The document discusses electronic source data (ESD) and the Retrieve Form for Data Capture (RFD) profile. It provides an overview of the RFD profile, which allows clinical data stored in electronic health records to be retrieved and used in clinical trials, registries, biosurveillance and other systems using open standards. Several scenarios are described where RFD could be used, such as a physician discovering an adverse drug event and summoning a form from the drug manufacturer to report it. The presentation demonstrates how RFD enables clinical data to be reused across different systems without re-entry.
CDISC is a non-profit standards development organization that aims to develop data standards for clinical research to enable data sharing and interoperability. It has developed several standards including SDTM for submission data, ODM for data exchange, and Define.xml for metadata. The standards are used by clinical research organizations, sponsors, investigators, and regulators to facilitate communication and archive of clinical data. CDISC is working on additional standards and initiatives to further its mission of improving medical research and healthcare through data standardization.
eSource, DIA EuroMeeting, Lisbon, March 2005AsseroLtd
The eSDI Group was formed to address issues with collecting and using electronic patient-reported outcomes data in clinical trials. The group has been meeting regularly and developing a draft white paper. Key areas of focus include interim analysis, psychometric and system validation, and moving towards electronic data collection while maintaining regulatory compliance. Next steps include further revising the white paper and soliciting broader feedback to help provide guidance on electronic patient-reported outcomes.
Artificial intelligence (AI) is everywhere, promising self-driving cars, medical breakthroughs, and new ways of working. But how do you separate hype from reality? How can your company apply AI to solve real business problems?
Here’s what AI learnings your business should keep in mind for 2017.
Study: The Future of VR, AR and Self-Driving CarsLinkedIn
We asked LinkedIn members worldwide about their levels of interest in the latest wave of technology: whether they’re using wearables, and whether they intend to buy self-driving cars and VR headsets as they become available. We asked them too about their attitudes to technology and to the growing role of Artificial Intelligence (AI) in the devices that they use. The answers were fascinating – and in many cases, surprising.
This SlideShare explores the full results of this study, including detailed market-by-market breakdowns of intention levels for each technology – and how attitudes change with age, location and seniority level. If you’re marketing a tech brand – or planning to use VR and wearables to reach a professional audience – then these are insights you won’t want to miss.
The document provides an overview of how integrated RIS/PACS systems can streamline radiology workflows and improve patient care. It features case studies of three healthcare organizations that implemented GE Healthcare's Centricity RIS-IC solution:
1) Cooper University Hospital in Camden, NJ saw productivity gains of 10-20% for radiologists and reduced radiology workflow from over 50 steps to under 10 steps. Physicians also experienced improved collaboration and faster report turnaround.
2) Radiology and Imaging Specialists in Lakeland, FL, a large radiology practice, used RIS-driven workflow to simplify operations across multiple hospitals and imaging centers.
3) United Memorial Medical Center in Batavia,
HIMSS National Data Warehousing WebinarDale Sanders
BMJ and other sources
• Integrated into Cerner EMR
• Action sets, order sets, reference
• Chronic condition management
• Population health monitoring
• Local quality improvement
• Data analytics and reporting
• Continuous improvement
• Outcomes and process measures
• Cost and utilization measures
• Staff education and training
• Governance and oversight
• Continuous refinement
• Continuous expansion of content
• Continuous expansion of use
• Continuous expansion of benefits
• Continuous expansion of users
• Continuous expansion of evidence
• Continuous expansion of data
• Continuous expansion of analytics
• Continuous expansion of improvement
• Continuous
In light of Cloud Computing System CDA Generation and Integration for Health ...IJAEMSJORNAL
Theoretical Successful sending of Electronic Health Record enhances tolerant security and nature of care, however it has the essential of interoperability between Health Information Exchange at various doctor's facilities. The Clinical Document Architecture (CDA) created by HL7 is a center record standard to guarantee such interoperability, and engendering of this archive configuration is basic for interoperability. Lamentably, clinics are hesitant to receive interoperable HIS because of its organization fetched with the exception of in a modest bunch nations. An issue emerges notwithstanding when more healing facilities begin utilizing the CDA archive arrange on the grounds that the information scattered in various reports are difficult to oversee. In this paper, we portray our CDA report era and incorporation Open API benefit in light of distributed computing, through which doctor's facilities are empowered to advantageously create CDA archives without purchasing restrictive programming. Our CDA archive combination framework incorporates various CDA records per tolerant into a solitary CDA report and doctors and patients can peruse the clinical information in sequential request. Our arrangement of CDA report era and joining depends on distributed computing and the administration is offered in Open API. Engineers utilizing distinctive stages along these lines can utilize our framework to improve interoperability.
CDISC is a non-profit standards development organization that aims to develop data standards for clinical research to enable data sharing and interoperability. It has developed several standards including SDTM for submission data, ODM for data exchange, and Define.xml for metadata. The standards are used by clinical research organizations, sponsors, investigators, and regulators to facilitate communication and archive of clinical data. CDISC is working on additional standards and initiatives to further its mission of improving medical research and healthcare through data standardization.
eSource, DIA EuroMeeting, Lisbon, March 2005AsseroLtd
The eSDI Group was formed to address issues with collecting and using electronic patient-reported outcomes data in clinical trials. The group has been meeting regularly and developing a draft white paper. Key areas of focus include interim analysis, psychometric and system validation, and moving towards electronic data collection while maintaining regulatory compliance. Next steps include further revising the white paper and soliciting broader feedback to help provide guidance on electronic patient-reported outcomes.
Artificial intelligence (AI) is everywhere, promising self-driving cars, medical breakthroughs, and new ways of working. But how do you separate hype from reality? How can your company apply AI to solve real business problems?
Here’s what AI learnings your business should keep in mind for 2017.
Study: The Future of VR, AR and Self-Driving CarsLinkedIn
We asked LinkedIn members worldwide about their levels of interest in the latest wave of technology: whether they’re using wearables, and whether they intend to buy self-driving cars and VR headsets as they become available. We asked them too about their attitudes to technology and to the growing role of Artificial Intelligence (AI) in the devices that they use. The answers were fascinating – and in many cases, surprising.
This SlideShare explores the full results of this study, including detailed market-by-market breakdowns of intention levels for each technology – and how attitudes change with age, location and seniority level. If you’re marketing a tech brand – or planning to use VR and wearables to reach a professional audience – then these are insights you won’t want to miss.
The document provides an overview of how integrated RIS/PACS systems can streamline radiology workflows and improve patient care. It features case studies of three healthcare organizations that implemented GE Healthcare's Centricity RIS-IC solution:
1) Cooper University Hospital in Camden, NJ saw productivity gains of 10-20% for radiologists and reduced radiology workflow from over 50 steps to under 10 steps. Physicians also experienced improved collaboration and faster report turnaround.
2) Radiology and Imaging Specialists in Lakeland, FL, a large radiology practice, used RIS-driven workflow to simplify operations across multiple hospitals and imaging centers.
3) United Memorial Medical Center in Batavia,
HIMSS National Data Warehousing WebinarDale Sanders
BMJ and other sources
• Integrated into Cerner EMR
• Action sets, order sets, reference
• Chronic condition management
• Population health monitoring
• Local quality improvement
• Data analytics and reporting
• Continuous improvement
• Outcomes and process measures
• Cost and utilization measures
• Staff education and training
• Governance and oversight
• Continuous refinement
• Continuous expansion of content
• Continuous expansion of use
• Continuous expansion of benefits
• Continuous expansion of users
• Continuous expansion of evidence
• Continuous expansion of data
• Continuous expansion of analytics
• Continuous expansion of improvement
• Continuous
In light of Cloud Computing System CDA Generation and Integration for Health ...IJAEMSJORNAL
Theoretical Successful sending of Electronic Health Record enhances tolerant security and nature of care, however it has the essential of interoperability between Health Information Exchange at various doctor's facilities. The Clinical Document Architecture (CDA) created by HL7 is a center record standard to guarantee such interoperability, and engendering of this archive configuration is basic for interoperability. Lamentably, clinics are hesitant to receive interoperable HIS because of its organization fetched with the exception of in a modest bunch nations. An issue emerges notwithstanding when more healing facilities begin utilizing the CDA archive arrange on the grounds that the information scattered in various reports are difficult to oversee. In this paper, we portray our CDA report era and incorporation Open API benefit in light of distributed computing, through which doctor's facilities are empowered to advantageously create CDA archives without purchasing restrictive programming. Our CDA archive combination framework incorporates various CDA records per tolerant into a solitary CDA report and doctors and patients can peruse the clinical information in sequential request. Our arrangement of CDA report era and joining depends on distributed computing and the administration is offered in Open API. Engineers utilizing distinctive stages along these lines can utilize our framework to improve interoperability.
Appalla Venkataprabhakar and I presented this at the Oracle\'s Annual Clinical Development and Safety Conference 2010 at Hyderabad, India on 6th October 2010.
Healthcare institutions are aggressively moving towards meeting compliance with MU1 and MU2 with the implementation of full-featured Electronic Health Records. Concomitantly, there will be a massive increase in the amount of clinical data captured electronically. Business intelligence (BI) which traditionally has focused on financial data can be leveraged to use clinical data to support providers in delivering high quality, efficient care. In addition, BI coupled with population health analytics can help meet many Accountable Care Organization needs. This presentation will discuss the Denver Health journey in using BI in a variety of was to facilitate the attainment of high quality care.
The document discusses DTECTM, a service that analyzes healthcare claims data to identify gaps in quality of care for patient populations with cardiovascular diseases. It produces reports that assess baseline performance, identify barriers, target individuals for intervention, and reassess performance. Examples show how DTECTM was used by health plans to measure quality indicators, identify members for programs, and document trends over time. The document suggests DTECTM could help Quality Improvement Organizations and Medicare Part D by leveraging claims data to provide insights into care quality and support clinical decision making.
1. The document discusses integrating electronic health records and clinical research systems using IHE profiles and specifications such as RFD, CRD, and Redaction Services.
2. It proposes using web services and workflow automation to enable EHRs and research systems to directly communicate and exchange information.
3. Key IHE integration profiles and specifications discussed include RFD for retrieving case report forms, CRD for pre-populating forms with patient data from EHRs, and Redaction Services for tailoring the pre-populated data to match protocol requirements.
Selecting Core Clinical It Solutions For Life Sciences Organizations – Key S...Vinoth Kumar T
This document summarizes a presentation on selecting core clinical IT solutions for life sciences organizations. It discusses the challenges life sciences companies face with drug development timelines and costs. Effective clinical data management can help address these challenges by streamlining processes, improving data quality and security, and enabling faster data review and regulatory submissions. When selecting clinical IT solutions, companies should evaluate vendors, ensure regulatory compliance, and consider costs, integration, usability, and ongoing support. A successful implementation requires understanding existing workflows, conducting pilots, addressing security risks, and having open communication channels to resolve problems.
The speaker discusses mapping CDA (Clinical Document Architecture) documents to FHIR (Fast Healthcare Interoperability Resources). CDA was difficult to construct and read, while FHIR provides a more streamlined approach. A joint project maps CDA elements to FHIR specifications and profiles to define the relationship between the standards. The goal is a common syntax and resources that support both documents and APIs, with CDA documents eventually represented in FHIR.
Route from CCDA to FHIR by Grahame GrieveFurore_com
The speaker discusses mapping CDA (Clinical Document Architecture) documents to FHIR (Fast Healthcare Interoperability Resources). CDA was found to be difficult to construct and read, and not well-suited for granular data exchange. FHIR addresses these issues and can be used for both documents and APIs. A project is underway to map CDA elements to FHIR counterparts and define profiles to represent CDA documents in FHIR. This will help with the transition from CDA to FHIR for document exchange.
This document discusses clinical data standards and data integration tools. It provides an overview of leading organizations that develop clinical data standards like CDISC and HL7. It describes the evolution of standards development and FDA's endorsement of CDISC standards. The document reviews CDISC models, global adoption trends, benefits, and barriers to adoption. It defines extract, transform, load (ETL) tools and their importance for future clinical data integration and cross-study analysis. The future of standards is discussed, including increased adoption of CDISC, new therapeutic area standards, integration of different data sources, and the convergence of CDISC and HL7 standards with semantic web technologies.
The document summarizes the major topics in radiology IT that will be covered at the RSNA annual meeting. It discusses initiatives around monitoring patient radiation exposure through initiatives like the IHE-REM profile. It also covers efforts to improve image sharing through standards like IHE XDS for sharing images and reports between institutions. Additional areas covered include decision support, teaching/research tools like MIRC and CTP, and the use of Radlex as an ontology. RSNA's informatics committee and showcase at the annual meeting will provide more details on these initiatives.
1) The document discusses options for trial implementations of health information exchange (HIE) in New Zealand that are aligned with national HIE standards and have the potential to engage health system vendors.
2) Three potential trial options are compared: sharing InterRAI assessments with community pharmacists, sharing hospital discharge summaries with after-hours and emergency health services, and sharing primary care summaries with after-hours and emergency health services.
3) The document seeks feedback on the options from the Ministry of Health and healthAlliance to select trial implementation options and develop project plans.
Presentation on Healthcare Interoperability at AEA, delhi chapter meeting 27t...Kumar Satyam
This document summarizes an upcoming meeting of the Association of Enterprise Architects Delhi Chapter. The meeting agenda includes updates on the chapter and EA field, a presentation by Mr. Kumar Satyam from Philips on healthcare interoperability, feedback/Q&A, and future plans. The chapter aims to advance EA excellence in Delhi/NCR. The healthcare interoperability talk will discuss challenges like standards, data sharing, and regulations, and opportunities like APIs and initiatives like NDHM and IHE profiles.
This document outlines the key components and users of a Public Health Information System (PHI). The system collects data from various sources like food units, epidemiology, and schools. It stores the data in operational databases and a data warehouse. The data is then analyzed and used to support decision making, program planning, and health education. The system allows workload distribution and notification across different administrative levels like the central level, districts, and facilities.
This document discusses how the increased generation of data in pharmaceutical R&D has failed to improve productivity due to an inability to properly organize and apply knowledge. It describes how existing integration strategies store data in isolated "silos" that are difficult to access and compare. The author argues that new semantic technologies based on ontologies can better integrate knowledge across discovery, development, and other business areas to improve transparency, safety monitoring, and decision making.
This document provides definitions and explanations of key terms related to the HealthVault platform:
- HealthVault is a platform that allows applications to connect to securely store and access a user's health information. The main components are the HealthVault applications, shell, and records.
- HealthVault applications can send and access data from a user's HealthVault record. The shell is a special application that allows a user to manage access to their record and see activity logs. Records can contain multiple types of structured and unstructured health data.
- Developers can build and test applications using the pre-production environment before an application goes live on the production platform used by consumers. Additional terms defined include things, vocabularies, and
CER HUB An Informatics Platform for Conducting Compartive Effectiveness with ...HMO Research Network
The document describes the CER Hub, an informatics platform for conducting comparative effectiveness research using electronic medical record data. The CER Hub allows researchers to develop standardized processors to generate research datasets from heterogeneous EMR systems. It facilitates collaborative projects to address questions like evaluating asthma control and smoking cessation treatments. Initial projects through the CER Hub involve developing measures of asthma control and comparing the effectiveness of treatment intensification options using EMR data from six health systems.
1. A clinical data management system (CDMS) is used to manage data from clinical trials by storing data entered in case report forms (CRFs) by investigators.
2. Data management involves planning, collection, entry, validation, manipulation, backup and documentation of data to create a high quality database. Commonly used CDMS tools include Oracle Clinical, ClinTrial, Macro and eClinical Suite.
3. Open source CDMS tools include OpenClinica, openCDMS, TrialDB and PhOSCo which are free. All CDMS tools ensure an audit trail and management of discrepancies according to roles and user access levels.
Clinical data management involves processing clinical trial data through activities like data entry, validation, query resolution and medical coding. It aims to ensure the integrity and quality of clinical trial data, which regulatory agencies rely on for drug approval. The document provides an overview of the clinical data management process and roles involved at each stage, from study set-up to closeout.
Event brochure for the upcoming Clinical Data Standardisation and Managment event in London, June.
The event will feature best practice case studies from CDISC
Webcast: CIO Insights: How to Optimize User Experience Across 60 Hospitals Compuware APM
** If you would like to download a copy of the slides- please email jessica.murphy@compuware.com and she will send the slideset to you via email.**
For health services provider Christus Health, poorly performing applications are never an option. Just as medical equipment cannot fail, the applications supporting Christus Health must operate flawlessly. In order to avoid lost revenue, decreased clinical productivity and increased risk to patients, Christus employs an end-user perspective to application performance management.
Join Christus Health CIO George Conklin in this Compuware webcast to learn:
• What impacts healthcare app performance has on customer experience and business goals
• How Christus IT and the business teams optimize customer experience
• Real-world best practices for improving user experience without slowing down your healthcare processes and procedures
What You Will Learn:
George Conklin, Senior VP and CIO of Christus will share real-world experiences and Christus Heath’s best practice approach for ensuring users in their healthcare system have the best application performance possible.
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Appalla Venkataprabhakar and I presented this at the Oracle\'s Annual Clinical Development and Safety Conference 2010 at Hyderabad, India on 6th October 2010.
Healthcare institutions are aggressively moving towards meeting compliance with MU1 and MU2 with the implementation of full-featured Electronic Health Records. Concomitantly, there will be a massive increase in the amount of clinical data captured electronically. Business intelligence (BI) which traditionally has focused on financial data can be leveraged to use clinical data to support providers in delivering high quality, efficient care. In addition, BI coupled with population health analytics can help meet many Accountable Care Organization needs. This presentation will discuss the Denver Health journey in using BI in a variety of was to facilitate the attainment of high quality care.
The document discusses DTECTM, a service that analyzes healthcare claims data to identify gaps in quality of care for patient populations with cardiovascular diseases. It produces reports that assess baseline performance, identify barriers, target individuals for intervention, and reassess performance. Examples show how DTECTM was used by health plans to measure quality indicators, identify members for programs, and document trends over time. The document suggests DTECTM could help Quality Improvement Organizations and Medicare Part D by leveraging claims data to provide insights into care quality and support clinical decision making.
1. The document discusses integrating electronic health records and clinical research systems using IHE profiles and specifications such as RFD, CRD, and Redaction Services.
2. It proposes using web services and workflow automation to enable EHRs and research systems to directly communicate and exchange information.
3. Key IHE integration profiles and specifications discussed include RFD for retrieving case report forms, CRD for pre-populating forms with patient data from EHRs, and Redaction Services for tailoring the pre-populated data to match protocol requirements.
Selecting Core Clinical It Solutions For Life Sciences Organizations – Key S...Vinoth Kumar T
This document summarizes a presentation on selecting core clinical IT solutions for life sciences organizations. It discusses the challenges life sciences companies face with drug development timelines and costs. Effective clinical data management can help address these challenges by streamlining processes, improving data quality and security, and enabling faster data review and regulatory submissions. When selecting clinical IT solutions, companies should evaluate vendors, ensure regulatory compliance, and consider costs, integration, usability, and ongoing support. A successful implementation requires understanding existing workflows, conducting pilots, addressing security risks, and having open communication channels to resolve problems.
The speaker discusses mapping CDA (Clinical Document Architecture) documents to FHIR (Fast Healthcare Interoperability Resources). CDA was difficult to construct and read, while FHIR provides a more streamlined approach. A joint project maps CDA elements to FHIR specifications and profiles to define the relationship between the standards. The goal is a common syntax and resources that support both documents and APIs, with CDA documents eventually represented in FHIR.
Route from CCDA to FHIR by Grahame GrieveFurore_com
The speaker discusses mapping CDA (Clinical Document Architecture) documents to FHIR (Fast Healthcare Interoperability Resources). CDA was found to be difficult to construct and read, and not well-suited for granular data exchange. FHIR addresses these issues and can be used for both documents and APIs. A project is underway to map CDA elements to FHIR counterparts and define profiles to represent CDA documents in FHIR. This will help with the transition from CDA to FHIR for document exchange.
This document discusses clinical data standards and data integration tools. It provides an overview of leading organizations that develop clinical data standards like CDISC and HL7. It describes the evolution of standards development and FDA's endorsement of CDISC standards. The document reviews CDISC models, global adoption trends, benefits, and barriers to adoption. It defines extract, transform, load (ETL) tools and their importance for future clinical data integration and cross-study analysis. The future of standards is discussed, including increased adoption of CDISC, new therapeutic area standards, integration of different data sources, and the convergence of CDISC and HL7 standards with semantic web technologies.
The document summarizes the major topics in radiology IT that will be covered at the RSNA annual meeting. It discusses initiatives around monitoring patient radiation exposure through initiatives like the IHE-REM profile. It also covers efforts to improve image sharing through standards like IHE XDS for sharing images and reports between institutions. Additional areas covered include decision support, teaching/research tools like MIRC and CTP, and the use of Radlex as an ontology. RSNA's informatics committee and showcase at the annual meeting will provide more details on these initiatives.
1) The document discusses options for trial implementations of health information exchange (HIE) in New Zealand that are aligned with national HIE standards and have the potential to engage health system vendors.
2) Three potential trial options are compared: sharing InterRAI assessments with community pharmacists, sharing hospital discharge summaries with after-hours and emergency health services, and sharing primary care summaries with after-hours and emergency health services.
3) The document seeks feedback on the options from the Ministry of Health and healthAlliance to select trial implementation options and develop project plans.
Presentation on Healthcare Interoperability at AEA, delhi chapter meeting 27t...Kumar Satyam
This document summarizes an upcoming meeting of the Association of Enterprise Architects Delhi Chapter. The meeting agenda includes updates on the chapter and EA field, a presentation by Mr. Kumar Satyam from Philips on healthcare interoperability, feedback/Q&A, and future plans. The chapter aims to advance EA excellence in Delhi/NCR. The healthcare interoperability talk will discuss challenges like standards, data sharing, and regulations, and opportunities like APIs and initiatives like NDHM and IHE profiles.
This document outlines the key components and users of a Public Health Information System (PHI). The system collects data from various sources like food units, epidemiology, and schools. It stores the data in operational databases and a data warehouse. The data is then analyzed and used to support decision making, program planning, and health education. The system allows workload distribution and notification across different administrative levels like the central level, districts, and facilities.
This document discusses how the increased generation of data in pharmaceutical R&D has failed to improve productivity due to an inability to properly organize and apply knowledge. It describes how existing integration strategies store data in isolated "silos" that are difficult to access and compare. The author argues that new semantic technologies based on ontologies can better integrate knowledge across discovery, development, and other business areas to improve transparency, safety monitoring, and decision making.
This document provides definitions and explanations of key terms related to the HealthVault platform:
- HealthVault is a platform that allows applications to connect to securely store and access a user's health information. The main components are the HealthVault applications, shell, and records.
- HealthVault applications can send and access data from a user's HealthVault record. The shell is a special application that allows a user to manage access to their record and see activity logs. Records can contain multiple types of structured and unstructured health data.
- Developers can build and test applications using the pre-production environment before an application goes live on the production platform used by consumers. Additional terms defined include things, vocabularies, and
CER HUB An Informatics Platform for Conducting Compartive Effectiveness with ...HMO Research Network
The document describes the CER Hub, an informatics platform for conducting comparative effectiveness research using electronic medical record data. The CER Hub allows researchers to develop standardized processors to generate research datasets from heterogeneous EMR systems. It facilitates collaborative projects to address questions like evaluating asthma control and smoking cessation treatments. Initial projects through the CER Hub involve developing measures of asthma control and comparing the effectiveness of treatment intensification options using EMR data from six health systems.
1. A clinical data management system (CDMS) is used to manage data from clinical trials by storing data entered in case report forms (CRFs) by investigators.
2. Data management involves planning, collection, entry, validation, manipulation, backup and documentation of data to create a high quality database. Commonly used CDMS tools include Oracle Clinical, ClinTrial, Macro and eClinical Suite.
3. Open source CDMS tools include OpenClinica, openCDMS, TrialDB and PhOSCo which are free. All CDMS tools ensure an audit trail and management of discrepancies according to roles and user access levels.
Clinical data management involves processing clinical trial data through activities like data entry, validation, query resolution and medical coding. It aims to ensure the integrity and quality of clinical trial data, which regulatory agencies rely on for drug approval. The document provides an overview of the clinical data management process and roles involved at each stage, from study set-up to closeout.
Event brochure for the upcoming Clinical Data Standardisation and Managment event in London, June.
The event will feature best practice case studies from CDISC
Webcast: CIO Insights: How to Optimize User Experience Across 60 Hospitals Compuware APM
** If you would like to download a copy of the slides- please email jessica.murphy@compuware.com and she will send the slideset to you via email.**
For health services provider Christus Health, poorly performing applications are never an option. Just as medical equipment cannot fail, the applications supporting Christus Health must operate flawlessly. In order to avoid lost revenue, decreased clinical productivity and increased risk to patients, Christus employs an end-user perspective to application performance management.
Join Christus Health CIO George Conklin in this Compuware webcast to learn:
• What impacts healthcare app performance has on customer experience and business goals
• How Christus IT and the business teams optimize customer experience
• Real-world best practices for improving user experience without slowing down your healthcare processes and procedures
What You Will Learn:
George Conklin, Senior VP and CIO of Christus will share real-world experiences and Christus Heath’s best practice approach for ensuring users in their healthcare system have the best application performance possible.
Similar to eSource, DIA CDM, Florida, March 2007 (20)
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Cover Story - China's Investment Leader - Dr. Alyce SUmsthrill
In World Expo 2010 Shanghai – the most visited Expo in the World History
https://www.britannica.com/event/Expo-Shanghai-2010
China’s official organizer of the Expo, CCPIT (China Council for the Promotion of International Trade https://en.ccpit.org/) has chosen Dr. Alyce Su as the Cover Person with Cover Story, in the Expo’s official magazine distributed throughout the Expo, showcasing China’s New Generation of Leaders to the World.
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Prescriptive analytics BA4206 Anna University PPTFreelance
Business analysis - Prescriptive analytics Introduction to Prescriptive analytics
Prescriptive Modeling
Non Linear Optimization
Demonstrating Business Performance Improvement
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2. CDISC Initiative: Healthcare Link
Patient Care Clinical Research
World World
CDISC Initiative:
Healthcare Link
An industry initiative that has successfully demonstrated
clinical information interoperability between physician
clinical systems (EHR) and pharmaceutical clinical trials
systems based on open standards.
- Duke Clinical Research Institute, CDISC, Novartis, Merck, J&J, Microsoft.
Next Step: Development and Demonstration of
an Integration Profile (through IHE),
called Retrieve Form for Data Capture (RFD),
to be demonstrated in five use cases at HIMSS 07
Slide courtesy of Landen Bain, CDISC
DIA CDM Meeting, Florida, March 2007. 2
3. HIMSS 07 - New Orleans
DIA CDM Meeting, Florida, March 2007. 3
4. Clinic Back Office
6
1
5
2
3
4
Picture courtesy of Charles Jaffe, MD, PhD
DIA CDM Meeting, Florida, March 2007. 4
5. Before RFD
Trial Registry Clinical Trials
Biosurviellance Safety
Clinicians need to re-
enter data several
times to serve many
EHR needs. No re-use of
data
DIA CDM Meeting, Florida, March 2007. 5
6. A Framework for Interoperability
• Integrating the Healthcare Enterprise:
– An initiative that improves patient care by
harmonizing healthcare information exchange
– Provides a common standards-based framework
for seamlessly passing health information among
care providers, enabling local, regional and
national health information networks
– Promotes the coordinated use of established
standards–Health Level 7, ASTM, DICOM,
CDISC, W3C, IEEE, etc.—to address specific
clinical needs
Slide courtesy of Landen Bain, CDISC
DIA CDM Meeting, Florida, March 2007. 6
7. RFD Profile
• A standard way Retrieve Form external data
RFD = of displaying for Data-Capture
capture forms inside an EHR.
• Many-to-many integration – any EHR can
retrieve forms from many external systems.
• Applications to clinical trials, registries, bio-
surveillance, and pharmacovigilance.
RFD = Retrieve Form
for Data Capture
Slide courtesy of Landen Bain, CDISC
DIA CDM Meeting, Florida, March 2007. 7
8. Before RFD
Trial Registry Clinical Trials
Biosurviellance Safety
Clinicians need to re-
enter data several
times to serve many
EHR needs. No re-use of
data
DIA CDM Meeting, Florida, March 2007. 8
9. After RFD
Trial Registry Clinical Trials
Biosurviellance Safety
RFD provides for
EHR easy re-use of the
data already in the
EHR and for a better
process to capture
new data.
DIA CDM Meeting, Florida, March 2007. 9
10. RFD Profile
ArchiveF
A
orm
D
Form Filler
Form Archiver
Retrieve Submit
Form Form
B C
Form Manager Form Receiver
DIA CDM Meeting, Florida, March 2007. 10
11. Overview
Pfizer Lilly Novartis Genzyme SAIC
Form Filler
Allscripts
Cerner Siemens Allscripts Allscripts
Accenture
Form Manager
Sentrx
IBM Novartis DIFZ IBM
Relsys
Form Receiver
Sentrx Phase
Novartis SAS IBM
Relsys Forward
Form Archiver
SAS IBM SAS Assero SAS
DIA CDM Meeting, Florida, March 2007. 11
12. RFD Sceanrios
• Pharmaco-vigilance
Five Life Science Use Cases
• Investigational New Drug Trials
• Bio-surveillance
• Labs and Images
• Disease registry
DIA CDM Meeting, Florida, March 2007. 12
13. Pharmaco-vigilance
• Team: Pfizer, Sentrx, Allscripts, Accenture
• Standard: XForm, ODM, ICH E2B
• Scenario: Physician investigator, using an
EHR, discovers a suspected adverse drug
event and summons a data-capture form
from the drug manufacturer to provide
information on the event.
DIA CDM Meeting, Florida, March 2007. 13
14. Investigational New Drug Trials
• Team: Lilly, Cerner, Phase Forward, IBM
Investigational New Drug Trials
• Standard: XForm, ODM
• Scenario: A physician investigator utilizes an
EHR and collects Clinical Research (CR)
related data and then request a CR form to
finish collecting sponsor data.
The data is sent and loaded into the EDC
system for further data review and analysis
by the investigator and sponsor
DIA CDM Meeting, Florida, March 2007. 14
15. Bio-surveillance
• Team: SAIC, CDC, IBM, Allscripts
• Standard: XForm
• Scenario: A physician using an EHR
discovers a suspected outbreak of a disease.
Using RFD, the physician summons a data-
capture form from CDC, completes the form,
and returns.
DIA CDM Meeting, Florida, March 2007. 15
16. Labs and Images
• Team: Novartis, Siemens
• Standards: XForm, ODM, DICOM
• Scenario: A physician investigator completes
a clinical research form that included lab and
image data.
DIA CDM Meeting, Florida, March 2007. 16
17. Disease registry
• Team: Genzyme, DIFZ, SAS, Outcome,
Allscripts, Assero
• Standard: XForm, ODM
• Scenario: EHR user completes a guest form
for disease registry.
DIA CDM Meeting, Florida, March 2007. 17
18. eSDI Document Content
• Review and analysis of the relevant existing
regulations
• Twelve User Requirements for conducting regulated
clinical research using eSource data collection in the
context of existing regulations
• Five potential eSDI-based scenarios, three include
the use of electronic health record systems (EHR)
• Template for Evaluation of eSource data collection
process per the Requirements
• Good Practices Checklist for Investigators
http://www.cdisc.org/eSDI/eSDI.pdf
DIA CDM Meeting, Florida, March 2007. 18
19. eSDI History
• Started November 2004
• February & March 2005 informal comments
• 1st Draft, 14th March 2005
• 2nd Draft, 25th May 2005
• 3rd Draft,11th August 2005
• 4th Draft, 29th August 2005
• 5th Draft, 16th September 2005
• 6th Draft, 16th August 2006
• Issue 1, 20th November 2006
DIA CDM Meeting, Florida, March 2007. 19
20. User Requirements
1. An instrument used to capture source data 6. Source data shall only be modified with the
shall ensure that the data is captured as knowledge or approval of the investigator.
specified within the protocol.
2. Source data shall be Accurate, Legible, 7. Source documents and data shall be
Contemporaneous, Original, Attributable, protected from destruction.
Complete and Consistent.
3. An audit trail shall be maintained as part of 8. The source document shall allow for
the source documents for the original accurate copies to be made.
creation and subsequent modification of all
source data.
4. The storage of source documents shall 9. Source documents shall be protected
provide for their ready retrieval. against unauthorized access.
5. The investigator shall maintain the original 11. The location of source documents and
source document or a certified copy. the associated source data shall be clearly
identified at all points within the capture
process.
10. The sponsor shall not have exclusive 12. When source data are copied, the process
control of a source document. used shall ensure that the copy is an exact
copy preserving all of the data and metadata
of the original.
DIA CDM Meeting, Florida, March 2007. 20
21. eSDI Scenarios 4 & 5
Scenario 5
Sponsor
Scenario 4
Paper Source electronic Source
DIA CDM Meeting, Florida, March 2007. 21
22. RFD and eSource
ArchiveF
A
orm
D
Form Filler
Form Archiver
Retrieve Submit
Form Form
B C
Form Manager Form Receiver
DIA CDM Meeting, Florida, March 2007. 22
23. RFD and eSource
Investigator sphere
of control
EHR
FA
DIA CDM Meeting, Florida, March 2007. 23
24. RFD Flow
1. Request Form
2. Form
ODM &
XForms
ODM
3. Insert
Initial Offline: Use
Data ODM metadata
to create form
XML
Sponsor
Site ODM
4. Submit Data
DIA CDM Meeting, Florida, March 2007. Form Archiver 24
25. User Requirements
1. An instrument used to capture source data 6. Source data shall only be modified with the
shall ensure that the data is captured as knowledge or approval of the investigator.
FA
specified within the protocol.
2. Source data shall be Accurate, Legible, 7. Source documents and data shall be
Contemporaneous, Original, Attributable, protected from destruction. FA
Complete and Consistent.
3. An audit trail shall be maintained as part of 8. The source document shall allow for
the source documents for the original FA accurate copies to be made. FA
creation and subsequent modification of all
source data.
4. The storage of source documents shall
FA 9. Source documents shall be protected FA
provide for their ready retrieval. against unauthorized access.
5. The investigator shall maintain the original 11. The location of source documents and
source document or a certified copy. the associated source data shall be clearly
FA identified at all points within the capture FA
process.
10. The sponsor shall not have exclusive 12. When source data are copied, the process
control of a source document. used shall ensure that the copy is an exact
FA copy preserving all of the data and metadata
FA
of the original.
DIA CDM Meeting, Florida, March 2007. 25
26. … and reality, the IHE Connectathon
DIA CDM Meeting, Florida, March 2007. 26
27. Summary
• Practical Demonstration
• Based on Standards
– ODM
– SDTM
– E2B
– DICOM
• Architecture allows for eSource and ability to
meet the regulatory need.
DIA CDM Meeting, Florida, March 2007. 27