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Ranallo P, Southwell B, Tignanelli C, Johnson SG, Krueger R, Sevareid-Groth T, Carvel A, Melton GB. Promoting Learning Health System Cycles by Optimizing EHR Data Clinical Concept Encoding Processes. Stud Health Technol Inform 2024; 310:68-73. [PMID: 38269767 DOI: 10.3233/shti230929] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/26/2024]
Abstract
Electronic health records (EHRs) and other real-world data (RWD) are critical to accelerating and scaling care improvement and transformation. To efficiently leverage it for secondary uses, EHR/RWD should be optimally managed and mapped to industry standard concepts (ISCs). Inherent challenges in concept encoding usually result in inefficient and costly workflows and resultant metadata representation structures outside the EHR. Using three related projects to map data to ISCs, we describe the development of standard, repeatable processes for precisely and unambiguously representing EHR data using appropriate ISCs within the EHR platform lifecycle and mappings specific to SNOMED-CT for Demographics, Specialty and Services. Mappings in these 3 areas resulted in ISC mappings of 779 data elements requiring 90 new concept requests to SNOMED-CT and 738 new ISCs mapped into the workflow within an accessible, enterprise-wide EHR resource with supporting processes.
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Affiliation(s)
| | | | | | | | | | | | - Adam Carvel
- Fairview Health Services, Minneapolis, MN USA
| | - Genevieve B Melton
- Fairview Health Services, Minneapolis, MN USA
- University of Minnesota, Minneapolis, MN USA
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2
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Faccini de Lima C, Wang F, Leffel TA, Miller T, Johnson SG, Gumennik A. Multimaterial fiber as a physical simulator of a capillary instability. Nat Commun 2023; 14:5816. [PMID: 37752148 PMCID: PMC10522671 DOI: 10.1038/s41467-023-41216-7] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/13/2023] [Accepted: 08/28/2023] [Indexed: 09/28/2023] Open
Abstract
Capillary breakup of cores is an exclusive approach to fabricating fiber-integrated optoelectronics and photonics. A physical understanding of this fluid-dynamic process is necessary for yielding the desired solid-state fiber-embedded multimaterial architectures by design rather than by exploratory search. We discover that the nonlinearly complex and, at times, even chaotic capillary breakup of multimaterial fiber cores becomes predictable when the fiber is exposed to the spatiotemporal temperature profile, imposing a viscosity modulation comparable to the breakup wavelength. The profile acts as a notch filter, allowing only a single wavelength out of the continuous spectrum to develop predictably, following Euler-Lagrange dynamics. We argue that this understanding not only enables designing the outcomes of the breakup necessary for turning it into a technology for materializing fiber-embedded functional systems but also positions a multimaterial fiber as a universal physical simulator of capillary instability in viscous threads.
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Affiliation(s)
- Camila Faccini de Lima
- Department of Intelligent Systems Engineering, Luddy School of Informatics, Computing, and Engineering, Indiana University Bloomington, Bloomington, IN, USA
| | - Fan Wang
- Department of Mechanical Engineering, Massachusetts Institute of Technology, Cambridge, MA, USA
| | - Troy A Leffel
- Department of Intelligent Systems Engineering, Luddy School of Informatics, Computing, and Engineering, Indiana University Bloomington, Bloomington, IN, USA
| | - Tyson Miller
- Department of Intelligent Systems Engineering, Luddy School of Informatics, Computing, and Engineering, Indiana University Bloomington, Bloomington, IN, USA
| | - Steven G Johnson
- Department of Mathematics, Massachusetts Institute of Technology, Cambridge, MA, USA
- Department of Physics, Massachusetts Institute of Technology, Cambridge, MA, USA
| | - Alexander Gumennik
- Department of Intelligent Systems Engineering, Luddy School of Informatics, Computing, and Engineering, Indiana University Bloomington, Bloomington, IN, USA.
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3
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Li WF, Arya G, Roques-Carmes C, Lin Z, Johnson SG, Soljačić M. Transcending shift-invariance in the paraxial regime via end-to-end inverse design of freeform nanophotonics. Opt Express 2023; 31:24260-24272. [PMID: 37475257 DOI: 10.1364/oe.492553] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Received: 04/18/2023] [Accepted: 05/28/2023] [Indexed: 07/22/2023]
Abstract
Traditional optical elements and conventional metasurfaces obey shift-invariance in the paraxial regime. For imaging systems obeying paraxial shift-invariance, a small shift in input angle causes a corresponding shift in the sensor image. Shift-invariance has deep implications for the design and functionality of optical devices, such as the necessity of free space between components (as in compound objectives made of several curved surfaces). We present a method for nanophotonic inverse design of compact imaging systems whose resolution is not constrained by paraxial shift-invariance. Our method is end-to-end, in that it integrates density-based full-Maxwell topology optimization with a fully iterative elastic-net reconstruction algorithm. By the design of nanophotonic structures that scatter light in a non-shift-invariant manner, our optimized nanophotonic imaging system overcomes the limitations of paraxial shift-invariance, achieving accurate, noise-robust image reconstruction beyond shift-invariant resolution.
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Wong R, Lam E, Bramante CT, Johnson SG, Reusch J, Wilkins KJ, Yeh HC. Does COVID-19 Infection Increase the Risk of Diabetes? Current Evidence. Curr Diab Rep 2023:10.1007/s11892-023-01515-1. [PMID: 37284921 DOI: 10.1007/s11892-023-01515-1] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Grants] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Accepted: 05/18/2023] [Indexed: 06/08/2023]
Abstract
PURPOSE OF REVIEW Multiple studies report an increased incidence of diabetes following SARS-CoV-2 infection. Given the potential increased global burden of diabetes, understanding the effect of SARS-CoV-2 in the epidemiology of diabetes is important. Our aim was to review the evidence pertaining to the risk of incident diabetes after COVID-19 infection. RECENT FINDINGS Incident diabetes risk increased by approximately 60% compared to patients without SARS-CoV-2 infection. Risk also increased compared to non-COVID-19 respiratory infections, suggesting SARS-CoV-2-mediated mechanisms rather than general morbidity after respiratory illness. Evidence is mixed regarding the association between SARS-CoV-2 infection and T1D. SARS-CoV-2 infection is associated with an elevated risk of T2D, but it is unclear whether the incident diabetes is persistent over time or differs in severity over time. SARS-CoV-2 infection is associated with an increased risk of incident diabetes. Future studies should evaluate vaccination, viral variant, and patient- and treatment-related factors that influence risk.
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Affiliation(s)
- Rachel Wong
- Department of Biomedical Informatics, Stony Brook University, Stony Brook, NY, USA.
- Health Science Center, Stony Brook Medical Center, Level 3, Room 45101 Nicolls Road, Stony Brook, NY, 11794, USA.
| | - Emily Lam
- Department of Biomedical Informatics, Stony Brook University, Stony Brook, NY, USA
| | - Carolyn T Bramante
- Division of General Internal Medicine, University of Minnesota Medical School, Minneapolis, MN, USA
| | - Steven G Johnson
- Institute for Health Informatics, University of Minnesota, Minneapolis, MN, USA
| | - Jane Reusch
- Division of Endocrinology, Metabolism & Diabetes, University of Colorado Anschutz Medical Campus, Aurora, CO, 80045, USA
| | - Kenneth J Wilkins
- Biostatistics Program/Office of Clinical Research Support, National Institute of Diabetes and Digestive and Kidney Diseases, National Institutes of Health, Bethesda, MD, USA
| | - Hsin-Chieh Yeh
- Department of Medicine, Johns Hopkins University, Baltimore, MD, USA
- Department of Epidemiology, Johns Hopkins University, Baltimore, MD, USA
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5
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Johnson SG, Fermin LM, Aberdein D, Lawrence KE. Smooth muscle hamartoma in a castrated male red deer ( Cervus elaphus) in New Zealand. N Z Vet J 2023:1-3. [PMID: 37070608 DOI: 10.1080/00480169.2023.2204827] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 04/19/2023]
Affiliation(s)
- S G Johnson
- Tāwharau Ora - School of Veterinary Science, Massey University, Palmerston North, New Zealand
| | - L M Fermin
- Tāwharau Ora - School of Veterinary Science, Massey University, Palmerston North, New Zealand
| | - D Aberdein
- Tāwharau Ora - School of Veterinary Science, Massey University, Palmerston North, New Zealand
| | - K E Lawrence
- Tāwharau Ora - School of Veterinary Science, Massey University, Palmerston North, New Zealand
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Reddy NV, Yeh HC, Tronieri JS, Stürmer T, Buse JB, Reusch JE, Johnson SG, Wong R, Moffitt R, Wilkins KJ, Harper J, Bramante CT. Are fewer cases of diabetes mellitus diagnosed in the months after SARS-CoV-2 infection? A population-level view in the EHR-based RECOVER program. J Clin Transl Sci 2023; 7:e90. [PMID: 37125061 PMCID: PMC10130848 DOI: 10.1017/cts.2023.34] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/07/2022] [Revised: 02/24/2023] [Accepted: 02/27/2023] [Indexed: 03/11/2023] Open
Abstract
Long-term sequelae of severe acute respiratory coronavirus-2 (SARS-CoV-2) infection may include increased incidence of diabetes. Here we describe the temporal relationship between new type 2 diabetes and SARS-CoV-2 infection in a nationwide database. We found that while the proportion of newly diagnosed type 2 diabetes increased during the acute period of SARS-CoV-2 infection, the mean proportion of new diabetes cases in the 6 months post-infection was about 83% lower than the 6 months preinfection. These results underscore the need for further investigation to understand the timing of new diabetes after COVID-19, etiology, screening, and treatment strategies.
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Affiliation(s)
- Neha V. Reddy
- Division of General Internal Medicine, Department of Medicine, University of Minnesota Medical School, Minneapolis, MN, USA
| | - Hsin-Chieh Yeh
- Departments of Medicine, Epidemiology and Oncology, Welch Center for Prevention, Epidemiology, and Clinical Research, Johns Hopkins University, Baltimore, MD, USA
| | - Jena S. Tronieri
- Department of Psychiatry, Perelman School of Medicine at the University of Pennsylvania, Philadelphia, PA, USA
| | - Til Stürmer
- Department of Epidemiology, Gillings School of Global Public Health, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA
| | - John B. Buse
- Division of Endocrinology, Department of Medicine, University of North Carolina Medical School, Chapel Hill, NC, USA
| | - Jane E. Reusch
- University of Colorado Denver Anschutz Medical Campus, Denver, CO, USA
| | - Steven G. Johnson
- Institute for Health Informatics, University of Minnesota, Minneapolis, MN, USA
| | - Rachel Wong
- Department of Biomedical Informatics, Stony Brook University, Stony Brook, NY, USA
| | - Richard Moffitt
- Department of Biomedical Informatics, Stony Brook University, Stony Brook, NY, USA
| | - Kenneth J. Wilkins
- Biostatistics Program, Office of the Director, National Institute of Diabetes and Digestive and Kidney Disease, Bethesda, MD, USA
| | | | - Carolyn T. Bramante
- Division of General Internal Medicine, Department of Medicine, University of Minnesota Medical School, Minneapolis, MN, USA
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7
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Casiraghi E, Wong R, Hall M, Coleman B, Notaro M, Evans MD, Tronieri JS, Blau H, Laraway B, Callahan TJ, Chan LE, Bramante CT, Buse JB, Moffitt RA, Stürmer T, Johnson SG, Raymond Shao Y, Reese J, Robinson PN, Paccanaro A, Valentini G, Huling JD, Wilkins KJ. A method for comparing multiple imputation techniques: A case study on the U.S. national COVID cohort collaborative. J Biomed Inform 2023; 139:104295. [PMID: 36716983 PMCID: PMC10683778 DOI: 10.1016/j.jbi.2023.104295] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/02/2022] [Revised: 01/16/2023] [Accepted: 01/21/2023] [Indexed: 02/01/2023]
Abstract
Healthcare datasets obtained from Electronic Health Records have proven to be extremely useful for assessing associations between patients' predictors and outcomes of interest. However, these datasets often suffer from missing values in a high proportion of cases, whose removal may introduce severe bias. Several multiple imputation algorithms have been proposed to attempt to recover the missing information under an assumed missingness mechanism. Each algorithm presents strengths and weaknesses, and there is currently no consensus on which multiple imputation algorithm works best in a given scenario. Furthermore, the selection of each algorithm's parameters and data-related modeling choices are also both crucial and challenging. In this paper we propose a novel framework to numerically evaluate strategies for handling missing data in the context of statistical analysis, with a particular focus on multiple imputation techniques. We demonstrate the feasibility of our approach on a large cohort of type-2 diabetes patients provided by the National COVID Cohort Collaborative (N3C) Enclave, where we explored the influence of various patient characteristics on outcomes related to COVID-19. Our analysis included classic multiple imputation techniques as well as simple complete-case Inverse Probability Weighted models. Extensive experiments show that our approach can effectively highlight the most promising and performant missing-data handling strategy for our case study. Moreover, our methodology allowed a better understanding of the behavior of the different models and of how it changed as we modified their parameters. Our method is general and can be applied to different research fields and on datasets containing heterogeneous types.
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Affiliation(s)
- Elena Casiraghi
- AnacletoLab, Department of Computer Science "Giovanni degli Antoni", Università degli Studi di Milano, Milan, Italy; CINI, Infolife National Laboratory, Roma, Italy; Environmental Genomics and Systems Biology Division, Lawrence Berkeley National Laboratory, Berkeley, CA, USA
| | - Rachel Wong
- Department of Biomedical Informatics, Stony Brook University, Stony Brook, NY, USA
| | - Margaret Hall
- Department of Biomedical Informatics, Stony Brook University, Stony Brook, NY, USA
| | - Ben Coleman
- The Jackson Laboratory for Genomic Medicine, Farmington, USA; Institute for Systems Genomics, University of Connecticut, Farmington, CT, USA
| | - Marco Notaro
- AnacletoLab, Department of Computer Science "Giovanni degli Antoni", Università degli Studi di Milano, Milan, Italy; CINI, Infolife National Laboratory, Roma, Italy
| | - Michael D Evans
- Biostatistical Design and Analysis Center, Clinical and Translational Science Institute, University of Minnesota, Minneapolis, MN, USA
| | - Jena S Tronieri
- Department of Psychiatry, Perelman School of Medicine at the University of Pennsylvania, Philadelphia, PA, USA
| | - Hannah Blau
- The Jackson Laboratory for Genomic Medicine, Farmington, USA
| | - Bryan Laraway
- University of Colorado, Anschutz Medical Campus, Aurora, CO, USA
| | | | - Lauren E Chan
- College of Public Health and Human Sciences, Oregon State University, Corvallis, USA
| | - Carolyn T Bramante
- Division of General Internal Medicine, University of Minnesota, Minneapolis, MN, USA
| | - John B Buse
- NC Translational and Clinical Sciences Institute, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA; Division of Endocrinology, Department of Medicine, University of North Carolina School of Medicine, USA
| | - Richard A Moffitt
- Department of Biomedical Informatics, Stony Brook University, Stony Brook, NY, USA
| | - Til Stürmer
- Department of Epidemiology, Gillings School of Global Public Health, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA
| | - Steven G Johnson
- Institute for Health Informatics, University of Minnesota, Minneapolis, MN, USA
| | - Yu Raymond Shao
- Harvard-MIT Division of Health Sciences and Technology (HST), 260 Longwood Ave, Boston, USA; Department of Radiation Oncology, UT Southwestern Medical Center, Dallas, USA
| | - Justin Reese
- Environmental Genomics and Systems Biology Division, Lawrence Berkeley National Laboratory, Berkeley, CA, USA
| | - Peter N Robinson
- The Jackson Laboratory for Genomic Medicine, Farmington, USA; Institute for Systems Genomics, University of Connecticut, Farmington, CT, USA
| | - Alberto Paccanaro
- School of Applied Mathematics (EMAp), Fundação Getúlio Vargas, Rio de Janeiro, Brazil; Department of Computer Science, Royal Holloway, University of London, Egham, UK
| | - Giorgio Valentini
- AnacletoLab, Department of Computer Science "Giovanni degli Antoni", Università degli Studi di Milano, Milan, Italy; CINI, Infolife National Laboratory, Roma, Italy
| | - Jared D Huling
- Division of Biostatistics, School of Public Health, University of Minnesota, Minneapolis, MN, USA
| | - Kenneth J Wilkins
- Biostatistics Program, Office of the Director, National Institute of Diabetes and Digestive and Kidney Diseases, National Institutes of Health, Bethesda, MD, USA
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Wang Q, Huang Z, Li J, Huang GY, Wang D, Zhang H, Guo J, Ding M, Chen J, Zhang Z, Rui Z, Shang W, Xu JY, Zhang J, Shiomi J, Fu T, Deng T, Johnson SG, Xu H, Cui K. Module-Level Polaritonic Thermophotovoltaic Emitters via Hierarchical Sequential Learning. Nano Lett 2023; 23:1144-1151. [PMID: 36749930 DOI: 10.1021/acs.nanolett.2c03476] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/18/2023]
Abstract
Thermophotovoltaic (TPV) generators provide continuous and high-efficiency power output by utilizing local thermal emitters to convert energy from various sources to thermal radiation matching the bandgaps of photovoltaic cells. Lack of effective guidelines for thermal emission control at high temperatures, poor thermal stability, and limited fabrication scalability are the three key challenges for the practical deployment of TPV devices. Here we develop a hierarchical sequential-learning optimization framework and experimentally realize a 6″ module-scale polaritonic thermal emitter with bandwidth-controlled thermal emission as well as excellent thermal stability at 1473 K. The 300 nm bandwidth thermal emission is realized by a complex photon polariton based on the superposition of Tamm plasmon polariton and surface plasmon polariton. We experimentally achieve a spectral efficiency of 65.6% (wavelength range of 0.4-8 μm) with statistical deviation less than 4% over the 6″ emitter, demonstrating industrial-level reliability for module-scale TPV applications.
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Affiliation(s)
- Qixiang Wang
- School of Materials Science and Engineering, State Key Laboratory of Metal Matrix Composites, Center for Hydrogen Science, Shanghai Jiao Tong University, Shanghai200240, China
| | - Zhequn Huang
- Zhiyuan Innovative Research Center, Shanghai Jiao Tong University, Shanghai200240, China
| | - Jiazhou Li
- Key Laboratory for Thermal Science and Power Engineering of Ministry of Education, Beijing Key Laboratory of CO2 Utilization and Reduction Technology, Department of Energy and Power Engineering, Tsinghua University, Beijing100084, China
- State Key Laboratory of Heavy Oil Processing, State Key Laboratory of Petroleum Resources and Prospecting, College of Petroleum Engineering, College of Carbon Neutrality Future Technology, China University of Petroleum, Beijing102249, China
| | - Guan-Yao Huang
- Key Laboratory for Thermal Science and Power Engineering of Ministry of Education, Beijing Key Laboratory of CO2 Utilization and Reduction Technology, Department of Energy and Power Engineering, Tsinghua University, Beijing100084, China
| | - Dewen Wang
- Research Center for Transparent Ceramics, Shanghai Institute of Ceramics, Chinese Academy of Sciences, Shanghai200050, China
| | - Heng Zhang
- School of Materials Science and Engineering, State Key Laboratory of Metal Matrix Composites, Center for Hydrogen Science, Shanghai Jiao Tong University, Shanghai200240, China
| | - Jiang Guo
- Department of Mechanical Engineering, The University of Tokyo, Tokyo113-8656, Japan
| | - Min Ding
- Shanghai HeiYi Materials Technology Co. Ltd., Shanghai200240, China
| | - Jintao Chen
- Zhiyuan College, Shanghai Jiao Tong University, Shanghai200240, China
- School of Electronic Information and Electrical Engineering, Shanghai Jiao Tong University, Shanghai200240, China
| | - Zihan Zhang
- Zhiyuan College, Shanghai Jiao Tong University, Shanghai200240, China
- School of Mathematical Science, Shanghai Jiao Tong University, Shanghai200240, China
| | - Zhenhua Rui
- State Key Laboratory of Heavy Oil Processing, State Key Laboratory of Petroleum Resources and Prospecting, College of Petroleum Engineering, College of Carbon Neutrality Future Technology, China University of Petroleum, Beijing102249, China
| | - Wen Shang
- School of Materials Science and Engineering, State Key Laboratory of Metal Matrix Composites, Center for Hydrogen Science, Shanghai Jiao Tong University, Shanghai200240, China
| | - Jia-Yue Xu
- School of Materials Science and Engineering, Shanghai Institute of Technology, Shanghai201418, China
| | - Jian Zhang
- Research Center for Transparent Ceramics, Shanghai Institute of Ceramics, Chinese Academy of Sciences, Shanghai200050, China
| | - Junichiro Shiomi
- Department of Mechanical Engineering, The University of Tokyo, Tokyo113-8656, Japan
| | - Tairan Fu
- Key Laboratory for Thermal Science and Power Engineering of Ministry of Education, Beijing Key Laboratory of CO2 Utilization and Reduction Technology, Department of Energy and Power Engineering, Tsinghua University, Beijing100084, China
| | - Tao Deng
- School of Materials Science and Engineering, State Key Laboratory of Metal Matrix Composites, Center for Hydrogen Science, Shanghai Jiao Tong University, Shanghai200240, China
| | - Steven G Johnson
- Department of Mathematics, Massachusetts Institute of Technology, Cambridge, Massachusetts02139, United States
| | - Hongxing Xu
- Institute of Advanced Studies, School of Physics and Technology, Wuhan University, Wuhan430072, China
| | - Kehang Cui
- School of Materials Science and Engineering, State Key Laboratory of Metal Matrix Composites, Center for Hydrogen Science, Shanghai Jiao Tong University, Shanghai200240, China
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Yao W, Verdugo F, Everitt HO, Christiansen RE, Johnson SG. Designing structures that maximize spatially averaged surface-enhanced Raman spectra. Opt Express 2023; 31:4964-4977. [PMID: 36785451 DOI: 10.1364/oe.472646] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Received: 08/07/2022] [Accepted: 10/02/2022] [Indexed: 06/18/2023]
Abstract
We present a general framework for inverse design of nanopatterned surfaces that maximize spatially averaged surface-enhanced Raman (SERS) spectra from molecules distributed randomly throughout a material or fluid, building upon a recently proposed trace formulation for optimizing incoherent emission. This leads to radically different designs than optimizing SERS emission at a single known location, as we illustrate using several 2D design problems addressing effects of hot-spot density, angular selectivity, and nonlinear damage. We obtain optimized structures that perform about 4 × better than coating with optimized spheres or bowtie structures and about 20 × better when the nonlinear damage effects are included.
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10
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Reddy NV, Yeh HC, Tronieri JS, Stürmer T, Buse JB, Reusch JE, Johnson SG, Wong R, Moffitt R, Wilkins KJ, Harper J, Bramante CT. Are fewer cases of diabetes mellitus diagnosed in the months after SARS-CoV-2 infection? medRxiv 2022:2022.12.02.22283029. [PMID: 36482974 PMCID: PMC9727757 DOI: 10.1101/2022.12.02.22283029] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Indexed: 12/07/2022]
Abstract
Long-term sequelae of severe acute respiratory coronavirus-2 (SARS-CoV-2) infection may include an increased incidence of diabetes. Our objective was to describe the temporal relationship between new diagnoses of diabetes mellitus and SARS-CoV-2 infection in a nationally representative database. There appears to be a sharp increase in diabetes diagnoses in the 30 days surrounding SARS-CoV-2 infection, followed by a decrease in new diagnoses in the post-acute period, up to 360 days after infection. These results underscore the need for further investigation, as understanding the timing of new diabetes onset after COVID-19 has implications regarding potential etiology and screening and treatment strategies.
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Affiliation(s)
- Neha V Reddy
- Division of General Internal Medicine, Department of Medicine, University of Minnesota Medical School, Minneapolis, MN
| | - Hsin-Chieh Yeh
- Departments of Medicine, Epidemiology and Oncology, Welch Center for Prevention, Epidemiology, and Clinical Research, Johns Hopkins University, Baltimore, MD
| | - Jena S Tronieri
- Department of Psychiatry, Perelman School of Medicine at the University of Pennsylvania, Philadelphia, PA
| | - Til Stürmer
- Department of Epidemiology, Gillings School of Global Public Health, University of North Carolina at Chapel Hill, Chapel Hill, NC
| | - John B Buse
- Division of Endocrinology, Department of Medicine, University of North Carolina Medical School, Chapel Hill, NC
| | - Jane E Reusch
- University of Colorado Denver Anschutz Medical Campus, Denver, CO
| | - Steven G Johnson
- Institute for Health Informatics, University of Minnesota, Minneapolis, MN
| | - Rachel Wong
- Department of Biomedical Informatics, Stony Brook University, Stony Brook, NY
| | - Richard Moffitt
- Department of Biomedical Informatics, Stony Brook University, Stony Brook, NY
| | - Kenneth J Wilkins
- Biostatistics Program, Office of the Director, National Institute of Diabetes and Digestive and Kidney Disease, Bethesda, MD
| | | | - Carolyn T Bramante
- Division of General Internal Medicine, Department of Medicine, University of Minnesota Medical School, Minneapolis, MN
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11
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Bramante CT, Johnson SG, Garcia V, Evans MD, Harper J, Wilkins KJ, Huling JD, Mehta H, Alexander C, Tronieri J, Hong S, Kahkoska A, Alamgir J, Koraishy F, Hartman K, Yang K, Abrahamsen T, Stürmer T, Buse JB. Diabetes medications and associations with Covid-19 outcomes in the N3C database: A national retrospective cohort study. PLoS One 2022; 17:e0271574. [PMID: 36395143 PMCID: PMC9671347 DOI: 10.1371/journal.pone.0271574] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/08/2021] [Accepted: 07/04/2022] [Indexed: 11/19/2022] Open
Abstract
BACKGROUND While vaccination is the most important way to combat the SARS-CoV-2 pandemic, there may still be a need for early outpatient treatment that is safe, inexpensive, and currently widely available in parts of the world that do not have access to the vaccine. There are in-silico, in-vitro, and in-tissue data suggesting that metformin inhibits the viral life cycle, as well as observational data suggesting that metformin use before infection with SARS-CoV2 is associated with less severe COVID-19. Previous observational analyses from single-center cohorts have been limited by size. METHODS Conducted a retrospective cohort analysis in adults with type 2 diabetes (T2DM) for associations between metformin use and COVID-19 outcomes with an active comparator design of prevalent users of therapeutically equivalent diabetes monotherapy: metformin versus dipeptidyl-peptidase-4-inhibitors (DPP4i) and sulfonylureas (SU). This took place in the National COVID Cohort Collaborative (N3C) longitudinal U.S. cohort of adults with +SARS-CoV-2 result between January 1 2020 to June 1 2021. Findings included hospitalization or ventilation or mortality from COVID-19. Back pain was assessed as a negative control outcome. RESULTS 6,626 adults with T2DM and +SARS-CoV-2 from 36 sites. Mean age was 60.7 +/- 12.0 years; 48.7% male; 56.7% White, 21.9% Black, 3.5% Asian, and 16.7% Latinx. Mean BMI was 34.1 +/- 7.8kg/m2. Overall 14.5% of the sample was hospitalized; 1.5% received mechanical ventilation; and 1.8% died. In adjusted outcomes, compared to DPP4i, metformin had non-significant associations with reduced need for ventilation (RR 0.68, 0.32-1.44), and mortality (RR 0.82, 0.41-1.64). Compared to SU, metformin was associated with a lower risk of ventilation (RR 0.5, 95% CI 0.28-0.98, p = 0.044) and mortality (RR 0.56, 95%CI 0.33-0.97, p = 0.037). There was no difference in unadjusted or adjusted results of the negative control. CONCLUSIONS There were clinically significant associations between metformin use and less severe COVID-19 compared to SU, but not compared to DPP4i. New-user studies and randomized trials are needed to assess early outpatient treatment and post-exposure prophylaxis with therapeutics that are safe in adults, children, pregnancy and available worldwide.
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Affiliation(s)
- Carolyn T. Bramante
- Division of General Internal Medicine, Department of Medicine, University of Minnesota Medical School, Minneapolis, Minnesota, United States of America
| | - Steven G. Johnson
- Institute for Health Informatics, University of Minnesota Medical School, Minneapolis, Minnesota, United States of America
| | - Victor Garcia
- Department of Biomedical Informatics, Stony Brook University Hospital, Stony Brook, New York, United States of America
| | - Michael D. Evans
- Biostatistical Design and Analysis Center, University of Minnesota Medical School, Minneapolis, Minnesota, United States of America
| | - Jeremy Harper
- Owl HealthWorks, Indianapolis, IN, United States of America
| | - Kenneth J. Wilkins
- Biostatistics Program, Office of the Director, National Institute of Diabetes and Digestive and Kidney Disease, Bethesda, Maryland, United States of America
| | - Jared D. Huling
- Division of Biostatistics, University of Minnesota School of Public Health, Minneapolis, Minnesota, United States of America
| | - Hemalkumar Mehta
- Division of Epidemiology and Methodology, Johns Hopkins School of Public Health, Baltimore, Maryland, United States of America
| | - Caleb Alexander
- Division of General Internal Medicine, Department of Medicine, Johns Hopkins School of Medicine, Baltimore, Maryland, United States of America
| | - Jena Tronieri
- Department of Psychiatry, Perelman School of Medicine at the University of Pennsylvania, Philadelphia, Pennsylvania, United States of America
| | - Stephenie Hong
- Division of Epidemiology and Methodology, Johns Hopkins School of Public Health, Baltimore, Maryland, United States of America
| | - Anna Kahkoska
- Department of Nutrition, Gillings School of Global Public Health, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina, United States of America
| | - Joy Alamgir
- ARIScience, Boston, Massachusetts, United States of America
| | - Farrukh Koraishy
- Division of Nephrology, Stony Brook University Hospital, Stony Brook, New York, United States of America
| | - Katrina Hartman
- Division of General Internal Medicine, Department of Medicine, University of Minnesota Medical School, Minneapolis, Minnesota, United States of America
| | - Kaifeng Yang
- Division of Biostatistics, University of Minnesota School of Public Health, Minneapolis, Minnesota, United States of America
| | | | - Til Stürmer
- Department of Epidemiology, Gillings School of Global Public Health, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina, United States of America
| | - John B. Buse
- Division of Endocrinology, Department of Medicine, University of North Carolina Medical School, Chapel Hill, North Carolina, United States of America
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12
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Wong R, Vaddavalli R, Hall MA, Patel MV, Bramante CT, Casarighi E, Johnson SG, Lingam V, Miller JD, Reusch J, Saltz M, Stürmer T, Tronieri JS, Wilkins KJ, Buse JB, Saltz J, Huling JD, Moffitt R. Effect of SARS-CoV-2 Infection and Infection Severity on Longer-Term Glycemic Control and Weight in People With Type 2 Diabetes. Diabetes Care 2022; 45:2709-2717. [PMID: 36098660 PMCID: PMC9679257 DOI: 10.2337/dc22-0730] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 04/14/2022] [Accepted: 07/16/2022] [Indexed: 02/03/2023]
Abstract
OBJECTIVE To evaluate the association of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection and severity of infection with longer-term glycemic control and weight in people with type 2 diabetes (T2D) in the U.S. RESEARCH DESIGN AND METHODS We conducted a retrospective cohort study using longitudinal electronic health record data of patients with SARS-CoV-2 infection from the National COVID Cohort Collaborative (N3C). Patients were ≥18 years old with an ICD-10 diagnosis of T2D and at least one HbA1c and weight measurement prior to and after an index date of their first coronavirus disease 2019 (COVID-19) diagnosis or negative SARS-CoV-2 test. We used propensity scores to identify a matched cohort balanced on demographic characteristics, comorbidities, and medications used to treat diabetes. The primary outcome was the postindex average HbA1c and postindex average weight over a 1 year time period beginning 90 days after the index date among patients who did and did not have SARS-CoV-2 infection. Secondary outcomes were postindex average HbA1c and weight in patients who required hospitalization or mechanical ventilation. RESULTS There was no significant difference in the postindex average HbA1c or weight in patients who had SARS-CoV-2 infection compared with control subjects. Mechanical ventilation was associated with a decrease in average HbA1c after COVID-19. CONCLUSIONS In a multicenter cohort of patients in the U.S. with preexisting T2D, there was no significant change in longer-term average HbA1c or weight among patients who had COVID-19. Mechanical ventilation was associated with a decrease in HbA1c after COVID-19.
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Affiliation(s)
- Rachel Wong
- Department of Biomedical Informatics, Stony Brook University, Stony Brook, NY
| | - Rohith Vaddavalli
- Department of Computer Science, Stony Brook University, Stony Brook, NY
| | - Margaret A. Hall
- Department of Biomedical Informatics, Stony Brook University, Stony Brook, NY
| | - Monil V. Patel
- Department of Medicine, Renaissance School of Medicine at Stony Brook University, Stony Brook, NY
| | - Carolyn T. Bramante
- Division of General Internal Medicine, University of Minnesota Medical School, Minneapolis, MN
| | - Elena Casarighi
- AnacletoLab, Department of Computer Science “Giovanni degli Antoni,” Università degli Studi di Milano, Milan, Italy
- CINI, Infolife National Laboratory, Roma, Italy
| | - Steven G. Johnson
- Institute for Health Informatics, University of Minnesota, Minneapolis, MN
| | - Veena Lingam
- Department of Biomedical Informatics, Stony Brook University, Stony Brook, NY
| | - Joshua D. Miller
- Division of Endocrinology and Metabolism, Department of Medicine, Renaissance School of Medicine at Stony Brook University, Stony Brook, NY
| | - Jane Reusch
- Division of Endocrinology, Metabolism & Diabetes, University of Colorado Anschutz Medical Campus, Aurora, CO
| | - Mary Saltz
- Department of Biomedical Informatics, Stony Brook University, Stony Brook, NY
| | - Til Stürmer
- Department of Epidemiology, University of North Carolina at Chapel Hill Gillings School of Global Public Health, Chapel Hill, NC
| | - Jena S. Tronieri
- Department of Psychiatry, Perelman School of Medicine at the University of Pennsylvania, Philadelphia, PA
| | - Kenneth J. Wilkins
- Office of the Director, Biostatistics Program/Office of Clinical Research Support, National Institute of Diabetes and Digestive and Kidney Diseases, National Institutes of Health, Bethesda, MD
| | - John B. Buse
- Division of Endocrinology and Metabolism, Department of Medicine, University of North Carolina School of Medicine, Chapel Hill, NC
- North Carolina Translational and Clinical Sciences Institute, University of North Carolina School of Medicine, Chapel Hill, NC
| | - Joel Saltz
- Department of Biomedical Informatics, Stony Brook University, Stony Brook, NY
| | - Jared D. Huling
- Division of Biostatistics, School of Public Health, University of Minnesota, Minneapolis, MN
| | - Richard Moffitt
- Department of Biomedical Informatics, Stony Brook University, Stony Brook, NY
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13
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Lin Z, Pestourie R, Roques-Carmes C, Li Z, Capasso F, Soljačić M, Johnson SG. End-to-end metasurface inverse design for single-shot multi-channel imaging. Opt Express 2022; 30:28358-28370. [PMID: 36299033 DOI: 10.1364/oe.449985] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Received: 12/02/2021] [Accepted: 03/20/2022] [Indexed: 06/16/2023]
Abstract
We introduce end-to-end inverse design for multi-channel imaging, in which a nanophotonic frontend is optimized in conjunction with an image-processing backend to extract depth, spectral and polarization channels from a single monochrome image. Unlike diffractive optics, we show that subwavelength-scale "metasurface" designs can easily distinguish similar wavelength and polarization inputs. The proposed technique integrates a single-layer metasurface frontend with an efficient Tikhonov reconstruction backend, without any additional optics except a grayscale sensor. Our method yields multi-channel imaging by spontaneous demultiplexing: the metaoptics front-end separates different channels into distinct spatial domains whose locations on the sensor are optimally discovered by the inverse-design algorithm. We present large-area metasurface designs, compatible with standard lithography, for multi-spectral imaging, depth-spectral imaging, and "all-in-one" spectro-polarimetric-depth imaging with robust reconstruction performance (≲ 10% error with 1% detector noise). In contrast to neural networks, our framework is physically interpretable and does not require large training sets. It can be used to reconstruct arbitrary three-dimensional scenes with full multi-wavelength spectra and polarization textures.
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14
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Li Z, Pestourie R, Park JS, Huang YW, Johnson SG, Capasso F. Inverse design enables large-scale high-performance meta-optics reshaping virtual reality. Nat Commun 2022; 13:2409. [PMID: 35504864 PMCID: PMC9064995 DOI: 10.1038/s41467-022-29973-3] [Citation(s) in RCA: 11] [Impact Index Per Article: 5.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/23/2021] [Accepted: 04/11/2022] [Indexed: 12/30/2022] Open
Abstract
Meta-optics has achieved major breakthroughs in the past decade; however, conventional forward design faces challenges as functionality complexity and device size scale up. Inverse design aims at optimizing meta-optics design but has been currently limited by expensive brute-force numerical solvers to small devices, which are also difficult to realize experimentally. Here, we present a general inverse-design framework for aperiodic large-scale (20k × 20k λ2) complex meta-optics in three dimensions, which alleviates computational cost for both simulation and optimization via a fast approximate solver and an adjoint method, respectively. Our framework naturally accounts for fabrication constraints via a surrogate model. In experiments, we demonstrate aberration-corrected metalenses working in the visible with high numerical aperture, poly-chromatic focusing, and large diameter up to the centimeter scale. Such large-scale meta-optics opens a new paradigm for applications, and we demonstrate its potential for future virtual-reality platforms by using a meta-eyepiece and a laser back-illuminated micro-Liquid Crystal Display.
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Affiliation(s)
- Zhaoyi Li
- Harvard John A. Paulson School of Engineering and Applied Sciences, Harvard University, Cambridge, MA, USA.
| | - Raphaël Pestourie
- Department of Mathematics, Massachusetts Institute of Technology, Cambridge, MA, USA
| | - Joon-Suh Park
- Harvard John A. Paulson School of Engineering and Applied Sciences, Harvard University, Cambridge, MA, USA
- Nanophotonics Research Center, Korea Institute of Science and Technology, Seoul, Republic of Korea
| | - Yao-Wei Huang
- Harvard John A. Paulson School of Engineering and Applied Sciences, Harvard University, Cambridge, MA, USA
- Department of Electrical and Computer Engineering, National University of Singapore, Singapore, Singapore
- Department of Photonics, National Yang Ming Chiao Tung University, Hsinchu, Taiwan
| | - Steven G Johnson
- Department of Mathematics, Massachusetts Institute of Technology, Cambridge, MA, USA.
| | - Federico Capasso
- Harvard John A. Paulson School of Engineering and Applied Sciences, Harvard University, Cambridge, MA, USA.
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15
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Bradwell KR, Wooldridge JT, Amor B, Bennett TD, Anand A, Bremer C, Yoo YJ, Qian Z, Johnson SG, Pfaff ER, Girvin AT, Manna A, Niehaus EA, Hong SS, Zhang XT, Zhu RL, Bissell M, Qureshi N, Saltz J, Haendel MA, Chute CG, Lehmann HP, Moffitt RA. Harmonizing units and values of quantitative data elements in a very large nationally pooled electronic health record (EHR) dataset. J Am Med Inform Assoc 2022; 29:1172-1182. [PMID: 35435957 PMCID: PMC9196692 DOI: 10.1093/jamia/ocac054] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/21/2021] [Revised: 03/25/2022] [Accepted: 04/08/2022] [Indexed: 11/24/2022] Open
Abstract
Objective The goals of this study were to harmonize data from electronic health records (EHRs) into common units, and impute units that were missing. Materials and Methods The National COVID Cohort Collaborative (N3C) table of laboratory measurement data—over 3.1 billion patient records and over 19 000 unique measurement concepts in the Observational Medical Outcomes Partnership (OMOP) common-data-model format from 55 data partners. We grouped ontologically similar OMOP concepts together for 52 variables relevant to COVID-19 research, and developed a unit-harmonization pipeline comprised of (1) selecting a canonical unit for each measurement variable, (2) arriving at a formula for conversion, (3) obtaining clinical review of each formula, (4) applying the formula to convert data values in each unit into the target canonical unit, and (5) removing any harmonized value that fell outside of accepted value ranges for the variable. For data with missing units for all the results within a lab test for a data partner, we compared values with pooled values of all data partners, using the Kolmogorov-Smirnov test. Results Of the concepts without missing values, we harmonized 88.1% of the values, and imputed units for 78.2% of records where units were absent (41% of contributors’ records lacked units). Discussion The harmonization and inference methods developed herein can serve as a resource for initiatives aiming to extract insight from heterogeneous EHR collections. Unique properties of centralized data are harnessed to enable unit inference. Conclusion The pipeline we developed for the pooled N3C data enables use of measurements that would otherwise be unavailable for analysis.
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Affiliation(s)
| | - Jacob T Wooldridge
- Department of Biomedical Informatics, Stony Brook University, Stony Brook, New York, USA
| | | | - Tellen D Bennett
- Section of Informatics and Data Science, Department of Pediatrics, University of Colorado School of Medicine, University of Colorado, Aurora, Colorado, USA
| | - Adit Anand
- Department of Biomedical Informatics, Stony Brook University, Stony Brook, New York, USA
| | - Carolyn Bremer
- Department of Biomedical Informatics, Stony Brook University, Stony Brook, New York, USA
| | - Yun Jae Yoo
- Department of Biomedical Informatics, Stony Brook University, Stony Brook, New York, USA
| | - Zhenglong Qian
- Department of Biomedical Informatics, Stony Brook University, Stony Brook, New York, USA
| | - Steven G Johnson
- Institute for Health Informatics, University of Minnesota, Minneapolis, Minnesota, USA
| | - Emily R Pfaff
- Department of Medicine, North Carolina Translational and Clinical Sciences Institute, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina, USA
| | | | - Amin Manna
- Palantir Technologies, Denver, Colorado, USA
| | | | - Stephanie S Hong
- School of Medicine, Section of Biomedical Informatics and Data Science, Johns Hopkins University School of Medicine, Baltimore, Maryland, USA
| | | | - Richard L Zhu
- Department of Medicine, Johns Hopkins, Baltimore, Maryland, USA
| | | | | | - Joel Saltz
- Department of Biomedical Informatics, Stony Brook University, Stony Brook, New York, USA
| | | | - Christopher G Chute
- Schools of Medicine, Public Health, and Nursing, Johns Hopkins University, Baltimore, Maryland, USA
| | | | - Richard A Moffitt
- Department of Biomedical Informatics, Stony Brook University, Stony Brook, New York, USA
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16
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Pfaff ER, Girvin AT, Gabriel DL, Kostka K, Morris M, Palchuk MB, Lehmann HP, Amor B, Bissell M, Bradwell KR, Gold S, Hong SS, Loomba J, Manna A, McMurry JA, Niehaus E, Qureshi N, Walden A, Zhang XT, Zhu RL, Moffitt RA, Haendel MA, Chute CG, Adams WG, Al-Shukri S, Anzalone A, Baghal A, Bennett TD, Bernstam EV, Bernstam EV, Bissell MM, Bush B, Campion TR, Castro V, Chang J, Chaudhari DD, Chen W, Chu S, Cimino JJ, Crandall KA, Crooks M, Davies SJD, DiPalazzo J, Dorr D, Eckrich D, Eltinge SE, Fort DG, Golovko G, Gupta S, Haendel MA, Hajagos JG, Hanauer DA, Harnett BM, Horswell R, Huang N, Johnson SG, Kahn M, Khanipov K, Kieler C, Luzuriaga KRD, Maidlow S, Martinez A, Mathew J, McClay JC, McMahan G, Melancon B, Meystre S, Miele L, Morizono H, Pablo R, Patel L, Phuong J, Popham DJ, Pulgarin C, Santos C, Sarkar IN, Sazo N, Setoguchi S, Soby S, Surampalli S, Suver C, Vangala UMR, Visweswaran S, von Oehsen J, Walters KM, Wiley L, Williams DA, Zai A. Synergies between centralized and federated approaches to data quality: a report from the national COVID cohort collaborative. J Am Med Inform Assoc 2022; 29:609-618. [PMID: 34590684 PMCID: PMC8500110 DOI: 10.1093/jamia/ocab217] [Citation(s) in RCA: 29] [Impact Index Per Article: 14.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/15/2021] [Revised: 08/19/2021] [Accepted: 09/23/2021] [Indexed: 02/01/2023] Open
Abstract
OBJECTIVE In response to COVID-19, the informatics community united to aggregate as much clinical data as possible to characterize this new disease and reduce its impact through collaborative analytics. The National COVID Cohort Collaborative (N3C) is now the largest publicly available HIPAA limited dataset in US history with over 6.4 million patients and is a testament to a partnership of over 100 organizations. MATERIALS AND METHODS We developed a pipeline for ingesting, harmonizing, and centralizing data from 56 contributing data partners using 4 federated Common Data Models. N3C data quality (DQ) review involves both automated and manual procedures. In the process, several DQ heuristics were discovered in our centralized context, both within the pipeline and during downstream project-based analysis. Feedback to the sites led to many local and centralized DQ improvements. RESULTS Beyond well-recognized DQ findings, we discovered 15 heuristics relating to source Common Data Model conformance, demographics, COVID tests, conditions, encounters, measurements, observations, coding completeness, and fitness for use. Of 56 sites, 37 sites (66%) demonstrated issues through these heuristics. These 37 sites demonstrated improvement after receiving feedback. DISCUSSION We encountered site-to-site differences in DQ which would have been challenging to discover using federated checks alone. We have demonstrated that centralized DQ benchmarking reveals unique opportunities for DQ improvement that will support improved research analytics locally and in aggregate. CONCLUSION By combining rapid, continual assessment of DQ with a large volume of multisite data, it is possible to support more nuanced scientific questions with the scale and rigor that they require.
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Affiliation(s)
- Emily R Pfaff
- Department of Medicine, UNC Chapel Hill School of Medicine, Chapel Hill, North Carolina, USA
| | | | - Davera L Gabriel
- Section of Biomedical Informatics and Data Science, Johns Hopkins University School of Medicine, Baltimore, Maryland, USA
| | - Kristin Kostka
- The OHDSI Center at the Roux Institute, Northeastern University, Portland, Maine, USA
| | - Michele Morris
- Department of Biomedical Informatics, University of Pittsburgh, Pittsburgh, Pennsylvania, USA
| | | | - Harold P Lehmann
- Department of Medicine, Johns Hopkins School of Medicine, Baltimore, Maryland, USA
| | | | | | | | - Sigfried Gold
- Section of Biomedical Informatics and Data Science, Johns Hopkins University School of Medicine, Baltimore, Maryland, USA
| | - Stephanie S Hong
- Section of Biomedical Informatics and Data Science, Johns Hopkins University School of Medicine, Baltimore, Maryland, USA
| | | | - Amin Manna
- Palantir Technologies, Denver, Colorado, USA
| | - Julie A McMurry
- Center for Health AI, University of Colorado Anschutz Medical Campus, Aurora, Colorado, USA
| | | | | | - Anita Walden
- Department of Medical Informatics and Clinical Epidemiology, Oregon Health & Science University, Portland, Oregon, USA
| | | | - Richard L Zhu
- Johns Hopkins University School of Medicine, Baltimore, Maryland, USA
| | - Richard A Moffitt
- Department of Biomedical Informatics, Stony Brook University, Stony Brook, New York, USA
| | - Melissa A Haendel
- University of Colorado Anschutz Medical Campus, Aurora, Colorado, USA
| | - Christopher G Chute
- Schools of Medicine, Public Health, and Nursing, Johns Hopkins University, Baltimore, Maryland, USA
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17
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Winkelman TNA, Margolis KL, Waring S, Bodurtha PJ, Khazanchi R, Gildemeister S, Mink PJ, DeSilva M, Murray AM, Rai N, Sonier J, Neely C, Johnson SG, Chamberlain AM, Yu Y, McFarling LM, Dudley RA, Drawz PE. Minnesota Electronic Health Record Consortium COVID-19 Project: Informing Pandemic Response Through Statewide Collaboration Using Observational Data. Public Health Rep 2022; 137:263-271. [PMID: 35060411 PMCID: PMC8900228 DOI: 10.1177/00333549211061317] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/26/2023] Open
Abstract
OBJECTIVE Robust disease and syndromic surveillance tools are underdeveloped in the United States, as evidenced by limitations and heterogeneity in sociodemographic data collection throughout the COVID-19 pandemic. To monitor the COVID-19 pandemic in Minnesota, we developed a federated data network in March 2020 using electronic health record (EHR) data from 8 multispecialty health systems. MATERIALS AND METHODS In this serial cross-sectional study, we examined patients of all ages who received a COVID-19 polymerase chain reaction test, had symptoms of a viral illness, or received an influenza test from January 3, 2016, through November 7, 2020. We evaluated COVID-19 testing rates among patients with symptoms of viral illness and percentage positivity among all patients tested, in aggregate and by zip code. We stratified results by patient and area-level characteristics. RESULTS Cumulative COVID-19 positivity rates were similar for people aged 12-64 years (range, 15.1%-17.6%) but lower for adults aged ≥65 years (range, 9.3%-10.7%). We found notable racial and ethnic disparities in positivity rates early in the pandemic, whereas COVID-19 positivity was similarly elevated across most racial and ethnic groups by the end of 2020. Positivity rates remained substantially higher among Hispanic patients compared with other racial and ethnic groups throughout the study period. We found similar trends across area-level income and rurality, with disparities early in the pandemic converging over time. PRACTICE IMPLICATIONS We rapidly developed a distributed data network across Minnesota to monitor the COVID-19 pandemic. Our findings highlight the utility of using EHR data to monitor the current pandemic as well as future public health priorities. Building partnerships with public health agencies can help ensure data streams are flexible and tailored to meet the changing needs of decision makers.
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Affiliation(s)
- Tyler N. A. Winkelman
- Division of General Internal Medicine, Department of Medicine, Hennepin Healthcare, Minneapolis, MN, USA
- Health, Homelessness, and Criminal Justice Lab, Hennepin Healthcare Research Institute, Minneapolis, MN, USA
| | | | - Stephen Waring
- Essentia Health, Essentia Institute of Health, Duluth, MN, USA
| | - Peter J. Bodurtha
- Health, Homelessness, and Criminal Justice Lab, Hennepin Healthcare Research Institute, Minneapolis, MN, USA
| | - Rohan Khazanchi
- Health, Homelessness, and Criminal Justice Lab, Hennepin Healthcare Research Institute, Minneapolis, MN, USA
- School of Public Health, University of Minnesota, Minneapolis, MN, USA
- College of Medicine, University of Nebraska Medical Center, Omaha, NE, USA
| | | | | | | | - Anne M. Murray
- Division of Geriatrics, Department of Internal Medicine, Hennepin Healthcare, Minneapolis, MN, USA
- Berman Center for Outcomes and Clinical Research, Hennepin Healthcare Research Institute, Minneapolis, MN, USA
| | - Nayanjot Rai
- Division of Nephrology and Hypertension, University of Minnesota Medical School, Minneapolis, MN, USA
| | | | - Claire Neely
- Institute for Clinical Systems Improvement, Minneapolis, MN, USA
| | - Steven G. Johnson
- Institute for Health Informatics, University of Minnesota, Minneapolis, MN, USA
| | | | - Yue Yu
- Department of Quantitative Health Sciences, Mayo Clinic, Rochester, MN, USA
| | | | - R. Adams Dudley
- Institute for Health Informatics, University of Minnesota, Minneapolis, MN, USA
- Department of Medicine, University of Minnesota Medical School, Minneapolis, MN, USA
- Minneapolis Veterans Affairs Medical Center, Minneapolis, MN, USA
| | - Paul E. Drawz
- Division of Nephrology and Hypertension, University of Minnesota Medical School, Minneapolis, MN, USA
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18
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Winkelman TNA, Rai NK, Bodurtha PJ, Chamberlain AM, DeSilva M, Jeruzal J, Johnson SG, Kharbanda A, Klyn N, Mink PJ, Muscoplat M, Waring S, Yu Y, Drawz PE. Trends in COVID-19 Vaccine Administration and Effectiveness Through October 2021. JAMA Netw Open 2022; 5:e225018. [PMID: 35357452 PMCID: PMC8972031 DOI: 10.1001/jamanetworkopen.2022.5018] [Citation(s) in RCA: 7] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Track Full Text] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 11/16/2022] Open
Abstract
IMPORTANCE COVID-19 vaccines are effective, but inequities in vaccine administration and waning immunity may limit vaccine effectiveness. OBJECTIVES To report statewide trends in vaccine administration and vaccine effectiveness in Minnesota. DESIGN, SETTING, AND PARTICIPANTS This cohort study used COVID-19 vaccine data from the Minnesota Immunization Information Connection from October 25, 2020, through October 30, 2021 that were linked with electronic health record (EHR) data from health systems collaborating as part of the Minnesota EHR Consortium (MNEHRC). Participants included individuals who were seen at a participating health system in Minnesota. EXPOSURES Individuals were considered fully vaccinated in the second week after receipt of a second dose of a BNT162b2 or mRNA-1273 vaccine or a single dose of an Ad26.COV.2.S vaccine. MAIN OUTCOMES AND MEASURES A completed vaccination series and vaccine breakthrough, defined as either a positive SARS-CoV-2 polymerase chain reaction (PCR) test or a hospital admission the same week or within the 3 weeks following a positive SARS-CoV-2 PCR test. A test-negative design and incident rate ratio were used to evaluate COVID-19 vaccine effectiveness separately for the BNT162b2, mRNA-1273, and Ad26.COV.2.S vaccines. Rurality and social vulnerability index were assessed at the area level. RESULTS This study included 4 431 190 unique individuals at participating health systems, and 3 013 704 (68%) of the individuals were fully vaccinated. Vaccination rates were lowest among Minnesotans who identified as Hispanic (116 422 of 217 019 [54%]), multiracial (30 066 of 57 412 [52%]), American Indian or Alaska Native (22 190 of 41 437 [54%]), and Black or African American (158 860 of 326 595 [49%]) compared with Minnesotans who identified as Asian or Pacific Islander (159 999 of 210 994 [76%]) or White (2 402 928 of 3 391 747 [71%]). Among individuals aged 19 to 64 years, vaccination rates were lower in rural areas (196 479 of 308 047 [64%]) compared with urban areas (151 541 of 1 951 265 [77%]) and areas with high social vulnerability (544 433 of 774 952 [70%]) compared with areas with low social vulnerability (571 613 of 724 369 [79%]). In the 9 weeks ending October 30, 2021, vaccine effectiveness as assessed by a test-negative design was 33% (95% CI, 30%-37%) for Ad26.COV.2.S; 53% (95% CI, 52%-54%) for BNT162b2; and 66% (95% CI, 65%-67%) for mRNA-1273. For SARS-CoV-2-related hospitalizations, vaccine effectiveness in the 9 weeks ending October 30, 2021, was 78% (95% CI, 75%-81%) for Ad26.COV.2.S; 81% (95% CI, 79%-82%) for BNT162b2; and 81% (95% CI, 79%-82%) for mRNA-1273. CONCLUSIONS AND RELEVANCE This cohort study of data from a Minnesota statewide consortium suggests disparities in vaccine administration and effectiveness. Vaccine effectiveness against infection was lower for Ad26.COV.2.S and BNT162b2 but was associated with protection against SARS-CoV-2-related hospitalizations despite the increased prevalence of the Delta variant in Minnesota.
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Affiliation(s)
- Tyler N A Winkelman
- Division of General Internal Medicine, Department of Medicine, Hennepin Healthcare, Minneapolis, Minnesota
- Health, Homelessness, and Criminal Justice Lab, Hennepin Healthcare Research Institute, Minneapolis, Minnesota
| | - Nayanjot K Rai
- Division of Nephrology and Hypertension, University of Minnesota Medical School, Minneapolis
| | - Peter J Bodurtha
- Health, Homelessness, and Criminal Justice Lab, Hennepin Healthcare Research Institute, Minneapolis, Minnesota
| | | | | | - Jessica Jeruzal
- Health, Homelessness, and Criminal Justice Lab, Hennepin Healthcare Research Institute, Minneapolis, Minnesota
| | - Steven G Johnson
- Institute for Health Informatics, University of Minnesota, Minneapolis
| | - Anupam Kharbanda
- Department of Pediatric Emergency Medicine, Children's Minnesota, Minneapolis
| | - Niall Klyn
- Department of Information Services, Essentia Health, Duluth, Minnesota
- School of Communication, Northwestern University, Evanston, Illinois
| | - Pamela J Mink
- Health Economics Program, Health Policy Division, Minnesota Department of Health, Saint Paul
| | - Miriam Muscoplat
- Division of Infectious Disease, Epidemiology, Prevention, and Control, Minnesota Department of Health, Saint Paul
| | | | - Yue Yu
- Department of Quantitative Health Sciences, Mayo Clinic, Rochester, Minnesota
| | - Paul E Drawz
- Division of Nephrology and Hypertension, University of Minnesota Medical School, Minneapolis
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19
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Roques-Carmes C, Rivera N, Ghorashi A, Kooi SE, Yang Y, Lin Z, Beroz J, Massuda A, Sloan J, Romeo N, Yu Y, Joannopoulos JD, Kaminer I, Johnson SG, Soljačić M. A framework for scintillation in nanophotonics. Science 2022; 375:eabm9293. [DOI: 10.1126/science.abm9293] [Citation(s) in RCA: 6] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/15/2023]
Abstract
Bombardment of materials by high-energy particles often leads to light emission in a process known as scintillation. Scintillation has widespread applications in medical imaging, x-ray nondestructive inspection, electron microscopy, and high-energy particle detectors. Most research focuses on finding materials with brighter, faster, and more controlled scintillation. We developed a unified theory of nanophotonic scintillators that accounts for the key aspects of scintillation: energy loss by high-energy particles, and light emission by non-equilibrium electrons in nanostructured optical systems. We then devised an approach based on integrating nanophotonic structures into scintillators to enhance their emission, obtaining nearly an order-of-magnitude enhancement in both electron-induced and x-ray–induced scintillation. Our framework should enable the development of a new class of brighter, faster, and higher-resolution scintillators with tailored and optimized performance.
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Affiliation(s)
- Charles Roques-Carmes
- Research Laboratory of Electronics, Massachusetts Institute of Technology, Cambridge, MA 02139, USA
| | - Nicholas Rivera
- Department of Physics, Massachusetts Institute of Technology, Cambridge, MA 02139, USA
| | - Ali Ghorashi
- Department of Physics, Massachusetts Institute of Technology, Cambridge, MA 02139, USA
| | - Steven E. Kooi
- Institute for Soldier Nanotechnologies, Massachusetts Institute of Technology, Cambridge, MA 02139, USA
| | - Yi Yang
- Research Laboratory of Electronics, Massachusetts Institute of Technology, Cambridge, MA 02139, USA
- Department of Physics, Massachusetts Institute of Technology, Cambridge, MA 02139, USA
- Department of Physics, University of Hong Kong, Hong Kong, China
| | - Zin Lin
- Department of Mathematics, Massachusetts Institute of Technology, Cambridge, MA 02139, USA
| | - Justin Beroz
- Department of Physics, Massachusetts Institute of Technology, Cambridge, MA 02139, USA
| | - Aviram Massuda
- Microsystems Technology Laboratories, Massachusetts Institute of Technology, Cambridge, MA 02139, USA
| | - Jamison Sloan
- Research Laboratory of Electronics, Massachusetts Institute of Technology, Cambridge, MA 02139, USA
| | - Nicolas Romeo
- Department of Physics, Massachusetts Institute of Technology, Cambridge, MA 02139, USA
| | - Yang Yu
- Raith America Inc., Troy, NY 12180, USA
| | - John D. Joannopoulos
- Department of Physics, Massachusetts Institute of Technology, Cambridge, MA 02139, USA
- Institute for Soldier Nanotechnologies, Massachusetts Institute of Technology, Cambridge, MA 02139, USA
| | - Ido Kaminer
- Department of Electrical and Computer Engineering, Technion, Haifa 32000, Israel
| | - Steven G. Johnson
- Department of Physics, Massachusetts Institute of Technology, Cambridge, MA 02139, USA
- Department of Physics, University of Hong Kong, Hong Kong, China
| | - Marin Soljačić
- Research Laboratory of Electronics, Massachusetts Institute of Technology, Cambridge, MA 02139, USA
- Department of Physics, Massachusetts Institute of Technology, Cambridge, MA 02139, USA
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20
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Drawz PE, DeSilva M, Bodurtha P, Benitez GV, Murray A, Chamberlain AM, Dudley RA, Waring S, Kharbanda AB, Murphy D, Muscoplat MH, Melendez V, Margolis KL, McFarling L, Lupu R, Winkelman TNA, Johnson SG. Effectiveness of BNT162b2 and mRNA-1273 Second Doses and Boosters for SARS-CoV-2 infection and SARS-CoV-2 Related Hospitalizations: A Statewide Report from the Minnesota Electronic Health Record Consortium. Clin Infect Dis 2022; 75:890-892. [PMID: 35137021 PMCID: PMC8903410 DOI: 10.1093/cid/ciac110] [Citation(s) in RCA: 8] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/15/2021] [Indexed: 12/16/2022] Open
Abstract
Using vaccine data combined with electronic health records, we report that mRNA boosters provide greater protection than a two-dose regimen against SARS-CoV-2 infection and related hospitalizations. The benefit of a booster was more evident in the elderly and those with comorbidities. These results support the case for COVID-19 boosters.
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Affiliation(s)
- Paul E Drawz
- Division of Nephrology and Hypertension, University of Minnesota Medical School, Minneapolis, MN USA
| | | | - Peter Bodurtha
- Health, Homelessness, and Criminal Justice Lab, Hennepin Healthcare Research Institute, Minneapolis, MN USA
| | | | - Anne Murray
- Berman Center for Clinical Research, Hennepin Healthcare Research Institute USA
| | | | - R Adams Dudley
- Center for Care Delivery and Outcomes Research, Minneapolis Veterans Affairs Medical Center, Minneapolis, MN USA
| | | | - Anupam B Kharbanda
- Department of Pediatric Emergency Medicine, Children's Minnesota, Minneapolis, MN USA
| | - Daniel Murphy
- Division of Nephrology and Hypertension, University of Minnesota Medical School, Minneapolis, MN USA
| | - Miriam Halstead Muscoplat
- Division of Infectious Disease, Epidemiology and Infection Control, Minnesota Department of Health, Saint Paul, MN USA
| | | | | | | | | | - Tyler N A Winkelman
- Health, Homelessness, and Criminal Justice Lab, Hennepin Healthcare Research Institute, Minneapolis, MN USA
| | - Steven G Johnson
- Institute for Health Informatics, University of Minnesota, Minneapolis, MN USA
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21
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Hammond AM, Oskooi A, Chen M, Lin Z, Johnson SG, Ralph SE. High-performance hybrid time/frequency-domain topology optimization for large-scale photonics inverse design. Opt Express 2022; 30:4467-4491. [PMID: 35209683 DOI: 10.1364/oe.442074] [Citation(s) in RCA: 8] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Received: 08/31/2021] [Accepted: 01/10/2022] [Indexed: 06/14/2023]
Abstract
We present a photonics topology optimization (TO) package capable of addressing a wide range of practical photonics design problems, incorporating robustness and manufacturing constraints, which can scale to large devices and massive parallelism. We employ a hybrid algorithm that builds on a mature time-domain (FDTD) package Meep to simultaneously solve multiple frequency-domain TO problems over a broad bandwidth. This time/frequency-domain approach is enhanced by new filter-design sources for the gradient calculation and new material-interpolation methods for optimizing dispersive media, as well as by multiple forms of computational parallelism. The package is available as free/open-source software with extensive tutorials and multi-platform support.
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22
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Mroz P, Michel S, Allen JD, Meyer T, McGonagle EJ, Carpentier R, Vecchia A, Schlichte A, Bishop JR, Dunnenberger HM, Yohe S, Thyagarajan B, Jacobson PA, Johnson SG. Development and Implementation of In-House Pharmacogenomic Testing Program at a Major Academic Health System. Front Genet 2021; 12:712602. [PMID: 34745204 PMCID: PMC8564018 DOI: 10.3389/fgene.2021.712602] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/20/2021] [Accepted: 09/16/2021] [Indexed: 12/26/2022] Open
Abstract
Pharmacogenomics (PGx) studies how a person's genes affect the response to medications and is quickly becoming a significant part of precision medicine. The clinical application of PGx principles has consistently been cited as a major opportunity for improving therapeutic outcomes. Several recent studies have demonstrated that most individuals (> 90%) harbor PGx variants that would be clinically actionable if prescribed a medication relevant to that gene. In multiple well-conducted studies, the results of PGx testing have been shown to guide therapy choice and dosing modifications which improve treatment efficacy and reduce the incidence of adverse drug reactions (ADRs). Although the value of PGx testing is evident, its successful implementation in a clinical setting presents a number of challenges to molecular diagnostic laboratories, healthcare systems, providers and patients. Different molecular methods can be applied to identify PGx variants and the design of the assay is therefore extremely important. Once the genotyping results are available the biggest technical challenge lies in turning this complex genetic information into phenotypes and actionable recommendations that a busy clinician can effectively utilize to provide better medical care, in a cost-effective, efficient and reliable manner. In this paper we describe a successful and highly collaborative implementation of the PGx testing program at the University of Minnesota and MHealth Fairview Molecular Diagnostic Laboratory and selected Pharmacies and Clinics. We offer detailed descriptions of the necessary components of the pharmacogenomic testing implementation, the development and technical validation of the in-house SNP based multiplex PCR based assay targeting 20 genes and 48 SNPs as well as a separate CYP2D6 copy number assay along with the process of PGx report design, results of the provider and pharmacists usability studies, and the development of the software tool for genotype-phenotype translation and gene-phenotype-drug CPIC-based recommendations. Finally, we outline the process of developing the clinical workflow that connects the providers with the PGx experts within the Molecular Diagnostic Laboratory and the Pharmacy.
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Affiliation(s)
- Pawel Mroz
- Department of Laboratory Medicine and Pathology, University of Minnesota Medical School, Minneapolis, MN, United States
| | - Stephen Michel
- Department of Laboratory Medicine and Pathology, University of Minnesota Medical School, Minneapolis, MN, United States
| | - Josiah D Allen
- Department of Experimental and Clinical Pharmacology, University of Minnesota College of Pharmacy, Minneapolis, MN, United States
| | - Tim Meyer
- Institute for Health Informatics, University of Minnesota, Minneapolis, MN, United States
| | - Erin J McGonagle
- Department of Experimental and Clinical Pharmacology, University of Minnesota College of Pharmacy, Minneapolis, MN, United States
| | | | | | | | - Jeffrey R Bishop
- Department of Experimental and Clinical Pharmacology, University of Minnesota College of Pharmacy, Minneapolis, MN, United States.,Department of Psychiatry, University of Minnesota Medical School, Minneapolis, MN, United States
| | - Henry M Dunnenberger
- Mark R Neaman Center for Personalized Medicine Center, NorthShore University HealthSystem, Evanston, IL, United States
| | - Sophia Yohe
- Department of Laboratory Medicine and Pathology, University of Minnesota Medical School, Minneapolis, MN, United States
| | - Bharat Thyagarajan
- Department of Laboratory Medicine and Pathology, University of Minnesota Medical School, Minneapolis, MN, United States
| | - Pamala A Jacobson
- Department of Experimental and Clinical Pharmacology, University of Minnesota College of Pharmacy, Minneapolis, MN, United States
| | - Steven G Johnson
- Institute for Health Informatics, University of Minnesota, Minneapolis, MN, United States
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23
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Bonsaksen T, Magne TA, Stigen L, Gramstad A, Åsli L, Mørk G, Johnson SG, Carstensen T. Associations between occupational therapy students' academic performance and their study approaches and perceptions of the learning environment. BMC Med Educ 2021; 21:496. [PMID: 34537041 PMCID: PMC8449916 DOI: 10.1186/s12909-021-02940-0] [Citation(s) in RCA: 6] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 12/04/2020] [Accepted: 09/11/2021] [Indexed: 06/13/2023]
Abstract
BACKGROUND Relationships between students' academic performance and their employed study approaches have been studied extensively. However, research using study approaches and learning environment factors as concurrent predictors of academic performance is sparse. There is a need to disentangle the potentially interrelated influences of individual and contextual factors on students' academic performance. OBJECTIVE This study aimed to increase the understanding of the associations between occupational therapy students' academic performance, and their approaches to studying, perceptions of the learning environment, and sociodemographic characteristics. METHOD A cross-sectional study was designed, and 174 first-year students completed the Approaches and Study Skills Inventory for Students and the Course Experience Questionnaire, in addition to background information. Data on grades were collected from the data registries of each education institution, and associations were analyzed by multiple linear regression. RESULTS None of the learning environment scales were associated with grades. Adjusting for all variables, better exam results were associated with being female (β = 0.22, p < 0.01) and having higher scores on strategic approach (β = 0.31, p < 0.001) and lower scores on surface approach (β = -0.20, p < 0.01). CONCLUSION The study suggests that students with a desire for obtaining good grades ought to use strategic study behaviors and avoid using surface approach behaviors. While it is important to ensure good quality of the learning environment for a variety of reasons, the learning environment did not contribute significantly to explain the students' academic performance.
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Affiliation(s)
- T Bonsaksen
- Department of Health and Nursing Sciences, Faculty of Social and Health Sciences, Inland Norway University of Applied Science, Elverum, Norway.
- Faculty of Health Studies, VID Specialized University, Sandnes, Norway.
- Department of Occupational Therapy, Prosthetics and Orthotics, Faculty of Health Sciences, Oslo Metropolitan University, Oslo, Norway.
| | - T A Magne
- Department of Neuromedicine and Movement Science, Faculty of Medicine and Health Science, Norwegian University of Science and Technology, Trondheim, Norway
| | - L Stigen
- Department of Health Sciences, Faculty of Medicine and Health Science, Norwegian University of Science and Technology, Gjøvik, Norway
| | - A Gramstad
- UiT The Arctic University of Norway, Tromsø, Norway
- Centre for care research, Tromsø, Norway
| | - L Åsli
- UiT The Arctic University of Norway, Tromsø, Norway
| | - G Mørk
- Faculty of Health Studies, VID Specialized University, Sandnes, Norway
| | - S G Johnson
- Department of Occupational Therapy, Faculty of health and function, Western Norway University of Applied Sciences, Bergen, Norway
| | - T Carstensen
- Department of Neuromedicine and Movement Science, Faculty of Medicine and Health Science, Norwegian University of Science and Technology, Trondheim, Norway
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24
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Hammond AM, Oskooi A, Johnson SG, Ralph SE. Photonic topology optimization with semiconductor-foundry design-rule constraints. Opt Express 2021; 29:23916-23938. [PMID: 34614647 DOI: 10.1364/oe.431188] [Citation(s) in RCA: 13] [Impact Index Per Article: 4.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Received: 05/13/2021] [Accepted: 06/25/2021] [Indexed: 06/13/2023]
Abstract
We present a unified density-based topology-optimization framework that yields integrated photonic designs optimized for manufacturing constraints including all those of commercial semiconductor foundries. We introduce a new method to impose minimum-area and minimum-enclosed-area constraints, and simultaneously adapt previous techniques for minimum linewidth, linespacing, and curvature, all of which are implemented without any additional re-parameterizations. Furthermore, we show how differentiable morphological transforms can be used to produce devices that are robust to over/under-etching while also satisfying manufacturing constraints. We demonstrate our methodology by designing three broadband silicon-photonics devices for nine different foundry-constraint combinations.
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25
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Bishop JR, Huang RS, Brown JT, Mroz P, Johnson SG, Allen JD, Bielinski SJ, England J, Farley JF, Gregornik D, Giri J, Kroger C, Long SE, Luczak T, McGonagle EJ, Ma S, Matey ET, Mandic PK, Moyer AM, Nicholson WT, Petry N, Pawloski PA, Schlichte A, Schondelmeyer SW, Seifert RD, Speedie MK, Stenehjem D, Straka RJ, Wachtl J, Waring SC, Ness BV, Zierhut HA, Aliferis C, Wolf SM, McCarty CA, Jacobson PA. Pharmacogenomics education, research and clinical implementation in the state of Minnesota. Pharmacogenomics 2021; 22:681-691. [PMID: 34137665 DOI: 10.2217/pgs-2021-0058] [Citation(s) in RCA: 6] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/06/2023] Open
Abstract
Several healthcare organizations across Minnesota have developed formal pharmacogenomic (PGx) clinical programs to increase drug safety and effectiveness. Healthcare professional and student education is strong and there are multiple opportunities in the state for learners to gain workforce skills and develop advanced competency in PGx. Implementation planning is occurring at several organizations and others have incorporated structured utilization of PGx into routine workflows. Laboratory-based and translational PGx research in Minnesota has driven important discoveries in several therapeutic areas. This article reviews the state of PGx activities in Minnesota including educational programs, research, national consortia involvement, technology, clinical implementation and utilization and reimbursement, and outlines the challenges and opportunities in equitable implementation of these advances.
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Affiliation(s)
- Jeffrey R Bishop
- Department of Experimental & Clinical Pharmacology, University of Minnesota College of Pharmacy, Minneapolis, MN 55455, USA.,Department of Psychiatry and Behavioral Sciences, University of Minnesota Medical School, Minneapolis, MN 55455, USA
| | - R Stephanie Huang
- Department of Experimental & Clinical Pharmacology, University of Minnesota College of Pharmacy, Minneapolis, MN 55455, USA
| | - Jacob T Brown
- Department of Pharmacy Practice & Pharmaceutical Sciences, University of Minnesota College of Pharmacy, Duluth, MN 55812, USA
| | - Pawel Mroz
- Department of Laboratory Medicine & Pathology, University of Minnesota Medical School, Minneapolis, MN 55455, USA
| | - Steven G Johnson
- Institute for Health Informatics, University of Minnesota, Minneapolis, MN 55455, USA
| | - Josiah D Allen
- University of Minnesota College of Pharmacy, Minneapolis, MN 55455, USA.,Medigenics Consulting LLC, Minneapolis, MN 55407, USA
| | - Suzette J Bielinski
- Department of Quantitative Health Sciences, Division of Epidemiology, Mayo Clinic, Rochester, MN 55905, USA
| | | | - Joel F Farley
- Department of Pharmaceutical Care & Health Systems, University of Minnesota College of Pharmacy, Minneapolis, MN 55455, USA
| | - David Gregornik
- Pharmacogenomics Program, Children's Minnesota, Minneapolis, MN 55407, USA
| | - Jyothsna Giri
- Mayo Clinic Center for Individualized Medicine, Mayo Clinic College of Medicine & Science, Mayo Clinic, Rochester, MN 55905, USA
| | | | - Susie E Long
- MHealth Fairview. Acute Care Pharmacy Services, Minneapolis, MN 55455, USA
| | - Tiana Luczak
- Department of Pharmacy Practice & Pharmaceutical Sciences, University of Minnesota College of Pharmacy, Duluth, MN 55812, USA.,Essentia Health, Duluth, MN 55805, USA
| | - Erin J McGonagle
- Department of Experimental & Clinical Pharmacology, University of Minnesota College of Pharmacy, Minneapolis, MN 55455, USA
| | - Sisi Ma
- Institute for Health Informatics, University of Minnesota, Minneapolis, MN 55455, USA
| | - Eric T Matey
- Department of Pharmacy, Mayo Clinic College of Medicine & Science, Mayo Clinic, Rochester, MN 55905, USA
| | - Pinar K Mandic
- Department of Finance, University of Minnesota Carlson School of Management, Minneapolis, MN 55455, USA
| | - Ann M Moyer
- Department of Laboratory Medicine & Pathology, Mayo Clinic College of Medicine & Science, Mayo Clinic, Rochester, MN 55905, USA
| | - Wayne T Nicholson
- Department of Anesthesiology & Perioperative Medicine, Mayo Clinic College of Medicine & Science, Mayo Clinic, Rochester, MN 55905, USA
| | - Natasha Petry
- Sanford Health Imagenetics, Sioux Falls, SD 57105, USA.,Department of Pharmacy Practice, North Dakota State University College of Health Professions, Fargo, ND 58108, USA
| | | | | | - Stephen W Schondelmeyer
- Department of Pharmaceutical Care & Health Systems, University of Minnesota College of Pharmacy, Minneapolis, MN 55455, USA
| | - Randall D Seifert
- Department of Pharmacy Practice & Pharmaceutical Sciences, University of Minnesota College of Pharmacy, Duluth, MN 55812, USA
| | - Marilyn K Speedie
- Department of Medicinal Chemistry, University of Minnesota College of Pharmacy, Minneapolis, MN 55455, USA
| | - David Stenehjem
- Department of Pharmacy Practice & Pharmaceutical Sciences, University of Minnesota College of Pharmacy, Duluth, MN 55812, USA
| | - Robert J Straka
- Department of Experimental & Clinical Pharmacology, University of Minnesota College of Pharmacy, Minneapolis, MN 55455, USA
| | - Jason Wachtl
- Geritom Medical, Inc, Bloomington, MN 55438, USA
| | | | - Brian Van Ness
- Department of Genetics, Cell Biology & Development, University of Minnesota Medical School, Minneapolis, MN 55455, USA
| | - Heather A Zierhut
- Department of Genetics, Cell Biology & Development, University of Minnesota Medical School, Minneapolis, MN 55455, USA
| | - Constantin Aliferis
- Institute for Health Informatics, University of Minnesota, Minneapolis, MN 55455, USA
| | - Susan M Wolf
- Law School, Medical School, Consortium on Law & Values in Health, Environment & the Life Sciences, University of Minnesota, Minneapolis, MN 55455, USA
| | - Catherine A McCarty
- Department of Family Medicine & Biobehavioral Health, University of Minnesota Medical School, Duluth, MN 55812, USA
| | - Pamala A Jacobson
- Department of Experimental & Clinical Pharmacology, University of Minnesota College of Pharmacy, Minneapolis, MN 55455, USA
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26
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Lytle KS, Westra BL, Whittenburg L, Adams M, Akre M, Ali S, Furukawa M, Hartleben S, Hook M, Johnson SG, Settergren TT, Thibodeaux M. Information Models Offer Value to Standardize Electronic Health Record Flowsheet Data: A Fall Prevention Exemplar. J Nurs Scholarsh 2021; 53:306-314. [PMID: 33720514 DOI: 10.1111/jnu.12646] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.7] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 01/13/2021] [Indexed: 11/28/2022]
Abstract
PURPOSE The rapid implementation of electronic health records (EHRs) resulted in a lack of data standardization and created considerable difficulty for secondary use of EHR documentation data within and between organizations. While EHRs contain documentation data (input), nurses and healthcare organizations rarely have useable documentation data (output). The purpose of this article is to describe a method of standardizing EHR flowsheet documentation data using information models (IMs) to support exchange, quality improvement, and big data research. As an exemplar, EHR flowsheet metadata (input) from multiple organizations was used to validate a fall prevention IM. DESIGN A consensus-based, qualitative, descriptive approach was used to identify a minimum set of essential fall prevention data concepts documented by staff nurses in acute care. The goal was to increase generalizable and comparable nurse-sensitive data on the prevention of falls across organizations for big data research. METHODS The research team conducted a retrospective, observational study using an iterative, consensus-based approach to map, analyze, and evaluate nursing flowsheet metadata contributed by eight health systems. The team used FloMap software to aggregate flowsheet data across organizations for mapping and comparison of data to a reference IM. The FloMap analysis was refined with input from staff nurse subject matter experts, review of published evidence, current documentation standards, Magnet Recognition nursing standards, and informal fall prevention nursing use cases. FINDINGS Flowsheet metadata analyzed from the EHR systems represented 6.6 million patients, 27 million encounters, and 683 million observations. Compared to the original reference IM, five new IM classes were added, concepts were reduced by 14 (from 57 to 43), and 157 value set items were added. The final fall prevention IM incorporated 11 condition or age-specific fall risk screening tools and a fall event details class with 14 concepts. CONCLUSION The iterative, consensus-based refinement and validation of the fall prevention IM from actual EHR fall prevention flowsheet documentation contributes to the ability to semantically exchange and compare fall prevention data across multiple health systems and organizations. This method and approach provides a process for standardizing flowsheet data as coded data for information exchange and use in big data research. CLINICAL RELEVANCE Opportunities exist to work with EHR vendors and the Office of the National Coordinator for Health Information Technology to implement standardized IMs within EHRs to expand interoperability of nurse-sensitive data.
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Affiliation(s)
- Kay S Lytle
- Alpha Alpha & Beta Nu, Chief Nursing Information Officer, Duke University Health System, Durham, NC, USA
| | - Bonnie L Westra
- Associate Professor Emerita, School of Nursing, University of Minnesota, Minneapolis, MN, USA
| | | | - Mischa Adams
- Clinical Outcomes Improvement Director, Health Catalyst, Minneapolis, MN, USA
| | - Mari Akre
- Sr. Population Health Strategy Executive, Cerner Corporation, Kansas City, MO, USA
| | - Samira Ali
- Adjunct Faculty, School of Nursing, Grand Canyon University, Phoenix, AZ, USA
| | - Meg Furukawa
- Nurse Informaticist, University of California Los Angeles Health, Los Angeles, CA, USA
| | - Stephanie Hartleben
- Kappa Upsilon, Senior Principal Clinical Informatics, Elsevier Clinical Solutions, Bismarck, ND, USA
| | - Mary Hook
- Eta Nu, Nursing Research Manager, AdvocateAuroraHealth, Milwaukee, WI, USA
| | - Steven G Johnson
- Director CTSI Clinical Informatics Services, Institute for Health Informatics, University of Minnesota, Minneapolis, MN, USA
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27
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Christiansen RE, Lin Z, Roques-Carmes C, Salamin Y, Kooi SE, Joannopoulos JD, Soljačić M, Johnson SG. Fullwave Maxwell inverse design of axisymmetric, tunable, and multi-scale multi-wavelength metalenses. Opt Express 2020; 28:33854-33868. [PMID: 33182865 DOI: 10.1364/oe.403192] [Citation(s) in RCA: 12] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 05/06/2023]
Abstract
We demonstrate new axisymmetric inverse-design techniques that can solve problems radically different from traditional lenses, including reconfigurable lenses (that shift a multi-frequency focal spot in response to refractive-index changes) and widely separated multi-wavelength lenses (λ = 1 µm and 10 µm). We also present experimental validation for an axisymmetric inverse-designed monochrome lens in the near-infrared fabricated via two-photon polymerization. Axisymmetry allows fullwave Maxwell solvers to be scaled up to structures hundreds or even thousands of wavelengths in diameter before requiring domain-decomposition approximations, while multilayer topology optimization with ∼105 degrees of freedom can tackle challenging design problems even when restricted to axisymmetric structures.
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28
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Yao W, Benzaouia M, Miller OD, Johnson SG. Approaching the upper limits of the local density of states via optimized metallic cavities. Opt Express 2020; 28:24185-24197. [PMID: 32752402 DOI: 10.1364/oe.397502] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Received: 05/11/2020] [Accepted: 06/18/2020] [Indexed: 06/11/2023]
Abstract
By computational optimization of air-void cavities in metallic substrates, we show that the local density of states (LDOS) can reach within a factor of ≈10 of recent theoretical upper limits and within a factor ≈4 for the single-polarization LDOS, demonstrating that the theoretical limits are nearly attainable. Optimizing the total LDOS results in a spontaneous symmetry breaking where it is preferable to couple to a specific polarization. Moreover, simple shapes such as optimized cylinders attain nearly the performance of complicated many-parameter optima, suggesting that only one or two key parameters matter in order to approach the theoretical LDOS bounds for metallic resonators.
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29
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Michon J, Benzaouia M, Yao W, Miller OD, Johnson SG. Limits to surface-enhanced Raman scattering near arbitrary-shape scatterers: erratum. Opt Express 2020; 28:22264-22265. [PMID: 32752491 DOI: 10.1364/oe.401577] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Received: 07/07/2020] [Indexed: 06/11/2023]
Abstract
In this erratum, we correct two minor algebraic errors from our previous published manuscript [Opt. Express 27, 35189 (2019)], which do not affect the main results or conclusions, and make a corresponding small change to one figure.
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30
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Johnson SG, Pruinelli L, Westra BL. Machine Learned Mapping of Local EHR Flowsheet Data to Standard Information Models using Topic Model Filtering. AMIA Annu Symp Proc 2020; 2019:504-513. [PMID: 32308844 PMCID: PMC7153147] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Subscribe] [Scholar Register] [Indexed: 06/11/2023]
Abstract
Electronic health record (EHR) data must be mapped to standard information models for interoperability and to support research across organizations. New information models are being developed and validated for data important to nursing, but a significant problem remains for how to correctly map the information models to an organization's specific flowsheet data implementation. This paper describes an approach for automating the mapping process by using stacked machine learning models. A first model uses a topic model keyword filter to identify the most likely flowsheet rows that map to a concept. A second model is a support vector machine (SVM) that is trained to be a more accurate classifier for each concept. The stacked combination results in a classifier that is good at mapping flowsheets to information models with an overall f2 score of 0.74. This approach is generalizable to mapping other data types that have short text descriptions.
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Affiliation(s)
- Steven G Johnson
- Institute for Health Informatics, University of Minnesota, Minneapolis, MN
| | - Lisiane Pruinelli
- Institute for Health Informatics, University of Minnesota, Minneapolis, MN
- School of Nursing, University of Minnesota, Minneapolis, MN
| | - Bonnie L Westra
- Institute for Health Informatics, University of Minnesota, Minneapolis, MN
- School of Nursing, University of Minnesota, Minneapolis, MN
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Preston DB, Johnson SG. Generalist grasshoppers from thermally variable sites do not have higher thermal tolerance than grasshoppers from thermally stable sites - A study of five populations. J Therm Biol 2020; 88:102527. [PMID: 32126002 DOI: 10.1016/j.jtherbio.2020.102527] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/09/2019] [Revised: 01/20/2020] [Accepted: 01/20/2020] [Indexed: 11/24/2022]
Abstract
Thermal tolerance allows many organisms, including insects, to withstand stressful temperatures. Thermal generalists are expected to have higher thermal tolerance than specialists, but the environmental conditions leading to the evolution of a thermal generalist life history are not fully understood. Thermal variability has been put forth as an evolutionary driver of high thermal tolerance, but rarely has this been empirically tested. We used a generalist agricultural pest grasshopper, Melanoplus differentialis, to test upper and lower thermal limits of populations that experienced different levels of thermal variability. We quantified thermal heterogeneity at five sites in a longitudinal transect in the Midwestern U.S. by examining, over a 101-year period, 1) variance in daily thermal maxima and minima; and 2) daily range. Also, as a measure of a biologically relevant thermal extreme, we depicted days per month at each site that reached a stressfully high temperature for M. differentialis. We collected individuals from these sites and tested their upper and lower thermal limits. We found that most of our metrics of thermal heterogeneity differed among sites, while all sites experienced an average of at least two stressfully high temperature events per month. We found that heavier males from these sites were able to withstand both warmer and colder temperatures than smaller males, while heavier females had no thermal advantage over lighter females. However, site of origin had no effect on thermal tolerance. Our findings indicate three things: 1) there is no clear correlation between thermal variability and thermal tolerance in the populations we studied; 2) weight affects thermal tolerance range among sites for M. differentialis males, and 3) thermal extremes may be more important than thermal variability in determining CTMax in this species.
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Affiliation(s)
- Devin B Preston
- Department of Biological Sciences, University of New Orleans, New Orleans, LA, USA.
| | - Steven G Johnson
- Department of Biological Sciences, University of New Orleans, New Orleans, LA, USA.
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Christiansen RE, Michon J, Benzaouia M, Sigmund O, Johnson SG. Inverse design of nanoparticles for enhanced Raman scattering. Opt Express 2020; 28:4444-4462. [PMID: 32121681 DOI: 10.1364/oe.28.004444] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Received: 11/13/2019] [Accepted: 11/29/2019] [Indexed: 06/10/2023]
Abstract
We show that topology optimization (TO) of metallic resonators can lead to ∼102 × improvement in surface-enhanced Raman scattering (SERS) efficiency compared to traditional resonant structures such as bowtie antennas. TO inverse design leads to surprising structures very different from conventional designs, which simultaneously optimize focusing of the incident wave and emission from the Raman dipole. We consider isolated metallic particles as well as more complicated configurations such as periodic surfaces or resonators coupled to dielectric waveguides, and the benefits of TO are even greater in the latter case. Our results are motivated by recent rigorous upper bounds to Raman scattering enhancement, and shed light on the extent to which these bounds are achievable.
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Michon J, Benzaouia M, Yao W, Miller OD, Johnson SG. Limits to surface-enhanced Raman scattering near arbitrary-shape scatterers. Opt Express 2019; 27:35189-35202. [PMID: 31878692 DOI: 10.1364/oe.27.035189] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.4] [Reference Citation Analysis] [What about the content of this article? (0)] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Received: 09/25/2019] [Accepted: 10/22/2019] [Indexed: 06/10/2023]
Abstract
The low efficiency of Raman spectroscopy can be overcome by placing the active molecules in the vicinity of scatterers, typically rough surfaces or nanostructures with various shapes. This surface-enhanced Raman scattering (SERS) leads to substantial enhancement that depends on the scatterer that is used. In this work, we find fundamental upper bounds on the Raman enhancement for arbitrary-shaped scatterers, depending only on its material constants and the separation distance from the molecule. According to our metric, silver is optimal in visible wavelengths while aluminum is better in the near-UV region. Our general analytical bound scales as the volume of the scatterer and the inverse sixth power of the distance to the active molecule. Numerical computations show that simple geometries fall short of the bounds, suggesting further design opportunities for future improvement. For periodic scatterers, we use two formulations to discover different bounds, and the tighter of the two always must apply. Comparing these bounds suggests an optimal period depending on the volume of the scatterer.
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Chevalier P, Amirzhan A, Wang F, Piccardo M, Johnson SG, Capasso F, Everitt HO. Widely tunable compact terahertz gas lasers. Science 2019; 366:856-860. [DOI: 10.1126/science.aay8683] [Citation(s) in RCA: 46] [Impact Index Per Article: 9.2] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/15/2019] [Accepted: 10/21/2019] [Indexed: 01/23/2023]
Affiliation(s)
- Paul Chevalier
- Harvard John A. Paulson School of Engineering and Applied Sciences, Harvard University, Cambridge, MA 02138, USA
| | - Arman Amirzhan
- Harvard John A. Paulson School of Engineering and Applied Sciences, Harvard University, Cambridge, MA 02138, USA
| | - Fan Wang
- Department of Mechanical Engineering, Massachusetts Institute of Technology, Cambridge, MA 02139, USA
| | - Marco Piccardo
- Harvard John A. Paulson School of Engineering and Applied Sciences, Harvard University, Cambridge, MA 02138, USA
| | - Steven G. Johnson
- Department of Mathematics, Massachusetts Institute of Technology, Cambridge, MA 02139, USA
- Department of Physics, Massachusetts Institute of Technology, Cambridge, MA 02139, USA
| | - Federico Capasso
- Harvard John A. Paulson School of Engineering and Applied Sciences, Harvard University, Cambridge, MA 02138, USA
| | - Henry O. Everitt
- U.S. Army Combat Capabilities Development Command Aviation and Missile Center, Redstone Arsenal, AL 35898, USA
- Department of Physics, Duke University, Durham, NC 27708, USA
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Lin Z, Johnson SG. Overlapping domains for topology optimization of large-area metasurfaces. Opt Express 2019; 27:32445-32453. [PMID: 31684457 DOI: 10.1364/oe.27.032445] [Citation(s) in RCA: 14] [Impact Index Per Article: 2.8] [Reference Citation Analysis] [What about the content of this article? (0)] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Received: 06/13/2019] [Accepted: 08/15/2019] [Indexed: 05/21/2023]
Abstract
We introduce an overlapping-domain approach to large-area metasurface design, in which each simulated domain consists of a unit cell and overlapping regions from the neighboring cells plus PML absorbers. We show that our approach generates greatly improved metalens quality compared to designs produced using a locally periodic approximation, thanks to ∼10× better accuracy with similar computational cost. We use the new approach with topology optimization to design large-area (200λ) high-NA (0.71) multichrome and broadband achromatic lenses with high focusing efficiency (∼50%), greatly improving upon previously reported works.
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Abstract
Achieving topologically-protected robust transport in optical systems has recently been of great interest. Most studied topological photonic structures can be understood by solving the eigenvalue problem of Maxwell’s equations for static linear systems. Here, we extend topological phases into dynamically driven systems and achieve a Floquet Chern insulator of light in nonlinear photonic crystals (PhCs). Specifically, we start by presenting the Floquet eigenvalue problem in driven two-dimensional PhCs. We then define topological invariant associated with Floquet bands, and show that topological band gaps with non-zero Chern number can be opened by breaking time-reversal symmetry through the driving field. Finally, we numerically demonstrate the existence of chiral edge states at the interfaces between a Floquet Chern insulator and normal insulators, where the transport is non-reciprocal and uni-directional. Our work paves the way to further exploring topological phases in driven optical systems and their optoelectronic applications. Topological photonic structures can be understood by solving the eigenvalue problem of Maxwell’s equations in the static case. Here, the authors study Floquet topological phases in nonlinear photonic crystals under external drive and show how non-reciprocal transport can be achieved in a Floquet Chern insulator.
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Affiliation(s)
- Li He
- Department of Physics and Astronomy, University of Pennsylvania, Philadelphia, PA, 19104, USA
| | - Zachariah Addison
- Department of Physics and Astronomy, University of Pennsylvania, Philadelphia, PA, 19104, USA
| | - Jicheng Jin
- Department of Physics and Astronomy, University of Pennsylvania, Philadelphia, PA, 19104, USA
| | - Eugene J Mele
- Department of Physics and Astronomy, University of Pennsylvania, Philadelphia, PA, 19104, USA
| | - Steven G Johnson
- Department of Mathematics, Massachusetts Institute of Technology, Cambridge, MA, 02139, USA
| | - Bo Zhen
- Department of Physics and Astronomy, University of Pennsylvania, Philadelphia, PA, 19104, USA.
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Lin Z, Liu V, Pestourie R, Johnson SG. Topology optimization of freeform large-area metasurfaces. Opt Express 2019; 27:15765-15775. [PMID: 31163767 DOI: 10.1364/oe.27.015765] [Citation(s) in RCA: 28] [Impact Index Per Article: 5.6] [Reference Citation Analysis] [What about the content of this article? (0)] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Received: 02/08/2019] [Accepted: 03/20/2019] [Indexed: 06/09/2023]
Abstract
We demonstrate optimization of optical metasurfaces over 105-106 degrees of freedom in two and three dimensions, 100-1000+ wavelengths (λ) in diameter, with 100+ parameters per λ2. In particular, we show how topology optimization, with one degree of freedom per high-resolution "pixel," can be extended to large areas with the help of a locally periodic approximation that was previously only used for a few parameters per λ2. In this way, we can computationally discover completely unexpected metasurface designs for challenging multi-frequency, multi-angle problems, including designs for fully coupled multi-layer structures with arbitrary per-layer patterns. Unlike typical metasurface designs based on subwavelength unit cells, our approach can discover both sub- and supra-wavelength patterns and can obtain both the near and far fields.
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Johnson SG, Pruinelli L, Hoff A, Kumar V, Simon GJ, Steinbach M, Westra BL. A Framework for Visualizing Data Quality for Predictive Models and Clinical Quality Measures. AMIA Jt Summits Transl Sci Proc 2019; 2019:630-638. [PMID: 31259018 PMCID: PMC6568139] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Grants] [Subscribe] [Scholar Register] [Indexed: 06/09/2023]
Abstract
The ability to assess data quality is essential for secondary use of EHR data and an automated Healthcare Data Quality Framework (HDQF) can be used as a tool to support a healthcare organization's data quality initiatives. Use of a general purpose HDQF provides a method to assess and visualize data quality to quickly identify areas for improvement. The value of the approach is illustrated for two analytics use cases: 1) predictive models and 2) clinical quality measures. The results show that data quality issues can be efficiently identified and visualized. The automated HDQF is much less time consuming than a manual approach to data quality and the framework can be rerun repeatedly on additional datasets without much effort.
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Affiliation(s)
| | - Lisiane Pruinelli
- Institute for Health Informatics, University of Minnesota
- School of Nursing, University of Minnesota
| | - Alexander Hoff
- Department of Computer Science & Engineering, University of Minnesota
| | - Vipin Kumar
- Department of Computer Science & Engineering, University of Minnesota
| | - György J Simon
- Institute for Health Informatics, University of Minnesota
| | - Michael Steinbach
- Department of Computer Science & Engineering, University of Minnesota
| | - Bonnie L Westra
- Institute for Health Informatics, University of Minnesota
- School of Nursing, University of Minnesota
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Pestourie R, Pérez-Arancibia C, Lin Z, Shin W, Capasso F, Johnson SG. Inverse design of large-area metasurfaces. Opt Express 2018; 26:33732-33747. [PMID: 30650806 DOI: 10.1364/oe.26.033732] [Citation(s) in RCA: 48] [Impact Index Per Article: 8.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Received: 08/14/2018] [Accepted: 10/08/2018] [Indexed: 06/09/2023]
Abstract
We present a computational framework for efficient optimization-based "inverse design" of large-area "metasurfaces" (subwavelength-patterned surfaces) for applications such as multi-wavelength/multi-angle optimizations, and demultiplexers. To optimize surfaces that can be thousands of wavelengths in diameter, with thousands (or millions) of parameters, the key is a fast approximate solver for the scattered field. We employ a "locally periodic" approximation in which the scattering problem is approximated by a composition of periodic scattering problems from each unit cell of the surface, and validate it against brute-force Maxwell solutions. This is an extension of ideas in previous metasurface designs, but with greatly increased flexibility, e.g. to automatically balance tradeoffs between multiple frequencies or to optimize a photonic device given only partial information about the desired field. Our approach even extends beyond the metasurface regime to non-subwavelength structures where additional diffracted orders must be included (but the period is not large enough to apply scalar diffraction theory).
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Pruinelli L, Ma S, Westra BL, Johnson SG, O'Conner Von S, Speedie SM. Multiple Factors Drive Opioid Prescribing at the Time of Discharge. AMIA Annu Symp Proc 2018; 2018:916-921. [PMID: 30815134 PMCID: PMC6371345] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Subscribe] [Scholar Register] [Indexed: 06/09/2023]
Abstract
Multiple factors potentially influence pain intensity or frequency, and consequently the need for an opioid prescription. This study aims to identify factors associated with being discharged with an outpatient opioid prescription. We constructed a database containing clinical, non-clinical, and organizational variables from the EHR that are potentially relevant for ordering an opioid at discharge. Descriptive statistics of these variables and univariate association analysis reveal that all of the examined variables to be statistically significantly associated with opioid prescription at discharge. Further, we fitted a random forest model to examine the information content in the examined variables regarding whether a patient will be discharged with an opioid. The model resulted in a mean AUC of 0.84, suggesting the factors examined in this study in combination contain significant information regarding prescription of an opioid at discharge.
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Affiliation(s)
| | - Sisi Ma
- School of Medicine, University of Minnesota, Minneapolis, MN
- Institute for Health Informatics, University of Minnesota, Minneapolis, MN
| | - Bonnie L Westra
- School of Nursing, University of Minnesota, Minneapolis, MN
- Institute for Health Informatics, University of Minnesota, Minneapolis, MN
| | | | | | - Stuart M Speedie
- Institute for Health Informatics, University of Minnesota, Minneapolis, MN
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Pérez-Arancibia C, Pestourie R, Johnson SG. Sideways adiabaticity: beyond ray optics for slowly varying metasurfaces. Opt Express 2018; 26:30202-30230. [PMID: 30469898 DOI: 10.1364/oe.26.030202] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Received: 06/18/2018] [Accepted: 09/03/2018] [Indexed: 06/09/2023]
Abstract
Optical metasurfaces (subwavelength-patterned surfaces typically described by variable effective surface impedances) are typically modeled by an approximation akin to ray optics: the reflection or transmission of an incident wave at each point of the surface is computed as if the surface were "locally uniform," and then the total field is obtained by summing all of these local scattered fields via a Huygens principle. (Similar approximations are found in scalar diffraction theory and in ray optics for curved surfaces.) In this paper, we develop a precise theory of such approximations for variable-impedance surfaces. Not only do we obtain a type of adiabatic theorem showing that the "zeroth-order" locally uniform approximation converges in the limit as the surface varies more and more slowly, including a way to quantify the rate of convergence, but we also obtain an infinite series of higher-order corrections. These corrections, which can be computed to any desired order by performing integral operations on the surface fields, allow rapidly varying surfaces to be modeled with arbitrary accuracy, and also allow one to validate designs based on the zeroth-order approximation (which is often surprisingly accurate) without resorting to expensive brute-force Maxwell solvers. We show that our formulation works arbitrarily close to the surface, and can even compute coupling to guided modes, whereas in the far-field limit our zeroth-order result simplifies to an expression similar to what has been used by other authors.
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Westra BL, Johnson SG, Ali S, Bavuso KM, Cruz CA, Collins S, Furukawa M, Hook ML, LaFlamme A, Lytle K, Pruinelli L, Rajchel T, Settergren TT, Westman KF, Whittenburg L. Validation and Refinement of a Pain Information Model from EHR Flowsheet Data. Appl Clin Inform 2018; 9:185-198. [PMID: 29539649 PMCID: PMC5851787 DOI: 10.1055/s-0038-1636508] [Citation(s) in RCA: 17] [Impact Index Per Article: 2.8] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/14/2017] [Accepted: 01/15/2018] [Indexed: 10/17/2022] Open
Abstract
BACKGROUND Secondary use of electronic health record (EHR) data can reduce costs of research and quality reporting. However, EHR data must be consistent within and across organizations. Flowsheet data provide a rich source of interprofessional data and represents a high volume of documentation; however, content is not standardized. Health care organizations design and implement customized content for different care areas creating duplicative data that is noncomparable. In a prior study, 10 information models (IMs) were derived from an EHR that included 2.4 million patients. There was a need to evaluate the generalizability of the models across organizations. The pain IM was selected for evaluation and refinement because pain is a commonly occurring problem associated with high costs for pain management. OBJECTIVE The purpose of our study was to validate and further refine a pain IM from EHR flowsheet data that standardizes pain concepts, definitions, and associated value sets for assessments, goals, interventions, and outcomes. METHODS A retrospective observational study was conducted using an iterative consensus-based approach to map, analyze, and evaluate data from 10 organizations. RESULTS The aggregated metadata from the EHRs of 8 large health care organizations and the design build in 2 additional organizations represented flowsheet data from 6.6 million patients, 27 million encounters, and 683 million observations. The final pain IM has 30 concepts, 4 panels (classes), and 396 value set items. Results are built on Logical Observation Identifiers Names and Codes (LOINC) pain assessment terms and extend the need for additional terms to support interoperability. CONCLUSION The resulting pain IM is a consensus model based on actual EHR documentation in the participating health systems. The IM captures the most important concepts related to pain.
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Affiliation(s)
- Bonnie L. Westra
- School of Nursing, University of Minnesota, Minneapolis, Minnesota, United States
| | - Steven G. Johnson
- School of Nursing, University of Minnesota, Minneapolis, Minnesota, United States
| | - Samira Ali
- Adjunct Faculty, School of Nursing, Grand Canyon University, Phoenix, Arizona, United States
| | - Karen M. Bavuso
- Department of Clinical Informatics, Partners Healthcare System, Wellesley, Massachusetts, United States
| | - Christopher A. Cruz
- Department of Care Delivery BioClinical Informatics, Kaiser Permanente, Oakland, California, United States
| | - Sarah Collins
- Department of Medicine, Brigham and Women's Hospital, Partners Healthcare System, Harvard Medical School, Boston, Massachusetts, United States
| | - Meg Furukawa
- Department of Information Services & Solutions, University of California Los Angeles Health, Los Angeles, California, United States
| | - Mary L. Hook
- Center for Nursing Practice and Research, Aurora Health Care, Milwaukee, Wisconsin, United States
| | - Anne LaFlamme
- Department of Nursing, Fairview Health Services, Minneapolis, Minnesota, United States
| | - Kay Lytle
- Department of Nursing & Duke Health Technology Solutions, Duke University Health System, Durham, North Carolina, United States
| | - Lisiane Pruinelli
- School of Nursing, University of Minnesota, Minneapolis, Minnesota, United States
| | - Tari Rajchel
- Department of Information Technology, North Memorial Medical Center, Robbinsdale, Minnesota, United States
| | - Theresa Tess Settergren
- Department of Enterprise Information Services, Cedars-Sinai Health System, Los Angeles, California, United States
| | - Kathryn F. Westman
- Department of Nursing, Allina Health, Minneapolis, Minnesota, United States
| | - Luann Whittenburg
- Informatics Consultant, Bumrungrad International, Health Informatics/Health System Architecture, Bangkok, Thailand
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Abstract
Objective The objective of this study was to demonstrate the utility of a healthcare data quality framework by using it to measure the impact of synthetic data quality issues on the validity of an eMeasure (CMS178—urinary catheter removal after surgery).
Methods Data quality issues were artificially created by systematically degrading the underlying quality of EHR data using two methods: independent and correlated degradation. A linear model that describes the change in the events included in the eMeasure quantifies the impact of each data quality issue.
Results Catheter duration had the most impact on the CMS178 eMeasure with every 1% reduction in data quality causing a 1.21% increase in the number of missing events. For birth date and admission type, every 1% reduction in data quality resulted in a 1% increase in missing events.
Conclusion This research demonstrated that the impact of data quality issues can be quantified using a generalized process and that the CMS178 eMeasure, as currently defined, may not measure how well an organization is meeting the intended best practice goal. Secondary use of EHR data is warranted only if the data are of sufficient quality. The assessment approach described in this study demonstrates how the impact of data quality issues on an eMeasure can be quantified and the approach can be generalized for other data analysis tasks. Healthcare organizations can prioritize data quality improvement efforts to focus on the areas that will have the most impact on validity and assess whether the values that are reported should be trusted.
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Affiliation(s)
- Steven G Johnson
- Institute for Health Informatics, University of Minnesota, Minneapolis, Minnesota, United States
| | - Stuart Speedie
- Institute for Health Informatics, University of Minnesota, Minneapolis, Minnesota, United States
| | - Gyorgy Simon
- Institute for Health Informatics, University of Minnesota, Minneapolis, Minnesota, United States
| | - Vipin Kumar
- Department of Computer Science, University of Minnesota, Minneapolis, Minnesota, United States
| | - Bonnie L Westra
- Institute for Health Informatics, University of Minnesota, Minneapolis, Minnesota, United States.,School of Nursing, University of Minnesota, Minneapolis, Minnesota, United States
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Westra BL, Christie B, Johnson SG, Pruinelli L, LaFlamme A, Sherman SG, Park JI, Delaney CW, Gao G, Speedie S. Modeling Flowsheet Data to Support Secondary Use. Comput Inform Nurs 2017; 35:452-458. [PMID: 28346243 DOI: 10.1097/cin.0000000000000350] [Citation(s) in RCA: 14] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/25/2022]
Abstract
The purpose of this study was to create information models from flowsheet data using a data-driven consensus-based method. Electronic health records contain a large volume of data about patient assessments and interventions captured in flowsheets that measure the same "thing," but the names of these observations often differ, according to who performs documentation or the location of the service (eg, pulse rate in an intensive care, the emergency department, or a surgical unit documented by a nurse or therapist or captured by automated monitoring). Flowsheet data are challenging for secondary use because of the existence of multiple semantically equivalent measures representing the same concepts. Ten information models were created in this study: five related to quality measures (falls, pressure ulcers, venous thromboembolism, genitourinary system including catheter-associated urinary tract infection, and pain management) and five high-volume physiological systems: cardiac, gastrointestinal, musculoskeletal, respiratory, and expanded vital signs/anthropometrics. The value of the information models is that flowsheet data can be extracted and mapped for semantically comparable flowsheet measures from a clinical data repository regardless of the time frame, discipline, or setting in which documentation occurred. The 10 information models simplify the representation of the content in flowsheet data, reducing 1552 source measures to 557 concepts. The amount of representational reduction ranges from 3% for falls to 78% for the respiratory system. The information models provide a foundation for including nursing and interprofessional assessments and interventions in common data models, to support research within and across health systems.
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Affiliation(s)
- Bonnie L Westra
- Author Affiliations: School of Nursing (Drs Westra, Johnson, Pruinelli, Park, Delaney, and Gao) and Institute for Health Informatics, University of Minnesota (Drs Westra, Delaney, and Speedie); Fairview Health Services & University of Minnesota Health (Drs Christie, LaFlamme, and Sherman), Minneapolis, MN
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Miller OD, Ilic O, Christensen T, Reid MTH, Atwater HA, Joannopoulos JD, Soljačić M, Johnson SG. Limits to the Optical Response of Graphene and Two-Dimensional Materials. Nano Lett 2017; 17:5408-5415. [PMID: 28776375 DOI: 10.1021/acs.nanolett.7b02007] [Citation(s) in RCA: 5] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 05/06/2023]
Abstract
Two-dimensional (2D) materials provide a platform for strong light-matter interactions, creating wide-ranging design opportunities via new-material discoveries and new methods for geometrical structuring. We derive general upper bounds to the strength of such light-matter interactions, given only the optical conductivity of the material, including spatial nonlocality, and otherwise independent of shape and configuration. Our material figure-of-merit shows that highly doped graphene is an optimal material at infrared frequencies, whereas single-atomic-layer silver is optimal in the visible. For quantities ranging from absorption and scattering to near-field spontaneous-emission enhancements and radiative heat transfer, we consider canonical geometrical structures and show that in certain cases the bounds can be approached, while in others there may be significant opportunity for design improvement. The bounds can encourage systematic improvements in the design of ultrathin broadband absorbers, 2D antennas, and near-field energy harvesters.
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Affiliation(s)
- Owen D Miller
- Department of Applied Physics and Energy Sciences Institute, Yale University , New Haven, Connecticut 06511, United States
| | - Ognjen Ilic
- Department of Applied Physics and Material Science, California Institute of Technology , Pasadena, California 91125, United States
| | - Thomas Christensen
- Department of Physics, Massachusetts Institute of Technology , Cambridge, Massachusetts 02139, United States
| | - M T Homer Reid
- Department of Mathematics, Massachusetts Institute of Technology , Cambridge, Massachusetts 02139, United States
| | - Harry A Atwater
- Department of Applied Physics and Material Science, California Institute of Technology , Pasadena, California 91125, United States
| | - John D Joannopoulos
- Department of Physics, Massachusetts Institute of Technology , Cambridge, Massachusetts 02139, United States
| | - Marin Soljačić
- Department of Physics, Massachusetts Institute of Technology , Cambridge, Massachusetts 02139, United States
| | - Steven G Johnson
- Department of Physics, Massachusetts Institute of Technology , Cambridge, Massachusetts 02139, United States
- Department of Mathematics, Massachusetts Institute of Technology , Cambridge, Massachusetts 02139, United States
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Johnson SG, Bragg E. AGE AND POLYPHYLETIC ORIGINS OF HYBRID AND SPONTANEOUS PARTHENOGENETIC
CAMPELOMA
(GASTROPODA: VIVIPARIDAE) FROM THE SOUTHEASTERN UNITED STATES. Evolution 2017; 53:1769-1781. [DOI: 10.1111/j.1558-5646.1999.tb04561.x] [Citation(s) in RCA: 23] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/27/1998] [Accepted: 06/10/1999] [Indexed: 11/30/2022]
Affiliation(s)
- Steven G. Johnson
- Department of Biological Sciences University of New Orleans New Orleans Louisiana 70148
| | - Eric Bragg
- Department of Biological Sciences University of New Orleans New Orleans Louisiana 70148
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Pick A, Zhen B, Miller OD, Hsu CW, Hernandez F, Rodriguez AW, Soljačić M, Johnson SG. General theory of spontaneous emission near exceptional points. Opt Express 2017; 25:12325-12348. [PMID: 28786590 DOI: 10.1364/oe.25.012325] [Citation(s) in RCA: 33] [Impact Index Per Article: 4.7] [Reference Citation Analysis] [What about the content of this article? (0)] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Received: 03/14/2017] [Accepted: 04/20/2017] [Indexed: 06/07/2023]
Abstract
We present a general theory of spontaneous emission at exceptional points (EPs)-exotic degeneracies in non-Hermitian systems. Our theory extends beyond spontaneous emission to any light-matter interaction described by the local density of states (e.g., absorption, thermal emission, and nonlinear frequency conversion). Whereas traditional spontaneous-emission theories imply infinite enhancement factors at EPs, we derive finite bounds on the enhancement, proving maximum enhancement of 4 in passive systems with second-order EPs and significantly larger enhancements (exceeding 400×) in gain-aided and higher-order EP systems. In contrast to non-degenerate resonances, which are typically associated with Lorentzian emission curves in systems with low losses, EPs are associated with non-Lorentzian lineshapes, leading to enhancements that scale nonlinearly with the resonance quality factor. Our theory can be applied to dispersive media, with proper normalization of the resonant modes.
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Lee YE, Miller OD, Homer Reid MT, Johnson SG, Fang NX. Computational inverse design of non-intuitive illumination patterns to maximize optical force or torque. Opt Express 2017; 25:6757-6766. [PMID: 28381019 DOI: 10.1364/oe.25.006757] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.6] [Reference Citation Analysis] [What about the content of this article? (0)] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/07/2023]
Abstract
This paper aims to maximize optical force or torque on arbitrary micro- and nanoscale objects using numerically optimized structured illumination. By developing a numerical framework for computer-automated design of 3d vector-field illumination, we demonstrate a 20-fold enhancement in optical torque per intensity over circularly polarized plane wave on a model plasmonic particle. The nonconvex optimization is efficiently performed by combining a compact cylindrical Bessel basis representation with a fast boundary element method and a standard derivative-free, local optimization algorithm. We analyze the optimization results for 2000 random initial configurations, discuss the tradeoff between robustness and enhancement, and compare the different effects of multipolar plasmon resonances on enhancing force or torque. All results are obtained using open-source computational software available online.
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Kahn MG, Callahan TJ, Barnard J, Bauck AE, Brown J, Davidson BN, Estiri H, Goerg C, Holve E, Johnson SG, Liaw ST, Hamilton-Lopez M, Meeker D, Ong TC, Ryan P, Shang N, Weiskopf NG, Weng C, Zozus MN, Schilling L. A Harmonized Data Quality Assessment Terminology and Framework for the Secondary Use of Electronic Health Record Data. ACTA ACUST UNITED AC 2016; 4:1244. [PMID: 27713905 PMCID: PMC5051581 DOI: 10.13063/2327-9214.1244] [Citation(s) in RCA: 176] [Impact Index Per Article: 22.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/24/2022]
Abstract
Objective: Harmonized data quality (DQ) assessment terms, methods, and reporting practices can establish a common understanding of the strengths and limitations of electronic health record (EHR) data for operational analytics, quality improvement, and research. Existing published DQ terms were harmonized to a comprehensive unified terminology with definitions and examples and organized into a conceptual framework to support a common approach to defining whether EHR data is ‘fit’ for specific uses. Materials and Methods: DQ publications, informatics and analytics experts, managers of established DQ programs, and operational manuals from several mature EHR-based research networks were reviewed to identify potential DQ terms and categories. Two face-to-face stakeholder meetings were used to vet an initial set of DQ terms and definitions that were grouped into an overall conceptual framework. Feedback received from data producers and users was used to construct a draft set of harmonized DQ terms and categories. Multiple rounds of iterative refinement resulted in a set of terms and organizing framework consisting of DQ categories, subcategories, terms, definitions, and examples. The harmonized terminology and logical framework’s inclusiveness was evaluated against ten published DQ terminologies. Results: Existing DQ terms were harmonized and organized into a framework by defining three DQ categories: (1) Conformance (2) Completeness and (3) Plausibility and two DQ assessment contexts: (1) Verification and (2) Validation. Conformance and Plausibility categories were further divided into subcategories. Each category and subcategory was defined with respect to whether the data may be verified with organizational data, or validated against an accepted gold standard, depending on proposed context and uses. The coverage of the harmonized DQ terminology was validated by successfully aligning to multiple published DQ terminologies. Discussion: Existing DQ concepts, community input, and expert review informed the development of a distinct set of terms, organized into categories and subcategories. The resulting DQ terms successfully encompassed a wide range of disparate DQ terminologies. Operational definitions were developed to provide guidance for implementing DQ assessment procedures. The resulting structure is an inclusive DQ framework for standardizing DQ assessment and reporting. While our analysis focused on the DQ issues often found in EHR data, the new terminology may be applicable to a wide range of electronic health data such as administrative, research, and patient-reported data. Conclusion: A consistent, common DQ terminology, organized into a logical framework, is an initial step in enabling data owners and users, patients, and policy makers to evaluate and communicate data quality findings in a well-defined manner with a shared vocabulary. Future work will leverage the framework and terminology to develop reusable data quality assessment and reporting methods.
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Affiliation(s)
| | | | | | | | | | | | - Hossein Estiri
- University of Washington, Institute of Translational Health Sciences
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Westra BL, Christie B, Johnson SG, Pruinelli L, LaFlamme A, Park JI, Sherman SG, Byrne MD, Ranallo P, Speedie S. Expanding Interprofessional EHR Data in i2b2. AMIA Jt Summits Transl Sci Proc 2016; 2016:260-8. [PMID: 27570680 PMCID: PMC5001775] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Indexed: 10/26/2022]
Abstract
Emerging issues of team-based care, precision medicine, and big data science underscore the need for health information technology (HIT) tools for integrating complex data in consistent ways to achieve the triple aims of improving patient outcomes, patient experience, and cost reductions. The purpose of this study was to demonstrate the feasibility of creating a hierarchical flowsheet ontology in i2b2 using data-derived information models and determine the underlying informatics and technical issues. This study is the first of its kind to use information models that aggregate team-based care across time, disciplines, and settings into 14 information models that were integrated into i2b2 in a hierarchical model. In the process of successfully creating a hierarchical ontology for flowsheet data in i2b2, we uncovered a variety of informatics and technical issues described in this paper.
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Affiliation(s)
- Bonnie L. Westra
- University of Minnesota, School of Nursing, Minneapolis, MN;,University of Minnesota, Institute for Health Informatics, Minneapolis, MN
| | | | - Steven G. Johnson
- University of Minnesota, Institute for Health Informatics, Minneapolis, MN
| | | | | | - Jung In Park
- University of Minnesota, School of Nursing, Minneapolis, MN
| | | | | | | | - Stuart Speedie
- University of Minnesota, Institute for Health Informatics, Minneapolis, MN
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