2016 LabHIT Vision
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The document discusses the CDC's LabHIT program which aims to facilitate laboratory test ordering and reporting in electronic health records. The program develops and disseminates standardized terminology and code sets to support clinical data capture and interoperability. It also works with various stakeholders to engage in terminology development, promote semantic interoperability, and ensure usability and patient safety. The long-term goal is a single national reference database for recommended vocabulary sets to achieve full-scale interoperability for laboratory data.
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Combining Patient Records, Genomic Data and Environmental Data to Enable Tran...
Combining Patient Records, Genomic Data and Environmental Data to Enable Tran...Perficient, Inc.The average academic research organization (ARO) and hospital has many systems that house patient-related information, such as patient records and genomic data. Combining data from a variety of sources in an ongoing manner can enable complex and meaningful querying, reporting and analysis for the purposes of improving patient safety and care, boosting operational efficiency, and supporting personalized medicine initiatives.
In this webinar, Perficient’s Mike Grossman, a director of clinical data warehousing and analytics, and Martin Sizemore, a healthcare strategist, discussed:
-How AROs and hospitals can benefit from a systematic approach to combining data from diverse systems and utilizing a suite of data extraction, reporting, and analytical tools, in order to support a wide variety of needs and requests
-Examples of proposed solutions to real-life challenges AROs and hospitals often encounter
Brendan Delany – Chair in Medical Informatics and Decision Making, Imperial...
Brendan Delany – Chair in Medical Informatics and Decision Making, Imperial...HIMSS UKThe document discusses the EU-funded TRANSFoRm project, which aimed to develop methods and validated architectures to support a learning health system. The project involved 21 partners from 10 EU member states. It sought to enable real-time clinical diagnosis and trials using data from electronic health records. It developed ontologies and standards to maintain meaning across the learning health system. A prototype clinical decision support system integrated into a primary care electronic health record was evaluated in a simulation and found to improve diagnostic accuracy and management without increasing consultation time or test ordering.
CDx-NGS-webinar
CDx-NGS-webinarPistoia AllianceThe Pistoia Alliance is examining the challenges of the Faster Safe Companion Diagnostics (CDx) by Aligning Discovery & Clinical Data in the Regulatory Domain.
The slides discuss whether the data standards used in the research environment be aligned better with the data standards used in the regulated environment? If so, the time and cost of the development of NGS-based CDx could be reduced.
The need for interoperability in blockchain-based initiatives to facilitate c...
The need for interoperability in blockchain-based initiatives to facilitate c...Massimiliano Masiݺߣs for the IEEE Blockchain Symposium in Glasgow, https://blockchain.ieee.org/standards/clinicaltrialseurope18, https://blockchain.ieee.org/standards/clinicaltrialseurope18/speakers
Strengthening Health Systems through the application of Wireless Technology
Strengthening Health Systems through the application of Wireless TechnologyOPS ColombiaPresentación realizada por el Dr. Trishan Panch, de Harvard School of Public Health, el 20 de Septiembre en OPS Colombia, en el espacio de intercambio sobre e-health.
El Dr. Panch, participa, con el auspicio de esta Representación, como conferencista en el IV Congreso Colombiano de Bioingeniería e Ingeniería Biomédica que se realizará en Barranquilla del 21 al 24 de septiembre del 2011.
Data Management in Clinical Research
Data Management in Clinical ResearchijtsrdA crucial stage in clinical research is clinical data management CDM , which produces high quality, reliable, and statistically sound data from clinical trials. This results in a significantly shorter period of time between drug development and marketing. Team members of CDM are laboriously involved in all stages of clinical trials right from commencement to completion. They should be able to sustain the quality standards set by CDM processes by having sufficient process expertise. colorful procedures in CDM including Case Report Form CRF designing, CRF reflection, database designing, data entry, data confirmation, distinction operation, medical coding, data birth, and database locking are assessed for quality at regular intervals during a trial. In the present script, theres an increased demand to ameliorate the CDM norms to meet the nonsupervisory conditions and stay ahead of the competition by means of brisk commercialization of products. With the perpetration of nonsupervisory biddable data operation tools, the CDM platoon can meet these demands. also, its getting obligatory for companies to submit the data electronically. CDM professionals should meet applicable prospects and set norms for data quality and also have the drive to acclimatize to the fleetly changing technology. This composition highlights the processes involved and provides the anthology an overview of the tools and norms espoused as well as the places and liabilities in CDM. Syed Shahnawaz Quadri | Syeda Saniya Ifteqar | Syed Shafa Raoof "Data Management in Clinical Research" Published in International Journal of Trend in Scientific Research and Development (ijtsrd), ISSN: 2456-6470, Volume-7 | Issue-2 , April 2023, URL: https://www.ijtsrd.com.com/papers/ijtsrd55050.pdf Paper URL: https://www.ijtsrd.com.com/pharmacy/other/55050/data-management-in-clinical-research/syed-shahnawaz-quadri
Informatics Standards And Interoperability20090325
Informatics Standards And Interoperability20090325Abdul-Malik ShakirA presentation about the role of informatics standards in facilitating electronic data interchange, and a framework for service-oriented semantic interoperability among data systems.
What lies ahead for india
What lies ahead for indiaNASSCOM CoE - IoTNASSCOM CoE IoT spearheaded a high-level industry roundtable to discuss firsthand the challenges & opportunities in India’s clinical trial industry and how technology can accelerate development
6292016 library.ahima.orgPBDataStandards#appxAhttpl.docx
6292016 library.ahima.orgPBDataStandards#appxAhttpl.docxpriestmanmable6/29/2016 library.ahima.org/PB/DataStandards#appxA
http://library.ahima.org/PB/DataStandards#appxA 1/20
DataStandards,DataQuality,andInteroperability(2013
update)
RemovefrommyBoK
Editor'snote:Thisupdatereplacesthe2007practicebrief"DataStandards,DataQuality,andInteroperability."
Dataqualityandconsistencyarecriticaltoensuringpatientsafety,communicatingdeliveryofhealthservices,coordinating
care,andhealthcarereporting.Assessingthequalityandconsistencyofdatarequiresdatastandards.Thispracticebrief
provideshealthinformationmanagement(HIM)professionalswithaclearunderstandingofdatastandardsasatoolto
enableinteroperabilityandpromotedataquality.
Theonlineversionofthispracticebrief[...]isaccompaniedbyanappendixthatprovidesHIMprofessionalswithalistof
standardstoreferenceindatadictionarydevelopment,electronichealthrecords,theexchangeofhealthinformation,and
generaldatamanagementprocessestoensureinformationintegrityandreliability.Evaluationofdatavalidity,reliability,
completeness,andtimelinessareaccomplishedthroughacombinationofhumanandmachineprocessesinhealthcare,and
thelistofdatastandardsourcesisahelpfulreferenceguidewhenmoredetailedinformationisrequired.
DataStandardsandRegulatoryFramework
Datastandardsare"documentedagreementsonrepresentations,formats,anddefinitionsofcommondata.Datastandards
provideamethodtocodifyinvalid,meaningful,comprehensive,andactionableways,informationcapturedinthecourseof
doingbusiness." Rulestodescribehowthedataisrecordedtoensureconsistencyacrossmultiplesourcesisanotherwayto
thinkofdatastandards.Withoutdatastandardsanddataquality,thefutureofinteroperabilityisbleak.Datafieldsandthe
contentofthosefieldsneedtobestandardized.
Standardsdevelopmentorganizations(SDOs)addressavarietyofaspectsofhealthinformationandinformatics.For
example,theAmericanSocietyforTestingandMaterials(ASTM)andHealthLevelSeven(HL7)targetclinicaldata
standards.InsuranceandremittancestandardsareafocusoftheAccreditedStandardsCommittee(ASC)X12.Standardsto
transmitdiagnosticimagesaredevelopedthroughDigitalImagingandCommunicationsinMedicine(DICOM).The
NationalCouncilforPrescriptionDrugPrograms(NCPDP)representspharmacymessages.
TheInstituteofElectricalandElectronicsEngineers(IEEE),HL7,ASTM,andothersdevelopdatamodelsand
frameworks.Seethetableonpage65forabreakdownofregulatoryagenciesresponsibleforworkingwiththeAmerican
NationalStandardsInstitute(ANSI)todrivedatastandardstoachieveinteroperability.
TheAHIMALeadershipModelstatesthatHIMprofessionalsshouldserveastheleadersinhealthcareorganizationsandin
theirprofessionalcommunityforensuringthatdatacontentstandardsareidentified,understood,implemented,a.
6292016 library.ahima.orgPBDataStandards#appxAhttpl.docx
6292016 library.ahima.orgPBDataStandards#appxAhttpl.docxblondellchancy6/29/2016 library.ahima.org/PB/DataStandards#appxA
http://library.ahima.org/PB/DataStandards#appxA 1/20
DataStandards,DataQuality,andInteroperability(2013
update)
RemovefrommyBoK
Editor'snote:Thisupdatereplacesthe2007practicebrief"DataStandards,DataQuality,andInteroperability."
Dataqualityandconsistencyarecriticaltoensuringpatientsafety,communicatingdeliveryofhealthservices,coordinating
care,andhealthcarereporting.Assessingthequalityandconsistencyofdatarequiresdatastandards.Thispracticebrief
provideshealthinformationmanagement(HIM)professionalswithaclearunderstandingofdatastandardsasatoolto
enableinteroperabilityandpromotedataquality.
Theonlineversionofthispracticebrief[...]isaccompaniedbyanappendixthatprovidesHIMprofessionalswithalistof
standardstoreferenceindatadictionarydevelopment,electronichealthrecords,theexchangeofhealthinformation,and
generaldatamanagementprocessestoensureinformationintegrityandreliability.Evaluationofdatavalidity,reliability,
completeness,andtimelinessareaccomplishedthroughacombinationofhumanandmachineprocessesinhealthcare,and
thelistofdatastandardsourcesisahelpfulreferenceguidewhenmoredetailedinformationisrequired.
DataStandardsandRegulatoryFramework
Datastandardsare"documentedagreementsonrepresentations,formats,anddefinitionsofcommondata.Datastandards
provideamethodtocodifyinvalid,meaningful,comprehensive,andactionableways,informationcapturedinthecourseof
doingbusiness." Rulestodescribehowthedataisrecordedtoensureconsistencyacrossmultiplesourcesisanotherwayto
thinkofdatastandards.Withoutdatastandardsanddataquality,thefutureofinteroperabilityisbleak.Datafieldsandthe
contentofthosefieldsneedtobestandardized.
Standardsdevelopmentorganizations(SDOs)addressavarietyofaspectsofhealthinformationandinformatics.For
example,theAmericanSocietyforTestingandMaterials(ASTM)andHealthLevelSeven(HL7)targetclinicaldata
standards.InsuranceandremittancestandardsareafocusoftheAccreditedStandardsCommittee(ASC)X12.Standardsto
transmitdiagnosticimagesaredevelopedthroughDigitalImagingandCommunicationsinMedicine(DICOM).The
NationalCouncilforPrescriptionDrugPrograms(NCPDP)representspharmacymessages.
TheInstituteofElectricalandElectronicsEngineers(IEEE),HL7,ASTM,andothersdevelopdatamodelsand
frameworks.Seethetableonpage65forabreakdownofregulatoryagenciesresponsibleforworkingwiththeAmerican
NationalStandardsInstitute(ANSI)todrivedatastandardstoachieveinteroperability.
TheAHIMALeadershipModelstatesthatHIMprofessionalsshouldserveastheleadersinhealthcareorganizationsandin
theirprofessionalcommunityforensuringthatdatacontentstandardsareidentified,understood,implemented,a ...
Pandemic Tech: How Emerging Technologies Can Mitigate the Impact of Covid-19 ...
Pandemic Tech: How Emerging Technologies Can Mitigate the Impact of Covid-19 ...Tory CenajThis document summarizes how emerging technologies like blockchain can help address challenges posed by the COVID-19 pandemic and future pandemics. It discusses how blockchain can enable self-sovereign identity and health records, improve supply chain management, sustain economies, create medical professional registries, and incentivize responsible behavior. The document also provides an overview of Sean Manion's presentation on how blockchain can accelerate medical research by improving data sharing, tracking of methods/analyses, peer review processes, and publishing models.
Microsoft: A Waking Giant In Healthcare Analytics and Big Data
Microsoft: A Waking Giant In Healthcare Analytics and Big DataHealth CatalystIn 2005, Northwestern Memorial Healthcare embarked upon a strategic Enterprise Data Warehousing (EDW) initiative with the Microsoft technology platform as the foundation. Dale Sanders was CIO at Northwestern and led the development of Northwestern’s Microsoft-based EDW. At that time, Microsoft as an EDW platform was not en vogue and there were many who doubted the success of the Northwestern project. While other organizations were spending millions of dollars and years developing EDW’s and analytics on other platforms, Northwestern achieved great and rapid value at a fraction of the cost of the more typical technology platforms. Now, there are more healthcare data warehouses built around Microsoft products than any other vendor. The risky bet on Microsoft in 2005 paid off.
Ten years ago, critics didn’t believe that Microsoft could scale in the second generation of relational data warehouses, but they did. More recently, many of these same pundits have criticized Microsoft for missing the technology wave du jour in cloud offerings, mobile technology, and big data. But, once again, Microsoft has been quietly reengineering its culture and products, and as a result, they now offer the best value and most visionary platform for cloud services, big data, and analytics in healthcare.
In this context, Dale will talk about:
His up and down journey with Microsoft as an Air Force and healthcare CIO, and why he is now more bullish on Microsoft like never before
A quick review of the Healthcare Analytics Adoption Model and Closed Loop Analytics in healthcare, and how Microsoft products relate to both
The rise of highly specialized, cloud-based analytic services and their value to healthcare organizations’ analytics strategies
Microsoft’s transformation from a closed-system, desktop PC company to an open-system consumer and business infrastructure company
The current transition period of enterprise data warehouses between the decline of relational databases and the rise of non-relational databases, and the new Microsoft products, notably Azure and the Analytic Platform System (APS), that bridge the transition of skills and technology while still integrating with core products like Office, Active Directory, and System Center
Microsoft’s strategy with its PowerX product line, and geospatial analysis and machine learning visualization tools
The Role of Data Lakes in Healthcare
The Role of Data Lakes in HealthcarePerficient, Inc.The document discusses the role of data lakes in healthcare. It defines a data lake as a system that holds large amounts of raw data from various sources in its original format to enable analysis. Data lakes allow healthcare organizations to gain insights from patient outcomes, fraud detection, clinical trials, and more. Examples of potential use cases in healthcare include genomic analytics, improving clinical trials, predictive healthcare costs, creating a 360-degree view of patients, identifying billing opportunities from unstructured text, and psychographic prescriptive modeling. The document outlines best practices for assessing the need for a data lake, planning, implementing, and governing a data lake project in a healthcare organization.
2016 Standardization of Laboratory Test Coding - PHI Conference
2016 Standardization of Laboratory Test Coding - PHI ConferenceMegan Sawchuk
Big data, RWE and AI in Clinical Trials made simple
Big data, RWE and AI in Clinical Trials made simpleHadas Jacoby
1. keynote dominic mack morehouse school of medicine
1. keynote dominic mack morehouse school of medicineGreaterRomeChamber
Challenges and Opportunities Around Integration of Clinical Trials Data
Challenges and Opportunities Around Integration of Clinical Trials DataCitiusTech
Combining Patient Records, Genomic Data and Environmental Data to Enable Tran...
Combining Patient Records, Genomic Data and Environmental Data to Enable Tran...Perficient, Inc.
Brendan Delany – Chair in Medical Informatics and Decision Making, Imperial...
Brendan Delany – Chair in Medical Informatics and Decision Making, Imperial...HIMSS UK
The need for interoperability in blockchain-based initiatives to facilitate c...
The need for interoperability in blockchain-based initiatives to facilitate c...Massimiliano Masi
Strengthening Health Systems through the application of Wireless Technology
Strengthening Health Systems through the application of Wireless TechnologyOPS Colombia
Informatics Standards And Interoperability20090325
Informatics Standards And Interoperability20090325Abdul-Malik Shakir
6292016 library.ahima.orgPBDataStandards#appxAhttpl.docx
6292016 library.ahima.orgPBDataStandards#appxAhttpl.docxpriestmanmable
6292016 library.ahima.orgPBDataStandards#appxAhttpl.docx
6292016 library.ahima.orgPBDataStandards#appxAhttpl.docxblondellchancy
Pandemic Tech: How Emerging Technologies Can Mitigate the Impact of Covid-19 ...
Pandemic Tech: How Emerging Technologies Can Mitigate the Impact of Covid-19 ...Tory Cenaj
Microsoft: A Waking Giant In Healthcare Analytics and Big Data
Microsoft: A Waking Giant In Healthcare Analytics and Big DataHealth Catalyst
2016 LabHIT Vision
- 1. www.cdc.gov | Contact CDC at: 1-800-CDC-INFO or www.cdc.gov/info The findings and conclusions in this report are those of the authors and do not necessarily represent the official position of the Centers for Disease Control and Prevention. Division of Laboratory Systems LabHIT Team: Megan E. Sawchuk, BS, MT(ASCP), MariBeth Gagnon, MS CT(ASCP)HTL, Nancy E. Cornish, MD, FCAP, Ira M. Lubin, PhD, FACMG, Graylin Mitchell, MPH, MT, Sonya Strider, PhD, MT(ASCP), Manjula Gama Ralalage, MBBS, MSc Facilitating Laboratory Test Ordering and Reporting in the Electronic Health Record Division of Laboratory Systems Objectives: Quality Clinical Data Capture and Achieving Meaningful Use Develop and disseminate code sets to support quality clinical data capture, thereby enabling electronic health record data to be used to inform decision making for individuals, healthcare providers, researchers and public health. Methods aLOINC® - Model Example Project Laboratory Test Order Codes Initiative for Top Ordered Tests SNOMED CT® - Model Example Project Specimen attribute coding to fully define the tested specimen Vision: Achieving Interoperability “Stretch Goal” Support full-scale interoperability for laboratory data by providing a single national reference database of recommended vocabulary sets with mapping of test systems to code systems. Building World-Class Local, Regional & National Surveillance Capability Goal: Patient Safety & Data Integrity Laboratory data can be distributed rapidly and to numerous users in the healthcare system. The goal of interoperability is to ensure data integrity, or trust, in every electronic transmission, thereby also ensuring laboratory data is provided in a manner to support patient safety and optimized healthcare decision making. LabHIT’s Central Role Bringing diverse stakeholders together Results • aLOINC® order codes will be included in Regenstrief’s LOINC Mapping Assistant (RELMA®) tool. • SNOMED CT® codes are completed and available to fully define specimens. • Terminology work is resource intensive and voluminous, requiring a long term commitment of resources. • The long term iterative process to develop health IT terminology can result in duplicative efforts over time and from different stakeholders, nationally and internationally. • An incremental approach is needed to continue moving each code set toward the vision. Next Steps ENGAGEMENT • Continue promoting health IT opportunities via LabHIT email subscriber database: • Relevant federal grant opportunities (CDC, ONC, AHRQ) • Association of Pathology Informatics (API) Technical Member category to groom next generation laboratory science SMEs • Comment periods on proposed regulations, guidelines, and requests for information • Facilitate participation of stakeholders with standards organizations, including clinical SMEs, software vendors, manufacturers, and professional organizations INTEROPERABILITY • Promote semantic interoperability workshops and guidance for laboratory testing systems in collaboration with FDA, NLM, CMS and ONC • Support participation and leadership of private industry test system manufacturer funded organizations with an interest in interoperability • Identify mechanisms to distribute standardized vocabulary for specimen test ordering to EHR vendors, e.g. relational database • Serve as SMEs on numerous HL7 Initiatives related to laboratory standards • Promote use of the CLIA standard level LRI Validation Suite by EHR vendors • Propose a centralized laboratory LOINC® and SNOMED CT® coding process USABILITY & SAFETY • Participate on HL7 Laboratory Functional Behaviors Guide Workgroup • Support NIST’s 2016 Usability Workshop, “The Role of Standards in Preventing & Mitigating Health IT Patient Safety Risks” • Evaluate health IT related patient safety events reported to the FDA • Create laboratory safety checklist for assessment of laboratory data display Use of trade names, commercial sources or private organizations is for identification only and does not imply endorsement by the U.S. Department of Health and Human Services and/or CDC. Poster presented at the 2016 Public Health Informatics Conference, Atlanta GA (August 22, 2016) and the CDC 5th Global Health Lab Forum, Atlanta GA (September 12, 2016). For more information: visit www.cdc.gov/labhit or email LabHIT@cdc.gov Regulatory and Accreditation Organizations Professional Societies Vendors Health IT Clinical Laboratories LabHIT Clinical and Public Health Laboratory Reporting