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Article ; Online: Applying a Commercialization-Readiness Framework to Optimize Value for Achieving Sustainability of an Electronic Health Data Research Network and Its Data Capabilities

Elaine H. Morrato / Mika K. Hamer / Marion Sills / Bethany Kwan / Lisa M. Schilling

eGEMs, Vol 7, Iss

The SAFTINet Experience

2019 Volume 1

Abstract: Context: Sustaining electronic health data networks and maximizing return on federal investment in their development is essential for achieving national data insight goals for transforming health care. However, crossing the business model chasm from ... ...

Abstract	Context: Sustaining electronic health data networks and maximizing return on federal investment in their development is essential for achieving national data insight goals for transforming health care. However, crossing the business model chasm from grant funding to self-sustaining viability is challenging. Case description: This paper presents lessons learned in seeking the sustainability of the Scalable Architecture for Federated Translational Inquiries Network (SAFTINet), and electronic health data network involving over 50 primary care practices in three states. SAFTINet was developed with funding from the Agency for Healthcare Research and Quality to create a multi-state network for comparative effectiveness research (CER) involving safety-net patients. Methods: Three analyses were performed: (1) a product gap analysis of alternative data sources; (2) a Strengths-Weaknesses-Opportunities-Threat (SWOT) analysis of SAFTINet in the context of competing alternatives; and (3) a customer discovery process involving approximately 150 SAFTINet stakeholders to identify SAFTINet’s sustaining value proposition for health services researchers, clinical data partners, and policy makers. Findings: The results of this business model analysis informed SAFTINet’s sustainability strategy. The fundamental high-level product needs were similar between the three primary customer segments: credible data, efficient and easy to use, and relevance to their daily work or ‘jobs to be done’. However, how these benefits needed to be minimally demonstrated varied by customer such that different supporting evidence was required. Major Themes: The SAFTINet experience illustrates that commercialization-readiness and business model methods can be used to identify multi-sided value propositions for sustaining electronic health data networks and their data capabilities as drivers of health care transformation.
Keywords	electronic health data networks ; FQHC ; CER ; PCOR ; dissemination ; implementation ; Computer applications to medicine. Medical informatics ; R858-859.7
Subject code	650
Language	English
Publishing date	2019-08-01T00:00:00Z
Publisher	Ubiquity Press
Document type	Article ; Online
Database	BASE - Bielefeld Academic Search Engine (life sciences selection)

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Article ; Online: Dynamic-ETL

Toan C. Ong / Michael G. Kahn / Bethany M. Kwan / Traci Yamashita / Elias Brandt / Patrick Hosokawa / Chris Uhrich / Lisa M. Schilling

BMC Medical Informatics and Decision Making, Vol 17, Iss 1, Pp 1-

a hybrid approach for health data extraction, transformation and loading

2017 Volume 12

Abstract: Abstract Background Electronic health records (EHRs) contain detailed clinical data stored in proprietary formats with non-standard codes and structures. Participating in multi-site clinical research networks requires EHR data to be restructured and ... ...

Abstract	Abstract Background Electronic health records (EHRs) contain detailed clinical data stored in proprietary formats with non-standard codes and structures. Participating in multi-site clinical research networks requires EHR data to be restructured and transformed into a common format and standard terminologies, and optimally linked to other data sources. The expertise and scalable solutions needed to transform data to conform to network requirements are beyond the scope of many health care organizations and there is a need for practical tools that lower the barriers of data contribution to clinical research networks. Methods We designed and implemented a health data transformation and loading approach, which we refer to as Dynamic ETL (Extraction, Transformation and Loading) (D-ETL), that automates part of the process through use of scalable, reusable and customizable code, while retaining manual aspects of the process that requires knowledge of complex coding syntax. This approach provides the flexibility required for the ETL of heterogeneous data, variations in semantic expertise, and transparency of transformation logic that are essential to implement ETL conventions across clinical research sharing networks. Processing workflows are directed by the ETL specifications guideline, developed by ETL designers with extensive knowledge of the structure and semantics of health data (i.e., “health data domain experts”) and target common data model. Results D-ETL was implemented to perform ETL operations that load data from various sources with different database schema structures into the Observational Medical Outcome Partnership (OMOP) common data model. The results showed that ETL rule composition methods and the D-ETL engine offer a scalable solution for health data transformation via automatic query generation to harmonize source datasets. Conclusions D-ETL supports a flexible and transparent process to transform and load health data into a target data model. This approach offers a solution that lowers technical barriers that prevent data partners from participating in research data networks, and therefore, promotes the advancement of comparative effectiveness research using secondary electronic health data.
Keywords	Electronic health records ; Extraction ; Transformation and loading ; Distributed research networks ; Data harmonization ; Rule-based ETL ; Computer applications to medicine. Medical informatics ; R858-859.7
Subject code	006
Language	English
Publishing date	2017-09-01T00:00:00Z
Publisher	BMC
Document type	Article ; Online
Database	BASE - Bielefeld Academic Search Engine (life sciences selection)

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Article ; Online: The DARTNet Institute

Wilson D. Pace / Chet Fox / Turner White / Deborah Graham / Lisa M. Schilling / David R. West

eGEMs, Vol 2, Iss

Seeking a Sustainable Support Mechanism for Electronic Data Enabled Research Networks

2014 Volume 2

Abstract: Context: Clinical data research networks require large investments in infrastructure support to maintain their abilities to extract, transform, and load data from varied data sources, expand electronic data sources and develop learning communities. Case ... ...

Abstract	Context: Clinical data research networks require large investments in infrastructure support to maintain their abilities to extract, transform, and load data from varied data sources, expand electronic data sources and develop learning communities. Case Description: This paper outlines a sustainable business model of ongoing infrastructure support for clinical data research activities. The DARTNet Institute is a not-for-profit 501(c)(3) organization that serves as a support entity for multiple practice-based research networks. Several clinical data research networks working closely with a professional society began collaborating to support shared goals in 2008. This loose affiliation called itself the “DARTNet Collaborative.” In 2011, the DARTNet Institute incorporated as an independent, not-for-profit entity. The business structure allows DARTNet to advocate for all partners without operating its own practice-based research network, serve as a legal voice for activities that overlap multiple partners, share personnel resources through service contracts between partners, and purchase low-cost (nonprofit rate) software. Major Themes: DARTNet’s business model relies upon four diverse sources of revenue: (1) DARTNet licenses and provides access to a propriety software system that extracts, transforms, and loads data from all major electronic health records (EHRs) utilized in the United States, and which also provides clinical decision support for research studies; (2) DARTNet operates a recognized, national professional-society-quality improvement registry that enables organizations to fulfill Meaningful Use 2 criteria; (3) DARTNet provides access to data for research activities that are funded by direct research dollars, provided at prices that generate excess revenue; and (4) DARTNet provides access to large primary care datasets for observational studies and pregrant analyses such as for sample size development. The ability of the system to support pragmatic trials will be described. Conclusion: The DARTNet model facilitates the use of direct grant dollars to generate revenue to support the overall enterprise through a purchased services arrangement. Other services provided through subcontracting provide facilities and administration fees as well as direct dollars to support the system. The flexibility of the business model overcomes the complicated financial arrangements and governance requirements of many professional associations and academic medical centers.
Keywords	Computer applications to medicine. Medical informatics ; R858-859.7
Subject code	020
Language	English
Publishing date	2014-09-01T00:00:00Z
Publisher	Ubiquity Press
Document type	Article ; Online
Database	BASE - Bielefeld Academic Search Engine (life sciences selection)

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Article ; Online: Transparent Reporting of Data Quality in Distributed Data Networks

Michael G. Kahn / Jeffrey S. Brown / Alein T. Chun / Bruce N. Davidson / Daniella Meeker / Patrick B. Ryan / Lisa M. Schilling / Nicole G. Weiskopf / Andrew E. Williams / Meredith Nahm Zozus

eGEMs, Vol 3, Iss

2015 Volume 1

Abstract: Introduction: Poor data quality can be a serious threat to the validity and generalizability of clinical research findings. The growing availability of electronic administrative and clinical data is accompanied by a growing concern about the quality of ... ...

Abstract	Introduction: Poor data quality can be a serious threat to the validity and generalizability of clinical research findings. The growing availability of electronic administrative and clinical data is accompanied by a growing concern about the quality of these data for observational research and other analytic purposes. Currently, there are no widely accepted guidelines for reporting quality results that would enable investigators and consumers to independently determine if a data source is fit for use to support analytic inferences and reliable evidence generation. Model and Methods: We developed a conceptual model that captures the flow of data from data originator across successive data stewards and finally to the data consumer. This “data lifecycle” model illustrates how data quality issues can result in data being returned back to previous data custodians. We highlight the potential risks of poor data quality on clinical practice and research results. Because of the need to ensure transparent reporting of a data quality issues, we created a unifying data-quality reporting framework and a complementary set of 20 data-quality reporting recommendations for studies that use observational clinical and administrative data for secondary data analysis. We obtained stakeholder input on the perceived value of each recommendation by soliciting public comments via two face-to-face meetings of informatics and comparative-effectiveness investigators, through multiple public webinars targeted to the health services research community, and with an open access online wiki. Recommendations: Our recommendations propose reporting on both general and analysis-specific data quality features. The goals of these recommendations are to improve the reporting of data quality measures for studies that use observational clinical and administrative data, to ensure transparency and consistency in computing data quality measures, and to facilitate best practices and trust in the new clinical discoveries based on secondary use of observational data.
Keywords	Computer applications to medicine. Medical informatics ; R858-859.7
Subject code	310
Language	English
Publishing date	2015-03-01T00:00:00Z
Publisher	Ubiquity Press
Document type	Article ; Online
Database	BASE - Bielefeld Academic Search Engine (life sciences selection)

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Article ; Online: Medical Home Characteristics and Asthma Control

Marion R. Sills / Bethany M. Kwan / Barbara P. Yawn / Brian C. Sauer / Diane L. Fairclough / Monica J. Federico / Elizabeth Juarez-Colunga / Lisa M. Schilling

eGEMs, Vol 1, Iss

A Prospective, Observational Cohort Study Protocol

2013 Volume 3

Abstract: Background: This paper describes the methods for an observational comparative effectiveness research study designed to test the association between practice-level medical home characteristics and asthma control in children and adults receiving care in ... ...

Abstract	Background: This paper describes the methods for an observational comparative effectiveness research study designed to test the association between practice-level medical home characteristics and asthma control in children and adults receiving care in safety-net primary care practices. Methods: This is a prospective, longitudinal cohort study, utilizing survey methodologies and secondary analysis of existing structured clinical, administrative, and claims data. The Scalable Architecture for Federated Translational Inquiries Network (SAFTINet) is a safety net-oriented, primary care practice-based research network, with federated databases containing electronic health record (EHR) and Medicaid claims data. Data from approximately 20,000 patients from 50 practices in four healthcare organizations will be included. Practice-level medical home characteristics will be correlated with patient-level asthma outcomes, controlling for potential confounding variables, using a clustered design. Linear and non-linear mixed models will be used for analysis. Study inception was July 1, 2012. A causal graph theory approach was used to guide covariate selection to control for bias and confounding. Discussion:' 'Strengths of this design include 'a priori' specification of hypotheses and methods, a large sample of patients with asthma cared for in safety-net practices, the study of real-world variations in the implementation of the medical home concept, and the innovative use of a combination of claims data, patient-reported data, clinical data from EHRs, and practice-level surveys. We address limitations in causal inference using theory, design and analysis.
Keywords	Computer applications to medicine. Medical informatics ; R858-859.7
Subject code	310
Language	English
Publishing date	2013-12-01T00:00:00Z
Publisher	Ubiquity Press
Document type	Article ; Online
Database	BASE - Bielefeld Academic Search Engine (life sciences selection)

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Article ; Online: Consensus Statement on Electronic Health Predictive Analytics

Ruben Amarasingham / Anne-Marie J. Audet / David W. Bates / I. Glenn Cohen / Martin Entwistle / G. J. Escobar / Vincent Liu / Lynn Etheredge / Bernard Lo / Lucila Ohno-Machado / Sudha Ram / Suchi Saria / Lisa M. Schilling / Anand Shah / Walter F. Stewart / Ewout W. Steyerberg / Bin Xie

eGEMs, Vol 4, Iss

A Guiding Framework to Address Challenges

2016 Volume 1

Abstract: Context: The recent explosion in available electronic health record (EHR) data is motivating a rapid expansion of electronic health care predictive analytic (e-HPA) applications, defined as the use of electronic algorithms that forecast clinical events ... ...

Abstract	Context: The recent explosion in available electronic health record (EHR) data is motivating a rapid expansion of electronic health care predictive analytic (e-HPA) applications, defined as the use of electronic algorithms that forecast clinical events in real time with the intent to improve patient outcomes and reduce costs. There is an urgent need for a systematic framework to guide the development and application of e-HPA to ensure that the field develops in a scientifically sound, ethical, and efficient manner. Objectives: Building upon earlier frameworks of model development and utilization, we identify the emerging opportunities and challenges of e-HPA, propose a framework that enables us to realize these opportunities, address these challenges, and motivate e-HPA stakeholders to both adopt and continuously refine the framework as the applications of e-HPA emerge. Methods: To achieve these objectives, 17 experts with diverse expertise including methodology, ethics, legal, regulation, and health care delivery systems were assembled to identify emerging opportunities and challenges of e-HPA and to propose a framework to guide the development and application of e-HPA. Findings: The framework proposed by the panel includes three key domains where e-HPA differs qualitatively from earlier generations of models and algorithms (Data Barriers, Transparency, and Ethics) and areas where current frameworks are insufficient to address the emerging opportunities and challenges of e-HPA (Regulation and Certification; and Education and Training). The following list of recommendations summarizes the key points of the framework: 1. Data Barriers: Establish mechanisms within the scientific community to support data sharing for predictive model development and testing. 2. Transparency: Set standards around e-HPA validation based on principles of scientific transparency and reproducibility. 3. Ethics: Develop both individual-centered and society-centered risk-benefit approaches to evaluate e-HPA. 4. Regulation and Certification: Construct a self-regulation and certification framework within e-HPA. 5. Education and Training: Make significant changes to medical, nursing, and paraprofessional curricula by including training for understanding, evaluating, and utilizing predictive models.
Keywords	Computer applications to medicine. Medical informatics ; R858-859.7
Subject code	170
Language	English
Publishing date	2016-03-01T00:00:00Z
Publisher	Ubiquity Press
Document type	Article ; Online
Database	BASE - Bielefeld Academic Search Engine (life sciences selection)

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Book ; Online: Heterogeneity and temporal variation in the management of COVID-19

Albert Prats-Uribe / Anthony G. Sena / Lana Yin Hui Lai / Waheed-Ul-Rahman Ahmed / Heba Alghoul / Osaid Alser / Thamir M Alshammari / Carlos Areia / William Carter / Paula Casajust / Dalia Dawoud / Asieh Golozar / Jitendra Jonnagaddala / Paras Mehta / Gong Menchung / Daniel R Morales / Fredrik Nyberg / Jose D Posada / Martina Recalde /

a multinational drug utilization study including 71,921 hospitalized patients from China, South Korea, Spain, and the United States of America

2020

Abstract: Objectives: A plethora of medicines have been repurposed or used as adjunctive therapies for COVID-19. We characterized the utilization of medicines as prescribed in routine practice amongst patients hospitalized for COVID-19 in South Korea, China, Spain, ...

Abstract	Objectives: A plethora of medicines have been repurposed or used as adjunctive therapies for COVID-19. We characterized the utilization of medicines as prescribed in routine practice amongst patients hospitalized for COVID-19 in South Korea, China, Spain, and the USA. Design: International network cohort Setting: Hospital electronic health records from Columbia University Irving Medical Centre (NYC, USA), Stanford (CA, USA), Tufts (MA, USA), Premier (USA), Optum EHR (USA), department of veterans affairs (USA), NFHCRD (Honghu, China) and HM Hospitals (Spain); and nationwide claims from HIRA (South Korea) Participants: patients hospitalized for COVID-19 from January to June 2020 Main outcome measures: Prescription/dispensation of any medicine on or 30 days after hospital admission date Analyses: Number and percentage of users overall and over time Results: 71,921 people were included: 304 from China, 2,089 from Spain, 7,599 from South Korea, and 61,929 from the USA. A total of 3,455 medicines were identified. Common repurposed medicines included hydroxychloroquine (<2% in NFHCRD to 85.4% in HM), azithromycin (4.9% in NFHCRD to 56.5% in HM), lopinavir/ritonavir (<3% in all US but 34.9% in HIRA and 56.5% in HM), and umifenovir (0% in all except 78.3% in NFHCRD). Adjunctive medicines were used with great variability, with the ten most used treatments being (in descending order): bemiparin, enoxaparin, heparin, ceftriaxone, aspirin, vitamin D, famotidine, vitamin C, dexamethasone, and metformin. Hydroxychloroquine and azithromycin increased rapidly in use in March-April but declined steeply in May-June. Conclusions: Multiple medicines were used in the first months of COVID-19 pandemic, with substantial geographic and temporal variation. Hydroxychloroquine, azithromycin, lopinavir-ritonavir, and umifenovir (in China only) were the most prescribed repurposed medicines. Antithrombotics, antibiotics, H2 receptor antagonists and corticosteroids were often used as adjunctive treatments. Research is needed on the comparative risk and benefit of these treatments in the management of COVID-19.
Keywords	COVID-19 ; Electronic health records ; Hydroxychloroquine ; Lopinavir/Ritonavir ; Umifenovir ; Azithromycin ; covid19
Subject code	950
Publishing date	2020-09-25
Publishing country	eu
Document type	Book ; Online
Database	BASE - Bielefeld Academic Search Engine (life sciences selection)

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Book ; Online: Baseline characteristics, management, and outcomes of 55,270 children and adolescents diagnosed with COVID-19 and 1,952,693 with influenza in France, Germany, Spain, South Korea and the United States

Talita Duarte-Salles / David Vizcaya / Andrea Pistillo / Paula Casajust / Anthony G. Sena / Lana Yin Hui Lai / Albert Prats-Uribe / Waheed-Ul-Rahman Ahmed / Thamir M Alshammari / Heba Alghoul / Osaid Alser / Edward Burn / Seng Chan You / Carlos Areia / Clair Blacketer / Scott DuVall / Thomas Falconer / Sergio Fernandez-Bertolin / Stephen Fortin /

an international network cohort study

2020

Abstract: Objectives To characterize the demographics, comorbidities, symptoms, in-hospital treatments, and health outcomes among children/adolescents diagnosed or hospitalized with COVID-19. Secondly, to describe health outcomes amongst children/adolescents ... ...

Abstract	Objectives To characterize the demographics, comorbidities, symptoms, in-hospital treatments, and health outcomes among children/adolescents diagnosed or hospitalized with COVID-19. Secondly, to describe health outcomes amongst children/adolescents diagnosed with previous seasonal influenza. Design International network cohort. Setting Real-world data from European primary care records (France/Germany/Spain), South Korean claims and US claims and hospital databases. Participants Diagnosed and/or hospitalized children/adolescents with COVID-19 at age <18 between January and June 2020; diagnosed with influenza in 2017-2018. Main outcome measures Baseline demographics and comorbidities, symptoms, 30-day in-hospital treatments and outcomes including hospitalization, pneumonia, acute respiratory distress syndrome (ARDS), multi-system inflammatory syndrome (MIS-C), and death. Results A total of 55,270 children/adolescents diagnosed and 3,693 hospitalized with COVID-19 and 1,952,693 diagnosed with influenza were studied. Comorbidities including neurodevelopmental disorders, heart disease, and cancer were all more common among those hospitalized vs diagnosed with COVID-19. The most common COVID-19 symptom was fever. Dyspnea, bronchiolitis, anosmia and gastrointestinal symptoms were more common in COVID-19 than influenza. In-hospital treatments for COVID-19 included repurposed medications (<10%), and adjunctive therapies: systemic corticosteroids (6.8% to 37.6%), famotidine (9.0% to 28.1%), and antithrombotics such as aspirin (2.0% to 21.4%), heparin (2.2% to 18.1%), and enoxaparin (2.8% to 14.8%). Hospitalization was observed in 0.3% to 1.3% of the COVID-19 diagnosed cohort, with undetectable (N<5 per database) 30-day fatality. Thirty-day outcomes including pneumonia, ARDS, and MIS-C were more frequent in COVID-19 than influenza. Conclusions Despite negligible fatality, complications including pneumonia, ARDS and MIS-C were more frequent in children/adolescents with COVID-19 than with influenza. Dyspnea, anosmia and gastrointestinal symptoms could help differential diagnosis. A wide range of medications were used for the inpatient management of pediatric COVID-19.
Keywords	COVID-19 ; Demographics ; Comorbidities ; Symptoms ; Treatments ; Health outcomes ; Children ; Influenza ; Real-world data ; Primary care records ; Claims ; Hospital databases ; covid19
Subject code	360
Publishing date	2020-10-30
Publishing country	eu
Document type	Book ; Online
Database	BASE - Bielefeld Academic Search Engine (life sciences selection)

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Book ; Online: Characteristics and outcomes of 627 044 COVID-19 patients with and without obesity in the United States, Spain, and the United Kingdom

Martina Recalde / Elena Roel / Andrea Pistillo / Anthony G Sena / Albert Prats-Uribe / Waheed Ul-Rahman Ahmed / Heba Alghoul / Thamir M Alshammari / Osaid Alser / Carlos Areia / Edward Burn / Paula Casajust / Dalia Dawoud / Scott L DuVall / Thomas Falconer / Sergio Fernandez-Bertolin / Asieh Golozar / Mengchun Gong / Lana Yin Hui Lai /

Jennifer C.E Lane / Kristine E Lynch / Michael E Matheny / Paras P Mehta / Daniel R Morales / Karthik Natarjan / Fredrik Nyberg / Jose D Posada / Christian G Reich / Lisa M Schilling / Karishma Shah / Nigham H Shah / Vignesh Subbian / Lin Zhang / Hong Zhu / Patrick Ryan / Daniel Prieto-Alhambra / Kristin Kostka / Talita Duarte-Salles

2020

Abstract: Background: COVID-19 may differentially impact people with obesity. We aimed to describe and compare the demographics, comorbidities, and outcomes of obese patients with COVID-19 to those of non-obese patients with COVID-19, or obese patients with ... ...

Abstract	Background: COVID-19 may differentially impact people with obesity. We aimed to describe and compare the demographics, comorbidities, and outcomes of obese patients with COVID-19 to those of non-obese patients with COVID-19, or obese patients with seasonal influenza. Methods: We conducted a cohort study based on outpatient/inpatient care, and claims data from January to June 2020 from the US, Spain, and the UK. We used six databases standardized to the OMOP common data model. We defined two cohorts of patients diagnosed and/or hospitalized with COVID-19. We created corresponding cohorts for patients with influenza in 2017-2018. We followed patients from index date to 30 days or death. We report the frequency of socio-demographics, prior comorbidities, and 30-days outcomes (hospitalization, events, and death) by obesity status. Findings: We included 627 044 COVID-19 (US: 502 650, Spain: 122 058, UK: 2336) and 4 549 568 influenza (US: 4 431 801, Spain: 115 224, UK: 2543) patients. The prevalence of obesity was higher among hospitalized COVID-19 (range: 38% to 54%) than diagnosed COVID-19 (30% to 47%), or diagnosed/hospitalized influenza (15% to 48%) patients. Obese hospitalized COVID-19 patients were more often female and younger than non-obese COVID-19 patients or obese influenza patients. Obese COVID-19 patients were more likely to have prior comorbidities, present with cardiovascular and respiratory events during hospitalization, require intensive services, or die compared to non-obese COVID-19 patients. Obese COVID-19 patients were also more likely to require intensive services or die compared to obese influenza patients, despite presenting with fewer comorbidities. Interpretation: We show that obesity is more common among COVID-19 than influenza patients, and that obese patients present with more severe forms of COVID-19 with higher hospitalization, intensive services, and fatality than non-obese patients. These data are instrumental for guiding preventive strategies of COVID-19 infection and complications
Keywords	COVID-19 ; Obesity ; Hospital admission ; Case-fatality rate ; covid19
Subject code	610
Publishing date	2020-09-03
Publishing country	eu
Document type	Book ; Online
Database	BASE - Bielefeld Academic Search Engine (life sciences selection)

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Article ; Online: An international characterisation of patients hospitalised with COVID-19 and a comparison with those previously hospitalised with influenza

Edward Burn / Seng Chan You / Anthony Sena / Kristin Kostka / Hamed Abedtash / Maria Tereza F. Abrahao / Amanda Alberga / Heba Alghoul / Osaid Alser / Thamir M Alshammari / Carlos Areia / Juan M Banda / Jaehyeong Cho / Aedin C Culhane / Alexander Davydov / Frank J DeFalco / Talita Duarte-Salles / Scott L DuVall / Thomas Falconer /

Weihua Gao / Asieh Golozar / Jill Hardin / George Hripcsak / Vojtech Huser / Hokyun Jeon / Yonghua Jing / Chi Young Jung / Benjamin Skov Kaas-Hansen / Denys Kaduk / Seamus Kent / Yeesuk Kim / Spyros Kolovos / Jennifer Lane / Hyejin Lee / Kristine E. Lynch / Rupa Makadia / Michael E. Matheny / Paras Mehta / Daniel R. Morales / Karthik Natarajan / Fredrik Nyberg / Anna Ostropolets / Rae Woong Park / Jimyung Park / Jose D. Posada / Albert Prats-Uribe / Gowtham A. Rao / Christian Reich / Yeunsook Rho / Peter Rijnbeek / Selva Muthu Kumaran Sathappan / Lisa M. Schilling / Martijn Schuemie / Nigam H. Shah / Azza Shoaibi / Seokyoung Song / Matthew Spotnitz / Marc A. Suchard / Joel Swerdel / David Vizcaya / Salvatore Volpe / Haini Wen / Andrew E Williams / Belay B Yimer / Lin Zhang / Oleg Zhuk / Daniel Prieto-Alhambra / Patrick Ryan

Abstract: Background To better understand the profile of individuals with severe coronavirus disease 2019 (COVID-19), we characterised individuals hospitalised with COVID-19 and compared them to individuals previously hospitalised with influenza. Methods We report ...

Abstract	Background To better understand the profile of individuals with severe coronavirus disease 2019 (COVID-19), we characterised individuals hospitalised with COVID-19 and compared them to individuals previously hospitalised with influenza. Methods We report the characteristics (demographics, prior conditions and medication use) of patients hospitalised with COVID-19 between December 2019 and April 2020 in the US (Columbia University Irving Medical Center [CUIMC], STAnford Medicine Research data Repository [STARR-OMOP], and the Department of Veterans Affairs [VA OMOP]) and Health Insurance Review & Assessment [HIRA] of South Korea. Patients hospitalised with COVID-19 were compared with patients previously hospitalised with influenza in 2014-19. Results 6,806 (US: 1,634, South Korea: 5,172) individuals hospitalised with COVID-19 were included. Patients in the US were majority male (VA OMOP: 94%, STARR-OMOP: 57%, CUIMC: 52%), but were majority female in HIRA (56%). Age profiles varied across data sources. Prevalence of asthma ranged from 7% to 14%, diabetes from 18% to 43%, and hypertensive disorder from 22% to 70% across data sources, while between 9% and 39% were taking drugs acting on the renin-angiotensin system in the 30 days prior to their hospitalisation. Compared to 52,422 individuals hospitalised with influenza, patients admitted with COVID-19 were more likely male, younger, and, in the US, had fewer comorbidities and lower medication use. Conclusions Rates of comorbidities and medication use are high among individuals hospitalised with COVID-19. However, COVID-19 patients are more likely to be male and appear to be younger and, in the US, generally healthier than those typically admitted with influenza.
Keywords	covid19
Publisher	medrxiv
Document type	Article ; Online
DOI	10.1101/2020.04.22.20074336
Database	COVID19

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