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Peter J. Embi, MD, MS, FACP, FACMI
Assoc Prof & Vice Chair, Dept of Biomedical Informatics
Associate Professor of Medicine
Chief Research Information Officer
Co-Director, Biomedical Informatics, CCTS
The Ohio State University
San Francisco, California
March 22, 2013
Approach to this presentation
 Mixed approach to article identification:
 Started with structured approach
 (akin to ACP “update” sessions)
 Augment with “what seemed interesting” approach
 Learned a lot from doing this last two years
 Tracked manuscripts throughout the year
 (still worked down to the wire)
 So, what was my approach…
Source of Content for Session
 Literature review:
 Initial search by MESH terms:
 ("Biomedical Research"[Mesh] NOT "Genetic
Research"[Mesh]) NOT "Translational Research"[Mesh]) AND
"Informatics"[Mesh] AND "2012/01/01"[PDat] :
"2013/02/01"[Pdat]
 Resulted in 90 articles; 33 were CRI relevant
 Additional 483 articles found via:
 Recommendations from colleagues
 Other keyword searches using terms like:
 Clinical Trials, Clinical Research, Informatics, Translational, Data
Warehouse, Research Registries, Recruitment
 Yielding 48 more CRI-relevant articles, for a total of…
 Result = 81 total CRI relevant
 From those, I’ve selected 35 representative papers that
I’ll present here (briefly)
Session caveats
 What this is not…
 A systematic review of the literature
 An exhaustive review
 What this is…
 My best attempt at briefly covering some of the
representative CRI literature from the past year
 A snap-shot of excellent CRI activity over past year
 What I thought was particularly notable
Clinical and Translational Research & Informatics:
T1, T2, and Areas of Overlap for Informatics
Shaded CRI Region is Main Area of Focus
Embi & Payne, JAMIA 2009
Topics
 Grouped 35 articles into several CRI categories
(admittedly, not all CRI areas)
 Clinical Data Re-Use for Research
 Data/Knowledge Management & Discovery
 Researcher Support & Resources
 Participant Recruitment
 Policy & Perspectives
 In each category, I’ll highlight a few key articles
and then given a quick “shout out” to a few others
 Conclude with notable events from the past year
Apologies up front
 I’m CERTAIN I’ve missed a lot of great work
 I’m REALLY SORRY about that
Clinical Data Re-Use for Research
“Patient characteristics associated with venous
thromboembolic events: a cohort study using pooled
electronic health record data.” (Kaelber DC et al,
JAMIA, 2012)
 Goal: Demonstrate the potential of de-identified clinical
data from multiple systems using different EHRs to be
used for large retrospective cohort studies
 Methods: Data of 959,030 patients, pooled, standardized
and normalized using common ontologies, searchable
through a HIPAA-compliant, patient de-identified web
application (Explore; Explorys Inc). Patients were 26 years
or older seen in multiple healthcare systems from 1999 to
2011 with data from EHR.
“Patient
characteristics
associated with
venous
thromboembolic
events: a cohort
study using
pooled electronic
health record
data.”
(Kaelber DC et al,
JAMIA, 2012)
“Patient characteristics associated with venous
thromboembolic events: a cohort study using pooled
electronic health record data.” (Kaelber DC et al,
JAMIA, 2012)
 Results: Comparing obese/tall subjects with normal
weight/short subjects, the venous thromboembolic events
(VTE) OR was 1.83 for women and 1.21 for men. Weight
had more effect then height on VTE. Compared with
Caucasian, Hispanic/Latino subjects had a much lower risk
of VTE (female OR 0.47; male OR 0.24) and African-
Americans a substantially higher risk (female OR 1.83,;
male OR 1.58). This 13-year retrospective study of almost
one million patients was performed over approximately 125
h in 11 weeks, part time by the five authors.
 Conclusion: Informatics approaches to pool EHR-derived
clinical will provide opportunities for CRI to transform the
scale and resources needed to perform certain types of
clinical research. Potential to achieve results similar to
much more costly, time-intensive study approaches.
“QT interval and antidepressant use: a cross
sectional study of electronic health records.”
(Castro VM, et al, BMJ, 2013)
 Objective: To quantify the impact of citalopram and other
selective serotonin reuptake inhibitors on corrected QT
interval (QTc), a marker of risk for ventricular arrhythmia, in
a large and diverse clinical population.
 Method: Cross-sectional study using EHR-data (ECGs,
Rx, Clinical) to explore relation between antidepressant
dose and QTc. 38,397 adult patients with an
electrocardiogram recorded after prescription of
antidepressant or methadone between February 1990 and
August 2011.
“QT interval and antidepressant use: a cross
sectional study of electronic health records.”
(Castro VM, et al, BMJ, 2013)
 Results: Dose-response association with QTc prolongation
was identified for citalopram, escitalopram, and
amitriptyline, but not for other antidepressants examined.
An association with QTc shortening was identified for
bupropion. Within-subject paired observations supported
the QTc prolonging effect of citalopram.
 Conclusions: Confirmed modest prolongation of QT
interval with citalopram, and identified additional
antidepressants with similar risk. Pharmacovigilance
studies using electronic health record data may be a useful
method of identifying potential risk associated with
treatments.
“Discovering Medical Conditions Associated with
Periodontitis Using Linked Electronic Health Records”
(Boland MR. et al, J of Clin Periodontol, 2013)
 Goal: To use linked electronic medical and dental records
to discover associations between periodontitis and medical
conditions independent of a priori hypotheses.
 Methods: This case-control study included 2475 patients
who underwent dental treatment at the College of Dental
Medicine at Columbia University and medical treatment at
NewYork-Presbyterian Hospital. Our cases are patients
who received periodontal treatment and our controls are
patients who received dental maintenance but no
periodontal treatment. Chi-square analysis was performed
for medical treatment codes and logistic regression was
used to adjust for confounders.
“Discovering Medical Conditions Associated with
Periodontitis Using Linked Electronic Health Records”
(Boland MR. et al, J of Clin Periodontol, 2013)
 Results: The method
replicated several
important periodontitis
associations in a largely
Hispanic population,
including diabetes
mellitus type I and II,
hypertension,
hypercholesterolemia,
hyperlipidemia, and
conditions related to
pregnancy, child-birth.
 Also, previously
unreported association
with BPH.
“Discovering Medical Conditions Associated with
Periodontitis Using Linked Electronic Health Records”
(Boland MR. et al, J of Clin Periodontol, 2013)
 Conclusions: Describes a high-throughput method for
associating periodontitis with systemic diseases using
linked electronic records.
 Beyond that – is another good example of using linked
electronic health records (and dental records in this case)
for disease association studies, and identifying
associations that may have been previously unrecognized.
Other notable papers in this category:
 “A pragmatic framework for single-site and multisite data quality
assessment in electronic health record-based clinical research.”
(Kahn MG et al. Medical care. 2012)
 “Oncoshare: lessons learned from building an integrated multi-
institutional database for comparative effectiveness research.”
(Weber S et al. AMIA Annual Symposium proceedings 2012)
 “Standardizing clinical laboratory data for secondary use.”
(Abhyankar S et al. Journal of biomedical informatics. 2012)
 Mining electronic health records: towards better research
applications and clinical care. (Jensen PB. Nature Reviews
Genetics. 2012)
 "In Search of a Data-in-Once, Electronic Health Record-Linked,
Multicenter Registry— How Far We Have Come and How Far We
Still Have to Go,” (Marsolo K. eGEMs (Generating Evidence &
Methods to improve patient outcomes): Vol. 1: Iss. 1, 3.)
Data/Knowledge Management &
Discovery
“A survey of informatics platforms that enable
distributed comparative effectiveness research using
multi-institutional heterogenous clinical data.”
(Sittig et al, Medical Care, 2012)
 Goal: To compare and contrast 6 large-scale projects that
are either developing or extending existing informatics
platforms for CER.
 Methods: Rather than compare the informatics platforms
at an abstract level, focused specific CER projects that
provide implementations of informatics platforms and
highlight design requirements and solutions. Utilized an 8-
dimension, sociotechnical model of health information
technology to help guide work
 Results: Identified 6 generic steps that are necessary in
any distributed, multi-institutional CER project: data
identification, extraction, modeling, aggregation, analysis,
and dissemination.
“A survey of informatics platforms that enable
distributed comparative effectiveness research using
multi-institutional heterogenous clinical data.”
(Sittig et al, Medical Care, 2012)
“A survey of informatics platforms that enable
distributed comparative effectiveness research using
multi-institutional heterogenous clinical data.”
(Sittig et al, Medical Care, 2012)
 Conclusions: CER stands to transform the current health
care delivery system by identifying which therapies,
procedures, preventive tests, and health care processes
are most effective from the standpoints of cost, quality, and
safety.
 State-of-the-art informatics platforms are necessary to
carry out this type of research across organizations with
disparate patient populations, health information systems,
data types, and local governance structures.
 Such platforms and resources will continue to grow and be
tested, essential to advancing CER and related research
initiatives.
“An i2b2-based, generalizable, open source,
self-scaling chronic disease registry.”
(Natter et al, JAMIA, 2013)
 Goal: Registries growing in importance for obtaining high-
quality, disease-specific data. But, they are often highly
project-specific in design, implementation and usage. This
project sought to develop a “self-scaling” approach for
collaborative data sharing.
 Methods: Leveraging i2b2 and SHRINE networking
software platforms, created modular, ontology-based,
federated infrastructure to give researchers access to data
from multiple sites for Childhood Arthritis & Rheumatology
Research Alliance (CARRA) Registry
“An i2b2-based, generalizable, open source,
self-scaling chronic disease registry.”
(Natter et al, JAMIA, 2013)
“An i2b2-based, generalizable, open source,
self-scaling chronic disease registry.”
(Natter et al, JAMIA, 2013)
“An i2b2-based, generalizable, open source,
self-scaling chronic disease registry.”
(Natter et al, JAMIA, 2013)
 Results: Use of this federated, self-scaling registry
platform enabled collaborative data sharing and
collaboration while enabling fine-grained control over data
sharing.
 The implementation of i2b2-SSR for the multi-site, multi-
stakeholder CARRA Registry has established a digital
infrastructure for community-driven research data sharing
in pediatric rheumatology in the US.
 Conclusions: Such data sharing needs across sites are
expected to grow, and this is a great example of leveraging
current informatics platforms and approaches to
accomplish this.
“Validation of a common data model for active
safety surveillance research” (Overhage JM.
JAMIA. 2012)
 Problem: Systematic analysis of observational medical
databases for active safety surveillance is hindered by the
variation in data models and coding systems. Translating
the data from idiosyncratic data models to a common data
model (CDM) could facilitate both analysts' understanding
and the suitability for large-scale systematic analysis. In
addition to facilitating analysis, a suitable CDM has to
faithfully represent the source observational database.
 Goal: Before beginning to use the Observational Medical
Outcomes Partnership (OMOP) CDM and a related
dictionary of standardized terminologies for a study of
large-scale systematic active safety surveillance, the
authors validated the model's suitability for this use by
example.
“Validation of a common data model for active
safety surveillance research” (Overhage JM.
JAMIA. 2012)
 Approach: To validate the OMOP CDM, the model was
instantiated into a relational database, data from 10
different observational healthcare databases were loaded
into separate instances, a comprehensive array of analytic
methods that operate on the data model was created, and
these methods were executed against the databases to
measure performance.
 Conclusion: Acceptable representation of data from 10
observational databases in the OMOP CDM using the
standardized terminologies selected, and a range of
analytic methods developed and executed with sufficient
performance to be useful for active safety surveillance.
 Nice example of validating data model for use with
observational data - will only become more common
Other notable papers in this category:
 “Identifying clinical/translational research cohorts:
ascertainment via querying an integrated multi-source
database.” (Hurdle JF. JAMIA. 2013)
 “Data model considerations for clinical effectiveness
researchers.” (Kahn MG. Medical care. 2012)
 “Applying knowledge-anchored hypothesis discovery
methods to advance clinical and translational
research: the OAMiner project.” (Payne PR. JAMIA
2012)
 “Translating standards into practice: experiences and
lessons learned in biomedicine and health care.”
(Chen ES. Journal of biomedical informatics. 2012)
Researcher Support & Resources
“Practices and perspectives on building integrated
data repositories: results from a 2010 CTSA survey.”
(Mackenzie et al, JAMIA, 2012)
 Goals: Clinical integrated data repositories (IDRs) are
poised to become a foundational element of biomedical
and translational research by providing the coordinated
data sources necessary to conduct retrospective analytic
research and to identify and recruit prospective research
subjects.
 Methods: The CTSA consortium's Informatics IDR Group
conducted a Web-based survey of 2010 consortium
members to evaluate recent trends in IDR implementation
and use to support research between 2008 and 2010.
 Results: 74% response rate representing 28 sites and NIH
clinical center.
“Practices and perspectives on building integrated
data repositories: results from a 2010 CTSA survey.”
(Mackenzie et al, JAMIA, 2012)
 Results: Vast majority of sites had an IDR (74%) or
multiple IDRs (12%)
“Practices and perspectives on building integrated
data repositories: results from a 2010 CTSA survey.”
(Mackenzie et al, JAMIA, 2012)
 Results:
Major data
types across sites
“Practices and perspectives on building integrated
data repositories: results from a 2010 CTSA survey.”
(Mackenzie et al, JAMIA, 2012)
 Conclusions: Survey results suggest that individual
organizations are progressing in their approaches to the
development, management, and use of IDRs as a means
to support a broad array of research.
 Fits with another publication on infrastructure…
“Current State of Information Technologies for
the Clinical Research Enterprise across
Academic Medical Centers”
(Murphy SN, et al. Clin Trans Sci. 2012)
 Goals: Clinical Research Forum IT Roundtable group
surveyed member organizations to assess current state,
changes in Research IT infrastructure since prior surveys
in 2005 and 2007.
 Methods: Survey to all member sites. Four main areas:
 The use of IT in research compliance, such as conflicts of
interest, research budgeting, and reporting to the Institutional
Review Board (IRB);
 The use of IT for electronic data capture (EDC) requirements
related to clinical studies and trials of different size;
 The use of data repositories for the repurposing of clinical care
data for research; and,
 The IT infrastructure needs and support for research
collaboration and communication.
“Current State of Information Technologies for
the Clinical Research Enterprise across
Academic Medical Centers”
(Murphy SN, et al. Clin Trans Sci. 2012)
 Results: 17/51 responded (33% response rate)
“Current State of Information Technologies for the Clinical Research
Enterprise across Academic Medical Centers”
(Murphy SN, et al. Clin Trans Sci. 2012)
 Results: 17/51 responded (33% response rate)
“Current State of Information Technologies for the
Clinical Research Enterprise across Academic Medical
Centers”
(Murphy SN, et al. Clin Trans Sci. 2012)
 Conclusions: Research IS adoption across respondent
sites has increased over past 7 years. The availability of
more robust and available vendor-based and “open-
source” solutions, coupled with new research initiatives
(e.g., CTSA) and regulatory requirements, appear to be
contributing to these advances.
“Access to core facilities and other research
resources provided by the Clinical and Translational
Science Awards.” (Rosenblum D. Clin Trans Sci. 2012)
 Goal: Review of 60 CTSA website offerings to assess
and categorize.
 Results: Over 170 generic services, which this review
has categorized in the following seven areas: (1) core
facilities, (2) biomedical informatics, (3) funding, (4)
regulatory knowledge and support, (5) biostatistics,
epidemiology, research design, and ethics, (6) participant
and clinical interaction resources, and (7) community
engagement. In addition, many facilitate access to
resources with search engines, navigators, studios,
project development teams, collaboration tools,
communication systems, and teaching tools.
 Conclusion: CTSAs significantly impacting awareness
of and access to research resources.
Other notable papers in this category:
 “A model for the electronic support of practice-based
research networks.” (Peterson KA. Annals of family
medicine. 2012)
 “Approaches to facilitate institutional review board
approval of multicenter research studies.” (Marsolo K.
Med care. 2012)
 “Building the informatics infrastructure for
comparative effectiveness research (CER): a review of
the literature.” (Lopez MH. Med care. 2012)
 “Clinical and translational research studios: a
multidisciplinary internal support program.” (Byrne
DW. Academic Med 2012)
 “The feasibility of cell phone based electronic diaries
for STI/HIV research” (Hensel DJ. BMC medical research
methodology. 2012.
Recruitment Informatics
“Evaluation of a prototype interactive consent
program for pediatric clinical trials: a pilot study.
(Tait AR, et al. JAMIA. 2012)
 Issue: Standard written methods of presenting research
information may be difficult for many parents and children
to understand.
 Goals: Examine use of novel prototype interactive
consent for describing hypothetical pediatric asthma trial
to parents and children
 Methods: Parents and children interviewed to examine
baseline understanding of key elements of clinical trial,
reviewed age-appropriate versions of interactive program
describing asthma trial, and tested for understanding.
“Evaluation of a prototype interactive consent
program for pediatric clinical trials: a pilot study.
(Tait AR, et al. JAMIA. 2012)
 Results: Parents and children improved understanding
of key research concepts following program. E.g.
percentage of parents and children who could correctly
define the terms clinical trials and placebo improved from
60% to 80%, and 80% to 100% among parents and 25%
to 50% and 0% to 50% among children, respectively.
Results also suggest that the interactive programs were
easy to use, facilitated understanding of the trial among
parents and children.
 Conclusions: Interactive media may offer an effective
means of presenting understandable information to
parents and children regarding participation in clinical
trials. This will likely grow along with need for better ways
of ensuring “informed” consent using novel, automated
approaches.
“Challenges in creating an opt-in biobank with a
registrar-based consent process and a
commercial EHR.”
(Marsolo K. JAMIA, 2012)
 Goal: Implement an opt-in biobank, with auto-consent at
the time of registration and the decision stored in EHR for
data and bio-specimen re-use.
 Methods: Implemented at registration and information
about decision and related data stored in system.
Investigators can search for samples using i2b2 data
warehouse.
 Results: Patient opt-in rate over 86%, with 83%
requesting to be notified of any incidental research
findings. In 6 months, obtained decisions from over
18,000 patients and processed 8000 blood samples for
storage in our research biobank. Found some limitations
in current systems that required work-arounds.
“Challenges in creating an opt-in biobank with a
registrar-based consent process and a
commercial EHR.”
(Marsolo K. JAMIA, 2012)
 Conclusions: Real-world example with impressive
success in obtaining consent/assent from majority of
patients requiring limited resources. Lessons that should
help others advance these kinds of efforts to re-use data
and specimens for research and inform improvements to
IT systems to support such efforts.
“Evaluating alert fatigue over time to EHR-based
clinical trial alerts: findings from a randomized
controlled study.”
(Embi & Leonard, et al. JAMIA, 2012)
 Goal: Study whether repeated exposure to such alerts
leads to declining user responsiveness and to
characterize its extent if present to better inform future
CTA deployments.
 Methods: During a 36-week study period, we
systematically documented the response patterns of 178
physician users randomized to receive CTAs for an
ongoing clinical trial. Data were collected on: (1)
response rates to the CTA; and (2) referral rates per
physician, per time unit.
 Significant declining trend in overall CTA response rate
 2.7% decline in each 2-week time period
 Significantly different than zero (flat), p<0.0001
 Notably – still at ~35% response rate after 36 weeks exposure
“Evaluating alert fatigue over time to EHR-
based clinical trial alerts: findings from a
randomized controlled study.”
(Embi & Leonard, et al. JAMIA, 2012)
 Decline in “referral” rates more pronounced than for
“response” rates
 4.9% decrease per time period, p = 0.0294
“Evaluating alert fatigue over time to EHR-
based clinical trial alerts: findings from a
randomized controlled study.”
(Embi & Leonard, et al. JAMIA, 2012)
 Conclusions: CTA response rates declined over
time, suggesting some contribution of alert fatigue.
More so among community vs. university based
MDs. Overall response rates remained relatively
high, however (~35%) over the 36-week study.
 Approach to measuring alert-fatigue could be helpful
when monitoring and applying in more widespread
fashion.
“Evaluating alert fatigue over time to EHR-
based clinical trial alerts: findings from a
randomized controlled study.”
(Embi & Leonard, et al. JAMIA, 2012)
Other notable papers for this section:
 “Secondary use of routinely collected patient data in a
clinical trial: An evaluation of the effects on patient
recruitment and data acquisition. (Köpcke F, et al. Int J
Med Inform. 2013)
 “Connecting communities to health research:
Development of the Project CONNECT minority
research registry.” (Green MA, et al. Contemporary
clinical trials. 2013)
 “A model for the design and implementation of a
participant recruitment registry for clinical studies of
older adults.” (Dowling NM, et al. Clinical trials. 2012)
 “Computational challenges and human factors
influencing the design and use of clinical research
participant eligibility pre-screening tools.” (Pressler
TR, et al. BMC medical informatics and decision making.
2012)
Policy and Perspectives
CRI Policy & Perspectives Pieces:
 “Using EHRs to integrate research with patient care:
promises and challenges.” (Weng C. et al. JAMIA 2012)
 “Opportunities and challenges for comparative
effectiveness research (CER) with Electronic Clinical
Data: a perspective from the EDM forum” (Holve E.
Medical care. 2012)
 “Health services research evaluation principles.
Broadening a general framework for evaluating health
information technology” (Sockolow PS et al. Meth Info in
Med. 2012)
 “Informatics and operations - let's get integrated”
(Marsolo K. JAMIA. 2013)
 The SMART Platform: early experience enabling
substitutable applications for electronic health
records. (Mandl KD. JAMIA. 2012)
Notable CRI-Related Events in Past Year
Release of the HIPAA Omnibus Rule –
Jan 2013
 The Final Rule provisions has important implications for
research:
 Changes allowing compound authorizations should alleviate
administrative burdens on clinical trial subjects and researchers
and facilitate harmonization with the Common Rule and global
requirements for research documentation.
 Revised interpretation regarding authorization for future research
use will remove barriers on researchers' ability to use data for
future research purposes – some of which cannot even be
contemplated at the time the data is gathered, but which could
hold great promise to advance science and medical care.
 The declassification as "PHI" of certain information of decedents
over time will ease researchers' ability to perform research using
such information.
 Researchers, research institutions and research
sponsors have until September 23, 2013, to come into full
compliance with the Final Rule. Start now!
Fiscal Cliff Legislation and Research…
(Not all bad news)
 As noted, registries are growing in importance
 Incentives needed to encourage participation
 Legislation to avert the fiscal cliff (at least once)
passed in January included a little known
provision
 Incentive to contribute to clinical data registries
 Physicians get rewarded as if using current CMS
PQRS reporting system
 Should help encourage adoption and contribution to
specialty registries like those now being established
by leveraging CRI innovations
Special Journal Issues dedicated to CRI Topics
New e-Journal about
Evidence Generating
Activities:
eGEMs
 Generating Evidence
& Methods to improve
patient outcomes
 Four Thematic Areas:
 Methods
 Informatics
 Governance
 Learning Health System
 Out of the EDM Forum of Academy Health
 Free, Open, Peer-reviewed
First of its kind textbook dedicated to CRI
 Editors: Richesson & Andrews
 Contributing authors from
across our community
 A major achievement
 More evidence of CRI as
established domain
 http://www.springer.com/public+health/book/978-1-84882-447-8
 http://www.amazon.com/Clinical-Research-Informatics-Health/dp/1848824475
In Summary…
 Maturing data infrastructure and sharing capabilities
 Increases in informatics approaches to re-use data
accelerating and yielding real results
 Infrastructure advances maturing and beginning to
accelerate and improve science
 Some (too few) evaluations, controlled studies
 Poised to deploy and test our approaches to realize
the “learning health system”
 Exciting time to be in CRI!
Thanks!
Special thanks to:
Philip Payne
Eta Berner
Rachel Richesson
Adam Wilcox
Shawn Murphy
Chunhua Weng
Thanks!
Peter.Embi@osumc.edu
Slides will be posted on AMIA Website & on
http://www.embi.net/ (click on “Informatics”)

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Embi cri review-2013-final

  • 1. Peter J. Embi, MD, MS, FACP, FACMI Assoc Prof & Vice Chair, Dept of Biomedical Informatics Associate Professor of Medicine Chief Research Information Officer Co-Director, Biomedical Informatics, CCTS The Ohio State University San Francisco, California March 22, 2013
  • 2. Approach to this presentation  Mixed approach to article identification:  Started with structured approach  (akin to ACP “update” sessions)  Augment with “what seemed interesting” approach  Learned a lot from doing this last two years  Tracked manuscripts throughout the year  (still worked down to the wire)  So, what was my approach…
  • 3. Source of Content for Session  Literature review:  Initial search by MESH terms:  ("Biomedical Research"[Mesh] NOT "Genetic Research"[Mesh]) NOT "Translational Research"[Mesh]) AND "Informatics"[Mesh] AND "2012/01/01"[PDat] : "2013/02/01"[Pdat]  Resulted in 90 articles; 33 were CRI relevant  Additional 483 articles found via:  Recommendations from colleagues  Other keyword searches using terms like:  Clinical Trials, Clinical Research, Informatics, Translational, Data Warehouse, Research Registries, Recruitment  Yielding 48 more CRI-relevant articles, for a total of…  Result = 81 total CRI relevant  From those, I’ve selected 35 representative papers that I’ll present here (briefly)
  • 4. Session caveats  What this is not…  A systematic review of the literature  An exhaustive review  What this is…  My best attempt at briefly covering some of the representative CRI literature from the past year  A snap-shot of excellent CRI activity over past year  What I thought was particularly notable
  • 5. Clinical and Translational Research & Informatics: T1, T2, and Areas of Overlap for Informatics Shaded CRI Region is Main Area of Focus Embi & Payne, JAMIA 2009
  • 6. Topics  Grouped 35 articles into several CRI categories (admittedly, not all CRI areas)  Clinical Data Re-Use for Research  Data/Knowledge Management & Discovery  Researcher Support & Resources  Participant Recruitment  Policy & Perspectives  In each category, I’ll highlight a few key articles and then given a quick “shout out” to a few others  Conclude with notable events from the past year
  • 7. Apologies up front  I’m CERTAIN I’ve missed a lot of great work  I’m REALLY SORRY about that
  • 8. Clinical Data Re-Use for Research
  • 9. “Patient characteristics associated with venous thromboembolic events: a cohort study using pooled electronic health record data.” (Kaelber DC et al, JAMIA, 2012)  Goal: Demonstrate the potential of de-identified clinical data from multiple systems using different EHRs to be used for large retrospective cohort studies  Methods: Data of 959,030 patients, pooled, standardized and normalized using common ontologies, searchable through a HIPAA-compliant, patient de-identified web application (Explore; Explorys Inc). Patients were 26 years or older seen in multiple healthcare systems from 1999 to 2011 with data from EHR.
  • 10. “Patient characteristics associated with venous thromboembolic events: a cohort study using pooled electronic health record data.” (Kaelber DC et al, JAMIA, 2012)
  • 11. “Patient characteristics associated with venous thromboembolic events: a cohort study using pooled electronic health record data.” (Kaelber DC et al, JAMIA, 2012)  Results: Comparing obese/tall subjects with normal weight/short subjects, the venous thromboembolic events (VTE) OR was 1.83 for women and 1.21 for men. Weight had more effect then height on VTE. Compared with Caucasian, Hispanic/Latino subjects had a much lower risk of VTE (female OR 0.47; male OR 0.24) and African- Americans a substantially higher risk (female OR 1.83,; male OR 1.58). This 13-year retrospective study of almost one million patients was performed over approximately 125 h in 11 weeks, part time by the five authors.  Conclusion: Informatics approaches to pool EHR-derived clinical will provide opportunities for CRI to transform the scale and resources needed to perform certain types of clinical research. Potential to achieve results similar to much more costly, time-intensive study approaches.
  • 12. “QT interval and antidepressant use: a cross sectional study of electronic health records.” (Castro VM, et al, BMJ, 2013)  Objective: To quantify the impact of citalopram and other selective serotonin reuptake inhibitors on corrected QT interval (QTc), a marker of risk for ventricular arrhythmia, in a large and diverse clinical population.  Method: Cross-sectional study using EHR-data (ECGs, Rx, Clinical) to explore relation between antidepressant dose and QTc. 38,397 adult patients with an electrocardiogram recorded after prescription of antidepressant or methadone between February 1990 and August 2011.
  • 13. “QT interval and antidepressant use: a cross sectional study of electronic health records.” (Castro VM, et al, BMJ, 2013)  Results: Dose-response association with QTc prolongation was identified for citalopram, escitalopram, and amitriptyline, but not for other antidepressants examined. An association with QTc shortening was identified for bupropion. Within-subject paired observations supported the QTc prolonging effect of citalopram.  Conclusions: Confirmed modest prolongation of QT interval with citalopram, and identified additional antidepressants with similar risk. Pharmacovigilance studies using electronic health record data may be a useful method of identifying potential risk associated with treatments.
  • 14. “Discovering Medical Conditions Associated with Periodontitis Using Linked Electronic Health Records” (Boland MR. et al, J of Clin Periodontol, 2013)  Goal: To use linked electronic medical and dental records to discover associations between periodontitis and medical conditions independent of a priori hypotheses.  Methods: This case-control study included 2475 patients who underwent dental treatment at the College of Dental Medicine at Columbia University and medical treatment at NewYork-Presbyterian Hospital. Our cases are patients who received periodontal treatment and our controls are patients who received dental maintenance but no periodontal treatment. Chi-square analysis was performed for medical treatment codes and logistic regression was used to adjust for confounders.
  • 15. “Discovering Medical Conditions Associated with Periodontitis Using Linked Electronic Health Records” (Boland MR. et al, J of Clin Periodontol, 2013)  Results: The method replicated several important periodontitis associations in a largely Hispanic population, including diabetes mellitus type I and II, hypertension, hypercholesterolemia, hyperlipidemia, and conditions related to pregnancy, child-birth.  Also, previously unreported association with BPH.
  • 16. “Discovering Medical Conditions Associated with Periodontitis Using Linked Electronic Health Records” (Boland MR. et al, J of Clin Periodontol, 2013)  Conclusions: Describes a high-throughput method for associating periodontitis with systemic diseases using linked electronic records.  Beyond that – is another good example of using linked electronic health records (and dental records in this case) for disease association studies, and identifying associations that may have been previously unrecognized.
  • 17. Other notable papers in this category:  “A pragmatic framework for single-site and multisite data quality assessment in electronic health record-based clinical research.” (Kahn MG et al. Medical care. 2012)  “Oncoshare: lessons learned from building an integrated multi- institutional database for comparative effectiveness research.” (Weber S et al. AMIA Annual Symposium proceedings 2012)  “Standardizing clinical laboratory data for secondary use.” (Abhyankar S et al. Journal of biomedical informatics. 2012)  Mining electronic health records: towards better research applications and clinical care. (Jensen PB. Nature Reviews Genetics. 2012)  "In Search of a Data-in-Once, Electronic Health Record-Linked, Multicenter Registry— How Far We Have Come and How Far We Still Have to Go,” (Marsolo K. eGEMs (Generating Evidence & Methods to improve patient outcomes): Vol. 1: Iss. 1, 3.)
  • 19. “A survey of informatics platforms that enable distributed comparative effectiveness research using multi-institutional heterogenous clinical data.” (Sittig et al, Medical Care, 2012)  Goal: To compare and contrast 6 large-scale projects that are either developing or extending existing informatics platforms for CER.  Methods: Rather than compare the informatics platforms at an abstract level, focused specific CER projects that provide implementations of informatics platforms and highlight design requirements and solutions. Utilized an 8- dimension, sociotechnical model of health information technology to help guide work  Results: Identified 6 generic steps that are necessary in any distributed, multi-institutional CER project: data identification, extraction, modeling, aggregation, analysis, and dissemination.
  • 20. “A survey of informatics platforms that enable distributed comparative effectiveness research using multi-institutional heterogenous clinical data.” (Sittig et al, Medical Care, 2012)
  • 21. “A survey of informatics platforms that enable distributed comparative effectiveness research using multi-institutional heterogenous clinical data.” (Sittig et al, Medical Care, 2012)  Conclusions: CER stands to transform the current health care delivery system by identifying which therapies, procedures, preventive tests, and health care processes are most effective from the standpoints of cost, quality, and safety.  State-of-the-art informatics platforms are necessary to carry out this type of research across organizations with disparate patient populations, health information systems, data types, and local governance structures.  Such platforms and resources will continue to grow and be tested, essential to advancing CER and related research initiatives.
  • 22. “An i2b2-based, generalizable, open source, self-scaling chronic disease registry.” (Natter et al, JAMIA, 2013)  Goal: Registries growing in importance for obtaining high- quality, disease-specific data. But, they are often highly project-specific in design, implementation and usage. This project sought to develop a “self-scaling” approach for collaborative data sharing.  Methods: Leveraging i2b2 and SHRINE networking software platforms, created modular, ontology-based, federated infrastructure to give researchers access to data from multiple sites for Childhood Arthritis & Rheumatology Research Alliance (CARRA) Registry
  • 23. “An i2b2-based, generalizable, open source, self-scaling chronic disease registry.” (Natter et al, JAMIA, 2013)
  • 24. “An i2b2-based, generalizable, open source, self-scaling chronic disease registry.” (Natter et al, JAMIA, 2013)
  • 25. “An i2b2-based, generalizable, open source, self-scaling chronic disease registry.” (Natter et al, JAMIA, 2013)  Results: Use of this federated, self-scaling registry platform enabled collaborative data sharing and collaboration while enabling fine-grained control over data sharing.  The implementation of i2b2-SSR for the multi-site, multi- stakeholder CARRA Registry has established a digital infrastructure for community-driven research data sharing in pediatric rheumatology in the US.  Conclusions: Such data sharing needs across sites are expected to grow, and this is a great example of leveraging current informatics platforms and approaches to accomplish this.
  • 26. “Validation of a common data model for active safety surveillance research” (Overhage JM. JAMIA. 2012)  Problem: Systematic analysis of observational medical databases for active safety surveillance is hindered by the variation in data models and coding systems. Translating the data from idiosyncratic data models to a common data model (CDM) could facilitate both analysts' understanding and the suitability for large-scale systematic analysis. In addition to facilitating analysis, a suitable CDM has to faithfully represent the source observational database.  Goal: Before beginning to use the Observational Medical Outcomes Partnership (OMOP) CDM and a related dictionary of standardized terminologies for a study of large-scale systematic active safety surveillance, the authors validated the model's suitability for this use by example.
  • 27. “Validation of a common data model for active safety surveillance research” (Overhage JM. JAMIA. 2012)  Approach: To validate the OMOP CDM, the model was instantiated into a relational database, data from 10 different observational healthcare databases were loaded into separate instances, a comprehensive array of analytic methods that operate on the data model was created, and these methods were executed against the databases to measure performance.  Conclusion: Acceptable representation of data from 10 observational databases in the OMOP CDM using the standardized terminologies selected, and a range of analytic methods developed and executed with sufficient performance to be useful for active safety surveillance.  Nice example of validating data model for use with observational data - will only become more common
  • 28. Other notable papers in this category:  “Identifying clinical/translational research cohorts: ascertainment via querying an integrated multi-source database.” (Hurdle JF. JAMIA. 2013)  “Data model considerations for clinical effectiveness researchers.” (Kahn MG. Medical care. 2012)  “Applying knowledge-anchored hypothesis discovery methods to advance clinical and translational research: the OAMiner project.” (Payne PR. JAMIA 2012)  “Translating standards into practice: experiences and lessons learned in biomedicine and health care.” (Chen ES. Journal of biomedical informatics. 2012)
  • 29. Researcher Support & Resources
  • 30. “Practices and perspectives on building integrated data repositories: results from a 2010 CTSA survey.” (Mackenzie et al, JAMIA, 2012)  Goals: Clinical integrated data repositories (IDRs) are poised to become a foundational element of biomedical and translational research by providing the coordinated data sources necessary to conduct retrospective analytic research and to identify and recruit prospective research subjects.  Methods: The CTSA consortium's Informatics IDR Group conducted a Web-based survey of 2010 consortium members to evaluate recent trends in IDR implementation and use to support research between 2008 and 2010.  Results: 74% response rate representing 28 sites and NIH clinical center.
  • 31. “Practices and perspectives on building integrated data repositories: results from a 2010 CTSA survey.” (Mackenzie et al, JAMIA, 2012)  Results: Vast majority of sites had an IDR (74%) or multiple IDRs (12%)
  • 32. “Practices and perspectives on building integrated data repositories: results from a 2010 CTSA survey.” (Mackenzie et al, JAMIA, 2012)  Results: Major data types across sites
  • 33. “Practices and perspectives on building integrated data repositories: results from a 2010 CTSA survey.” (Mackenzie et al, JAMIA, 2012)  Conclusions: Survey results suggest that individual organizations are progressing in their approaches to the development, management, and use of IDRs as a means to support a broad array of research.  Fits with another publication on infrastructure…
  • 34. “Current State of Information Technologies for the Clinical Research Enterprise across Academic Medical Centers” (Murphy SN, et al. Clin Trans Sci. 2012)  Goals: Clinical Research Forum IT Roundtable group surveyed member organizations to assess current state, changes in Research IT infrastructure since prior surveys in 2005 and 2007.  Methods: Survey to all member sites. Four main areas:  The use of IT in research compliance, such as conflicts of interest, research budgeting, and reporting to the Institutional Review Board (IRB);  The use of IT for electronic data capture (EDC) requirements related to clinical studies and trials of different size;  The use of data repositories for the repurposing of clinical care data for research; and,  The IT infrastructure needs and support for research collaboration and communication.
  • 35. “Current State of Information Technologies for the Clinical Research Enterprise across Academic Medical Centers” (Murphy SN, et al. Clin Trans Sci. 2012)  Results: 17/51 responded (33% response rate)
  • 36. “Current State of Information Technologies for the Clinical Research Enterprise across Academic Medical Centers” (Murphy SN, et al. Clin Trans Sci. 2012)  Results: 17/51 responded (33% response rate)
  • 37. “Current State of Information Technologies for the Clinical Research Enterprise across Academic Medical Centers” (Murphy SN, et al. Clin Trans Sci. 2012)  Conclusions: Research IS adoption across respondent sites has increased over past 7 years. The availability of more robust and available vendor-based and “open- source” solutions, coupled with new research initiatives (e.g., CTSA) and regulatory requirements, appear to be contributing to these advances.
  • 38. “Access to core facilities and other research resources provided by the Clinical and Translational Science Awards.” (Rosenblum D. Clin Trans Sci. 2012)  Goal: Review of 60 CTSA website offerings to assess and categorize.  Results: Over 170 generic services, which this review has categorized in the following seven areas: (1) core facilities, (2) biomedical informatics, (3) funding, (4) regulatory knowledge and support, (5) biostatistics, epidemiology, research design, and ethics, (6) participant and clinical interaction resources, and (7) community engagement. In addition, many facilitate access to resources with search engines, navigators, studios, project development teams, collaboration tools, communication systems, and teaching tools.  Conclusion: CTSAs significantly impacting awareness of and access to research resources.
  • 39. Other notable papers in this category:  “A model for the electronic support of practice-based research networks.” (Peterson KA. Annals of family medicine. 2012)  “Approaches to facilitate institutional review board approval of multicenter research studies.” (Marsolo K. Med care. 2012)  “Building the informatics infrastructure for comparative effectiveness research (CER): a review of the literature.” (Lopez MH. Med care. 2012)  “Clinical and translational research studios: a multidisciplinary internal support program.” (Byrne DW. Academic Med 2012)  “The feasibility of cell phone based electronic diaries for STI/HIV research” (Hensel DJ. BMC medical research methodology. 2012.
  • 41. “Evaluation of a prototype interactive consent program for pediatric clinical trials: a pilot study. (Tait AR, et al. JAMIA. 2012)  Issue: Standard written methods of presenting research information may be difficult for many parents and children to understand.  Goals: Examine use of novel prototype interactive consent for describing hypothetical pediatric asthma trial to parents and children  Methods: Parents and children interviewed to examine baseline understanding of key elements of clinical trial, reviewed age-appropriate versions of interactive program describing asthma trial, and tested for understanding.
  • 42.
  • 43. “Evaluation of a prototype interactive consent program for pediatric clinical trials: a pilot study. (Tait AR, et al. JAMIA. 2012)  Results: Parents and children improved understanding of key research concepts following program. E.g. percentage of parents and children who could correctly define the terms clinical trials and placebo improved from 60% to 80%, and 80% to 100% among parents and 25% to 50% and 0% to 50% among children, respectively. Results also suggest that the interactive programs were easy to use, facilitated understanding of the trial among parents and children.  Conclusions: Interactive media may offer an effective means of presenting understandable information to parents and children regarding participation in clinical trials. This will likely grow along with need for better ways of ensuring “informed” consent using novel, automated approaches.
  • 44. “Challenges in creating an opt-in biobank with a registrar-based consent process and a commercial EHR.” (Marsolo K. JAMIA, 2012)  Goal: Implement an opt-in biobank, with auto-consent at the time of registration and the decision stored in EHR for data and bio-specimen re-use.  Methods: Implemented at registration and information about decision and related data stored in system. Investigators can search for samples using i2b2 data warehouse.  Results: Patient opt-in rate over 86%, with 83% requesting to be notified of any incidental research findings. In 6 months, obtained decisions from over 18,000 patients and processed 8000 blood samples for storage in our research biobank. Found some limitations in current systems that required work-arounds.
  • 45. “Challenges in creating an opt-in biobank with a registrar-based consent process and a commercial EHR.” (Marsolo K. JAMIA, 2012)  Conclusions: Real-world example with impressive success in obtaining consent/assent from majority of patients requiring limited resources. Lessons that should help others advance these kinds of efforts to re-use data and specimens for research and inform improvements to IT systems to support such efforts.
  • 46. “Evaluating alert fatigue over time to EHR-based clinical trial alerts: findings from a randomized controlled study.” (Embi & Leonard, et al. JAMIA, 2012)  Goal: Study whether repeated exposure to such alerts leads to declining user responsiveness and to characterize its extent if present to better inform future CTA deployments.  Methods: During a 36-week study period, we systematically documented the response patterns of 178 physician users randomized to receive CTAs for an ongoing clinical trial. Data were collected on: (1) response rates to the CTA; and (2) referral rates per physician, per time unit.
  • 47.  Significant declining trend in overall CTA response rate  2.7% decline in each 2-week time period  Significantly different than zero (flat), p<0.0001  Notably – still at ~35% response rate after 36 weeks exposure “Evaluating alert fatigue over time to EHR- based clinical trial alerts: findings from a randomized controlled study.” (Embi & Leonard, et al. JAMIA, 2012)
  • 48.  Decline in “referral” rates more pronounced than for “response” rates  4.9% decrease per time period, p = 0.0294 “Evaluating alert fatigue over time to EHR- based clinical trial alerts: findings from a randomized controlled study.” (Embi & Leonard, et al. JAMIA, 2012)
  • 49.  Conclusions: CTA response rates declined over time, suggesting some contribution of alert fatigue. More so among community vs. university based MDs. Overall response rates remained relatively high, however (~35%) over the 36-week study.  Approach to measuring alert-fatigue could be helpful when monitoring and applying in more widespread fashion. “Evaluating alert fatigue over time to EHR- based clinical trial alerts: findings from a randomized controlled study.” (Embi & Leonard, et al. JAMIA, 2012)
  • 50. Other notable papers for this section:  “Secondary use of routinely collected patient data in a clinical trial: An evaluation of the effects on patient recruitment and data acquisition. (Köpcke F, et al. Int J Med Inform. 2013)  “Connecting communities to health research: Development of the Project CONNECT minority research registry.” (Green MA, et al. Contemporary clinical trials. 2013)  “A model for the design and implementation of a participant recruitment registry for clinical studies of older adults.” (Dowling NM, et al. Clinical trials. 2012)  “Computational challenges and human factors influencing the design and use of clinical research participant eligibility pre-screening tools.” (Pressler TR, et al. BMC medical informatics and decision making. 2012)
  • 52. CRI Policy & Perspectives Pieces:  “Using EHRs to integrate research with patient care: promises and challenges.” (Weng C. et al. JAMIA 2012)  “Opportunities and challenges for comparative effectiveness research (CER) with Electronic Clinical Data: a perspective from the EDM forum” (Holve E. Medical care. 2012)  “Health services research evaluation principles. Broadening a general framework for evaluating health information technology” (Sockolow PS et al. Meth Info in Med. 2012)  “Informatics and operations - let's get integrated” (Marsolo K. JAMIA. 2013)  The SMART Platform: early experience enabling substitutable applications for electronic health records. (Mandl KD. JAMIA. 2012)
  • 54. Release of the HIPAA Omnibus Rule – Jan 2013  The Final Rule provisions has important implications for research:  Changes allowing compound authorizations should alleviate administrative burdens on clinical trial subjects and researchers and facilitate harmonization with the Common Rule and global requirements for research documentation.  Revised interpretation regarding authorization for future research use will remove barriers on researchers' ability to use data for future research purposes – some of which cannot even be contemplated at the time the data is gathered, but which could hold great promise to advance science and medical care.  The declassification as "PHI" of certain information of decedents over time will ease researchers' ability to perform research using such information.  Researchers, research institutions and research sponsors have until September 23, 2013, to come into full compliance with the Final Rule. Start now!
  • 55. Fiscal Cliff Legislation and Research… (Not all bad news)  As noted, registries are growing in importance  Incentives needed to encourage participation  Legislation to avert the fiscal cliff (at least once) passed in January included a little known provision  Incentive to contribute to clinical data registries  Physicians get rewarded as if using current CMS PQRS reporting system  Should help encourage adoption and contribution to specialty registries like those now being established by leveraging CRI innovations
  • 56. Special Journal Issues dedicated to CRI Topics
  • 57. New e-Journal about Evidence Generating Activities: eGEMs  Generating Evidence & Methods to improve patient outcomes  Four Thematic Areas:  Methods  Informatics  Governance  Learning Health System  Out of the EDM Forum of Academy Health  Free, Open, Peer-reviewed
  • 58. First of its kind textbook dedicated to CRI  Editors: Richesson & Andrews  Contributing authors from across our community  A major achievement  More evidence of CRI as established domain  http://www.springer.com/public+health/book/978-1-84882-447-8  http://www.amazon.com/Clinical-Research-Informatics-Health/dp/1848824475
  • 59. In Summary…  Maturing data infrastructure and sharing capabilities  Increases in informatics approaches to re-use data accelerating and yielding real results  Infrastructure advances maturing and beginning to accelerate and improve science  Some (too few) evaluations, controlled studies  Poised to deploy and test our approaches to realize the “learning health system”  Exciting time to be in CRI!
  • 60. Thanks! Special thanks to: Philip Payne Eta Berner Rachel Richesson Adam Wilcox Shawn Murphy Chunhua Weng
  • 61. Thanks! Peter.Embi@osumc.edu Slides will be posted on AMIA Website & on http://www.embi.net/ (click on “Informatics”)

Editor's Notes

  1. None from this meeting – just too late breaking I’m afraid.
  2. Some could fit into more than one category – so I just chose…
  3. Patient characteristics associated with venous thromboembolic events: a cohort study using pooled electronic health record data. Kaelber DC, Foster W, Gilder J, Love TE, Jain AK. Source Department of Information Services, The MetroHealth System, Cleveland, Ohio, USA. david.kaelber@case.edu Abstract OBJECTIVE: To demonstrate the potential of de-identified clinical data from multiple healthcare systems using different electronic health records (EHR) to be efficiently used for very large retrospective cohort studies. MATERIALS AND METHODS: Data of 959 030 patients, pooled from multiple different healthcare systems with distinct EHR, were obtained. Data were standardized and normalized using common ontologies, searchable through a HIPAA-compliant, patient de-identified web application (Explore; Explorys Inc). Patients were 26 years or older seen in multiple healthcare systems from 1999 to 2011 with data from EHR. RESULTS: Comparing obese, tall subjects with normal body mass index, short subjects, the venous thromboembolic events (VTE) OR was 1.83 (95% CI 1.76 to 1.91) for women and 1.21 (1.10 to 1.32) for men. Weight had more effect then height on VTE. Compared with Caucasian, Hispanic/Latino subjects had a much lower risk of VTE (female OR 0.47, 0.41 to 0.55; male OR 0.24, 0.20 to 0.28) and African-Americans a substantially higher risk (female OR 1.83, 1.76 to 1.91; male OR 1.58, 1.50 to 1.66). This 13-year retrospective study of almost one million patients was performed over approximately 125 h in 11 weeks, part time by the five authors. DISCUSSION: As research informatics tools develop and more clinical data become available in EHR, it is important to study and understand unique opportunities for clinical research informatics to transform the scale and resources needed to perform certain types of clinical research. CONCLUSIONS: With the right clinical research informatics tools and EHR data, some types of very large cohort studies can be completed with minimal resources.
  4. Patient characteristics associated with venous thromboembolic events: a cohort study using pooled electronic health record data. Kaelber DC, Foster W, Gilder J, Love TE, Jain AK. Source Department of Information Services, The MetroHealth System, Cleveland, Ohio, USA. david.kaelber@case.edu Abstract OBJECTIVE: To demonstrate the potential of de-identified clinical data from multiple healthcare systems using different electronic health records (EHR) to be efficiently used for very large retrospective cohort studies. MATERIALS AND METHODS: Data of 959 030 patients, pooled from multiple different healthcare systems with distinct EHR, were obtained. Data were standardized and normalized using common ontologies, searchable through a HIPAA-compliant, patient de-identified web application (Explore; Explorys Inc). Patients were 26 years or older seen in multiple healthcare systems from 1999 to 2011 with data from EHR. RESULTS: Comparing obese, tall subjects with normal body mass index, short subjects, the venous thromboembolic events (VTE) OR was 1.83 (95% CI 1.76 to 1.91) for women and 1.21 (1.10 to 1.32) for men. Weight had more effect then height on VTE. Compared with Caucasian, Hispanic/Latino subjects had a much lower risk of VTE (female OR 0.47, 0.41 to 0.55; male OR 0.24, 0.20 to 0.28) and African-Americans a substantially higher risk (female OR 1.83, 1.76 to 1.91; male OR 1.58, 1.50 to 1.66). This 13-year retrospective study of almost one million patients was performed over approximately 125 h in 11 weeks, part time by the five authors. DISCUSSION: As research informatics tools develop and more clinical data become available in EHR, it is important to study and understand unique opportunities for clinical research informatics to transform the scale and resources needed to perform certain types of clinical research. CONCLUSIONS: With the right clinical research informatics tools and EHR data, some types of very large cohort studies can be completed with minimal resources.
  5. Patient characteristics associated with venous thromboembolic events: a cohort study using pooled electronic health record data. Kaelber DC, Foster W, Gilder J, Love TE, Jain AK. Source Department of Information Services, The MetroHealth System, Cleveland, Ohio, USA. david.kaelber@case.edu Abstract OBJECTIVE: To demonstrate the potential of de-identified clinical data from multiple healthcare systems using different electronic health records (EHR) to be efficiently used for very large retrospective cohort studies. MATERIALS AND METHODS: Data of 959 030 patients, pooled from multiple different healthcare systems with distinct EHR, were obtained. Data were standardized and normalized using common ontologies, searchable through a HIPAA-compliant, patient de-identified web application (Explore; Explorys Inc). Patients were 26 years or older seen in multiple healthcare systems from 1999 to 2011 with data from EHR. RESULTS: Comparing obese, tall subjects with normal body mass index, short subjects, the venous thromboembolic events (VTE) OR was 1.83 (95% CI 1.76 to 1.91) for women and 1.21 (1.10 to 1.32) for men. Weight had more effect then height on VTE. Compared with Caucasian, Hispanic/Latino subjects had a much lower risk of VTE (female OR 0.47, 0.41 to 0.55; male OR 0.24, 0.20 to 0.28) and African-Americans a substantially higher risk (female OR 1.83, 1.76 to 1.91; male OR 1.58, 1.50 to 1.66). This 13-year retrospective study of almost one million patients was performed over approximately 125 h in 11 weeks, part time by the five authors. DISCUSSION: As research informatics tools develop and more clinical data become available in EHR, it is important to study and understand unique opportunities for clinical research informatics to transform the scale and resources needed to perform certain types of clinical research. CONCLUSIONS: With the right clinical research informatics tools and EHR data, some types of very large cohort studies can be completed with minimal resources.
  6. Castro VM, Clements CC, Murphy SN, Gainer VS, Fava M, Weilburg JB, et al. QT interval and antidepressant use: a cross sectional study of electronic health records. BMJ (Clinical research ed). 2013;346:f288. PubMed PMID: 23360890. Pubmed Central PMCID: PMC3558546. Epub 2013/01/31. eng. OBJECTIVE: To quantify the impact of citalopram and other selective serotonin reuptake inhibitors on corrected QT interval (QTc), a marker of risk for ventricular arrhythmia, in a large and diverse clinical population. DESIGN: A cross sectional study using electrocardiographic, prescribing, and clinical data from electronic health records to explore the relation between antidepressant dose and QTc. Methadone, an opioid known to prolong QT, was included to demonstrate assay sensitivity. SETTING: A large New England healthcare system comprising two academic medical centres and outpatient clinics. PARTICIPANTS: 38,397 adult patients with an electrocardiogram recorded after prescription of antidepressant or methadone between February 1990 and August 2011. MAIN OUTCOME MEASURES: Relation between antidepressant dose and QTc interval in linear regression, adjusting for potential clinical and demographic confounding variables. For a subset of patients, change in QTc after drug dose was also examined. RESULTS: Dose-response association with QTc prolongation was identified for citalopram (adjusted beta 0.10 (SE 0.04), P&amp;lt;0.01), escitalopram (adjusted beta 0.58 (0.15), P&amp;lt;0.001), and amitriptyline (adjusted beta 0.11 (0.03), P&amp;lt;0.001), but not for other antidepressants examined. An association with QTc shortening was identified for bupropion (adjusted beta 0.02 (0.01) P&amp;lt;0.05). Within-subject paired observations supported the QTc prolonging effect of citalopram (10 mg to 20 mg, mean QTc increase 7.8 (SE 3.6) ms, adjusted P&amp;lt;0.05; and 20 mg to 40 mg, mean QTc increase 10.3 (4.0) ms, adjusted P&amp;lt;0.01). CONCLUSIONS: This study confirmed a modest prolongation of QT interval with citalopram, and identified additional antidepressants with similar observed risk. Pharmacovigilance studies using electronic health record data may be a useful method of identifying potential risk associated with treatments.
  7. Castro VM, Clements CC, Murphy SN, Gainer VS, Fava M, Weilburg JB, et al. QT interval and antidepressant use: a cross sectional study of electronic health records. BMJ (Clinical research ed). 2013;346:f288. PubMed PMID: 23360890. Pubmed Central PMCID: PMC3558546. Epub 2013/01/31. eng. OBJECTIVE: To quantify the impact of citalopram and other selective serotonin reuptake inhibitors on corrected QT interval (QTc), a marker of risk for ventricular arrhythmia, in a large and diverse clinical population. DESIGN: A cross sectional study using electrocardiographic, prescribing, and clinical data from electronic health records to explore the relation between antidepressant dose and QTc. Methadone, an opioid known to prolong QT, was included to demonstrate assay sensitivity. SETTING: A large New England healthcare system comprising two academic medical centres and outpatient clinics. PARTICIPANTS: 38,397 adult patients with an electrocardiogram recorded after prescription of antidepressant or methadone between February 1990 and August 2011. MAIN OUTCOME MEASURES: Relation between antidepressant dose and QTc interval in linear regression, adjusting for potential clinical and demographic confounding variables. For a subset of patients, change in QTc after drug dose was also examined. RESULTS: Dose-response association with QTc prolongation was identified for citalopram (adjusted beta 0.10 (SE 0.04), P&amp;lt;0.01), escitalopram (adjusted beta 0.58 (0.15), P&amp;lt;0.001), and amitriptyline (adjusted beta 0.11 (0.03), P&amp;lt;0.001), but not for other antidepressants examined. An association with QTc shortening was identified for bupropion (adjusted beta 0.02 (0.01) P&amp;lt;0.05). Within-subject paired observations supported the QTc prolonging effect of citalopram (10 mg to 20 mg, mean QTc increase 7.8 (SE 3.6) ms, adjusted P&amp;lt;0.05; and 20 mg to 40 mg, mean QTc increase 10.3 (4.0) ms, adjusted P&amp;lt;0.01). CONCLUSIONS: This study confirmed a modest prolongation of QT interval with citalopram, and identified additional antidepressants with similar observed risk. Pharmacovigilance studies using electronic health record data may be a useful method of identifying potential risk associated with treatments.
  8. Out of Columbia U. Aim: To use linked electronic medical and dental records to discover associations between periodontitis and medical conditions independent of a priori hypotheses. Materials and Methods: This case-control study included 2475 patients who underwent dental treatment at the College of Dental Medicine at Columbia University and medical treatment at NewYork-Presbyterian Hospital. Our cases are patients who received periodontal treatment and our controls are patients who received dental maintenance but no periodontal treatment. Chi-square analysis was performed for medical treatment codes and logistic regression was used to adjust for confounders. Results: Our method replicated several important periodontitis associations in a largely Hispanic population, including diabetes mellitus type I (OR = 1.6, 95% CI 1.30–1.99, p &amp;lt; 0.001) and type II (OR = 1.4, 95% CI 1.22–1.67, p &amp;lt; 0.001), hypertension (OR = 1.2, 95% CI 1.10–1.37, p &amp;lt; 0.001), hypercholesterolaemia (OR = 1.2, 95% CI 1.07–1.38, p = 0.004), hyperlipidaemia (OR = 1.2, 95% CI 1.06–1.43, p = 0.008) and conditions pertaining to pregnancy and childbirth (OR = 2.9, 95% CI: 1.32–7.21, p = 0.014). We also found a previously unreported association with benign prostatic hyperplasia (OR = 1.5, 95% CI 1.05–2.10, p = 0.026) after adjusting for age, gender, ethnicity, hypertension, diabetes, obesity, lipid and circulatory system conditions, alcohol and tobacco abuse. Conclusions: This study contributes a high-throughput method for associating periodontitis with systemic diseases using linked electronic records.
  9. Out of Columbia U. Aim: To use linked electronic medical and dental records to discover associations between periodontitis and medical conditions independent of a priori hypotheses. Materials and Methods: This case-control study included 2475 patients who underwent dental treatment at the College of Dental Medicine at Columbia University and medical treatment at NewYork-Presbyterian Hospital. Our cases are patients who received periodontal treatment and our controls are patients who received dental maintenance but no periodontal treatment. Chi-square analysis was performed for medical treatment codes and logistic regression was used to adjust for confounders. Results: Our method replicated several important periodontitis associations in a largely Hispanic population, including diabetes mellitus type I (OR = 1.6, 95% CI 1.30–1.99, p &amp;lt; 0.001) and type II (OR = 1.4, 95% CI 1.22–1.67, p &amp;lt; 0.001), hypertension (OR = 1.2, 95% CI 1.10–1.37, p &amp;lt; 0.001), hypercholesterolaemia (OR = 1.2, 95% CI 1.07–1.38, p = 0.004), hyperlipidaemia (OR = 1.2, 95% CI 1.06–1.43, p = 0.008) and conditions pertaining to pregnancy and childbirth (OR = 2.9, 95% CI: 1.32–7.21, p = 0.014). We also found a previously unreported association with benign prostatic hyperplasia (OR = 1.5, 95% CI 1.05–2.10, p = 0.026) after adjusting for age, gender, ethnicity, hypertension, diabetes, obesity, lipid and circulatory system conditions, alcohol and tobacco abuse. Conclusions: This study contributes a high-throughput method for associating periodontitis with systemic diseases using linked electronic records.
  10. Out of Columbia U. Aim: To use linked electronic medical and dental records to discover associations between periodontitis and medical conditions independent of a priori hypotheses. Materials and Methods: This case-control study included 2475 patients who underwent dental treatment at the College of Dental Medicine at Columbia University and medical treatment at NewYork-Presbyterian Hospital. Our cases are patients who received periodontal treatment and our controls are patients who received dental maintenance but no periodontal treatment. Chi-square analysis was performed for medical treatment codes and logistic regression was used to adjust for confounders. Results: Our method replicated several important periodontitis associations in a largely Hispanic population, including diabetes mellitus type I (OR = 1.6, 95% CI 1.30–1.99, p &amp;lt; 0.001) and type II (OR = 1.4, 95% CI 1.22–1.67, p &amp;lt; 0.001), hypertension (OR = 1.2, 95% CI 1.10–1.37, p &amp;lt; 0.001), hypercholesterolaemia (OR = 1.2, 95% CI 1.07–1.38, p = 0.004), hyperlipidaemia (OR = 1.2, 95% CI 1.06–1.43, p = 0.008) and conditions pertaining to pregnancy and childbirth (OR = 2.9, 95% CI: 1.32–7.21, p = 0.014). We also found a previously unreported association with benign prostatic hyperplasia (OR = 1.5, 95% CI 1.05–2.10, p = 0.026) after adjusting for age, gender, ethnicity, hypertension, diabetes, obesity, lipid and circulatory system conditions, alcohol and tobacco abuse. Conclusions: This study contributes a high-throughput method for associating periodontitis with systemic diseases using linked electronic records.
  11. Comparative effectiveness research (CER) has the potential to transform the current health care delivery system by identifying the most effective medical and surgical treatments, diagnostic tests, disease prevention methods, and ways to deliver care for specific clinical conditions. To be successful, such research requires the identification, capture, aggregation, integration, and analysis of disparate data sources held by different institutions with diverse representations of the relevant clinical events. In an effort to address these diverse demands, there have been multiple new designs and implementations of informatics platforms that provide access to electronic clinical data and the governance infrastructure required for interinstitutional CER. The goal of this manuscript is to help investigators understand why these informatics platforms are required and to compare and contrast 6 large-scale, recently funded, CER-focused informatics platform development efforts. We utilized an 8-dimension, sociotechnical model of health information technology to help guide our work. We identified 6 generic steps that are necessary in any distributed, multi-institutional CER project: data identification, extraction, modeling, aggregation, analysis, and dissemination. We expect that over the next several years these projects will provide answers to many important, and heretofore unanswerable, clinical research questions.
  12. Really a form of cheating on my part – review that covers many of the large-scale repositories that exist for this purpose – as illustrated in table 2 – and lays out the various aspects of these that must be considered by researchers for their use in CER, OR
  13. Comparative effectiveness research (CER) has the potential to transform the current health care delivery system by identifying the most effective medical and surgical treatments, diagnostic tests, disease prevention methods, and ways to deliver care for specific clinical conditions. To be successful, such research requires the identification, capture, aggregation, integration, and analysis of disparate data sources held by different institutions with diverse representations of the relevant clinical events. In an effort to address these diverse demands, there have been multiple new designs and implementations of informatics platforms that provide access to electronic clinical data and the governance infrastructure required for interinstitutional CER. The goal of this manuscript is to help investigators understand why these informatics platforms are required and to compare and contrast 6 large-scale, recently funded, CER-focused informatics platform development efforts. We utilized an 8-dimension, sociotechnical model of health information technology to help guide our work. We identified 6 generic steps that are necessary in any distributed, multi-institutional CER project: data identification, extraction, modeling, aggregation, analysis, and dissemination. We expect that over the next several years these projects will provide answers to many important, and heretofore unanswerable, clinical research questions.
  14. OBJECTIVE: Registries are a well-established mechanism for obtaining high quality, disease-specific data, but are often highly project-specific in their design, implementation, and policies for data use. In contrast to the conventional model of centralized data contribution, warehousing, and control, we design a self-scaling registry technology for collaborative data sharing, based upon the widely adopted Integrating Biology &amp; the Bedside (i2b2) data warehousing framework and the Shared Health Research Information Network (SHRINE) peer-to-peer networking software. MATERIALS AND METHODS: Focusing our design around creation of a scalable solution for collaboration within multi-site disease registries, we leverage the i2b2 and SHRINE open source software to create a modular, ontology-based, federated infrastructure that provides research investigators full ownership and access to their contributed data while supporting permissioned yet robust data sharing. We accomplish these objectives via web services supporting peer-group overlays, group-aware data aggregation, and administrative functions. RESULTS: The 56-site Childhood Arthritis &amp; Rheumatology Research Alliance (CARRA) Registry and 3-site Harvard Inflammatory Bowel Diseases Longitudinal Data Repository now utilize i2b2 self-scaling registry technology (i2b2-SSR). This platform, extensible to federation of multiple projects within and between research networks, encompasses &amp;gt;6000 subjects at sites throughout the USA. DISCUSSION: We utilize the i2b2-SSR platform to minimize technical barriers to collaboration while enabling fine-grained control over data sharing. CONCLUSIONS: The implementation of i2b2-SSR for the multi-site, multi-stakeholder CARRA Registry has established a digital infrastructure for community-driven research data sharing in pediatric rheumatology in the USA. We envision i2b2-SSR as a scalable, reusable solution facilitating interdisciplinary research across diseases.
  15. Figure 1 The i2b2-SSR architecture. Shows interaction of i2b2-SSR core web services C and D, which are customized, i2b2-SSR ‘dropin’ replacements for the standard SHRINE Broadcaster/Aggregator and i2b2 Project Manager Cell, respectively. In coordination with the i2b2-SSR Overlay Service (E), these modules support introduction of peer-group overlays for sharing of multiple datasets (I) using standard i2b2 nodes and SHRINE adapters (detail H). The authorized end-user (A) constructs a query based on shared ontologies that are pre-defined for the shared datasets. The Shared Ontology Service (F) may employ a standard i2b2 Ontology cell; alternatively, we provide an i2b2 Ontology module with the i2b2-SSR distribution that implements memory-based caching with ontology term search and autocomplete capabilities.
  16. End user query interface. The Site Investigator dashboard view is shown, illustrating a sample visualization of summary statistics for site ‘ABC’ versus the entire CARRAnet registry.
  17. OBJECTIVE: Registries are a well-established mechanism for obtaining high quality, disease-specific data, but are often highly project-specific in their design, implementation, and policies for data use. In contrast to the conventional model of centralized data contribution, warehousing, and control, we design a self-scaling registry technology for collaborative data sharing, based upon the widely adopted Integrating Biology &amp; the Bedside (i2b2) data warehousing framework and the Shared Health Research Information Network (SHRINE) peer-to-peer networking software. MATERIALS AND METHODS: Focusing our design around creation of a scalable solution for collaboration within multi-site disease registries, we leverage the i2b2 and SHRINE open source software to create a modular, ontology-based, federated infrastructure that provides research investigators full ownership and access to their contributed data while supporting permissioned yet robust data sharing. We accomplish these objectives via web services supporting peer-group overlays, group-aware data aggregation, and administrative functions. RESULTS: The 56-site Childhood Arthritis &amp; Rheumatology Research Alliance (CARRA) Registry and 3-site Harvard Inflammatory Bowel Diseases Longitudinal Data Repository now utilize i2b2 self-scaling registry technology (i2b2-SSR). This platform, extensible to federation of multiple projects within and between research networks, encompasses &amp;gt;6000 subjects at sites throughout the USA. DISCUSSION: We utilize the i2b2-SSR platform to minimize technical barriers to collaboration while enabling fine-grained control over data sharing. CONCLUSIONS: The implementation of i2b2-SSR for the multi-site, multi-stakeholder CARRA Registry has established a digital infrastructure for community-driven research data sharing in pediatric rheumatology in the USA. We envision i2b2-SSR as a scalable, reusable solution facilitating interdisciplinary research across diseases.
  18. Chen ES, Melton GB, Sarkar IN. Translating standards into practice: experiences and lessons learned in biomedicine and health care. Journal of biomedical informatics. 2012 Aug;45(4):609-12. PubMed PMID: 22750046. Epub 2012/07/04. eng. Hurdle JF: The Utah Population Database Limited query tool allows users to build complex queries that may span several types of health records, such as cancer registries, inpatient hospital discharges, and death certificates; in addition, these can be combined with family history information. The architectural approach incorporates several coding systems for medical information. It provides a front-end graphical user interface and enables researchers to build and run queries and view aggregate results. Multiple strategies have been incorporated to maintain confidentiality. RESULTS: This tool was rapidly adopted; since its release, 241 users representing a wide range of disciplines from 17 institutions have signed the user agreement and used the query tool. Three examples are discussed: pregnancy complications co-occurring with cardiovascular disease; spondyloarthritis; and breast cancer. Kahn MG, Batson D, Schilling LM. Data model considerations for clinical effectiveness researchers. - The Scalable Architecture for Federated Translational Inquiries Network (SAFTINet) was one of 3 projects receiving Agency for Healthcare Quality and Research funds to create a scalable, distributed network to support Comparative Effectiveness Research. SAFTINet&amp;apos;s method of extracting and compiling data from disparate entities requires the use of a shared common data model. Describe how they ultimately chose OMOP model, but that others would have been valid choices and the considerations that went into that. Kahn MG, Raebel MA, Glanz JM, Riedlinger K, Steiner JF. A pragmatic framework for single-site and multisite data quality assessment in electronic health record-based clinical research. Medical care. 2012 Jul;50 Suppl:S21-9. PubMed PMID: 22692254. Epub 2012/06/22. eng. Payne PR, Jackson RD, Best TM, Borlawsky TB, Lai AM, James S, et al. Applying knowledge-anchored hypothesis discovery methods to advance clinical and translational research: the OAMiner project. Journal of the American Medical Informatics Association : JAMIA. 2012 Nov-Dec;19(6):1110-4. PubMed PMID: 22647689. Pubmed Central PMCID: 3534452. Overhage JM, Ryan PB, Reich CG, Hartzema AG, Stang PE. Validation of a common data model for active safety surveillance research. J Am Med Inform Assoc 2012;19(1):54-60. (Good paper on observational data use)
  19. Hurdle JF: The Utah Population Database Limited query tool allows users to build complex queries that may span several types of health records, such as cancer registries, inpatient hospital discharges, and death certificates; in addition, these can be combined with family history information. The architectural approach incorporates several coding systems for medical information. It provides a front-end graphical user interface and enables researchers to build and run queries and view aggregate results. Multiple strategies have been incorporated to maintain confidentiality. RESULTS: This tool was rapidly adopted; since its release, 241 users representing a wide range of disciplines from 17 institutions have signed the user agreement and used the query tool. Three examples are discussed: pregnancy complications co-occurring with cardiovascular disease; spondyloarthritis; and breast cancer. Kahn MG, Batson D, Schilling LM. Data model considerations for clinical effectiveness researchers. - The Scalable Architecture for Federated Translational Inquiries Network (SAFTINet) was one of 3 projects receiving Agency for Healthcare Quality and Research funds to create a scalable, distributed network to support Comparative Effectiveness Research. SAFTINet&amp;apos;s method of extracting and compiling data from disparate entities requires the use of a shared common data model. Describe how they ultimately chose OMOP model, but that others would have been valid choices and the considerations that went into that. Payne PR, Jackson RD, Best TM, Borlawsky TB, Lai AM, James S, et al. Applying knowledge-anchored hypothesis discovery methods to advance clinical and translational research: the OAMiner project. Journal of the American Medical Informatics Association : JAMIA. 2012 Nov-Dec;19(6):1110-4. PubMed PMID: 22647689. Pubmed Central PMCID: 3534452. Chen ES, Melton GB, Sarkar IN. Translating standards into practice: experiences and lessons learned in biomedicine and health care. Journal of biomedical informatics. 2012 Aug;45(4):609-12. PubMed PMID: 22750046. Epub 2012/07/04. eng.
  20. Clinical integrated data repositories (IDRs) are poised to become a foundational element of biomedical and translational research by providing the coordinated data sources necessary to conduct retrospective analytic research and to identify and recruit prospective research subjects. The Clinical and Translational Science Award (CTSA) consortium&amp;apos;s Informatics IDR Group conducted a survey of 2010 consortium members to evaluate recent trends in IDR implementation and use to support research between 2008 and 2010. A web-based survey based in part on a prior 2008 survey was developed and deployed to 46 national CTSA centers. A total of 35 separate organizations completed the survey (74%), representing 28 CTSAs and the National Institutes of Health Clinical Center. Survey results suggest that individual organizations are progressing in their approaches to the development, management, and use of IDRs as a means to support a broad array of research. We describe the major trends and emerging practices below.
  21. Clinical integrated data repositories (IDRs) are poised to become a foundational element of biomedical and translational research by providing the coordinated data sources necessary to conduct retrospective analytic research and to identify and recruit prospective research subjects. The Clinical and Translational Science Award (CTSA) consortium&amp;apos;s Informatics IDR Group conducted a survey of 2010 consortium members to evaluate recent trends in IDR implementation and use to support research between 2008 and 2010. A web-based survey based in part on a prior 2008 survey was developed and deployed to 46 national CTSA centers. A total of 35 separate organizations completed the survey (74%), representing 28 CTSAs and the National Institutes of Health Clinical Center. Survey results suggest that individual organizations are progressing in their approaches to the development, management, and use of IDRs as a means to support a broad array of research. We describe the major trends and emerging practices below.
  22. Clinical integrated data repositories (IDRs) are poised to become a foundational element of biomedical and translational research by providing the coordinated data sources necessary to conduct retrospective analytic research and to identify and recruit prospective research subjects. The Clinical and Translational Science Award (CTSA) consortium&amp;apos;s Informatics IDR Group conducted a survey of 2010 consortium members to evaluate recent trends in IDR implementation and use to support research between 2008 and 2010. A web-based survey based in part on a prior 2008 survey was developed and deployed to 46 national CTSA centers. A total of 35 separate organizations completed the survey (74%), representing 28 CTSAs and the National Institutes of Health Clinical Center. Survey results suggest that individual organizations are progressing in their approaches to the development, management, and use of IDRs as a means to support a broad array of research. We describe the major trends and emerging practices below.
  23. Clinical integrated data repositories (IDRs) are poised to become a foundational element of biomedical and translational research by providing the coordinated data sources necessary to conduct retrospective analytic research and to identify and recruit prospective research subjects. The Clinical and Translational Science Award (CTSA) consortium&amp;apos;s Informatics IDR Group conducted a survey of 2010 consortium members to evaluate recent trends in IDR implementation and use to support research between 2008 and 2010. A web-based survey based in part on a prior 2008 survey was developed and deployed to 46 national CTSA centers. A total of 35 separate organizations completed the survey (74%), representing 28 CTSAs and the National Institutes of Health Clinical Center. Survey results suggest that individual organizations are progressing in their approaches to the development, management, and use of IDRs as a means to support a broad array of research. We describe the major trends and emerging practices below.
  24. Information technology (IT) to support clinical research has steadily grown over the past 10 years. Many new applications at the enterprise level are available to assist with the numerous tasks necessary in performing clinical research. However, it is not clear how rapidly this technology is being adopted, or whether it is making an impact upon how clinical research is being performed. The Clinical Research Forum’s IT Roundtable performed a survey of 17 representative academic medical centers (AMCs) to understand the adoption rate and implementation strategies within this field. The results were compared with similar surveys from 4 and 6 years ago. We found the adoption rate for four prominent areas of IT-supported clinical research had increased remarkably, specifically, regulatory compliance, electronic data capture for clinical trials, data repositories for secondary use of clinical data, and infrastructure for supporting collabora- tion. Adoption of other areas of clinical research IT was more irregular with wider differences between AMCs. This difference appeared to be partially due to a set of openly available applications that have emerged to occupy an important place in the landscape of clinical research enterprise level support at AMC’s. Clin Trans Sci 2012;
  25. Figure 1 compares the current results with those from the two surveys in 2007 and 2005. Figure 1(A)shows the number of responses relative to the total number of invited responses for each of the three surveys (2005, 2007, and 2011). It is not surprising that the response rate was similar for the online surveys done in 2007 and 2011 and much higher for the 2005 survey, which was conducted via one-on-one conference calls. The data needed to populate this graph came from the current survey and published results from the prior surveys.4,5 Figure 1(B) depicts changes over time in the percentage of respondents who have implemented elements of functionality pertaining to the general areas of research compliance (compliance), EDC, clinical data repositories (research repositories), and general clinical research computing infrastructure (infrastructure). To make such comparisons across time (and across surveys), an attempt was made to match a measurement from the current survey corresponding to an element of functionality from each of the areas above to the most similar respective measurement in the prior studies of 2007 and 2005.4,5 When a measurement in the current survey matched a corresponding measurement in both the 2005 and 2007 surveys, only those from the 2007 study were used. For research compliance, electronic IRB submission and processing was a common element of functionality that was measured among all the studies (2011, 2007, and 2005).4,5 For the purpose of comparison, Figure 1(B) compares the current (2011) results with the corresponding results of the 2007 study only. For EDC, the subcategory of “EDC for investigator initiated studies” measured in the current survey was the broadest and most inclusive definition, and thus was the best comparator for the 2005 measure “EDC applications for clinical trials.”4 For clinical data repositories (research repositories), the subcategories of “receiving clinical care data” and “store and archive data,” both of which had the same results with regards to fraction of respondents with completed installations, were matched with the measurement of the fraction of respondents with completed installations of a “patient data warehouse” application from the 2005 study.
  26. Figure 2 presents the percentage of respondents in the current survey who have completed the implementation of various elements of functionality contained within each of the general areas mentioned earlier, along with the names of the open-source solutions and the most commonly used solutions (commercial or open source) mentioned by respondents who had completed such implementations. Note that not all respondents completed all the questions in each of the sections of the survey, but for any question the number of responses was never less than 16.
  27. Information technology (IT) to support clinical research has steadily grown over the past 10 years. Many new applications at the enterprise level are available to assist with the numerous tasks necessary in performing clinical research. However, it is not clear how rapidly this technology is being adopted, or whether it is making an impact upon how clinical research is being performed. The Clinical Research Forum’s IT Roundtable performed a survey of 17 representative academic medical centers (AMCs) to understand the adoption rate and implementation strategies within this field. The results were compared with similar surveys from 4 and 6 years ago. We found the adoption rate for four prominent areas of IT-supported clinical research had increased remarkably, specifically, regulatory compliance, electronic data capture for clinical trials, data repositories for secondary use of clinical data, and infrastructure for supporting collabora- tion. Adoption of other areas of clinical research IT was more irregular with wider differences between AMCs. This difference appeared to be partially due to a set of openly available applications that have emerged to occupy an important place in the landscape of clinical research enterprise level support at AMC’s. Clin Trans Sci 2012;
  28. Principal investigators who received Clinical and Translational Science Awards created academic homes for biomedical research. They developed program-supported websites to offer coordinated access to a range of core facilities and other research resources. Visitors to the 60 websites will find at least 170 generic services, which this review has categorized in the following seven areas: (1) core facilities, (2) biomedical informatics, (3) funding, (4) regulatory knowledge and support, (5) biostatistics, epidemiology, research design, and ethics, (6) participant and clinical interaction resources, and (7) community engagement. In addition, many websites facilitate access to resources with search engines, navigators, studios, project development teams, collaboration tools, communication systems, and teaching tools. Each of these websites may be accessed from a single site, http://www.CTSAcentral.org. The ability to access the research resources from 60 of the nation&amp;apos;s academic health centers presents a novel opportunity for investigators engaged in clinical and translational research.
  29. Marsolo - A literature search was conducted to identify sources that described the challenges and potential strategies to facilitate multicenter IRB approval. The most promising avenues were identified and included in this review. Phone interviews were conducted with the Principal Investigators and Project Managers of 2 successful multicenter research networks to learn their &amp;quot;keys to success&amp;quot; and their lessons learned. RESULTS: Three strategies were identified that held the most promise: working with IRBs before submission, the use of central and/or federated IRBs, and the establishment of an umbrella protocol. Each of these strategies was used to some degree by the case study projects. Lopez – nice lit review of the informatics aspects related to CER Hensel – as part of larger study of risky sexual behaviors, nice demonstration of using ubiquitous mobile technologies to capture sensitive information in timely manner
  30. Standard written methods of presenting research information may be difficult for many parents and children to understand. This pilot study was designed to examine the use of a novel prototype interactive consent program for describing a hypothetical pediatric asthma trial to parents and children. Parents and children were interviewed to examine their baseline understanding of key elements of a clinical trial, eg, randomization, placebo, and blinding. Subjects then reviewed age-appropriate versions of an interactive computer program describing an asthma trial, and their understanding of key research concepts was again tested along with their understanding of the details of the trial. Parents and children also completed surveys to examine their perceptions and satisfaction with the program. Both parents and children demonstrated improved understanding of key research concepts following administration of the consent program. For example, the percentage of parents and children who could correctly define the terms clinical trials and placebo improved from 60% to 80%, and 80% to 100% among parents and 25% to 50% and 0% to 50% among children, respectively, following review of the interactive programs. Parents and children&amp;apos;s overall understanding of the details of the asthma trial were 14.2+/-0.84 and 9.25+/-4.9 (0-15 scale, where 15 is complete understanding), respectively. Results also suggest that the interactive programs were easy to use and facilitated understanding of the clinical trial among parents and children. Interactive media may offer an effective means of presenting understandable information to parents and children regarding participation in clinical trials. Further work to examine this novel approach appears warranted.
  31. Standard written methods of presenting research information may be difficult for many parents and children to understand. This pilot study was designed to examine the use of a novel prototype interactive consent program for describing a hypothetical pediatric asthma trial to parents and children. Parents and children were interviewed to examine their baseline understanding of key elements of a clinical trial, eg, randomization, placebo, and blinding. Subjects then reviewed age-appropriate versions of an interactive computer program describing an asthma trial, and their understanding of key research concepts was again tested along with their understanding of the details of the trial. Parents and children also completed surveys to examine their perceptions and satisfaction with the program. Interactive media may offer an effective means of presenting understandable information to parents and children regarding participation in clinical trials. Further work to examine this novel approach appears warranted.
  32. Residual clinical samples represent a very appealing source of biomaterial for translational and clinical research. We describe the implementation of an opt-in biobank, with consent being obtained at the time of registration and the decision stored in our electronic health record, Epic. Information on that decision, along with laboratory data, is transferred to an application that signals to biobank staff whether a given sample can be kept for research. Investigators can search for samples using our i2b2 data warehouse. Patient participation has been overwhelmingly positive and much higher than anticipated. Over 86% of patients provided consent and almost 83% requested to be notified of any incidental research findings. In 6 months, we obtained decisions from over 18 000 patients and processed 8000 blood samples for storage in our research biobank. However, commercial electronic health records like Epic lack key functionality required by a registrar-based consent process, although workarounds exist.
  33. Residual clinical samples represent a very appealing source of biomaterial for translational and clinical research. We describe the implementation of an opt-in biobank, with consent being obtained at the time of registration and the decision stored in our electronic health record, Epic. Information on that decision, along with laboratory data, is transferred to an application that signals to biobank staff whether a given sample can be kept for research. Investigators can search for samples using our i2b2 data warehouse. Patient participation has been overwhelmingly positive and much higher than anticipated. Over 86% of patients provided consent and almost 83% requested to be notified of any incidental research findings. In 6 months, we obtained decisions from over 18 000 patients and processed 8000 blood samples for storage in our research biobank. However, commercial electronic health records like Epic lack key functionality required by a registrar-based consent process, although workarounds exist.
  34. OBJECTIVE: Inadequate participant recruitment is a major problem facing clinical research. Recent studies have demonstrated that electronic health record (EHR)-based, point-of-care, clinical trial alerts (CTA) can improve participant recruitment to certain clinical research studies. Despite their promise, much remains to be learned about the use of CTAs. Our objective was to study whether repeated exposure to such alerts leads to declining user responsiveness and to characterize its extent if present to better inform future CTA deployments. METHODS: During a 36-week study period, we systematically documented the response patterns of 178 physician users randomized to receive CTAs for an ongoing clinical trial. Data were collected on: (1) response rates to the CTA; and (2) referral rates per physician, per time unit. Variables of interest were offset by the log of the total number of alerts received by that physician during that time period, in a Poisson regression. RESULTS: Response rates demonstrated a significant downward trend across time, with response rates decreasing by 2.7% for each advancing time period, significantly different from zero (flat) (p&amp;lt;0.0001). Even after 36 weeks, response rates remained in the 30%-40% range. Subgroup analyses revealed differences between community-based versus university-based physicians (p=0.0489). DISCUSSION: CTA responsiveness declined gradually over prolonged exposure, although it remained reasonably high even after 36 weeks of exposure. There were also notable differences between community-based versus university-based users. CONCLUSIONS: These findings add to the limited literature on this form of EHR-based alert fatigue and should help inform future tailoring, deployment, and further study of CTAs.. Embi PJ, Leonard AC. Evaluating alert fatigue over time to EHR-based clinical trial alerts: findings from a randomized controlled study. Journal of the American Medical Informatics Association : JAMIA. 2012 Jun;19(e1):e145-8.
  35. Kopcke – study form europe demonstrating benefit of augmenting manual strategies to identify and recruit patients with clinical data reports Green – nice study showing how use of a research participant registry targeting undrereprested minority groups can help increase awareness, and as part of a multi-pronged approach to enhancing recruitment.
  36. Medical care – EDM forum issue s- 16 articles – June 2012 JAMIA focus on TBI And CRI – with 21 on CRI – July 2012 Several of the ones highlighted in this talk from one of these