distance. To adjust for the nonrandom selection of patients for OOH-ETI, we used a propensity score based on clinical variables: prehospital physiology, demographics, transport mode, mechanism, comorbidities, Abbreviated Injury Scale head injury score >or= 3, Injury Severity Score, blood transfusion, and major surgery. Propensity-adjusted multivariable logistic regression with mode of transport was used to test the interaction between distance and OOH-ETI. RESULTS: 8,786 patients were included, 534 with OOH-ETI. Patients with OOH-ETI had higher adjusted mortality (odds ratio [OR] 2.06, 95% confidence interval [CI] 1.33-3.18), and there was a significant interaction between distance and OOH-ETI (p = 0.02). Patients with shortest distances had the highest mortality (OR 3.98, 95% CI 2.08-7.60). Probability of mortality was higher with OOH-ETI across all distances and increased for patients closest to the hospital. Helicopter transport was associated with improved survival. CONCLUSIONS: Prehospital intubation is associated with increased mortality among trauma patients at all distances from the hospital. Patients with the shortest transport distances had the greatest mortality associated with OOH-ETI, whereas helicopter transport was associated with improved survival. The event location and ensuing distance to the hospital are another factor to consider when instituting and modifying OOH airway protocols.

The diagnosis of acute mesenteric ischemia: A systematic review and meta-analysis.

OBJECTIVES: Acute mesenteric ischemia is an infrequent cause of abdominal pain in emergency department (ED) patients; however, mortality for this condition is high. Rapid diagnosis and surgery are key to survival, but presenting signs are often vague or variable, and there is no pathognomonic laboratory screening test. A systematic review and meta-analysis of the available literature was performed to determine diagnostic test characteristics of patient symptoms, objective signs, laboratory studies, and diagnostic modalities to help rule in or out the diagnosis of acute mesenteric ischemia in the ED. METHODS: In concordance with published guidelines for systematic reviews, the medical literature was searched for relevant articles. The Quality Assessment Tool for Diagnostic Accuracy Studies-2 (QUADAS-2) for systematic reviews was used to evaluate the overall quality of the trials included. Summary estimates of diagnostic accuracy were computed by using a random-effects model to combine studies. Those studies without data to fully complete a two-by-two table were not included in the meta-analysis portion of the project. RESULTS: The literature search identified 1,149 potentially relevant studies, of which 23 were included in the final analysis. The quality of the diagnostic studies was highly variable. A total of 1,970 patients were included in the combined population of all included studies. The prevalence of acute mesenteric ischemia ranged from 8% to 60%. There was a pooled sensitivity for l-lactate of 86% (95% confidence interval [CI] = 73% to 94%) and a pooled specificity of 44% (95% CI = 32% to 55%). There was a pooled sensitivity for D-dimer of 96% (95% CI = 89% to 99%) and a pooled specificity of 40% (95% CI = 33% to 47%). For computed tomography (CT), we found a pooled sensitivity of 94% (95% CI = 90% to 97%) and specificity of 95% (95% CI = 93% to 97%). The positive likelihood ratio (+LR) for a positive CT was 17.5 (95% CI = 5.99 to 51.29), and the negative likelihood ratio (-LR) was 0.09 (95% CI = 0.05 to 0.17). The pooled operative mortality rate for mesenteric ischemia was 47% (95% CI = 40% to 54%). Given these findings, the test threshold of 2.1% (below this pretest probability, do not test further) and a treatment threshold of 74% (above this pretest probability, proceed to surgical management) were calculated. CONCLUSIONS: The quality of the overall literature base for mesenteric ischemia is varied. Signs, symptoms, and laboratory testing are insufficiently diagnostic for the condition. Only CT angiography had adequate accuracy to establish the diagnosis of acute mesenteric ischemia in lieu of laparotomy.

Identifying high-risk geographic areas for cardiac arrest using three methods for cluster analysis.

OBJECTIVES: The objective was to identify high-risk census tracts, defined as those areas that have both a high incidence of out-of-hospital cardiac arrest (OHCA) and a low prevalence of bystander cardiopulmonary resuscitation (CPR), by using three spatial statistical methods. METHODS: This was a secondary analysis of two prospectively collected registries in the city of Columbus, Ohio. Consecutive adult (≥18 years) OHCA patients, restricted to those of cardiac etiology and treated by emergency medical services (EMS) from April 1, 2004, to April 30, 2009, were studied. Three different spatial analysis methods (Global Empirical Bayes, Local Moran's I, and SaTScan's spatial scan statistic) were used to identify high-risk census tracts. RESULTS: A total of 4,553 arrests in 200 census tracts occurred during the study period, with 1,632 arrests included in the final sample after exclusions for no resuscitation attempt, noncardiac etiology, etc. The overall incidence for OHCA was 0.70 per 1,000 people for the 6-year study period (SD = ±0.52). Bystander CPR occurred in 20.2% (n = 329), with 10.0% (n = 167) surviving to hospital discharge. Five high-risk census tracts were identified by all three analytic methods. CONCLUSIONS: The five high-risk census tracts identified may be possible sites for high-yield targeted community-based interventions to improve CPR training and cardiovascular disease education efforts and ultimately improve survival from OHCA.

Increasing hospital volume is not associated with improved survival in out of hospital cardiac arrest of cardiac etiology.

BACKGROUND: Resuscitation centers may improve patient outcomes by achieving sufficient experience in post-resuscitation care. We analyzed the relationship between survival and hospital volume among patients suffering out-of-hospital cardiac arrest (OHCA). METHODS: This prospective cohort investigation collected data from the Cardiac Arrest Registry to Enhance Survival database from 10/1/05 to 12/31/09. Primary outcome was survival to discharge. Hospital characteristics were obtained via 2005 American Hospital Association Survey. A hospital's use of hypothermia was obtained via direct survey. To adjust for hospital- and patient-level variation, multilevel, hierarchical logistic regression was performed. Hospital volume was modeled as a categorical (OHCA/year≤10, 11-39, ≥40) variable. A stratified analysis evaluating those with ventricular fibrillation or pulseless ventricular tachycardia (VF/VT) was also performed. RESULTS: The cohort included 4125 patients transported by EMS to 155 hospitals in 16 states. Overall survival to hospital discharge was 35% among those admitted to the hospital. Individual hospital rates of survival varied widely (0-100%). Unadjusted survival did not differ between the 3 hospital groups (36% for ≤10 OHCA/year, 35% for 11-39, and 36% for ≥40; p=0.75). After multilevel adjustment, differences in survival across the groups were not statistically significant. Compared to patients at hospitals with ≤10 OHCA/year, adjusted OR for survival was 1.04 (CI(95) 0.83-1.28) among 11-39 annual volume and 0.97 (CI(95) 0.73-1.30) among the ≥40 volume hospitals. Among patients presenting with VF/VT, no difference in survival was identified between the hospital groups. CONCLUSION: Survival varied substantially across hospitals. However, hospital OHCA volume was not associated with likelihood of survival. Additional efforts are required to determine what hospital characteristics might account for the variability observed in OHCA hospital outcomes.

Modification of Glasgow Coma Scale criteria for injured elders.

OBJECTIVES: An abnormal field Glasgow Coma Scale (GCS) score of ≤13 has been used in our emergency medical services (EMS) system to prompt transport to a trauma center. For elders, Ohio has recently adopted a GCS of ≤14 to prompt EMS transport to a trauma center, as older patients respond differently to trauma and may benefit from a different GCS threshold. This study sought to determine if a field GCS of 14 is an appropriate cutoff to initiate transport to a trauma center among injured elders. METHODS: This was a retrospective, observational statewide analysis of injured patients ≥16 years old captured by the Ohio Trauma Registry from 2002 to 2007. Outcomes studied included mortality, traumatic brain injury (TBI), neurosurgical intervention, and endotracheal intubation (ETI). Multiple imputation was performed to account for missing data. Age-stratified sensitivity and specificity for proposed GCS cutoffs of 13 and 14 were calculated. A series of multivariate logistic regression models was then constructed using each outcome as a dependent variable. Independent variables included age, GCS score, sex, blood pressure, injury type, nontrauma center, race, ethnicity, and Injury Severity Score (ISS). Two separate analyses were performed. For each age group, odds ratios (ORs) of each outcome were calculated both for the decrease in GCS from 15 to 14 and for the decrease from 14 to 13. The group of elders with GCS 14 was then compared to adults with GCS 13. RESULTS: A total of 52,412 study patients were identified. For a GCS cutoff of 13, sensitivity among elders for each outcome was >20% less than sensitivity for adults, and specificity was 5% to 10% greater. Increasing the GCS cutoff for elders to 14 resulted in improved sensitivity for all outcomes (approximately 10%), with a decline in specificity to values near that of adults with GCS 13. In the multivariate models for elders, mortality increased with a decrease in GCS both from 15 to 14 (OR = 1.40, 95% confidence interval [CI] = 1.07 to 1.83) and from GCS 14 to 13 (OR = 2.34, 95% CI = 1.57 to 3.52). In adults, mortality did not increase with the drop from GCS 15 to 14 (OR = 1.22, 95% CI = 0.88 to 1.71) or from GCS 14 to 13 (OR = 1.45, 95% CI = 0.91 to 2.30). When comparing elders with GCS 14 to adults with GCS 13, elders had greater odds of mortality (OR = 4.68, 95% CI = 2.90 to 7.54) and TBI (OR = 1.84, 95% CI = 1.45 to 2.34). CONCLUSIONS: Changing the EMS trauma triage cutoff for elders from GCS 13 to GCS 14 results in improved sensitivity for clinically relevant outcomes. In injured elders, the decline in GCS from 15 to 14 is associated with increased mortality, a finding not observed in younger adults. Elders with GCS 14 have greater odds of mortality and TBI than adults with GCS 13. These results support recent changes in EMS trauma triage guidelines for elders adopted in Ohio.

Are all trauma centers created equally? A statewide analysis.

OBJECTIVES: Prior work has shown differences in mortality at different levels of trauma centers (TCs). There are limited data comparing mortality of equivalently verified TCs. This study sought to assess the potential differences in mortality as well as discharge destination (discharge to home vs. to a rehabilitation center or skilled nursing facility) across Level I TCs in the state of Ohio. METHODS: This was a retrospective, multicenter, statewide analysis of a state trauma registry of American College of Surgeons (ACS)-verified Level I TCs from 2003 to 2006. All adult (>15 years) patients transferred from the scene to one of the 10 Level I TCs throughout the state were included (n = 16,849). Multivariable logistic regression models were developed to assess for differences in mortality, keeping each TC as a fixed-effect term and adjusting for patient demographics, injury severity, mechanism of injury, and emergency medical services and emergency department procedures. Outcomes included in-hospital mortality and discharge destination (home vs. rehabilitation center or skilled nursing facility). Adjusted odds ratios (ORs) for each TC were also calculated. RESULTS: Considerable variability existed in unadjusted mortality between the centers, from 3.8% (95% confidence interval [CI] = 3.7% to 3.9%) to 24.2% (95% CI = 24.1% to 24.3%), despite similar patient characteristics and injury severity. Adjusted mortality had similar variability as well, ranging from an OR of 0.93 (95% CI = 0.47 to 1.84) to an OR of 6.02 (95% CI= 3.70 to 9.79). Similar results were seen with the secondary outcomes (discharge destination). CONCLUSIONS: There is considerable variability in the mortality of injured patients at Level I TCs in the state of Ohio. The patient differences or care processes responsible for this variation should be explored.

A geospatial assessment of transport distance and survival to discharge in out of hospital cardiac arrest patients: Implications for resuscitation centers.

OBJECTIVES: National leaders have suggested that patients with an out of hospital cardiac arrest (OOHCA) may benefit from transport to specialized hospitals. We sought to assess the survival of OOHCA patients by transport distance and hospital proximity. METHODS: Prospective, cohort study of OOHCA patients in 11 Resuscitation Outcomes Consortium (ROC) sites across North America. Transport distance and hospital proximity was calculated using weighted centroid of census tract location by Geographic Information Systems (GIS). Patients were stratified into quartiles based on transport distance to the receiving hospital calculated via GIS. Descriptive statistics were used to describe characteristics by transport distance and to compare proximity to other hospitals. Multivariate logistic regression was used to evaluate the impact of transport distance on survival. RESULTS: 26,628 patients were identified, 7540 (28%) were transported by EMS and included in the final analysis. The median transport time was 6.3 min (IQR 5.4); the median transport distance being 2.4 miles (3.9 km). Most patients were taken to the closest hospital (71.7%; N=5412). However, unadjusted survival to discharge was lower for those taken to the closest compared to further hospitals (12.1% vs. 16.5%) despite similar patient characteristics. Transport distance was not associated with survival on logistic analysis (OR 1.00; 95% CI 0.99-1.01). CONCLUSIONS: Survival to discharge was higher in OOHCA patients taken to hospitals located further than the closest hospital while transport distance was not associated with survival. This suggests that longer transport distance/time might not adversely affect outcome. Further studies are needed to inform policy decisions regarding best destination post-cardiac arrest.

Prehospital electrocardiograms (ECGs) do not improve the process of emergency department care in hospitals with higher usage of ECGs in non-ST-segment elevation myocardial infarction patients.

BACKGROUND: This article will describe the impact of prehospital electrocardiogram (ECG) use on emergency department (ED) processes of care for non-ST-segment elevation myocardial infarction (NSTEMI) patients and assess the characteristics associated with prehospital ECG use. METHODS: This is a retrospective, multicenter, observational analysis of NSTEMI patients captured by the National Cardiovascular Data Registry-Acute Coronary Treatment and Intervention Outcomes Network Registry-Get with the Guidelines (NCDR ACTION-GWTG) in 2007. Patient and hospital data were stratified by documentation of a prehospital ECG (pECG). Hospitals were stratified into tertiles of pECG use by higher pECG (>5.6%, n 91), lower pECG (< or = 5.6%, n = 83), or no pECG (n = 100). Statistical evaluation was done via Wilcoxon rank sum and chi(2) tests. RESULTS: There were 21 251 patients eligible for analysis. A pECG was documented in 1609 (7.6%) patients. Of 274 hospitals, 100 (36.5%) had no pECGs recorded. Median ED length of stay (LOS) was shorter at no pECG hospitals vs lower pECG hospitals (3.97 h vs 4.12 h, P < 0.05), but not higher pECG hospitals vs no pECG hospitals (3.85 h vs 3.97 h, P = not significant [NS]). A pECG was not associated with an improvement in ED performance metrics (use of aspirin, beta-blocker, any heparin) in the higher pECG hospitals vs no pECG hospitals or the lower pECG hospitals vs no pECG hospitals. CONCLUSIONS: Use of prehospital ECG in NSTEMI patients is uncommon. In contrast to its impact on reperfusion times in ST-segment elevation myocardial infarction (STEMI) patients, its use does not appear to be associated with an improvement in ED processes of care at the hospital level.

Endotracheal intubation increases out-of-hospital time in trauma patients.

OBJECTIVES: Prior efforts have linked field endotracheal intubation (ETI) with increased out of hospital (OOH) time, but it is not clear if the additional time delay is due to the procedure, patient acuity, or transport distance. We sought to assess the difference in OOH time among trauma patients with and without OOH-ETI after accounting for distance and other clinical variables. METHODS: Retrospective cohort analysis of trauma patients 14 years or older transported by ground or air to one of two Level 1 trauma centers from January 2000 to December 2003. Geographical data were probabilistically linked to trauma registry records for transport distance. Trauma registry OOH time (interval from 9-1-1 call to hospital arrival) was validated against a subset of linked ambulance records using Bland-Altman plots and tested by using the Spearman rank correlation coefficient. Based on the validation, the sample was restricted to patients with OOH time 100 minutes or less. The propensity for OOH-ETI was calculated by using field vital signs, demographics, mechanism, transport mode, comorbidities, Abbreviated Injury Scale head injury 3 or greater, injury severity score, blood transfusion, and major surgery. Multivariable linear regression (outcome = total OOH time) was used to assess the time increase (minutes) associated with OOH-ETI after adjusting for distance, propensity for OOH-ETI, and mode of transport. RESULTS: A total of 8,707 patients were included in the analysis, of which 570 (6.5%) were intubated in the field. Adjusted only for distance, OOH times averaged 6.1 minutes longer (95% CI 4.2-7.9) among patients intubated with RSI. After including other covariates, OOH time was 10.7 minutes (95% CI 7.7-13.8) longer among patients with RSI and 5.2 minutes (95% CI 2.2-8.1) longer among patients with conventional ETI. The time difference was greatest farther from the hospital. CONCLUSIONS: Patients with OOH-ETI have increased total OOH time, especially among those using RSI, even after accounting for distance and other clinical factors. Injured patients may benefit from airway management techniques that require less time for execution.

Adequacy of online medical command communication and emergency medical services documentation of informed refusals.

BACKGROUND: In the out-of-hospital setting, when emergency medical services (EMS) providers respond to a 9-1-1 call and encounter a patient who wishes to refuse medical treatment and/or transport to the hospital, the EMS providers must ensure the patient possesses medical decision-making capacity and obtain an informed refusal. In the city of Cleveland, Ohio, Cleveland EMS completes a nontransport worksheet that prompts the paramedics to evaluate specific patient characteristics that can influence medical decision-making capacity and then discuss the risks of refusing with the patient. Cleveland EMS then contacts an online medical command (OLMC) physician to authorize the refusal. OLMC calls are recorded for review. OBJECTIVES: To assess the ability of EMS to determine medical decision-making capacity and obtain an informed refusal of transport. METHODS: This study was a retrospective review of a cohort of recorded OLMC refusal calls and of the accompanying written documentation by Cleveland EMS. The completeness of the verbal communication between the paramedic and OLMC physician and the written documentation on the nontransport worksheet were measured as surrogate markers of the adequacy of determining medical decision-making capacity and obtaining an informed refusal. RESULTS: One hundred thirty-seven OLMC calls for patient-initiated refusals were reviewed. Vital signs and alertness/orientation were verbally communicated more than 83% of the time. The presence of head injury, presence of alcohol or drug intoxication, and presence of hypoglycemia were verbally communicated less than 31% of the time. Verbal communication stating that the risks of refusing had been discussed with the patient occurred 44.5% of the time. The written documentation of the refusal encounter was more complete, exceeding 95% for vital signs and alertness/orientation, and exceeding 80% for the remaining patient characteristics. The rate of written documentation that the risks of refusing had been discussed with the patient was 48.7%. Discrepancies between the verbal and written paramedic reports were clinically insignificant. CONCLUSIONS: Paramedic and OLMC physician communication for patients refusing out-of-hospital medical treatment and/or transport is inadequate in the Cleveland EMS system. A written nontransport worksheet improves documentation of the refusal encounter but does not ensure that every patient who refuses possesses medical decision-making capacity and the capacity to provide an informed refusal.