Presented at CDISC 2009 in Baltimore, it explores what the Semantic Web can bring to Healthcare. Can it be deployed right now? With ease? CDISC sets standards for the exchange of clinical trial data. Once deployed, they remove much of the redundancy and paper processing that characterizes a typical trial today. Its membership includes government regulators like the US FDA, all the major drug companies and their IT vendors.
Health care wants Linked Data, a semantic web of taxonomies and patient information that empowers patients, doctors and researchers. Hoot72, a straightforward way to break into the silo's of today, is a key step to get there.
Hoot72 throws light on a health-care facility's care-process. It transfers clinical data into the Semantic Web from HL7 messages being exchanged by Health-care applications.
Throw the Semantic Web at Today's Health-carehoot72
Health-care needs functioning IT - and there is finance available. Yet still, it lumbers along, mired in the same talking points: we need Portable Health Records; we need to exchange clinical care information; we need fuller descriptions. Is the Semantic Web the answer? Can it get to work right now?
WEBINAR: The Yosemite Project PART 6 -- Data-Driven Biomedical Research with ...DATAVERSITY
In this presentation, our speaker, Dr. Michel Dumontier, will explore the use of Semantic Web technologies to reduce the overwhelming burden of integrating clinical data with public biomedical data, and enabling a new generation of translational research and their clinical application.
DISTANT-CTO: A Zero Cost, Distantly Supervised Approach to Improve Low-Resour...Anjani Dhrangadhariya
PICO recognition is an information extraction task for identifying participant, intervention, comparator, and outcome information from clinical literature.
Manually identifying PICO information is the most time-consuming step for conducting systematic reviews (SR) which is already a labor-intensive process.
A lack of diversified and large, annotated corpora restricts innovation and adoption of automated PICO recognition systems.
The largest-available PICO entity/span corpus is manually annotated which is too expensive for a majority of the scientific community.
To break through the bottleneck, we propose DISTANT-CTO, a novel distantly supervised PICO entity extraction approach using the clinical trials literature, to generate a massive weakly-labeled dataset with more than a million ``Intervention'' and ``Comparator'' entity annotations.
We train distant NER (named-entity recognition) models using this weakly-labeled dataset and demonstrate that it outperforms even the sophisticated models trained on the manually annotated dataset with a 2\% F1 improvement over the Intervention entity of the PICO benchmark and more than 5\% improvement when combined with the manually annotated dataset.
We investigate the generalizability of our approach and gain an impressive F1 score on another domain-specific PICO benchmark.
The approach is not only zero-cost but is also scalable for a constant stream of PICO entity annotations.
Semantic Technology for Provider-Payer-Pharma Data CollaborationThomas Kelly, PMP
Semantic Technology for Provider-Payer-Pharma Cross-Industry Data Collaboration
Building Intelligent Health Data Integration
The cost to cover the typical family of four under an employer health insurance plan is expected to top
$20,000 this year. The integration of health data (including electronic health records, health insurer records, pharma research and clinical data, and real-world evidence) will increase transparency and efficiency, improve individual and population health outcomes, and expand the ability to study and improve quality of care.
Traditional approaches to data integration and analytics depend on widely understood data and well-defined use cases for analyzing that data. The integration of pharma, provider, payer, and real-world data will identify new ways in which health data can be combined and analyzed to improve quality of care. Semantic technology can speed integration of health data, while supporting an evolutionary approach to developing and leveraging expertise.
An overview of the i2b2 clinical research platform, and the implications of connecting Indivo to i2b2 as a source of patient-reported outcomes. Presented at the 2012 Indivo X Users' Conference.
By Shawn Murphy MD, Ph.D., Partners Healthcare.
SNOMED CT and other healthcare terminology standards: competition or cooperat...THL
SNOMED CT and other healthcare terminology standards: competition or cooperation? SNOMED CT in relation to LOINC, ICD, ICPC and other terminologies.
Robert Hausam, Hausam Consulting LLC
SNOMED CT 2019 -seminaari (29.3.2019
Presented at Cambridge Semantic Web Monthly Meetup on September 8, 2015
http://www.meetup.com/The-Cambridge-Semantic-Web-Meetup-Group/events/223161012/
Next generation electronic medical records and search a test implementation i...lucenerevolution
Presented by David Piraino, Chief Imaging Information Officer, Imaging Institute Cleveland Clinic, Cleveland Clinic
& Daniel Palmer, Chief Imaging Information Officer, Imaging Institute Cleveland Clinic, Cleveland Clinic
Most patient specifc medical information is document oriented with varying amounts of associated meta-data. Most of pateint medical information is textual and semi-structured. Electronic Medical Record Systems (EMR) are not optimized to present the textual information to users in the most understandable ways. Present EMRs show information to the user in a reverse time oriented patient specific manner only. This talk discribes the construction and use of Solr search technologies to provide relevant historical information at the point of care while intepreting radiology images.
Radiology reports over a 4 year period were extracted from our Radiology Information System (RIS) and passed through a text processing engine to extract the results, impression, exam description, location, history, and date. Fifteen cases reported during clinical practice were used as test cases to determine if ""similar"" historical cases were found . The results were evaluated by the number of searches that returned any result in less than 3 seconds and the number of cases that illustrated the questioned diagnosis in the top 10 results returned as determined by a bone and joint radiologist. Also methods to better optimize the search results were reviewed.
An average of 7.8 out of the 10 highest rated reports showed a similar case highly related to the present case. The best search showed 10 out of 10 cases that were good examples and the lowest match search showed 2 out of 10 cases that were good examples.The talk will highlight this specific use case and the issues and advances of using Solr search technology in medicine with focus on point of care applications.
NVBDCP.pptx Nation vector borne disease control programSapna Thakur
NVBDCP was launched in 2003-2004 . Vector-Borne Disease: Disease that results from an infection transmitted to humans and other animals by blood-feeding arthropods, such as mosquitoes, ticks, and fleas. Examples of vector-borne diseases include Dengue fever, West Nile Virus, Lyme disease, and malaria.
Ethanol (CH3CH2OH), or beverage alcohol, is a two-carbon alcohol
that is rapidly distributed in the body and brain. Ethanol alters many
neurochemical systems and has rewarding and addictive properties. It
is the oldest recreational drug and likely contributes to more morbidity,
mortality, and public health costs than all illicit drugs combined. The
5th edition of the Diagnostic and Statistical Manual of Mental Disorders
(DSM-5) integrates alcohol abuse and alcohol dependence into a single
disorder called alcohol use disorder (AUD), with mild, moderate,
and severe subclassifications (American Psychiatric Association, 2013).
In the DSM-5, all types of substance abuse and dependence have been
combined into a single substance use disorder (SUD) on a continuum
from mild to severe. A diagnosis of AUD requires that at least two of
the 11 DSM-5 behaviors be present within a 12-month period (mild
AUD: 2–3 criteria; moderate AUD: 4–5 criteria; severe AUD: 6–11 criteria).
The four main behavioral effects of AUD are impaired control over
drinking, negative social consequences, risky use, and altered physiological
effects (tolerance, withdrawal). This chapter presents an overview
of the prevalence and harmful consequences of AUD in the U.S.,
the systemic nature of the disease, neurocircuitry and stages of AUD,
comorbidities, fetal alcohol spectrum disorders, genetic risk factors, and
pharmacotherapies for AUD.
More Related Content
Similar to CDISC - Healthcare, meet the Semantic Web
Health care wants Linked Data, a semantic web of taxonomies and patient information that empowers patients, doctors and researchers. Hoot72, a straightforward way to break into the silo's of today, is a key step to get there.
Hoot72 throws light on a health-care facility's care-process. It transfers clinical data into the Semantic Web from HL7 messages being exchanged by Health-care applications.
Throw the Semantic Web at Today's Health-carehoot72
Health-care needs functioning IT - and there is finance available. Yet still, it lumbers along, mired in the same talking points: we need Portable Health Records; we need to exchange clinical care information; we need fuller descriptions. Is the Semantic Web the answer? Can it get to work right now?
WEBINAR: The Yosemite Project PART 6 -- Data-Driven Biomedical Research with ...DATAVERSITY
In this presentation, our speaker, Dr. Michel Dumontier, will explore the use of Semantic Web technologies to reduce the overwhelming burden of integrating clinical data with public biomedical data, and enabling a new generation of translational research and their clinical application.
DISTANT-CTO: A Zero Cost, Distantly Supervised Approach to Improve Low-Resour...Anjani Dhrangadhariya
PICO recognition is an information extraction task for identifying participant, intervention, comparator, and outcome information from clinical literature.
Manually identifying PICO information is the most time-consuming step for conducting systematic reviews (SR) which is already a labor-intensive process.
A lack of diversified and large, annotated corpora restricts innovation and adoption of automated PICO recognition systems.
The largest-available PICO entity/span corpus is manually annotated which is too expensive for a majority of the scientific community.
To break through the bottleneck, we propose DISTANT-CTO, a novel distantly supervised PICO entity extraction approach using the clinical trials literature, to generate a massive weakly-labeled dataset with more than a million ``Intervention'' and ``Comparator'' entity annotations.
We train distant NER (named-entity recognition) models using this weakly-labeled dataset and demonstrate that it outperforms even the sophisticated models trained on the manually annotated dataset with a 2\% F1 improvement over the Intervention entity of the PICO benchmark and more than 5\% improvement when combined with the manually annotated dataset.
We investigate the generalizability of our approach and gain an impressive F1 score on another domain-specific PICO benchmark.
The approach is not only zero-cost but is also scalable for a constant stream of PICO entity annotations.
Semantic Technology for Provider-Payer-Pharma Data CollaborationThomas Kelly, PMP
Semantic Technology for Provider-Payer-Pharma Cross-Industry Data Collaboration
Building Intelligent Health Data Integration
The cost to cover the typical family of four under an employer health insurance plan is expected to top
$20,000 this year. The integration of health data (including electronic health records, health insurer records, pharma research and clinical data, and real-world evidence) will increase transparency and efficiency, improve individual and population health outcomes, and expand the ability to study and improve quality of care.
Traditional approaches to data integration and analytics depend on widely understood data and well-defined use cases for analyzing that data. The integration of pharma, provider, payer, and real-world data will identify new ways in which health data can be combined and analyzed to improve quality of care. Semantic technology can speed integration of health data, while supporting an evolutionary approach to developing and leveraging expertise.
An overview of the i2b2 clinical research platform, and the implications of connecting Indivo to i2b2 as a source of patient-reported outcomes. Presented at the 2012 Indivo X Users' Conference.
By Shawn Murphy MD, Ph.D., Partners Healthcare.
SNOMED CT and other healthcare terminology standards: competition or cooperat...THL
SNOMED CT and other healthcare terminology standards: competition or cooperation? SNOMED CT in relation to LOINC, ICD, ICPC and other terminologies.
Robert Hausam, Hausam Consulting LLC
SNOMED CT 2019 -seminaari (29.3.2019
Presented at Cambridge Semantic Web Monthly Meetup on September 8, 2015
http://www.meetup.com/The-Cambridge-Semantic-Web-Meetup-Group/events/223161012/
Next generation electronic medical records and search a test implementation i...lucenerevolution
Presented by David Piraino, Chief Imaging Information Officer, Imaging Institute Cleveland Clinic, Cleveland Clinic
& Daniel Palmer, Chief Imaging Information Officer, Imaging Institute Cleveland Clinic, Cleveland Clinic
Most patient specifc medical information is document oriented with varying amounts of associated meta-data. Most of pateint medical information is textual and semi-structured. Electronic Medical Record Systems (EMR) are not optimized to present the textual information to users in the most understandable ways. Present EMRs show information to the user in a reverse time oriented patient specific manner only. This talk discribes the construction and use of Solr search technologies to provide relevant historical information at the point of care while intepreting radiology images.
Radiology reports over a 4 year period were extracted from our Radiology Information System (RIS) and passed through a text processing engine to extract the results, impression, exam description, location, history, and date. Fifteen cases reported during clinical practice were used as test cases to determine if ""similar"" historical cases were found . The results were evaluated by the number of searches that returned any result in less than 3 seconds and the number of cases that illustrated the questioned diagnosis in the top 10 results returned as determined by a bone and joint radiologist. Also methods to better optimize the search results were reviewed.
An average of 7.8 out of the 10 highest rated reports showed a similar case highly related to the present case. The best search showed 10 out of 10 cases that were good examples and the lowest match search showed 2 out of 10 cases that were good examples.The talk will highlight this specific use case and the issues and advances of using Solr search technology in medicine with focus on point of care applications.
NVBDCP.pptx Nation vector borne disease control programSapna Thakur
NVBDCP was launched in 2003-2004 . Vector-Borne Disease: Disease that results from an infection transmitted to humans and other animals by blood-feeding arthropods, such as mosquitoes, ticks, and fleas. Examples of vector-borne diseases include Dengue fever, West Nile Virus, Lyme disease, and malaria.
Ethanol (CH3CH2OH), or beverage alcohol, is a two-carbon alcohol
that is rapidly distributed in the body and brain. Ethanol alters many
neurochemical systems and has rewarding and addictive properties. It
is the oldest recreational drug and likely contributes to more morbidity,
mortality, and public health costs than all illicit drugs combined. The
5th edition of the Diagnostic and Statistical Manual of Mental Disorders
(DSM-5) integrates alcohol abuse and alcohol dependence into a single
disorder called alcohol use disorder (AUD), with mild, moderate,
and severe subclassifications (American Psychiatric Association, 2013).
In the DSM-5, all types of substance abuse and dependence have been
combined into a single substance use disorder (SUD) on a continuum
from mild to severe. A diagnosis of AUD requires that at least two of
the 11 DSM-5 behaviors be present within a 12-month period (mild
AUD: 2–3 criteria; moderate AUD: 4–5 criteria; severe AUD: 6–11 criteria).
The four main behavioral effects of AUD are impaired control over
drinking, negative social consequences, risky use, and altered physiological
effects (tolerance, withdrawal). This chapter presents an overview
of the prevalence and harmful consequences of AUD in the U.S.,
the systemic nature of the disease, neurocircuitry and stages of AUD,
comorbidities, fetal alcohol spectrum disorders, genetic risk factors, and
pharmacotherapies for AUD.
Tom Selleck Health: A Comprehensive Look at the Iconic Actor’s Wellness Journeygreendigital
Tom Selleck, an enduring figure in Hollywood. has captivated audiences for decades with his rugged charm, iconic moustache. and memorable roles in television and film. From his breakout role as Thomas Magnum in Magnum P.I. to his current portrayal of Frank Reagan in Blue Bloods. Selleck's career has spanned over 50 years. But beyond his professional achievements. fans have often been curious about Tom Selleck Health. especially as he has aged in the public eye.
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Introduction
Many have been interested in Tom Selleck health. not only because of his enduring presence on screen but also because of the challenges. and lifestyle choices he has faced and made over the years. This article delves into the various aspects of Tom Selleck health. exploring his fitness regimen, diet, mental health. and the challenges he has encountered as he ages. We'll look at how he maintains his well-being. the health issues he has faced, and his approach to ageing .
Early Life and Career
Childhood and Athletic Beginnings
Tom Selleck was born on January 29, 1945, in Detroit, Michigan, and grew up in Sherman Oaks, California. From an early age, he was involved in sports, particularly basketball. which played a significant role in his physical development. His athletic pursuits continued into college. where he attended the University of Southern California (USC) on a basketball scholarship. This early involvement in sports laid a strong foundation for his physical health and disciplined lifestyle.
Transition to Acting
Selleck's transition from an athlete to an actor came with its physical demands. His first significant role in "Magnum P.I." required him to perform various stunts and maintain a fit appearance. This role, which he played from 1980 to 1988. necessitated a rigorous fitness routine to meet the show's demands. setting the stage for his long-term commitment to health and wellness.
Fitness Regimen
Workout Routine
Tom Selleck health and fitness regimen has evolved. adapting to his changing roles and age. During his "Magnum, P.I." days. Selleck's workouts were intense and focused on building and maintaining muscle mass. His routine included weightlifting, cardiovascular exercises. and specific training for the stunts he performed on the show.
Selleck adjusted his fitness routine as he aged to suit his body's needs. Today, his workouts focus on maintaining flexibility, strength, and cardiovascular health. He incorporates low-impact exercises such as swimming, walking, and light weightlifting. This balanced approach helps him stay fit without putting undue strain on his joints and muscles.
Importance of Flexibility and Mobility
In recent years, Selleck has emphasized the importance of flexibility and mobility in his fitness regimen. Understanding the natural decline in muscle mass and joint flexibility with age. he includes stretching and yoga in his routine. These practices help prevent injuries, improve posture, and maintain mobilit
micro teaching on communication m.sc nursing.pdfAnurag Sharma
Microteaching is a unique model of practice teaching. It is a viable instrument for the. desired change in the teaching behavior or the behavior potential which, in specified types of real. classroom situations, tends to facilitate the achievement of specified types of objectives.
New Drug Discovery and Development .....NEHA GUPTA
The "New Drug Discovery and Development" process involves the identification, design, testing, and manufacturing of novel pharmaceutical compounds with the aim of introducing new and improved treatments for various medical conditions. This comprehensive endeavor encompasses various stages, including target identification, preclinical studies, clinical trials, regulatory approval, and post-market surveillance. It involves multidisciplinary collaboration among scientists, researchers, clinicians, regulatory experts, and pharmaceutical companies to bring innovative therapies to market and address unmet medical needs.
The prostate is an exocrine gland of the male mammalian reproductive system
It is a walnut-sized gland that forms part of the male reproductive system and is located in front of the rectum and just below the urinary bladder
Function is to store and secrete a clear, slightly alkaline fluid that constitutes 10-30% of the volume of the seminal fluid that along with the spermatozoa, constitutes semen
A healthy human prostate measures (4cm-vertical, by 3cm-horizontal, 2cm ant-post ).
It surrounds the urethra just below the urinary bladder. It has anterior, median, posterior and two lateral lobes
It’s work is regulated by androgens which are responsible for male sex characteristics
Generalised disease of the prostate due to hormonal derangement which leads to non malignant enlargement of the gland (increase in the number of epithelial cells and stromal tissue)to cause compression of the urethra leading to symptoms (LUTS
New Directions in Targeted Therapeutic Approaches for Older Adults With Mantl...i3 Health
i3 Health is pleased to make the speaker slides from this activity available for use as a non-accredited self-study or teaching resource.
This slide deck presented by Dr. Kami Maddocks, Professor-Clinical in the Division of Hematology and
Associate Division Director for Ambulatory Operations
The Ohio State University Comprehensive Cancer Center, will provide insight into new directions in targeted therapeutic approaches for older adults with mantle cell lymphoma.
STATEMENT OF NEED
Mantle cell lymphoma (MCL) is a rare, aggressive B-cell non-Hodgkin lymphoma (NHL) accounting for 5% to 7% of all lymphomas. Its prognosis ranges from indolent disease that does not require treatment for years to very aggressive disease, which is associated with poor survival (Silkenstedt et al, 2021). Typically, MCL is diagnosed at advanced stage and in older patients who cannot tolerate intensive therapy (NCCN, 2022). Although recent advances have slightly increased remission rates, recurrence and relapse remain very common, leading to a median overall survival between 3 and 6 years (LLS, 2021). Though there are several effective options, progress is still needed towards establishing an accepted frontline approach for MCL (Castellino et al, 2022). Treatment selection and management of MCL are complicated by the heterogeneity of prognosis, advanced age and comorbidities of patients, and lack of an established standard approach for treatment, making it vital that clinicians be familiar with the latest research and advances in this area. In this activity chaired by Michael Wang, MD, Professor in the Department of Lymphoma & Myeloma at MD Anderson Cancer Center, expert faculty will discuss prognostic factors informing treatment, the promising results of recent trials in new therapeutic approaches, and the implications of treatment resistance in therapeutic selection for MCL.
Target Audience
Hematology/oncology fellows, attending faculty, and other health care professionals involved in the treatment of patients with mantle cell lymphoma (MCL).
Learning Objectives
1.) Identify clinical and biological prognostic factors that can guide treatment decision making for older adults with MCL
2.) Evaluate emerging data on targeted therapeutic approaches for treatment-naive and relapsed/refractory MCL and their applicability to older adults
3.) Assess mechanisms of resistance to targeted therapies for MCL and their implications for treatment selection
Recomendações da OMS sobre cuidados maternos e neonatais para uma experiência pós-natal positiva.
Em consonância com os ODS – Objetivos do Desenvolvimento Sustentável e a Estratégia Global para a Saúde das Mulheres, Crianças e Adolescentes, e aplicando uma abordagem baseada nos direitos humanos, os esforços de cuidados pós-natais devem expandir-se para além da cobertura e da simples sobrevivência, de modo a incluir cuidados de qualidade.
Estas diretrizes visam melhorar a qualidade dos cuidados pós-natais essenciais e de rotina prestados às mulheres e aos recém-nascidos, com o objetivo final de melhorar a saúde e o bem-estar materno e neonatal.
Uma “experiência pós-natal positiva” é um resultado importante para todas as mulheres que dão à luz e para os seus recém-nascidos, estabelecendo as bases para a melhoria da saúde e do bem-estar a curto e longo prazo. Uma experiência pós-natal positiva é definida como aquela em que as mulheres, pessoas que gestam, os recém-nascidos, os casais, os pais, os cuidadores e as famílias recebem informação consistente, garantia e apoio de profissionais de saúde motivados; e onde um sistema de saúde flexível e com recursos reconheça as necessidades das mulheres e dos bebês e respeite o seu contexto cultural.
Estas diretrizes consolidadas apresentam algumas recomendações novas e já bem fundamentadas sobre cuidados pós-natais de rotina para mulheres e neonatos que recebem cuidados no pós-parto em unidades de saúde ou na comunidade, independentemente dos recursos disponíveis.
É fornecido um conjunto abrangente de recomendações para cuidados durante o período puerperal, com ênfase nos cuidados essenciais que todas as mulheres e recém-nascidos devem receber, e com a devida atenção à qualidade dos cuidados; isto é, a entrega e a experiência do cuidado recebido. Estas diretrizes atualizam e ampliam as recomendações da OMS de 2014 sobre cuidados pós-natais da mãe e do recém-nascido e complementam as atuais diretrizes da OMS sobre a gestão de complicações pós-natais.
O estabelecimento da amamentação e o manejo das principais intercorrências é contemplada.
Recomendamos muito.
Vamos discutir essas recomendações no nosso curso de pós-graduação em Aleitamento no Instituto Ciclos.
Esta publicação só está disponível em inglês até o momento.
Prof. Marcus Renato de Carvalho
www.agostodourado.com
Lung Cancer: Artificial Intelligence, Synergetics, Complex System Analysis, S...Oleg Kshivets
RESULTS: Overall life span (LS) was 2252.1±1742.5 days and cumulative 5-year survival (5YS) reached 73.2%, 10 years – 64.8%, 20 years – 42.5%. 513 LCP lived more than 5 years (LS=3124.6±1525.6 days), 148 LCP – more than 10 years (LS=5054.4±1504.1 days).199 LCP died because of LC (LS=562.7±374.5 days). 5YS of LCP after bi/lobectomies was significantly superior in comparison with LCP after pneumonectomies (78.1% vs.63.7%, P=0.00001 by log-rank test). AT significantly improved 5YS (66.3% vs. 34.8%) (P=0.00000 by log-rank test) only for LCP with N1-2. Cox modeling displayed that 5YS of LCP significantly depended on: phase transition (PT) early-invasive LC in terms of synergetics, PT N0—N12, cell ratio factors (ratio between cancer cells- CC and blood cells subpopulations), G1-3, histology, glucose, AT, blood cell circuit, prothrombin index, heparin tolerance, recalcification time (P=0.000-0.038). Neural networks, genetic algorithm selection and bootstrap simulation revealed relationships between 5YS and PT early-invasive LC (rank=1), PT N0—N12 (rank=2), thrombocytes/CC (3), erythrocytes/CC (4), eosinophils/CC (5), healthy cells/CC (6), lymphocytes/CC (7), segmented neutrophils/CC (8), stick neutrophils/CC (9), monocytes/CC (10); leucocytes/CC (11). Correct prediction of 5YS was 100% by neural networks computing (area under ROC curve=1.0; error=0.0).
CONCLUSIONS: 5YS of LCP after radical procedures significantly depended on: 1) PT early-invasive cancer; 2) PT N0--N12; 3) cell ratio factors; 4) blood cell circuit; 5) biochemical factors; 6) hemostasis system; 7) AT; 8) LC characteristics; 9) LC cell dynamics; 10) surgery type: lobectomy/pneumonectomy; 11) anthropometric data. Optimal diagnosis and treatment strategies for LC are: 1) screening and early detection of LC; 2) availability of experienced thoracic surgeons because of complexity of radical procedures; 3) aggressive en block surgery and adequate lymph node dissection for completeness; 4) precise prediction; 5) adjuvant chemoimmunoradiotherapy for LCP with unfavorable prognosis.
Pulmonary Thromboembolism - etilogy, types, medical- Surgical and nursing man...VarunMahajani
Disruption of blood supply to lung alveoli due to blockage of one or more pulmonary blood vessels is called as Pulmonary thromboembolism. In this presentation we will discuss its causes, types and its management in depth.
2. Hoot72.org
• “Demonstrate the power the
Semantic Web brings to Health-Care
and how easy it is to deploy today.”
• Incubate: open source, docs
• Not Green Field - 40+ years of
Health IT
3. : Just Another Format?
• Technology: Web Stack++
• Reuse: HTTP, URIs, not HTML
• + RDF, OWL, SPARQL
• Get Link docs -> Query Link data
• One more reuse: Link ANYWHERE
• Begone CD-ROM: no islands
• WW: new adds on, reuse, open
4. A Linkable Patient
type
Patient
about
personName
observation observationValue
familyName
givenName Doe
CodingSystem Code
middleName
Code CodingSystem
John Fitzgerald
LN 30949-2 005 NIP
Identifiers and Time not shown
URI: http://www.facilityx.com/cdrs/112123449
5. Now Just Ask ...
All Patients with adverse outcome from
vaccine ...
SELECT DISTINCT ?givenName ?familyName
WHERE {
?patient hoot72:personName
[ hoot72:givenName ?givenName ;
hoot72:familyName ?familyName ] .
[ hoot72:about ?patient ;
?assert [ hoot72:nameOfCodingSystem "LN" ;
hoot72:simpleIdentifier "30949-2" ] ]
}
6. Move out and up
• Question: Patients taking “Weight Loss Drugs”
• Patient Web: very particular
• Patient drugs as NDC codes: DESOXYN
TABLETS (00074337701) ...
• Too big a gap?
7. Ontologies Link!
Obese StanDrug: C0025611 Methamphetamine
May Treat
Name Name
SameAs
Stanford Drug
Ontology Methamphetamine RxNorm:6816
Ingredient
NDC: 00074337701
Patient Joe
SameAs
Hoot72 Name
Patient Medication
Graph Desoxyn 5MG Tablet
NDC: 00074337701
RxNorm
* Dotted: composite of links to save space
** w3c HCLS Example
8. The Ontologies?
• “an implementable model of the entities that need
to be understood in common in order for some
group of software systems and their users to
function and communicate at the level required for
a set of tasks” -- Alan Rector
• “Shared Knowledge” for Machines
• Links, hierarchies, equivalence ...
• The “middleware” of the Semantic Web
• OWL (WOL) - Web Ontology Language
10. Not just “Standards”
SameAs
CodingSystem CodingSystem Code
Text
Code
Local 182253 MRSA Culture LN 13317-3
Local Code LOINC Code
• Enable standard, off-the-shelf queries
• Definition is incremental
11. CDISC: it’s the content
• Roadmap: “The separation of content
standards from the means of
transporting that content”
• Terms: to OWL and Endpoints
• “BRIDGing” in OWL
• Trials as querable Graphs (vs docs)
12. Many Users, Contributors
Patient Researcher
Linked Health Data
Doctor Informatics
Insurance Manager
One Semantic Web for Health-Care
13. But ... “Patient Gap”
• “Trapped”, “Silo’ed”
• Ontologies Left Waiting
• EMRs Hold Back
15. Enabler: the Silo’s chat
“HL7 version 2 is a major
breakthrough and market 2.2
success. More than 93% 2.1
3.0 2.3
hospitals in US are using this 2.5
2.4
standard” - Health Level
Horizon (HLH) Project
2.3.1
2.1 2.2 2.3 2.3.1 2.4
2.5 3.0
Source: Neotool, V3 vs V2
16. HL7 “tweet” ...
MSH|^~&|REGADT|MCM|IFENG||199112311501||ADT^A04^ADT_A01|000001|P|2.4|||
EVN|A04|199901101500|199901101400|01||199901101410
PID|||191919^^GENHOS^MR~371-66-9256^^^USSSA^SS|253763|MASSIE^JAMES^A||
19560129|M|||171 ZOBERLEIN^^ISHPEMING^MI^49849^""^||(900)485-5344|
(900)485-5344||S^^HL70002|C^^HL70006|10199925^^^GENHOS^AN|371-66-9256||
NK1|1|MASSIE^ELLEN|SPOUSE^^HL70063|171
ZOBERLEIN^^ISHPEMING^MI^49849^""^
|(900)485-5344|(900)545-1234~(900)545-1200|EC1^FIRST EMERGENCY
CONTACT^HL70131
NK1|2|MASSIE^MARYLOU|MOTHER^^HL70063|300
ZOBERLEIN^^ISHPEMING^MI^49849^""^
|(900)485-5344|(900)545-1234~(900)545-1200|EC2^SECOND EMERGENCY
CONTACT^HL70131
NK1|3
NK1|4|||123 INDUSTRY WAY^^ISHPEMING^MI^49849^""^||(900)545-1200|
EM^EMPLOYER^HL70131|19940605||PROGRAMMER|||ACME SOFTWARE COMPANY
PV1||O|O/R||||0148^ADDISON,JAMES|0148^ADDISON,JAMES||AMB|||||||
0148^ADDISON,JAMES|S|1400|A|||||||||||||||||||GENHOS|||||199501101410|
PV2||||||||199901101400|||||||||||||||||||||||||199901101400
ROL||AD|CP^^HL70443|0148^ADDISON,JAMES
OBX||NM|3141-9^BODY WEIGHT^LN||62|kg|||||F
James was admitted ... his wife is his emergency contact ... hereʼs his weight ...
18. Observation
PID|||1234^^^^SR~1234-12^^^^LR~00725^^^^MR||Doe^John^Fitzgerald^JR^^^L|
...
OBX|4|CE|30949-2^Vaccination adverse event outcome^LN|1|005^required
hospitalization^NIP|
type
Patient
about
personName
observation observationValue
familyName
givenName Doe
CodingSystem Code
middleName
Code CodingSystem
John Fitzgerald
LN 30949-2 005 NIP Identifiers and Time not shown
20. Which Represents ...
CDR/S EMR
Research HL7...
URL
SPARQL
Personal
Ontology
Report Represent Produce
21. Reality: from Vets
• Concrete EMR - VistA
• VA: Largest U.S. Care Provider
• 128 VistAs, federated, 14+ Million in MPI - ICNs
• Available under FOIA
• The Proof
• Mapper Subscribes for HL7 (30/120 packs)
• Maintains a CDR/S for VistA (1 or more)
25. Every EMR, an EndPoint
• EMR links to the cloud, natively
• Mini-Austin: MPI only (old VA Approach)
• Lucky: MUMPS repositories
• Network-Format ala Semantic Web
• VistA’s FileMan (no scale to test)
• If only you could SPARQL them ...
26. FMQL: SPARQL-like
SELECT ?name ?diagnosis ?age ?history FILE
"PATIENT" WHERE {?r "NAME" ?name ;
"DIAGNOSIS" ?d . ?d "DIAGNOSIS" ?diagnosis ;
"AGE AT ONSET" ?age ; "HISTORY" ?history }
• Specification in progress
• Initial goal: limited Patient, meta data dumps
27. Summary
• Semantic Web growing in Health-Care
• But a “Patient Gap”
• Different ways to bridge
• CDISC can drive it forward
• More: http://www.hoot72.org
Editor's Notes
There are green field demos already
Like “goodness”
NOT HTML ... Querying like DB querying, not page fetching
FORM-CONCEPT-QUERY
run thru on baltimore becomes linkable data about baltimore
web didn’t make hyperlinks or protocols or page layout
SEM WEB: ONE MORE WEB THING ... the power, the scale was link anywhere
Nodes and Literals ... Codes would break down
SIMPLE ENCOUNTER
Detailed discussion of semi-structured (not going to get into this aspect)
Observable (OBX|4|CE|30949-2^Vaccination adverse event outcome^LN|1|005^required hospitalization^NIP|)
NIP= National Immunization Program within the Center for Disease Control
ala DATABASE, SEEMS TRIVIAL
One standard code is 30949-2.
For the astute: better if code became URI.
Beyond an isolated set of patients
FOLLOW THE LINKS: Typical Report: chase type (Ontology) in a world of (EMR) particulars. Stanford Drug Ontology gives compounds that treat conditions. RxNorm relates compounds to branded drugs. Hoot72 Clinical Data has branded drugs.
From: HCLS == the w3c Health Care and Life Sciences Interest Group
Patient Data is secure - “intranet” LINK OUT
RxNorm not yet an ontology but has web api so can represent it as a SPARQL end point
Simplied to fit. Ingredient = consists of to ingredient to brand name etc.
Ala Semantic Web: pretty loose definitions. Philosophy.
Dumb AI
from obese to desoxyn ... we need entities
Middleware - format gets out of the way. IT gets out of the reformatting business.
NOT CLASS HIER.
Growing in number ... Billions of triples, ready to be leveraged, all these URIs.
Gen purpose (demographics) and PubMed, Drug Bank, GeneID, Diseasome
Arrows representing linking out to another conceptual scheme
1. STANFORD and BIO-MED guys big ...
2. ONTOLOGY == “TYPE” vs “THING” ... TYPE AND THING
CDASH ODM (machine readable)
CDISC SDTM and other terminology goes through an extensive process of definition, development, and review before it is declared ready for release. Terminology that has completed this process is tagged as "Production," and now includes some 50 SDTM codelists with about 2,200 terms covering demographics, interventions, findings, events, trial design, units, frequency, and ECG terminology. This terminology is maintained and distributed as part of NCI Thesaurus
CDC Example.
We will have standard and local ontologies, standard and local queries
there may be several different ways to express the same concept. Human users may be able to recognise that these are essentially the same, but the rules for doing so must be made explicit to be usable by computer. -- Why is Terminology hard?, Alan Rector
ME to learn of CDISC work. See how to leverage all the work.
CONTENT KING
FDA: “Improve Interoperability: The Target EA establishes enterprise-wide standards that promote platform and vendor independence, enabling greater interoperability across disparate applications, both internal and external”
DOCUMENT model vs GRAPH model
Trial == Snapshot. Extrapolated from individual observations (weight gain etc)
... Here at the Drug Information Association (DIA), you can see a “live” implementation of the interoperability that is possible between Electronic Health Record (EHR) systems and Electronic Data Capture (EDC) systems used for clinical research, which leverages the Integrating the Healthcare Enterprise’s (IHE) Retrieve Form for Data Capture (RFD) integration profile along with CDISC’s ODM and CDASH standards
Contrast to RDIF XFORMs.
ALL ROSY - CONCEPT and PATICULAR, TYPE and THING
The big picture ... Concept and Concrete, Users and Contributors in one web
Trial Recruitment, Drug Safety, Outcomes research
HL7 holds our health data
HL7 everywhere means v2. Small V3.
Of course, more structured than your average tweet
Pick out message type, patient name, contact relationship, body weight observation
SO MANY CODES IN HEALTHCARE
Unload the Truck
What we've done
Key is automatic i.e. requirement
Mapping is on the site.
Moving beyond rough logs.
STILL TOO ACADEMIC
But don't just want a script EMR
Get Real
The Integration Control Number (ICN) - ASTM e1714-95 standard for a universal health identifier.
Like the efforts in the showcase to interop EMRs
Already done for us - or at least we know it works
Note Multiple VistAs
HL7 is triggered. Data there and WHEN it is there.
GE TOO - FLU TO CDC
open use docs first
DO SEGWAY
MUMPS (Massachusetts General Hospital Utility Multi-Programming System)
EMR NOT LEFT OUT OF THE PICTURE, not just a “old” aside.
Looking in the code, you could see ...