Vojtech huser-2009-amia-clinical-research-informatics-panel-eligibility-v011
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  • premise: we all did research last year, or even 5 years ago – how has it changed, Informatics can create standards, best practices, computerize How can we make the trial be cheaper and go more smoothely Scenario: for example: BigPharmaA is sponsoring the trial (new chemoterapy agent) or MidWest Lymphoma Consortium B (testing a new treatment protocol) CCHIT+Meaningful use (voices which want research capabilities of EHR be included in meaningful use matrix)
  • Scenario Doing research oroginating from within – NIH funded, local industry In next slides – I wil go through those 3 key issues – query, screening/enrolling and I will not be quoting exact numbers and percentages
  • Mediated: 5/5 100% speed of it is important, at some institutions – the response can be even same day (4 hours) or it can take a week Non-mediated currently used: 4/5 80% home grown: 4 out of 4 (100%) (self service, use by researchers, review preliminary to research, not requiring IRB approval) Majority have something in place (or even several in place – legacy and new system (COH for example -)) Often is web based, but can also be a fat client (e.g., C or Java application) Example: At Intermountain, Clinical Programs Framework (e.g., Oncology, Primary Care,
  • Ability to export is limited Code for female may be different: may be solved in the SHRINE consortium or Meaningful use: HIT Standards Committee: gender HL7 v.2.5.1 Table 0001
  • Variation: Range from (A) manually Done through clinical research coordinators (or clinicians) to (Z) computerized system with computerized enrollment logic and support for human element Link to local system is necessary, centralized solution is not possible (e.g., BigPharmaA can not have notification of new cancer patients from all consortium participants) (privacy issues) Data source: DW data is often not real time -1 day delay Vigilance system is capable of encoding a computerized eligibility criteria. It is connected to data feeds from EHR system. It is similar to a decision support platform used at Columbia University. (which uses Arden Syntax representation format and is an internally build Arden Syntax execution engine) A designated team (programmer) can translate a narrative logic into an MLM Q:(WOULD SCREENSHOT FROM COLUMBIA BE POSSIBLE?) Example2 Example 3 – next slide – involving the patient
  • 2 components of the system Public internet: use by patients Secured website: use by Clinical Research Staff
  • 100% of institutions use paper based forms but most have some capacity to make them electronic in in few sutdi Same problem: can have legacy and new system Market share of different CTMS (Velos, enCore, MediData) Agreement on Standardized Protocol Inclusion Requirements for Eligibility

Vojtech huser-2009-amia-clinical-research-informatics-panel-eligibility-v011 Vojtech huser-2009-amia-clinical-research-informatics-panel-eligibility-v011 Presentation Transcript

  • Development, Selection, and Adoption of Clinical Research Eligibility Representation Standards and Screening Methods: Current and Future Directions fall AMIA 2009 panel (CRI WG sponsored) Joyce C. Niland, PhD, MS1, Gilan El Saadawi, MD, PhD2, Chunhua Weng, PhD3, Vojtech Huser, MD, PhD 4, Jason P. Jones, PhD5,6 , Rachel Richesson, PhD7 1City of Hope National Medical Center, Duarte CA; 2University of Pittsburgh. Pittsburgh, PA; 3Columbia University, New York, NY; 4Biomedical Informatics Research Center, Marshfield Clinic Research Foundation, Marshfield, WI; 5Intermountain Healthcare, Salt Lake City, UT; 6University of Utah, Salt Lake City, UT, 6University of South Florida, Tampa, FL
    • Some are slides not included
  • Vojtech Huser
    • Survey results
  • Survey
    • Investigate current technologies
    • Convenience sample of institutions
    • Qualitative analysis (structured interviews)
    • Example scenario (Hodgkin Lymphoma)
      • 1. Number of HL patients in 2008
      • 2. Strategy to enroll HL patients in 2010
      • 3. Additional questions (additional tests, future plans)
    • Related Standards and Initiatives (BRIDG, Arden Syntax, caGrid, i2b2, CCHIT)
  • Institutions
    • Different types of institutions
      • university affiliated medical centers, integrated delivery network
    • Range of other factors
      • home-grown EHR vs. vendor, CTSA site
    • Institutions
      • Columbia U
      • U of Pittsburg
      • Marshfield Clinic
      • Intermountain Healthcare
      • City of Hope Medical Center
  • 1. Query
    • How many Hodgkin Lymphoma patients in 2008?
    • Mediated data warehouse request
    • Non-mediated system
    • Example: Intermountain Healthcare
      • Clinical Programs framework
      • Designated analyst with expert data warehouse knowledge for a given domain
    http://intermountainhealthcare.org/about/quality/Pages/ClinicalPrograms.aspx
  •  
  • 2. Screening
    • How can you enroll new HL patients (2010)?
    • Wide variation, active area of research
    • Data source: EHR system vs. Data Warehouse
    • Example1: Columbia university
      • Vigilance system
      • Standard: Arden Syntax
    • Example2: Marshfield Clinic
      • FlowGuide system (pilot phase)
      • Standard: XML process definition language
  • Example 2: Marshfield Clinic Editor Execution Engine
  • Patient self-referral example http://clinicaltrials.coh.org
  • 3. Follow-up
    • Are you willing to undergo additional tests? Are you planning to be pregnant?
    • Paper based Case Report Forms (CRF)
    • Size of the study (local, consortium, industry)
    • Standards: role of BRIDG?
    • Research features of EHR systems (CCHIT)
    • Clinical Trial Management System (CTMS) capabilities
  • CTMSs
  •  
  • Electronic research form within PHR
  • Form setup example (Velos): Are you willing to undergo additional tests? Data element creation: Form creation: (XSLT+JavaScript; FieldID)
  • Survey conclusions
    • Existing standards are not equally adopted by surveyed sites
    • Limited ability of existing standards to represent and distribute a query, enrolment logic and follow-up questions
    • Survey limitations
  • Future
    • New initiatives
      • ERGO and OCRe
      • New Oct 2009 release of BRIDG (ver 3.0)
      • HL7: Clinical Research Filtered Query Service
    • CTMS vendors
      • Standard adoption
      • Proprietary solutions
    Niland (2008), Sim (2008), Tu (2008), Wang (2009)