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Article ; Online: Response by Kummer et al to Letter Regarding Article, "History of Stroke Is Independently Associated With In-Hospital Death in Patients With COVID-19".

Kummer, Benjamin R / Klang, Eyal / Jetté, Nathalie

2020 Volume 52, Issue 1, Page(s) e31

MeSH term(s)	COVID-19 ; Hospital Mortality ; Humans ; Medical History Taking ; SARS-CoV-2 ; Stroke
Language	English
Publishing date	2020-12-28
Publishing country	United States
Document type	Letter ; Comment
ZDB-ID	80381-9
ISSN	1524-4628 ; 0039-2499 ; 0749-7954
ISSN (online)	1524-4628
ISSN	0039-2499 ; 0749-7954
DOI	10.1161/STROKEAHA.120.032886
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Article ; Online: Latent class analysis of eHealth behaviors among adults with epilepsy.

Kee, Dustin / Jetté, Nathalie / Blank, Leah J / Kummer, Benjamin R / Mazumdar, Madhu / Agarwal, Parul

Epilepsia

2022 Volume 64, Issue 2, Page(s) 479–499

Abstract: Objective: The objective of this study was to determine the proportions of uptake and factors associated with electronic health (eHealth) behaviors among adults with epilepsy.: Methods: The 2013, 2015, and 2017 National Health Interview Surveys were ... ...

Abstract	Objective: The objective of this study was to determine the proportions of uptake and factors associated with electronic health (eHealth) behaviors among adults with epilepsy. Methods: The 2013, 2015, and 2017 National Health Interview Surveys were analyzed. We assessed the proportions of use of five domains of eHealth in those with epilepsy: looked up health information on the internet, filled a prescription on the internet, scheduled a medical appointment on the internet, communicated with a health care provider via email, and used chat groups to learn about health topics. Multivariate logistic regressions were conducted to identify factors associated with any eHealth behaviors among those with active epilepsy. Latent class analysis was performed to identify underlying patterns of eHealth activity. Survey participants were classified into three discrete classes: (1) frequent, (2) infrequent, and (3) nonusers of eHealth. Multinomial logistic regression was performed to identify factors associated with frequency of eHealth use. Results: There were 1770 adults with epilepsy, of whom 65.87% had at least one eHealth behavior in the prior year. By domain, 62.61% looked up health information on the internet, 15.81% filled a prescription on the internet, 14.95% scheduled a medical appointment on the internet, 17.20% communicated with a health care provider via email, and 8.27% used chat groups to learn about health topics. Among those with active epilepsy, female sex, more frequent computer usage, and internet usage were associated with any eHealth behavior. Female sex and frequent computer use were associated with frequent eHealth use as compared to nonusers. Significance: A majority of persons with epilepsy were found to use at least one form of eHealth. Various technological and demographic factors were associated with eHealth behaviors. Individuals with lower eHealth behaviors should be provided with targeted interventions that address barriers to the adoption of these technologies.
MeSH term(s)	Humans ; Adult ; Female ; Latent Class Analysis ; Telemedicine ; Surveys and Questionnaires ; Patient Acceptance of Health Care ; Electronics ; Internet
Language	English
Publishing date	2022-12-28
Publishing country	United States
Document type	Journal Article ; Research Support, Non-U.S. Gov't
ZDB-ID	216382-2
ISSN	1528-1167 ; 0013-9580
ISSN (online)	1528-1167
ISSN	0013-9580
DOI	10.1111/epi.17483
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Zs.A 517: Show issues			Location: Je nach Verfügbarkeit (siehe Angabe bei Bestand) bis Jg. 1994: Bestellungen von Artikeln über das Online-Bestellformular Jg. 1995 - 2021: Lesesall (1.OG) ab Jg. 2022: Lesesaal (EG)
Zs.MO 475: Show issues

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Article ; Online: Clinical Decision Support for Cerebral Perfusion Optimization After Traumatic Brain Injury.

Schmidt, J Michael / Kummer, Benjamin R

Critical care medicine

2016 Volume 44, Issue 10, Page(s) 1958–1960

MeSH term(s)	Brain ; Brain Injuries, Traumatic ; Cerebrovascular Circulation ; Decision Support Systems, Clinical ; Humans ; Intracranial Pressure
Language	English
Publishing date	2016-09-16
Publishing country	United States
Document type	Editorial ; Comment
ZDB-ID	197890-1
ISSN	1530-0293 ; 0090-3493
ISSN (online)	1530-0293
ISSN	0090-3493
DOI	10.1097/CCM.0000000000001918
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Zs.A 1261: Show issues

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Article ; Online: Healthcare utilization impacts of an eConsult program for headache at an academic medical center.

Downes, Margaret H / Morgenstern, Rachelle / Naasan, Georges / Patterson, Shanna / Pace, Anna / Agarwal, Parul / Shin, Susan / Abrams, Rory / Mueller, Bridget / Young, James / Tamler, Ronald / Vickrey, Barbara G / Kummer, Benjamin R

Journal of telemedicine and telecare

2023 , Page(s) 1357633X231207908

Abstract: Introduction: Interprofessional consultations ("eConsults") can reduce healthcare utilization. However, the impact of eConsults on healthcare utilization remains poorly characterized among patients with headache.: Methods: We performed a ... ...

Abstract	Introduction: Interprofessional consultations ("eConsults") can reduce healthcare utilization. However, the impact of eConsults on healthcare utilization remains poorly characterized among patients with headache. Methods: We performed a retrospective, 1:1 matched cohort study comparing patients evaluated for headache via eConsult request or in-person referral at the Mount Sinai Health System in New York. Groups were matched on clinical and demographic characteristics. Our primary outcome was one or more outpatient headache-related encounters in 6 months following referral date. Secondary outcomes included one or more all-cause outpatient neurology and headache-related emergency department (ED) encounters during the same period. We used univariable and multivariable logistic regression to model associations between independent variables and outcomes. Results: We identified 74 patients with headache eConsults who were matched to 74 patients with in-person referrals. Patients in the eConsult group were less likely to achieve the primary outcome (29.7% vs 62.2%, Discussion: In comparison to in-person referrals, eConsult requests for headache were associated with reduced likelihood of outpatient neurology encounters in the short-term but not with differential use of headache-related ED encounters. Larger-scale, prospective studies should validate our findings and assess patient outcomes.
Language	English
Publishing date	2023-10-30
Publishing country	England
Document type	Journal Article
ZDB-ID	1340281-x
ISSN	1758-1109 ; 1357-633X
ISSN (online)	1758-1109
ISSN	1357-633X
DOI	10.1177/1357633X231207908
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Zs.A 4525: Show issues

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Article ; Online: Disparities in telehealth utilization in patients with pain during COVID-19.

Mueller, Bridget R / Lawrence, Steven / Benn, Emma / Nirenberg, Sharon / Kummer, Benjamin / Jette, Nathalie / George, Mary-Catherine / Robinson-Papp, Jessica

Pain reports

2022 Volume 7, Issue 3, Page(s) e1001

Abstract: Introduction: The shift from in-person visits to telehealth visits during the COVID-19 pandemic presented unique challenges for patients with pain. Disparities in health care access already existed, and the impact of telehealth on these inequities has ... ...

Abstract	Introduction: The shift from in-person visits to telehealth visits during the COVID-19 pandemic presented unique challenges for patients with pain. Disparities in health care access already existed, and the impact of telehealth on these inequities has not been studied. Objectives: To identify sociodemographic characteristics of patients with pain obtaining care through video, telephone, and in-person visits as social distancing restrictions evolved during the COVID-19 pandemic. Methods: Using our institutional clinical data warehouse, we identified 3314 patients with pain receiving care at a large academic institution in New York City during a baseline period (September 23, 2019-March 22, 2020) and counted telephone, video, and in-person visits during the following conditions: a shutdown period (March 23, 2020-May 23, 2020), when nonessential in-person visits were strictly limited, and a reopening period (May 23, 2020-September 23, 2020), when restrictions were relaxed and in-person visits were available. Patients were categorized into 4 groups based on the technology used to complete a visit: (1) video, (2) telephone, (3) in-person, and (4) no visit. Results: Patients who were older, publicly insured, and identified as Black or Hispanic were overrepresented in the telephone visit group during shutdown and the in-person group during reopening. A video visit during shutdown increased the likelihood of continued video visit use during reopening despite the return of in-person visits. Conclusions: Results show differences in how patients with pain accessed clinical care in a socially distanced world and that flexibility in method of health care delivery may reduce barriers to access. Future research will identify factors (eg, Internet access, digital literacy, provider-patient relationships) driving heterogeneity in telehealth use in patients with pain.
Language	English
Publishing date	2022-04-14
Publishing country	United States
Document type	Journal Article
ISSN	2471-2531
ISSN (online)	2471-2531
DOI	10.1097/PR9.0000000000001001
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Article: Comparative analysis, applications, and interpretation of electronic health record-based stroke phenotyping methods.

Thangaraj, Phyllis M / Kummer, Benjamin R / Lorberbaum, Tal / Elkind, Mitchell S V / Tatonetti, Nicholas P

BioData mining

2020 Volume 13, Issue 1, Page(s) 21

Abstract: Background: Accurate identification of acute ischemic stroke (AIS) patient cohorts is essential for a wide range of clinical investigations. Automated phenotyping methods that leverage electronic health records (EHRs) represent a fundamentally new ... ...

Abstract	Background: Accurate identification of acute ischemic stroke (AIS) patient cohorts is essential for a wide range of clinical investigations. Automated phenotyping methods that leverage electronic health records (EHRs) represent a fundamentally new approach cohort identification without current laborious and ungeneralizable generation of phenotyping algorithms. We systematically compared and evaluated the ability of machine learning algorithms and case-control combinations to phenotype acute ischemic stroke patients using data from an EHR. Materials and methods: Using structured patient data from the EHR at a tertiary-care hospital system, we built and evaluated machine learning models to identify patients with AIS based on 75 different case-control and classifier combinations. We then estimated the prevalence of AIS patients across the EHR. Finally, we externally validated the ability of the models to detect AIS patients without AIS diagnosis codes using the UK Biobank. Results: Across all models, we found that the mean AUROC for detecting AIS was 0.963 ± 0.0520 and average precision score 0.790 ± 0.196 with minimal feature processing. Classifiers trained with cases with AIS diagnosis codes and controls with no cerebrovascular disease codes had the best average F1 score (0.832 ± 0.0383). In the external validation, we found that the top probabilities from a model-predicted AIS cohort were significantly enriched for AIS patients without AIS diagnosis codes (60-150 fold over expected). Conclusions: Our findings support machine learning algorithms as a generalizable way to accurately identify AIS patients without using process-intensive manual feature curation. When a set of AIS patients is unavailable, diagnosis codes may be used to train classifier models.
Language	English
Publishing date	2020-12-07
Publishing country	England
Document type	Journal Article
ZDB-ID	2438773-3
ISSN	1756-0381
ISSN	1756-0381
DOI	10.1186/s13040-020-00230-x
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Article ; Online: History of Stroke Is Independently Associated With In-Hospital Death in Patients With COVID-19.

Kummer, Benjamin R / Klang, Eyal / Stein, Laura K / Dhamoon, Mandip S / Jetté, Nathalie

Stroke

2020 Volume 51, Issue 10, Page(s) 3112–3114

Abstract: Background and purpose: In December 2019, an outbreak of severe acute respiratory syndrome coronavirus causing coronavirus disease 2019 (COVID-19) occurred in China, and evolved into a worldwide pandemic. It remains unclear whether the history of ... ...

Abstract	Background and purpose: In December 2019, an outbreak of severe acute respiratory syndrome coronavirus causing coronavirus disease 2019 (COVID-19) occurred in China, and evolved into a worldwide pandemic. It remains unclear whether the history of cerebrovascular disease is associated with in-hospital death in patients with COVID-19. Methods: We conducted a retrospective, multicenter cohort study at Mount Sinai Health System in New York City. Using our institutional data warehouse, we identified all adult patients who were admitted to the hospital between March 1, 2020 and May 1, 2020 and had a positive nasopharyngeal swab polymerase chain reaction test for severe acute respiratory syndrome coronavirus in the emergency department. Using our institutional electronic health record, we extracted clinical characteristics of the cohort, including age, sex, and comorbidities. Using multivariable logistic regression to control for medical comorbidities, we modeled the relationship between history of stroke and all-cause, in-hospital death. Results: We identified 3248 patients, of whom 387 (11.9%) had a history of stroke. Compared with patients without history of stroke, patients with a history of stroke were significantly older, and were significantly more likely to have a history of all medical comorbidities except for obesity, which was more prevalent in patients without a history of stroke. Compared with patients without history of stroke, patients with a history of stroke had higher in-hospital death rates during the study period (48.6% versus 31.7%, Conclusions: We found that history of stroke was associated with in-hospital death among hospitalized patients with COVID-19. Further studies should confirm these results.
MeSH term(s)	Aged ; Aged, 80 and over ; Betacoronavirus ; COVID-19 ; Cause of Death ; Comorbidity ; Coronavirus Infections/mortality ; Female ; Hospital Mortality ; Humans ; Logistic Models ; Male ; Middle Aged ; Multivariate Analysis ; New York City/epidemiology ; Pandemics ; Pneumonia, Viral/mortality ; Retrospective Studies ; SARS-CoV-2 ; Stroke/epidemiology
Keywords	covid19
Language	English
Publishing date	2020-08-10
Publishing country	United States
Document type	Journal Article ; Observational Study
ZDB-ID	80381-9
ISSN	1524-4628 ; 0039-2499 ; 0749-7954
ISSN (online)	1524-4628
ISSN	0039-2499 ; 0749-7954
DOI	10.1161/STROKEAHA.120.030685
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Zs.A 448: Show issues

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Jg. 1995 - 2021: Lesesall (1.OG)
ab Jg. 2022: Lesesaal (EG)

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Article: Usage Patterns of Web-Based Stroke Calculators in Clinical Decision Support: Retrospective Analysis.

Kummer, Benjamin / Shakir, Lubaina / Kwon, Rachel / Habboushe, Joseph / Jetté, Nathalie

JMIR medical informatics

2021 Volume 9, Issue 8, Page(s) e28266

Abstract: Background: Clinical scores are frequently used in the diagnosis and management of stroke. While medical calculators are increasingly important support tools for clinical decisions, the uptake and use of common medical calculators for stroke remain ... ...

Abstract	Background: Clinical scores are frequently used in the diagnosis and management of stroke. While medical calculators are increasingly important support tools for clinical decisions, the uptake and use of common medical calculators for stroke remain poorly characterized. Objective: We aimed to describe use patterns in frequently used stroke-related medical calculators for clinical decisions from a web-based support system. Methods: We conducted a retrospective study of calculators from MDCalc, a web-based and mobile app-based medical calculator platform based in the United States. We analyzed metadata tags from MDCalc's calculator use data to identify all calculators related to stroke. Using relative page views as a measure of calculator use, we determined the 5 most frequently used stroke-related calculators between January 2016 and December 2018. For all 5 calculators, we determined cumulative and quarterly use, mode of access (eg, app or web browser), and both US and international distributions of use. We compared cumulative use in the 2016-2018 period with use from January 2011 to December 2015. Results: Over the study period, we identified 454 MDCalc calculators, of which 48 (10.6%) were related to stroke. Of these, the 5 most frequently used calculators were the CHA Conclusions: The most frequently used stroke calculators were the CHA
Language	English
Publishing date	2021-08-02
Publishing country	Canada
Document type	Journal Article
ZDB-ID	2798261-0
ISSN	2291-9694
ISSN	2291-9694
DOI	10.2196/28266
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Article: Ischemic Stroke After Emergency Department Discharge for Symptoms of Transient Neurological Attack.

Parikh, Neal S / Merkler, Alexander E / Kummer, Benjamin R / Kamel, Hooman

The Neurohospitalist

2018 Volume 8, Issue 3, Page(s) 135–140

Abstract: Background and purpose: The significance of transient neurological attack (TNA) symptoms is unclear. We sought to determine the risk of ischemic stroke after discharge from the emergency department (ED) with a diagnosis consistent with symptoms of TNA.!# ...

Abstract	Background and purpose: The significance of transient neurological attack (TNA) symptoms is unclear. We sought to determine the risk of ischemic stroke after discharge from the emergency department (ED) with a diagnosis consistent with symptoms of TNA. Methods: Using administrative claims data, we identified patients discharged from EDs in New York between 2006 and 2012 with a primary discharge diagnosis of a TNA symptom, defined as altered mental status, generalized weakness, and sensory changes. The primary outcome was ischemic stroke. We used Kaplan-Meier survival statistics to calculate cumulative rates, and Cox regression to compare stroke risk after TNA versus after transient ischemic attack (TIA; positive control) or renal colic (negative control) while adjusting for demographics and vascular risk factors. Results: Of 499 369 patients diagnosed with a TNA symptom and discharged from the ED, 7756 were hospitalized for ischemic stroke over a period of 4.7 (±1.9) years. At 90 days, the cumulative stroke rate was 0.29% (95% confidence interval [CI]: 0.28%-0.31%) after TNA symptoms versus 2.08% (95% CI: 1.89%-2.28%) after TIA and 0.03% (95% CI: 0.02%-0.04%) after renal colic. The hazard ratio (HR) of stroke was higher after TNA than after renal colic (HR: 2.13; 95% CI: 1.90-2.40) but significantly lower than after TIA (HR: 0.47; 95% CI: 0.44-0.50). Compared to TIA, TNA was less strongly associated with stroke among patients under 60 years of age compared to those over 60. Conclusions: Patients discharged from the ED with TNA symptoms faced a higher risk of ischemic stroke than patients with renal colic, but the magnitude of stroke risk was low, particularly compared to TIA.
Language	English
Publishing date	2018-02-18
Publishing country	United States
Document type	Journal Article
ZDB-ID	2629083-2
ISSN	1941-8752 ; 1941-8744
ISSN (online)	1941-8752
ISSN	1941-8744
DOI	10.1177/1941874417750996
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Article: Teleneurology Expansion in Response to the COVID-19 Outbreak at a Tertiary Health System in New York City.

Kummer, Benjamin R / Sweetnam, Chloe / Vickrey, Barbara G / Naasan, Georges / Harvey, Dayneen / Gallagher, Kimberly / Jetté, Nathalie

Neurology. Clinical practice

2021 Volume 11, Issue 2, Page(s) e102–e111

Abstract: Objective: To assess the implementation of teleneurology (TN), including patient and clinician experiences, during the coronavirus respiratory disease 2019 (COVID-19) pandemic.: Methods: We studied synchronous (video visit) and asynchronous (store- ... ...

Abstract	Objective: To assess the implementation of teleneurology (TN), including patient and clinician experiences, during the coronavirus respiratory disease 2019 (COVID-19) pandemic. Methods: We studied synchronous (video visit) and asynchronous (store-and-forward, patient-portal evaluation, remote monitoring) TN utilization in the Mount Sinai Health System Neurology Department in New York, 2 months before and after the start of our department's response to the pandemic in mid-March 2020. Weekly division meetings enabled ongoing assessments and analysis of barriers and facilitators according to the Consolidated Framework for Implementation Research and the Expert Recommendations for Implementing Change models. We used postvisit surveys of clinicians (from April 13 to May 15, 2020) and patients (from May 11 to 15, 2020) to determine technology platforms used, and TN experience and acceptability, using Likert scales (1 = very poor/unlikely to 5 = very good/likely). Results: Over the 4-month period, 117 TN clinicians (n = 14 subspecialties) conducted 4,225 TN visits with 3,717 patients (52 pre- vs 4,173 post-COVID-19). No asynchronous TN services were delivered. Post-COVID-19, the number of TN clinicians, subspecialties performing TN, and visits increased by 963%, 133%, and 7,925%, respectively. Mean acceptability among patients and clinicians was 4.7 (SD 0.6) and 3.4 (SD 1.6), respectively. Most video visits were completed using Epic MyChart (78.5%) and Zoom (8.1%). TN implementation facilitators included Medicare geographic restriction waivers, development of clinician educational materials, and MyChart outreach programs for patients experiencing technical difficulties. Conclusions: A significant expansion of TN utilization accompanied the COVID-19 response. Patients found TN more acceptable than did clinicians. Proactive application of an implementation framework facilitated rapid and effective TN expansion.
Language	English
Publishing date	2021-04-02
Publishing country	United States
Document type	Journal Article
ZDB-ID	2645818-4
ISSN	2163-0933 ; 2163-0402
ISSN (online)	2163-0933
ISSN	2163-0402
DOI	10.1212/CPJ.0000000000001057
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