Relevant bibliographies by topics / Mount Sinai Hospital (New York

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Academic literature on the topic 'Mount Sinai Hospital (New York'

Author: Grafiati
Published: 4 June 2021
Last updated: 26 February 2023

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Journal articles on the topic "Mount Sinai Hospital (New York"

1

N/A. "The Mount Sinai Hospital, New York, Names New President." Journal Of Investigative Medicine 52, no. 02 (2004): 082. http://dx.doi.org/10.2310/6650.2004.17769.

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Harden, Cynthia L. "Introducing New Guidelines on Sudden Unexpected Death in Epilepsy." US Endocrinology 13, no. 02 (2017): 65. http://dx.doi.org/10.17925/use.2017.13.02.65.

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Cynthia L Harden, MD, received her medical degree at the University of Wisconsin. She trained in internal medicine at Mount Sinai St Luke’s Hospital and neurology at Mount Sinai Hospital, both in New York City, and in clinical neurophysiology at Albert Einstein College of Medicine in the Bronx. She served most of her career at Weill Cornell College of Medicine, where she became Professor of Neurology. Dr Harden serves as Chair of the Guideline Development, Dissemination and Implementation Subcommittee of the American Academy of Neurology (AAN). In 2016, she was also elected Chair of AAN’s Epilepsy Section for a 2-year term.
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Harden, Cynthia L. "Introducing New Guidelines on Sudden Unexpected Death in Epilepsy." US Neurology 13, no. 02 (2017): 65. http://dx.doi.org/10.17925/usn.2017.13.02.65.

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Cynthia L Harden, MD, received her medical degree at the University of Wisconsin. She trained in internal medicine at Mount Sinai St Luke’s Hospital and neurology at Mount Sinai Hospital, both in New York City, and in clinical neurophysiology at Albert Einstein College of Medicine in the Bronx. She served most of her career at Weill Cornell College of Medicine, where she became Professor of Neurology. Dr Harden serves as Chair of the Guideline Development, Dissemination and Implementation Subcommittee of the American Academy of Neurology (AAN). In 2016, she was also elected Chair of AAN’s Epilepsy Section for a 2-year term.
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Adams, Annmarie, and Mary Anne Poutanen. "Architecture, Religion, and Tuberculosis in Sainte-Agathe-des-Monts, Quebec1." Scientia Canadensis 32, no. 1 (July 7, 2009): 1–19. http://dx.doi.org/10.7202/037627ar.

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Abstract This paper explores the architecture of the Mount Sinai Sanatorium in Sainte-Agathe-des-Monts (Qc) to disentangle the role of religion in the treatment of tuberculosis. In particular, we analyze the design of Mount Sinai, the jewel in the crown of Jewish philanthropy in Montreal, in relation to that of the nearby Laurentian Sanatorium. While Mount Sinai offered free treatment to the poor in a stunning, Art Deco building of 1930, the Protestant hospital had by then served paying patients for more than two decades in a purposefully home-like, Tudor-revival setting. Using architectural historian Bernard Herman's concept of embedded landscapes, we show how the two hospitals differed in terms of their relationship to site, access, and, most importantly, to city, knowledge, and community. Architects Scopes & Feustmann, who designed the Laurentian hospital, operated an office at Saranac Lake, New York, America's premier destination for consumptives. The qualifications of Mount Sinai architects Spence & Goodman, however, derived from their experience with Jewish institutions in Montreal. Following Herman's approach to architecture through movement and context, how did notions of medical therapy and Judaism intersect in the plans of Mount Sinai?
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Geller, Stephen A. "Surgical pathology in the 20th century at The Mount Sinai Hospital, New York." Seminars in Diagnostic Pathology 25, no. 3 (August 2008): 178–89. http://dx.doi.org/10.1053/j.semdp.2008.06.003.

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6

Silverman, Lewis R., James F. Holland, Erin P. Demakos, Anna Gattani, and Janet Cuttner. "5-Azacytidine in myelodysplastic syndromes (MDS): The experience at mount Sinai Hospital, New York." Leukemia Research 18 (January 1994): 21. http://dx.doi.org/10.1016/0145-2126(94)90171-6.

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7

Holcombe, Randall F., Michelle Evangelista, and Frances Cartwright. "Delivery of Quality Oncology Care in a Large, Urban Practice: A Primer." Journal of Oncology Practice 12, no. 10 (October 2016): 892–97. http://dx.doi.org/10.1200/jop.2016.015040.

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A comprehensive quality improvement program is critically important for participation in value-based reimbursement models. Seven essential characteristics must be addressed in the development of a cancer-focused quality program. These include leadership, environment, engagement, ethos, metrics, accountability, and sustainability (Q=LE3MAS). This article describes how to address each essential characteristic and provides examples from the experience at Mount Sinai Hospital, a large, urban, academic hospital/health system in New York City.
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8

Ornstein, Katherine, Cameron R. Hernandez, Linda V. DeCherrie, and Theresa A. Soriano. "The Mount Sinai (New York) Visiting Doctors Program: Meeting the Needs of the Urban Homebound Population." Care Management Journals 12, no. 4 (December 2011): 139–43. http://dx.doi.org/10.1891/1521-0987.12.4.159.

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The Mount Sinai Visiting Doctors program, a joint program of Mount Sinai Medical Center’s Departments of Medicine and Geriatrics, is a large multidisciplinary teaching, research, and clinical care initiative serving homebound adults in Manhattan since 1995. Caring for more than 1,000 patients annually, the physicians of Visiting Doctors make more than 6,000 urgent and routine visits each year, making it the largest program of its kind in the country. Services include 24–hour physician availability, palliative care, social work case management, collaboration with nursing agencies, and in-home specialty consultation. The program serves many individuals who have previously received inadequate and inconsistent medical care. Patients are referred by social service agencies, local physicians, and hospitals and are primarily frail older individuals with complex needs. Funded by Mount Sinai and private support, the program serves as a major teaching site for medical, nursing, and social work trainees interested in home-based primary care.
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9

Trivedi, Vrinda, Raymonde E. Jean, Frank Genese, Katherine A. Fuhrmann, Anjeet K. Saini, Van Derick Mangulabnan, and Chirag Bavishi. "Impact of Obesity on Outcomes in a Multiethnic Cohort of Medical Intensive Care Unit Patients." Journal of Intensive Care Medicine 33, no. 2 (May 2, 2016): 97–103. http://dx.doi.org/10.1177/0885066616646099.

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Purpose: To examine the association of obesity with in-hospital mortality and complications during critical illness. Methods: We performed a retrospective analysis of a multiethnic cohort of 699 patients admitted to medical intensive care unit between January 2010 and May 2011 at Mount Sinai St. Luke’s and Mount Sinai West Hospitals, tertiary care centers in New York City. Multivariate logistic regression analysis was used to evaluate the association between obesity (body mass index [BMI] ≥ 30] and in-hospital mortality. Subgroup analysis was performed in elderly patients (age ≥65 years). Results: Compared to normal BMI, obese patients had lower in-hospital mortality (24.4% vs 17.6%, P = .04). On multivariate analysis, obesity was independently associated with lower in-hospital mortality (odds ratio [OR]: 0.49, 95% confidence interval [CI]: 0.27-0.89, P = .018). There was no significant difference in rates of mechanical ventilation, reintubation, and vasopressor requirement across BMI categories. In subgroup analysis, elderly obese patients did not display lower in-hospital mortality (adjusted OR: 0.85, 95% CI: 0.40-1.82, P = .68). Conclusion: Our study supports the hypothesis that obesity is associated with decreased mortality during critical illness. However, this finding was not observed among elderly obese patients. Further studies should explore the interaction between age, obesity, and outcomes in critical illness.
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10

Paranjpe, Ishan, Adam J. Russak, Jessica K. De Freitas, Anuradha Lala, Riccardo Miotto, Akhil Vaid, Kipp W. Johnson, et al. "Retrospective cohort study of clinical characteristics of 2199 hospitalised patients with COVID-19 in New York City." BMJ Open 10, no. 11 (November 2020): e040736. http://dx.doi.org/10.1136/bmjopen-2020-040736.

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ObjectiveThe COVID-19 pandemic is a global public health crisis, with over 33 million cases and 999 000 deaths worldwide. Data are needed regarding the clinical course of hospitalised patients, particularly in the USA. We aimed to compare clinical characteristic of patients with COVID-19 who had in-hospital mortality with those who were discharged alive.DesignDemographic, clinical and outcomes data for patients admitted to five Mount Sinai Health System hospitals with confirmed COVID-19 between 27 February and 2 April 2020 were identified through institutional electronic health records. We performed a retrospective comparative analysis of patients who had in-hospital mortality or were discharged alive.SettingAll patients were admitted to the Mount Sinai Health System, a large quaternary care urban hospital system.ParticipantsParticipants over the age of 18 years were included.Primary outcomesWe investigated in-hospital mortality during the study period.ResultsA total of 2199 patients with COVID-19 were hospitalised during the study period. As of 2 April, 1121 (51%) patients remained hospitalised, and 1078 (49%) completed their hospital course. Of the latter, the overall mortality was 29%, and 36% required intensive care. The median age was 65 years overall and 75 years in those who died. Pre-existing conditions were present in 65% of those who died and 46% of those discharged. In those who died, the admission median lymphocyte percentage was 11.7%, D-dimer was 2.4 μg/mL, C reactive protein was 162 mg/L and procalcitonin was 0.44 ng/mL. In those discharged, the admission median lymphocyte percentage was 16.6%, D-dimer was 0.93 μg/mL, C reactive protein was 79 mg/L and procalcitonin was 0.09 ng/mL.ConclusionsIn our cohort of hospitalised patients, requirement of intensive care and mortality were high. Patients who died typically had more pre-existing conditions and greater perturbations in inflammatory markers as compared with those who were discharged.
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Books on the topic "Mount Sinai Hospital (New York"

1

Barbara, Niss, ed. This house of noble deeds: The Mount Sinai Hospital, 1852-2002. New York: New York University Press, 2002.

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2

Lewis, Marjorie Gulla. The Sinai nurse: A history of nursing at the Mount Sinai Hospital, New York, New York, 1852-2000. West Kennebunk, Me: Phoenix Pub., 2001.

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Gary, Rosenberg, ed. The social work-medicine relationship: 100 years at Mount Sinai. New York: Haworth Social Work Practice Press, 2006.

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4

Helen, Rehr, Rosenberg Gary, and Blumenfield Susan, eds. Creative social work in health care: Clients, the community, and your organization. New York: Springer Pub. Co., 1998.

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5

J, Levy Norman, ed. In the matter of a public hearing concerning construction alternatives for the improvement of Route 25-A in the Rocky Point-Miller Place-Mount Sinai area of Suffolk County, Long Island, New York: Proceedings, October 8, 1986 : before the New York State Senate Standing Committee on Transportation. Albany, NY: Pauline E. Williman, certified shorthand reporter, 1986.

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6

Niss, Barbara, and Jr Arthur H. Aufses. This House of Noble Deeds: The Mount Sinai Hospital, 1852-2002. NYU Press, 2002.

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Niss, Barbara, and Arthur H. Aufses Jr. This House of Noble Deeds: The Mount Sinai Hospital, 1852-2002. New York University Press, 2002.

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8

Rehr, Helen, and Rosenberg Gary. Social Work-Medicine Relationship: 100 Years at Mount Sinai. Taylor & Francis Group, 2012.

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Rehr, Helen, and Rosenberg Gary. Social Work-Medicine Relationship: 100 Years at Mount Sinai. Taylor & Francis Group, 2012.

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Rehr, Helen, and Rosenberg Gary. Social Work-Medicine Relationship: 100 Years at Mount Sinai. Taylor & Francis Group, 2012.

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Book chapters on the topic "Mount Sinai Hospital (New York"

1

Cui, Wanting, and Joseph Finkelstein. "Using Machine Learning to Identify No-Show Telemedicine Encounters in a New York City Hospital." In Studies in Health Technology and Informatics. IOS Press, 2022. http://dx.doi.org/10.3233/shti220729.

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No-show visits are a serious problem for healthcare centers. It costs a major hospital over 15 million dollars annually. The goal of this paper was to build machine learning models to identify potential no-show telemedicine visits and to identify significant factors that affect no-show visits. 257,293 telemedicine sessions and 152,164 unique patients were identified in Mount Sinai Health System between March 2020 and December 2020. 5,124 (2%) of these sessions were no-show encounters. Extreme Gradient Boosting (XGB) with under-sampling was the best machine learning model to identify no-show visits using telemedicine service. The accuracy was 0.74, with an AUC score of 0.68. Patients with previous no-show encounters, non-White or non-Asian patients, and patients living in Bronx and Manhattan were all important factors for no-show encounters. Furthermore, providers’ specialties in psychiatry and nutrition, and social workers were more susceptible to higher patient no-show rates.
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"22. New Talent: Mount Sinai Hospital and Women’s College Hospital." In Partnership for Excellence. Toronto: University of Toronto Press, 2012. http://dx.doi.org/10.3138/9781442664036-022.

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"21. About Icahn School of Medicine at Mount Sinai and the James J. Peters Veterans ’ Administration Medical Center, New York City, United States." In Adolescent Psychiatry, 237–38. De Gruyter, 2013. http://dx.doi.org/10.1515/9783110316612.237.

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Shah-Mohammadi, Fatemeh, Wanting Cui, Keren Bachi, Yasmin Hurd, and Joseph Finkelstein. "Latent COVID-19 Clusters in Patients with Opioid Misuse." In Studies in Health Technology and Informatics. IOS Press, 2022. http://dx.doi.org/10.3233/shti210874.

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The goal of this paper is to apply unsupervised machine learning techniques in order to discover latent clusters in patients who have opioid misuse and also undergone COVID-19 testing. Target dataset has been constructed based on COVID-19 testing results at Mount Sinai Health System and opioid treatment program (OTP) information from New York State Office of Addiction Service and Support (OASAS). The dataset was preprocessed using factor analysis for mixed data (FAMD) method and then K-means algorithm along with elbow method were used to determine the number of optimal clusters. Four patient clusters were identified among which the fourth cluster constituted the maximum percentage of positive COVID-19 test results (20%). Compared to the other clusters, this cluster has the highest percentage of African Americans. This cluster has also the highest mortality rate (16.52%), hospitalization rate after receiving the COVID-19 test result (72.17%, use of ventilator (7.83%) and ICU admission rate (47.83%). In addition, this cluster has the highest percentage of patients with at least one chronic disease (99.13%) and age-adjusted comorbidity score more than 1 (83.48%). Longer participation in OTP was associated with the highest morbidity and mortality from COVID-19.
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