46 results on '"Jayson S. Marwaha"'
Search Results
2. An operational guide to translational clinical machine learning in academic medical centers
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Mukund Poddar, Jayson S. Marwaha, William Yuan, Santiago Romero-Brufau, and Gabriel A. Brat
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Computer applications to medicine. Medical informatics ,R858-859.7 - Abstract
Abstract Few published data science tools are ever translated from academia to real-world clinical settings for which they were intended. One dimension of this problem is the software engineering task of turning published academic projects into tools that are usable at the bedside. Given the complexity of the data ecosystem in large health systems, this task often represents a significant barrier to the real-world deployment of data science tools for prospective piloting and evaluation. Many information technology companies have created Machine Learning Operations (MLOps) teams to help with such tasks at scale, but the low penetration of home-grown data science tools in regular clinical practice precludes the formation of such teams in healthcare organizations. Based on experiences deploying data science tools at two large academic medical centers (Beth Israel Deaconess Medical Center, Boston, MA; Mayo Clinic, Rochester, MN), we propose a strategy to facilitate this transition from academic product to operational tool, defining the responsibilities of the principal investigator, data scientist, machine learning engineer, health system IT administrator, and clinician end-user throughout the process. We first enumerate the technical resources and stakeholders needed to prepare for model deployment. We then propose an approach to planning how the final product will work from data extraction and analysis to visualization of model outputs. Finally, we describe how the team should execute on this plan. We hope to guide health systems aiming to deploy minimum viable data science tools and realize their value in clinical practice.
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- 2024
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3. The role of digital technology in surgical home hospital programs
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Kavya Pathak, Jayson S. Marwaha, and Thomas C. Tsai
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Computer applications to medicine. Medical informatics ,R858-859.7 - Abstract
Abstract Home hospital (HH), a care delivery model of providing hospital-grade care to patients in their homes, has become increasingly common in medical settings, though surgical uptake has been limited. HH programs have been shown to be safe and effective in a variety of medical contexts, with increased usage of this care pathway during the COVID-19 pandemic. Though surgical patients have unique clinical considerations, surgical Home Hospital (SHH) programs may have important benefits for this population. Various technologies exist for the delivery of hospital care in the home, such as clinical risk prediction models and remote patient monitoring platforms. Here, we use institutional experiences at Brigham and Women’s Hospital (BWH) to discuss the utility of technology in enabling SHH programs and highlight current limitations. Additionally, we comment on the importance of data interoperability, access for all patients, and clinical workflow design in successfully implementing SHH programs.
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- 2023
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4. Clinical phenotypes and outcomes in children with multisystem inflammatory syndrome across SARS-CoV-2 variant eras: a multinational study from the 4CE consortiumResearch in context
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Francesca Sperotto, Alba Gutiérrez-Sacristán, Simran Makwana, Xiudi Li, Valerie N. Rofeberg, Tianxi Cai, Florence T. Bourgeois, Gilbert S. Omenn, David A. Hanauer, Carlos Sáez, Clara-Lea Bonzel, Emily Bucholz, Audrey Dionne, Matthew D. Elias, Noelia García-Barrio, Tomás González González, Richard W. Issitt, Kate F. Kernan, Jessica Laird-Gion, Sarah E. Maidlow, Kenneth D. Mandl, Taha Mohseni Ahooyi, Cinta Moraleda, Michele Morris, Karyn L. Moshal, Miguel Pedrera-Jiménez, Mohsin A. Shah, Andrew M. South, Anastasia Spiridou, Deanne M. Taylor, Guillaume Verdy, Shyam Visweswaran, Xuan Wang, Zongqi Xia, Joany M. Zachariasse, Jane W. Newburger, Paul Avillach, James R. Aaron, Atif Adam, Giuseppe Agapito, Adem Albayrak, Giuseppe Albi, Mario Alessiani, Anna Alloni, Danilo F. Amendola, François Angoulvant, Li LLJ. Anthony, Bruce J. Aronow, Fatima Ashraf, Andrew Atz, Vidul Ayakulangara Panickan, Paula S. Azevedo, Rafael Badenes, James Balshi, Ashley Batugo, Brendin R. Beaulieu-Jones, Brett K. Beaulieu-Jones, Douglas S. Bell, Antonio Bellasi, Riccardo Bellazzi, Vincent Benoit, Michele Beraghi, José Luis Bernal-Sobrino, Mélodie Bernaux, Romain Bey, Surbhi Bhatnagar, Alvar Blanco-Martínez, Martin Boeker, John Booth, Silvano Bosari, Robert L. Bradford, Gabriel A. Brat, Stéphane Bréant, Nicholas W. Brown, Raffaele Bruno, William A. Bryant, Mauro Bucalo, Anita Burgun, Mario Cannataro, Aldo Carmona, Anna Maria Cattelan, Charlotte Caucheteux, Julien Champ, Jin Chen, Krista Y. Chen, Luca Chiovato, Lorenzo Chiudinelli, Kelly Cho, James J. Cimino, Tiago K. Colicchio, Sylvie Cormont, Sébastien Cossin, Jean B. Craig, Juan Luis Cruz-Bermúdez, Jaime Cruz-Rojo, Arianna Dagliati, Mohamad Daniar, Christel Daniel, Priyam Das, Batsal Devkota, Rui Duan, Julien Dubiel, Scott L. DuVall, Loic Esteve, Hossein Estiri, Shirley Fan, Robert W. Follett, Thomas Ganslandt, Lana X. Garmire, Nils Gehlenborg, Emily J. Getzen, Alon Geva, Rachel SJ. Goh, Tobias Gradinger, Alexandre Gramfort, Romain Griffier, Nicolas Griffon, Olivier Grisel, Pietro H. Guzzi, Larry Han, Christian Haverkamp, Derek Y. Hazard, Bing He, Darren W. Henderson, Martin Hilka, Yuk-Lam Ho, John H. Holmes, Jacqueline P. Honerlaw, Chuan Hong, Kenneth M. Huling, Meghan R. Hutch, Anne Sophie Jannot, Vianney Jouhet, Mundeep K. Kainth, Kernan F. Kate, Ramakanth Kavuluru, Mark S. Keller, Chris J. Kennedy, Daniel A. Key, Katie Kirchoff, Jeffrey G. Klann, Isaac S. Kohane, Ian D. Krantz, Detlef Kraska, Ashok K. Krishnamurthy, Sehi L'Yi, Judith Leblanc, Guillaume Lemaitre, Leslie Lenert, Damien Leprovost, Molei Liu, Ne Hooi Will Loh, Qi Long, Sara Lozano-Zahonero, Yuan Luo, Kristine E. Lynch, Sadiqa Mahmood, Adeline Makoudjou, Alberto Malovini, Chengsheng Mao, Anupama Maram, Monika Maripuri, Patricia Martel, Marcelo R. Martins, Jayson S. Marwaha, Aaron J. Masino, Maria Mazzitelli, Diego R. Mazzotti, Arthur Mensch, Marianna Milano, Marcos F. Minicucci, Bertrand Moal, Jason H. Moore, Jeffrey S. Morris, Sajad Mousavi, Danielle L. Mowery, Douglas A. Murad, Shawn N. Murphy, Thomas P. Naughton, Carlos Tadeu Breda Neto, Antoine Neuraz, Jane Newburger, Kee Yuan Ngiam, Wanjiku FM. Njoroge, James B. Norman, Jihad Obeid, Marina P. Okoshi, Karen L. Olson, Nina Orlova, Brian D. Ostasiewski, Nathan P. Palmer, Nicolas Paris, Lav P. Patel, Ashley C. Pfaff, Emily R. Pfaff, Danielle Pillion, Sara Pizzimenti, Tanu Priya, Hans U. Prokosch, Robson A. Prudente, Andrea Prunotto, Víctor Quirós-González, Rachel B. Ramoni, Maryna Raskin, Siegbert Rieg, Gustavo Roig-Domínguez, Pablo Rojo, Nekane Romero-Garcia, Paula Rubio-Mayo, Paolo Sacchi, Elisa Salamanca, Malarkodi Jebathilagam Samayamuthu, L. Nelson Sanchez-Pinto, Arnaud Sandrin, Nandhini Santhanam, Janaina C.C. Santos, Fernando J. Sanz Vidorreta, Maria Savino, Emily R. Schriver, Petra Schubert, Juergen Schuettler, Luigia Scudeller, Neil J. Sebire, Pablo Serrano-Balazote, Patricia Serre, Arnaud Serret-Larmande, Zahra Shakeri Hossein Abad, Domenick Silvio, Piotr Sliz, Jiyeon Son, Charles Sonday, Zachary H. Strasser, Amelia LM. Tan, Bryce W.Q. Tan, Byorn W.L. Tan, Suzana E. Tanni, Ana I. Terriza-Torres, Valentina Tibollo, Patric Tippmann, Emma MS. Toh, Carlo Torti, Enrico M. Trecarichi, Andrew K. Vallejos, Gael Varoquaux, Margaret E. Vella, Jill-Jênn Vie, Michele Vitacca, Kavishwar B. Wagholikar, Lemuel R. Waitman, Demian Wassermann, Griffin M. Weber, Martin Wolkewitz, Scott Wong, Xin Xiong, Ye Ye, Nadir Yehya, William Yuan, Janet J. Zahner, Alberto Zambelli, Harrison G. Zhang, Daniela Zöller, Valentina Zuccaro, and Chiara Zucco
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Multisystem inflammatory syndrome ,Paediatric inflammatory multisystem syndrome ,COVID-19 ,SARS-CoV-2 ,Variants ,Pediatrics ,Medicine (General) ,R5-920 - Abstract
Summary: Background: Multisystem inflammatory syndrome in children (MIS-C) is a severe complication of SARS-CoV-2 infection. It remains unclear how MIS-C phenotypes vary across SARS-CoV-2 variants. We aimed to investigate clinical characteristics and outcomes of MIS-C across SARS-CoV-2 eras. Methods: We performed a multicentre observational retrospective study including seven paediatric hospitals in four countries (France, Spain, U.K., and U.S.). All consecutive confirmed patients with MIS-C hospitalised between February 1st, 2020, and May 31st, 2022, were included. Electronic Health Records (EHR) data were used to calculate pooled risk differences (RD) and effect sizes (ES) at site level, using Alpha as reference. Meta-analysis was used to pool data across sites. Findings: Of 598 patients with MIS-C (61% male, 39% female; mean age 9.7 years [SD 4.5]), 383 (64%) were admitted in the Alpha era, 111 (19%) in the Delta era, and 104 (17%) in the Omicron era. Compared with patients admitted in the Alpha era, those admitted in the Delta era were younger (ES −1.18 years [95% CI −2.05, −0.32]), had fewer respiratory symptoms (RD −0.15 [95% CI −0.33, −0.04]), less frequent non-cardiogenic shock or systemic inflammatory response syndrome (SIRS) (RD −0.35 [95% CI −0.64, −0.07]), lower lymphocyte count (ES −0.16 × 109/uL [95% CI −0.30, −0.01]), lower C-reactive protein (ES −28.5 mg/L [95% CI −46.3, −10.7]), and lower troponin (ES −0.14 ng/mL [95% CI −0.26, −0.03]). Patients admitted in the Omicron versus Alpha eras were younger (ES −1.6 years [95% CI −2.5, −0.8]), had less frequent SIRS (RD −0.18 [95% CI −0.30, −0.05]), lower lymphocyte count (ES −0.39 × 109/uL [95% CI −0.52, −0.25]), lower troponin (ES −0.16 ng/mL [95% CI −0.30, −0.01]) and less frequently received anticoagulation therapy (RD −0.19 [95% CI −0.37, −0.04]). Length of hospitalization was shorter in the Delta versus Alpha eras (−1.3 days [95% CI −2.3, −0.4]). Interpretation: Our study suggested that MIS-C clinical phenotypes varied across SARS-CoV-2 eras, with patients in Delta and Omicron eras being younger and less sick. EHR data can be effectively leveraged to identify rare complications of pandemic diseases and their variation over time. Funding: None.
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- 2023
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5. Characterization of long COVID temporal sub-phenotypes by distributed representation learning from electronic health record data: a cohort studyResearch in Context
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Arianna Dagliati, Zachary H. Strasser, Zahra Shakeri Hossein Abad, Jeffrey G. Klann, Kavishwar B. Wagholikar, Rebecca Mesa, Shyam Visweswaran, Michele Morris, Yuan Luo, Darren W. Henderson, Malarkodi Jebathilagam Samayamuthu, Bryce W.Q. Tan, Guillame Verdy, Gilbert S. Omenn, Zongqi Xia, Riccardo Bellazzi, Shawn N. Murphy, John H. Holmes, Hossein Estiri, James R. Aaron, Giuseppe Agapito, Adem Albayrak, Giuseppe Albi, Mario Alessiani, Anna Alloni, Danilo F. Amendola, François Angoulvant, Li L.L.J. Anthony, Bruce J. Aronow, Fatima Ashraf, Andrew Atz, Paul Avillach, Paula S. Azevedo, James Balshi, Brett K. Beaulieu-Jones, Douglas S. Bell, Antonio Bellasi, Vincent Benoit, Michele Beraghi, José Luis Bernal-Sobrino, Mélodie Bernaux, Romain Bey, Surbhi Bhatnagar, Alvar Blanco-Martínez, Clara-Lea Bonzel, John Booth, Silvano Bosari, Florence T. Bourgeois, Robert L. Bradford, Gabriel A. Brat, Stéphane Bréant, Nicholas W. Brown, Raffaele Bruno, William A. Bryant, Mauro Bucalo, Emily Bucholz, Anita Burgun, Tianxi Cai, Mario Cannataro, Aldo Carmona, Charlotte Caucheteux, Julien Champ, Jin Chen, Krista Y. Chen, Luca Chiovato, Lorenzo Chiudinelli, Kelly Cho, James J. Cimino, Tiago K. Colicchio, Sylvie Cormont, Sébastien Cossin, Jean B. Craig, Juan Luis Cruz-Bermúdez, Jaime Cruz-Rojo, Mohamad Daniar, Christel Daniel, Priyam Das, Batsal Devkota, Audrey Dionne, Rui Duan, Julien Dubiel, Scott L. DuVall, Loic Esteve, Shirley Fan, Robert W. Follett, Thomas Ganslandt, Noelia García- Barrio, Lana X. Garmire, Nils Gehlenborg, Emily J. Getzen, Alon Geva, Tobias Gradinger, Alexandre Gramfort, Romain Griffier, Nicolas Griffon, Olivier Grisel, Alba Gutiérrez-Sacristán, Larry Han, David A. Hanauer, Christian Haverkamp, Derek Y. Hazard, Bing He, Martin Hilka, Yuk-Lam Ho, Chuan Hong, Kenneth M. Huling, Meghan R. Hutch, Richard W. Issitt, Anne Sophie Jannot, Vianney Jouhet, Ramakanth Kavuluru, Mark S. Keller, Chris J. Kennedy, Daniel A. Key, Katie Kirchoff, Isaac S. Kohane, Ian D. Krantz, Detlef Kraska, Ashok K. Krishnamurthy, Sehi L'Yi, Trang T. Le, Judith Leblanc, Guillaume Lemaitre, Leslie Lenert, Damien Leprovost, Molei Liu, Ne Hooi Will Loh, Qi Long, Sara Lozano-Zahonero, Kristine E. Lynch, Sadiqa Mahmood, Sarah E. Maidlow, Adeline Makoudjou, Alberto Malovini, Kenneth D. Mandl, Chengsheng Mao, Anupama Maram, Patricia Martel, Marcelo R. Martins, Jayson S. Marwaha, Aaron J. Masino, Maria Mazzitelli, Arthur Mensch, Marianna Milano, Marcos F. Minicucci, Bertrand Moal, Taha Mohseni Ahooyi, Jason H. Moore, Cinta Moraleda, Jeffrey S. Morris, Karyn L. Moshal, Sajad Mousavi, Danielle L. Mowery, Douglas A. Murad, Thomas P. Naughton, Carlos Tadeu Breda Neto, Antoine Neuraz, Jane Newburger, Kee Yuan Ngiam, Wanjiku F.M. Njoroge, James B. Norman, Jihad Obeid, Marina P. Okoshi, Karen L. Olson, Nina Orlova, Brian D. Ostasiewski, Nathan P. Palmer, Nicolas Paris, Lav P. Patel, Miguel Pedrera-Jiménez, Emily R. Pfaff, Ashley C. Pfaff, Danielle Pillion, Sara Pizzimenti, Hans U. Prokosch, Robson A. Prudente, Andrea Prunotto, Víctor Quirós-González, Rachel B. Ramoni, Maryna Raskin, Siegbert Rieg, Gustavo Roig-Domínguez, Pablo Rojo, Paula Rubio-Mayo, Paolo Sacchi, Carlos Sáez, Elisa Salamanca, L. Nelson Sanchez-Pinto, Arnaud Sandrin, Nandhini Santhanam, Janaina C.C. Santos, Fernando J. Sanz Vidorreta, Maria Savino, Emily R. Schriver, Petra Schubert, Juergen Schuettler, Luigia Scudeller, Neil J. Sebire, Pablo Serrano-Balazote, Patricia Serre, Arnaud Serret-Larmande, Mohsin Shah, Domenick Silvio, Piotr Sliz, Jiyeon Son, Charles Sonday, Andrew M. South, Anastasia Spiridou, Amelia L.M. Tan, Byorn W.L. Tan, Suzana E. Tanni, Deanne M. Taylor, Ana I. Terriza-Torres, Valentina Tibollo, Patric Tippmann, Emma M.S. Toh, Carlo Torti, Enrico M. Trecarichi, Yi-Ju Tseng, Andrew K. Vallejos, Gael Varoquaux, Margaret E. Vella, Guillaume Verdy, Jill-Jênn Vie, Michele Vitacca, Lemuel R. Waitman, Xuan Wang, Demian Wassermann, Griffin M. Weber, Martin Wolkewitz, Scott Wong, Xin Xiong, Ye Ye, Nadir Yehya, William Yuan, Alberto Zambelli, Harrison G. Zhang, Daniela Zo¨ller, Valentina Zuccaro, and Chiara Zucco
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Post-acute sequelae of SARS-CoV-2 ,PASC ,COVID-19 ,SARS-CoV-2 ,Electronic health records ,Medicine (General) ,R5-920 - Abstract
Summary: Background: Characterizing Post-Acute Sequelae of COVID (SARS-CoV-2 Infection), or PASC has been challenging due to the multitude of sub-phenotypes, temporal attributes, and definitions. Scalable characterization of PASC sub-phenotypes can enhance screening capacities, disease management, and treatment planning. Methods: We conducted a retrospective multi-centre observational cohort study, leveraging longitudinal electronic health record (EHR) data of 30,422 patients from three healthcare systems in the Consortium for the Clinical Characterization of COVID-19 by EHR (4CE). From the total cohort, we applied a deductive approach on 12,424 individuals with follow-up data and developed a distributed representation learning process for providing augmented definitions for PASC sub-phenotypes. Findings: Our framework characterized seven PASC sub-phenotypes. We estimated that on average 15.7% of the hospitalized COVID-19 patients were likely to suffer from at least one PASC symptom and almost 5.98%, on average, had multiple symptoms. Joint pain and dyspnea had the highest prevalence, with an average prevalence of 5.45% and 4.53%, respectively. Interpretation: We provided a scalable framework to every participating healthcare system for estimating PASC sub-phenotypes prevalence and temporal attributes, thus developing a unified model that characterizes augmented sub-phenotypes across the different systems. Funding: Authors are supported by National Institute of Allergy and Infectious Diseases, National Institute on Aging, National Center for Advancing Translational Sciences, National Medical Research Council, National Institute of Neurological Disorders and Stroke, European Union, National Institutes of Health, National Center for Advancing Translational Sciences.
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- 2023
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6. The digital transformation of surgery
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Jayson S. Marwaha, Marium M. Raza, and Joseph C. Kvedar
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Computer applications to medicine. Medical informatics ,R858-859.7 - Abstract
Abstract Rapid advances in digital technology and artificial intelligence in recent years have already begun to transform many industries, and are beginning to make headway into healthcare. There is tremendous potential for new digital technologies to improve the care of surgical patients. In this piece, we highlight work being done to advance surgical care using machine learning, computer vision, wearable devices, remote patient monitoring, and virtual and augmented reality. We describe ways these technologies can be used to improve the practice of surgery, and discuss opportunities and challenges to their widespread adoption and use in operating rooms and at the bedside.
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- 2023
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7. Deploying digital health tools within large, complex health systems: key considerations for adoption and implementation
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Jayson S. Marwaha, Adam B. Landman, Gabriel A. Brat, Todd Dunn, and William J. Gordon
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Computer applications to medicine. Medical informatics ,R858-859.7 - Abstract
Abstract In recent years, the number of digital health tools with the potential to significantly improve delivery of healthcare services has grown tremendously. However, the use of these tools in large, complex health systems remains comparatively limited. The adoption and implementation of digital health tools at an enterprise level is a challenge; few strategies exist to help tools cross the chasm from clinical validation to integration within the workflows of a large health system. Many previously proposed frameworks for digital health implementation are difficult to operationalize in these dynamic organizations. In this piece, we put forth nine dimensions along which clinically validated digital health tools should be examined by health systems prior to adoption, and propose strategies for selecting digital health tools and planning for implementation in this setting. By evaluating prospective tools along these dimensions, health systems can evaluate which existing digital health solutions are worthy of adoption, ensure they have sufficient resources for deployment and long-term use, and devise a strategic plan for implementation.
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- 2022
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8. Long-term kidney function recovery and mortality after COVID-19-associated acute kidney injury: An international multi-centre observational cohort studyResearch in context
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Byorn W.L. Tan, Bryce W.Q. Tan, Amelia L.M. Tan, Emily R. Schriver, Alba Gutiérrez-Sacristán, Priyam Das, William Yuan, Meghan R. Hutch, Noelia García Barrio, Miguel Pedrera Jimenez, Noor Abu-el-rub, Michele Morris, Bertrand Moal, Guillaume Verdy, Kelly Cho, Yuk-Lam Ho, Lav P. Patel, Arianna Dagliati, Antoine Neuraz, Jeffrey G. Klann, Andrew M. South, Shyam Visweswaran, David A. Hanauer, Sarah E. Maidlow, Mei Liu, Danielle L. Mowery, Ashley Batugo, Adeline Makoudjou, Patric Tippmann, Daniela Zöller, Gabriel A. Brat, Yuan Luo, Paul Avillach, Riccardo Bellazzi, Luca Chiovato, Alberto Malovini, Valentina Tibollo, Malarkodi Jebathilagam Samayamuthu, Pablo Serrano Balazote, Zongqi Xia, Ne Hooi Will Loh, Lorenzo Chiudinelli, Clara-Lea Bonzel, Chuan Hong, Harrison G. Zhang, Griffin M. Weber, Isaac S. Kohane, Tianxi Cai, Gilbert S. Omenn, John H. Holmes, Kee Yuan Ngiam, James R. Aaron, Giuseppe Agapito, Adem Albayrak, Giuseppe Albi, Mario Alessiani, Anna Alloni, Danilo F. Amendola, François Angoulvant, Li L.L.J. Anthony, Bruce J. Aronow, Fatima Ashraf, Andrew Atz, Vidul Ayakulangara Panickan, Paula S. Azevedo, James Balshi, Brett K. Beaulieu-Jones, Brendin R. Beaulieu-Jones, Douglas S. Bell, Antonio Bellasi, Vincent Benoit, Michele Beraghi, José Luis Bernal-Sobrino, Mélodie Bernaux, Romain Bey, Surbhi Bhatnagar, Alvar Blanco-Martínez, Martin Boeker, John Booth, Silvano Bosari, Florence T. Bourgeois, Robert L. Bradford, Stéphane Bréant, Nicholas W. Brown, Raffaele Bruno, William A. Bryant, Mauro Bucalo, Emily Bucholz, Anita Burgun, Mario Cannataro, Aldo Carmona, Anna Maria Cattelan, Charlotte Caucheteux, Julien Champ, Jin Chen, Krista Y. Chen, James J. Cimino, Tiago K. Colicchio, Sylvie Cormont, Sébastien Cossin, Jean B. Craig, Juan Luis Cruz-Bermúdez, Jaime Cruz-Rojo, Mohamad Daniar, Christel Daniel, Batsal Devkota, Audrey Dionne, Rui Duan, Julien Dubiel, Scott L. DuVall, Loic Esteve, Hossein Estiri, Shirley Fan, Robert W. Follett, Thomas Ganslandt, Noelia García-Barrio, Lana X. Garmire, Nils Gehlenborg, Emily J. Getzen, Alon Geva, Tomás González González, Tobias Gradinger, Alexandre Gramfort, Romain Griffier, Nicolas Griffon, Olivier Grisel, Pietro H. Guzzi, Larry Han, Christian Haverkamp, Derek Y. Hazard, Bing He, Darren W. Henderson, Martin Hilka, Jacqueline P. Honerlaw, Kenneth M. Huling, Richard W. Issitt, Anne Sophie Jannot, Vianney Jouhet, Ramakanth Kavuluru, Mark S. Keller, Chris J. Kennedy, Kate F. Kernan, Daniel A. Key, Katie Kirchoff, Ian D. Krantz, Detlef Kraska, Ashok K. Krishnamurthy, Sehi L'Yi, Trang T. Le, Judith Leblanc, Guillaume Lemaitre, Leslie Lenert, Damien Leprovost, Molei Liu, Qi Long, Sara Lozano-Zahonero, Kristine E. Lynch, Sadiqa Mahmood, Simran Makwana, Kenneth D. Mandl, Chengsheng Mao, Anupama Maram, Monika Maripuri, Patricia Martel, Marcelo R. Martins, Jayson S. Marwaha, Aaron J. Masino, Maria Mazzitelli, Diego R. Mazzotti, Arthur Mensch, Marianna Milano, Marcos F. Minicucci, Taha Mohseni Ahooyi, Jason H. Moore, Cinta Moraleda, Jeffrey S. Morris, Karyn L. Moshal, Sajad Mousavi, Douglas A. Murad, Shawn N. Murphy, Thomas P. Naughton, Carlos Tadeu Breda Neto, Jane Newburger, Wanjiku F.M. Njoroge, James B. Norman, Jihad Obeid, Marina P. Okoshi, Karen L. Olson, Nina Orlova, Brian D. Ostasiewski, Nathan P. Palmer, Nicolas Paris, Miguel Pedrera-Jiménez, Ashley C. Pfaff, Emily R. Pfaff, Danielle Pillion, Sara Pizzimenti, Tanu Priya, Hans U. Prokosch, Robson A. Prudente, Andrea Prunotto, Víctor Quirós-González, Rachel B. Ramoni, Maryna Raskin, Siegbert Rieg, Gustavo Roig-Domínguez, Pablo Rojo, Paula Rubio-Mayo, Paolo Sacchi, Carlos Sáez, Elisa Salamanca, L. Nelson Sanchez-Pinto, Arnaud Sandrin, Nandhini Santhanam, Janaina C.C. Santos, Fernando J. Sanz Vidorreta, Maria Savino, Petra Schubert, Juergen Schuettler, Luigia Scudeller, Neil J. Sebire, Pablo Serrano-Balazote, Patricia Serre, Arnaud Serret-Larmande, Mohsin Shah, Zahra Shakeri Hossein Abad, Domenick Silvio, Piotr Sliz, Jiyeon Son, Charles Sonday, Francesca Sperotto, Anastasia Spiridou, Zachary H. Strasser, Suzana E. Tanni, Deanne M. Taylor, Ana I. Terriza-Torres, Emma M.S. Toh, Carlo Torti, Enrico M. Trecarichi, Andrew K. Vallejos, Gael Varoquaux, Margaret E. Vella, Jill-Jênn Vie, Michele Vitacca, Kavishwar B. Wagholikar, Lemuel R. Waitman, Xuan Wang, Demian Wassermann, Martin Wolkewitz, Scott Wong, Xin Xiong, Ye Ye, Nadir Yehya, Joany M. Zachariasse, Janet J. Zahner, Alberto Zambelli, Valentina Zuccaro, and Chiara Zucco
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COVID-19 ,Acute kidney injury ,SARS-CoV-2 ,Chronic kidney disease ,Electronic health records ,Medicine (General) ,R5-920 - Abstract
Summary: Background: While acute kidney injury (AKI) is a common complication in COVID-19, data on post-AKI kidney function recovery and the clinical factors associated with poor kidney function recovery is lacking. Methods: A retrospective multi-centre observational cohort study comprising 12,891 hospitalized patients aged 18 years or older with a diagnosis of SARS-CoV-2 infection confirmed by polymerase chain reaction from 1 January 2020 to 10 September 2020, and with at least one serum creatinine value 1–365 days prior to admission. Mortality and serum creatinine values were obtained up to 10 September 2021. Findings: Advanced age (HR 2.77, 95%CI 2.53–3.04, p
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- 2023
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9. Machine learning nonresponse adjustment of patient-reported opioid consumption data to enable consumption-informed postoperative opioid prescribing guidelines
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Chris J. Kennedy, Jayson S. Marwaha, Brendin R. Beaulieu-Jones, P. Nina Scalise, Kortney A. Robinson, Brandon Booth, Aaron Fleishman, Larry A. Nathanson, and Gabriel A. Brat
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Surgery ,RD1-811 - Abstract
Background: Post-discharge opioid consumption is a crucial patient-reported outcome informing opioid prescribing guidelines, but its collection is resource-intensive and vulnerable to inaccuracy due to nonresponse bias. Methods: We developed a post-discharge text message-to-web survey system for efficient collection of patient-reported pain outcomes. We prospectively recruited surgical patients at Beth Israel Deaconess Medical Center in Boston, Massachusetts from March 2019 through October 2020, sending an SMS link to a secure web survey to quantify opioids consumed after discharge from hospitalization. Patient factors extracted from the electronic health record were tested for nonresponse bias and observable confounding. Following targeted learning-based nonresponse adjustment, procedure-specific opioid consumption quantiles (medians and 75th percentiles) were estimated and compared to a previous telephone-based reference survey. Results: 6553 patients were included. Opioid consumption was measured in 44% of patients (2868), including 21% (1342) through survey response. Characteristics associated with inability to measure opioid consumption included age, tobacco use, and prescribed opioid dose. Among the 10 most common procedures, median consumption was only 36% of the median prescription size; 64% of prescribed opioids were not consumed. Among those procedures, nonresponse adjustment corrected the median opioid consumption by an average of 37% (IQR: 7, 65%) compared to unadjusted estimates, and corrected the 75th percentile by an average of 5% (IQR: 0, 12%). This brought median estimates for 5/10 procedures closer to telephone survey-based consumption estimates, and 75th percentile estimates for 2/10 procedures closer to telephone survey-based estimates. Conclusions: SMS-recruited online surveying can generate reliable opioid consumption estimates after nonresponse adjustment using patient factors recorded in the electronic health record, protecting patients from the risk of inaccurate prescription guidelines.
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- 2022
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10. Video-based physiologic monitoring: promising applications for the ICU and beyond
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James A. Diao, Jayson S. Marwaha, and Joseph C. Kvedar
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Computer applications to medicine. Medical informatics ,R858-859.7 - Abstract
The vital signs—temperature, heart rate, respiratory rate, and blood pressure—are indispensable in clinical decision-making. These metrics are widely used to identify physiologic decline and prompt investigation or intervention. Vital sign monitoring is particularly important in acute care settings, where patients are at higher risk and may require additional vigilance. Conventional contact-based devices, while widespread and generally reliable, can be inconvenient or disruptive to patients, families, and staff. Non-contact, video-based methods present a more flexible and information-dense alternative that may enable creative improvements to patient care. Still, these approaches are susceptible to several sources of bias and require rigorous clinical validation. A recent study by Jorge et al. demonstrates that video-based monitoring can reliably capture heart rate and respiratory rate and overcome many potential sources of bias in post-operative settings. This presents real-world evaluation of a practical, noninvasive, and continuous monitoring technology that had previously only been tested in controlled settings.
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- 2022
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11. Crossing the chasm from model performance to clinical impact: the need to improve implementation and evaluation of AI
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Jayson S. Marwaha and Joseph C. Kvedar
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Computer applications to medicine. Medical informatics ,R858-859.7 - Published
- 2022
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12. Cultural adaptation: a framework for addressing an often-overlooked dimension of digital health accessibility
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Jayson S. Marwaha and Joseph C. Kvedar
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Computer applications to medicine. Medical informatics ,R858-859.7 - Abstract
Abstract Relatively little is known about how to make digital health tools accessible to different populations from a cultural standpoint. Alignment with cultural values and communication styles may affect these tools’ ability to diagnose and treat various conditions. In this Editorial, we highlight the findings of recent work to make digital tools for mental health more culturally accessible, and propose ways to advance this area of study.
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- 2021
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13. Leveraging External Data to Make Local Predictions of Post-Surgical Opioid Use: Investigating the Role of External Validation and Transfer Learning.
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Chris J. Kennedy, Jayson S. Marwaha, Brendin Beaulieu-Jones, Josh Bleicher, Lyen Huang, and Gabriel A. Brat
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- 2022
14. There is Variability in the Accuracy of Diagnosis Codes Used to Identify COVID-19 Patients.
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Jayson S. Marwaha, Elizabeth Eldridge, Sahr Syed, Perry L. Mar, Philip Ballentine, Denis Agniel, Nathan P. Palmer, Sadiqa Mahmood, and Gabriel A. Brat
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- 2021
15. Evaluation of U.S. state opioid prescribing restrictions using patient opioid consumption patterns from a single, urban, academic institution
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Kortney A. Robinson, Jayson S. Marwaha, Chris J. Kennedy, Brendin R. Beaulieu-Jones, Aaron Fleishman, Justin K. Yu, Larry A. Nathanson, and Gabriel A. Brat
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Analgesics, Opioid ,Pain, Postoperative ,Psychiatry and Mental health ,Aftercare ,Humans ,Medicine (miscellaneous) ,Practice Patterns, Physicians' ,Opioid-Related Disorders ,Patient Discharge ,Retrospective Studies - Published
- 2022
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16. In Silico Performance Versus Real-World Utility of Surgical Prediction Models: What Does it Take to Change a Surgeon’s Mind?
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Joyce E Wang, Chris J Kennedy, Gabriel A Brat, and Jayson S Marwaha
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Surgery - Published
- 2023
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17. Open science practices in research published in surgical journals: A cross-sectional study
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Kavya Pathak, Jayson S. Marwaha, Hao Wei Chen, Harlan M. Krumholz, and Jeffrey B. Matthews
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Article - Abstract
Open science practices are research tools used to improve research quality and transparency. These practices have been used by researchers in various medical fields, though the usage of these practices in the surgical research ecosystem has not been quantified. In this work, we studied the use of open science practices in general surgery journals. Eight of the highest-ranked general surgery journals by SJR2 were chosen and their author guidelines were reviewed. From each journal, 30 articles published between January 1, 2019 and August 11, 2021 were randomly chosen and analyzed. Five open science practices were measured (preprint publication prior to peer-reviewed publication, use of Equator guidelines, study protocol preregistration prior to peer-reviewed publication, published peer review, and public accessibility of data, methods, and/or code). Across all 240 articles, 82 (34%) used one or more open science practices. Articles in theInternational Journal of Surgeryshowed greatest use of open science practices, with a mean of 1.6 open science practices compared to 0.36 across the other journals (p
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- 2023
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18. Artificial Intelligence-enabled Decision Support in Surgery
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Tyler J. Loftus, Maria S. Altieri, Jeremy A. Balch, Kenneth L. Abbott, Jeff Choi, Jayson S. Marwaha, Daniel A. Hashimoto, Gabriel A. Brat, Yannis Raftopoulos, Heather L. Evans, Gretchen P. Jackson, Danielle S. Walsh, and Christopher J. Tignanelli
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Surgery - Published
- 2023
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19. Surgical Residency Programs Should Leverage Recent Advances in National Policy, Real-World Data, and Public Opinion to Improve Post-Surgery Opioid Prescribing
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Jayson S. Marwaha, Chris J. Kennedy, and Gabriel A. Brat
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Analgesics, Opioid ,Policy ,Public Opinion ,Humans ,Internship and Residency ,General Medicine ,Practice Patterns, Physicians' ,Perspectives - Published
- 2022
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20. The Impact of Concurrent Multi-Service Coverage on Quality and Safety in Trauma Care
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Brian C. Drolet, Jayson S. Marwaha, and Charles A. Adams
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Surgeons ,medicine.medical_specialty ,Critical Care ,business.industry ,Trauma center ,Psychological intervention ,Workload ,Odds ratio ,Logistic regression ,Article ,United States ,Trauma Centers ,Acute care ,Emergency medicine ,medicine ,Humans ,Surgery ,Risk factor ,Complication ,business ,Retrospective Studies - Abstract
Background At many trauma centers in the United States, one acute care surgeon is responsible for overnight coverage of both the emergency general surgery (EGS) and trauma services. The impact of this scheduling phenomenon on the quality and safety of trauma care has not been studied. Methods Overnight (12:00 AM to 7:00 AM) trauma admissions to an academic Level 1 trauma center from 2013-2015 were studied after the institution adopted this scheduling phenomenon. Admissions were divided into two groups based on whether the admitting surgeon covered only the trauma service, or both the trauma and EGS services ("multi-service coverage"). Four major outcomes (e.g., mortality and complications), six quality metrics (e.g., time to first odds ratio visit and unplanned transfers to the ICU), and procedural utilization patterns were compared. Results A total of 1046 admissions were included. There were no differences in any major outcomes between the two exposure groups, including any National Trauma Data Bank-defined complication (OR 1.1, 95% CI 0.8-1.5, P= 0.5). Quality metrics dependent on the admitting surgeon remained unchanged, including attending presence at the highest-level trauma activations within 15 min of arrival (93% versus 86%, P= 0.07) and time to urgent operative intervention (68 min versus 82 min, P= 0.9). There were no differences in the number of laboratory and imaging studies (4.1 versus 4.1, P= 0.9) or bedside interventions (1.8 versus 2.1, P= 0.4) performed per patient by the admitting surgeon. Multivariate logistic regression did not identify multi-service coverage as an independent risk factor for adverse patient outcomes or quality metrics. Conclusions Trauma admissions under a surgeon covering multiple services simultaneously had similar outcomes, quality metrics, and procedural utilization patterns compared to trauma admissions under surgeons covering only the trauma service. Despite concerns that multiple-service coverage may overburden one acute care surgeon, time-dependent quality metrics and studies done during the initial workup of trauma patients remained unchanged. These findings suggest that simultaneous trauma and EGS service coverage by one acute care surgeon does not adversely impact trauma patient care.
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- 2022
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21. Pearls of wisdom from the past 5 years of working in telehealth
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Jayson S. Marwaha and Joseph C. Kvedar
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- 2023
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22. Research priorities for the surgical care of patients taking opioids preoperatively
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Jayson S Marwaha, Brendin R Beaulieu-Jones, Chris J Kennedy, Mark C Bicket, and Gabriel A Brat
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Anesthesiology and Pain Medicine ,General Medicine - Published
- 2022
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23. Long-term kidney function recovery and mortality after COVID-19-associated acute kidney injury: An international multi-centre observational cohort study
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Byorn W.L. Tan, Bryce W.Q. Tan, Amelia L.M. Tan, Emily R. Schriver, Alba Gutiérrez-Sacristán, Priyam Das, William Yuan, Meghan R. Hutch, Noelia García Barrio, Miguel Pedrera Jimenez, Noor Abu-el-rub, Michele Morris, Bertrand Moal, Guillaume Verdy, Kelly Cho, Yuk-Lam Ho, Lav P. Patel, Arianna Dagliati, Antoine Neuraz, Jeffrey G. Klann, Andrew M. South, Shyam Visweswaran, David A. Hanauer, Sarah E. Maidlow, Mei Liu, Danielle L. Mowery, Ashley Batugo, Adeline Makoudjou, Patric Tippmann, Daniela Zöller, Gabriel A. Brat, Yuan Luo, Paul Avillach, Riccardo Bellazzi, Luca Chiovato, Alberto Malovini, Valentina Tibollo, Malarkodi Jebathilagam Samayamuthu, Pablo Serrano Balazote, Zongqi Xia, Ne Hooi Will Loh, Lorenzo Chiudinelli, Clara-Lea Bonzel, Chuan Hong, Harrison G. Zhang, Griffin M. Weber, Isaac S. Kohane, Tianxi Cai, Gilbert S. Omenn, John H. Holmes, Kee Yuan Ngiam, James R. Aaron, Giuseppe Agapito, Adem Albayrak, Giuseppe Albi, Mario Alessiani, Anna Alloni, Danilo F. Amendola, François Angoulvant, Li L.L.J. Anthony, Bruce J. Aronow, Fatima Ashraf, Andrew Atz, Vidul Ayakulangara Panickan, Paula S. Azevedo, James Balshi, Brett K. Beaulieu-Jones, Brendin R. Beaulieu-Jones, Douglas S. Bell, Antonio Bellasi, Vincent Benoit, Michele Beraghi, José Luis Bernal-Sobrino, Mélodie Bernaux, Romain Bey, Surbhi Bhatnagar, Alvar Blanco-Martínez, Martin Boeker, John Booth, Silvano Bosari, Florence T. Bourgeois, Robert L. Bradford, Stéphane Bréant, Nicholas W. Brown, Raffaele Bruno, William A. Bryant, Mauro Bucalo, Emily Bucholz, Anita Burgun, Mario Cannataro, Aldo Carmona, Anna Maria Cattelan, Charlotte Caucheteux, Julien Champ, Jin Chen, Krista Y. Chen, James J. Cimino, Tiago K. Colicchio, Sylvie Cormont, Sébastien Cossin, Jean B. Craig, Juan Luis Cruz-Bermúdez, Jaime Cruz-Rojo, Mohamad Daniar, Christel Daniel, Batsal Devkota, Audrey Dionne, Rui Duan, Julien Dubiel, Scott L. DuVall, Loic Esteve, Hossein Estiri, Shirley Fan, Robert W. Follett, Thomas Ganslandt, Noelia García-Barrio, Lana X. Garmire, Nils Gehlenborg, Emily J. Getzen, Alon Geva, Tomás González González, Tobias Gradinger, Alexandre Gramfort, Romain Griffier, Nicolas Griffon, Olivier Grisel, Pietro H. Guzzi, Larry Han, Christian Haverkamp, Derek Y. Hazard, Bing He, Darren W. Henderson, Martin Hilka, Jacqueline P. Honerlaw, Kenneth M. Huling, Richard W. Issitt, Anne Sophie Jannot, Vianney Jouhet, Ramakanth Kavuluru, Mark S. Keller, Chris J. Kennedy, Kate F. Kernan, Daniel A. Key, Katie Kirchoff, Ian D. Krantz, Detlef Kraska, Ashok K. Krishnamurthy, Sehi L'Yi, Trang T. Le, Judith Leblanc, Guillaume Lemaitre, Leslie Lenert, Damien Leprovost, Molei Liu, Qi Long, Sara Lozano-Zahonero, Kristine E. Lynch, Sadiqa Mahmood, Simran Makwana, Kenneth D. Mandl, Chengsheng Mao, Anupama Maram, Monika Maripuri, Patricia Martel, Marcelo R. Martins, Jayson S. Marwaha, Aaron J. Masino, Maria Mazzitelli, Diego R. Mazzotti, Arthur Mensch, Marianna Milano, Marcos F. Minicucci, Taha Mohseni Ahooyi, Jason H. Moore, Cinta Moraleda, Jeffrey S. Morris, Karyn L. Moshal, Sajad Mousavi, Douglas A. Murad, Shawn N. Murphy, Thomas P. Naughton, Carlos Tadeu Breda Neto, Jane Newburger, Wanjiku F.M. Njoroge, James B. Norman, Jihad Obeid, Marina P. Okoshi, Karen L. Olson, Nina Orlova, Brian D. Ostasiewski, Nathan P. Palmer, Nicolas Paris, Miguel Pedrera-Jiménez, Ashley C. Pfaff, Emily R. Pfaff, Danielle Pillion, Sara Pizzimenti, Tanu Priya, Hans U. Prokosch, Robson A. Prudente, Andrea Prunotto, Víctor Quirós-González, Rachel B. Ramoni, Maryna Raskin, Siegbert Rieg, Gustavo Roig-Domínguez, Pablo Rojo, Paula Rubio-Mayo, Paolo Sacchi, Carlos Sáez, Elisa Salamanca, L. Nelson Sanchez-Pinto, Arnaud Sandrin, Nandhini Santhanam, Janaina C.C. Santos, Fernando J. Sanz Vidorreta, Maria Savino, Petra Schubert, Juergen Schuettler, Luigia Scudeller, Neil J. Sebire, Pablo Serrano-Balazote, Patricia Serre, Arnaud Serret-Larmande, Mohsin Shah, Zahra Shakeri Hossein Abad, Domenick Silvio, Piotr Sliz, Jiyeon Son, Charles Sonday, Francesca Sperotto, Anastasia Spiridou, Zachary H. Strasser, Suzana E. Tanni, Deanne M. Taylor, Ana I. Terriza-Torres, Emma M.S. Toh, Carlo Torti, Enrico M. Trecarichi, Andrew K. Vallejos, Gael Varoquaux, Margaret E. Vella, Jill-Jênn Vie, Michele Vitacca, Kavishwar B. Wagholikar, Lemuel R. Waitman, Xuan Wang, Demian Wassermann, Martin Wolkewitz, Scott Wong, Xin Xiong, Ye Ye, Nadir Yehya, Joany M. Zachariasse, Janet J. Zahner, Alberto Zambelli, Valentina Zuccaro, and Chiara Zucco
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General Medicine - Abstract
While acute kidney injury (AKI) is a common complication in COVID-19, data on post-AKI kidney function recovery and the clinical factors associated with poor kidney function recovery is lacking.A retrospective multi-centre observational cohort study comprising 12,891 hospitalized patients aged 18 years or older with a diagnosis of SARS-CoV-2 infection confirmed by polymerase chain reaction from 1 January 2020 to 10 September 2020, and with at least one serum creatinine value 1-365 days prior to admission. Mortality and serum creatinine values were obtained up to 10 September 2021.Advanced age (HR 2.77, 95%CI 2.53-3.04, p 0.0001), severe COVID-19 (HR 2.91, 95%CI 2.03-4.17, p 0.0001), severe AKI (KDIGO stage 3: HR 4.22, 95%CI 3.55-5.00, p 0.0001), and ischemic heart disease (HR 1.26, 95%CI 1.14-1.39, p 0.0001) were associated with worse mortality outcomes. AKI severity (KDIGO stage 3: HR 0.41, 95%CI 0.37-0.46, p 0.0001) was associated with worse kidney function recovery, whereas remdesivir use (HR 1.34, 95%CI 1.17-1.54, p 0.0001) was associated with better kidney function recovery. In a subset of patients without chronic kidney disease, advanced age (HR 1.38, 95%CI 1.20-1.58, p 0.0001), male sex (HR 1.67, 95%CI 1.45-1.93, p 0.0001), severe AKI (KDIGO stage 3: HR 11.68, 95%CI 9.80-13.91, p 0.0001), and hypertension (HR 1.22, 95%CI 1.10-1.36, p = 0.0002) were associated with post-AKI kidney function impairment. Furthermore, patients with COVID-19-associated AKI had significant and persistent elevations of baseline serum creatinine 125% or more at 180 days (RR 1.49, 95%CI 1.32-1.67) and 365 days (RR 1.54, 95%CI 1.21-1.96) compared to COVID-19 patients with no AKI.COVID-19-associated AKI was associated with higher mortality, and severe COVID-19-associated AKI was associated with worse long-term post-AKI kidney function recovery.Authors are supported by various funders, with full details stated in the acknowledgement section.
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- 2022
24. Distinguishing Admissions Specifically for COVID-19 from Incidental SARS-CoV-2 Admissions: A National EHR Research Consortium Study
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Jeffrey G, Klann, Zachary H, Strasser, Meghan R, Hutch, Chris J, Kennedy, Jayson S, Marwaha, Michele, Morris, Malarkodi Jebathilagam, Samayamuthu, Ashley C, Pfaff, Hossein, Estiri, Andrew M, South, Griffin M, Weber, William, Yuan, Paul, Avillach, Kavishwar B, Wagholikar, Yuan, Luo, Gilbert S, Omenn, Shyam, Visweswaran, John H, Holmes, Zongqi, Xia, Gabriel A, Brat, and Shawn N, Murphy
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Hospitalization ,SARS-CoV-2 ,COVID-19 ,Electronic Health Records ,Humans ,Article ,Retrospective Studies - Abstract
Admissions are generally classified as COVID-19 hospitalizations if the patient has a positive SARS-CoV-2 polymerase chain reaction (PCR) test. However, because 35% of SARS-CoV-2 infections are asymptomatic, patients admitted for unrelated indications with an incidentally positive test could be misclassified as a COVID-19 hospitalization. Electronic health record (EHR)-based studies have been unable to distinguish between a hospitalization specifically for COVID-19 versus an incidental SARS-CoV-2 hospitalization. Although the need to improve classification of COVID-19 versus incidental SARS-CoV-2 is well understood, the magnitude of the problems has only been characterized in small, single-center studies. Furthermore, there have been no peer-reviewed studies evaluating methods for improving classification.The aims of this study are to, first, quantify the frequency of incidental hospitalizations over the first 15 months of the pandemic in multiple hospital systems in the United States and, second, to apply electronic phenotyping techniques to automatically improve COVID-19 hospitalization classification.From a retrospective EHR-based cohort in 4 US health care systems in Massachusetts, Pennsylvania, and Illinois, a random sample of 1123 SARS-CoV-2 PCR-positive patients hospitalized from March 2020 to August 2021 was manually chart-reviewed and classified as "admitted with COVID-19" (incidental) versus specifically admitted for COVID-19 ("for COVID-19"). EHR-based phenotyping was used to find feature sets to filter out incidental admissions.EHR-based phenotyped feature sets filtered out incidental admissions, which occurred in an average of 26% of hospitalizations (although this varied widely over time, from 0% to 75%). The top site-specific feature sets had 79%-99% specificity with 62%-75% sensitivity, while the best-performing across-site feature sets had 71%-94% specificity with 69%-81% sensitivity.A large proportion of SARS-CoV-2 PCR-positive admissions were incidental. Straightforward EHR-based phenotypes differentiated admissions, which is important to assure accurate public health reporting and research.
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- 2022
25. Real-world Data-A Key Barrier to Building Out the Science of Firearm Safety
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Jayson S. Marwaha, Nicole Lunardi, and Joseph V. Sakran
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Firearms ,Ownership ,Humans ,Surgery ,Wounds, Gunshot - Published
- 2022
26. Trends in Medical Management of Moderately to Severely Active Ulcerative Colitis: A Nationwide Retrospective Analysis
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William Yuan, Jayson S Marwaha, Shana T Rakowsky, Nathan P Palmer, Isaac S Kohane, David T Rubin, Gabriel A Brat, and Joseph D Feuerstein
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Clinical Research ,Gastroenterology ,Immunology and Allergy - Abstract
Background With an increasing number of therapeutic options available for the management of ulcerative colitis (UC), the variability in treatment and prescribing patterns is not well known. While recent guidelines have provided updates on how these therapeutic options should be used, patterns of long-term use of these drugs over the past 2 decades remain unclear. Methods We analyzed a retrospective, nationwide cohort of more than 1.7 million prescriptions for trends in prescribing behaviors and to evaluate practices suggested in guidelines relating to ordering biologics, step-up therapy, and combination therapy. The primary outcome was 30-day steroid-free remission and secondary outcomes included hospitalization, cost, and additional steroid usage. A pipeline was created to identify cohorts of patients under active UC medical management grouped by prescribing strategies to evaluate comparative outcomes between strategies. Cox proportional hazards and multivariate regression models were utilized to assess postexposure outcomes and adjust for confounders. Results Among 6 major drug categories, we noted major baseline differences in patient characteristics at first exposure corresponding to disease activity. We noted earlier use of biologics in patient trajectories (762 days earlier relative to UC diagnosis, 2018 vs 2008; P < .001) and greater overall use of biologics over time (2.53× more in 2018 vs 2008; P < .00001) . Among biologic-naive patients, adalimumab was associated with slightly lower rates of remission compared with infliximab or vedolizumab (odds ratio, 0.92; P < .005). Comparisons of patients with early biologic initiation to patients who transitioned to biologics from 5-aminosalicylic acid suggest lower steroid consumption for early biologic initiation (-761 mg prednisone; P < .001). Combination thiopurine-biologic therapy was associated with higher odds of remission compared with biologic monotherapy (odds ratio, 1.36; P = .01). Conclusions As biologic drugs have become increasingly available for UC management, they have increasingly been used at earlier stages of disease management. Large-scale analyses of prescribing behaviors provide evidence supporting early use of biologics compared with step-up therapy and use of thiopurine and biologic combination therapy.
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- 2022
27. Crossing the chasm from model performance to clinical impact: the need to improve implementation and evaluation of AI
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Jayson S. Marwaha and Joseph C. Kvedar
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Health Information Management ,Medicine (miscellaneous) ,Health Informatics ,Computer Science Applications - Published
- 2021
28. Who doesn't fit? A multi-institutional study using machine learning to uncover the limits of opioid prescribing guidelines
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Justin K. Yu, Jayson S. Marwaha, Chris J. Kennedy, Kortney A. Robinson, Aaron Fleishman, Brendin R. Beaulieu-Jones, Josh Bleicher, Lyen C. Huang, Peter Szolovits, and Gabriel A. Brat
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Analgesics, Opioid ,Machine Learning ,Pain, Postoperative ,Aftercare ,Humans ,Surgery ,Practice Patterns, Physicians' ,Patient Discharge ,Retrospective Studies - Abstract
Many U.S. institutions have adopted postsurgical opioid-prescribing guidelines to standardize prescribing practices, and yet there is inherent variability in patients' opioid consumption after surgery. The utility of these guidelines is limited by the fact that some patients' needs will inevitably exceed them, and yet there are no evidence-based tools to help providers identify these patients. In this study we aimed to maximize the value of these guidelines by training machine learning models to predict patients whose needs will be met by these smaller recommended prescriptions, and patients who may require an additional degree of personalization. The aim of the present study was to develop predictive models for determining whether a surgical patient's postdischarge opioid requirement will fall above or below common opioid prescribing guidelines.We conducted a retrospective cohort study of surgical patients at one institution from 2017 to 2018. Patients were called after discharge to collect opioid consumption data. Machine learning models were used to identify outlier opioid consumers (ie, exceeding our institutional prescribing guidelines) using diagnosis codes, medical history, in-hospital opioid use, and perioperative factors as predictors. External validation was performed on opioid consumption data collected at a second institution from 2020 to 2021, and sensitivity analysis was performed using a third institution's prescribing guidelines.The development and external validation cohorts included 1,867 and 498 patients, respectively. Age, body mass index, tobacco use, preoperative opioid exposure, and in-hospital opioid consumption were the strongest predictors of postdischarge consumption. A lasso regression model exhibited an area under the receiver operating characteristic curve of 0.74 (95% confidence interval 0.67-0.81) in predicting postdischarge opioid consumption. External validation of a limited lasso model yielded an area under the receiver operating characteristic curve of 0.67 (0.60-0.74). Performance was preserved when evaluated on another institution's guidelines (area under the receiver operating characteristic curve 0.76 [0.72-0.80]).Patient characteristics reliably predict postdischarge opioid consumption in relation to prescribing guidelines for both opioid-naive and exposed populations. This model may be used to help providers confidently follow prescribing guidelines for patients with typical opioid responsiveness and correctly pursue more personalized prescribing for others.
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- 2021
29. Milestones on the Plastic Surgery In-Service Training Examination
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Brian C. Drolet, Nishant Ganesh Kumar, and Jayson S. Marwaha
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Service (systems architecture) ,medicine.medical_specialty ,Medical education ,Inservice Training ,Descriptive statistics ,Core competency ,Internship and Residency ,Interpersonal communication ,Education ,03 medical and health sciences ,Plastic surgery ,0302 clinical medicine ,Content analysis ,030220 oncology & carcinogenesis ,medicine ,Milestone (project management) ,Surgery ,Clinical Competence ,030212 general & internal medicine ,Metric (unit) ,Surgery, Plastic ,Psychology - Abstract
Background The Plastic Surgery Milestones Project was implemented in 2014 to establish standards for competency based resident education. In restructuring educational activities under the Milestones, various pedagogical tools have been revised. However, these standards have not yet been applied to the Plastic Surgery In-Service Training Examination. The purpose of this study was to determine the representation of the various components of the Plastic Surgery Milestones Project, on the In-Service Training Examination. Methods All questions from the 2014 ‐ 2018 In-Service Examinations were evaluated within the framework of the current Plastic Surgery Milestones. Using content analysis, each Examination question was mapped to a single Milestone. Descriptive analysis of Milestone subject area and Core Competency breakdown, as well as year to year trends, were performed. Results Of the 1,150 questions analyzed, there was an unequal representation of individual Milestones (0-7.4%). Of the 36 Plastic Surgery Milestones, 10 represented more than 50% of the PSITEs while 8 Milestones had less than 1% representation. The most common subject area was Head and Neck (12.7%) and least common was Reconstruction of the Trunk and Perineum. Among Core Competencies, more than half (50.4%) tested Patient Care while Interpersonal and Communication Skills was the lowest represented, 0.2%. Conclusions The Plastic Surgery In-Service Examination tests a variable proportion of Milestones. Currently, the PSITE is not well integrated with competency based education in spite of a shift towards such a training model. Going forward, the PSITE may include an associated Milestone with each question in order to better incorporate Competencies into this important annual evaluation metric.
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- 2019
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30. Nonresponse adjustment using clinical and perioperative patient characteristics is critical for understanding post-discharge opioid consumption
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Chris J. Kennedy, Larry A. Nathanson, Jayson S. Marwaha, Booth B, Scalise Pn, Gabriel A. Brat, Aaron Fleishman, and Kortney A. Robinson
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Consumption (economics) ,medicine.medical_specialty ,Percentile ,Short Message Service ,Opioid consumption ,business.industry ,Post discharge ,Emergency medicine ,medicine ,Patient characteristics ,Non-response bias ,Perioperative ,business - Abstract
BackgroundPost-discharge opioid consumption is an important source of data in guiding appropriate opioid prescribing guidelines, but its collection is tedious and requires significant resources. Furthermore, the reliability of post-discharge opioid consumption surveys is unclear. Our group developed an automated short messaging service (SMS)-to-web survey for collecting this data from patients. In this study, we assessed its effectiveness in estimating opioid consumption by performing causal adjustment and comparison to a phone-based survey as reference.MethodsPatients who underwent surgical procedures at our institution from 2019-2020 were sent an SMS message with a link to a secure web survey to quantify opioids consumed after discharge. Several patient factors extracted from the EHR were tested for association with survey response. Following targeted learning (TL) nonresponse adjustment using these EHR-based factors, opioid consumption survey results were compared to a prior telephone-based survey at our institution as a reference.Results6,553 patients were included. Opioid consumption was measured in 2,883 (44%), including 1,342 (20.5%) through survey response. Characteristics associated with inability to measure opioid consumption included age, length of stay, race, tobacco use, and missing preoperative assessment. Among the top 10 procedures by volume, EHR-based TL nonresponse bias adjustment corrected the median opioid consumption reported by an average of 57%, and corrected the 75th percentile of reported consumption by an average of 11%. This brought median estimates for 6/10 procedures closer to telephone survey-based consumption estimates, and 75th percentile estimates for 3/10 procedures closer to telephone survey-based consumption estimates.ConclusionWe found that applying electronic health record (EHR)-based machine learning nonresponse bias adjustment is essential for debiased opioid consumption estimates from patient surveys. After adjustment, post-discharge surveys can generate reliable opioid consumption estimates. Clinical factors from the EHR combined with TL adjustment appropriately capture differences between responders and nonresponders and should be used prior to generalizing or applying opioid consumption estimates to patient care.
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- 2021
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31. Overwhelmed Hospitals May Soon Lead to Overwhelmed Rehabilitation Facilities Unless Post-Acute Care Infrastructure Is Strengthened
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Jayson S, Marwaha, Carmen M, Terzic, David J, Kennedy, John, Halamka, and Gabriel A, Brat
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Inpatients ,Intensive Care Units ,Crowding ,SARS-CoV-2 ,Hospitals, Rehabilitation ,COVID-19 ,Humans ,Pandemics ,Rehabilitation Centers ,Subacute Care ,United States - Published
- 2021
32. Association of Postsurgical Opioid Refills for Patients With Risk of Opioid Misuse and Chronic Opioid Use Among Family Members
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Denis, Agniel, Gabriel A, Brat, Jayson S, Marwaha, Kathe, Fox, Daniel, Knecht, Harold L, Paz, Mark C, Bicket, Brian, Yorkgitis, Nathan, Palmer, and Isaac, Kohane
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Adult ,Analgesics, Opioid ,Cohort Studies ,Male ,Young Adult ,Adolescent ,Humans ,Family ,Female ,General Medicine ,Opioid-Related Disorders ,Retrospective Studies - Abstract
The US health care system is experiencing a sharp increase in opioid-related adverse events and spending, and opioid overprescription may be a key factor in this crisis. Ambient opioid exposure within households is one of the known major dangers of overprescription.To quantify the association between the postsurgical initiation of prescription opioid use in opioid-naive patients and the subsequent prescription opioid misuse and chronic opioid use among opioid-naive family members.This cohort study was conducted using administrative data from the database of a US commercial insurance provider with more than 35 million covered individuals. Participants included pairs of patients who underwent surgery from January 1, 2008, to December 31, 2016, and their family members within the same household. Data were analyzed from January 1 to November 30, 2018.Duration of opioid exposure and refills of opioid prescriptions received by patients after surgery.Risk of opioid misuse and chronic opioid use in family members were calculated using inverse probability weighted Cox proportional hazards regression models.The final cohort included 843 531 pairs of patients and family members. Most pairs included female patients (445 456 [52.8%]) and male family members (442 992 [52.5%]), and a plurality of pairs included patients in the 45 to 54 years age group (249 369 [29.6%]) and family members in the 15 to 24 years age group (313 707 [37.2%]). A total of 3894 opioid misuse events (0.5%) and 7485 chronic opioid use events (0.9%) occurred in family members. In adjusted models, each additional opioid prescription refill for the patient was associated with a 19.2% (95% CI, 14.5%-24.0%) increase in hazard of opioid misuse in family members. The risk of opioid misuse appeared to increase only in households in which the patient obtained refills. Family members in households with any refill had a 32.9% (95% CI, 22.7%-43.8%) increased adjusted hazard of opioid misuse. When patients became chronic opioid users, the hazard ratio for opioid misuse among family members was 2.52 (95% CI, 1.68-3.80), and similar patterns were found for chronic opioid use.This cohort study found that opioid exposure was a household risk. Family members of a patient who received opioid prescription refills after surgery had an increased risk of opioid misuse and chronic opioid use.
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- 2022
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33. Implicit Surgeon Perceptions of Patient Personas: a Framework for Surgical Informed Consent Design
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Jasmine Panton, Jayson S. Marwaha, and Gabriel A. Brat
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Nursing ,business.industry ,Informed consent ,Perception ,media_common.quotation_subject ,Medicine ,Surgery ,Persona ,business ,media_common - Published
- 2021
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34. A Nonresponse-adjusted Text Message-to-Web Survey Provides Sustainable Post-discharge Opioid Consumption Data From Surgical Patients
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Kortney A. Robinson, Aaron Fleishman, Brandon Booth, Chris J. Kennedy, Pamela Scalise, Jayson S. Marwaha, and Gabriel A. Brat
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Post discharge ,business.industry ,Opioid consumption ,medicine ,Surgery ,Medical emergency ,medicine.disease ,business ,Text message ,Web survey ,Surgical patients - Published
- 2021
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35. Comment on: Truth and truthiness: evidence, experience and clinical judgement in surgery
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Gabriel A. Brat, Brett K. Beaulieu-Jones, Jayson S. Marwaha, and William Yuan
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medicine.medical_specialty ,business.industry ,General surgery ,Clinical judgement ,Clinical Decision-Making ,History, 19th Century ,History, 20th Century ,Clinical Reasoning ,History, 18th Century ,Truth Disclosure ,History, 21st Century ,History, Medieval ,History, 17th Century ,Judgment ,History, 16th Century ,General Surgery ,Correspondence ,medicine ,Humans ,Surgery ,business ,History, Ancient ,History, 15th Century - Published
- 2021
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36. Overwhelmed Hospitals May Soon Lead to Overwhelmed Rehabilitation Facilities Unless Post–Acute Care Infrastructure Is Strengthened
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John Halamka, David J. Kennedy, Jayson S. Marwaha, Carmen M Terzic, and Gabriel A. Brat
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medicine.medical_specialty ,2019-20 coronavirus outbreak ,Rehabilitation ,Coronavirus disease 2019 (COVID-19) ,business.industry ,Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) ,medicine.medical_treatment ,MEDLINE ,Physical Therapy, Sports Therapy and Rehabilitation ,Crowding ,Post acute care ,Pandemic ,medicine ,Intensive care medicine ,business - Published
- 2021
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37. Electronic Communication of Protected Health Information: Privacy, Security, and HIPAA Compliance
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Brian C. Drolet, Phillip E. Blazar, Jayson S. Marwaha, Brad T. Hyatt, and Scott D. Lifchez
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Response rate (survey) ,business.industry ,Health Insurance Portability and Accountability Act ,010102 general mathematics ,Internet privacy ,01 natural sciences ,Compliance (psychology) ,Statute ,03 medical and health sciences ,0302 clinical medicine ,Medicine ,Orthopedics and Sports Medicine ,Surgery ,Electronic communication ,030212 general & internal medicine ,0101 mathematics ,business ,Mobile device ,Human services ,Protected health information - Abstract
Purpose Technology has enhanced modern health care delivery, particularly through accessibility to health information and ease of communication with tools like mobile device messaging (texting). However, text messaging has created new risks for breach of protected health information (PHI). In the current study, we sought to evaluate hand surgeons' knowledge and compliance with privacy and security standards for electronic communication by text message. Methods A cross-sectional survey of the American Society for Surgery of the Hand membership was conducted in March and April 2016. Descriptive and inferential statistical analyses were performed of composite results as well as relevant subgroup analyses. Results A total of 409 responses were obtained (11% response rate). Although 63% of surgeons reported that they believe that text messaging does not meet Health Insurance Portability and Accountability Act of 1996 security standards, only 37% reported they do not use text messages to communicate PHI. Younger surgeons and respondents who believed that their texting was compliant were statistically significantly more like to report messaging of PHI (odds ratio, 1.59 and 1.22, respectively). Discussion A majority of hand surgeons in this study reported the use of text messaging to communicate PHI. Of note, neither the Health Insurance Portability and Accountability Act of 1996 statute nor US Department of Health and Human Services specifically prohibits this form of electronic communication. To be compliant, surgeons, practices, and institutions need to take reasonable security precautions to prevent breach of privacy with electronic communication. Clinical relevance Communication of clinical information by text message is not prohibited under Health Insurance Portability and Accountability Act of 1996, but surgeons should use appropriate safeguards to prevent breach when using this form of communication.
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- 2017
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38. Preoperative Myocardial Injury as a Predictor of Mortality in Emergency General Surgery: An Analysis Using the American College of Surgeons NSQIP Database
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Charles A. Adams, David P. Harrington, Asha Zimmerman, Andrew H. Stephen, Hector Nunez, Jayson S. Marwaha, Daithi S. Heffernan, and Sean F. Monaghan
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Adult ,Male ,medicine.medical_specialty ,Multivariate analysis ,Databases, Factual ,030204 cardiovascular system & hematology ,computer.software_genre ,Risk Assessment ,03 medical and health sciences ,Postoperative Complications ,0302 clinical medicine ,Risk Factors ,Troponin I ,medicine ,Humans ,030212 general & internal medicine ,Adverse effect ,Aged ,Retrospective Studies ,biology ,Database ,Septic shock ,business.industry ,General surgery ,Retrospective cohort study ,Odds ratio ,Middle Aged ,Prognosis ,medicine.disease ,Troponin ,Surgery ,Logistic Models ,General Surgery ,Surgical Procedures, Operative ,Multivariate Analysis ,Preoperative Period ,biology.protein ,Female ,Emergencies ,Cardiomyopathies ,Risk assessment ,business ,computer ,Biomarkers - Abstract
Recent studies have linked postoperative serum troponin elevation to mortality in a range of different clinical scenarios. To date, there has been no investigation into the significance of preoperative troponin elevation in emergency general surgery (EGS) patients. We define this as preoperative myocardial injury (PMI). We hypothesize that PMI seen in EGS patients may predict postoperative morbidity and mortality.Using the American College of Surgeons (ACS) National Surgical Quality Improvement Program (NSQIP) database, we performed a retrospective review of all EGS cases between 2008 and 2014. Patients with preoperative troponin I drawn were compared.There were 464 EGS patients who had troponin I measurements preoperatively. Eighty-two (18%) had preoperative troponin elevations. Patients with PMI were more likely to have the following preoperative physiologic derangements: acute renal failure (18% vs 4%; p = 0.002) and septic shock (40% vs 13%; p0.001). Patient comorbidities associated with PMI included congestive heart failure (13% vs 3%; p = 0.007), dialysis dependence (16% vs 3%; p = 0.002), and American Society of Anesthesiologists (ASA) class ≥ 4 (52% vs 29%; p0.001). Compared with controls, patients with PMI had higher rates of postoperative events (77% vs 52%; p0.001) and mortality (34% vs 13%; p = 0.009). Univariate analysis showed that patients with PMI had an increased risk of postoperative events (odds ratio [OR] 3.02; 95% CI 1.74 to 5.25) and mortality (OR 3.53; 95% CI 1.66 to 7.47). Multivariate analysis revealed preoperative troponin I elevation was an independent predictor of mortality (OR 3.03; 95% CI 1.19 to 7.72, p = 0.020).Emergency general surgery patients with PMI are at increased risk for postoperative events and death. Preoperative myocardial injury is an independent predictor of mortality and has prognostic utility that can prepare surgical teams for adverse events so that they can be recognized, evaluated, and treated earlier.
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- 2016
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39. Program Director Perceptions of the General Surgery Milestones Project
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Brian C. Drolet, Adam Pallant, Abdul Wasey, and Jayson S. Marwaha
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Male ,medicine.medical_specialty ,Evaluation system ,020205 medical informatics ,media_common.quotation_subject ,Graduate medical education ,02 engineering and technology ,Positive perception ,Education ,Physician Executives ,03 medical and health sciences ,0302 clinical medicine ,Overall response rate ,Perception ,0202 electrical engineering, electronic engineering, information engineering ,medicine ,Humans ,030212 general & internal medicine ,media_common ,Accreditation ,Medical education ,business.industry ,General surgery ,Core competency ,food and beverages ,Program director ,Quality Improvement ,Competency-Based Education ,United States ,Education, Medical, Graduate ,Family medicine ,General Surgery ,Surgery ,Female ,Clinical Competence ,business ,Program Evaluation - Abstract
Objective As a result of the Milestones Project, all Accreditation Council for Graduate Medical Education accredited training programs now use an evaluation framework based on outcomes in 6 core competencies. Despite their widespread use, the Milestones have not been broadly evaluated. This study sought to examine program director (PD) perceptions of the Milestones Project. Design, Setting, and Participants A national survey of general surgery PDs distributed between January and March of 2016. Results A total of 132 surgical PDs responded to the survey (60% response rate). Positive perceptions included value for education (55%) and evaluation of resident performance (58%), as well as ability of Milestones to provide unbiased feedback (55%) and to identify areas of resident deficiency (58%). Meanwhile, time input and the ability of Milestones to discriminate underperforming programs were less likely to be rated positively (25% and 21%, respectively). Half of PDs felt that the Milestones were an improvement over their previous evaluation system (55%). Conclusions Using the Milestones as competency-based, developmental outcomes measures, surgical PDs reported perceived benefits for education and objectivity in the evaluation of resident performance. The overall response to the Milestones was generally favorable, and most PDs would not return to their previous evaluation systems. To improve future iterations of the Milestones, many PDs expressed a desire for customization of the Milestones’ content and structure to allow for programmatic differences.
- Published
- 2016
40. Reappraisal of mesenchymal chondrosarcoma: novel morphologic observations of the hyaline cartilage and endochondral ossification and β-catenin, Sox9, and osteocalcin immunostaining of 22 cases
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Aaron Auerbach, Elisabeth J. Rushing, Jayson S. Marwaha, Zengfeng Wang, and Julie C. Fanburg-Smith
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Adult ,Male ,musculoskeletal diseases ,Pathology ,medicine.medical_specialty ,animal structures ,Adolescent ,Osteocalcin ,Bone Neoplasms ,Biology ,Bone and Bones ,Pathology and Forensic Medicine ,Chondrocytes ,medicine ,Humans ,Child ,Endochondral ossification ,beta Catenin ,Aged ,Osteoblasts ,Brain Neoplasms ,Hyaline cartilage ,Ossification ,Ossification, Heterotopic ,Cartilage ,SOX9 Transcription Factor ,Middle Aged ,musculoskeletal system ,medicine.disease ,Chondrogenesis ,Immunohistochemistry ,Mesenchymal chondrosarcoma ,Hyaline Cartilage ,medicine.anatomical_structure ,embryonic structures ,Chondrosarcoma, Mesenchymal ,Female ,Sarcoma ,Chondrosarcoma ,medicine.symptom - Abstract
Mesenchymal chondrosarcoma, a rare malignant round cell and hyaline cartilage tumor, is most commonly intraosseous but can occur in extraskeletal sites. We intensively observed the morphology and applied Sox9 (master regulator of chondrogenesis), beta-catenin (involved in bone formation, thought to inhibit chondrogenesis in a Sox9-dependent manner), and osteocalcin (a marker for osteoblastic phenotype) to 22 central nervous system and musculoskeletal mesenchymal chondrosarcoma. Cases of mesenchymal chondrosarcoma were retrieved and reviewed from our files. Immunohistochemistry and follow-up were obtained on mesenchymal chondrosarcoma and tumor controls. Twenty-two mesenchymal chondrosarcomas included 5 central nervous system (all female; mean age, 30.2; mean size, 7.8 cm; in frontal lobe [n = 4] and spinal cord [n = 1]) and 17 musculoskeletal (female-male ratio, 11:6; mean age, 31.1; mean size, 6.2 cm; 3 each of humerus and vertebrae; 2 each of pelvis, rib, tibia, neck soft tissue; one each of femur, unspecified bone, and elbow soft tissue). The hyaline cartilage in most tumors revealed a consistent linear progression of chondrocyte morphology, from resting to proliferating to hypertrophic chondrocytes. Sixty-seven percent of cases demonstrated cell death and acquired osteoblastic phenotype, cells positive for osteocalcin at the site of endochondral ossification. Small round cells of mesenchymal chondrosarcoma were negative for osteocalcin. SOX9 was positive in both components of 21 of 22 cases of mesenchymal chondrosarcoma. beta-Catenin highlighted rare nuclei at the interface between round cells and hyaline cartilage in 35% cases. Control skull and central nervous system cases were compared, including chondrosarcomas and small cell osteosarcoma, the latter positive for osteocalcin in small cells. Mesenchymal chondrosarcoma demonstrates centrally located hyaline cartilage with a linear progression of chondrocytes from resting to proliferative to hypertrophic, which undergoes endochondral ossification, recapitulating growth plate cartilage and suggesting that this component of mesenchymal chondrosarcoma may be a differentiated (benign or metaplastic) component of a malignant metastasizing tumor. This hyaline cartilage component is morphologically different from cartilage of control chondrosarcoma. Mesenchymal chondrosarcoma can be separated from small cell osteosarcoma, using Sox 9 for cartilage and osteocalcin for osteoblastic phenotype. Rare nuclear beta-catenin expression at the interface between hyaline cartilage and small round cells potentially implicates the APC/Wnt pathway during endochondral ossification in morphologically benign hyaline cartilage component of mesenchymal chondrosarcoma.
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- 2010
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41. The Impact of the 2011 Accreditation Council for Graduate Medical Education Duty Hour Reform on Quality and Safety in Trauma Care
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Brian C. Drolet, Suma S. Maddox, Charles A. Adams, and Jayson S. Marwaha
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Gerontology ,Adult ,Male ,medicine.medical_specialty ,Quality Assurance, Health Care ,media_common.quotation_subject ,Graduate medical education ,Personnel Staffing and Scheduling ,Workload ,030204 cardiovascular system & hematology ,Accreditation ,03 medical and health sciences ,0302 clinical medicine ,Trauma Centers ,Medicine ,Humans ,Quality (business) ,030212 general & internal medicine ,Duty ,media_common ,Aged ,Quality Indicators, Health Care ,Retrospective Studies ,Academic Medical Centers ,business.industry ,Trauma center ,Internship and Residency ,Rhode Island ,Middle Aged ,Trauma care ,Outcome and Process Assessment, Health Care ,Traumatology ,Education, Medical, Graduate ,Family medicine ,Injury Severity Score ,Resource use ,Regression Analysis ,Surgery ,Female ,Patient Safety ,business ,Follow-Up Studies - Abstract
In 2011, the ACGME limited duty hours for residents. Although studies evaluating the 2011 policy have not shown improvements in general measures of morbidity or mortality, these outcomes might not reflect changes in specialty-specific practice patterns and secondary quality measures.All trauma admissions from July 2009 through June 2013 at an academic Level I trauma center were evaluated for 5 primary outcomes (eg, mortality and length of stay), and 10 secondary quality measures and practice patterns (eg, operating room [OR] visits). All variables were compared before and after the reform (July 1, 2011). Piecewise regression was used to study temporal trends in quality.There were 11,740 admissions studied. The reform was not strongly associated with changes in any primary outcomes except length of stay (7.98 to 7.36 days; p = 0.01). However, many secondary quality metrics changed. The total number of OR and bedside procedures per admission (6.72 to 7.34; p0.001) and OR visits per admission (0.76 to 0.91; p 0.001) were higher in the post-reform group, representing an additional 9,559 procedures and 1,584 OR visits. Use of minor bedside procedures, such as laboratory and imaging studies, increased most significantly.Although most major outcomes were unaffected, quality of care might have changed after the reform. Indeed, a consistent change in resource use patterns was manifested by substantial post-reform increases in measures such as bedside procedures and OR visits. No secondary quality measures exhibited improvements strongly associated with the reform. Several factors, including attending oversight, might have insulated major outcomes from change. Our findings show that some less-commonly studied quality metrics related to costs of care changed after the 2011 reform at our institution.
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- 2015
42. Impact of Multiple-Service Coverage Shifts on Quality and Safety in Trauma Care
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Charles A. Adams, Brian C. Drolet, and Jayson S. Marwaha
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business.industry ,media_common.quotation_subject ,Medicine ,Surgery ,Quality (business) ,Medical emergency ,business ,Trauma care ,medicine.disease ,Service coverage ,media_common - Published
- 2017
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43. Soft tissue Rosai-Dorfman disease: 29 new lesions in 18 patients, with detection of polyomavirus antigen in 3 abdominal cases
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A. Anandan, Aaron Auerbach, Jayson S. Marwaha, Julie C. Fanburg-Smith, Wael Al-Daraji, and Mary Klassen-Fischer
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Adult ,Male ,Pathology ,medicine.medical_specialty ,Adolescent ,Simian virus 40 ,Biology ,Pathology and Forensic Medicine ,Lesion ,Abdomen ,medicine ,Humans ,Antigens, Viral, Tumor ,Child ,Histiocyte ,Rosai–Dorfman disease ,Aged ,Aged, 80 and over ,S100 Proteins ,Soft tissue ,General Medicine ,Middle Aged ,medicine.disease ,Emperipolesis ,medicine.anatomical_structure ,Pleomorphism (cytology) ,Inflammatory pseudotumor ,Female ,medicine.symptom ,Histiocytosis, Sinus ,Polyomavirus - Abstract
Soft tissue Rosai-Dorfman disease (STRDD) is rare, previously reported only as single cases and few series. Simian virus 40 (SV40), a polyomavirus, has been identified in lymphoid processes and has a controversial role in neoplasia etiology. Occasional cytoplasmic pink granular inclusions and nuclear changes led us to explore a viral etiology. Only unpublished STRDD from our files with adequate material, soft tissue location, and diagnostic confirmation were included. Immunohistochemistry and follow-up were obtained. Eighteen STRDD patients, 4 male and 14 female, had 29 lesions; 5 with 2 or more lesions. Ages ranged from 8 to 81 years (mean 42.6 years and median 42.5 years). Soft tissue Rosai-Dorfman disease locations include trunk or proximal extremity (n = 19), distal extremity (n = 5), "abdominal" (n = 3), face (n = 1), and unknown subcutaneous site (n = 1). Sizes ranged from 0.5 to 13.7 cm (median, 2.4 cm). Previous disease included lymphoma, buttocks injection site, diabetes and hypothyroidism, and radiation for chronic dermopathy. No patients had a preceding or concurrent known viral infection; none had lymphadenopathy at present. None were known to be immunocompromised. Soft tissue Rosai-Dorfman disease was rapidly progressing. Initial pathologic diagnosis ranged from Rosai-Dorfman disease or inflammatory pseudotumor to inflammatory malignant fibrous histiocytoma. Grossly STRDDs were multilobulated, tan-yellow, and firm; morphologically, circumscribed, and subcutaneous-based. All had sheets of polygonal histiocytes with abundant pale eosinophilic cytoplasm, emperipolesis, plasma cells, and lymphocytes scattered and within clusters. Focal spindle cell change and mild pleomorphism were each observed in 3 patients; 2 had focal necrosis, none with mitoses. Small granular pink cytoplasmic inclusions and nuclear viral-like changes were observed. By immunohistochemistry, all STRDDs were positive for S100 protein, negative for CD1a, Epstein-Barr virus, and latent membrane protein, yet 3 (all abdominal, 1 multicentric) of the 9 studied were focally positive for cytoplasmic and nuclear SV40 polyomavirus. All were treated by local excision. Follow-up on 14 patients older than 8 to 16 years revealed recurrence in 3 patients with persistent multiple lesions, one with abdominal location. There were no metastases or death from disease. Soft tissue Rosai-Dorfman disease is a rapidly evolving, mostly solitary and nonrecurrent trunk and proximal extremity subcutaneous lesion in middle-aged females. More than one third can have persistent multicentric disease. It is important to recognize STRDD, to separate it from malignancy. Epstein-Barr virus/latent membrane protein was negative but polyomavirus was positive in 3 patients with abdominal STRDD, one with multicentric persistent disease. The relationship of polyomavirus to the evolution of abdominal STRDD should be further explored.
- Published
- 2010
44. Immunoprofile of mesenchymal chondrosarcoma: aberrant desmin and EMA expression, retention of INI1, and negative estrogen receptor in 22 female-predominant central nervous system and musculoskeletal cases
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Mariarita Santi, Alexander R. Judkins, Julie C. Fanburg-Smith, Jayson S. Marwaha, Elisabeth J. Rushing, Aaron Auerbach, and Zengfeng Wang
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Adult ,Male ,Pathology ,medicine.medical_specialty ,Adolescent ,Chromosomal Proteins, Non-Histone ,Nervous System Neoplasms ,Estrogen receptor ,Bone Neoplasms ,Biology ,Pathology and Forensic Medicine ,Desmin ,Young Adult ,medicine ,Biomarkers, Tumor ,Humans ,Rhabdomyosarcoma ,Child ,Myogenin ,Aged ,Mucin-1 ,General Medicine ,SMARCB1 Protein ,Middle Aged ,medicine.disease ,Immunohistochemistry ,Mesenchymal chondrosarcoma ,body regions ,DNA-Binding Proteins ,Teratoid tumor ,Receptors, Estrogen ,Chondrosarcoma, Mesenchymal ,Female ,Chondrosarcoma ,Follow-Up Studies ,Transcription Factors - Abstract
Mesenchymal chondrosarcoma is a rare malignant tumor in the differential diagnosis of other small, round blue cell tumors, including atypical teratoid tumor in the central nervous system (CNS) and rhabdomyosarcoma in the musculoskeletal (MSK) locations. We reviewed the morphology of CNS and MSK cases and applied a panel of immunostains. Archival cases were pulled from our files. Immunohistochemistry and follow-up were obtained. Twenty-two cases included 5 CNS (all female; mean age, 30.2) and 17 MSK (11 female and 6 male; mean age, 31.1). Both CNS and MSK examples had similar round cells, staghorn vascular pattern, increased mitotic activity, and centrally located hyaline cartilage islands. The CNS examples demonstrated more spindling and the MSK cases more necrosis. INI1 was retained in all tumors studied. Epithelial membrane antigen (EMA) and desmin were expressed focally in 35% and 50% of cases, respectively. The round cells of all cases were negative for MyoD1, myogenin, smooth muscle actin (SMA), glial fibrillary acid protein (GFAP), keratins, and estrogen receptor, as well as a panel of other antiobodies. Eighty percent of patients with follow-up had pulmonary metastases and/or died within a mean of 5 years. The CNS and MSK mesenchymal chondrosarcoma predominantly affects adult females with poor prognosis. There are only subtle morphologic differences between the CNS and MSK groups. By immunohistochemistry, mesenchymal chondrosarcoma occasionally expresses aberrant desmin and EMA but is negative for SMA, myogenin MyoD1, GFAP, and keratins, refuting true smooth or skeletal muscle, epithelial, or meningothelial phenotype. Retained INI1 separates these tumors from atypical teratoid tumor. Despite marked female predominance in our series, estrogen receptor is negative in mesenchymal chondrosarcoma.
- Published
- 2009
45. Efficacy of technology-driven interventions targeting hospital equipment breakdowns in Zanzibar, Tanzania
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H.S. Chia, K. McCracken, M. Koster, Jayson S. Marwaha, and J. Hamad
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medicine.medical_specialty ,biology ,business.industry ,Psychological intervention ,Infectious and parasitic diseases ,RC109-216 ,General Medicine ,biology.organism_classification ,Tanzania ,Family medicine ,medicine ,Optometry ,Public aspects of medicine ,RA1-1270 ,business - Published
- 2014
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46. Distinguishing Admissions Specifically for COVID-19 From Incidental SARS-CoV-2 Admissions: National Retrospective Electronic Health Record Study
- Author
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Jeffrey G Klann, Zachary H Strasser, Meghan R Hutch, Chris J Kennedy, Jayson S Marwaha, Michele Morris, Malarkodi Jebathilagam Samayamuthu, Ashley C Pfaff, Hossein Estiri, Andrew M South, Griffin M Weber, William Yuan, Paul Avillach, Kavishwar B Wagholikar, Yuan Luo, Gilbert S Omenn, Shyam Visweswaran, John H Holmes, Zongqi Xia, Gabriel A Brat, and Shawn N Murphy
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Computer applications to medicine. Medical informatics ,R858-859.7 ,Public aspects of medicine ,RA1-1270 - Abstract
BackgroundAdmissions are generally classified as COVID-19 hospitalizations if the patient has a positive SARS-CoV-2 polymerase chain reaction (PCR) test. However, because 35% of SARS-CoV-2 infections are asymptomatic, patients admitted for unrelated indications with an incidentally positive test could be misclassified as a COVID-19 hospitalization. Electronic health record (EHR)–based studies have been unable to distinguish between a hospitalization specifically for COVID-19 versus an incidental SARS-CoV-2 hospitalization. Although the need to improve classification of COVID-19 versus incidental SARS-CoV-2 is well understood, the magnitude of the problems has only been characterized in small, single-center studies. Furthermore, there have been no peer-reviewed studies evaluating methods for improving classification. ObjectiveThe aims of this study are to, first, quantify the frequency of incidental hospitalizations over the first 15 months of the pandemic in multiple hospital systems in the United States and, second, to apply electronic phenotyping techniques to automatically improve COVID-19 hospitalization classification. MethodsFrom a retrospective EHR-based cohort in 4 US health care systems in Massachusetts, Pennsylvania, and Illinois, a random sample of 1123 SARS-CoV-2 PCR-positive patients hospitalized from March 2020 to August 2021 was manually chart-reviewed and classified as “admitted with COVID-19” (incidental) versus specifically admitted for COVID-19 (“for COVID-19”). EHR-based phenotyping was used to find feature sets to filter out incidental admissions. ResultsEHR-based phenotyped feature sets filtered out incidental admissions, which occurred in an average of 26% of hospitalizations (although this varied widely over time, from 0% to 75%). The top site-specific feature sets had 79%-99% specificity with 62%-75% sensitivity, while the best-performing across-site feature sets had 71%-94% specificity with 69%-81% sensitivity. ConclusionsA large proportion of SARS-CoV-2 PCR-positive admissions were incidental. Straightforward EHR-based phenotypes differentiated admissions, which is important to assure accurate public health reporting and research.
- Published
- 2022
- Full Text
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