Toward a Responsible Future: Recommendations for AI-enabled Clinical Decision Support View
Toward a Responsible Future: Recommendations for AI-enabled Clinical Decision Support
  • Published: 11 October 2024
  • Posted: 11 October 2024

A discussion of the JAMIA paper that makes practical suggestions for creating methods, rules, and guidelines to ensure that the development, testing, supervision, and use of AI in clinical decision support (CDS) systems are done well and safely for patients

Read "Toward a responsible future: recommendations for AI-enabled clinical decision support" in the Journal of the American Medical Informatics Association, 2024, 1–10 https://doi.org/10.1093/jamia/ocae209

See also the DCI Network webinar series on this paper to be held December 6, 2024 hosted by Dr. Yuri Quintana and Dr. Steve Labkoff. Register for the webinar at https://www.dcinetwork.org/events/206

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Recording: Use Case 2: Improving Clinical Trial Recruitment
Platinum member
  • Published: 27 September 2024
  • Posted: 04 October 2024
  • Focus: Create a platform for matching patients with clinical trials
  • KPIs:
    • Increased enrollment rate
    • Reduced time-to-enrollment
    • Enhanced diversity in enrollment
    • Improved patient engagement
    • Increased trial awareness
    • Cost reduction
  • Data Models: Patient demographics, medical history, genomic profile, trial eligibility criteria, patient preferences, trial matching algorithm
  • Terminologies: ICD-10, SNOMED CT, LOINC, RxNorm, NCI Thesaurus, CDISC
  • Data Sources: EHRs, genomic databases, clinical trial registries, patient surveys, social media
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Recording: Use Case 3: Real-World Evidence and Use Case 4: Comparative Effectiveness Research
Platinum member
  • Published: 27 September 2024
  • Posted: 04 October 2024

Use Case 3:

  • Focus: Develop a module for analyzing treatment and outcome data
  • KPIs:
    • Improved treatment selection
    • Reduced adverse events
    • Enhanced patient outcomes
    • Increased efficiency in clinical decision-making
    • Cost-effectiveness
  • Data Models: Patient demographics, medical history, treatment data, outcome data, genomic data, real-world data
  • Terminologies: ICD-10, SNOMED CT, LOINC, RxNorm, MedDRA, NCI Thesaurus, PROMIS, EORTC QLQ-C30
  • Data Sources: EHRs, claims databases, patient registries, genomic databases, PRO surveys

Use Case 4:

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Recording: Use Case 7: Enabling Timely and Relevant Clinical Data Exchange
Platinum member
  • Published: 27 September 2024
  • Posted: 04 October 2024
  • Focus: Implement standardized data exchange interface for care transitions
  • KPIs:
    • Reduced time to treatment initiation
    • Decreased duplicate testing
    • Enhanced care coordination
    • Improved patient satisfaction
    • Reduced hospital readmissions
    • Increased adherence to treatment plans
  • Data Models: Patient demographics, medical history, diagnostic reports, treatment plans, progress notes, referral information
  • Terminologies: ICD-10, SNOMED CT, LOINC, RxNorm, FHIR, NCI Thesaurus
  • Data Sources: EHRs, laboratory information systems, radiology information systems, pathology information systems, patient portals
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Recording: Use Case 6: Improving Reporting and Classification of Adverse Event Analysis
Platinum member
  • Published: 27 September 2024
  • Posted: 04 October 2024
  • Focus: Develop unified adverse event reporting system
  • KPIs:
    • Increased AE reporting rate
    • Improved AE detection
    • Enhanced AE classification accuracy
    • Timely identification of safety signals
    • Reduced time and effort for AE reporting
    • Increased patient engagement in AE reporting
  • Data Models: Patient demographics, adverse event details, MedDRA coding, patient-reported outcomes, social media data
  • Terminologies: MedDRA, WHO-ART, SNOMED CT
  • Data Sources: EHRs, PRO measures, social media platforms, spontaneous AE reporting systems
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Recording: Use Case 5: Aggregating Data from Virtual Tumor Boards
Platinum member
  • Published: 27 September 2024
  • Posted: 04 October 2024
  • Focus: Develop platform for collecting and analyzing virtual tumor board data
  • KPIs:
    • VTB data utilization
    • Novel biomarker discovery
    • Personalized treatment recommendations
    • Patient outcomes
    • Collaboration and knowledge sharing
    • Data quality and completeness
  • Data Models: Patient demographics, clinical characteristics, genomic profile, treatment decisions, outcome data, VTB discussion data
  • Terminologies: Same as Use Case 3, plus HGVS nomenclature
  • Data Sources: VTB platforms, EHRs, genomic databases, imaging repositories, pathology reports, research databases, external data sources
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Recording: Use Case 1: Enhancing Cancer Screening through Targeted Communication
Platinum member
  • Published: 27 September 2024
  • Posted: 04 October 2024
  • Focus: Develop a module for personalized screening recommendations
  • Key Performance Indicators (KPIs):
    • Screening rate increase
    • Patient engagement
    • Disparity reduction
    • Time-to-diagnosis
  • Data Models: Patient demographics, risk factors, communication preferences, screening recommendations, educational materials, outreach
  • Terminologies: ICD-10, LOINC,  CT, NCI Thesaurus, SEER Coding Manual
  • Data Sources: EHRs, cancer registries, patient surveys, SDOH data
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Recording: Panel Session - Use Cases for Connecting Data Across Silos and Institutions
Visible to Users of this Site
  • Published: 26 September 2024
  • Posted: 03 October 2024

Panel Session - Use Cases for Connecting Data Across Silos and Institutions

  • Improving Cancer Screening - Eric Perakslis, PhD, Chief Scientific and Data Officer, Pluto Health; Senior Vice President and Chief Technology Officer, IMIDomics
  • Improving how we analyze and visualize data - Ino de Bruijn, MSc, Manager Bioinformatics Software Engineering, Data Visualization Team Lead, Memorial Sloan Kettering Cancer Center
  • Improving our data vision and data strategies - Xuelu "Jeff" Liu, PMP, CSM, Director, Data Management & Strategy, Division of Population Sciences, Department of Medical Oncology, Dana-Farber Cancer Institute, Boston, Massachusetts
  • Improving how we learn from virtual tumor boards - Yuri Quintana, PhD, FACMI
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Recording: Comparing Outcomes
Visible to Users of this Site
  • Published: 26 September 2024
  • Posted: 03 October 2024

Comparing Outcomes

  • Improving how we compare treatment outcomes - Jeremy Warner, MD, Professor of Biostatistics, Professor of Medicine and Professor of Biostatistics at Brown University, the Associate Director of Data Science at the Legorreta Cancer Center at Brown University.
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Recording: Observational Data Models
Visible to Users of this Site
  • Published: 26 September 2024
  • Posted: 03 October 2024

Observational Data Models

  • Talk Title: OMOP Oncology
  • Speaker: Asieh Golozar, VP, Global Head of Data Science at Odysseus Data Services, Inc. | Professor of the Practice & Director of Clinical Research at the OHDSI Center, Northeastern University
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Recording: Minimal Data Standards - mCODE
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  • Published: 26 September 2024
  • Posted: 03 October 2024

Minimal Data Standards - mCODE

  • Talk Title: Cancer on FHIR: Unlocking the Potential of Cancer Data Exchange with mCODE
  • Speakers: May Terry M.Sc., BSEE, BSN, RN; and Su Chen, MD, is a Clinical Science Principal at MITRE
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Slides: Improving how we analyze and visualize data
Visible to Users of this Site
  • Published: 26 September 2024
  • Posted: 03 October 2024

Panel Session - Use Cases for Connecting Data Across Silos and Institutions

  • Improving Cancer Screening - Eric Perakslis, PhD, Chief Scientific and Data Officer, Pluto Health; Senior Vice President and Chief Technology Officer, IMIDomics
  • Improving how we analyze and visualize data - Ino de Bruijn, MSc, Manager Bioinformatics Software Engineering, Data Visualization Team Lead, Memorial Sloan Kettering Cancer Center
  • Improving our data vision and data strategies - Xuelu "Jeff" Liu, PMP, CSM, Director, Data Management & Strategy, Division of Population Sciences, Department of Medical Oncology, Dana-Farber Cancer Institute, Boston, Massachusetts
  • Improving how we learn from virtual tumor boards - Yuri Quintana, PhD, FACMI
View
Slides: Improving our data vision and data strategies
Visible to Users of this Site
  • Published: 26 September 2024
  • Posted: 03 October 2024

Panel Session - Use Cases for Connecting Data Across Silos and Institutions

  • Improving Cancer Screening - Eric Perakslis, PhD, Chief Scientific and Data Officer, Pluto Health; Senior Vice President and Chief Technology Officer, IMIDomics
  • Improving how we analyze and visualize data - Ino de Bruijn, MSc, Manager Bioinformatics Software Engineering, Data Visualization Team Lead, Memorial Sloan Kettering Cancer Center
  • Improving our data vision and data strategies - Xuelu "Jeff" Liu, PMP, CSM, Director, Data Management & Strategy, Division of Population Sciences, Department of Medical Oncology, Dana-Farber Cancer Institute, Boston, Massachusetts
  • Improving how we learn from virtual tumor boards - Yuri Quintana, PhD, FACMI
View
Slides: Comparing Outcomes
Visible to Users of this Site
  • Published: 26 September 2024
  • Posted: 03 October 2024

Comparing Outcomes

  • Improving how we compare treatment outcomes - Jeremy Warner, MD, Professor of Biostatistics, Professor of Medicine and Professor of Biostatistics at Brown University, the Associate Director of Data Science at the Legorreta Cancer Center at Brown University.
View
Slides: Observational Data Models
Visible to Users of this Site
  • Published: 26 September 2024
  • Posted: 03 October 2024

Observational Data Models

  • Talk Title: OMOP Oncology
  • Speaker: Asieh Golozar, VP, Global Head of Data Science at Odysseus Data Services, Inc. | Professor of the Practice & Director of Clinical Research at the OHDSI Center, Northeastern University
View
Slides: Minimal Data Standards - mCODE
Visible to Users of this Site
  • Published: 26 September 2024
  • Posted: 03 October 2024

Minimal Data Standards - mCODE

  • Talk Title: Cancer on FHIR: Unlocking the Potential of Cancer Data Exchange with mCODE
  • Speakers: May Terry M.Sc., BSEE, BSN, RN; and Su Chen, MD, is a Clinical Science Principal at MITRE
View
Slides: Emerging Standards - USCDI+
Visible to Users of this Site
  • Published: 26 September 2024
  • Posted: 03 October 2024

Emerging Standards - USCDI+

  • Talk Title: Unlocking Cancer Data Insights: Advancing Cancer Data Interoperability with the USCDI+ Cancer
  • Speakers: Umit Topaloglu, PhD,, Chief, Clinical and Translational Research Informatics Branch, and Liz Turi, MEng Assistant Secretary for Technology Policy/Office of the National Coordinator for Health Information Technology (hereafter ASTP)
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Recording: Emerging Standards - USCDI+
Visible to Users of this Site
  • Published: 26 September 2024
  • Posted: 03 October 2024

Emerging Standards - USCDI+

  • Talk Title: Unlocking Cancer Data Insights: Advancing Cancer Data Interoperability with the USCDI+ Cancer
  • Speakers: Umit Topaloglu, PhD,, Chief, Clinical and Translational Research Informatics Branch, and Liz Turi, MEng Assistant Secretary for Technology Policy/Office of the National Coordinator for Health Information Technology (hereafter ASTP)
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Slides: Lessons Learned from Large-Scale Cancer Longitudinal Databases
Visible to Users of this Site
  • Published: 26 September 2024
  • Posted: 03 October 2024

Lessons Learned from Large-Scale Cancer Longitudinal Databases

  • Talk Title: The NCI's Childhood Cancer Data Initiative: Building on the Power of data and Community
  • Speaker: Gregory H. Reaman, M.D., Scientific Director, Childhood Cancer Data Initiative (CCDI), Division of Cancer Treatment and Diagnosis/OD, National Cancer Institute
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Recording: Lessons Learned from Large-Scale Cancer Longitudinal Databases
Visible to Users of this Site
  • Published: 26 September 2024
  • Posted: 03 October 2024

Lessons Learned from Large-Scale Cancer Longitudinal Databases

  • Talk Title: The NCI's Childhood Cancer Data Initiative: Building on the Power of data and Community
  • Speaker: Gregory H. Reaman, M.D., Scientific Director, Childhood Cancer Data Initiative (CCDI), Division of Cancer Treatment and Diagnosis/OD, National Cancer Institute
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Slides: Patient-Centric Data Science Perspectives
Visible to Users of this Site
  • Published: 26 September 2024
  • Posted: 03 October 2024

Patient-Centric Data Science Perspectives

  • Talk Title: Toward health records that serve clinicians and patients
  • Keynote Speaker: Amada Borens, MS Founder Tesselate Data Consulting, LLC
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Recording: Patient-Centric Data Science Perspectives
Visible to Users of this Site
  • Published: 26 September 2024
  • Posted: 03 October 2024

Patient-Centric Data Science Perspectives

  • Talk Title: Toward health records that serve clinicians and patients
  • Keynote Speaker: Amada Borens, MS Founder Tesselate Data Consulting, LLC
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Slides: Workshop Introduction and Long-Term Goals
Visible to Users of this Site
  • Published: 26 September 2024
  • Posted: 03 October 2024

Workshop Introduction and Long-Term Goals

  • Talk Title: Towards better data harmonization and linking across silos with coordinate data architectures, data models and cooperative agreements
  • Speaker: Yuri Quintana, PhD, Chief of Division of Clinical Informatics, Beth Israel Deaconess Medical Center.
  • Bio: https://research.bidmc.org/yuriquintana
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