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March 13, 2007: I. Sim Informatics for Clinical TrialsEpi 206 – Medical Informatics
Ida Sim, MD, PhD
March 13, 2007
Division of General Internal Medicine, and Center for Clinical and Translational Informatics
UCSF
Informatics for Clinical Trials
Copyright Ida Sim, 2007. All federal and state rights reserved for all original material presented in this course through any medium, including lecture or print.
March 13, 2007: I. Sim Informatics for Clinical TrialsEpi 206 – Medical Informatics
Outline
• Clinical Trial Informatics– clinical trial management systems (CTMS)
– NCI/NIH vision
• Velos at UCSF Cancer Center• Running a Trial• Reporting Trials• Summary
March 13, 2007: I. Sim Informatics for Clinical TrialsEpi 206 – Medical Informatics
Biomedical Informatics Spheres
Administrative Clinical Care Research
ClinicalBilling
Physical Networking
Standard Communications Protocols (e.g., HL-7)
Standard Vocabulary
PracticeManagement
Systems
Medical BusinessData Model
ElectronicMedicalRecord
Clinical CareData Model
??
??
March 13, 2007: I. Sim Informatics for Clinical TrialsEpi 206 – Medical Informatics
CTMS
Administrative Clinical Care Research
ClinicalBilling
Physical Networking
Standard Communications Protocols (e.g., HL-7)
Standard Vocabulary
PracticeManagement
Systems
ElectronicMedicalRecord
Clinical Trial Management
Systems
Medical BusinessData Model
Clinical CareData Model
Clinical StudyData Models
March 13, 2007: I. Sim Informatics for Clinical TrialsEpi 206 – Medical Informatics
The Clinical Trial Cycle
New Ideas
Protocol & Funding
Findings
Approval &Preparation
Design Trial
Activate TrialConductTrial
UtilizeResults •trial simulators
•trial costing•protocol authoring
•IRB approval•CRF design
•data management•remote data entry•GCP compliance
•data analysis•reporting
March 13, 2007: I. Sim Informatics for Clinical TrialsEpi 206 – Medical Informatics
Anything Missing?
for patientcare & policy
for clinical researchNew Ideas
Protocol & Funding
Findings
Approval &Preparation
DesignStudy
ActivateStudy
ConductStudy
UtilizeResults for basic research
ClinicalCare
March 13, 2007: I. Sim Informatics for Clinical TrialsEpi 206 – Medical Informatics
Nothing Talks to Nothing...
New Ideas
Protocol & Funding
Findings
Approval &Preparation
Design Trial
Activate TrialConductTrial
UtilizeResults •trial simulators
•trial costing•protocol authoring
•IRB approval•CRF design
•data management•remote data entry•GCP compliance
•data analysis•reporting
March 13, 2007: I. Sim Informatics for Clinical TrialsEpi 206 – Medical Informatics
Interoperability Review
• in·ter·op·er·a·bil·i·ty– ability of a system...to use the parts or equipment
of another systemSource: Merriam-Webster web site
• interoperability– ability of two or more systems or components to
exchange information and to use the information that has been exchanged.
Source: IEEE Standard Computer Dictionary: A Compilation of IEEE Standard Computer Glossaries, IEEE, 1990]
• Syntactic -- grammar or composition of what is said• Semantic -- meaning of what is said
March 13, 2007: I. Sim Informatics for Clinical TrialsEpi 206 – Medical Informatics
2 Routes to Interoperability
• “Microsoft” approach– one end-to-end system from trial inception to end
– used by all PIs, industry, CROs, worldwide
• Modular, component-based, interfaces approach– define common terms, models, interchange
protocols
– provide software components for assembly
– provide way to “certify” compatibility of systems
March 13, 2007: I. Sim Informatics for Clinical TrialsEpi 206 – Medical Informatics
NCI CTMS in caBIG
Clinical Trial Management Infrastructure
Adverse Event Reporting
Study Calendar
Routine Data Exchange Financial Billing
Structured Protocol
Representation
Laboratory Interfaces
Clinical Trials DatabaseSystems
Interoperation
CRF Standardization
InvestigatorAnd
Site Credentialing
March 13, 2007: I. Sim Informatics for Clinical TrialsEpi 206 – Medical Informatics
NCI/NIH “xx”BIG Vision
caBIGTM Architecture WorkspacecaBIGTM Architecture Workspace
caBIGTM Vocabularies and Common Data Elements WorkspacecaBIGTM Vocabularies and Common Data Elements Workspace
Strategic Planning
Workspace
Strategic Planning
Workspace
Training Workspace
Training Workspace
Integrative Cancer
Research
Workspace
Integrative Cancer
Research
Workspace
In Vivo Imaging
Workspace
In Vivo Imaging
Workspace
Tissue Banks &
Pathology Tools
Workspace
Tissue Banks &
Pathology Tools
Workspace
Data Sharing & Intellectual
Capital Workspace
Data Sharing & Intellectual
Capital Workspace
Clinical Trials
Management Systems
Workspace
Clinical Trials
Management Systems
Workspace
March 13, 2007: I. Sim Informatics for Clinical TrialsEpi 206 – Medical Informatics
Critical Components
• Terminologies– base terms used to describe biomedical concepts
• e.g., SNOMED, NCI Thesaurus
• Common Data Elements– clinicallly-agreed upon data items for research
• e.g., “menopause” defined a certain way
• Common data model of study protocol– study information: e.g., eligibility criteria, treatment, outcomes
• CTOM, SDTM, BRIDG, etc. etc.
• Common interchange standards– so design, monitoring, reporting systems, etc. can talk
March 13, 2007: I. Sim Informatics for Clinical TrialsEpi 206 – Medical Informatics
Outline
• Clinical Trial Informatics– clinical trial management systems (CTMS)
– NCI/NIH vision
• Velos at UCSF Cancer Center• Running a Trial• Reporting Trials• Summary
March 13, 2007: I. Sim Informatics for Clinical TrialsEpi 206 – Medical Informatics
Commercial CTMSs• Functions
– document management (protocol, CRFs (Case Report Forms))
– finances, IRB– study calendar (what to do to whom when)– data management and analysis– reporting
• Examples– proprietary
• OracleClinical, C3D, Velos, etc. etc.
– open source• OpenClinica
March 13, 2007: I. Sim Informatics for Clinical TrialsEpi 206 – Medical Informatics
Cancer Center Needs
• Reports need to continue as an NCI-designated Cancer Center– e.g., trials initiated, pt demographics
• UCSF CC needed good data for reports– bought Velos eResearch in 2003 for reporting
– required all CC investigators to use Velos• licenses issued to PIs in CC and some in GCRCs
March 13, 2007: I. Sim Informatics for Clinical TrialsEpi 206 – Medical Informatics
What Gets into Velos?
• Study summary data, as free text– administrative (PI, contact info, etc)– protocol (treatments, outcomes, etc)– IRB-related
• submitted protocol, approval status, current protocol• tied into Cancer Center PRS review, but not CHR
• Patient data– PI can define CRFs, data entered would be stored
in a Velos database• basic report functions• export to SAS or Excel for analysis
March 13, 2007: I. Sim Informatics for Clinical TrialsEpi 206 – Medical Informatics
How is it Working?• Adoption
– rocky initially, better since integrated with PRS • For NCI reporting, successful• For data hosting and analysis
– just started this in 2007(!)– “easy to get data in, hard to get data out”
• biostatisticians are not too happy
• underlying data schema and access are opaque, by design
• less reponsive/customizable to reporting and analysis needs
• Not used for finances, study calendar, standardization of terms, etc.
March 13, 2007: I. Sim Informatics for Clinical TrialsEpi 206 – Medical Informatics
Outline
• Clinical Trial Informatics– clinical trial management systems (CTMS)
– NCI/NIH vision
• Velos at UCSF Cancer Center• Running a Trial• Reporting Trials• Summary
March 13, 2007: I. Sim Informatics for Clinical TrialsEpi 206 – Medical Informatics
Clinical Trial Tasks
• Investigator credentialing• Study design
– find previous trials
– design protocol, CRFs
• IRB approval• Trial registration• Participant recruitment• Randomization• Run study
– distribute CRFs, collect data per study calendar
• Analyze
March 13, 2007: I. Sim Informatics for Clinical TrialsEpi 206 – Medical Informatics
Investigator Credentialing
• For FDA-related trials, Form 1572 to be filed every year, multiple other layers of credentialing
• Today– mostly paper-based
– no coordination
• Tomorrow– one-stop, one-shop
– NCI’s caBIG priority task
– CRIX’s Firebird, collaboration of FDA, NCI, pharma
March 13, 2007: I. Sim Informatics for Clinical TrialsEpi 206 – Medical Informatics
Clinical Trial Tasks
• Investigator credentialing• Study design
– find previous trials
– design protocol, CRFs
• IRB approval• Trial registration• Participant recruitment• Randomization• Run study
– distribute CRFs, collect data per study calendar
• Analyze
March 13, 2007: I. Sim Informatics for Clinical TrialsEpi 206 – Medical Informatics
Find Previous Trials• Trial registration
– to be considered for publication in NEJM, JAMA, etc., all “hypothesis-testing” trials must be registered at inception
• 20-item Trial Registration Data Set http://www.who.int/ictrp
• in US, use ClinicalTrials.gov
– WHO Search Portal to all national/intl registers in beta• Unclear what proportion of trials are being registered
– no penalties for disobeying FDAMA law “requiring” registration of all “life-threatening” condition trials
– pending Enzi-Kennedy act will require registration and reporting of all trials
• Registration entires not routinely linked to results
March 13, 2007: I. Sim Informatics for Clinical TrialsEpi 206 – Medical Informatics
Other Sources• Published
– Medline
– Cochrane Controlled Trials Register• ~328,000 records of controlled trials
• manual logging of CCTs by hand searching journals
• accessible from UCSF machines (IP address) only
• Commercial: mostly for patient recruitment– www.centerwatch.com
– www.ClinicalTrialFinder.com
– www.controlled-trials.com
– www.clinicaltrials.com
– etc., etc., etc.
March 13, 2007: I. Sim Informatics for Clinical TrialsEpi 206 – Medical Informatics
Clinical Trial Tasks
• Investigator credentialing• Study design
– find previous trials
– design protocol, CRFs
• IRB approval• Trial registration• Participant recruitment• Randomization• Run study
– distribute CRFs, collect data per study calendar
• Analyze
March 13, 2007: I. Sim Informatics for Clinical TrialsEpi 206 – Medical Informatics
Protocol Design Assistance• Simluations
– protocol simulation• ePCRN: apply eligibility criteria to research network to estimate
potential recruitment pool
• some pharma companies use Markov models to simulate trial outcomes, couple with value-of-information theory to make go no-go decisions
– pharmacokinetics simulation available• e.g., PharSight
• Critiquing of study design– automated help is topic of informatics research (e.g.,
Design-a-Trial)– at UCSF, go to CTSI’s BREAD for advice
March 13, 2007: I. Sim Informatics for Clinical TrialsEpi 206 – Medical Informatics
Data Elements• To ensure sharable data, research data variables
should be standardized– at conceptual level, terms should be from a controlled
vocabulary (e.g., SNOMED)• e.g., SNOMED term menopause, available from NCI’s
Enterprise Vocabulary System (EVS)
– at study/scientific level, common variables should be used (e.g., NCI’s CDEs)
• e.g., menopause with full clinical definition, to be used in all breast cancer trials
• at caDSR (Data Standards Repository), you can– use existing CDEs that others have defined– you can define new CDEs using terms from EVS
March 13, 2007: I. Sim Informatics for Clinical TrialsEpi 206 – Medical Informatics
Case Report Forms
• Why reinvent the wheel for common forms?• caDSR has a Forms Builder
– pull together CDEs into CRFs• can download as HTML, XML, Excel, Word, PDF
• Homework #5 due Friday, March 23– http://cdebrowser.nci.nih.gov/CDEBrowser/
• NCI now building library of CRFs – e.g., Demographics CRF built from CDEs
• PDF, Word, etc. or directly to CTMS for direct data entry
• Velos– can design CRFs in Velos, with direct access to NCI’s CDEs– if caBIG compatible, could in future access NCI’s CRF
library directly
March 13, 2007: I. Sim Informatics for Clinical TrialsEpi 206 – Medical Informatics
Clinical Trial Tasks
• Investigator credentialing• Study design
– find previous trials
– design protocol, CRFs
• IRB approval• Trial registration• Participant recruitment• Randomization• Run study
– distribute CRFs, collect data per study calendar
• Analyze
March 13, 2007: I. Sim Informatics for Clinical TrialsEpi 206 – Medical Informatics
IRB Approval
• IRBs very fragmented, overwhelmed– institutional (e.g., university, community hosp)– for-profit (e.g., Western IRB certifies majority of
commerical trials)• Large overlap of jurisdiction
– multi-site trials, international trials, etc.• Some exploration of new IRB models
– e.g., one NIH IRB, regional IRBs, etc• For now, no coordination, good luck...
March 13, 2007: I. Sim Informatics for Clinical TrialsEpi 206 – Medical Informatics
Clinical Trial Tasks
• Investigator credentialing• Study design
– find previous trials
– design protocol, CRFs
• IRB approval• Trial registration• Participant recruitment• Randomization• Run study
– distribute CRFs, collect data per study calendar
• Analyze
March 13, 2007: I. Sim Informatics for Clinical TrialsEpi 206 – Medical Informatics
Trial Registration
• By “responsible registrant”– PI or sponsor (e.g., pharma) or NIH Project Officer
• Today– diffuse responsibility, risk
of duplicate registration, double-entry required
– http://prsinfo.clinicaltrials.gov/ for US
• Tomorrow– registration “falls out” of CTMS
trial design and/or IRB approval modules
– trial gets a UTRN (Universal Trial Reference Number)
– indexed in WHO Register Network
March 13, 2007: I. Sim Informatics for Clinical TrialsEpi 206 – Medical Informatics
Clinical Trial Tasks
• Investigator credentialing• Study design
– find previous trials
– design protocol, CRFs
• IRB approval• Trial registration• Participant recruitment• Randomization• Run study
– distribute CRFs, collect data per study calendar
• Analyze
March 13, 2007: I. Sim Informatics for Clinical TrialsEpi 206 – Medical Informatics
Eligibility Determination
• Study enrollment is big bottleneck• Eligible patients: patients whose characteristics
match with eligibility criteria• For computerized matching, need to have
computer-interpretable descriptions of– patient characteristics
– the eligibility criteria
Match Eligible Patients
EHR
Eligibility Rule
March 13, 2007: I. Sim Informatics for Clinical TrialsEpi 206 – Medical Informatics
Eligibility Example• Eligibility criterion: women who are 2 or fewer years
post-menopause, as defined in NCI’s Common Data Elements set
• Allowed values:Above categories not applicable AND Age < 50
Above categories not applicable AND Age >=50
Post (Prior bilateral ovariectomy, OR >12 mo since LMP with no prior hysterectomy and not currently receiving therapy with LH-RH analogs [eg. Zolades])
Post (Prior bilateral ovariectomy, OR >12 mo since LMP with no prior hysterectomy)
Pre (<6 mo since LMP AND no prior bilateral ovariectomy, AND not on estrogen replacement)
March 13, 2007: I. Sim Informatics for Clinical TrialsEpi 206 – Medical Informatics
EHR Data Needed
• Gender• Age• Time since LMP, whether
– 6 or fewer months, or 12 or more months
• Past surgical history– bilateral ovariectomy and/or hysterectomy
• Therapy– LH-RH analogs, or
– estrogen replacement
March 13, 2007: I. Sim Informatics for Clinical TrialsEpi 206 – Medical Informatics
Computable Eligibility Rules
• Logical rules– (Prior bilateral ovariectomy) OR
(>12 mo since LMP AND no prior hysterectomy)• Temporal constraints
– greater than 12 months since LMP...– representing time requires second-order logic
• Can do simple cases with database rules and triggers• More robust solution not yet available
– CDISC, HL7, NCI, Trial Bank Project all working on related standards
• syntactic: how to express logical and temporal meaning• clinical: standard eligibility rules for particular domains (e.g., breast
cancer)
March 13, 2007: I. Sim Informatics for Clinical TrialsEpi 206 – Medical Informatics
Need to Query EHR
itsa
coordcenter with DSS
ucsf.edu
LAN
Site 1/GE EHR Site 2/Epic EHR
1. Is C. Jones eligible for this trial?
2. …Exclusion Rule #3: Does C. Jones have a history of congestive heart failure?
3. Return Yes if “congestive heart failure” is in Past Medical History
HL-7 communications protocol
4. If Yes to history of CHF, C. Jones is not eligible
March 13, 2007: I. Sim Informatics for Clinical TrialsEpi 206 – Medical Informatics
Promising, but...
• Coding of eligibility rules is difficult• Richly detailed, coded EHR not widely
available– need a common EHR model (e.g., HL7 CDA v 2)
• At present, can only expect computer to suggest potential subjects. EHR can– prompt MD in real-time to refer patient to study, or– periodically batch notify MD of eligible patients, or– send letter of solicitation to patients
• Similar problems bedevil automated identification of guideline eligibility
March 13, 2007: I. Sim Informatics for Clinical TrialsEpi 206 – Medical Informatics
Clinical Trial Tasks
• Investigator credentialing• Study design
– find previous trials
– design protocol, CRFs
• IRB approval• Trial registration• Participant recruitment• Randomization• Run study
– distribute CRFs, collect data per study calendar
• Analyze
March 13, 2007: I. Sim Informatics for Clinical TrialsEpi 206 – Medical Informatics
• Requirements– a web-based data collection form to collect patient
information– programs to verify eligibility and randomize patient– program to generate a response to the enroller
– security, privacy, and backup provisions• Commercial systems available for this
Web-based Randomization
Project Central Enroller
patient info
randomization results
March 13, 2007: I. Sim Informatics for Clinical TrialsEpi 206 – Medical Informatics
Clinical Trial Tasks
• Investigator credentialing• Study design
– find previous trials
– design protocol, CRFs
• IRB approval• Trial registration• Participant recruitment• Randomization• Run study
– distribute CRFs, collect data per study calendar
• Analyze
March 13, 2007: I. Sim Informatics for Clinical TrialsEpi 206 – Medical Informatics
Study Calendar
• Protocol-driven care: what to do to whom when– alert and reminder functions
– should be integrated to protocol and EHR
• Available in some CTMS products– e.g., Velos, OracleClinical
• Same informatics issues for supporting guideline-based care
March 13, 2007: I. Sim Informatics for Clinical TrialsEpi 206 – Medical Informatics
Distributing CRFs• e.g., from a project website
– latest protocol, IRB approvals, CRFs, listservs, etc.• Requirements
– a web server• internal to UCSF
– free web hosting by UCSF OAAIS– free hosting by School of Medicine if using SOM templates
» if your own design, $22-89/mo
• external web hosting service (see http://www.cnet.com/)– website design
• School of Medicine: 80 hours free design if use their templates– if using your own design, $62/hr for design services
• Note recent design guidelines from UCSF Pub Affairs
March 13, 2007: I. Sim Informatics for Clinical TrialsEpi 206 – Medical Informatics
CRF Distribution
itsa
smoking
ucsf.edu
KaiserOakland
KaiserSanta Clara
Internet
at homedial-in to itsa.ucsf.edu via modem
pacbell.net
aol.com
LAN
KaiserSan Diego
• “smoking.ucsf.edu” “serves” forms such ashttp://smoking.ucsf.edu/case-form.pdf for printing out
March 13, 2007: I. Sim Informatics for Clinical TrialsEpi 206 – Medical Informatics
Electronic Data Capture (1)
• Capturing data from manual entry into CRFs– “active” CRFs must be served over the web
• e.g., basic HTML to fancy ActiveX, Ajax, etc. input forms
– need security mechanisms• e.g., user login, timeouts, audit trails
– need data validation checks built into forms entry• e.g., age between 0 and 120
– input forms must send data directly to a database• needs ODBC (Open DataBase Connectivity) drivers, etc.
• e.g., using Access Visual Basic, Access and FrontPage, any other back end database (Oracle, mySQL, etc.)
March 13, 2007: I. Sim Informatics for Clinical TrialsEpi 206 – Medical Informatics
Capturing Smoking CRF Data
itsa
smoking
ucsf.edu
KaiserOakland
KaiserSanta Clara
Internet
at homedial-in to itsa.ucsf.edu via modem
pacbell.net
aol.com
LAN
KaiserSan Diego
• “smoking.ucsf.edu” “serves” online entry formssuch as http://smoking.ucsf.edu/case-form.asp.Users enter data, which get checked at the clientside, and data is sent back to “smoking.ucsf.edu.”
March 13, 2007: I. Sim Informatics for Clinical TrialsEpi 206 – Medical Informatics
Electronic Data Capture (2)
• From EHR– CTMS needs to know how to access particular data
items in an EHR• e.g., get Mrs. Jones’ serum K+ on March 3, 2006
– which table, which data element, name of data element?
– need a standard EHR data model, so CTMSs can get serum K+ from any EHR without having to know each EHR’s relational database schema
– need standard vocabulary for data element names...
• Bottom line...not happening
March 13, 2007: I. Sim Informatics for Clinical TrialsEpi 206 – Medical Informatics
Clinical Trial Tasks
• Investigator credentialing• Study design
– find previous trials
– design protocol, CRFs
• IRB approval• Trial registration• Participant recruitment• Randomization• Run study
– distribute CRFs, collect data per study calendar
• Analyze
March 13, 2007: I. Sim Informatics for Clinical TrialsEpi 206 – Medical Informatics
Analyzing Data
• Almost all systems can export a “flat file” to SAS, STATA, etc.– Velos exports to SAS, Excel, etc.
• Can share views of Access database on web
Access DB
Internet Information Server 4.0
KaiserOakland
KaiserSanta Clara
Internet
KaiserSan Diego
Active Server Pages (ASP)
smoking.ucsf.edu
March 13, 2007: I. Sim Informatics for Clinical TrialsEpi 206 – Medical Informatics
Clinical Trial Tasks Summary
• Investigator credentialing• Study design
– find previous trials– design protocol, CRFs
• IRB approval• Trial registration• Participant recruitment• Randomization• Run study• Analyze
Clinical Trial Tasks SummaryTask Today Tomorrow FutureCredentialing ✓
Study design
find trials ✓ ✓ ✓
protocol design ✓
CRF design ✓ ✓ ✓
IRB approval ✓?
Trial registration ✓ ✓ ✓
Recruitment ✓ ✓ ✓
Randomization ✓ ✓
Run study
project website ✓ ✓
EDC from EHR ✓
Analyze ✓
March 13, 2007: I. Sim Informatics for Clinical TrialsEpi 206 – Medical Informatics
Outline
• Clinical Trial Informatics– clinical trial management systems (CTMS)
– NCI/NIH vision
• Velos at UCSF Cancer Center• Running a Trial• Reporting Trials• Summary
March 13, 2007: I. Sim Informatics for Clinical TrialsEpi 206 – Medical Informatics
Data Aggregation Across Trials
• How many Phase III RCTs does NIH fund?• What percentage of depression RCTs are
placebo-controlled?• What percentage of patients in CHF trials
have renal failure?• Which acute MI trials report 5 year mortality?• Is industry funding correlated with positive
outcomes?• What percentage of trials report outcome
results selectively?
March 13, 2007: I. Sim Informatics for Clinical TrialsEpi 206 – Medical Informatics
Trial Results Reporting• Publication bias now recognized
– ICMJE requires trial registration & protocols to be submitted with manuscripts, to ensure full and complete reporting
• Results reporting policies– NIH: all grants over $500,000 direct required to
“report all data publicly”
– CIHR, UK, and EU moving towards mandatory reporting
– WHO defining required “Minimum Trial Report”
March 13, 2007: I. Sim Informatics for Clinical TrialsEpi 206 – Medical Informatics
Results Databases
• Should be computable and sharable– Trial Bank Project rctbank.ucsf.edu
• computable reporting: RCT data model, UMLS terms...
• Results database initiatives– ClinicalTrials.gov under pressure from Congress
– caBIG Clinical Trials Database of results
– European Union “Clinical Trials Data Repository”
– Global Trial Bank
March 13, 2007: I. Sim Informatics for Clinical TrialsEpi 206 – Medical Informatics
Globally Integrated Knowledge
• Results databases need to interoperate to– WHO Registers Network
– bioinformatics databases• DNA sequences: GenBank
• metabolic pathways: BioCyc
• pharmacogenetics, pharmacogenomics: PharmGKB
• protein sequence: UniProt
• protein structure: PDB
• SNPs: SNPdB, etc.
• and to EHRs, for clinical decision support
March 13, 2007: I. Sim Informatics for Clinical TrialsEpi 206 – Medical Informatics
Outline
• Clinical Trial Informatics– clinical trial management systems (CTMS)
– NCI/NIH vision
• Velos at UCSF Cancer Center• Running a Trial• Reporting Trials• Summary
March 13, 2007: I. Sim Informatics for Clinical TrialsEpi 206 – Medical Informatics
Summary
• Clinical trials still mostly paper– fragmented systems, lack of wide EHR adoption, lack of
standard clinical and research coding
• Commercial CTMSs – mostly document centered (e.g., PDF) rather than
computable data
– some are more caBIG compatible (e.g., Velos)
– UCSF plans for CTMS support are not yet defined
• Great changes happening...towards eScience?– in NIH investment in clinical trial informatics infrastructure
– in trial registration and reporting for knowledge management
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