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Koehler S, Hengel FE, Dumoulin B, Damashek L, Holzman LB, Susztak K, Huber TB. The 14th International Podocyte Conference 2023: from podocyte biology to glomerular medicine. Kidney Int 2024; 105:935-952. [PMID: 38447880 DOI: 10.1016/j.kint.2024.01.042] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/30/2023] [Revised: 12/11/2023] [Accepted: 01/02/2024] [Indexed: 03/08/2024]
Abstract
The 14th International Podocyte Conference took place in Philadelphia, Pennsylvania, USA from May 23 to 26, 2023. It commenced with an early-career researchers' meeting on May 23, providing young scientists with a platform to present and discuss their research findings. Throughout the main conference, 29 speakers across 9 sessions shared their insights on podocyte biology, glomerular medicine, novel technologic advancements, and translational approaches. Additionally, the event featured 3 keynote lectures addressing engineered chimeric antigen receptor T cell- and mRNA-based therapies and the use of biobanks for enhanced disease comprehension. Furthermore, 4 brief oral abstract sessions allowed scientists to present their findings to a broad audience. The program also included a panel discussion addressing the challenges of conducting human research within the American Black community. Remarkably, after a 5-year hiatus from in-person conferences, the 14th International Podocyte Conference successfully convened scientists from around the globe, fostering the presentation and discussion of crucial research findings, as summarized in this review. Furthermore, to ensure continuous and sustainable education, research, translation, and trial medicine related to podocyte and glomerular diseases for the benefit of patients, the International Society of Glomerular Disease was officially launched during the conference.
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Affiliation(s)
- Sybille Koehler
- III. Department of Medicine and Hamburg Center for Kidney Health (HCKH), University Medical Center Hamburg-Eppendorf (UKE), Hamburg, Germany
| | - Felicitas E Hengel
- III. Department of Medicine and Hamburg Center for Kidney Health (HCKH), University Medical Center Hamburg-Eppendorf (UKE), Hamburg, Germany
| | - Bernhard Dumoulin
- III. Department of Medicine and Hamburg Center for Kidney Health (HCKH), University Medical Center Hamburg-Eppendorf (UKE), Hamburg, Germany; Renal, Electrolyte, and Hypertension Division, Department of Medicine, University of Pennsylvania Perelman School of Medicine, Philadelphia, Pennsylvania, USA
| | - Laurel Damashek
- International Society of Glomerular Disease, Florence, Massachusetts, USA
| | - Lawrence B Holzman
- Renal, Electrolyte, and Hypertension Division, Department of Medicine, University of Pennsylvania Perelman School of Medicine, Philadelphia, Pennsylvania, USA
| | - Katalin Susztak
- Renal, Electrolyte, and Hypertension Division, Department of Medicine, University of Pennsylvania Perelman School of Medicine, Philadelphia, Pennsylvania, USA; Institute of Diabetes, Obesity and Metabolism, Perelman School of Medicine, University of Pennsylvania, Philadelphia, Pennsylvania, USA; Department of Genetics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, Pennsylvania, USA
| | - Tobias B Huber
- III. Department of Medicine and Hamburg Center for Kidney Health (HCKH), University Medical Center Hamburg-Eppendorf (UKE), Hamburg, Germany; International Society of Glomerular Disease, Florence, Massachusetts, USA.
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Lee YC, Liu L, Yuan L, Risk M, Heinrich K, Witteveen-Lane M, Hayek S, Malosh R, Pop-Busui R, Jiang B, Shen C, Chesla D, Kennedy R, Xu S, Sims M, Homayouni R, Zhao L. Influenza vaccine effectiveness against hospitalized SARS-CoV-2 infection. MEDRXIV : THE PREPRINT SERVER FOR HEALTH SCIENCES 2023:2023.10.27.23297682. [PMID: 37961376 PMCID: PMC10635222 DOI: 10.1101/2023.10.27.23297682] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 11/15/2023]
Abstract
Background Some studies conducted before the Delta and Omicron variant-dominant periods have indicated that influenza vaccination provided protection against COVID-19 infection or hospitalization, but these results were limited by small study cohorts and a lack of comprehensive data on patient characteristics. No studies have examined this question during the Delta and Omicron periods (08/01/2021 to 2/22/2022). Methods We conducted a retrospective cohort study of influenza-vaccinated and unvaccinated patients in the Corewell Health East(CHE, formerly known as Beaumont Health), Corewell Health West(CHW, formerly known as Spectrum Health) and Michigan Medicine (MM) healthcare system during the Delta-dominant and Omicron-dominant periods. We used a test-negative, case-control analysis to assess the effectiveness of the influenza vaccine against hospitalized SARS-CoV-2 outcome in adults, while controlling for individual characteristics as well as pandameic severity and waning immunity of COVID-19 vaccine. Results The influenza vaccination has shown to provided some protection against SARS-CoV-2 hospitalized outcome across three main healthcare systems. CHE site (odds ratio [OR]=0.73, vaccine effectiveness [VE]=27%, 95% confidence interval [CI]: [18-35], p<0.001), CHW site (OR=0.85, VE=15%, 95% CI: [6-24], p<0.001), MM (OR=0.50, VE=50%, 95% CI: [40-58], p <0.001) and overall (OR=0.75, VE=25%, 95% CI: [20-30], p <0.001). Conclusion The influenza vaccine provides a small degree of protection against SARS-CoV-2 infection across our study sites.
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Subica AM, Aitaoto N, Li Q, Morey BN, Wu LT, Iwamoto DK, Guerrero EG, Moss HB. Assessing the Impact of COVID-19 on the Health of Native Hawaiian/Pacific Islander People in the United States, 2021. Public Health Rep 2023; 138:164-173. [PMID: 36113145 PMCID: PMC9482884 DOI: 10.1177/00333549221123579] [Citation(s) in RCA: 5] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/03/2023] Open
Abstract
OBJECTIVES Minimal research has assessed COVID-19's unique impact on the Native Hawaiian/Pacific Islander (NH/PI) population-an Indigenous-colonized racial group with social and health disparities that increase their risk for COVID-19 morbidity and mortality. To address this gap, we explored the scope of COVID-19 outcomes, vaccination status, and health in diverse NH/PI communities. METHODS NH/PI staff at partner organizations collected survey data from April through November 2021 from 319 community-dwelling NH/PI adults in 5 states with large NH/PI populations: Arkansas, California, Oregon, Utah, and Washington. Data were analyzed with descriptive statistics, Pearson χ2 tests, independent and paired t tests, and linear and logistic regression analyses. RESULTS During the COVID-19 pandemic, 30% of survey participants had contracted COVID-19, 16% had a close family member who died of the disease, and 64% reported COVID-19 vaccine uptake. Thirty percent reported fair/poor health, 21% currently smoked cigarettes, and 58% reported obesity. Survey participants reported heightened COVID-19-related psychosocial distress (mean score = 4.9 on 10-point scale), which was more likely when health outcomes (general health, sleep, obesity) were poor or a family member had died of COVID-19. Logistic regression indicated that age, experiencing COVID-19 distress, and past-year use of influenza vaccines were associated with higher odds of COVID-19 vaccine uptake (1.06, 1.18, and 7.58 times, respectively). CONCLUSIONS Our empirical findings highlight the acute and understudied negative impact of COVID-19 on NH/PI communities in the United States and suggest new avenues for improving NH/PI community health, vaccination, and recovery from COVID-19.
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Affiliation(s)
- Andrew M. Subica
- Department of Social Medicine, Population, and Public Health, School of Medicine, University of California, Riverside, Riverside, CA, USA
| | - Nia Aitaoto
- Pacific Islander Center of Primary Care Excellence, San Leandro, CA, USA
| | - Qiuxi Li
- Special Services for Groups, Los Angeles, CA, USA
| | - Brittany N. Morey
- Department of Health, Society, and Behavior, University of California, Irvine, Irvine, CA, USA
| | - Li-Tzy Wu
- School of Medicine, Duke University, Durham, NC, USA
| | - Derek K. Iwamoto
- Department of Psychology, University of Maryland, College Park, MD, USA
| | | | - Howard B. Moss
- Department of Social Medicine, Population, and Public Health, School of Medicine, University of California, Riverside, Riverside, CA, USA
- Department of Psychiatry, School of Medicine, University of California, Riverside, Riverside, CA, USA
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Verma A, Damrauer SM, Naseer N, Weaver J, Kripke CM, Guare L, Sirugo G, Kember RL, Drivas TG, Dudek SM, Bradford Y, Lucas A, Judy R, Verma SS, Meagher E, Nathanson KL, Feldman M, Ritchie MD, Rader DJ, BioBank FTPM. The Penn Medicine BioBank: Towards a Genomics-Enabled Learning Healthcare System to Accelerate Precision Medicine in a Diverse Population. J Pers Med 2022; 12:jpm12121974. [PMID: 36556195 PMCID: PMC9785650 DOI: 10.3390/jpm12121974] [Citation(s) in RCA: 49] [Impact Index Per Article: 24.5] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/08/2022] [Revised: 11/17/2022] [Accepted: 11/19/2022] [Indexed: 12/02/2022] Open
Abstract
The Penn Medicine BioBank (PMBB) is an electronic health record (EHR)-linked biobank at the University of Pennsylvania (Penn Medicine). A large variety of health-related information, ranging from diagnosis codes to laboratory measurements, imaging data and lifestyle information, is integrated with genomic and biomarker data in the PMBB to facilitate discoveries and translational science. To date, 174,712 participants have been enrolled into the PMBB, including approximately 30% of participants of non-European ancestry, making it one of the most diverse medical biobanks. There is a median of seven years of longitudinal data in the EHR available on participants, who also consent to permission to recontact. Herein, we describe the operations and infrastructure of the PMBB, summarize the phenotypic architecture of the enrolled participants, and use body mass index (BMI) as a proof-of-concept quantitative phenotype for PheWAS, LabWAS, and GWAS. The major representation of African-American participants in the PMBB addresses the essential need to expand the diversity in genetic and translational research. There is a critical need for a "medical biobank consortium" to facilitate replication, increase power for rare phenotypes and variants, and promote harmonized collaboration to optimize the potential for biological discovery and precision medicine.
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Affiliation(s)
- Anurag Verma
- Department of Medicine, Division of Translational Medicine and Human Genetics, University of Pennsylvania, Philadelphia, PA 19104, USA
- Institute for Translational Medicine and Therapeutics, University of Pennsylvania, Philadelphia, PA 19104, USA
- Correspondence: (A.V.); (D.J.R.)
| | - Scott M. Damrauer
- Institute for Translational Medicine and Therapeutics, University of Pennsylvania, Philadelphia, PA 19104, USA
- Department of Genetics, University of Pennsylvania, Philadelphia, PA 19104, USA
- Department of Surgery, Division of Vascular Surgery and Endovascular Therapy, University of Pennsylvania, Philadelphia, PA 19104, USA
| | - Nawar Naseer
- Institute for Translational Medicine and Therapeutics, University of Pennsylvania, Philadelphia, PA 19104, USA
| | - JoEllen Weaver
- Institute for Translational Medicine and Therapeutics, University of Pennsylvania, Philadelphia, PA 19104, USA
| | - Colleen M. Kripke
- Department of Medicine, Division of Translational Medicine and Human Genetics, University of Pennsylvania, Philadelphia, PA 19104, USA
- Institute for Translational Medicine and Therapeutics, University of Pennsylvania, Philadelphia, PA 19104, USA
| | - Lindsay Guare
- Department of Pathology, University of Pennsylvania, Philadelphia, PA 19104, USA
| | - Giorgio Sirugo
- Department of Medicine, Division of Translational Medicine and Human Genetics, University of Pennsylvania, Philadelphia, PA 19104, USA
- Institute for Translational Medicine and Therapeutics, University of Pennsylvania, Philadelphia, PA 19104, USA
| | - Rachel L. Kember
- Department of Psychiatry, University of Pennsylvania, Philadelphia, PA 19104, USA
| | - Theodore G. Drivas
- Department of Medicine, Division of Translational Medicine and Human Genetics, University of Pennsylvania, Philadelphia, PA 19104, USA
| | - Scott M. Dudek
- Department of Genetics, University of Pennsylvania, Philadelphia, PA 19104, USA
| | - Yuki Bradford
- Department of Genetics, University of Pennsylvania, Philadelphia, PA 19104, USA
| | - Anastasia Lucas
- Department of Genetics, University of Pennsylvania, Philadelphia, PA 19104, USA
| | - Renae Judy
- Department of Surgery, Division of Vascular Surgery and Endovascular Therapy, University of Pennsylvania, Philadelphia, PA 19104, USA
| | - Shefali S. Verma
- Department of Pathology, University of Pennsylvania, Philadelphia, PA 19104, USA
| | - Emma Meagher
- Department of Medicine, Division of Translational Medicine and Human Genetics, University of Pennsylvania, Philadelphia, PA 19104, USA
- Institute for Translational Medicine and Therapeutics, University of Pennsylvania, Philadelphia, PA 19104, USA
| | - Katherine L. Nathanson
- Department of Medicine, Division of Translational Medicine and Human Genetics, University of Pennsylvania, Philadelphia, PA 19104, USA
- Abramson Cancer Center, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA 19104, USA
| | - Michael Feldman
- Department of Pathology, University of Pennsylvania, Philadelphia, PA 19104, USA
| | - Marylyn D. Ritchie
- Department of Genetics, University of Pennsylvania, Philadelphia, PA 19104, USA
| | - Daniel J. Rader
- Department of Medicine, Division of Translational Medicine and Human Genetics, University of Pennsylvania, Philadelphia, PA 19104, USA
- Institute for Translational Medicine and Therapeutics, University of Pennsylvania, Philadelphia, PA 19104, USA
- Department of Genetics, University of Pennsylvania, Philadelphia, PA 19104, USA
- Correspondence: (A.V.); (D.J.R.)
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Truong VQ, Woerner JA, Cherlin TA, Bradford Y, Lucas AM, Okeh CC, Shivakumar MK, Hui DH, Kumar R, Pividori M, Jones SC, Bossa AC, Turner SD, Ritchie MD, Verma SS. Quality Control Procedures for Genome-Wide Association Studies. Curr Protoc 2022; 2:e603. [PMID: 36441943 DOI: 10.1002/cpz1.603] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 06/16/2023]
Abstract
Genome-wide association studies (GWAS) are being conducted at an unprecedented rate in population-based cohorts and have increased our understanding of the pathophysiology of many complex diseases. Regardless of the context, the practical utility of this information ultimately depends upon the quality of the data used for statistical analyses. Quality control (QC) procedures for GWAS are constantly evolving. Here, we enumerate some of the challenges in QC of genotyped GWAS data and describe the approaches involving genotype imputation of a sample dataset along with post-imputation quality assurance, thereby minimizing potential bias and error in GWAS results. We discuss common issues associated with QC of the GWAS data (genotyped and imputed), including data file formats, software packages for data manipulation and analysis, sex chromosome anomalies, sample identity, sample relatedness, population substructure, batch effects, and marker quality. We provide detailed guidelines along with a sample dataset to suggest current best practices and discuss areas of ongoing and future research. © 2022 Wiley Periodicals LLC.
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Affiliation(s)
- Van Q Truong
- Genomics and Computational Biology Graduate Group, University of Pennsylvania, Perelman School of Medicine, Philadelphia, Pennsylvania, USA
- Department of Genetics, University of Pennsylvania, Perelman School of Medicine, Philadelphia, Pennsylvania, USA
| | - Jakob A Woerner
- Genomics and Computational Biology Graduate Group, University of Pennsylvania, Perelman School of Medicine, Philadelphia, Pennsylvania, USA
- Department of Genetics, University of Pennsylvania, Perelman School of Medicine, Philadelphia, Pennsylvania, USA
| | - Tess A Cherlin
- Department of Pathology and Laboratory Medicine, University of Pennsylvania, Perelman School of Medicine, Philadelphia, Pennsylvania, USA
| | - Yuki Bradford
- Department of Genetics, University of Pennsylvania, Perelman School of Medicine, Philadelphia, Pennsylvania, USA
| | - Anastasia M Lucas
- Genomics and Computational Biology Graduate Group, University of Pennsylvania, Perelman School of Medicine, Philadelphia, Pennsylvania, USA
- Department of Genetics, University of Pennsylvania, Perelman School of Medicine, Philadelphia, Pennsylvania, USA
| | - Chelsea C Okeh
- Department of Pathology and Laboratory Medicine, University of Pennsylvania, Perelman School of Medicine, Philadelphia, Pennsylvania, USA
| | - Manu K Shivakumar
- Genomics and Computational Biology Graduate Group, University of Pennsylvania, Perelman School of Medicine, Philadelphia, Pennsylvania, USA
- Department of Genetics, University of Pennsylvania, Perelman School of Medicine, Philadelphia, Pennsylvania, USA
| | - Daniel H Hui
- Genomics and Computational Biology Graduate Group, University of Pennsylvania, Perelman School of Medicine, Philadelphia, Pennsylvania, USA
- Department of Genetics, University of Pennsylvania, Perelman School of Medicine, Philadelphia, Pennsylvania, USA
| | - Rachit Kumar
- Genomics and Computational Biology Graduate Group, University of Pennsylvania, Perelman School of Medicine, Philadelphia, Pennsylvania, USA
- Department of Genetics, University of Pennsylvania, Perelman School of Medicine, Philadelphia, Pennsylvania, USA
| | - Milton Pividori
- Department of Genetics, University of Pennsylvania, Perelman School of Medicine, Philadelphia, Pennsylvania, USA
| | - S Chris Jones
- Genomics and Computational Biology Graduate Group, University of Pennsylvania, Perelman School of Medicine, Philadelphia, Pennsylvania, USA
- Department of Genetics, University of Pennsylvania, Perelman School of Medicine, Philadelphia, Pennsylvania, USA
| | - Abigail C Bossa
- Department of Genetics, University of Pennsylvania, Perelman School of Medicine, Philadelphia, Pennsylvania, USA
| | | | - Marylyn D Ritchie
- Department of Genetics, University of Pennsylvania, Perelman School of Medicine, Philadelphia, Pennsylvania, USA
| | - Shefali S Verma
- Department of Pathology and Laboratory Medicine, University of Pennsylvania, Perelman School of Medicine, Philadelphia, Pennsylvania, USA
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Ragon B, Volkov BB, Pulley C, Holmes K. Using informatics to advance translational science: Environmental scan of adaptive capacity and preparedness of Clinical and Translational Science Award Program hubs. J Clin Transl Sci 2022; 6:e76. [PMID: 35836790 PMCID: PMC9274387 DOI: 10.1017/cts.2022.402] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/24/2022] [Accepted: 04/06/2022] [Indexed: 11/29/2022] Open
Abstract
As the USA and the rest of the world raced to fight the COVID-19 pandemic, years of investments from the National Center for Advancing Translational Sciences allowed for informatics services and resources at CTSA hubs to play a significant role in addressing the crisis. CTSA hubs partnered with local and regional partners to collect data on the pandemic, provide access to relevant patient data, and produce data dashboards to support decision-making. Coordinated efforts, like the National COVID Cohort Collaborative (N3C), helped to aggregate and harmonize clinical data nationwide. Even with significant informatics investments, some CTSA hubs felt unprepared in their ability to respond to the fast-moving public health crisis. Many hubs were forced to quickly evolve to meet local needs. Informatics teams expanded critical support at their institutions which included an engagement platform for clinical research, COVID-19 awareness and education activities in the community, and COVID-19 data dashboards. Continued investments in informatics resources will aid in ensuring that tools, resources, practices, and policies are aligned to meet local and national public health needs.
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Affiliation(s)
- Bart Ragon
- Integrated Translational Health Research Institute of Virginia, Charlottesville, VA, USA
- University of Virginia, Charlottesville, VA, USA
| | - Boris B. Volkov
- University of Minnesota Clinical and Translational Science Institute, Minneapolis, MN, USA
- Institute for Health Informatics and Division of Epidemiology and Community Health, University of Minnesota, Minneapolis, MN, USA
| | - Chris Pulley
- University of Minnesota Clinical and Translational Science Institute, Minneapolis, MN, USA
| | - Kristi Holmes
- Northwestern University Clinical and Translational Sciences Institute, Chicago, IL, USA
- Department of Preventive Medicine, Northwestern University Feinberg School of Medicine, Chicago, IL, USA
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Hitokoto H, Adeclas J. Harmony and Aversion in the Face of a Pandemic
1. JAPANESE PSYCHOLOGICAL RESEARCH 2022; 64:222-243. [PMID: 35599957 PMCID: PMC9115224 DOI: 10.1111/jpr.12416] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/24/2021] [Accepted: 02/04/2022] [Indexed: 12/15/2022]
Abstract
While the survival function of culture against infectious disease has been investigated, little is known about its psychological processes under the real‐world threat of infection. Here, we compare the subjective COVID‐19‐related symptoms of Japanese and French adults during the spring of 2021. We tested two regression models describing the downregulation of symptoms by germ aversion, and by interdependent happiness, together with relational mobility and demographics. We regard germ aversion as an individualized fending‐off process marked by discomfort with the general other in the face of possible infection. We regard interdependent happiness as a relational safeguarding process against possible infection. Results suggest that the effect of germ aversion differed across nations, negatively explaining symptoms in Japan but not in France, and that the effect of interdependent happiness was shared. A possible psychological mechanism whereby collectivist culture suppresses infection in the face of the pandemic is discussed.
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Verspoor K. The Evolution of Clinical Knowledge During COVID-19: Towards a Global Learning Health System. Yearb Med Inform 2021; 30:176-184. [PMID: 34479389 PMCID: PMC8416229 DOI: 10.1055/s-0041-1726503] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/08/2023] Open
Abstract
OBJECTIVES We examine the knowledge ecosystem of COVID-19, focusing on clinical knowledge and the role of health informatics as enabling technology. We argue for commitment to the model of a global learning health system to facilitate rapid knowledge translation supporting health care decision making in the face of emerging diseases. METHODS AND RESULTS We frame the evolution of knowledge in the COVID-19 crisis in terms of learning theory, and present a view of what has occurred during the pandemic to rapidly derive and share knowledge as an (underdeveloped) instance of a global learning health system. We identify the key role of information technologies for electronic data capture and data sharing, computational modelling, evidence synthesis, and knowledge dissemination. We further highlight gaps in the system and barriers to full realisation of an efficient and effective global learning health system. CONCLUSIONS The need for a global knowledge ecosystem supporting rapid learning from clinical practice has become more apparent than ever during the COVID-19 pandemic. Continued effort to realise the vision of a global learning health system, including establishing effective approaches to data governance and ethics to support the system, is imperative to enable continuous improvement in our clinical care.
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Affiliation(s)
- Karin Verspoor
- School of Computing Technologies, RMIT University, Melbourne VIC 3000 Australia
- Centre for Digital Transformation of Health, The University of Melbourne, Melbourne VIC 3010 Australia
- School of Computing and Information Systems, The University of Melbourne, Melbourne VIC 3010 Australia
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