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Naftali J, Tsur G, Auriel E, Raphaeli G, Findler M, Brauner R, Perlow A, Keret O, Barnea R. Impact of demographic and clinical factors on in-hospital delays in acute ischemic stroke treatment. Interv Neuroradiol 2024:15910199241264326. [PMID: 39053431 DOI: 10.1177/15910199241264326] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 07/27/2024] Open
Abstract
BACKGROUND Delays in reperfusion treatment, both intravenous thrombolysis (IVT) and endovascular treatment (EVT), adversely affect outcomes in patients with acute ischemic stroke (AIS). To alleviate these delays, it is essential to comprehend how patients' baseline and stroke characteristics impact in-hospital reperfusion delays. While demographic and socioeconomic factors affect stroke outcomes, their impact on in-hospital delays remains unclear. METHOD This is retrospective analysis at a tertiary stroke center, encompassing AIS patients receiving IVT and / or EVT between 2019 and 2022 (re-canalization cohort). Outcomes of interest were time intervals of admission to CT and admission to recanalization. Univariable analyses explored age, gender, baseline functional status, socioeconomic status (SES), ethnicity, vascular risk factors, and stroke characteristics. Subsequently, multivariable logistic regression analyses were performed. RESULTS Altogether, 313 patients treated with IVT and 293 with EVT were included in the re-canalization cohort. No demographic variables were found to be associated with stroke treatment time intervals. Following multivariable analysis, stroke severity (low NIHSS, p < 0.01), arrival to the hospital by other means than ambulance (p < 0.01), and atypical stroke symptoms (p < 0.01), were associated with in-hospital delays, both in the EVT and the IVT groups. CONCLUSION Our findings indicate that patients with a more severe ischemic stroke, typical stroke symptoms, and arrival by ambulance have shorter stroke treatment time intervals. These results emphasize that, in atypical cases, even a lower suspicion of stroke should promote urgent workup for stroke diagnosis. Our findings do not indicate any influence of demographic or SES on in-hospital reperfusion delays.
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Affiliation(s)
- Jonathan Naftali
- Department of Neurology, Rabin Medical Center, Petach Tikva, Israel
- Faculty of Medicine, Tel Aviv University, Tel-Aviv, Israel
| | - Gal Tsur
- Department of Neurology, Rabin Medical Center, Petach Tikva, Israel
| | - Eitan Auriel
- Department of Neurology, Rabin Medical Center, Petach Tikva, Israel
- Faculty of Medicine, Tel Aviv University, Tel-Aviv, Israel
| | - Guy Raphaeli
- Department of Neurology, Rabin Medical Center, Petach Tikva, Israel
- Faculty of Medicine, Tel Aviv University, Tel-Aviv, Israel
- Interventional Neuroradiology unit, Rabin Medical Center, Petach Tikva, Israel
| | - Michael Findler
- Department of Neurology, Rabin Medical Center, Petach Tikva, Israel
- Faculty of Medicine, Tel Aviv University, Tel-Aviv, Israel
- Interventional Neuroradiology unit, Rabin Medical Center, Petach Tikva, Israel
| | - Ran Brauner
- Department of Neurology, Rabin Medical Center, Petach Tikva, Israel
- Faculty of Medicine, Tel Aviv University, Tel-Aviv, Israel
- Interventional Neuroradiology unit, Rabin Medical Center, Petach Tikva, Israel
| | - Alain Perlow
- Faculty of Medicine, Tel Aviv University, Tel-Aviv, Israel
- Interventional Neuroradiology unit, Rabin Medical Center, Petach Tikva, Israel
| | - Ophir Keret
- Department of Neurology, Rabin Medical Center, Petach Tikva, Israel
- Faculty of Medicine, Tel Aviv University, Tel-Aviv, Israel
- Cognitive Neurology Clinic, Rabin Medical Center, Petach Tikva, Israel
| | - Rani Barnea
- Department of Neurology, Rabin Medical Center, Petach Tikva, Israel
- Faculty of Medicine, Tel Aviv University, Tel-Aviv, Israel
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Grubic N, Hill B, Allan KS, Maximova K, Banack HR, Del Rios M, Johri AM. Mediators of the Association Between Socioeconomic Status and Survival After Out-of-Hospital Cardiac Arrest: A Systematic Review. Can J Cardiol 2024; 40:1088-1101. [PMID: 38211888 DOI: 10.1016/j.cjca.2024.01.002] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/01/2023] [Revised: 12/21/2023] [Accepted: 01/01/2024] [Indexed: 01/13/2024] Open
Abstract
Low socioeconomic status (SES) is associated with poor outcomes after out-of-hospital cardiac arrest (OHCA). Patient characteristics, care processes, and other contextual factors may mediate the association between SES and survival after OHCA. Interventions that target these mediating factors may reduce disparities in OHCA outcomes across the socioeconomic spectrum. This systematic review identified and quantified mediators of the SES-survival after OHCA association. Electronic databases (MEDLINE, Embase, PubMed, Web of Science) and grey literature sources were searched from inception to July or August 2023. Observational studies of OHCA patients that conducted mediation analyses to evaluate potential mediators of the association between SES (defined by income, education, occupation, or a composite index) and survival outcomes were included. A total of 10 studies were included in this review. Income (n = 9), education (n = 4), occupation (n = 1), and composite indices (n = 1) were used to define SES. The proportion of OHCA cases that had bystander involvement, presented with an initial shockable rhythm, and survived to hospital discharge or 30 days increased with higher SES. Common mediators of the SES-survival association that were evaluated included initial rhythm (n = 6), emergency medical services response time (n = 5), and bystander cardiopulmonary resuscitation (n = 4). Initial rhythm was the most important mediator of this association, with a median percent excess risk explained of 37.4% (range 28.6%-40.0%; n = 5; 1 study reported no mediation) and mediation proportion of 41.8% (n = 1). To mitigate socioeconomic disparities in outcomes after OHCA, interventions should target potentially modifiable mediators, such as initial rhythm, which may involve improving bystander awareness of OHCA and the need for prompt resuscitation.
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Affiliation(s)
- Nicholas Grubic
- Dalla Lana School of Public Health, University of Toronto, Toronto, Ontario, Canada; Department of Medicine, Queen's University, Kingston, Ontario, Canada.
| | - Braeden Hill
- Department of Medicine, Queen's University, Kingston, Ontario, Canada
| | - Katherine S Allan
- Division of Cardiology, St Michael's Hospital, Toronto, Ontario, Canada
| | - Katerina Maximova
- Dalla Lana School of Public Health, University of Toronto, Toronto, Ontario, Canada; MAP Centre for Urban Health Solutions, St Michael's Hospital, Toronto, Ontario, Canada
| | - Hailey R Banack
- Dalla Lana School of Public Health, University of Toronto, Toronto, Ontario, Canada
| | - Marina Del Rios
- Carver College of Medicine, University of Iowa, Iowa City, Iowa, United States
| | - Amer M Johri
- Department of Medicine, Queen's University, Kingston, Ontario, Canada
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Metcalf D, Zhang D. Racial and ethnic disparities in the usage and outcomes of ischemic stroke treatment in the United States. J Stroke Cerebrovasc Dis 2023; 32:107393. [PMID: 37797411 PMCID: PMC10841526 DOI: 10.1016/j.jstrokecerebrovasdis.2023.107393] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/22/2023] [Revised: 09/12/2023] [Accepted: 09/25/2023] [Indexed: 10/07/2023] Open
Abstract
OBJECTIVES This study explores racial and ethnic differences in 1) receiving tissue plasminogen activator (tPA) and endovascular thrombectomy (EVT) as treatment for ischemic stroke and 2) outcomes and quality of care after use of tPA or EVT in the US. MATERIALS AND METHODS An observational analysis of 89,035 ischemic stroke patients from the 2019 National Inpatient Sample was conducted. We performed weighted logistic regressions between race and ethnicity and 1) tPA and EVT utilization and 2) in-hospital mortality. We also performed a weighted Poisson regression between race and ethnicity and length of stay (LOS) after tPA or EVT. RESULTS Non-Hispanic (NH) Black patients had significantly lower odds of receiving tPA (Adjusted odds ratio [AOR] = 0.85, 95 % Confidence Internal [C.I.]: 0.80-0.91) and EVT (AOR = 0.75, 95 % CI: 0.70-0.82) than NH White patients. Minority populations (including but not limited to NH Black, Hispanic, Pacific Islander, Native American, and Asian) had significantly longer hospital LOS after treatment with tPA or EVT. We did not find a significant difference between race/ethnicity and in-hospital mortality post-tPA or EVT. CONCLUSIONS While we failed to find a difference in in-hospital mortality, racial and ethnic disparities are still evident in the decreased usage of tPA and EVT and longer LOSs for racial and ethnic minority patients. This study calls for interventions to expand the utilization of tPA and EVT and advance quality of care post-tPA or EVT in order to improve stroke care for minority patients.
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Affiliation(s)
- Delaney Metcalf
- Medical College of Georgia and Augusta University/ University of Georgia Medical Partnership, Athens, GA 30605, United States.
| | - Donglan Zhang
- Center for Population Health and Health Services, Research Department of Foundations of Medicine, NYU Grossman Long Island School of Medicine, Mineola, NY 11501, United States
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Saceleanu VM, Toader C, Ples H, Covache-Busuioc RA, Costin HP, Bratu BG, Dumitrascu DI, Bordeianu A, Corlatescu AD, Ciurea AV. Integrative Approaches in Acute Ischemic Stroke: From Symptom Recognition to Future Innovations. Biomedicines 2023; 11:2617. [PMID: 37892991 PMCID: PMC10604797 DOI: 10.3390/biomedicines11102617] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/23/2023] [Revised: 09/21/2023] [Accepted: 09/21/2023] [Indexed: 10/29/2023] Open
Abstract
Among the high prevalence of cerebrovascular diseases nowadays, acute ischemic stroke stands out, representing a significant worldwide health issue with important socio-economic implications. Prompt diagnosis and intervention are important milestones for the management of this multifaceted pathology, making understanding the various stroke-onset symptoms crucial. A key role in acute ischemic stroke management is emphasizing the essential role of a multi-disciplinary team, therefore, increasing the efficiency of recognition and treatment. Neuroimaging and neuroradiology have evolved dramatically over the years, with multiple approaches that provide a higher understanding of the morphological aspects as well as timely recognition of cerebral artery occlusions for effective therapy planning. Regarding the treatment matter, the pharmacological approach, particularly fibrinolytic therapy, has its merits and challenges. Endovascular thrombectomy, a game-changer in stroke management, has witnessed significant advances, with technologies like stent retrievers and aspiration catheters playing pivotal roles. For select patients, combining pharmacological and endovascular strategies offers evidence-backed benefits. The aim of our comprehensive study on acute ischemic stroke is to efficiently compare the current therapies, recognize novel possibilities from the literature, and describe the state of the art in the interdisciplinary approach to acute ischemic stroke. As we aspire for holistic patient management, the emphasis is not just on medical intervention but also on physical therapy, mental health, and community engagement. The future holds promising innovations, with artificial intelligence poised to reshape stroke diagnostics and treatments. Bridging the gap between groundbreaking research and clinical practice remains a challenge, urging continuous collaboration and research.
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Affiliation(s)
- Vicentiu Mircea Saceleanu
- Neurosurgery Department, Sibiu County Emergency Hospital, 550245 Sibiu, Romania;
- Neurosurgery Department, “Lucian Blaga” University of Medicine, 550024 Sibiu, Romania
| | - Corneliu Toader
- Department of Neurosurgery, “Carol Davila” University of Medicine and Pharmacy, 020021 Bucharest, Romania; (R.-A.C.-B.); (H.P.C.); (B.-G.B.); (D.-I.D.); (A.B.); (A.D.C.); (A.V.C.)
- Department of Vascular Neurosurgery, National Institute of Neurology and Neurovascular Diseases, 020022 Bucharest, Romania
| | - Horia Ples
- Centre for Cognitive Research in Neuropsychiatric Pathology (NeuroPsy-Cog), “Victor Babes” University of Medicine and Pharmacy, 300736 Timisoara, Romania
- Department of Neurosurgery, “Victor Babes” University of Medicine and Pharmacy, 300041 Timisoara, Romania
| | - Razvan-Adrian Covache-Busuioc
- Department of Neurosurgery, “Carol Davila” University of Medicine and Pharmacy, 020021 Bucharest, Romania; (R.-A.C.-B.); (H.P.C.); (B.-G.B.); (D.-I.D.); (A.B.); (A.D.C.); (A.V.C.)
| | - Horia Petre Costin
- Department of Neurosurgery, “Carol Davila” University of Medicine and Pharmacy, 020021 Bucharest, Romania; (R.-A.C.-B.); (H.P.C.); (B.-G.B.); (D.-I.D.); (A.B.); (A.D.C.); (A.V.C.)
| | - Bogdan-Gabriel Bratu
- Department of Neurosurgery, “Carol Davila” University of Medicine and Pharmacy, 020021 Bucharest, Romania; (R.-A.C.-B.); (H.P.C.); (B.-G.B.); (D.-I.D.); (A.B.); (A.D.C.); (A.V.C.)
| | - David-Ioan Dumitrascu
- Department of Neurosurgery, “Carol Davila” University of Medicine and Pharmacy, 020021 Bucharest, Romania; (R.-A.C.-B.); (H.P.C.); (B.-G.B.); (D.-I.D.); (A.B.); (A.D.C.); (A.V.C.)
| | - Andrei Bordeianu
- Department of Neurosurgery, “Carol Davila” University of Medicine and Pharmacy, 020021 Bucharest, Romania; (R.-A.C.-B.); (H.P.C.); (B.-G.B.); (D.-I.D.); (A.B.); (A.D.C.); (A.V.C.)
| | - Antonio Daniel Corlatescu
- Department of Neurosurgery, “Carol Davila” University of Medicine and Pharmacy, 020021 Bucharest, Romania; (R.-A.C.-B.); (H.P.C.); (B.-G.B.); (D.-I.D.); (A.B.); (A.D.C.); (A.V.C.)
| | - Alexandru Vlad Ciurea
- Department of Neurosurgery, “Carol Davila” University of Medicine and Pharmacy, 020021 Bucharest, Romania; (R.-A.C.-B.); (H.P.C.); (B.-G.B.); (D.-I.D.); (A.B.); (A.D.C.); (A.V.C.)
- Neurosurgery Department, Sanador Clinical Hospital, 010991 Bucharest, Romania
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Hadianfar A, Sasannezhad P, Nazar E, Yousefi R, Shakeri M, Jafari Z, Hashtarkhani S. Predictors of in-hospital mortality among patients with symptoms of stroke, Mashhad, Iran: an application of auto-logistic regression model. Arch Public Health 2023; 81:73. [PMID: 37106443 PMCID: PMC10134659 DOI: 10.1186/s13690-023-01084-5] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/21/2022] [Accepted: 04/07/2023] [Indexed: 04/29/2023] Open
Abstract
BACKGROUND Stroke is the second leading cause of death in adults worldwide. There are remarkable geographical variations in the accessibility to emergency medical services (EMS). Moreover, transport delays have been documented to affect stroke outcomes. This study aimed to examine the spatial variations in in-hospital mortality among patients with symptoms of stroke transferred by EMS, and determine its related factors using the auto-logistic regression model. METHODS In this historical cohort study, we included patients with symptoms of stroke transferred to Ghaem Hospital of Mashhad, as the referral center for stroke patients, from April 2018 to March 2019. The auto-logistic regression model was applied to examine the possible geographical variations of in-hospital mortality and its related factors. All analysis was performed using the Statistical Package for the Social Sciences (SPSS, v. 16) and R 4.0.0 software at the significance level of 0.05. RESULTS In this study, a total of 1,170 patients with stroke symptoms were included. The overall mortality rate in the hospital was 14.2% and there was an uneven geographical distribution. The results of auto-logistic regression model showed that in-hospital stroke mortality was associated with age (OR = 1.03, 95% CI: 1.01-1.04), accessibility rate of ambulance vehicle (OR = 0.97, 95% CI: 0.94-0.99), final stroke diagnosis (OR = 1.60, 95% CI: 1.07-2.39), triage level (OR = 2.11, 95% CI: 1.31-3.54), and length of stay (LOS) in hospital (OR = 1.02, 95% CI: 1.01-1.04). CONCLUSION Our results showed considerable geographical variations in the odds of in-hospital stroke mortality in Mashhad neighborhoods. Also, the age- and sex-adjusted results highlighted the direct association between such variables as accessibility rate of an ambulance, screening time, and LOS in hospital with in-hospital stroke mortality. Thus, the prognosis of in-hospital stroke mortality could be improved by reducing delay time and increasing the EMS access rate.
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Affiliation(s)
- Ali Hadianfar
- Student Research Committee, Mashhad University of Medical Sciences (MUMS), Mashhad, Iran
| | - Payam Sasannezhad
- Department of Neurology, Mashhad University of Medical Sciences (MUMS), Mashhad, Iran
| | - Eisa Nazar
- International UNESCO Center for Health-Related Basic Sciences and Human Nutrition, Mashhad University of Medical Sciences (MUMS), Mashhad, Iran
- Psychiatry and Behavioral Sciences Research Center, Addiction Institute, Mazandaran University of Medical Sciences, Mazandaran, Iran
| | - Razieh Yousefi
- Student Research Committee, Mashhad University of Medical Sciences (MUMS), Mashhad, Iran
| | - Mohammadtaghi Shakeri
- Department of Biostatistics, School of Public Health, Social Determinants of Health Research Center, Mashhad University of Medical Sciences (MUMS), Mashhad, Iran.
| | - Zahra Jafari
- Clinical Research Development Unit, Ghaem Hospital, Mashhad University of Medical Sciences (MUMS), Mashhad, Iran
| | - Soheil Hashtarkhani
- Center for Biomedical Informatics, Department of Pediatrics, University of Tennessee Health Science Center, Memphis, USA
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Yang H, Wu Z, Huang X, Zhang M, Fu Y, Wu Y, Liu L, Li Y, Wang HHX. In-Hospital Emergency Treatment Delay Among Chinese Patients with Acute Ischaemic Stroke: Relation to Hospital Arrivals and Implications for Triage Pathways. Int J Gen Med 2023; 16:57-68. [PMID: 36636715 PMCID: PMC9829982 DOI: 10.2147/ijgm.s371687] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/03/2022] [Accepted: 11/18/2022] [Indexed: 01/05/2023] Open
Abstract
Introduction Timely access to emergency treatment during in-hospital care phase is critical for managing the onset of acute ischaemic stroke (AIS), particularly in developing countries. We aimed to explore in-hospital emergency treatment delay and the relation of door-to-needle (DTN) time to ambulance arrivals vs walk-in arrivals. Methods Data were collected from 1276 Chinese AIS patients admitted to a general, tertiary-level hospital for intravenous thrombolysis. Information on patients' characteristics and time taken during in-hospital emergency treatment was retrieved from the hospital registry data and medical records. Ambulance arrival was defined as being transported by emergency ambulance services, while walk-in arrival was defined as arriving at hospital by regular vehicle. In-hospital emergency treatment delay occurred when the DTN time exceeded 60 minutes. We performed multivariable logistic regression analysis to explore the association between hospital arrivals (by ambulance vs by walk-in) and treatment delay after adjustment for age, sex, education, marital status, residence, medical insurance, number of symptoms, clinical severity and survival outcome. Results Over half (53.76%) of patients aged over 60 years. Around one-fifth (20.61%) of patients admitted to hospital through emergency ambulance services, while their counterparts arrived by regular vehicle. Overall, the median time taken from the hospital door to treatment initiation was 86.0 minutes. Patients arrived by ambulance (adjusted odds ratio [aOR] = 1.744, 95% confidence interval [CI] = 1.185-2.566, p = 0.005), had higher socio-economic status (aOR = 1.821, 95% CI = 1.251-2.650; p = 0.002), or paid out-of-pocket (aOR = 2.323, 95% CI = 1.764-3.060; p < 0.001) had an increased likelihood of in-hospital emergency treatment delays. Conclusion In-hospital emergency treatment delay is common in China, and occurs throughout the entire emergency treatment journey. Having a triage pathway involving hospital arrival by ambulance seems to be more likely to experience in-hospital emergency treatment delay. Further efforts to improve triage pathways may require qualitative evidence on provider- and institutional-level factors associated with in-hospital emergency treatment delay.
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Affiliation(s)
- Huajie Yang
- School of Health Technology, Guangdong Open University (Guangdong Polytechnic Institute), Guangzhou, People’s Republic of China
| | - Zhuohua Wu
- The First Affiliated Hospital of Guangzhou Medical University, Guangzhou, People’s Republic of China
| | - Xiang Huang
- Sanxiang Community Health Service Centre of Zhongshan, Zhongshan, People’s Republic of China,Faculty of Medicine, Macau University of Science and Technology, Macau SAR, People’s Republic of China
| | - Man Zhang
- Sanxiang Community Health Service Centre of Zhongshan, Zhongshan, People’s Republic of China
| | - Yu Fu
- School of Public Health, Sun Yat-Sen University, Guangzhou, People’s Republic of China
| | - Yijuan Wu
- The First Affiliated Hospital of Guangzhou Medical University, Guangzhou, People’s Republic of China
| | - Lei Liu
- The First Affiliated Hospital of Guangzhou Medical University, Guangzhou, People’s Republic of China
| | - Yiheng Li
- The First Affiliated Hospital of Guangzhou Medical University, Guangzhou, People’s Republic of China,Yiheng Li, The First Affiliated Hospital of Guangzhou Medical University, Guangzhou, 510120, People’s Republic of China, Tel +86 20 83062721, Email
| | - Harry H X Wang
- School of Public Health, Sun Yat-Sen University, Guangzhou, People’s Republic of China,Correspondence: Harry HX Wang, School of Public Health, Sun Yat-Sen University, Guangzhou, 510080, People’s Republic of China, Tel +86 20 87330672, Email
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Chari SV, Cui ER, Fehl HE, Fernandez AR, Brice JH, Patel MD. Community socioeconomic and urban-rural differences in emergency medical services times for suspected stroke in North Carolina. Am J Emerg Med 2023; 63:120-126. [PMID: 36370608 PMCID: PMC10425758 DOI: 10.1016/j.ajem.2022.10.039] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/05/2022] [Revised: 10/19/2022] [Accepted: 10/23/2022] [Indexed: 11/06/2022] Open
Abstract
OBJECTIVE Our objectives were to describe time intervals of EMS encounters for suspected stroke patients in North Carolina (NC) and evaluate differences in EMS time intervals by community socioeconomic status (SES) and rurality. METHODS This cross-sectional study used statewide data on EMS encounters of suspected stroke in NC in 2019. Eligible patients were adults requiring EMS transport to a hospital following a 9-1-1 call for stroke-like symptoms. Incident street addresses were geocoded to census tracts and linked to American Community Survey SES data and to rural-urban commuting area (RUCA) codes. Community SES was defined as high, medium, or low based on tertiles of an SES index. Urban, suburban, and rural tracts were defined by RUCA codes 1, 2-6, and 7-10, respectively. Multivariable quantile regression was used to estimate how the median and 90th percentile of EMS time intervals varied by community SES and rurality, adjusting for each other; patient age, gender, and race/ethnicity; and incident characteristics. RESULTS We identified 17,117 eligible EMS encounters of suspected stroke from 2028 census tracts. The population was 65% 65+ years old; 55% female; and 69% Non-Hispanic White. Median response, scene, and transport times were 8 (interquartile range, IQR 6-11) min, 16 (IQR 12-20) min, and 14 (IQR 9-22) minutes, respectively. In quantile regression adjusted for patient demographics, minimal differences were observed for median response and scene times by community SES and rurality. The largest median differences were observed for transport times in rural (6.7 min, 95% CI 5.8, 7.6) and suburban (4.7 min, 95% CI 4.2, 5.1) tracts compared to urban tracts. Adjusted rural-urban differences in 90th percentile transport times were substantially greater (16.0 min, 95% CI 14.5, 17.5). Low SES was modesty associated with shorter median (-3.3 min, 95% CI -3.8, -2.9) and 90th percentile (-3.0 min, 95% CI -4.0, -2.0) transport times compared to high SES tracts. CONCLUSIONS While community-level factors were not strongly associated with EMS response and scene times for stroke, transport times were significantly longer rural tracts and modestly shorter in low SES tracts, accounting for patient demographics. Further research is needed on the role of community socioeconomic deprivation and rurality in contributing to delays in prehospital stroke care.
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Affiliation(s)
- Srihari V Chari
- Department of Emergency Medicine, University of North Carolina School of Medicine, Chapel Hill, NC, USA
| | - Eric R Cui
- Department of Emergency Medicine, University of North Carolina School of Medicine, Chapel Hill, NC, USA
| | - Haylie E Fehl
- Department of Emergency Medicine, University of North Carolina School of Medicine, Chapel Hill, NC, USA
| | - Antonio R Fernandez
- Department of Emergency Medicine, University of North Carolina School of Medicine, Chapel Hill, NC, USA; ESO, Austin, TX, USA
| | - Jane H Brice
- Department of Emergency Medicine, University of North Carolina School of Medicine, Chapel Hill, NC, USA
| | - Mehul D Patel
- Department of Emergency Medicine, University of North Carolina School of Medicine, Chapel Hill, NC, USA.
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Prehospital Time Interval for Urban and Rural Emergency Medical Services: A Systematic Literature Review. Healthcare (Basel) 2022; 10:healthcare10122391. [PMID: 36553915 PMCID: PMC9778378 DOI: 10.3390/healthcare10122391] [Citation(s) in RCA: 4] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/29/2022] [Revised: 11/18/2022] [Accepted: 11/19/2022] [Indexed: 12/05/2022] Open
Abstract
The aim of this study was to discuss the differences in pre-hospital time intervals between rural and urban communities regarding emergency medical services (EMS). A systematic search was conducted through various relevant databases, together with a manual search to find relevant articles that compared rural and urban communities in terms of response time, on-scene time, and transport time. A total of 37 articles were ultimately included in this review. The sample sizes of the included studies was also remarkably variable, ranging between 137 and 239,464,121. Twenty-nine (78.4%) reported a difference in response time between rural and urban areas. Among these studies, the reported response times for patients were remarkably variable. However, most of them (number (n) = 27, 93.1%) indicate that response times are significantly longer in rural areas than in urban areas. Regarding transport time, 14 studies (37.8%) compared this outcome between rural and urban populations. All of these studies indicate the superiority of EMS in urban over rural communities. In another context, 10 studies (27%) reported on-scene time. Most of these studies (n = 8, 80%) reported that the mean on-scene time for their populations is significantly longer in rural areas than in urban areas. On the other hand, two studies (5.4%) reported that on-scene time is similar in urban and rural communities. Finally, only eight studies (21.6%) reported pre-hospital times for rural and urban populations. All studies reported a significantly shorter pre-hospital time in urban communities compared to rural communities. Conclusions: Even with the recently added data, short pre-hospital time intervals are still superior in urban over rural communities.
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Farcas AM, Joiner AP, Rudman JS, Ramesh K, Torres G, Crowe RP, Curtis T, Tripp R, Bowers K, von Isenburg M, Logan R, Coaxum L, Salazar G, Lozano M, Page D, Haamid A. Disparities in Emergency Medical Services Care Delivery in the United States: A Scoping Review. PREHOSP EMERG CARE 2022; 27:1058-1071. [PMID: 36369725 DOI: 10.1080/10903127.2022.2142344] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/18/2022] [Accepted: 10/25/2022] [Indexed: 11/14/2022]
Abstract
BACKGROUND Emergency medical services (EMS) often serve as the first medical contact for ill or injured patients, representing a critical access point to the health care delivery continuum. While a growing body of literature suggests inequities in care within hospitals and emergency departments, limited research has comprehensively explored disparities related to patient demographic characteristics in prehospital care. OBJECTIVE We aimed to summarize the existing literature on disparities in prehospital care delivery for patients identifying as members of an underrepresented race, ethnicity, sex, gender, or sexual orientation group. METHODS We conducted a scoping review of peer-reviewed and non-peer-reviewed (gray) literature. We searched PubMed, CINAHL, Web of Science, Proquest Dissertations, Scopus, Google, and professional websites for studies set in the U.S. between 1960 and 2021. Each abstract and full-text article was screened by two reviewers. Studies written in English that addressed the underrepresented groups of interest and investigated EMS-related encounters were included. Studies were excluded if a disparity was noted incidentally but was not a stated objective or discussed. Data extraction was conducted using a standardized electronic form. Results were summarized qualitatively using an inductive approach. RESULTS One hundred forty-five full-text articles from the peer-reviewed literature and two articles from the gray literature met inclusion criteria: 25 studies investigated sex/gender, 61 studies investigated race/ethnicity, and 58 studies investigated both. One study investigated sexual orientation. The most common health conditions evaluated were out-of-hospital cardiac arrest (n = 50), acute coronary syndrome (n = 36), and stroke (n = 31). The phases of EMS care investigated included access (n = 55), pre-arrival care (n = 46), diagnosis/treatment (n = 42), and response/transport (n = 40), with several studies covering multiple phases. Disparities were identified related to all phases of EMS care for underrepresented groups, including symptom recognition, pain management, and stroke identification. The gray literature identified public perceptions of EMS clinicians' cultural competency and the ability to appropriately care for transgender patients in the prehospital setting. CONCLUSIONS Existing research highlights health disparities in EMS care delivery throughout multiple health outcomes and phases of EMS care. Future research is needed to identify structured mechanisms to eliminate disparities, address clinician bias, and provide high-quality equitable care for all patient populations.
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Affiliation(s)
- Andra M Farcas
- Department of Emergency Medicine, University of Colorado School of Medicine, Aurora, Colorado
| | - Anjni P Joiner
- Department of Emergency Medicine, Duke University School of Medicine, Durham, North Carolina
| | - Jordan S Rudman
- Harvard Affiliated Emergency Medicine Residency, Beth Israel Deaconess Medical Center, Boston, Massachusetts
| | - Karthik Ramesh
- School of Medicine, University of California San Diego, San Diego, California
| | | | | | | | - Rickquel Tripp
- Department of Emergency Medicine, University of Pittsburgh Medical Center, Pittsburgh, Pennsylvania
| | - Karen Bowers
- Atlanta Fire Rescue Department; Department of Emergency Medicine, University of Tennessee-Chattanooga, Chattanooga, Tennessee
| | - Megan von Isenburg
- Duke University Medical Center Library, Duke University, Durham, North Carolina
| | - Robert Logan
- San Diego Fire - Rescue Department, San Diego, California
| | - Lauren Coaxum
- Department of Emergency Medicine, Duke University School of Medicine, Durham, North Carolina
| | | | - Michael Lozano
- Division of Emergency Medicine, Morsani College of Medicine, University of South Florida, Tampa, Florida
| | - David Page
- Department of Emergency Medicine, David Geffen School of Medicine at UCLA, Los Angeles, California
| | - Ameera Haamid
- Section of Emergency Medicine, University of Chicago School of Medicine, Chicago, Illinois
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10
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Kuang J, Zhu X, Yang L, Gao Z, Wei X, Zhou K, Xu M. Factors influencing alertness to premonitory symptoms in stroke patients with pre-hospital delay. Public Health Nurs 2022; 39:1204-1212. [PMID: 35714655 DOI: 10.1111/phn.13108] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/18/2021] [Revised: 05/01/2022] [Accepted: 05/26/2022] [Indexed: 11/29/2022]
Abstract
OBJECTIVE The purpose was to explore the alertness of premonitory symptoms in stroke patients with prehospital delay, and to analyze the influencing factors. DESIGN AND SAMPLE A cross-sectional study using the convenience sampling method was conducted in the neurology department of a general hospital between November 2018 and July 2019. A total of 352 stroke patients were participated in the survey. MEASURES A hierarchical multiple regression was performed to analyze the factors related to the alertness of premonitory symptoms (0-9 scores) in stroke patients with prehospital delay. RESULTS The alertness score was 6.53 ± 2.377. The lowest score of 0.55 ± 0.498 was for "Continuous yawning occurs continuously despite no tiredness or lack of sleep is okay, and need not be treated." The hierarchical regression results revealed that symptom onset, symptom change before admission, knowledge, social support were the influencing factors delaying the alertness of premonitory symptoms. Knowledge and support from friends could improve the alertness, while support from family and other support had a notable negative impact. CONCLUSIONS Stroke patients need to be more alert toward premonitory symptoms. This alertness is related to stroke knowledge and social support. Nurses should formulate interventions and advise stroke patients to improve their stroke knowledge and expand their social network.
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Affiliation(s)
- Jinke Kuang
- School of Nursing, Qingdao University, Qingdao, Shandong Province, China
| | - Xuemei Zhu
- School of Nursing, Harbin Medical University/The 2nd Affiliated Hospital of Harbin Medical University, Harbin, Heilongjiang, China
| | - Li Yang
- School of Nursing, Qingdao University, Qingdao, Shandong Province, China
| | - Zihan Gao
- School of Nursing, Qingdao University, Qingdao, Shandong Province, China
| | - Xiao Wei
- School of Nursing, Qingdao University, Qingdao, Shandong Province, China
| | - Kexin Zhou
- School of Nursing, Qingdao University, Qingdao, Shandong Province, China
| | - Mengfan Xu
- School of Nursing, Qingdao University, Qingdao, Shandong Province, China
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11
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Amani F, Fattahzadeh-Ardalani G, Sharghi A, Jafarizadeh R. Using Multiple Logistic Regression to Determine Factors Affecting Delaying Hospital Arrival of Patients with Acute Ischemic Stroke. Neurol India 2022; 70:1548-1553. [PMID: 36076657 DOI: 10.4103/0028-3886.355102] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/04/2022]
Abstract
Background Early treatment of ischemic stroke patients who arrive at the hospital ≤4.5 hours after the onset of symptoms with recombinant tissue plasminogen activator is more beneficial and very important. Objective This study is aimed to investigate the factors delaying the hospital arrival of patients with acute ischemic stroke by using multiple logistic regression analysis. Methods and Materials This descriptive cross-sectional study was done on patients diagnosed with acute ischemic stroke who were referred to Ardabil city Training and Research hospital at 2018. All patients and/or patient relatives were interviewed and data were collected through a checklist including demographic and clinical data of patients to explore the involved factors delaying hospital arrival of patients and then analyzed using multiple logistic regression analysis. Results Of all included patients, only 25.3% arrived at the hospital in ≤ 4.5 hours. By using multivariate logistic regression analysis, living in cities (P = 0.007), cigarette consumption (P = 0.032), having valvular heart disease (P = 0.008), and gender (P = 0.049) were factors associated with an early arrival to the hospital. Conclusions Results showed that most of the patients had a considerable delay in arriving at the hospital in ≤ 4.5 hours. Thus, providing health promotion strategies to improve society awareness of early symptoms of stroke, training of local physicians about the importance of early arrival of stroke patients, and more extended ambulance services in all cities and rural areas are necessary for better management of acute stroke patients in this area.
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Affiliation(s)
- Firouz Amani
- Department of Community Medicine, Faculty of Medicine, Ardabil University of Medical Science, Ardabil, Iran
| | | | - Afshan Sharghi
- Department of Community Medicine, Faculty of Medicine, Ardabil University of Medical Science, Ardabil, Iran
| | - Raana Jafarizadeh
- Department of Medicine, Ardabil Branch, Islamic Azad University, Ardabil, Iran
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12
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Frydenlund J, Mackenhauer J, Christensen EF, Christensen HC, Væggemose U, Steinmetz J, Johnsen SP. Socioeconomic Disparities in Prehospital Emergency Care in a Danish Tax-Financed Healthcare System: Nationwide Cohort Study. Clin Epidemiol 2022; 14:555-565. [PMID: 35509522 PMCID: PMC9058017 DOI: 10.2147/clep.s358801] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/24/2022] [Accepted: 03/13/2022] [Indexed: 11/23/2022] Open
Abstract
Background Differences related to socioeconomic status (SES) in use of prehospital emergency medical services (EMS) have been reported. However, detailed data on potential disparities in the quality of the EMS according to SES are lacking. Methods A nationwide cohort study of medical emergency calls made to the Danish emergency number 1-1-2 in the period 2016–2017. To measure quality of care, performance indicators from the Danish Quality Registry for Prehospital Emergency Medical Services were used. SES was based on income, education and adherence to workforce. Poisson regression was used to measure relative risk (RR). Results We included 388,378 medical 1-1-2 calls, of which 261,771 were unique individuals; 42% of the calls concerned patients with low education, 5% concerned patients living in relative poverty and 23% concerned patients receiving social subsidy. There were no significant differences between the SES regarding time span for arrival of first EMS units. However, patients receiving social subsidy and retired people were more likely to be released at scene and to call again within 24 hours: Adjusted RRs were 2.79 [2.20; 3.54] and 2.08 [1.58; 2.75], respectively, compared with patients having a job. In addition, patients receiving social subsidy and retired people were more likely to call again within 24 hours after receiving telephone advice only: Adjusted RRs 2.35 [1.95; 2.82] and 1.88 [1.51; 2.35], respectively compared with patients having a job. Adjusted RRs for unplanned hospital contact after being treated and released at scene were higher for patients receiving social subsidy and retired people, respectively, relative to patients having a job. Conclusion Patients with low SES were significantly more likely to contact the hospital or EMS again after their first call or after treatment and release at scene compared with patients with high SES. This indicates that callers with low SES did not receive the appropriate help.
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Affiliation(s)
- Juliane Frydenlund
- Department of Clinical Medicine, Aalborg University, Aalborg East, 9220, Denmark
- Correspondence: Juliane Frydenlund, Department of Clinical Medicine, Aalborg University, Fredrik Bajers Vej 5, Aalborg East, 9220, Denmark, Tel +45 24671465, Email
| | - Julie Mackenhauer
- Department of Clinical Medicine, Aalborg University, Aalborg East, 9220, Denmark
| | - Erika F Christensen
- Department of Clinical Medicine, Aalborg University, Aalborg, 9000, Denmark
- Clinic for Internal and Emergency Medicine, Aalborg University Hospital, Aalborg, 9000, Denmark
- Emergency Medical Services, North Denmark Region, Aalborg, 9000, Denmark
| | | | - Ulla Væggemose
- Department of Research & Development, Prehospital Emergency Medical Services, Central Denmark Region, Aarhus, Denmark
- Department of Clinical Medicine, Aarhus University, Aarhus, Denmark
| | - Jacob Steinmetz
- Department of Anaesthesia, Centre of Head and Orthopaedics, Rigshospitalet, Copenhagen, Denmark
- Danish Air Ambulance, Aarhus, Denmark
| | - Søren Paaske Johnsen
- Department of Clinical Medicine, Aalborg University, Aalborg East, 9220, Denmark
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13
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Abbas AY, Odom EC, Nwaise I. Association between dispatch complaint and critical prehospital time intervals in suspected stroke 911 activations in the National Emergency Medical Services Information System, 2012-2016. J Stroke Cerebrovasc Dis 2021; 31:106228. [PMID: 34959039 DOI: 10.1016/j.jstrokecerebrovasdis.2021.106228] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/21/2021] [Accepted: 11/13/2021] [Indexed: 01/01/2023] Open
Abstract
OBJECTIVE Emergency Medical Services can help improve stroke outcomes by recognizing stroke symptoms, establishing response priority for 911 calls, and minimizing prehospital delays. This study examines 911 stroke events and evaluates associations between events dispatched as stroke and critical EMS time intervals. MATERIALS AND METHODS Data from the National Emergency Medical Services Information System, 2012 to 2016, were analyzed. Activations from 911 calls with a primary or secondary provider impression of stroke were included for adult patients transported to a hospital destination. Three prehospital time intervals were evaluated: (1) response time (RT) ≤8 min, (2) on-scene time (OST) ≤15 min, and (3) transport time (TT) ≤12 min. Associations between stroke dispatch complaint and prehospital time intervals were assessed using multivariate regression to estimate adjusted risk ratios (ARR) and 95% confidence intervals (CIs). RESULTS Approximately 37% of stroke dispatch complaints were identified by EMS as a suspected stroke. Compared to stroke events without a stroke dispatch complaint, median OST was shorter for events with a stroke dispatch (16 min vs. 14 min, respectively). In adjusted analyses, events dispatched as stroke were more likely to meet the EMS time benchmark for OST ≤15 min (OST, 1.20 [1.20-1.21]), but not RT or TT (RT, [1.00-1.01]; TT, 0.95 [0.94-0.95]). CONCLUSIONS Our results indicate that dispatcher recognition of stroke symptoms reduces the time spent on-scene by EMS personnel. These findings can inform future EMS stroke education and quality improvement efforts to emphasize dispatcher recognition of stroke signs and symptoms, as EMS dispatchers play a crucial role in optimizing the prehospital response.
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Affiliation(s)
- Amena Y Abbas
- Division for Heart Disease and Stroke Prevention, Oak Ridge Institute for Science and Education, National Center for Chronic Disease Prevention and Health Promotion, Centers for Disease Control and Prevention (CDC), United States.
| | - Erika C Odom
- Division for Heart Disease and Stroke Prevention, National Center for Chronic Disease Prevention and Health Promotion, Centers for Disease Control and Prevention (CDC), United States
| | - Isaac Nwaise
- Division for Heart Disease and Stroke Prevention, National Center for Chronic Disease Prevention and Health Promotion, Centers for Disease Control and Prevention (CDC), United States
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14
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Hassler J, Ceccato V. Socio-spatial disparities in access to emergency health care-A Scandinavian case study. PLoS One 2021; 16:e0261319. [PMID: 34890436 PMCID: PMC8664193 DOI: 10.1371/journal.pone.0261319] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/07/2021] [Accepted: 11/30/2021] [Indexed: 11/17/2022] Open
Abstract
Having timely access to emergency health care (EHC) depends largely on where you live. In this Scandinavian case study, we investigate how accessibility to EHC varies spatially in order to reveal potential socio-spatial disparities in access. Distinct measures of EHC accessibility were calculated for southern Sweden in a network analysis using a Geographical Information System (GIS) based on data from 2018. An ANOVA test was carried out to investigate how accessibility vary for different measures between urban and rural areas, and negative binominal regression modelling was then carried out to assess potential disparities in accessibility between socioeconomic and demographic groups. Areas with high shares of older adults show poor access to EHC, especially those in the most remote, rural areas. However, rurality alone does not preclude poor access to EHC. Education, income and proximity to ambulance stations were also associated with EHC accessibility, but not always in expected ways. Despite indications of a well-functioning EHC, with most areas served within one hour, socio-spatial disparities in access to EHC were detected both between places and population groups.
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Affiliation(s)
- Jacob Hassler
- Department of Urban Planning and Environment, KTH Royal Institute of Technology, Stockholm, Sweden
| | - Vania Ceccato
- Department of Urban Planning and Environment, KTH Royal Institute of Technology, Stockholm, Sweden
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15
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Characterizing the performance of emergency medical transport time metrics in a residentially segregated community. Am J Emerg Med 2021; 50:111-119. [PMID: 34340164 DOI: 10.1016/j.ajem.2021.07.013] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/01/2021] [Revised: 07/03/2021] [Accepted: 07/05/2021] [Indexed: 11/22/2022] Open
Abstract
OBJECTIVE To derive and characterize the performance of various metrics of emergency transport time in assessing for sociodemographic disparities in the setting of residential segregation. Secondarily to characterize racial disparities in emergency transport time of suspected stroke patients in Austin, Texas. DATA SOURCES We used a novel dataset of 2518 unique entries with detailed spatial and temporal information on all suspected stroke transports conducted by a public emergency medical service in Central Texas between 2010 and 2018. STUDY DESIGN We conducted one-way ANOVA tests with post-hoc pairwise t-tests to assess how mean hospital transport times varied by patient race. We also developed a spatially-independent metric of emergency transport urgency, the ratio of expected duration of self-transport to a hospital and the measured transport time by an ambulance. DATA COLLECTION/EXTRACTION We calculated ambulance arrival and destination times using sequential temporospatial coordinates. We excluded any entries in which patient race was not recorded. We also excluded entries in which ambulances' routes did not pass within 100 m of either the patient's location or the documented hospital destination. PRINCIPAL FINDINGS We found that mean transport time to a hospital was 2.5 min shorter for black patients compared to white patients. However, white patients' transport times to a hospital were found to be, on average, 4.1 min shorter than expected compared to 3.4 min shorter than expected for black patients. One-way ANOVA testing for the spatially-independent index of emergency transport urgency was not statistically significant, indicating that average transport time did not vary significantly across racial groups when accounting for variations in transport distance. CONCLUSIONS Using a novel transport urgency index, we demonstrate that these findings represent race-based variation in spatial distributions rather than racial bias in emergency medical transport. These results highlight the importance of closely examining spatial distributions when utilizing temporospatial data to investigate geographically-dependent research questions.
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16
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Heidet M, Da Cunha T, Brami E, Mermet E, Dru M, Simonnard B, Lecarpentier E, Chollet-Xémard C, Bergeron C, Khalid M, Grunau B, Marty J, Audureau E. EMS Access Constraints And Response Time Delays For Deprived Critically Ill Patients Near Paris, France. Health Aff (Millwood) 2021; 39:1175-1184. [PMID: 32634362 DOI: 10.1377/hlthaff.2019.00842] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/05/2022]
Abstract
Increased emergency medical services (EMS) response times and areas of low socioeconomic status are both associated with poorer outcomes for several time-sensitive medical conditions attended to by medical personnel before a patient is hospitalized. We evaluated the association between EMS response times, area deprivation level, and on-scene access constraints encountered by EMS in a large urban area in France. We conducted a multicenter prospective cohort study of EMS dispatches occurring in the forty-seven cities in a region southeast of Paris. We fit multilevel mixed-effects linear regression models for multivariate assessment of the predictors of EMS response times and then used multivariate logistic regression on outcomes among a subgroup of patients presenting with out-of-hospital cardiac arrest. We found evidence that access constraints were more frequently encountered by EMS in the most deprived areas compared to less deprived ones, and were associated with increased EMS response times until patient contact and with poorer outcomes from cardiac arrest. Strategies to anticipate and overcome access constraints should be implemented to improve outcomes for emergent conditions attended to by prehospital medical teams.
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Affiliation(s)
- Matthieu Heidet
- Matthieu Heidet is a physician with Service d'aide médicale urgente (SAMU) 94 and with Urgences at Hôpital Henri Mondor, Assistance Publique-Hôpitaux de Paris (AP-HP), in Créteil, France
| | - Thierry Da Cunha
- Thierry Da Cunha is a physician with SAMU 94 at Hôpital Henri Mondor, AP-HP
| | - Elise Brami
- Elise Brami is a physician with SAMU 94 at Hôpital Henri Mondor, AP-HP
| | - Eric Mermet
- Eric Mermet is a scientist at the Centre d'analyse et de mathématique sociales (CAMS), at the Centre national de la recherche scientifique (CNRS) and École des hautes études en sciences sociales (EHESS), in Paris, France
| | - Michel Dru
- Michel Dru is a physician with SAMU 94 at Hôpital Henri Mondor, AP-HP
| | - Béatrice Simonnard
- Béatrice Simonnard is a physician with SAMU 94 at Hôpital Henri Mondor, AP-HP
| | - Eric Lecarpentier
- Eric Lecarpentier is a physician with SAMU 94 at Hôpital Henri Mondor, AP-HP
| | | | - Corinne Bergeron
- Corinne Bergeron is a physician with SAMU 94 at Hôpital Henri Mondor, AP-HP
| | - Mohamed Khalid
- Mohamed Khalid is a physician with SAMU 94 at Hôpital Henri Mondor, AP-HP
| | - Brian Grunau
- Brian Grunau is a physician in the Department of Emergency Medicine, University of British Columbia, in Vancouver, British Columbia, Canada
| | - Jean Marty
- Jean Marty is a physician with SAMU 94 at Hôpital Henri Mondor, AP-HP, and head of the research team Analysis of Risks in Complex Health Systems (ARCHeS), Université Paris-Est Créteil (UPEC), in Créteil, France
| | - Etienne Audureau
- Etienne Audureau is a public health physician and scientist with the research team Clinical Epidemiology and Ageing Unit (CEpiA), UPEC
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17
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Asaithambi G, Tong X, Lakshminarayan K, Coleman King SM, George MG, Odom EC. Emergency Medical Services Utilization for Acute Stroke Care: Analysis of the Paul Coverdell National Acute Stroke Program, 2014-2019. PREHOSP EMERG CARE 2021; 26:326-332. [PMID: 33464940 DOI: 10.1080/10903127.2021.1877856] [Citation(s) in RCA: 7] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/22/2022]
Abstract
Objective: Emergency medical service (EMS) transportation after acute stroke is associated with shorter symptom-to-arrival times and more rapid medical attention when compared to patient transportation by private vehicle. Methods: We analyzed data from the Paul Coverdell National Acute Stroke Program from 2014 to 2019 among stroke (ischemic and hemorrhagic) and transient ischemic attack (TIA) patients to examine patterns in EMS utilization. Results: Of 500,829 stroke and TIA patients (mean age 70.9 years, 51.3% women) from 682 participating hospitals during the study period, 60% arrived by EMS. Patients aged 18-64 years vs. ≥65 years (AOR 0.67) were less likely to utilize EMS. Severe stroke patients (AOR 2.29, 95%CI, 2.15-2.44) and hemorrhagic stroke patients vs. ischemic stroke patients (AOR 1.47, 95% CI, 1.43-1.51) were more likely to utilize EMS. Medicare (AOR 1.35, 95% CI, 1.32-1.38) and Medicaid (AOR 1.41, 95% CI, 1.37-1.45) beneficiaries were more likely than privately insured patients to utilize EMS, but no difference was found between no insurance/self-pay patients and privately insured patients on EMS utilization. Overall, there was a decreasing trend in the utilization of EMS (59.6% to 59.3%, p = 0.037). The decreasing trend was identified among ischemic stroke (p < 0.0001) patients but not among TIA (p = 0.89) or hemorrhagic stroke (p = 0.44) patients. There was no observed trend in pre-notification among stroke patients' arrival by EMS across the study period (56.9% to 56.5%, p = 0.99). Conclusions: Strategies to help increase stroke awareness and utilization of EMS among those with symptoms of stroke should be considered in order to help improve stroke outcomes.
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Affiliation(s)
- Ganesh Asaithambi
- Received November 15, 2020 from United Hospital Department of Neurosciences, Allina Health, St. Paul, Minnesota, USA (GA); Division of Heart Disease and Stroke Prevention, Centers for Disease Control and Prevention, Atlanta, Georgia, USA (XT, SMCK, MGG; ECO); Division of Epidemiology and Community Health, University of Minnesota School of Public Health, Minneapolis, Minnesota, USA (KL); Department of Neurology, University of Minnesota Medical School, Minneapolis, Minnesota, USA (KL). Revision received January 14, 2021; accepted for publication January 14, 2021
| | - Xin Tong
- Received November 15, 2020 from United Hospital Department of Neurosciences, Allina Health, St. Paul, Minnesota, USA (GA); Division of Heart Disease and Stroke Prevention, Centers for Disease Control and Prevention, Atlanta, Georgia, USA (XT, SMCK, MGG; ECO); Division of Epidemiology and Community Health, University of Minnesota School of Public Health, Minneapolis, Minnesota, USA (KL); Department of Neurology, University of Minnesota Medical School, Minneapolis, Minnesota, USA (KL). Revision received January 14, 2021; accepted for publication January 14, 2021
| | - Kamakshi Lakshminarayan
- Received November 15, 2020 from United Hospital Department of Neurosciences, Allina Health, St. Paul, Minnesota, USA (GA); Division of Heart Disease and Stroke Prevention, Centers for Disease Control and Prevention, Atlanta, Georgia, USA (XT, SMCK, MGG; ECO); Division of Epidemiology and Community Health, University of Minnesota School of Public Health, Minneapolis, Minnesota, USA (KL); Department of Neurology, University of Minnesota Medical School, Minneapolis, Minnesota, USA (KL). Revision received January 14, 2021; accepted for publication January 14, 2021
| | - Sallyann M Coleman King
- Received November 15, 2020 from United Hospital Department of Neurosciences, Allina Health, St. Paul, Minnesota, USA (GA); Division of Heart Disease and Stroke Prevention, Centers for Disease Control and Prevention, Atlanta, Georgia, USA (XT, SMCK, MGG; ECO); Division of Epidemiology and Community Health, University of Minnesota School of Public Health, Minneapolis, Minnesota, USA (KL); Department of Neurology, University of Minnesota Medical School, Minneapolis, Minnesota, USA (KL). Revision received January 14, 2021; accepted for publication January 14, 2021
| | - Mary G George
- Received November 15, 2020 from United Hospital Department of Neurosciences, Allina Health, St. Paul, Minnesota, USA (GA); Division of Heart Disease and Stroke Prevention, Centers for Disease Control and Prevention, Atlanta, Georgia, USA (XT, SMCK, MGG; ECO); Division of Epidemiology and Community Health, University of Minnesota School of Public Health, Minneapolis, Minnesota, USA (KL); Department of Neurology, University of Minnesota Medical School, Minneapolis, Minnesota, USA (KL). Revision received January 14, 2021; accepted for publication January 14, 2021
| | - Erika C Odom
- Received November 15, 2020 from United Hospital Department of Neurosciences, Allina Health, St. Paul, Minnesota, USA (GA); Division of Heart Disease and Stroke Prevention, Centers for Disease Control and Prevention, Atlanta, Georgia, USA (XT, SMCK, MGG; ECO); Division of Epidemiology and Community Health, University of Minnesota School of Public Health, Minneapolis, Minnesota, USA (KL); Department of Neurology, University of Minnesota Medical School, Minneapolis, Minnesota, USA (KL). Revision received January 14, 2021; accepted for publication January 14, 2021
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Kamel H, Alwell K, Kissela BM, Sucharew HJ, Woo D, Flaherty M, Ferioli S, Demel SL, Moomaw CJ, Walsh K, Mackey J, De Los Rios La Rosa F, Jasne A, Slavin S, Martini S, Adeoye O, Baig T, Chen ML, Levitan EB, Soliman EZ, Kleindorfer DO. Racial Differences in Atrial Cardiopathy Phenotypes in Patients With Ischemic Stroke. Neurology 2021; 96:e1137-e1144. [PMID: 33239363 PMCID: PMC8055350 DOI: 10.1212/wnl.0000000000011197] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/15/2020] [Accepted: 10/23/2020] [Indexed: 12/17/2022] Open
Abstract
OBJECTIVE To test the hypothesis that thrombogenic atrial cardiopathy may be relevant to stroke-related racial disparities, we compared atrial cardiopathy phenotypes between Black vs White patients with ischemic stroke. METHODS We assessed markers of atrial cardiopathy in the Greater Cincinnati/Northern Kentucky Stroke Study, a study of stroke incidence in a population of 1.3 million. We obtained ECGs and reports of echocardiograms performed during evaluation of stroke during the 2010/2015 study periods. Patients with atrial fibrillation (AF) or flutter (AFL) were excluded. Investigators blinded to patients' characteristics measured P-wave terminal force in ECG lead V1 (PTFV1), a marker of left atrial fibrosis and impaired interatrial conduction, and abstracted left atrial diameter from echocardiogram reports. Linear regression was used to examine the association between race and atrial cardiopathy markers after adjustment for demographics, body mass index, and vascular comorbidities. RESULTS Among 3,426 ischemic stroke cases in Black or White patients without AF/AFL, 2,391 had a left atrial diameter measurement (mean, 3.65 ± 0.70 cm). Black race was associated with smaller left atrial diameter in unadjusted (β coefficient, -0.11; 95% confidence interval [CI], -0.17 to -0.05) and adjusted (β, -0.15; 95% CI, -0.21 to -0.09) models. PTFV1 measurements were available in 3,209 patients (mean, 3,434 ± 2,525 μV*ms). Black race was associated with greater PTFV1 in unadjusted (β, 1.59; 95% CI, 1.21-1.97) and adjusted (β, 1.45; 95% CI, 1.00-1.80) models. CONCLUSIONS We found systematic Black-White racial differences in left atrial structure and pathophysiology in a population-based sample of patients with ischemic stroke. CLASSIFICATION OF EVIDENCE This study provides Class II evidence that atrial cardiopathy phenotypes differ in Black people with acute stroke compared to White people.
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Affiliation(s)
- Hooman Kamel
- From the Clinical and Translational Neuroscience Unit, Feil Family Brain and Mind Research Institute and Department of Neurology (H.K., T.B., M.L.C.), Weill Cornell Medicine, New York, NY; Departments of Neurology and Rehabilitation Medicine (K.A., B.M.K., D.W., M.F., S.F., S.L.D., C.J.M., D.O.K.) and Emergency Medicine (K.W., O.A.), University of Cincinnati; Division of Biostatistics and Epidemiology (H.J.S.), Cincinnati Children's Hospital Medical Center; Department of Pediatrics (H.J.S.), University of Cincinnati College of Medicine, OH; Department of Neurology (J.M.), Indiana University School of Medicine, Indianapolis; Baptist Health Neuroscience Center (F.D.L.R.L.R.), Miami, FL; Department of Neurology (A.J.), Yale University, New Haven, CT; Department of Neurology (S.S.), University of Kansas Medical Center, Kansas City; Michael E. DeBakey VA Medical Center (S.M.), Houston, TX; Department of Epidemiology (E.B.L.), University of Alabama at Birmingham; and Division of Cardiology and Epidemiological Cardiology Research Center, Department of Epidemiology and Prevention, and Department of Internal Medicine-Cardiology (E.Z.S.), Wake Forest School of Medicine, Winston-Salem, NC.
| | - Kathleen Alwell
- From the Clinical and Translational Neuroscience Unit, Feil Family Brain and Mind Research Institute and Department of Neurology (H.K., T.B., M.L.C.), Weill Cornell Medicine, New York, NY; Departments of Neurology and Rehabilitation Medicine (K.A., B.M.K., D.W., M.F., S.F., S.L.D., C.J.M., D.O.K.) and Emergency Medicine (K.W., O.A.), University of Cincinnati; Division of Biostatistics and Epidemiology (H.J.S.), Cincinnati Children's Hospital Medical Center; Department of Pediatrics (H.J.S.), University of Cincinnati College of Medicine, OH; Department of Neurology (J.M.), Indiana University School of Medicine, Indianapolis; Baptist Health Neuroscience Center (F.D.L.R.L.R.), Miami, FL; Department of Neurology (A.J.), Yale University, New Haven, CT; Department of Neurology (S.S.), University of Kansas Medical Center, Kansas City; Michael E. DeBakey VA Medical Center (S.M.), Houston, TX; Department of Epidemiology (E.B.L.), University of Alabama at Birmingham; and Division of Cardiology and Epidemiological Cardiology Research Center, Department of Epidemiology and Prevention, and Department of Internal Medicine-Cardiology (E.Z.S.), Wake Forest School of Medicine, Winston-Salem, NC
| | - Brett M Kissela
- From the Clinical and Translational Neuroscience Unit, Feil Family Brain and Mind Research Institute and Department of Neurology (H.K., T.B., M.L.C.), Weill Cornell Medicine, New York, NY; Departments of Neurology and Rehabilitation Medicine (K.A., B.M.K., D.W., M.F., S.F., S.L.D., C.J.M., D.O.K.) and Emergency Medicine (K.W., O.A.), University of Cincinnati; Division of Biostatistics and Epidemiology (H.J.S.), Cincinnati Children's Hospital Medical Center; Department of Pediatrics (H.J.S.), University of Cincinnati College of Medicine, OH; Department of Neurology (J.M.), Indiana University School of Medicine, Indianapolis; Baptist Health Neuroscience Center (F.D.L.R.L.R.), Miami, FL; Department of Neurology (A.J.), Yale University, New Haven, CT; Department of Neurology (S.S.), University of Kansas Medical Center, Kansas City; Michael E. DeBakey VA Medical Center (S.M.), Houston, TX; Department of Epidemiology (E.B.L.), University of Alabama at Birmingham; and Division of Cardiology and Epidemiological Cardiology Research Center, Department of Epidemiology and Prevention, and Department of Internal Medicine-Cardiology (E.Z.S.), Wake Forest School of Medicine, Winston-Salem, NC
| | - Heidi J Sucharew
- From the Clinical and Translational Neuroscience Unit, Feil Family Brain and Mind Research Institute and Department of Neurology (H.K., T.B., M.L.C.), Weill Cornell Medicine, New York, NY; Departments of Neurology and Rehabilitation Medicine (K.A., B.M.K., D.W., M.F., S.F., S.L.D., C.J.M., D.O.K.) and Emergency Medicine (K.W., O.A.), University of Cincinnati; Division of Biostatistics and Epidemiology (H.J.S.), Cincinnati Children's Hospital Medical Center; Department of Pediatrics (H.J.S.), University of Cincinnati College of Medicine, OH; Department of Neurology (J.M.), Indiana University School of Medicine, Indianapolis; Baptist Health Neuroscience Center (F.D.L.R.L.R.), Miami, FL; Department of Neurology (A.J.), Yale University, New Haven, CT; Department of Neurology (S.S.), University of Kansas Medical Center, Kansas City; Michael E. DeBakey VA Medical Center (S.M.), Houston, TX; Department of Epidemiology (E.B.L.), University of Alabama at Birmingham; and Division of Cardiology and Epidemiological Cardiology Research Center, Department of Epidemiology and Prevention, and Department of Internal Medicine-Cardiology (E.Z.S.), Wake Forest School of Medicine, Winston-Salem, NC
| | - Daniel Woo
- From the Clinical and Translational Neuroscience Unit, Feil Family Brain and Mind Research Institute and Department of Neurology (H.K., T.B., M.L.C.), Weill Cornell Medicine, New York, NY; Departments of Neurology and Rehabilitation Medicine (K.A., B.M.K., D.W., M.F., S.F., S.L.D., C.J.M., D.O.K.) and Emergency Medicine (K.W., O.A.), University of Cincinnati; Division of Biostatistics and Epidemiology (H.J.S.), Cincinnati Children's Hospital Medical Center; Department of Pediatrics (H.J.S.), University of Cincinnati College of Medicine, OH; Department of Neurology (J.M.), Indiana University School of Medicine, Indianapolis; Baptist Health Neuroscience Center (F.D.L.R.L.R.), Miami, FL; Department of Neurology (A.J.), Yale University, New Haven, CT; Department of Neurology (S.S.), University of Kansas Medical Center, Kansas City; Michael E. DeBakey VA Medical Center (S.M.), Houston, TX; Department of Epidemiology (E.B.L.), University of Alabama at Birmingham; and Division of Cardiology and Epidemiological Cardiology Research Center, Department of Epidemiology and Prevention, and Department of Internal Medicine-Cardiology (E.Z.S.), Wake Forest School of Medicine, Winston-Salem, NC
| | - Matthew Flaherty
- From the Clinical and Translational Neuroscience Unit, Feil Family Brain and Mind Research Institute and Department of Neurology (H.K., T.B., M.L.C.), Weill Cornell Medicine, New York, NY; Departments of Neurology and Rehabilitation Medicine (K.A., B.M.K., D.W., M.F., S.F., S.L.D., C.J.M., D.O.K.) and Emergency Medicine (K.W., O.A.), University of Cincinnati; Division of Biostatistics and Epidemiology (H.J.S.), Cincinnati Children's Hospital Medical Center; Department of Pediatrics (H.J.S.), University of Cincinnati College of Medicine, OH; Department of Neurology (J.M.), Indiana University School of Medicine, Indianapolis; Baptist Health Neuroscience Center (F.D.L.R.L.R.), Miami, FL; Department of Neurology (A.J.), Yale University, New Haven, CT; Department of Neurology (S.S.), University of Kansas Medical Center, Kansas City; Michael E. DeBakey VA Medical Center (S.M.), Houston, TX; Department of Epidemiology (E.B.L.), University of Alabama at Birmingham; and Division of Cardiology and Epidemiological Cardiology Research Center, Department of Epidemiology and Prevention, and Department of Internal Medicine-Cardiology (E.Z.S.), Wake Forest School of Medicine, Winston-Salem, NC
| | - Simona Ferioli
- From the Clinical and Translational Neuroscience Unit, Feil Family Brain and Mind Research Institute and Department of Neurology (H.K., T.B., M.L.C.), Weill Cornell Medicine, New York, NY; Departments of Neurology and Rehabilitation Medicine (K.A., B.M.K., D.W., M.F., S.F., S.L.D., C.J.M., D.O.K.) and Emergency Medicine (K.W., O.A.), University of Cincinnati; Division of Biostatistics and Epidemiology (H.J.S.), Cincinnati Children's Hospital Medical Center; Department of Pediatrics (H.J.S.), University of Cincinnati College of Medicine, OH; Department of Neurology (J.M.), Indiana University School of Medicine, Indianapolis; Baptist Health Neuroscience Center (F.D.L.R.L.R.), Miami, FL; Department of Neurology (A.J.), Yale University, New Haven, CT; Department of Neurology (S.S.), University of Kansas Medical Center, Kansas City; Michael E. DeBakey VA Medical Center (S.M.), Houston, TX; Department of Epidemiology (E.B.L.), University of Alabama at Birmingham; and Division of Cardiology and Epidemiological Cardiology Research Center, Department of Epidemiology and Prevention, and Department of Internal Medicine-Cardiology (E.Z.S.), Wake Forest School of Medicine, Winston-Salem, NC
| | - Stacie L Demel
- From the Clinical and Translational Neuroscience Unit, Feil Family Brain and Mind Research Institute and Department of Neurology (H.K., T.B., M.L.C.), Weill Cornell Medicine, New York, NY; Departments of Neurology and Rehabilitation Medicine (K.A., B.M.K., D.W., M.F., S.F., S.L.D., C.J.M., D.O.K.) and Emergency Medicine (K.W., O.A.), University of Cincinnati; Division of Biostatistics and Epidemiology (H.J.S.), Cincinnati Children's Hospital Medical Center; Department of Pediatrics (H.J.S.), University of Cincinnati College of Medicine, OH; Department of Neurology (J.M.), Indiana University School of Medicine, Indianapolis; Baptist Health Neuroscience Center (F.D.L.R.L.R.), Miami, FL; Department of Neurology (A.J.), Yale University, New Haven, CT; Department of Neurology (S.S.), University of Kansas Medical Center, Kansas City; Michael E. DeBakey VA Medical Center (S.M.), Houston, TX; Department of Epidemiology (E.B.L.), University of Alabama at Birmingham; and Division of Cardiology and Epidemiological Cardiology Research Center, Department of Epidemiology and Prevention, and Department of Internal Medicine-Cardiology (E.Z.S.), Wake Forest School of Medicine, Winston-Salem, NC
| | - Charles J Moomaw
- From the Clinical and Translational Neuroscience Unit, Feil Family Brain and Mind Research Institute and Department of Neurology (H.K., T.B., M.L.C.), Weill Cornell Medicine, New York, NY; Departments of Neurology and Rehabilitation Medicine (K.A., B.M.K., D.W., M.F., S.F., S.L.D., C.J.M., D.O.K.) and Emergency Medicine (K.W., O.A.), University of Cincinnati; Division of Biostatistics and Epidemiology (H.J.S.), Cincinnati Children's Hospital Medical Center; Department of Pediatrics (H.J.S.), University of Cincinnati College of Medicine, OH; Department of Neurology (J.M.), Indiana University School of Medicine, Indianapolis; Baptist Health Neuroscience Center (F.D.L.R.L.R.), Miami, FL; Department of Neurology (A.J.), Yale University, New Haven, CT; Department of Neurology (S.S.), University of Kansas Medical Center, Kansas City; Michael E. DeBakey VA Medical Center (S.M.), Houston, TX; Department of Epidemiology (E.B.L.), University of Alabama at Birmingham; and Division of Cardiology and Epidemiological Cardiology Research Center, Department of Epidemiology and Prevention, and Department of Internal Medicine-Cardiology (E.Z.S.), Wake Forest School of Medicine, Winston-Salem, NC
| | - Kyle Walsh
- From the Clinical and Translational Neuroscience Unit, Feil Family Brain and Mind Research Institute and Department of Neurology (H.K., T.B., M.L.C.), Weill Cornell Medicine, New York, NY; Departments of Neurology and Rehabilitation Medicine (K.A., B.M.K., D.W., M.F., S.F., S.L.D., C.J.M., D.O.K.) and Emergency Medicine (K.W., O.A.), University of Cincinnati; Division of Biostatistics and Epidemiology (H.J.S.), Cincinnati Children's Hospital Medical Center; Department of Pediatrics (H.J.S.), University of Cincinnati College of Medicine, OH; Department of Neurology (J.M.), Indiana University School of Medicine, Indianapolis; Baptist Health Neuroscience Center (F.D.L.R.L.R.), Miami, FL; Department of Neurology (A.J.), Yale University, New Haven, CT; Department of Neurology (S.S.), University of Kansas Medical Center, Kansas City; Michael E. DeBakey VA Medical Center (S.M.), Houston, TX; Department of Epidemiology (E.B.L.), University of Alabama at Birmingham; and Division of Cardiology and Epidemiological Cardiology Research Center, Department of Epidemiology and Prevention, and Department of Internal Medicine-Cardiology (E.Z.S.), Wake Forest School of Medicine, Winston-Salem, NC
| | - Jason Mackey
- From the Clinical and Translational Neuroscience Unit, Feil Family Brain and Mind Research Institute and Department of Neurology (H.K., T.B., M.L.C.), Weill Cornell Medicine, New York, NY; Departments of Neurology and Rehabilitation Medicine (K.A., B.M.K., D.W., M.F., S.F., S.L.D., C.J.M., D.O.K.) and Emergency Medicine (K.W., O.A.), University of Cincinnati; Division of Biostatistics and Epidemiology (H.J.S.), Cincinnati Children's Hospital Medical Center; Department of Pediatrics (H.J.S.), University of Cincinnati College of Medicine, OH; Department of Neurology (J.M.), Indiana University School of Medicine, Indianapolis; Baptist Health Neuroscience Center (F.D.L.R.L.R.), Miami, FL; Department of Neurology (A.J.), Yale University, New Haven, CT; Department of Neurology (S.S.), University of Kansas Medical Center, Kansas City; Michael E. DeBakey VA Medical Center (S.M.), Houston, TX; Department of Epidemiology (E.B.L.), University of Alabama at Birmingham; and Division of Cardiology and Epidemiological Cardiology Research Center, Department of Epidemiology and Prevention, and Department of Internal Medicine-Cardiology (E.Z.S.), Wake Forest School of Medicine, Winston-Salem, NC
| | - Felipe De Los Rios La Rosa
- From the Clinical and Translational Neuroscience Unit, Feil Family Brain and Mind Research Institute and Department of Neurology (H.K., T.B., M.L.C.), Weill Cornell Medicine, New York, NY; Departments of Neurology and Rehabilitation Medicine (K.A., B.M.K., D.W., M.F., S.F., S.L.D., C.J.M., D.O.K.) and Emergency Medicine (K.W., O.A.), University of Cincinnati; Division of Biostatistics and Epidemiology (H.J.S.), Cincinnati Children's Hospital Medical Center; Department of Pediatrics (H.J.S.), University of Cincinnati College of Medicine, OH; Department of Neurology (J.M.), Indiana University School of Medicine, Indianapolis; Baptist Health Neuroscience Center (F.D.L.R.L.R.), Miami, FL; Department of Neurology (A.J.), Yale University, New Haven, CT; Department of Neurology (S.S.), University of Kansas Medical Center, Kansas City; Michael E. DeBakey VA Medical Center (S.M.), Houston, TX; Department of Epidemiology (E.B.L.), University of Alabama at Birmingham; and Division of Cardiology and Epidemiological Cardiology Research Center, Department of Epidemiology and Prevention, and Department of Internal Medicine-Cardiology (E.Z.S.), Wake Forest School of Medicine, Winston-Salem, NC
| | - Adam Jasne
- From the Clinical and Translational Neuroscience Unit, Feil Family Brain and Mind Research Institute and Department of Neurology (H.K., T.B., M.L.C.), Weill Cornell Medicine, New York, NY; Departments of Neurology and Rehabilitation Medicine (K.A., B.M.K., D.W., M.F., S.F., S.L.D., C.J.M., D.O.K.) and Emergency Medicine (K.W., O.A.), University of Cincinnati; Division of Biostatistics and Epidemiology (H.J.S.), Cincinnati Children's Hospital Medical Center; Department of Pediatrics (H.J.S.), University of Cincinnati College of Medicine, OH; Department of Neurology (J.M.), Indiana University School of Medicine, Indianapolis; Baptist Health Neuroscience Center (F.D.L.R.L.R.), Miami, FL; Department of Neurology (A.J.), Yale University, New Haven, CT; Department of Neurology (S.S.), University of Kansas Medical Center, Kansas City; Michael E. DeBakey VA Medical Center (S.M.), Houston, TX; Department of Epidemiology (E.B.L.), University of Alabama at Birmingham; and Division of Cardiology and Epidemiological Cardiology Research Center, Department of Epidemiology and Prevention, and Department of Internal Medicine-Cardiology (E.Z.S.), Wake Forest School of Medicine, Winston-Salem, NC
| | - Sabreena Slavin
- From the Clinical and Translational Neuroscience Unit, Feil Family Brain and Mind Research Institute and Department of Neurology (H.K., T.B., M.L.C.), Weill Cornell Medicine, New York, NY; Departments of Neurology and Rehabilitation Medicine (K.A., B.M.K., D.W., M.F., S.F., S.L.D., C.J.M., D.O.K.) and Emergency Medicine (K.W., O.A.), University of Cincinnati; Division of Biostatistics and Epidemiology (H.J.S.), Cincinnati Children's Hospital Medical Center; Department of Pediatrics (H.J.S.), University of Cincinnati College of Medicine, OH; Department of Neurology (J.M.), Indiana University School of Medicine, Indianapolis; Baptist Health Neuroscience Center (F.D.L.R.L.R.), Miami, FL; Department of Neurology (A.J.), Yale University, New Haven, CT; Department of Neurology (S.S.), University of Kansas Medical Center, Kansas City; Michael E. DeBakey VA Medical Center (S.M.), Houston, TX; Department of Epidemiology (E.B.L.), University of Alabama at Birmingham; and Division of Cardiology and Epidemiological Cardiology Research Center, Department of Epidemiology and Prevention, and Department of Internal Medicine-Cardiology (E.Z.S.), Wake Forest School of Medicine, Winston-Salem, NC
| | - Sharyl Martini
- From the Clinical and Translational Neuroscience Unit, Feil Family Brain and Mind Research Institute and Department of Neurology (H.K., T.B., M.L.C.), Weill Cornell Medicine, New York, NY; Departments of Neurology and Rehabilitation Medicine (K.A., B.M.K., D.W., M.F., S.F., S.L.D., C.J.M., D.O.K.) and Emergency Medicine (K.W., O.A.), University of Cincinnati; Division of Biostatistics and Epidemiology (H.J.S.), Cincinnati Children's Hospital Medical Center; Department of Pediatrics (H.J.S.), University of Cincinnati College of Medicine, OH; Department of Neurology (J.M.), Indiana University School of Medicine, Indianapolis; Baptist Health Neuroscience Center (F.D.L.R.L.R.), Miami, FL; Department of Neurology (A.J.), Yale University, New Haven, CT; Department of Neurology (S.S.), University of Kansas Medical Center, Kansas City; Michael E. DeBakey VA Medical Center (S.M.), Houston, TX; Department of Epidemiology (E.B.L.), University of Alabama at Birmingham; and Division of Cardiology and Epidemiological Cardiology Research Center, Department of Epidemiology and Prevention, and Department of Internal Medicine-Cardiology (E.Z.S.), Wake Forest School of Medicine, Winston-Salem, NC
| | - Opeolu Adeoye
- From the Clinical and Translational Neuroscience Unit, Feil Family Brain and Mind Research Institute and Department of Neurology (H.K., T.B., M.L.C.), Weill Cornell Medicine, New York, NY; Departments of Neurology and Rehabilitation Medicine (K.A., B.M.K., D.W., M.F., S.F., S.L.D., C.J.M., D.O.K.) and Emergency Medicine (K.W., O.A.), University of Cincinnati; Division of Biostatistics and Epidemiology (H.J.S.), Cincinnati Children's Hospital Medical Center; Department of Pediatrics (H.J.S.), University of Cincinnati College of Medicine, OH; Department of Neurology (J.M.), Indiana University School of Medicine, Indianapolis; Baptist Health Neuroscience Center (F.D.L.R.L.R.), Miami, FL; Department of Neurology (A.J.), Yale University, New Haven, CT; Department of Neurology (S.S.), University of Kansas Medical Center, Kansas City; Michael E. DeBakey VA Medical Center (S.M.), Houston, TX; Department of Epidemiology (E.B.L.), University of Alabama at Birmingham; and Division of Cardiology and Epidemiological Cardiology Research Center, Department of Epidemiology and Prevention, and Department of Internal Medicine-Cardiology (E.Z.S.), Wake Forest School of Medicine, Winston-Salem, NC
| | - Tehniyat Baig
- From the Clinical and Translational Neuroscience Unit, Feil Family Brain and Mind Research Institute and Department of Neurology (H.K., T.B., M.L.C.), Weill Cornell Medicine, New York, NY; Departments of Neurology and Rehabilitation Medicine (K.A., B.M.K., D.W., M.F., S.F., S.L.D., C.J.M., D.O.K.) and Emergency Medicine (K.W., O.A.), University of Cincinnati; Division of Biostatistics and Epidemiology (H.J.S.), Cincinnati Children's Hospital Medical Center; Department of Pediatrics (H.J.S.), University of Cincinnati College of Medicine, OH; Department of Neurology (J.M.), Indiana University School of Medicine, Indianapolis; Baptist Health Neuroscience Center (F.D.L.R.L.R.), Miami, FL; Department of Neurology (A.J.), Yale University, New Haven, CT; Department of Neurology (S.S.), University of Kansas Medical Center, Kansas City; Michael E. DeBakey VA Medical Center (S.M.), Houston, TX; Department of Epidemiology (E.B.L.), University of Alabama at Birmingham; and Division of Cardiology and Epidemiological Cardiology Research Center, Department of Epidemiology and Prevention, and Department of Internal Medicine-Cardiology (E.Z.S.), Wake Forest School of Medicine, Winston-Salem, NC
| | - Monica L Chen
- From the Clinical and Translational Neuroscience Unit, Feil Family Brain and Mind Research Institute and Department of Neurology (H.K., T.B., M.L.C.), Weill Cornell Medicine, New York, NY; Departments of Neurology and Rehabilitation Medicine (K.A., B.M.K., D.W., M.F., S.F., S.L.D., C.J.M., D.O.K.) and Emergency Medicine (K.W., O.A.), University of Cincinnati; Division of Biostatistics and Epidemiology (H.J.S.), Cincinnati Children's Hospital Medical Center; Department of Pediatrics (H.J.S.), University of Cincinnati College of Medicine, OH; Department of Neurology (J.M.), Indiana University School of Medicine, Indianapolis; Baptist Health Neuroscience Center (F.D.L.R.L.R.), Miami, FL; Department of Neurology (A.J.), Yale University, New Haven, CT; Department of Neurology (S.S.), University of Kansas Medical Center, Kansas City; Michael E. DeBakey VA Medical Center (S.M.), Houston, TX; Department of Epidemiology (E.B.L.), University of Alabama at Birmingham; and Division of Cardiology and Epidemiological Cardiology Research Center, Department of Epidemiology and Prevention, and Department of Internal Medicine-Cardiology (E.Z.S.), Wake Forest School of Medicine, Winston-Salem, NC
| | - Emily B Levitan
- From the Clinical and Translational Neuroscience Unit, Feil Family Brain and Mind Research Institute and Department of Neurology (H.K., T.B., M.L.C.), Weill Cornell Medicine, New York, NY; Departments of Neurology and Rehabilitation Medicine (K.A., B.M.K., D.W., M.F., S.F., S.L.D., C.J.M., D.O.K.) and Emergency Medicine (K.W., O.A.), University of Cincinnati; Division of Biostatistics and Epidemiology (H.J.S.), Cincinnati Children's Hospital Medical Center; Department of Pediatrics (H.J.S.), University of Cincinnati College of Medicine, OH; Department of Neurology (J.M.), Indiana University School of Medicine, Indianapolis; Baptist Health Neuroscience Center (F.D.L.R.L.R.), Miami, FL; Department of Neurology (A.J.), Yale University, New Haven, CT; Department of Neurology (S.S.), University of Kansas Medical Center, Kansas City; Michael E. DeBakey VA Medical Center (S.M.), Houston, TX; Department of Epidemiology (E.B.L.), University of Alabama at Birmingham; and Division of Cardiology and Epidemiological Cardiology Research Center, Department of Epidemiology and Prevention, and Department of Internal Medicine-Cardiology (E.Z.S.), Wake Forest School of Medicine, Winston-Salem, NC
| | - Elsayed Z Soliman
- From the Clinical and Translational Neuroscience Unit, Feil Family Brain and Mind Research Institute and Department of Neurology (H.K., T.B., M.L.C.), Weill Cornell Medicine, New York, NY; Departments of Neurology and Rehabilitation Medicine (K.A., B.M.K., D.W., M.F., S.F., S.L.D., C.J.M., D.O.K.) and Emergency Medicine (K.W., O.A.), University of Cincinnati; Division of Biostatistics and Epidemiology (H.J.S.), Cincinnati Children's Hospital Medical Center; Department of Pediatrics (H.J.S.), University of Cincinnati College of Medicine, OH; Department of Neurology (J.M.), Indiana University School of Medicine, Indianapolis; Baptist Health Neuroscience Center (F.D.L.R.L.R.), Miami, FL; Department of Neurology (A.J.), Yale University, New Haven, CT; Department of Neurology (S.S.), University of Kansas Medical Center, Kansas City; Michael E. DeBakey VA Medical Center (S.M.), Houston, TX; Department of Epidemiology (E.B.L.), University of Alabama at Birmingham; and Division of Cardiology and Epidemiological Cardiology Research Center, Department of Epidemiology and Prevention, and Department of Internal Medicine-Cardiology (E.Z.S.), Wake Forest School of Medicine, Winston-Salem, NC
| | - Dawn O Kleindorfer
- From the Clinical and Translational Neuroscience Unit, Feil Family Brain and Mind Research Institute and Department of Neurology (H.K., T.B., M.L.C.), Weill Cornell Medicine, New York, NY; Departments of Neurology and Rehabilitation Medicine (K.A., B.M.K., D.W., M.F., S.F., S.L.D., C.J.M., D.O.K.) and Emergency Medicine (K.W., O.A.), University of Cincinnati; Division of Biostatistics and Epidemiology (H.J.S.), Cincinnati Children's Hospital Medical Center; Department of Pediatrics (H.J.S.), University of Cincinnati College of Medicine, OH; Department of Neurology (J.M.), Indiana University School of Medicine, Indianapolis; Baptist Health Neuroscience Center (F.D.L.R.L.R.), Miami, FL; Department of Neurology (A.J.), Yale University, New Haven, CT; Department of Neurology (S.S.), University of Kansas Medical Center, Kansas City; Michael E. DeBakey VA Medical Center (S.M.), Houston, TX; Department of Epidemiology (E.B.L.), University of Alabama at Birmingham; and Division of Cardiology and Epidemiological Cardiology Research Center, Department of Epidemiology and Prevention, and Department of Internal Medicine-Cardiology (E.Z.S.), Wake Forest School of Medicine, Winston-Salem, NC
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Khanizade A, Khorasani-Zavareh D, Khodakarim S, Palesh M. Comparison of pre-hospital emergency services time intervals in patients with heart attack in Arak, Iran. J Inj Violence Res 2021; 13:31-38. [PMID: 33470221 PMCID: PMC8142335 DOI: 10.5249/jivr.v13i1.1614] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/26/2020] [Accepted: 12/24/2020] [Indexed: 11/08/2022] Open
Abstract
Background: After cardiac arrest, the possibility of death or irreversible complications will highly increase in the absence of cardiac resuscitation within 4 to 6 minutes. Accordingly, measuring the pre-hospital services time intervals is important for better management of emergency medical services delivery. The purpose of this study then was to investigate pre-hospital time intervals for patients with heart attack in Arak city, based on locations and time variables. Methods: This is a retrospective descriptive cross-sectional study, which was conducted at the Arak Emergency Medical Services (EMS) during 2017-2018. Data were analyzed by SPSS version 13. Results: The total number of heart attack patients registered in Arak emergency medical services was 2,659 of which 51% of patients were males. Six percent of patients were under 25 and about 49 percent were between 46 and 65 years old. The average of activation, response, on-scene, transportation, recovery and total time intervals were 3:30, 7:56, 15:15, 13:34, 11:07, 12:11, and 41:25, respectively. In the city area, the shortest and longest average response time intervals were in spring and winter, respectively. In out of the city area, the shortest average response time interval was in summer and the longest one in autumn. The shortest and the longest average response time intervals in the city area were in June and March, respectively, and in out of the city area, the shortest average response time interval was in June and the longest one in April. Conclusions: The shorter response and delivery time interval compared to the other studies may indicate improvement in the provision of EMS. Special attention should be paid to the facilities and equipment of vehicles during cold seasons to be in the shortest possible time. Also, training and informing the staff more about the code of cardiac patients along with general public education can help improve these intervals.
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Affiliation(s)
- Abed Khanizade
- Department of Health Services Management, Virtual School of Medical Education and Management, Shahid Beheshti University of Medical Sciences, Tehran, Iran
| | - Davoud Khorasani-Zavareh
- Workplace Health Promotion Research Center (WHPRC), Shahid Beheshti University of Medical Sciences, Tehran, Iran
| | | | - Mohammad Palesh
- Department of Health Services Management, Virtual School of Medical Education and Management, Shahid Beheshti University of Medical Sciences, Tehran, Iran.
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Jeong S, Cho SI, Kong SY. Long-Term Effect of Income Level on Mortality after Stroke: A Nationwide Cohort Study in South Korea. INTERNATIONAL JOURNAL OF ENVIRONMENTAL RESEARCH AND PUBLIC HEALTH 2020; 17:ijerph17228348. [PMID: 33187353 PMCID: PMC7697688 DOI: 10.3390/ijerph17228348] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 10/13/2020] [Revised: 11/08/2020] [Accepted: 11/09/2020] [Indexed: 11/16/2022]
Abstract
We investigated whether income level has long-term effects on mortality rate in stroke patients and whether this varies with time after the first stroke event, using the National Health Insurance Service National Sample Cohort data from 2002 to 2015 in South Korea. The study population was new-onset stroke patients ≥18 years of age. Patients were categorized into Category (1) insured employees and Category (2) insured self-employed/Medical Aid beneficiaries. Each category was divided into three and four income level groups, retrospectively. The study population comprised of 11,668 patients. Among the Category 1 patients (n = 7720), the low-income group's post-stroke mortality was 1.15-fold higher than the high-income group. Among the Category 2 patients (n = 3948), the lower income groups had higher post-stroke mortality than the high-income group (middle-income, aOR (adjusted odds ratio) 1.29; low-income, aOR 1.70; Medical Aid beneficiaries, aOR 2.19). In this category, the lower income groups' post-stroke mortality risks compared to the high-income group were highest at 13-36 months after the first stroke event(middle-income, aOR 1.52; low-income, aOR 2.31; Medical Aid beneficiaries, aOR 2.53). Medical Aid beneficiaries had a significantly higher post-stroke mortality risk than the high-income group at all time points.
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Affiliation(s)
- Seungmin Jeong
- Department of Preventive Medicine, Kangwon National University Hospital, Chuncheon-si, Gangwon-do 24289, Korea;
- Department of Public Health Science, Graduate School of Public Health, and Institute of Health and Environment, Seoul National University, Seoul 08826, Korea
| | - Sung-il Cho
- Department of Public Health Science, Graduate School of Public Health, and Institute of Health and Environment, Seoul National University, Seoul 08826, Korea
- Correspondence:
| | - So Yeon Kong
- Strategic Research, Laerdal Medical, 4002 Stavanger, Norway;
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Association between Area-Level Socioeconomic Deprivation and Prehospital Delay in Acute Ischemic Stroke Patients: An Ecological Study. INTERNATIONAL JOURNAL OF ENVIRONMENTAL RESEARCH AND PUBLIC HEALTH 2020; 17:ijerph17207392. [PMID: 33050565 PMCID: PMC7600419 DOI: 10.3390/ijerph17207392] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 09/09/2020] [Revised: 09/29/2020] [Accepted: 10/06/2020] [Indexed: 01/01/2023]
Abstract
We analyzed the associations between area-level socioeconomic status (SES) and prehospital delay in acute ischemic stroke (AIS) patients by degree of urbanization with the use of an ecological framework. The participants were 13,637 patients over 18 years of age who experienced AIS from 2007 to 2012 and were admitted to any of the 29 hospitals in South Korea. Area-level SES was determined using 11 variables from the 2010 Korean census. The primary outcome was a prehospital delay (more than three hours from AIS onset time). Multilevel logistic regression was conducted to define the associations of individual- and area-level SES with prehospital delay after adjusting for confounders, which includes the use of emergency medical services (EMS) and individual SES. After adjusting for covariates, it was found that the area-level SES and urbanization were not associated with prehospital delay and EMS use was beneficial in both urban and rural areas. However, after stratification by urbanization, low area-level SES was significantly associated with a prehospital delay in urban areas (adjusted odds ratio (aOR) 1.24, 95% confidence interval (CI) 1.04–1.47) but not in rural areas (aOR 1.04, 95% CI 0.78–1.38). Therefore, we posit that area-level SES in urban areas might be a significant barrier to improving prehospital delay in AIS patients.
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Nichols L, Stirling C, Stankovich J, Gall S. Time to treatment following an aneurysmal subarachnoid hemorrhage, rural place of residence and inter-hospital transfers. Australas Emerg Care 2020; 23:225-232. [PMID: 32883630 DOI: 10.1016/j.auec.2020.05.004] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/14/2020] [Revised: 04/21/2020] [Accepted: 05/20/2020] [Indexed: 12/11/2022]
Abstract
BACKGROUND Little is known about how transfers influence time to treatment for cases of aneurysmal subarachnoid hemorrhage (aSAH). We examine the effect of geographical location, socioeconomic status and inter-hospital transfer on time to treatment following an aSAH. METHODS A state-wide retrospective cohort study was established from 2010-2014. Time intervals from ictus to treatment were calculated. Linear regression examined associations between transfer status, place of residence and socioeconomic status and log-transformed times to treatment. RESULTS The median (IQR) time to intervention was 13.78 (6.48-20.63) hours. Socioeconomic disadvantage was associated with a 1.52-fold increase in the time to hospital (p<0.05) and a 1.76-fold increase in time to neurosurgical admission (p<0.05). Residing in an outer regional area was associated with a 2.27-fold increase (p<0.05) in time to neurosurgical admission. Inter-hospital transfers were associated with a 6.26-fold increase in time to neurosurgical admission (p<0.05). CONCLUSIONS The time to treatment was negatively influenced by socioeconomic disadvantage; geographical location and inter-hospital transfers. The urgent transfer of individuals with suspected aSAH is undeniably necessary when neurosurgical services are unavailable locally. The timeliness and organisation of transfers should be reviewed to overcome the potential vulnerability to poor outcomes for people from rural and disadvantaged areas.
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Affiliation(s)
| | | | - Jim Stankovich
- Department of Neuroscience, Central Clinical School, Monash University
| | - Seana Gall
- Menzies Institute for Medical Research, University of Tasmania
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Kannan VC, Rasamimanana GN, Novack V, Hassan L, Reynolds TA. The impact of socioeconomic status on emergency department outcome in a low-income country setting: A registry-based analysis. PLoS One 2019; 14:e0223045. [PMID: 31618277 PMCID: PMC6795438 DOI: 10.1371/journal.pone.0223045] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.6] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/26/2018] [Accepted: 09/12/2019] [Indexed: 11/18/2022] Open
Abstract
BACKGROUND The impact of socioeconomic status on health has been established via a broad body of literature, largely from high-income countries. Investigative efforts in low- and middle-income countries have suffered from a lack of reporting standardization required to draw comparisons across countries of varying economic strata. In this study we aimed to evaluate the impact of socioeconomic status on emergency department outcomes in a low-income African country using international data classification systems. METHODS This was a retrospective cohort study was conducted at a tertiary care center in northern Madagascar. Data were abstracted from paper charts into an electronic registry using Integrated Public Use Microdata Series codes for occupation, Nam-Powers-Boyd (NPB) scores for socioeconomic status, and Clinical Classifications Software ICD-9 equivalents for diagnosis. Outcome was dichotomized to the combined disposition of death or transfer directly to operating theater (OT) versus discharge. We used t-tests to compare baseline characteristics between these groups. We used chi-square analysis to test the association between occupational class and diagnosis. Finally, multivariate logistic regression analysis was performed examining the impact of NPB score on death/OT outcome, adjusting for age, gender, diagnosis and occupation. RESULTS 5271 patients were seen during the 21-month study period with a death/OT rate of 9.7%. Older age and male gender were more common in death/OT patients (both p<0.001), and were shown to have positive odds ratios for this outcome in multivariate modeling (p<0.006 and <0.001). Occupational class was found to influence diagnosis for all classes (p<0.001) except Sales and Office. Adjusting for these 3 factors, we found a strong independent association between NPB quartile and death/OT outcome. Relative to the 1st quartile, the odds ratio in the 4th quartile was 2.9 (p = 0.004), the 3rd quartile 1.8 (p = 0.094), and the 2nd quartile 3.1 (p<0.001). CONCLUSION To our knowledge, this is the first Malagasy study describing the relationship between socioeconomic status on emergency care outcomes. We found a stronger effect on health in this setting than in high-income countries, highlighting an important healthcare disparity. By using standardized classification systems we hope this study will serve as a model to facilitate future comparative efforts.
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Affiliation(s)
- Vijay C. Kannan
- Department of Emergency Medicine, Beth Israel Deaconess Medical Center, Boston, MA, United States of America
| | - Giannie N. Rasamimanana
- Emergency and Intensive Care Unit, Centre Hopitalier de Professeur Zagaga, Mahajanga, Madagascar
| | - Victor Novack
- Clinical Research Center, Soroka University Hospital and Faculty of Health Sciences, Ben-Gurion University of the Negev, Beer Sheba, Israel
| | - Lior Hassan
- Clinical Research Center, Soroka University Hospital and Faculty of Health Sciences, Ben-Gurion University of the Negev, Beer Sheba, Israel
| | - Teri A. Reynolds
- Department of Emergency Medicine, University of California, San Francisco, CA, United States of America
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25
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Ader J, Wu J, Fonarow GC, Smith EE, Shah S, Xian Y, Bhatt DL, Schwamm LH, Reeves MJ, Matsouaka RA, Sheth KN. Hospital distance, socioeconomic status, and timely treatment of ischemic stroke. Neurology 2019; 93:e747-e757. [PMID: 31320472 DOI: 10.1212/wnl.0000000000007963] [Citation(s) in RCA: 25] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/31/2018] [Accepted: 03/24/2019] [Indexed: 02/06/2023] Open
Abstract
OBJECTIVE To determine whether lower socioeconomic status (SES) and longer home to hospital driving time are associated with reductions in tissue plasminogen activator (tPA) administration and timeliness of the treatment. METHODS We conducted a retrospective observational study using data from the Get With The Guidelines-Stroke Registry (GWTG-Stroke) between January 2015 and March 2017. The study included 118,683 ischemic stroke patients age ≥18 who were transported by emergency medical services to one of 1,489 US hospitals. We defined each patient's SES based on zip code median household income. We calculated the driving time between each patient's home zip code and the hospital where he or she was treated using the Google Maps Directions Application Programing Interface. The primary outcomes were tPA administration and onset-to-arrival time (OTA). Outcomes were analyzed using hierarchical multivariable logistic regression models. RESULTS SES was not associated with OTA (p = 0.31) or tPA administration (p = 0.47), but was associated with the secondary outcomes of onset-to-treatment time (OTT) (p = 0.0160) and in-hospital mortality (p = 0.0037), with higher SES associated with shorter OTT and lower in-hospital mortality. Driving time was associated with tPA administration (p < 0.001) and OTA (p < 0.0001), with lower odds of tPA (0.83, 0.79-0.88) and longer OTA (1.30, 1.24-1.35) in patients with the longest vs shortest driving time quartiles. Lower SES quintiles were associated with slightly longer driving time quartiles (p = 0.0029), but there was no interaction between the SES and driving time for either OTA (p = 0.1145) or tPA (p = 0.6103). CONCLUSIONS Longer driving times were associated with lower odds of tPA administration and longer OTA; however, SES did not modify these associations.
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Affiliation(s)
- Jeremy Ader
- From the Department of Neurology (J.A.), Columbia University Medical Center, New York, NY; Duke Clinical Research Institute (J.W., S.S., Y.X., R.A.M.), Durham, NC; Division of Cardiology (G.C.F.), Ronald Reagan-UCLA Medical Center, Los Angeles, CA; Department of Clinical Neurosciences and Hotchkiss Brain Institute (E.E.S.), University of Calgary, Canada; Department of Neurology (S.S.), Duke University Hospital; Department of Neurology (Y.X.), Duke University Medical Center, Durham, NC; Brigham and Women's Hospital Heart & Vascular Center (D.L.B.) and Department of Neurology, Massachusetts General Hospital (L.H.S.), Harvard Medical School, Boston; Department of Epidemiology (M.J.R.), Michigan State University, East Lansing; Department of Biostatistics and Bioinformatics (R.A.M.), Duke University, Durham, NC; and Department of Neurology (K.N.S.), Division of Neurocritical Care & Emergency Neurology, Yale University, New Haven, CT.
| | - Jingjing Wu
- From the Department of Neurology (J.A.), Columbia University Medical Center, New York, NY; Duke Clinical Research Institute (J.W., S.S., Y.X., R.A.M.), Durham, NC; Division of Cardiology (G.C.F.), Ronald Reagan-UCLA Medical Center, Los Angeles, CA; Department of Clinical Neurosciences and Hotchkiss Brain Institute (E.E.S.), University of Calgary, Canada; Department of Neurology (S.S.), Duke University Hospital; Department of Neurology (Y.X.), Duke University Medical Center, Durham, NC; Brigham and Women's Hospital Heart & Vascular Center (D.L.B.) and Department of Neurology, Massachusetts General Hospital (L.H.S.), Harvard Medical School, Boston; Department of Epidemiology (M.J.R.), Michigan State University, East Lansing; Department of Biostatistics and Bioinformatics (R.A.M.), Duke University, Durham, NC; and Department of Neurology (K.N.S.), Division of Neurocritical Care & Emergency Neurology, Yale University, New Haven, CT
| | - Gregg C Fonarow
- From the Department of Neurology (J.A.), Columbia University Medical Center, New York, NY; Duke Clinical Research Institute (J.W., S.S., Y.X., R.A.M.), Durham, NC; Division of Cardiology (G.C.F.), Ronald Reagan-UCLA Medical Center, Los Angeles, CA; Department of Clinical Neurosciences and Hotchkiss Brain Institute (E.E.S.), University of Calgary, Canada; Department of Neurology (S.S.), Duke University Hospital; Department of Neurology (Y.X.), Duke University Medical Center, Durham, NC; Brigham and Women's Hospital Heart & Vascular Center (D.L.B.) and Department of Neurology, Massachusetts General Hospital (L.H.S.), Harvard Medical School, Boston; Department of Epidemiology (M.J.R.), Michigan State University, East Lansing; Department of Biostatistics and Bioinformatics (R.A.M.), Duke University, Durham, NC; and Department of Neurology (K.N.S.), Division of Neurocritical Care & Emergency Neurology, Yale University, New Haven, CT
| | - Eric E Smith
- From the Department of Neurology (J.A.), Columbia University Medical Center, New York, NY; Duke Clinical Research Institute (J.W., S.S., Y.X., R.A.M.), Durham, NC; Division of Cardiology (G.C.F.), Ronald Reagan-UCLA Medical Center, Los Angeles, CA; Department of Clinical Neurosciences and Hotchkiss Brain Institute (E.E.S.), University of Calgary, Canada; Department of Neurology (S.S.), Duke University Hospital; Department of Neurology (Y.X.), Duke University Medical Center, Durham, NC; Brigham and Women's Hospital Heart & Vascular Center (D.L.B.) and Department of Neurology, Massachusetts General Hospital (L.H.S.), Harvard Medical School, Boston; Department of Epidemiology (M.J.R.), Michigan State University, East Lansing; Department of Biostatistics and Bioinformatics (R.A.M.), Duke University, Durham, NC; and Department of Neurology (K.N.S.), Division of Neurocritical Care & Emergency Neurology, Yale University, New Haven, CT
| | - Shreyansh Shah
- From the Department of Neurology (J.A.), Columbia University Medical Center, New York, NY; Duke Clinical Research Institute (J.W., S.S., Y.X., R.A.M.), Durham, NC; Division of Cardiology (G.C.F.), Ronald Reagan-UCLA Medical Center, Los Angeles, CA; Department of Clinical Neurosciences and Hotchkiss Brain Institute (E.E.S.), University of Calgary, Canada; Department of Neurology (S.S.), Duke University Hospital; Department of Neurology (Y.X.), Duke University Medical Center, Durham, NC; Brigham and Women's Hospital Heart & Vascular Center (D.L.B.) and Department of Neurology, Massachusetts General Hospital (L.H.S.), Harvard Medical School, Boston; Department of Epidemiology (M.J.R.), Michigan State University, East Lansing; Department of Biostatistics and Bioinformatics (R.A.M.), Duke University, Durham, NC; and Department of Neurology (K.N.S.), Division of Neurocritical Care & Emergency Neurology, Yale University, New Haven, CT
| | - Ying Xian
- From the Department of Neurology (J.A.), Columbia University Medical Center, New York, NY; Duke Clinical Research Institute (J.W., S.S., Y.X., R.A.M.), Durham, NC; Division of Cardiology (G.C.F.), Ronald Reagan-UCLA Medical Center, Los Angeles, CA; Department of Clinical Neurosciences and Hotchkiss Brain Institute (E.E.S.), University of Calgary, Canada; Department of Neurology (S.S.), Duke University Hospital; Department of Neurology (Y.X.), Duke University Medical Center, Durham, NC; Brigham and Women's Hospital Heart & Vascular Center (D.L.B.) and Department of Neurology, Massachusetts General Hospital (L.H.S.), Harvard Medical School, Boston; Department of Epidemiology (M.J.R.), Michigan State University, East Lansing; Department of Biostatistics and Bioinformatics (R.A.M.), Duke University, Durham, NC; and Department of Neurology (K.N.S.), Division of Neurocritical Care & Emergency Neurology, Yale University, New Haven, CT
| | - Deepak L Bhatt
- From the Department of Neurology (J.A.), Columbia University Medical Center, New York, NY; Duke Clinical Research Institute (J.W., S.S., Y.X., R.A.M.), Durham, NC; Division of Cardiology (G.C.F.), Ronald Reagan-UCLA Medical Center, Los Angeles, CA; Department of Clinical Neurosciences and Hotchkiss Brain Institute (E.E.S.), University of Calgary, Canada; Department of Neurology (S.S.), Duke University Hospital; Department of Neurology (Y.X.), Duke University Medical Center, Durham, NC; Brigham and Women's Hospital Heart & Vascular Center (D.L.B.) and Department of Neurology, Massachusetts General Hospital (L.H.S.), Harvard Medical School, Boston; Department of Epidemiology (M.J.R.), Michigan State University, East Lansing; Department of Biostatistics and Bioinformatics (R.A.M.), Duke University, Durham, NC; and Department of Neurology (K.N.S.), Division of Neurocritical Care & Emergency Neurology, Yale University, New Haven, CT
| | - Lee H Schwamm
- From the Department of Neurology (J.A.), Columbia University Medical Center, New York, NY; Duke Clinical Research Institute (J.W., S.S., Y.X., R.A.M.), Durham, NC; Division of Cardiology (G.C.F.), Ronald Reagan-UCLA Medical Center, Los Angeles, CA; Department of Clinical Neurosciences and Hotchkiss Brain Institute (E.E.S.), University of Calgary, Canada; Department of Neurology (S.S.), Duke University Hospital; Department of Neurology (Y.X.), Duke University Medical Center, Durham, NC; Brigham and Women's Hospital Heart & Vascular Center (D.L.B.) and Department of Neurology, Massachusetts General Hospital (L.H.S.), Harvard Medical School, Boston; Department of Epidemiology (M.J.R.), Michigan State University, East Lansing; Department of Biostatistics and Bioinformatics (R.A.M.), Duke University, Durham, NC; and Department of Neurology (K.N.S.), Division of Neurocritical Care & Emergency Neurology, Yale University, New Haven, CT
| | - Mathew J Reeves
- From the Department of Neurology (J.A.), Columbia University Medical Center, New York, NY; Duke Clinical Research Institute (J.W., S.S., Y.X., R.A.M.), Durham, NC; Division of Cardiology (G.C.F.), Ronald Reagan-UCLA Medical Center, Los Angeles, CA; Department of Clinical Neurosciences and Hotchkiss Brain Institute (E.E.S.), University of Calgary, Canada; Department of Neurology (S.S.), Duke University Hospital; Department of Neurology (Y.X.), Duke University Medical Center, Durham, NC; Brigham and Women's Hospital Heart & Vascular Center (D.L.B.) and Department of Neurology, Massachusetts General Hospital (L.H.S.), Harvard Medical School, Boston; Department of Epidemiology (M.J.R.), Michigan State University, East Lansing; Department of Biostatistics and Bioinformatics (R.A.M.), Duke University, Durham, NC; and Department of Neurology (K.N.S.), Division of Neurocritical Care & Emergency Neurology, Yale University, New Haven, CT
| | - Roland A Matsouaka
- From the Department of Neurology (J.A.), Columbia University Medical Center, New York, NY; Duke Clinical Research Institute (J.W., S.S., Y.X., R.A.M.), Durham, NC; Division of Cardiology (G.C.F.), Ronald Reagan-UCLA Medical Center, Los Angeles, CA; Department of Clinical Neurosciences and Hotchkiss Brain Institute (E.E.S.), University of Calgary, Canada; Department of Neurology (S.S.), Duke University Hospital; Department of Neurology (Y.X.), Duke University Medical Center, Durham, NC; Brigham and Women's Hospital Heart & Vascular Center (D.L.B.) and Department of Neurology, Massachusetts General Hospital (L.H.S.), Harvard Medical School, Boston; Department of Epidemiology (M.J.R.), Michigan State University, East Lansing; Department of Biostatistics and Bioinformatics (R.A.M.), Duke University, Durham, NC; and Department of Neurology (K.N.S.), Division of Neurocritical Care & Emergency Neurology, Yale University, New Haven, CT
| | - Kevin N Sheth
- From the Department of Neurology (J.A.), Columbia University Medical Center, New York, NY; Duke Clinical Research Institute (J.W., S.S., Y.X., R.A.M.), Durham, NC; Division of Cardiology (G.C.F.), Ronald Reagan-UCLA Medical Center, Los Angeles, CA; Department of Clinical Neurosciences and Hotchkiss Brain Institute (E.E.S.), University of Calgary, Canada; Department of Neurology (S.S.), Duke University Hospital; Department of Neurology (Y.X.), Duke University Medical Center, Durham, NC; Brigham and Women's Hospital Heart & Vascular Center (D.L.B.) and Department of Neurology, Massachusetts General Hospital (L.H.S.), Harvard Medical School, Boston; Department of Epidemiology (M.J.R.), Michigan State University, East Lansing; Department of Biostatistics and Bioinformatics (R.A.M.), Duke University, Durham, NC; and Department of Neurology (K.N.S.), Division of Neurocritical Care & Emergency Neurology, Yale University, New Haven, CT
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Niklasson A, Herlitz J, Jood K. Socioeconomic disparities in prehospital stroke care. Scand J Trauma Resusc Emerg Med 2019; 27:53. [PMID: 31046804 PMCID: PMC6498576 DOI: 10.1186/s13049-019-0630-6] [Citation(s) in RCA: 18] [Impact Index Per Article: 3.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/17/2019] [Accepted: 04/17/2019] [Indexed: 12/14/2022] Open
Abstract
Background and purpose Recent studies have revealed socioeconomic disparities in stroke outcomes. Here, we investigated whether prehospital stroke care differs with respect to socioeconomic status (SES). Methods Consecutive stroke and TIA patients (n = 3006) admitted to stroke units at Sahlgrenska University Hospital, Gothenburg, Sweden, from 1 November 2014 to 31 July 2016, were included. Data on prehospital care were obtained from a local stroke register. Socioeconomic status was classified according to the average level of income and education within each patient’s neighbourhood (postcode area). Results The median system delay from calling the emergency medical communication centre (EMCC) to start of brain computed tomography on hospital arrival was 3 h 47 min (95% confidence interval (CI) 3 h 30 min to 4 h 05 min) for patients within the lowest SES tertile and 3 h 17 min (95% CI 3 h 00 min to 3 h 37 min) for the highest tertile (p < 0.05). Patients with a lower SES were less likely to receive the highest priority in the ambulance (p < 0.05) and had lower rates of prehospital recognition of stroke/TIA (p < 0.05) than those with a high SES. No inequities were found concerning EMCC prioritisation or the probability of ambulance transport. Conclusions We found socioeconomic inequities in prehospital stroke care which could affect the efficacy of acute stroke treatment. The ambulance nurses’ ability to recognise stroke/TIA may partly explain the observed inequities.
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Affiliation(s)
- Amanda Niklasson
- Institute of Neuroscience and Physiology, Department of Clinical Neuroscience, The Sahlgrenska Academy, University of Gothenburg, Blå Stråket 7, plan 3, SE-413 45, Gothenburg, Sweden.
| | - Johan Herlitz
- PreHospen - Centre for Prehospital Research, Faculty of Caring Science, Work Life and Social Welfare, University of Borås, Borås, Sweden
| | - Katarina Jood
- Institute of Neuroscience and Physiology, Department of Clinical Neuroscience, The Sahlgrenska Academy, University of Gothenburg, Blå Stråket 7, plan 3, SE-413 45, Gothenburg, Sweden
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Takaku R, Yamaoka A. Payment systems and hospital length of stay: a bunching-based evidence. INTERNATIONAL JOURNAL OF HEALTH ECONOMICS AND MANAGEMENT 2019; 19:53-77. [PMID: 29728908 DOI: 10.1007/s10754-018-9243-2] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.6] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 08/10/2016] [Accepted: 04/25/2018] [Indexed: 06/08/2023]
Abstract
Despite the huge attention on the long average hospital length of stay (LOS) in Japan, there are limited empirical studies on the impacts of the payment systems on LOS. In order to shed new light on this issue, we focus on the fact that reimbursement for hospital care is linked to the number of patient bed-days, where a "day" is defined as the period from one midnight to the next. This "midnight-to-midnight" definition may incentivize health care providers to manipulate hospital acceptance times in emergency patients, as patients admitted before midnight would have an additional day for reimbursement when compared with those admitted after midnight. We test this hypothesis using administrative data of emergency transportations in Japan from 2008 to 2011 (N = 2,146,498). The results indicate that there is a significant bunching in the number of acceptances at the emergency hospital around midnight; the number heaps a few minutes before midnight, but suddenly drops just after midnight. Given that the occurrence of emergency episode is random and the density is smooth during nighttime, bunching in the number of hospital acceptances around midnight suggests that hospital care providers shift the hospital acceptance times forward by hurrying-up to accept the patients. This manipulation clearly leads to longer LOS by one bed-day. In addition, the manipulation is observed in the prefectures where private hospitals mainly provide emergency medical services, suggesting hospital ownership is associated with the manipulation of hospital acceptance time.
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Affiliation(s)
- Reo Takaku
- Institute for Health Economics and Policy, 11 Toyo Kaiji Bldg. 2F, 1-5-11 Nishishimbashi, Minato-ku, Tokyo, 105-0003, Japan.
| | - Atsushi Yamaoka
- Institute for Health Economics and Policy, 11 Toyo Kaiji Bldg. 2F, 1-5-11 Nishishimbashi, Minato-ku, Tokyo, 105-0003, Japan
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Fuentes A, Schoen C, Kulzer RR, Long C, Bushnik T, Rath JF. Impact of racial-ethnic minority status and systemic vulnerabilities on time to acute TBI rehabilitation admission in an urban public hospital setting. Rehabil Psychol 2019; 64:229-236. [PMID: 30688481 DOI: 10.1037/rep0000260] [Citation(s) in RCA: 18] [Impact Index Per Article: 3.6] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/20/2023]
Abstract
PURPOSE/OBJECTIVE Racial/ethnic minorities and other vulnerable social groups experience health care disparities. There is a lack of research exploring how time to acute rehabilitation admission is impacted by race/ethnicity and other marginalizing systemic vulnerabilities. The purpose of this study is to investigate whether race/ethnicity and other sociodemographic vulnerabilities impact expediency of acute rehabilitation admission following traumatic brain injury (TBI). Research Method/Design: This study is a secondary analysis of an existing dataset of 111 patients admitted for acute TBI rehabilitation at an urban public hospital. Patient groups were defined by race/ethnicity (People of color or White) and vulnerable group status (high or low vulnerable group membership [VGM]). RESULTS White patients are admitted to acute TBI rehabilitation significantly faster than people of color. After taking vulnerabilities into account, high VGM people of color experience the most severe injuries and take the longest to receive acute TBI rehabilitation. Despite small differences in injury severity, low VGM people of color take longer to be admitted to acute TBI rehabilitation than White patients. High VGM White patients have less severe injuries yet take longer to be admitted to acute rehabilitation than low VGM White patients. Finally, notable differences exist between White patients and patients of color on rater-based injury severity scales that are discordant with severity as measured by more objective markers. CONCLUSIONS/IMPLICATIONS Overall, findings indicate that sociodemographic factors including race/ethnicity and systemic vulnerabilities impact injury severity and time to acute TBI rehabilitation admission. (PsycINFO Database Record (c) 2019 APA, all rights reserved).
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Affiliation(s)
- Armando Fuentes
- Department of Psychology, Rusk Rehabilitation at New York University Langone Health
| | - Chelsea Schoen
- Department of Psychology, Rusk Rehabilitation at New York University Langone Health
| | - Rebecca R Kulzer
- Department of Psychology, Rusk Rehabilitation at New York University Langone Health
| | - Coralynn Long
- Department of Psychology, Rusk Rehabilitation at New York University Langone Health
| | - Tamara Bushnik
- Department of Research, Rusk Rehabilitation at New York University Langone Health
| | - Joseph F Rath
- Department of Psychology, Rusk Rehabilitation at New York University Langone Health
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Roshanfekr P, Khodaie-Ardakani MR, Malek Afzali Ardakani H, Sajjadi H. Prevalence and Socio-Economic Determinants of Disabilities Caused by Road Traffic Accidents in Iran; A National Survey. Bull Emerg Trauma 2019; 7:60-66. [PMID: 30719468 PMCID: PMC6360010 DOI: 10.29252/beat-070109] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/01/2022] Open
Abstract
Objective To determine the prevalence and socio-economic disparity among victims with disabilities caused by RTAs in Iran as country with a high rate of accidents. Method The source of data was the Iranian Multiple Indicator Demographic and Health Survey, a nationwide cross-sectional study. The sampling framework was based on the population and housing census for Iran in 2006. Provincial samples ranged from 400 to 6,400 households. The target sample was 3,096 clusters consisting of 2,187 urban and 909 rural clusters. In the present study, all but a few indicators are reported at provincial levels. Mortality indicators, accident and disability rates, low birth weight rate and young age at marriage rates are presented at the national level only. Logistic regression was performed to investigate the individual and family factors influencing RTAs that lead to disability in Iran. Results The period prevalence (12 months) of road traffic accident disabilities (RTADs) in the total population of 111415 was 30.52 (95% CI: 21.13.41.64) per 100,000 individuals. Among those who had been injured during the year leading up to the study, the proportion of disabilities caused by RTAs was 31.67 (95% CI; 8.51.54.97) per 1000 pedestrians, 20.99 (95% CI: 13.37.30.75) per 1000 motorcyclists, 18.64 (95% CI: 7.71.29.57) per 1000 vehicle drivers. Multivariate logistic regression analysis showed that the risk of RTADs differed significantly in relation to age (AOR 50-59 vs. 0-9=10. 78, p-value:0.05); activity status (AOR unemployed vs. employed=4.72, p-value:0.001) and family income (AOR q2 vs. q1=0.37, p-value:0.048) of the victim. Conclusion In addition to the risks associated with socio-economic groups, particularly vulnerable groups, RTADs have consequences which can lead to further marginalization of individuals, can affect their quality of life and damage the community as a whole.
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Affiliation(s)
- Payam Roshanfekr
- Social Determinants of Health Research Center, University of Social Welfare and Rehabilitation Sciences, Tehran, Iran
| | | | - Hossein Malek Afzali Ardakani
- Department of Epidemiology and Biostatistics, School of Public Health, Tehran University of Medical Sciences, Tehran, Iran
| | - Homeira Sajjadi
- National Board Social Medicine, Social Determinants of Health Research Center, University of Social Welfare and Rehabilitation Sciences, Tehran, Iran
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Hsia RY, Huang D, Mann NC, Colwell C, Mercer MP, Dai M, Niedzwiecki MJ. A US National Study of the Association Between Income and Ambulance Response Time in Cardiac Arrest. JAMA Netw Open 2018; 1:e185202. [PMID: 30646394 PMCID: PMC6324393 DOI: 10.1001/jamanetworkopen.2018.5202] [Citation(s) in RCA: 55] [Impact Index Per Article: 9.2] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 11/22/2022] Open
Abstract
IMPORTANCE Emergency medical services (EMS) provide critical prehospital care, and disparities in response times to time-sensitive conditions, such as cardiac arrest, may contribute to disparities in patient outcomes. OBJECTIVES To investigate whether ambulance 9-1-1 times were longer in low-income vs high-income areas and to compare response times with national benchmarks of 4, 8, or 15 minutes across income quartiles. DESIGN, SETTING, AND PARTICIPANTS A retrospective cross-sectional study was performed of the 2014 National Emergency Medical Services Information System data in June 2017 using negative binomial and logistic regressions to examine the association between zip code-level income and EMS response times. The study used ambulance 9-1-1 response data for out-of-hospital cardiac arrest from 46 of 50 state repositories (92.0%) in the United States. The sample included 63 600 cardiac arrest encounters of patients who did not die on scene and were transported to the hospital. MAIN OUTCOMES AND MEASURES Four time measures were examined, including response time, on-scene time, transport time, and total EMS time. The study compared response times with EMS response time benchmarks for responding to cardiac arrest calls within 4, 8, and 15 minutes. RESULTS The study sample included 63 600 cardiac arrest encounters of patients (mean [SD] age, 60.6 [19.0] years; 57.9% male), with 37 550 patients (59.0%) from high-income areas and 8192 patients (12.9%) from low-income areas. High-income areas had greater proportions of white patients (70.1% vs 62.2%), male patients (58.8% vs 54.1%), privately insured patients (29.4% vs 15.9%), and uninsured patients (15.3% vs 7.9%), while low-income areas had a greater proportion of Medicaid-insured patients (38.3% vs 15.8%). The mean (SD) total EMS time was 37.5 (13.6) minutes in the highest zip code income quartile and 43.0 (18.8) minutes in the lowest. After controlling for urban zip code, weekday, and time of day in regression analyses, total EMS time remained 10% longer (95% CI, 9%-11%; P < .001), translating to 3.8 minutes longer in the poorest zip codes. The EMS response time to patients in high-income zip codes was more likely to meet 8-minute and 15-minute cutoffs compared with low-income zip codes. CONCLUSIONS AND RELEVANCE Patients with cardiac arrest from the poorest neighborhoods had longer EMS times compared with those from the wealthiest, and response times were less likely to meet national benchmarks in low-income areas, which may lead to increased disparities in prehospital delivery of care over time.
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Affiliation(s)
- Renee Y. Hsia
- Department of Emergency Medicine, University of California, San Francisco
- Philip R. Lee Institute for Health Policy Studies, University of California, San Francisco
| | - Delphine Huang
- Department of Emergency Medicine, University of California, San Francisco
| | - N. Clay Mann
- Department of Pediatrics, University of Utah School of Medicine, Salt Lake City
| | | | - Mary P. Mercer
- Department of Emergency Medicine, University of California, San Francisco
| | - Mengtao Dai
- Department of Pediatrics, University of Utah School of Medicine, Salt Lake City
| | - Matthew J. Niedzwiecki
- Department of Emergency Medicine, University of California, San Francisco
- Philip R. Lee Institute for Health Policy Studies, University of California, San Francisco
- Mathematica Policy Research, Oakland, California
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Hosseini SMR, Maleki M, Gorji HA, Khorasani-Zavareh D, Roudbari M. Factors affecting emergency medical dispatchers' decision-making: a qualitative study. J Multidiscip Healthc 2018; 11:391-398. [PMID: 30174433 PMCID: PMC6110286 DOI: 10.2147/jmdh.s159593] [Citation(s) in RCA: 10] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/22/2022] Open
Abstract
Introduction Prehospital emergency medical service dispatchers should make prompt and appropriate decisions to save the life of victims. The complexity of timely and reasonable decision-making in life-threatening conditions has driven researchers to investigate varying aspects of the emergency medical dispatch (EMD) process. The purpose of this study was to explore the contributors to appropriate and prompt decision-making among dispatchers. Methods A qualitative study through thematic analysis was designed. Data were collected using observation and semistructured interviews with 16 authorities and dispatchers in seven EMDs across Iran. Results The study found “responsiveness” as the main category contributing to improved decision-making in EMD. The components introduced in this study for dispatchers’ responsiveness consisted of two categories. The first was “personal values” including faith and belief, eagerness to help, service excellence, altruism, respect, and impartiality in clinical judgment. The second was “professional attitudes” resulting from education and experience, including the recognition of emergency as a threat to health, sensitivity in triage, response to all requests for help, care for early warnings, commitment to organizational goals and standards, attention to the emergency medical service social support responsibility, and professional temperance. Conclusion In this study, responsiveness was identified as a main category in improving the decision-making process among dispatchers. To attain responsiveness, institutionalization of its values and establishment of EMD-specific professional attitudes in dispatchers should be taken into consideration.
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Affiliation(s)
- Seyyed Mohammad Reza Hosseini
- Department of Health Services Management, School of Health Management and Information Sciences, Iran University of Medical Sciences, Tehran, Iran,
| | - Mohammadreza Maleki
- Department of Health Services Management, School of Health Management and Information Sciences, Iran University of Medical Sciences, Tehran, Iran,
| | - Hasan Abolghasem Gorji
- Department of Health Services Management, School of Health Management and Information Sciences, Iran University of Medical Sciences, Tehran, Iran,
| | - Davoud Khorasani-Zavareh
- Safety Promotion and Injury Prevention Research Center, Shahid Beheshti University of Medical Sciences, Tehran, Iran.,Department of Health in Disaster and Emergency, School of Health, Safety and Environment, Shahid Beheshti University of Medical Sciences, Tehran, Iran.,Department of Clinical Sciences and Education, Karolinska Institute, Södersjukhuset (KI SÖS), Stockholm, Sweden
| | - Masoud Roudbari
- Antimicrobial Resistance Research Center, Rasoul-e-Akram Hospital, Department of Biostatistics, School of Public Health, Iran University of Medical Sciences, Tehran, Iran
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Seim J, Glenn MJ, English J, Sporer K. Neighborhood Poverty and 9-1-1 Ambulance Response Time. PREHOSP EMERG CARE 2018; 22:436-444. [DOI: 10.1080/10903127.2017.1416209] [Citation(s) in RCA: 5] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/18/2022]
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Response to Symptoms and Prehospital Delay in Stroke Patients. Is It Time to Reconsider Stroke Awareness Campaigns? J Stroke Cerebrovasc Dis 2017; 27:625-632. [PMID: 29108809 DOI: 10.1016/j.jstrokecerebrovasdis.2017.09.036] [Citation(s) in RCA: 20] [Impact Index Per Article: 2.9] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/04/2017] [Accepted: 09/24/2017] [Indexed: 11/21/2022] Open
Abstract
BACKGROUND Despite recent advances in acute stroke care, reperfusion therapies are given to only 1%-8% of patients. Previous studies have focused on prehospital or decision delay. We aim to give a more comprehensive view by addressing different time delays and decisions. METHODS A total of 382 patients with either acute stroke or transient ischemic attack were prospectively included. Sociodemographic and clinical parameters and data on decision delay, prehospital delay, and first medical contact were recorded. Multivariate logistic regression analyses were conducted to identify factors related to decision delay of 15 minutes or shorter, calling the Extrahospital Emergency Services, and prehospital delay of 60 minutes or shorter and 180 minutes or shorter. RESULTS Prehospital delay was 60 minutes or shorter in 11.3% of our patients and 180 minutes or shorter in 48.7%. Major vascular risk factors were present in 89.8% of patients. Severity was associated with decision delay of 15 minutes or shorter (odds ratio [OR] 1.08; confidence interval [CI] 1.04-1.13), calling the Extrahospital Emergency Services (OR 1.17; CI 1.12-1.23), and prehospital delay of 180 minutes or shorter (OR 1.08; CI 1.01-1.15). Adult children as witnesses favored a decision delay of 15 minutes or shorter (OR 3.44; CI 95% 1.88-6.27; P < .001) and calling the Extrahospital Emergency Services (OR 2.24; IC 95% 1.20-4.22; P = .012). Calling the Extrahospital Emergency Services favored prehospital delay of 60 minutes or shorter (OR 5.69; CI 95% 2.41-13.45; P < .001) and prehospital delay of 180 minutes or shorter (OR 3.86; CI 95% 1.47-10.11; P = .006). CONCLUSIONS Severity and the bystander play a critical role in the response to stroke. Calling the Extrahospital Emergency Services promotes shorter delays. Future interventions should encourage immediately calling the Extrahospital Emergency Services, but the target should be redirected to those with known risk factors and their caregivers.
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Seremwe F, Kaseke F, Chikwanha TM, Chikwasha V. Factors associated with hospital arrival time after the onset of stroke symptoms: A cross-sectional study at two teaching hospitals in Harare, Zimbabwe. Malawi Med J 2017; 29:171-176. [PMID: 28955428 PMCID: PMC5610291 DOI: 10.4314/mmj.v29i2.18] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/25/2022] Open
Abstract
Background Late presentation to hospital after onset of stroke affects management and outcomes of the patients. This study aimed to determine the factors associated with time taken to present to hospital after the onset of acute stroke symptoms. Methods A descriptive cross sectional study was conducted at two teaching hospitals in Zimbabwe. Participants included patients admitted with stroke and their relatives. A self-administered questionnaire was used to collect information on history of stroke occurrence and time taken to present to hospital. Data was analysed for means, frequencies, percentages and Odds ratios. Results Less than half (33%) of the participants were able to recognize symptoms of stroke. Not having money to pay for hospital bills was a predictor of late hospital presentation (OR =6.64; 95% CI, (2.05–21.53); p=0.002). The other factors, though not statistically significant included not perceiving stroke as a serious illness (OR = 2.43; 95% CI (0.78–5.51); p=0.083) and unavailability of transport (OR=2.33; 95% CI (0.71–7.56); p=0.161). Predictors for early presentation included receiving knowledge about stroke from the community (OR=0.46; 95% CI (0.15–1.39); p=0.170); seeking help at the hospital (OR=0.50; 95% CI (0.18–1.37); p=0.177) and having a stroke while at the workplace (OR =0.46; 95% CI (0.08–2.72); p=0.389). Conclusions Regarding stroke as an emergency that does not require prerequisite payment for services at hospitals and improved community awareness on stroke may improve time taken to present to hospital after the onset of stroke symptoms.
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Affiliation(s)
| | - Farayi Kaseke
- Department of Rehabilitation, College of Health Sciences, University of Zimbabwe, Harare, Zimbabwe
| | - Theodora M Chikwanha
- Department of Rehabilitation, College of Health Sciences, University of Zimbabwe, Harare, Zimbabwe
| | - Vasco Chikwasha
- Department of Community Medicine, College of Health Sciences, University of Zimbabwe, Harare, Zimbabwe
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Miller AL, Simon D, Roe MT, Kontos MC, Diercks D, Amsterdam E, Bhatt DL. Comparison of Delay Times from Symptom Onset to Medical Contact in Blacks Versus Whites With Acute Myocardial Infarction. Am J Cardiol 2017; 119:1127-1134. [PMID: 28237284 DOI: 10.1016/j.amjcard.2016.12.021] [Citation(s) in RCA: 14] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 11/18/2016] [Revised: 12/22/2016] [Accepted: 12/22/2016] [Indexed: 12/13/2022]
Abstract
Clinical outcomes in acute myocardial infarction (AMI) worsen with increasing delay between symptom onset and clinical presentation. Previous studies have shown that black patients with AMI have longer presentation delays. The objective of this analysis is to explore the potential contribution of community factors to presentation delays in black patients with AMI. We linked clinical data for 346,499 consecutive patients with AMI from Acute Coronary Treatment Intervention Outcomes Network Registry-Get With the Guidelines™ (2007-2014) to socioeconomic and community information from the American Community Survey. Black patients with AMI had longer symptom onset to first medical contact times than white patients (114 vs 101 minutes, p <0.0001) regardless of ambulance versus self-transport. Compared with white patients, black patients were younger and more likely to have clinical co-morbidities such as hypertension, diabetes, previous heart failure, and stroke. They were also more likely to live in urban communities with lower socioeconomic status, lower rates of long-term residence, and higher proportion of single-person households than white patients. In sequential linear regression models adjusting for patient demographic and clinical characteristics, logistic barriers to prompt presentation, and community socioeconomic and composition factors, black patients had a persistent 9% greater time from symptom onset to presentation compared with white patients (95% CI 8% to 11%, p <0.0001). In conclusion, the longer delay in time to presentation in black patients with AMI compared with white patients persists after accounting for a number of both patient and community factors.
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Faigle R, Urrutia VC, Cooper LA, Gottesman RF. Individual and System Contributions to Race and Sex Disparities in Thrombolysis Use for Stroke Patients in the United States. Stroke 2017; 48:990-997. [PMID: 28283607 DOI: 10.1161/strokeaha.116.015056] [Citation(s) in RCA: 33] [Impact Index Per Article: 4.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/08/2016] [Revised: 12/19/2016] [Accepted: 01/20/2017] [Indexed: 12/22/2022]
Abstract
BACKGROUND AND PURPOSE Intravenous thrombolysis (IVT) is underutilized in ethnic minorities and women. To disentangle individual and system-based factors determining disparities in IVT use, we investigated race/sex differences in IVT utilization among hospitals serving varying proportions of minority patients. METHODS Ischemic stroke admissions were identified from the Nationwide Inpatient Sample between 2007 and 2011. Hospitals were categorized based on the percentage of minority patients admitted with stroke (<25% minority patients [white hospitals], 25% to 50% minority patients [mixed hospitals], or >50% minority patients [minority hospitals]). Logistic regression was used to evaluate the association between race/sex and IVT use within and between the different hospital strata. RESULTS Among 337 201 stroke admissions, white men had the highest odds of IVT among all race/sex groups in any hospital strata, and the odds of IVT for white men did not differ by hospital strata. For white women and minority men, the odds of IVT were significantly lower in minority hospitals compared with white hospitals (odds ratio, 0.83; 95% confidence interval, 0.71-0.97, for white women; and odds ratio, 0.82; 95% confidence interval, 0.69-0.99, for minority men). Race disparities in IVT use among women were observed in white hospitals (odds ratio, 0.88; 95% confidence interval, 0.78-0.99, in minority compared with white women), but not in minority hospitals (odds ratio, 0.94, 95% confidence interval, 0.82-1.09). Sex disparities in IVT use were observed among whites but not among minorities. CONCLUSIONS Minority men and white women have significantly lower odds of IVT in minority hospitals compared with white hospitals. IVT use in white men does not differ by hospital strata.
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Affiliation(s)
- Roland Faigle
- From the Department of Neurology (R.F., V.C.U., R.F.G.) and Department of Medicine (L.A.C.), Johns Hopkins University School of Medicine, Baltimore, MD.
| | - Victor C Urrutia
- From the Department of Neurology (R.F., V.C.U., R.F.G.) and Department of Medicine (L.A.C.), Johns Hopkins University School of Medicine, Baltimore, MD
| | - Lisa A Cooper
- From the Department of Neurology (R.F., V.C.U., R.F.G.) and Department of Medicine (L.A.C.), Johns Hopkins University School of Medicine, Baltimore, MD
| | - Rebecca F Gottesman
- From the Department of Neurology (R.F., V.C.U., R.F.G.) and Department of Medicine (L.A.C.), Johns Hopkins University School of Medicine, Baltimore, MD
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Hanaki N, Yamashita K, Kunisawa S, Imanaka Y. Effect of the number of request calls on the time from call to hospital arrival: a cross-sectional study of an ambulance record database in Nara prefecture, Japan. BMJ Open 2016; 6:e012194. [PMID: 27940625 PMCID: PMC5168703 DOI: 10.1136/bmjopen-2016-012194] [Citation(s) in RCA: 6] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 11/07/2022] Open
Abstract
OBJECTIVES In Japan, ambulance staff sometimes must make request calls to find hospitals that can accept patients because of an inadequate information sharing system. This study aimed to quantify effects of the number of request calls on the time interval between an emergency call and hospital arrival. DESIGN AND SETTING A cross-sectional study of an ambulance records database in Nara prefecture, Japan. CASES A total of 43 663 patients (50% women; 31.2% aged 80 years and over): (1) transported by ambulance from April 2013 to March 2014, (2) aged 15 years and over, and (3) with suspected major illness. PRIMARY OUTCOME MEASURES The time from call to hospital arrival, defined as the time interval from receipt of an emergency call to ambulance arrival at a hospital. RESULTS The mean time interval from emergency call to hospital arrival was 44.5 min, and the mean number of requests was 1.8. Multilevel linear regression analysis showed that ∼43.8% of variations in transportation times were explained by patient age, sex, season, day of the week, time, category of suspected illness, person calling for the ambulance, emergency status at request call, area and number of request calls. A higher number of request calls was associated with longer time intervals to hospital arrival (addition of 6.3 min per request call; p<0.001). In an analysis dividing areas into three groups, there were differences in transportation time for diseases needing cardiologists, neurologists, neurosurgeons and orthopaedists. CONCLUSIONS The study revealed 6.3 additional minutes needed in transportation time for every refusal of a request call, and also revealed disease-specific delays among specific areas. An effective system should be collaboratively established by policymakers and physicians to ensure the rapid identification of an available hospital for patient transportation in order to reduce the time from the initial emergency call to hospital arrival.
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Affiliation(s)
- Nao Hanaki
- Department of Healthcare Economics and Quality Management, Graduate School of Medicine, Kyoto University, Yoshida Konoe-cho, Sakyo-ku, Kyoto, Japan
| | - Kazuto Yamashita
- Department of Healthcare Economics and Quality Management, Graduate School of Medicine, Kyoto University, Yoshida Konoe-cho, Sakyo-ku, Kyoto, Japan
| | - Susumu Kunisawa
- Department of Healthcare Economics and Quality Management, Graduate School of Medicine, Kyoto University, Yoshida Konoe-cho, Sakyo-ku, Kyoto, Japan
| | - Yuichi Imanaka
- Department of Healthcare Economics and Quality Management, Graduate School of Medicine, Kyoto University, Yoshida Konoe-cho, Sakyo-ku, Kyoto, Japan
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Zock E, Kerkhoff H, Kleyweg RP, van Bavel-Ta TBV, Scott S, Kruyt ND, Nederkoorn PJ, van de Beek D. Help seeking behavior and onset-to-alarm time in patients with acute stroke: sub-study of the preventive antibiotics in stroke study. BMC Neurol 2016; 16:241. [PMID: 27884126 PMCID: PMC5123223 DOI: 10.1186/s12883-016-0749-2] [Citation(s) in RCA: 15] [Impact Index Per Article: 1.9] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/07/2016] [Accepted: 11/10/2016] [Indexed: 11/30/2022] Open
Abstract
BACKGROUND Patients with acute stroke often do not seek immediate medical help, which is assumed to be driven by lack of knowledge of stroke symptoms. We explored the process of help seeking behavior in patients with acute stroke, evaluating knowledge about stroke symptoms, socio-demographic and clinical characteristics, and onset-to-alarm time (OAT). METHODS In a sub-study of the Preventive Antibiotics in Stroke Study (PASS), 161 acute stroke patients were prospectively included in 3 Dutch hospitals. A semi-structured questionnaire was used to assess knowledge, recognition and interpretation of stroke symptoms. With in-depth interviews, response actions and reasons were explored. OAT was recorded and associations with socio-demographic, clinical parameters were assessed. RESULTS Knowledge about stroke symptoms does not always result in correct recognition of own stroke symptoms, neither into correct interpretation of the situation and subsequent action. In our study population of 161 patients with acute stroke, median OAT was 30 min (interquartile range [IQR] 10-150 min). Recognition of one-sided weakness and/or sensory loss (p = 0.046) and adequate interpretation of the stroke situation (p = 0.003), stroke at daytime (p = 0.002), severe stroke (p = 0.003), calling the emergency telephone number (p = 0.004), and transport by ambulance (p = 0.040) were associated with shorter OAT. CONCLUSION Help seeking behavior after acute stroke is a complex process. A shorter OAT after stroke is associated with correct recognition of one-sided weakness and/or sensory loss, adequate interpretation of the stroke situation by the patient and stroke characteristics and logistics of stroke care, but not by knowledge of stroke symptoms.
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Affiliation(s)
- E. Zock
- Department of Neurology, Albert Schweitzer Hospital Dordrecht, Albert Schweitzerplaats 25, 3318 AT Dordrecht, The Netherlands
- Department of Neurology, Academic Medical Center Amsterdam, Amsterdam, The Netherlands
| | - H. Kerkhoff
- Department of Neurology, Albert Schweitzer Hospital Dordrecht, Albert Schweitzerplaats 25, 3318 AT Dordrecht, The Netherlands
| | - R. P. Kleyweg
- Department of Neurology, Albert Schweitzer Hospital Dordrecht, Albert Schweitzerplaats 25, 3318 AT Dordrecht, The Netherlands
| | | | - S. Scott
- Department of Neurology, Slotervaart Hospital Amsterdam, Amsterdam, The Netherlands
| | - N. D. Kruyt
- Department of Neurology, Leiden University Medical Center, Leiden, The Netherlands
| | - P. J. Nederkoorn
- Department of Neurology, Academic Medical Center Amsterdam, Amsterdam, The Netherlands
| | - D. van de Beek
- Department of Neurology, Academic Medical Center Amsterdam, Amsterdam, The Netherlands
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Zock E, Kerkhoff H, Kleyweg RP, van de Beek D. Intrinsic factors influencing help-seeking behaviour in an acute stroke situation. Acta Neurol Belg 2016; 116:295-301. [PMID: 26732617 PMCID: PMC4989004 DOI: 10.1007/s13760-015-0555-4] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/17/2015] [Accepted: 10/12/2015] [Indexed: 02/03/2023]
Abstract
The proportion of stroke patients eligible for intravenous or intra-arterial treatment is still limited because many patients do not seek medical help immediately after stroke onset. The aim of our study was to explore which intrinsic factors and considerations influence help-seeking behaviour of relatively healthy participants, confronted with stroke situations. Semi-structured interviews were conducted with 25 non-stroke participants aged 50 years or older. We presented 5 clinical stroke situations as if experienced by the participants themselves. Recognition and interpretation of symptoms were evaluated and various factors influencing help-seeking behaviour were explored in-depth. We used the thematic synthesis method for data analysis. Five themes influencing help-seeking behaviour in a stroke situation were identified: influence of knowledge, views about seriousness, ideas about illness and health, attitudes towards others and beliefs about the emergency medical system. A correct recognition of stroke symptoms or a correct interpretation of the stroke situations did not automatically result in seeking medical help. Interestingly, similar factors could lead to different types of actions between participants. Many intrinsic, as well as social and environmental factors are of influence on help-seeking behaviour in an acute stroke situation. All these factors seem to play a complex role in help-seeking behaviour with considerable inter-individual variations. Accomplishing more patients eligible for acute stroke treatment, future research should focus on better understanding of all factors at various levels grounded in a theory of help-seeking behaviour.
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Direct admission to stroke centers reduces treatment delay and improves clinical outcome after intravenous thrombolysis. J Clin Neurosci 2016; 27:74-9. [DOI: 10.1016/j.jocn.2015.06.038] [Citation(s) in RCA: 9] [Impact Index Per Article: 1.1] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/14/2015] [Revised: 06/01/2015] [Accepted: 06/04/2015] [Indexed: 01/07/2023]
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Zhou Y, Yang T, Gong Y, Li W, Chen Y, Li J, Wang M, Yin X, Hu B, Lu Z. Pre-hospital Delay after Acute Ischemic Stroke in Central Urban China: Prevalence and Risk Factors. Mol Neurobiol 2016; 54:3007-3016. [PMID: 27032390 DOI: 10.1007/s12035-016-9750-4] [Citation(s) in RCA: 20] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/27/2015] [Accepted: 01/26/2016] [Indexed: 11/24/2022]
Abstract
Timely thrombolytic treatment is paramount after acute ischemic stroke (AIS); however, a large proportion of patients experience substantial delays in presentation to hospital. This study evaluates the prevalence and risk factors in pre-hospital delays after AIS in central urban China. AIS patients from 66 hospitals in 13 major cities across Hubei Province, between October 1, 2014 and January 31, 2015 were interviewed and their medical records were reviewed to identify those who suffered pre-hospital delays. Bivariate and multivariate analyses were undertaken to determine the prevalence rates and the risk factors associated with pre-hospital delays. A total of 1835 patients were included in the analysis, with 69.3 % patients reportedly arrived at hospital 3 or more hours after onset and 55.3 % patients arrived 6 or more hours after onset. Factors associated with increased pre-hospital delays for 3 or more hours were as follows: patient had a history of stroke (odds ratio (OR), 1.319, P = 0.028), onset location was at home (OR, 1.573, P = 0.002), and patients rather than someone else noticed the symptom onset first (OR, 1.711; P < 0.001). In contrast, knowing someone who had suffered a stroke, considering any kind of the symptoms as severe, transferring from a community-based hospital factors, calling emergency number (120), and shorter distance from the onset place to the first hospital were independently associated with decreased pre-hospital delays. These findings indicate that pre-hospital delays after AIS are common in urban central China, and future intervention programs should be focused on public awareness of stroke and appropriate response.
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Affiliation(s)
- Yanfeng Zhou
- Department of Social Medicine and Health Management, School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, 430030, China
| | - Tingting Yang
- Department of Social Medicine and Health Management, School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, 430030, China
| | - Yanhong Gong
- Department of Social Medicine and Health Management, School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, 430030, China
| | - Wenzhen Li
- Department of Social Medicine and Health Management, School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, 430030, China
| | - Yawen Chen
- Department of Social Medicine and Health Management, School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, 430030, China
| | - Jing Li
- Department of Social Medicine and Health Management, School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, 430030, China
| | - Mengdie Wang
- Department of Neurology, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, 430030, China
| | - Xiaoxv Yin
- Department of Social Medicine and Health Management, School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, 430030, China.
| | - Bo Hu
- Department of Neurology, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, 430030, China.
- The Stroke Quality Control Center of Hubei Province, Wuhan, 430030, China.
| | - Zuxun Lu
- Department of Social Medicine and Health Management, School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, 430030, China.
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Golden AP, Odoi A. Emergency medical services transport delays for suspected stroke and myocardial infarction patients. BMC Emerg Med 2015; 15:34. [PMID: 26634914 PMCID: PMC4668620 DOI: 10.1186/s12873-015-0060-3] [Citation(s) in RCA: 11] [Impact Index Per Article: 1.2] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/25/2014] [Accepted: 11/24/2015] [Indexed: 11/10/2022] Open
Abstract
BACKGROUND Prehospital delays in receiving emergency care for suspected stroke and myocardial infarction (MI) patients have significant impacts on health outcomes. Use of Emergency Medical Services (EMS) has been shown to reduce these delays. However, disparities in EMS transport delays are thought to exist. Therefore the objective of this study was to investigate and identify disparities in EMS transport times for suspected stroke and MI patients. METHODS Over 3,900 records of suspected stroke and MI patients, reported during 2006-2009, were obtained from two EMS agencies (EMS 1 & EMS 2) in Tennessee. Summary statistics of transport time intervals were computed. Multivariable logistic models were used to identify predictors of time intervals exceeding EMS guidelines. RESULTS Only 66 and 10 % of suspected stroke patients were taken to stroke centers by EMS 1 and 2, respectively. Most (80-83 %) emergency calls had response times within the recommended 10 min. However, over 1/3 of the calls had on-scene times exceeding the recommended 15 min. Predictors of time intervals exceeding EMS guidelines were EMS agency, patient age, season and whether or not patients were taken to a specialty center. The odds of total transport time exceeding EMS guidelines were significantly lower for patients not taken to specialty centers. Noteworthy was the 72 % lower odds of total time exceeding guidelines for stroke patients served by EMS 1 compared to those served by EMS 2. Additionally, for every decade increase in age of the patient, the odds of on-scene time exceeding guidelines increased by 15 and 19 % for stroke and MI patients, respectively. CONCLUSION In this study, prehospital delays, as measured by total transport time exceeding guideline was influenced by season, EMS agency responsible, patient age and whether or not the patient is transported to a specialty center. The magnitude of the delays associated with some of the factors are large enough to be clinically important although others, though statistically significant, may not be large enough to be clinically important. These findings should be useful for guiding future studies and local health initiatives that seek to reduce disparities in prehospital delays so as to improve health services and outcomes for stroke and MI patients.
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Affiliation(s)
- Ashley Pedigo Golden
- Department of Biomedical and Diagnostic Sciences, The University of Tennessee, 2407 River Drive, Knoxville, TN, 37996-4543, USA.
| | - Agricola Odoi
- Department of Biomedical and Diagnostic Sciences, The University of Tennessee, 2407 River Drive, Knoxville, TN, 37996-4543, USA.
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The Code Stroke: Medical evaluation by a pre-hospital attention service. MEDICINA UNIVERSITARIA 2015. [DOI: 10.1016/j.rmu.2015.09.001] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/23/2022] Open
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Meurer WJ, Levine DA, Kerber KA, Zahuranec DB, Burke J, Baek J, Sánchez B, Smith MA, Morgenstern LB, Lisabeth LD. Neighborhood Influences on Emergency Medical Services Use for Acute Stroke: A Population-Based Cross-sectional Study. Ann Emerg Med 2015; 67:341-348.e4. [PMID: 26386884 DOI: 10.1016/j.annemergmed.2015.07.524] [Citation(s) in RCA: 11] [Impact Index Per Article: 1.2] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/09/2014] [Revised: 07/20/2015] [Accepted: 07/20/2015] [Indexed: 11/17/2022]
Abstract
STUDY OBJECTIVE Delay to hospital arrival limits acute stroke treatment. Use of emergency medical services (EMS) is key in ensuring timely stroke care. We aim to identify neighborhoods with low EMS use and to evaluate whether neighborhood-level factors are associated with EMS use. METHODS We conducted a secondary analysis of data from the Brain Attack Surveillance in Corpus Christi project, a population-based stroke surveillance study of ischemic stroke and intracerebral hemorrhage cases presenting to emergency departments in Nueces County, TX. The primary outcome was arrival by EMS. The primary exposures were neighborhood resident age, poverty, and violent crime. We estimated the association of neighborhood-level factors with EMS use, using hierarchic logistic regression, controlling for individual factors (stroke severity, ethnicity, and age). RESULTS During 2000 to 2009 there were 4,004 identified strokes, with EMS use data available for 3,474. Nearly half (49%) of stroke cases arrived by EMS. Adjusted stroke EMS use was lower in neighborhoods with higher family income (odds ratio [OR] 0.86; 95% confidence interval [CI] 0.75 to 0.97) and a larger percentage of older adults (OR 0.70; 95% CI 0.56 to 0.89). Individual factors associated with stroke EMS use included white race (OR 1.41; 95% CI 1.13 to 1.76) and older age (OR 1.36 per 10-year age increment; 95% CI 1.27 to 1.46). The proportion of neighborhood stroke cases arriving by EMS ranged from 17% to 71%. The fully adjusted model explained only 0.3% (95% CI 0% to 1.1%) of neighborhood EMS stroke use variance, indicating that individual factors are more strongly associated with stroke EMS use than neighborhood factors. CONCLUSION Although some neighborhood-level factors were associated with EMS use, patient-level factors explained nearly all variability in stroke EMS use. In this community, strategies to increase EMS use should target individuals rather than specific neighborhoods.
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Affiliation(s)
- William J Meurer
- Department of Emergency Medicine, University of Michigan, Ann Arbor, MI; Department of Neurology, University of Michigan, Ann Arbor, MI; Michigan Center for Integrative Research in Critical Care, University of Michigan, Ann Arbor, MI; Institute of Healthcare Policy and Innovation, University of Michigan, Ann Arbor, MI; Stroke Program, University of Michigan, Ann Arbor, MI
| | - Deborah A Levine
- Institute of Healthcare Policy and Innovation, University of Michigan, Ann Arbor, MI; Stroke Program, University of Michigan, Ann Arbor, MI; Department of Internal Medicine, University of Michigan, Ann Arbor, MI
| | - Kevin A Kerber
- Department of Neurology, University of Michigan, Ann Arbor, MI; Institute of Healthcare Policy and Innovation, University of Michigan, Ann Arbor, MI
| | - Darin B Zahuranec
- Department of Neurology, University of Michigan, Ann Arbor, MI; Institute of Healthcare Policy and Innovation, University of Michigan, Ann Arbor, MI; Stroke Program, University of Michigan, Ann Arbor, MI
| | - James Burke
- Department of Neurology, University of Michigan, Ann Arbor, MI; Institute of Healthcare Policy and Innovation, University of Michigan, Ann Arbor, MI; Stroke Program, University of Michigan, Ann Arbor, MI
| | - Jonggyu Baek
- Department of Biostatistics, University of Michigan, Ann Arbor, MI
| | - Brisa Sánchez
- Institute of Healthcare Policy and Innovation, University of Michigan, Ann Arbor, MI; Stroke Program, University of Michigan, Ann Arbor, MI; Department of Biostatistics, University of Michigan, Ann Arbor, MI
| | - Melinda A Smith
- Department of Neurology, University of Michigan, Ann Arbor, MI
| | - Lewis B Morgenstern
- Department of Emergency Medicine, University of Michigan, Ann Arbor, MI; Department of Neurology, University of Michigan, Ann Arbor, MI; Institute of Healthcare Policy and Innovation, University of Michigan, Ann Arbor, MI; Stroke Program, University of Michigan, Ann Arbor, MI; Department of Epidemiology, University of Michigan, Ann Arbor, MI
| | - Lynda D Lisabeth
- Department of Neurology, University of Michigan, Ann Arbor, MI; Institute of Healthcare Policy and Innovation, University of Michigan, Ann Arbor, MI; Stroke Program, University of Michigan, Ann Arbor, MI; Department of Epidemiology, University of Michigan, Ann Arbor, MI.
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Wireklint Sundström B, Herlitz J, Hansson PO, Brink P. Comparison of the university hospital and county hospitals in western Sweden to identify potential weak links in the early chain of care for acute stroke: results of an observational study. BMJ Open 2015; 5:e008228. [PMID: 26351184 PMCID: PMC4563274 DOI: 10.1136/bmjopen-2015-008228] [Citation(s) in RCA: 14] [Impact Index Per Article: 1.6] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 01/31/2023] Open
Abstract
OBJECTIVE To identify weak links in the early chain of care for acute stroke. SETTING 9 emergency hospitals in western Sweden, each with a stroke unit, and the emergency medical services (EMS). PARTICIPANTS All patients hospitalised with a first and a final diagnosis of stroke-between 15 December 2010 and 15 April 2011. The university hospital in the city of Gothenburg was compared with 6 county hospitals. PRIMARY AND SECONDARY MEASURES: (1) The system delay, that is, median delay time from call to the EMS until diagnosis was designated as the primary end point. Secondary end points were: (2) the system delay time from call to the EMS until arrival in a hospital ward, (3) the use of the EMS, (4) priority at the dispatch centre and (5) suspicion of stroke by the EMS nurse. RESULTS In all, 1376 acute patients with stroke (median age 79 years; 49% women) were included. The median system delay from call to the EMS until (1) diagnosis (CT scan) and (2) arrival in a hospital ward was 3 h and 52 min and 4 h and 22 min, respectively. The system delay (1) was significantly shorter in county hospitals. (3) The study showed that 76% used the EMS (Gothenburg 71%; the county 79%; p<0.0001). (4) Priority 1 was given at the dispatch centre in 54% of cases. (5) Stroke was suspected in 65% of cases. A prenotification was sent in 32% (Gothenburg 52%; the county 20%; p<0.0001). CONCLUSIONS System delay is still long and only a small fraction of patients received thrombolysis. Three of four used the EMS (more frequent in the county). They were given the highest priority at the dispatch centre in half of the cases. Stroke was suspected in two-thirds of the cases, but a prenotification was seldom sent to the hospital.
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Affiliation(s)
- Birgitta Wireklint Sundström
- Faculty of Caring Science, Work Life and Social Welfare, Research Centre PreHospen, University of Borås, The Prehospital Research Centre of Western Sweden, Borås, Sweden
| | - Johan Herlitz
- Faculty of Caring Science, Work Life and Social Welfare, Research Centre PreHospen, University of Borås, The Prehospital Research Centre of Western Sweden, Borås, Sweden
| | - Per Olof Hansson
- Department of Molecular and Clinical Medicine/Cardiology, Sahlgrenska Academy, Institute of Medicine, University of Gothenburg, Gothenburg, Sweden
| | - Peter Brink
- Emergency Medical Service System, NU-Hospital Organisation,Trollhättan, Sweden
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Skolarus LE, Meurer WJ, Shanmugasundaram K, Adelman EE, Scott PA, Burke JF. Marked Regional Variation in Acute Stroke Treatment Among Medicare Beneficiaries. Stroke 2015; 46:1890-6. [PMID: 26038520 DOI: 10.1161/strokeaha.115.009163] [Citation(s) in RCA: 40] [Impact Index Per Article: 4.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/17/2015] [Accepted: 04/29/2015] [Indexed: 11/16/2022]
Abstract
BACKGROUND AND PURPOSE Little is known about how regions vary in their use of thrombolysis (intravenous tissue-type plasminogen activator and intra-arterial treatment) for acute stroke. We sought to determine regional variation in thrombolysis treatment and investigate the extent to which regional variation is accounted for by patient demographics, regional factors, and elements of stroke systems of care. METHODS Retrospective cross-sectional study of all fee-for-service Medicare patients with ischemic stroke admitted via the Emergency Department from 2007 to 2010 who were assigned to 1 of 3436 hospital service areas. Multilevel logistic regression was used to estimate regional thrombolysis rates, determine the variation in thrombolysis treatment attributable to the region and estimate thrombolysis treatment rates and disability prevented under varied improvement scenarios. RESULTS There were 844 241 ischemic stroke admissions of which 3.7% received intravenous tissue-type plasminogen activator and 0.5% received intra-arterial stroke treatment without or without intravenous tissue-type plasminogen activator over the 4-year period. The unadjusted proportion of patients with ischemic stroke who received thrombolysis varied from 9.3% in the highest treatment quintile compared with 0% in the lowest treatment quintile. Measured demographic and stroke system factors were weakly associated with treatment rates. Region accounted for 7% to 8% of the variation in receipt of thrombolysis treatment. If all regions performed at the level of 75th percentile region, ≈7000 additional patients with ischemic stroke would be treated with thrombolysis. CONCLUSIONS There is substantial regional variation in thrombolysis treatment. Future studies to determine features of high-performing thrombolysis treatment regions may identify opportunities to improve thrombolysis rates.
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Affiliation(s)
- Lesli E Skolarus
- From the Stroke Program, University of Michigan, Ann Arbor (L.E.S., W.J.M., E.E.A., P.A.S., J.F.B.); Department of Emergency Medicine, Ann Arbor, MI (W.J.M., P.A.S.); and University of Michigan Medical School, Ann Arbor (K.S.)
| | - William J Meurer
- From the Stroke Program, University of Michigan, Ann Arbor (L.E.S., W.J.M., E.E.A., P.A.S., J.F.B.); Department of Emergency Medicine, Ann Arbor, MI (W.J.M., P.A.S.); and University of Michigan Medical School, Ann Arbor (K.S.)
| | - Krithika Shanmugasundaram
- From the Stroke Program, University of Michigan, Ann Arbor (L.E.S., W.J.M., E.E.A., P.A.S., J.F.B.); Department of Emergency Medicine, Ann Arbor, MI (W.J.M., P.A.S.); and University of Michigan Medical School, Ann Arbor (K.S.)
| | - Eric E Adelman
- From the Stroke Program, University of Michigan, Ann Arbor (L.E.S., W.J.M., E.E.A., P.A.S., J.F.B.); Department of Emergency Medicine, Ann Arbor, MI (W.J.M., P.A.S.); and University of Michigan Medical School, Ann Arbor (K.S.)
| | - Phillip A Scott
- From the Stroke Program, University of Michigan, Ann Arbor (L.E.S., W.J.M., E.E.A., P.A.S., J.F.B.); Department of Emergency Medicine, Ann Arbor, MI (W.J.M., P.A.S.); and University of Michigan Medical School, Ann Arbor (K.S.)
| | - James F Burke
- From the Stroke Program, University of Michigan, Ann Arbor (L.E.S., W.J.M., E.E.A., P.A.S., J.F.B.); Department of Emergency Medicine, Ann Arbor, MI (W.J.M., P.A.S.); and University of Michigan Medical School, Ann Arbor (K.S.).
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Govindarajan P, Friedman BT, Delgadillo JQ, Ghilarducci D, Cook LJ, Grimes B, McCulloch CE, Johnston SC. Race and sex disparities in prehospital recognition of acute stroke. Acad Emerg Med 2015; 22:264-72. [PMID: 25728356 DOI: 10.1111/acem.12595] [Citation(s) in RCA: 15] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/19/2014] [Revised: 07/01/2014] [Accepted: 10/03/2014] [Indexed: 01/07/2023]
Abstract
OBJECTIVES The objective of this study was to examine prehospital provider recognition of stroke by race and sex. METHODS Diagnoses at emergency department (ED) and hospital discharge from a statewide database in California were linked to prehospital diagnoses from an electronic database from two counties in Northern California from January 2005 to December 2007 using probabilistic linkage. All patients 18 years and older, transported by ambulances (n = 309,866) within the two counties, and patients with hospital-based discharge diagnoses of stroke (n = 10,719) were included in the study. Logistic regression was used to analyze the independent association of race and sex with the correct prehospital diagnosis of stroke. RESULTS There were 10,719 patients discharged with primary diagnoses of stroke. Of those, 3,787 (35%) were transported by emergency medical services providers. Overall, 32% of patients ultimately diagnosed with stroke were identified in the prehospital setting. Correct prehospital recognition of stroke was lower among Hispanic patients (odds ratio [OR] = 0.77, 95% confidence interval [CI] 0.61 to 0.96), Asians (OR = 0.66, 95% CI 0.55 to 0.80), and others (OR = 0.71, 95% CI = 0.53 to 0.94), when compared with non-Hispanic whites, and in women compared with men (OR = 0.82, 95% CI = 0.71 to 0.94). Specificity for recognizing stroke was lower in females than males (OR = 0.84, 95% CI = 0.78 to 0.90). CONCLUSIONS Significant disparities exist in prehospital stroke recognition.
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Affiliation(s)
- Prasanthi Govindarajan
- The Department of Emergency Medicine; University of California at San Francisco; San Francisco CA
| | - Benjamin T. Friedman
- The School of Medicine; University of California at San Francisco; San Francisco CA
| | | | - David Ghilarducci
- Emergency Medical Services; American Medical Response; Santa Cruz CA
| | - Lawrence J. Cook
- The Department of Pediatrics; University of Utah; Salt Lake City UT
| | - Barbara Grimes
- The Department of Epidemiology and Biostatistics; University of California at San Francisco; San Francisco CA
| | - Charles E. McCulloch
- The Department of Epidemiology and Biostatistics; University of California at San Francisco; San Francisco CA
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Zhao Q, Yang L, Zuo Q, Zhu X, Zhang X, Wu Y, Yang L, Gao W, Li M. Instrument development and validation of the stroke pre-hospital delay behavior intention scale in a Chinese urban population. Health Qual Life Outcomes 2014; 12:170. [PMID: 25432795 PMCID: PMC4264611 DOI: 10.1186/s12955-014-0170-8] [Citation(s) in RCA: 8] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/26/2014] [Accepted: 11/12/2014] [Indexed: 01/12/2023] Open
Abstract
Background Several stroke impairment scales are currently available for stroke patients but none of them provide information regarding the pre-stroke behavioral intentions of high-risk stroke patients and their relatives. This study’s objective was to generate and validate a new written tool, the Stroke Pre-hospital Delay Behavior Intention (SPDBI) scale. It is suitable for use with high-risk stroke patients and their relatives to predict the likelihood of pre-hospital delay. Methods From a review of related studies, we formulated a prototype scale. We interviewed ten stroke patients in a semi-structured iterative process that included interviews with experts, high-risk patients, and their family members. Then, we pretested and filtered items. We next used a large sample size and factor analysis to determine the scale’s structure. Finally, we checked the reliability and validity of the scale. Results We identified five sub-domains (stroke warning signs, non-treatment justification, symptom attributions, habitual response style, and emergency system use). The SPDBI demonstrated good internal consistency and test-retest reliability (Cronbach’s α =0.808; Intraclass Correlation Coefficient [ICC] =0.797). Conclusions This SPDBI scale is a reliable, and valid measure of the likeliness of pre-hospital delay in high-risk stroke patients and their family members. It may provide scientific assessment for targeted health education intervention. Electronic supplementary material The online version of this article (doi:10.1186/s12955-014-0170-8) contains supplementary material, which is available to authorized users.
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Affiliation(s)
- Qiuli Zhao
- School of Nursing, The 2nd Affiliated Hospital of Harbin Medical University, Harbin Medical University, 246 Xuefu Road, Harbin, HeiLongJiang Province, 150086, China.
| | - Li Yang
- School of Nursing, The 2nd Affiliated Hospital of Harbin Medical University, Harbin Medical University, 246 Xuefu Road, Harbin, HeiLongJiang Province, 150086, China.
| | - Qingqing Zuo
- School of Nursing, The 2nd Affiliated Hospital of Harbin Medical University, Harbin Medical University, 246 Xuefu Road, Harbin, HeiLongJiang Province, 150086, China.
| | - Xuemei Zhu
- School of Nursing, The 2nd Affiliated Hospital of Harbin Medical University, Harbin Medical University, 246 Xuefu Road, Harbin, HeiLongJiang Province, 150086, China.
| | - Xiao Zhang
- School of Nursing, The 2nd Affiliated Hospital of Harbin Medical University, Harbin Medical University, 246 Xuefu Road, Harbin, HeiLongJiang Province, 150086, China.
| | - Yanni Wu
- Department of Nephrology, The 2nd Affiliated Hospital of Harbin Medical University, Harbin Medical University, Harbin, HeiLongJiang Province, 150086, China.
| | - Liu Yang
- School of Nursing, The 2nd Affiliated Hospital of Harbin Medical University, Harbin Medical University, 246 Xuefu Road, Harbin, HeiLongJiang Province, 150086, China.
| | - Wei Gao
- School of Nursing, The 2nd Affiliated Hospital of Harbin Medical University, Harbin Medical University, 246 Xuefu Road, Harbin, HeiLongJiang Province, 150086, China.
| | - Minghui Li
- School of Nursing, The 2nd Affiliated Hospital of Harbin Medical University, Harbin Medical University, 246 Xuefu Road, Harbin, HeiLongJiang Province, 150086, China.
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Disparities in Imaging Utilization for Acute Ischemic Stroke Based on Patient Insurance Status. AJR Am J Roentgenol 2014; 203:372-6. [DOI: 10.2214/ajr.13.12008] [Citation(s) in RCA: 19] [Impact Index Per Article: 1.9] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/18/2022]
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Patel MD, Brice JH, Moss C, Suchindran CM, Evenson KR, Rose KM, Rosamond WD. An evaluation of emergency medical services stroke protocols and scene times. PREHOSP EMERG CARE 2013; 18:15-21. [PMID: 24028711 DOI: 10.3109/10903127.2013.825354] [Citation(s) in RCA: 23] [Impact Index Per Article: 2.1] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/21/2022]
Abstract
BACKGROUND Acute stroke patients require immediate medical attention. Therefore, American Stroke Association guidelines recommend that for suspected stroke cases, emergency medical services (EMS) personnel spend less than 15 minutes on-scene at least 90% of the time. However, not all EMS providers include specific scene time limits in their stroke patient care protocols. OBJECTIVE We sought to determine whether having a protocol with a specific scene time limit was associated with less time EMS spent on scene. Methods. Stroke protocols from the 100 EMS systems in North Carolina were collected and abstracted for scene time instructions. Suspected stroke events occurring in 2009 were analyzed using data from the North Carolina Prehospital Medical Information System. Scene time was defined as the time from EMS arrival at the scene to departure with the patient. Quantile regression was used to estimate how the 90th percentile of the scene time distribution varied by systems with protocol instructions limiting scene time, adjusting for system patient volume and metropolitan status. RESULTS In 2009, 23 EMS systems in North Carolina had no instructions regarding scene time; 73 had general instructions to minimize scene time; and 4 had a specific limit for scene time (i.e., 10 or 15 min). Among 9,723 eligible suspected stroke events, mean scene time was 15.9 minutes (standard deviation 6.9 min) and median scene time was 15.0 minutes (90th percentile 24.3 min). In adjusted quantile regression models, the estimated reduction in the 90th percentile scene time, comparing protocols with a specific time limit to no instructions, was 2.2 minutes (95% confidence interval 1.3, 3.1 min). The difference in 90th percentile scene time between general and absent instructions was not statistically different (0.7 min [95% confidence interval -0.1, 1.4 min]). CONCLUSION Protocols with specific scene time limits were associated with EMS crews spending less time at the scene while general instructions were not. These findings suggest EMS systems can modestly improve scene times for stroke by specifying a time limit in their protocols.
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Affiliation(s)
- Mehul D Patel
- Received May 15, 2013 from the Departments of Epidemiology (MDP, KRE, WDR) and Biostatistics (CMS), Gillings School of Global Public Health, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina; the Department of Emergency Medicine (JHB, CM), School of Medicine, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina; and SRA International (KMR), Durham, North Carolina. Revision received June 14, 2013; accepted for publication June 20, 2013
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