scholarly journals Learning Associations Between Clinical Information and Motion-Based Descriptors Using a Large Scale MR-derived Cardiac Motion Atlas

2019 ◽  
pp. 94-102
Author(s):  
Esther Puyol-Antón ◽  
Bram Ruijsink ◽  
Hélène Langet ◽  
Mathieu De Craene ◽  
Paolo Piro ◽  
...  
Keyword(s):  
Large Scale ◽  
Clinical Information ◽  
Cardiac Motion

scholarly journals Implementing an Integrated Large-Scale Clinical Information System for ISSSTE’s Hospital Network in Mexico

2021 ◽  
Vol 3 (2) ◽  
pp. 444-453
Author(s):  
Arturo Cervantes Trejo ◽  
Sophie Domenge Treuille ◽  
Isaac Castañeda Alcántara
Keyword(s):  
Health Care ◽  
Information System ◽  
Health Care Services ◽  
Large Scale ◽  
Clinical Information System ◽  
Clinical Information ◽  
Public Hospitals ◽  
Care Services ◽  
Cost Reductions

AbstractThe Institute for Security and Social Services for State Workers (ISSSTE) is a large public provider of health care services that serve around 13.2 million Mexican government workers and their families. To attain process efficiencies, cost reductions, and improvement of the quality of diagnostic and imaging services, ISSSTE was set out in 2019 to create a digital filmless medical image and report management system. A large-scale clinical information system (CIS), including radiology information system (RIS), picture archiving and communication system (PACS), and clinical data warehouse (CDW) components, was implemented at ISSSTE’s network of forty secondary- and tertiary-level public hospitals, applying global HL-7 and Digital Imaging and Communications in Medicine (DICOM) standards. In just 5 months, 40 hospitals had their endoscopy, radiology, and pathology services functionally interconnected within a national CIS and RIS/PACS on secure private local area networks (LANs) and a secure national wide area network (WAN). More than 2 million yearly studies and reports are now in digital form in a CDW, securely stored and always available. Benefits include increased productivity, reduced turnaround times, reduced need for duplicate exams, and reduced costs. Functional IT solutions allow ISSSTE hospitals to leave behind the use of radiographic film and printed medical reports with important cost reductions, as well as social and environmental impacts, leading to direct improvement in the quality of health care services rendered.

Progressive alteration of DNA methylation of Alu, MGMT, MINT2, and TFPI2 genes in colonic mucosa during colorectal cancer development

2021 ◽  
pp. 1-6
Author(s):  
Ben Kang ◽  
Hyun Seok Lee ◽  
Seong Woo Jeon ◽  
Soo Yeun Park ◽  
Gyu Seog Choi ◽  
...  
Keyword(s):  
Colorectal Cancer ◽  
Dna Methylation ◽  
Healthy Subjects ◽  
Large Scale ◽  
Methylation Status ◽  
Clinical Information ◽  
Field Cancerization ◽  
Aberrant Methylation ◽  
Clinical Value ◽  
Mortality And Morbidity

BACKGROUND: Colorectal cancer (CRC) is one of the leading causes of mortality and morbidity in the world. It is characterized by different pathways of carcinogenesis and is a heterogeneous disease with diverse molecular landscapes that reflect histopathological and clinical information. Changes in the DNA methylation status of colon epithelial cells have been identified as critical components in CRC development and appear to be emerging biomarkers for the early detection and prognosis of CRC. OBJECTIVE: To explore the underlying disease mechanisms and identify more effective biomarkers of CRC. METHODS: We compared the levels and frequencies of DNA methylation in 11 genes (Alu, APC, DAPK, MGMT, MLH1, MINT1, MINT2, MINT3, p16, RGS6, and TFPI2) in colorectal cancer and its precursor adenomatous polyp with normal tissue of healthy subjects using pyrosequencing and then evaluated the clinical value of these genes. RESULTS: Aberrant methylation of Alu, MGMT, MINT2, and TFPI2 genes was progressively accumulated during the normal-adenoma-carcinoma progression. Additionally, CGI methylation occurred either as an adenoma-associated event for APC, MLH1, MINT1, MINT31, p16, and RGS6 or a tumor-associated event for DAPK. Moreover, relatively high levels and frequencies of DAPK, MGMT, and TFPI2 methylation were detected in the peritumoral nonmalignant mucosa of cancer patients in a field-cancerization manner, as compared to normal mucosa from healthy subjects. CONCLUSION: This study identified several biomarkers associated with the initiation and progression of CRC. As novel findings, they may have important clinical implications for CRC diagnostic and prognostic applications. Further large-scale studies are needed to confirm these findings.

scholarly journals Joint Imaging Platform for Federated Clinical Data Analytics

2020 ◽  
pp. 1027-1038
Author(s):  
Jonas Scherer ◽  
Marco Nolden ◽  
Jens Kleesiek ◽  
Jasmin Metzger ◽  
Klaus Kades ◽  
...  
Keyword(s):  
Data Analytics ◽  
Large Scale ◽  
Image Data ◽  
Clinical Information ◽  
Quality Data ◽  
Imaging Data ◽  
University Hospitals ◽  
High Quality Data ◽  
Interactive Analysis ◽  
Legal Constraints

PURPOSE Image analysis is one of the most promising applications of artificial intelligence (AI) in health care, potentially improving prediction, diagnosis, and treatment of diseases. Although scientific advances in this area critically depend on the accessibility of large-volume and high-quality data, sharing data between institutions faces various ethical and legal constraints as well as organizational and technical obstacles. METHODS The Joint Imaging Platform (JIP) of the German Cancer Consortium (DKTK) addresses these issues by providing federated data analysis technology in a secure and compliant way. Using the JIP, medical image data remain in the originator institutions, but analysis and AI algorithms are shared and jointly used. Common standards and interfaces to local systems ensure permanent data sovereignty of participating institutions. RESULTS The JIP is established in the radiology and nuclear medicine departments of 10 university hospitals in Germany (DKTK partner sites). In multiple complementary use cases, we show that the platform fulfills all relevant requirements to serve as a foundation for multicenter medical imaging trials and research on large cohorts, including the harmonization and integration of data, interactive analysis, automatic analysis, federated machine learning, and extensibility and maintenance processes, which are elementary for the sustainability of such a platform. CONCLUSION The results demonstrate the feasibility of using the JIP as a federated data analytics platform in heterogeneous clinical information technology and software landscapes, solving an important bottleneck for the application of AI to large-scale clinical imaging data.

The Angiosarcoma Project: Generating the genomic landscape of a rare cancer through a direct-to-patient initiative.

2017 ◽  
Vol 35 (15_suppl) ◽  
pp. 1519-1519 ◽  
Author(s):  
Corrie Painter ◽  
Michael Dunphy ◽  
Elana Anastasio ◽  
Mary McGillicuddy ◽  
Kristin Anderka ◽  
...  
Keyword(s):  
Medical Records ◽  
Large Scale ◽  
Dna Analysis ◽  
Genomic Analysis ◽  
Clinical Information ◽  
Rapid Identification ◽  
Blood Draw ◽  
Tissue Samples ◽  
The Usa ◽  
Reported Data

1519 Background: Angiosarcoma (AS) is a rare soft tissue sarcoma, with an incidence of 300/yr and a 5-year DSS of 30%. The low incidence has impeded large-scale research efforts that may lead to improved clinical outcomes. To address this, we launched a nationwide study, which seeks to empower patients (pts) to accelerate research by sharing their samples and clinical information remotely. Methods: With pts and advocacy groups we developed a website to allow AS pts to participate across the US. Pts are mailed a saliva and blood draw kit for germline and cell free (cf) DNA analysis. We then obtain medical records and stored tumor samples. Whole exome sequencing will be performed on tumor, cfDNA and saliva samples. Transcriptome analysis will be performed on tumor samples. A clinically annotated genomic database will be generated and shared widely to identify genomic drivers and mechanisms of response and resistance to therapies. Study updates will be shared with pts regularly. Results: We conducted a 3-week pilot study to test the feasibility of enrolling geographically dispersed AS pts through a direct-to-patient (DTP) approach. Through social media, we identified 100+ pts willing to participate, 90 within the first day of outreach. We enrolled 15 pts from 10 states to test our ability to remotely obtain pt reported data, online consent, and samples. The average age of pts is 48, ranging 23-71 yrs. Primary locations of AS are breast 6 pts (40%), cardiac 4 pts (27%), scalp 2 pts (13%), liver 1 pt (6%), bladder 1 pt (6%), forehead 1 pt (6%). 9 pts (60%) reported being disease free, 4 pts (27%) reported having AS spread to lung, lymph, bone, and hip. Requests for medical records and tissue samples are underway, and initial saliva samples have been received. We are now opening this study to all AS pts in the USA. Conclusions: A DTP approach enabled rapid identification of an initial cohort of AS pts willing to share tumors, saliva, blood and medical records. We were able to obtain detailed clinical experiences and samples to perform genomic analysis. This study serves as proof of principle that DTP genomics efforts can democratize cancer research for exceedingly rare cancers, which to date have been disproportionately understudied.

scholarly journals The Clinical Information Systems Response to the COVID-19 Pandemic

2021 ◽  
Vol 30 (01) ◽  
pp. 105-125
Author(s):  
J. Jeffery Reeves ◽  
Natalie M. Pageler ◽  
Elizabeth C. Wick ◽  
Genevieve B. Melton ◽  
Yu-Heng Gamaliel Tan ◽  
...  
Keyword(s):  
Information Systems ◽  
Information Exchange ◽  
Large Scale ◽  
Predictive Analytics ◽  
Clinical Care ◽  
Clinical Information ◽  
Machine Learning Algorithms ◽  
Screening Tools ◽  
Contact Tracing ◽  
Clinical Information Systems

Summary Objective: The year 2020 was predominated by the coronavirus disease 2019 (COVID-19) pandemic. The objective of this article is to review the areas in which clinical information systems (CIS) can be and have been utilized to support and enhance the response of healthcare systems to pandemics, focusing on COVID-19. Methods: PubMed/MEDLINE, Google Scholar, the tables of contents of major informatics journals, and the bibliographies of articles were searched for studies pertaining to CIS, pandemics, and COVID-19 through October 2020. The most informative and detailed studies were highlighted, while many others were referenced. Results: CIS were heavily relied upon by health systems and governmental agencies worldwide in response to COVID-19. Technology-based screening tools were developed to assist rapid case identification and appropriate triaging. Clinical care was supported by utilizing the electronic health record (EHR) to onboard frontline providers to new protocols, offer clinical decision support, and improve systems for diagnostic testing. Telehealth became the most rapidly adopted medical trend in recent history and an essential strategy for allowing safe and effective access to medical care. Artificial intelligence and machine learning algorithms were developed to enhance screening, diagnostic imaging, and predictive analytics - though evidence of improved outcomes remains limited. Geographic information systems and big data enabled real-time dashboards vital for epidemic monitoring, hospital preparedness strategies, and health policy decision making. Digital contact tracing systems were implemented to assist a labor-intensive task with the aim of curbing transmission. Large scale data sharing, effective health information exchange, and interoperability of EHRs remain challenges for the informatics community with immense clinical and academic potential. CIS must be used in combination with engaged stakeholders and operational change management in order to meaningfully improve patient outcomes. Conclusion: Managing a pandemic requires widespread, timely, and effective distribution of reliable information. In the past year, CIS and informaticists made prominent and influential contributions in the global response to the COVID-19 pandemic.

scholarly journals HeartBioPortal: an internet-of-omics for human cardiovascular disease data

2018 ◽  
Author(s):  
Bohdan Khomtchouk ◽  
Kasra A Vand ◽  
William C Koehler ◽  
Diem-Trang Tran ◽  
Kai Middlebrook ◽  
...  
Keyword(s):  
Cardiovascular Disease ◽  
Web Application ◽  
Large Scale ◽  
Data Science ◽  
Cancer Genomics ◽  
Clinical Information ◽  
Visual Access ◽  
Public Resources ◽  
User Friendly ◽  
Computational Platform

Cardiovascular disease (CVD) is the leading cause of death worldwide, causing over 17M deaths per year, which outpaces global cancer mortality rates. Despite these sobering statistics, the state-of-the-art in computational infrastructure to study datasets associated with CVD has lagged far behind public resources widely available in the oncology field, where improved data science and visualization methods have led to the development of large-scale cancer genomics resources like MSKCC's cBioPortal or NCI's Genomic Data Commons (GDC) Portal. Developing a similar user-friendly computational platform could significantly lower the barriers between complex CVD data and researchers who want rapid, intuitive, and high-quality visual access to molecular profiles and clinical attributes from existing CVD projects. Here we present HeartBioPortal: a publicly available web application that provides intuitive visualization, analysis, and downloads of large-scale CVD data currently focused on gene expression, genetic association, and ancestry information. By democratizing access to anonymized CVD data, HeartBioPortal's aim is to integrate relevant omics and clinical information across the biological dataverse to support CVD clinicians and researchers.

scholarly journals The Anorexia Nervosa Genetics Initiative: Overview and Methods

2017 ◽  
Author(s):  
Laura M Thornton ◽  
Melissa A Munn-Chernoff ◽  
Jessica H Baker ◽  
Anders Juréus ◽  
Richard Parker ◽  
...  
Keyword(s):  
Anorexia Nervosa ◽  
Eating Disorder ◽  
Large Scale ◽  
Eating Behaviors ◽  
Clinical Information ◽  
The United States ◽  
Sample Collection ◽  
Present Sample ◽  
Link Type ◽  
Dsm Iv

AbstractBackground:Genetic factors contribute to anorexia nervosa (AN); and the first genome-wide significant locus has been identified. We describe methods and procedures for the Anorexia Nervosa Genetics Initiative (ANGI), an international collaboration designed to rapidly recruit 13000 individuals with AN as well as ancestrally matched controls. We present sample characteristics and the utility of an online eating disorder diagnostic questionnaire suitable for large-scale genetic and population research.Methods:ANGI recruited from the United States (US), Australia/New Zealand (ANZ), Sweden (SE), and Denmark (DK). Recruitment was via national registers (SE, DK); treatment centers (US, ANZ, SE, DK); and social and traditional media (US, ANZ, SE). All cases had a lifetime AN diagnosis based on DSM-IV or ICD-10 criteria (excluding amenorrhea). Recruited controls had no lifetime history of disordered eating behaviors. To assess the positive and negative predictive validity of the online eating disorder questionnaire (ED100K-v1), 109 women also completed the Structured Clinical Interview for DSM-IV (SCID), Module H.Results:Blood samples and clinical information were collected from 13,364 individuals with lifetime AN and from controls. Online diagnostic phenotyping was effective and efficient; the validity of the questionnaire was acceptable.Conclusions:Our multipronged recruitment approach was highly effective for rapid recruitment and can be used as a model for efforts by other groups. High online presence of individuals with AN rendered the Internet/social media a remarkably effective recruitment tool in some countries. ANGI has substantially augmented Psychiatric Genomics Consortium AN sample collection. ANGI is a registered clinical trial: clinicaltrials.gov NCT01916538; https://clinicaltrials.gov/ct2/show/NCT01916538?cond=Anorexia+Nervosa&draw=1&rank=3.

Factors Influencing the Prioritization of Injured Patients for Transfer to a Burn or Trauma Center Following a Mass Casualty Event

2020 ◽  
pp. 1-8
Author(s):  
Elizabeth A. Lancet ◽  
Wei Wei Zhang ◽  
Patricia Roblin ◽  
Bonnie Arquilla ◽  
Rachel Zeig-Owens ◽  
...  
Keyword(s):  
New York ◽  
Large Scale ◽  
Local Community ◽  
Injury Severity ◽  
Community Hospital ◽  
Clinical Information ◽  
Mass Casualty ◽  
Patient Profile ◽  
Mass Casualty Event ◽  
Consultation Team

ABSTRACT Objectives: In New York City, a multi-disciplinary Mass Casualty Consultation team is proposed to support prioritization of patients for coordinated inter-facility transfer after a large-scale mass casualty event. This study examines factors that influence consultation team prioritization decisions. Methods: As part of a multi-hospital functional exercise, 2 teams prioritized the same set of 69 patient profiles. Prioritization decisions were compared between teams. Agreement between teams was assessed based on patient profile demographics and injury severity. An investigator interviewed team leaders to determine reasons for discordant transfer decisions. Results: The 2 teams differed significantly in the total number of transfers recommended (49 vs 36; P = 0.003). However, there was substantial agreement when recommending transfer to burn centers, with 85.5% agreement and inter-rater reliability of 0.67 (confidence interval: 0.49–0.85). There was better agreement for patients with a higher acuity of injuries. Based on interviews, the most common reason for discordance was insider knowledge of the local community hospital and its capabilities. Conclusions: A multi-disciplinary Mass Casualty Consultation team was able to rapidly prioritize patients for coordinated secondary transfer using limited clinical information. Training for consultation teams should emphasize guidelines for transfer based on existing services at sending and receiving hospitals, as knowledge of local community hospital capabilities influence physician decision-making.

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