Clinical Research Informatics
I.
The need for Clinical Research Informatics:
Healthcare
providers having a ‘Research Centre/Institute’ tag suffixed to their display
name has been a widespread phenomenon in our country. But in reality only a handful
of them actually engage in active clinical research while the others often
mistakenly use this to reap commercial benefits. The fact that clinical
research is the lynchpin that connects innovative technologies from basic
discovery research to their application as breakthroughs in patient care is deeply
undervalued by healthcare centers. Most care providers treat clinical research
as a byproduct of clinical care and the former is more of an afterthought / add
on to the later.
The flow of
research from bench to bedside and back again, through review in practice,
necessitates a comprehensive research strategy aligned to the organizational
vision. Many organizations falter with their research programs in absence of an
appropriate strategy and leadership commitment.
Developing
the right informatics infrastructure through provisioning relevant IT solutions
is a vital cog to a comprehensive research strategy. Moreover, with the correct
business model healthcare institutions derive additional research value from a
sophisticated IT infrastructure.
But
improvements through the use of electronic information exchange have been slow
in clinical research studies for many reasons, including the lack of
informatics infrastructure, exemplified by low EMR adoption, inconsistent data
standards and database architecture, and insufficient analytic tools. Even
though our healthcare leaders are being increasingly aware of the need for
digitizing the hospital operations, potential efficiencies available through IT
solutions for clinical research are largely undermined.
Studies
indicated that over 75 percent of information obtained for support of clinical
trials was entered on paper [1]. Use of electronic solutions can reduce the
cost of data collection by 55% over paper [2]. Furthermore, the information
once collected is typically entered for various needs from four to seven times
by clinicians
Additionally,
three main fields in science and medicine that are currently disconnected: 1)
basic research, which tries to understand the fundamental principles and
phenomena that drive cells, organisms and systems in both normal and
pathological conditions (such as cancer); 2) translational research and applied
medicine, which represent the application of basic research to solve specific
problems, aid in diseases and help society at different levels and 3) EMRs or
“Electronic Health Records” that have been developed as a new technology to
facilitate both patient care and research by collecting and archiving patients’
history. The key bottleneck is how to efficiently integrate these three
independent “parts” of medical and scientific areas in a single solution to
improve patient care.
·
Integration of
patient and research data
·
Sponsors to
understand the progress of their research projects
·
Institutions to
ensure ethical and regulatory compliance
·
Robust data
collection, processing and reporting
·
Capturing and
leveraging Intellectual Property generated
·
Enable collaboration
among partners and others in research fraternity
II.
The Clinical Research Workflow
Clinical
Research Study might be stated as an overarching terminology which envisages
sponsored or investigator initiated clinical trials or other survey oriented
non interventional studies. A typical clinical research study lifecycle
comprises of the following steps. The study originates from a hypothesis, and
then is detailed in a study protocol. The protocol documentation includes study
design and operational details such as the duration of the study, type of
participants, inclusion and exclusion criteria for subjects, patients’ schedule
for assessment and interventions, medications and dosages. Following this, the
protocol is assessed by an Institutional Ethics Committee (IEC) or
Institutional Review Board (IRB) to ensure the appropriateness of the clinical
trial protocol as well as weigh the risks and benefits to study participants.
It also reviews all study-related materials before and during the trial.
At the heart
of clinical research is the immense data collection and analysis that determines
the efficacy and safety of medical therapies. Currently, the processes for
identifying subjects eligible for research, collecting study parameters,
assembling information from multiple study sites, conducting oversight of study
protocols, and analyzing results involve manual operations which are time
consuming, labor intensive, and expensive
III.
Capabilities of an Integrated Clinical
Research Informatics Model:
Historically,
research and healthcare information technology systems have been disconnected,
supporting separate, but sometimes redundant, processes and workflows.
Unfortunately, the use of disparate systems can result in patient safety
concerns, inefficient processes, data quality issues and challenges
Most
Clinical Research Organizations (CROs’) and pharmaceutical companies engaged in
clinical trials rely on commercial off the shelf Clinical Trial Management
System (CTMS) solutions for digitizing the trial process. A CTMS package is an
integrated suite of applications sharing a common database designed to help
manage clinical trails acitivies at different levels. But for a hospital based
clinical research presents unique informatics requirements that are amenable to
solutions supported by EMR systems which might be already deployed. Such scenarios
solicit an EMR integrated comprehensive informatics solution which extends
beyond the scope of a traditional CTMS solution. The solution should enable:
·
Proactive identification of potential research
subjects from the EMR database
·
Help screen and recruit research participants
·
Research data
collection through electronic data capture methods (EDC) from the EMR including Web, Hand held
devices, and Phone based Interactive Voice recognition (IVR)
·
IRB
Document management, amendment and
milestone tracking
·
Randomization and blinding of
participants in a randomized control trial
·
De-identification of data according to HIPAA standards
·
Trail reporting
and identify data queries that needs to be addressed
·
Adverse events reporting
·
Easily move valid
data from EMR into research registries
·
Facilitate secure EMR access for research auditors/ monitors
·
Appropriately billing for Research visits to the sponsor unlike the normal visit
·
Tagging
hospital patients enrolled in a research study for easy
identification
·
Capture rich structured data from
the EMR (phenotypic) and combine with bio-informatics data (genotypic)
·
Enable export data in format ( for eg:
CDISC )for initial statistical purposes or downstream integration with other
tools
·
Provide coding
methods for fields such as pathology or medication data.
IV.
The Clinical Research Informatics
Model
Moreover, this lays a longer-term
foundation for accelerated discovery, extensive outcomes research, and
ultimately a “learning health system” in which a “bench-to-bedside-to-bench”
cycle of information will support continual improvement in knowledge, care and
health
The model is split in two distinct zones meant
for Patient Care and Clinical Research intersected by a Pseudonymisation wall
Research Specific Functionalities within EMR
The
Electronic Medical Record (EMR) is the centerpiece to all patient care
activities in the hospital. It is capable of capturing and archiving all
information (for eg: charts, orders, results, medications, diagnosis,
interventions etc) generated during patient care. For a hospital engaged in
clinical research, the EMR can be optimized to envisage pro research
functionalities such as:
• Study Feasibility & Screening – The EMR has potential to be an ideal system to
search for patients that are eligible for an ongoing or potential study. All
patient records from the EMR is maintained in a EMR Data Warehouse (EMR-DW), a
system that enables the patient records to be stored and used for analytical
purposes. With advanced search capabilities, it’s also possible to retrieve a
series or records to retrospective chart reviews.
• Recruitment Alerting –Inclusion criteria for clinical research studies
can be programmed into the EMR, which can the proactively alert the attending
physician that a patient is eligible for enrolment into a study when they are
in the clinic. Failure to recruit a sufficient number of eligible subjects presents a
major impediment to the success of clinical trials. This can be addressed if
the EMR has the capability of a real time Clinical Trial Alert (CTA). Without the assistance of IT solutions,
recruitment is extremely slow, expensive, and low-yield.
• Patient Tagging & Participant Tracking – Identification of
hospital patients involved in a research is crucial to protecting the safety and rights of
participants. The EMR should be capable of flagging (a sort of identification
on the patient’s record) the patient enrolled in a clinical research strudy
with information about clinical trials/studies in which he/she is
participating. This would help clinical staff, investigators, study
coordinators, clinicians, and oversight bodies such as the IRB to follow
participants throughout the research process and ensure that their safety and
rights are protected. An Integrated participant tracking enables better
management and eliminates need for multiple data entry
• Protocol Document Management – The system should
have document management capabilities for
support grants, peer review, IRB continuing review, ethics approval, adverse
event reporting, etc and support the informed consent and re-consenting
processes. Organizations of a larger scale prefer dedicated Enterprise Content
Management systems to fulfill this need.
Research Study Management System: Core
Functionalities.
1.
eCRF & Electronic Data Capture
Traditionally
paper based Case Report Forms (CRF) have been used to transcribe relevant data
manually from the medical record of a clinical research study subject. In
a paper system, data are entered first on the clinical report form and second
by the data entry group into an electronic system.
An eCRF is a pre configured
electronic form that eliminates manual data entry/re entry and fetches the data
from the medical records through electronic data capture.
The Electronic Data Capture (EDC) is a
system that electronically transcribes clinical data from the EMR into the
electronic case report form (eCRF). EDC replaces the traditional paper-based
data collection methodology to streamline data collection and management.
Since data are entered into a data collection
tool only once, processing time for data entry is reduced, and transcription
errors are less likely. EDC can help clean and lock data faster than
traditional paper CRF systems.
2. Pseudonymisation
Research
studies must use de-identified patient data according to relevant standards
(for eg: HIPAA). This is not only a legal requirement but is essential for
protecting patients’ rights. With that in effect, the patient data flow from
clinical to research domain should channel through a data pseudonymisation
system. This system will enable de-identification of patient identifiable data
to accepted standards such as HIPPA, assign codes to the data as well as support re-identification of
patients in case of medical emergencies.
Following pseudonymisation the de-identified data is expected to reside
in a separate research domain where is can be used by researchers who cannot
identify which patient the data is particular to. This includes having the
capability to handle cases of very small populations
The
De-identification system needs to integrate with any system where Personal
Health Information (PHI) is collected and will then be used for research
purposes
3. Randomization
and Blinding
Randomization
capability enables locally sponsored interventional clinical studies for
systematic assigning patients to different study arms in a statistically robust
fashion. It needs to interface with clinical systems including, but not limited
to EMR, the Pharmacy System, and the research systems and its associated
electronic data management systems.
For blinded
clinical trial that involves providing a blinded drug based intervention the
hospital pharmacy system needs to capabilities to un-blind in an emergency the
study treatments and to manage the resupply to the patient on the behalf of the
study
4.
Data Management
Accurate,
reliable, usable data — it's the lifeblood of clinical research. The method an
investigator chooses for collecting, storing and analyzing data can mean the
difference between a study that advances the science and improves patient care,
or a study with inconclusive results and no publications. Typically the Data
Management functionality will capture all of the structured and unstructured
data that is captured in study documents. This can be used to provide a
warehouse of all research data that has been captured from the research
activities. Also there should be a role and site level access which allows
users from other institutions to contribute data to the studies
The system
should not only be able to support studies requiring low to medium data
collection complexity but also should be able to manage regulatory compliance
(for eg: 21 CFR Part 11), sophisticated data management and quality control,
for multi-site trials.
5.
Data Marts and Knowledge Management
A project data mart is typically project specific collection of
data that enables clinical and research data to be extracted from their primary
data management systems and combines and curates the study data into a system
that enables researchers to explore and analyze their data according to the
study design.
A Knowledge Management System is a searchable repository of
research results (or Facts") that capture the published and published
findings of research activities. This includes statistical relationships
between patients and their biology and integrates entities across patients,
literature, markers and drugs. Data collected from across the research
activates needs to be analyzed to make inferences about the specific research hypothesis.
V.
The way ahead
India is being touted as one of the fastest
growing market globally for clinical trials with more than 15% of global
clinical trials expected to be carried out in the country [3]. With increasing
market size and complexity there is a need of better ways to transfer and
access patient information electronically. A clinical research enterprise that
is configured around such electronic information systems will yield more rapid
scientific discovery and will provide significant support of related activities
including Comparative effectiveness of
clinical trials and other outcomes-related research; Quality of care
measurement; public health and safety monitoring, and post-marketing
surveillance.
With a
widespread EMR adoption, the interface between “bench and bedside” is gradually
becoming more porous and productive, while providing the required oversight. These
improvements will positively affect patients, physicians, researchers, entities
which invest in clinical research, and ultimately all who look to scientific
discovery to propel medical advancement
[1]
Alschuler L, Bain L, Kush RD. Improving data collection for patient care and
clinical trials. Sci Career Mag Mar 26 2004
[2] Pavlovic I, Kern T, Miklavcic D. Comparison
of paper-based and electronic data collection process in clinical trials: Costs
simulation study. Contemp Clin Trials 2009; 30: 300-16.
Literature Review:
