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February 26, 2013: I. Sim APEX, etc. at UCSFEpi 206 — Medical Informatics
Ida Sim, MD, PhD
February 26, 2013
Division of General Internal Medicine, and Center for Clinical and Translational Informatics
UCSF
Clinical Research Informatics
Copyright Ida Sim, 2013. All federal and state rights reserved for all original material presented in this course through any medium, including lecture or print.
February 26, 2013: I. Sim Research InformaticsEpi 206 — Medical Informatics
Outline
• Systems for traditional clinical research• UCSF clinical research information systems
– REDCap– MyResearch– IDR Cohort Selection Tool– CELDAC
• Translational informatics
Big Picture of Health Informatics
Virtual Patient
Transactions
Raw data
Medical knowledge
Clinical research
transactions
Raw research
data
Dec
isio
n su
ppor
t
Med
ical
logi
c
CLINICAL CARE RESEARCH
Workflow modeling and support, usability, cognitive support, computer-supported cooperative work (CSCW), etc.
CTMSs
WELLNESS
February 26, 2013: I. Sim Research InformaticsEpi 206 — Medical Informatics
IRB Funding Agency
Study DB
Data analysis
Results reporting
Contract R
esearch O
rganization (C
RO
)
Protocol
Trial DesignSponsorsAcademic PIs
?Site 1 Site 2 Site 3
Site Management Organization (SMO)
Clinical Research Today
>80% on paper
February 26, 2013: I. Sim Research InformaticsEpi 206 — Medical Informatics
Clinical Trial Management Systems
• Clinical Trial Management Systems (CTMS) are for running/managing a study– document management (protocol, case report forms)– finances, IRB– study calendar (what to do to whom when) and data
entry– data management and analysis– reporting
February 26, 2013: I. Sim Research InformaticsEpi 206 — Medical Informatics
EHR vs. CTMS Contents
• EHR• Patient demographics• Chart notes
– problem list• Visit and assessment• Lab and other orders• Lab and other results• Clinical decision-making• Discharge summary
• CTMS• Title, NCT #, IRB #• Protocol document
– interventions, design,
outcomes, etc.• Study assessment• Outcomes assessment• Case report forms• Data analysis• Trial reporting/publication
February 26, 2013: I. Sim Research InformaticsEpi 206 — Medical Informatics
Just Like Need for EHR…
• Clinical trials are becoming very complex– avg 460 days (2002) to 780 days (2006)– avg # of participants: 1700 to 3400 over 30 yrs– # of study procedures: 70% increase to 85 procedures, from
2000 to 2005
• Fragmented, global industry– estimated 1100 organizations involved in clinical research in
2009 in US (Sponsors, CROs, SMOs, AHCs...)
– “43% big pharma FDA trials were conducted abroad... projecting as much as 65% within 3 years” [Tufts Outlook 2008]
• Can we afford to do this all in paper??
Tufts Center for the Study of Drug Development, “Growing Protocol Design Complexity Stresses Investigators, Volunteers,” Impact Report 10, no. 1 (January/February 2008).
February 26, 2013: I. Sim Research InformaticsEpi 206 — Medical Informatics
IRB
Trial Design
Protocol
Funding Agency
Site 1 Site 2 Site 3
Site Management Organization (SMO)
Study DB
Data analysis
Results reporting
Contract R
esearch Organ
ization
(CR
O)
SponsorsAcademic PIs
?
Need to Interoperate Multiple Systems
February 26, 2013: I. Sim Research InformaticsEpi 206 — Medical Informatics
Interoperation
• Ability of two or more systems or components to exchange information and to use the information that has been exchanged [IEEE Standard Computer Dictionary, 1990]
– syntactic: grammar, composition of what is said• e.g., using an exchange protocol over networks• e.g., HL7, DICOM, XML Document Type Definition (DTD)
– semantic: meaning of what is said• e.g., using a controlled vocabulary aka dictionary• e.g., SNOMED, ICD-9
February 26, 2013: I. Sim Research InformaticsEpi 206 — Medical Informatics
MICU
FinanceResearch
QA
Clinical / ResearchData Repository
Internet
ADT Chem EHR XRay PBM Claims
• How do the machines “talk” to each other?
Networking Basics
February 26, 2013: I. Sim Research InformaticsEpi 206 — Medical Informatics
Internet = Network of Networks
itsa
medicine
ucsf.edu
nci.nih.gov
“the cloud”
myhome.com
Main Trunk Cables
local trunk cablethrough Berkeley
amazon.com
at homedial-in to itsa.ucsf.edu via modem
pacbell.net
aol.com
Internet Service Provider (ISP)via DSLor cable
LAN
February 26, 2013: I. Sim Mobile and Internet-Based ResearchEpi 206 – Medical Informatics
Clients and Servers
itsa
medicine
ucsf.edu
nci.nih.gov
“the cloud”
myhome.com
Main Trunk Cables
local trunk cablethrough Berkeley
amazon.com
at homedial-in to itsa.ucsf.edu via modem
pacbell.net
aol.com
Internet Service Provider (ISP)via DSLor cable
LAN
Server
Client
February 26, 2013: I. Sim Mobile and Internet-Based ResearchEpi 206 – Medical Informatics
What Happens over the Cables
• Internet = network of networks– computers and cables all linked to one another and
talking to one another using protocols – supports lots of different internet protocols
• Protocol = “grammar” for machines talking to each other– e.g., hypertext transfer protocol http for web
• http://www.epibiostat.ucsf.edu/courses/schedule/med_informatics.html
– e.g., ftp file transfer protocol, smtp, https, etc. etc.– all sit on top of basic networking protocol TCP/IP
February 26, 2013: I. Sim Research InformaticsEpi 206 — Medical Informatics
• Web is the internet traffic that uses http– servers send out information in HTML
• Hypertext Markup Language
– web browsers can decode HTML and display it• Health-specific protocols needed “on top of” http or
TCP/IP– a “grammar” for how to exchange health-related data
Internet vs. Web
February 26, 2013: I. Sim Research InformaticsEpi 206 — Medical Informatics
Health Data Interchange Protocols• HL7, “containers” for data packages, e.g., lab
• DICOM, “containers” for radiology studies– machine used, type of study, # of images, etc.
• CCD (Continuity of Care Document) for EHR data interchange (official standard under Meaningful Use)– e.g., problem list, allergies, family history– supplanted by NHIN Direct?
• “Containers” do not address the data naming issue– e.g., Na, sodium, serum sodium -- need to standardize to a SNOMED code
MSH|…message headerPID|…patient identifier<!-OBX…observation result>OBX|1|ST|84295^NA||150|mmol/l|136-148|H||A|F|19850301<CR>
February 26, 2013: I. Sim Research InformaticsEpi 206 — Medical Informatics
Interoperation Over the Stack
Administrative Clinical Care Research
ClinicalBilling
Physical Networking
Communications Protocols (e.g., HL-7)
Standard Vocabulary
PracticeManagement
Systems
Medical BusinessData Model
ElectronicMedicalRecord
Clinical CareData Model
Clinical Res. Management
Systems
Clinical StudyData Models
Syn
tact
icS
em
ant
ic a
nd
Wo
rkflo
w
February 26, 2013: I. Sim Research InformaticsEpi 206 — Medical Informatics
Sharing Research Meaning
Administrative Clinical Care Research
ClinicalBilling
Physical Networking
Communications Protocols (e.g., HL-7)
Standard Vocabulary
PracticeManagement
Systems
Medical BusinessData Model
ElectronicMedicalRecord
Clinical CareData Model
Clinical Res. Management
Systems
Clinical StudyData Models
Syn
tact
icS
em
ant
ic a
nd
Wo
rkflo
w
February 26, 2013: I. Sim Research InformaticsEpi 206 — Medical Informatics
Study Protocol
• Study protocol is core essence of a research study– the investigational plan, including the actions to be
undertaken, the measurements, and the analysis
procedures to be followed– is not the same as the study protocol document (i.e.,
the Word or PDF file)• SPIRIT standard protocol items for clinical trials
– http://annals.org/article.aspx?articleid=1556168
February 26, 2013: I. Sim Research InformaticsEpi 206 — Medical Informatics
Components of a Study Protocol• Who
– participants: eligibility criteria, recruitment, followup– investigators: PI, sponsors, advisors, etc.
• What– interventions or exposures: experimental, control– study outcomes: primary, secondary, baseline
• When– dates of enrollment, timing of assessments
• Where– study sites
• Why– background, objective, hypothesis
• How– analytic approach, study monitoring, outcomes adjudication, etc.
February 26, 2013: I. Sim Research InformaticsEpi 206 — Medical Informatics
Computable Protocol
Administrative Clinical Care Research
ClinicalBilling
Physical Networking
Communications Protocols (e.g., HL-7)
Standard Vocabulary
PracticeManagement
Systems
Medical BusinessData Model
ElectronicMedicalRecord
Clinical CareData Model
Clinical Res. Management
Systems
Computable Protocol
Syn
tact
icS
em
ant
ic a
nd
Wo
rkflo
w
February 26, 2013: I. Sim Research InformaticsEpi 206 — Medical Informatics
Need Standardization On...
• Common computable study protocol– the study plan: e.g., eligibility criteria, treatment, outcomes
• Ontology of Clinical Research1, SDTM, BRIDG, etc. etc.
• Common variables (aka common data elements, CDEs)– see Clarke M, Trials 2007,e.g.,
• “menopause” definition to standardize enrolled population • common outcomes for data pooling, meta-analysis (e.g., “MI”)
• Terminologies/vocabularies– base terms used to describe biomedical concepts
• e.g., SNOMED, NCI Thesaurus
• Common interchange standards– e.g., CDISC (“HL7 for clinical research”)
1http://rctbank.ucsf.edu/home/ocre
February 26, 2013: I. Sim Research InformaticsEpi 206 — Medical Informatics
Sharing and Standardization
• …of research variables– PhenX Toolkit https://www.phenxtoolkit.org/
• a catalog of high-priority measures (e.g., MI) for genome-wide association studies (GWAS) and other studies
• NIDA requires Tier 1 substance abuse measures– PROMIS http://nihpromis.org/'s assessment library– NCI library of Common Data Elements (CDEs)– CDISC SHARE: industry, NCI, FDA http://www.cdisc.org/cdisc-share
– AHRQ Registry of Patient Registries CDE outcome measures– RedCAP see demo
• …of case report forms (NCI, OpenClinica, etc.)
February 26, 2013: I. Sim Research InformaticsEpi 206 — Medical Informatics
Summary: Sharing Research Data
• Interoperation = meaningful exchange of data among computers– syntactic: how things are said, the grammar– semantic: what is said, the meaning
• Semantic standardization a greater challenge in research than clinical care– need a common computable protocol model– need to be very precise, research needs change as
knowledge grows, researchers very individualistic• Moving towards standardized, coded variables• Culture of sharing is still new
February 26, 2013: I. Sim Research InformaticsEpi 206 — Medical Informatics
Outline
• Systems for traditional clinical research• UCSF clinical research information systems
– REDCap– MyResearch– IDR Cohort Selection Tool– CELDAC
• Translational informatics
February 26, 2013: I. Sim Research InformaticsEpi 206 — Medical Informatics
via iMedRIS
Funding Agency
MyResearch
Data analysis
Results reporting
On
cor C
RM
S
Protocol
Trial DesignSponsorsAcademic PIs
IRB
Site 1 Site 2 Site 3
Site Management Organization (SMO)
UCSF Research Info Systems
Integrated Data Repository
REDCap
APEX
February 26, 2013: I. Sim Research InformaticsEpi 206 — Medical Informatics
REDCap
• Web-based tool for building study databases and defining data entry forms– https://redcap.ucsfopenresearch.org/– https://redcap.ucsfopenresearch.org/index.php?ac
tion=training– is HIPAA-compliant (unlike Survey Monkey)
• Available to you for free
Other Data Collection Tools
• Web-based– RedCAP– SurveyMonkey, Datstat, etc.
• Mobile– see http://ctsi.mobiledata.sgizmo.com/s3– UCSF has BAA with Qualtrics• See this for more pointers:
https://www.ctspedia.org/do/view/CTSpedia/SoftwareInterviewing
February 26, 2013: I. Sim Research InformaticsEpi 206 — Medical Informatics
February 26, 2013: I. Sim Research InformaticsEpi 206 — Medical Informatics
via iMedRIS
Funding Agency
MyResearch
Data analysis
Results reporting
On
cor C
RM
S
Protocol
Trial DesignSponsorsAcademic PIs
IRB
Site 1 Site 2 Site 3
Site Management Organization (SMO)
Where Should Data Go?
Integrated Data Repository
REDCap
APEX
February 26, 2013: I. Sim Research InformaticsEpi 206 — Medical Informatics
No More Lax Storage
• Storing Protected Health Information (PHI) on laptops, unsecured desktops is bad– mid 2000’s cancer registry
theft
• CA law: you can be fined up to $250,000 for PHI breach– $1 million MGH penalty– 57,000 Stanford patients
data lost in MD car
PI #2
PI #1
February 26, 2013: I. Sim Research InformaticsEpi 206 — Medical Informatics
• PHI stored in FISMA level secure database
• Data never physically leaves MyResearch
• Your browser is a “dumb” window onto the MyResearch computer– SAS, etc. runs on data
on MyResearch– you see pixels only, no
local caching on your
computer
MyResearch
MyResearch
Secure location with backup
SAS, R
Firewall
Pixels only
Secure Global Desktop
February 26, 2013: I. Sim Research InformaticsEpi 206 — Medical Informatics
Using MyResearch
• Satisfies CHR criteria for secure data storage
• Works on PC, Mac with Leopard, Unix
• Free access to analytic software
• Need Internet connection to do your work (like Google Docs)
• http://myaccess.ucsf.edu – go to MyResearch
February 26, 2013: I. Sim Research InformaticsEpi 206 — Medical Informatics
via iMedRIS
Funding Agency
MyResearch
Data analysis
Results reporting
On
cor C
RM
S
Protocol
Trial DesignSponsorsAcademic PIs
IRB
Site 1 Site 2 Site 3
Site Management Organization (SMO)
Accessing Clinical Data
Integrated Data Repository
REDCap
APEX
February 26, 2013: I. Sim Research InformaticsEpi 206 — Medical Informatics
MICU
FinanceResearch
QA
IntegratedData Repository
Internet
ADT Chem EHR XRay PBM Claims
• autofeed nightly, data stored securely with backup
Data from UCare to IDR
Real Time "IDR" Mining
• Pediatricians at Stanford admitted a 13 year-old with lupus, nephrosis, antiphospholipid antibodies, pancreatitis– anti-coagulate or not? no formal or informal evidence available
• Consulted STRIDE (Stanford version of "IDR") in real time, over 4 hours– full text searching identified 98 pedi lupus patients between
Oct. 2004 and July 2009– 10 developed thrombosis (per EHR), RR 14.7 with nephrosis,
RR 11.8 with pancreatitis
• Patient was anti-coagulated within 24 hours of admission
February 26, 2013: I. Sim Research InformaticsEpi 206 — Medical Informatics
Frankovich, et al. NEJM 2011; 365(19):1758-9
UCSF CELDAC
Comparative Effectiveness Large Dataset Analysis Core (CELDAC), 80+ local and national health datasets
February 26, 2013: I. Sim Research InformaticsEpi 206 — Medical Informatics
Other Integrated Data Sets
• ICPSR (Inter-University Consortium for Political and Social Research)– 500,000 files, 16
specialized collections– 206 files under Health
Care and Facilities• ICPSR has its own
terminology for cross-walking the data sets
February 26, 2013: I. Sim Research InformaticsEpi 206 — Medical Informatics
February 26, 2013: I. Sim Research InformaticsEpi 206 — Medical Informatics
Research Informatics at UCSF
• Oncore clinical research management system for large studies
• RedCAP available for secure surveys– web-based and mobile– standard variables increasingly available in a library
• Must keep all data/analyses in MyResearch environment– heavy penalties for data breaches
• Beta version of Cohort Selection Tool for identifying UCare patient data
• CELDAC for large public datasets • Use of APEX for research is lower priority than clinical
roll-out
February 26, 2013: I. Sim Research InformaticsEpi 206 — Medical Informatics
Outline
• Systems for traditional clinical research• UCSF clinical research information systems
– REDCap– MyResearch– IDR Cohort Selection Tool– CELDAC
• Translational informatics
February 5, 2013: I. Sim OverviewMedical Informatics
Virtual Patient
Transactions
Raw data
Medical knowledge
Clinical research
transactions
Raw research
data
Dec
isio
n su
ppor
t
Med
ical
logi
c
CLINICAL CARE RESEARCH
Workflow modeling and support, usability, cognitive support, computer-supported cooperative work (CSCW), etc.
WELLNESS
Biophysio-logical knowledge
Translational Bioinformatics
February 26, 2013: I. Sim Research InformaticsEpi 206 — Medical Informatics
predictive, preventive, personalized, participatory
Informatics for P4 medicine
Sarkar, et al. JAMIA 2011; 18:354-7
Bioinformatics More "Advanced"
• Multitude of large-scale data– genome, phenome, metabolome, microbiome, etc.
• Established culture of data sharing– far less proprietary hoarding– common standards
• Gene Ontology, Minimum Information About a Microarray
Experiment (MIAME), Minimum Information About a
Proteomics Experiment (MIAPE), etc.
– large public datasets (GenBank, PharmGKB,
dbGAP, etc)
February 26, 2013: I. Sim Research InformaticsEpi 206 — Medical Informatics
Need System/Complexity Sciences
February 26, 2013: I. Sim Research InformaticsEpi 206 — Medical Informatics
• Bioinformatics data no longer the bottleneck; interpretation is
• Complexity is the study of complex adaptive systems– a collection of individual agents that can act in unpredictable
ways, and whose actions are interconnected so that one agent’s actions changes the context for other agents
– e.g., living cells, the brain, the immune system, the financial markets, ecosystems, and human populations
• Non-linear, self-organizing systems with feedback loops that cannot be understood simply by analyzing the individual components
From Data to Models
• Models– metabolic pathways, – multiscale models
February 26, 2013: I. Sim Research InformaticsEpi 206 — Medical Informatics
Five Rings of Human Health
Schatz, BR, et al. Healthcare Infrastructure: Health Systems for Individuals and Populations. Springer, 2013.
Bio/Clinical Informatics at UCSF
• Nascent Institute for Computational Health Sciences (ICHS)• CTSI and other resources
– Cancer Informatics– UC BRAID BioBank and EngageUC
• standards for biosamples; obtaining, processing, sharing biospecimens
across all 5 UCs
– CTSI Consultation Services in Bioinformatics– UCSF Core services
• Training and classes– UCSF Bioinformatics PhD and Graduate Group– Translational Bioinformatics and Clinical Research Informatics
Summit, SF, March 18-22– Stanford Bioinformatics Graduate Certificate
February 26, 2013: I. Sim Research InformaticsEpi 206 — Medical Informatics
February 26, 2013: I. Sim Research InformaticsEpi 206 — Medical Informatics
Summary: Research Informatics
• Clinical research fragmented, global, essentially separate from clinical care
• Clinical research informatics ongoing in two worlds– most still paper, commercial CTMSs mostly document centered (PDFs)– moving towards modular component approach with standard data
elements (CDEs) and case report forms (CRFs)
• Translational bioinformatics going from data tsunami to need for models and complexity sciences
• Will EHRs, clinical informatics, translational bioinformatics, and digital health all come together?
February 5, 2013: I. Sim OverviewMedical Informatics
Next Classes
• New Clinical Research Paradigms
• Research Designs and Methods in the Digital Age