Trial Sponsors and Their Contract Labs: Better Collaboration via OpenClinica

At Geneuity Clinical Research Services, we do lab tests for trial sponsors. As readers of this blog know, we use OpenClinica internally as an LIS (laboratory information system), but as more and more drug companies and CRO’s adopt OpenClinica we foresee the day when we will be using their installations as our LIS, not ours.  A common platform will eliminate lots of duplicated effort and will allow for real-time transparency and better collaboration.  But it will also require sponsors to design their CRF’s with their contracting laboratories in mind.  In this article, we describe how this could be done.

First, consider specimen collection and tracking.  Normally, trial sponsors don’t consider doing this within the context of OpenClinica.  But they should.  Let’s say a specimen accidentally thaws in transit between the collection site and the contract lab.  Shouldn’t that fact be summarily recorded in the same context as the resulting lab test whose value may ultimately be reported to the FDA?  I should say so.

So, can OpenClinica be configured to do this? Yes and easily. A separate CRF dedicated to specimen collection could be designed and assigned to each event.  Alternatively, a specimen section could be added to already existing CRF’s.  Either way, fields for such things like accession number and specimen type could then be included.  These would be filled in by site personnel responsible for specimen collection.  Additional fields like ‘shipping deviations’ and ‘laboratory receipt date’ could also be included and would be filled in by lab personnel upon specimen delivery to the testing lab.  When it comes time for data analysis, the sponsor can use OpenClinica’s data export capabilities to exclude or include those lab results with shipping deviations and to investigate the consequences.

Other important aspects of specimen collection include printing labels to barcode samples and generating an attendant paper manifest (know as a requisition) against which labs can check incoming shipments of specimens.  OpenClinica can’t do such things currently.  It would require a whole new software module, but lots of added value could be achieved if one were written.  For instance, one can envision that after accessioning a specimen, site personnel could print a corresponding requisition from the same application window.  Also, imagine the time savings if lab personnel could conveniently print barcode labels after receiving a specimen and recording its receipt date and shipping deviations (if any).  And because the paper requisitions would be generated within the context of OpenClinica, subsequent source data verification by lab personnel could be expedited using QR-encoded URL’s that drill-down into the patient-event matrix. For more on this, see here.

Specimen tracking is just part of the story when it comes to sponsors and their contract labs.  Getting lab data from the laboratory testing platform into OpenClinica is another.  Recently during OpenClinica’s March 22 Global Conference in Bethesda, Akaza Research and Geneuity did a live demonstration of how this can be achieved using a set of MirthConnect channels. A batch of raw lab data keyed only to accession numbers was sent from Geneuity’s corporate headquarters in Maryville, TN to a remote OpenClinica installation hosted at Akaza’s Waltham, MA facility where it was inserted into the database programmatically via an awaiting web service. The insertion was streamlined, secure and seamless.  When setting up a trial, sponsors should think about the lessons this demo provides and consider distributing already configured and validated MirthConnect channels to their contract labs.  In this way, sponsors can control how their data is treated and understand every detail of its electronic provenance. And because MirthConnect can be configured to store its history, the trial’s audit trail can be extended upstream to the data’s very source.
Finally, consider invoicing.  Contract labs have to be paid when they do a test.  Monthly invoicing reports could be generated from OpenClinica by configuring an appropriate ‘data set’ and having it execute at the end of each month using the application’s new built-in quartz scheduler.  In this way, billing would be a snap and everybody would be on the same page.

In summary, how can trial sponsors configure OpenClinica to collaborate better with their contract labs? Do the following, keeping the workflow shown in Figure 1 in mind:

1.    Include a specimen accessioning CRF for each event.  Educate your collection-site people and your lab people as to who is responsible for which fields.  Use OpenClinica’s internal messaging system to remind people of their roles when the study is actually underway.
2.    Exploit OpenClinica’s web services framework to enable batch uploads of laboratory data.
3.    Configure and validate MirthConnect channels to get the lab results from the source data files to your OpenClinica installation.
4.    Distribute these channels to your lab contractors and educate them on their use.
5.    Configure OpenClinica to automatically generate monthly data sets for billing purposes.

The bottom-line: OpenClinica is infinitely configurable and sponsors should start doing so with their lab contractors in mind.  The result will mean both better collaboration and lower costs.

Figure 1: A specimen is collected from a subject on site. The on-site data manager logs into OpenClinica and accessions the sample and prints an accompanying hard-copy requisition. The sample is then shipped to the contracting laboratory where lab personnel log into OpenClinica and indicate they have received the sample. Specimens are then tested in batch and the results are then uploaded en masse into the sponsor's installation of OpenClinica using a thoroughly vetted, validated and auditable MirthConnect channeling system.

Preview of the March 22nd OpenClinica Global Conference

With just a week to go, the OpenClinica Global Conference is shaping up to be an excellent event for learning about OpenClinica and networking with members of the OpenClinica community.

This is the first ever Global Conference and we are thrilled to have as a keynote speaker Mark Adams, Project Manager for the National Cancer Institute’s Cancer Biomedical Informatics Grid (caBIG). As a fellow pioneer working to bring open source to clinical research domain, caBIG has developed a set of interoperable, open source clinical informatics tools which address functions such as adverse event reporting, patient registries, study calendaring, clinical trial management, imaging, and tissue banking. The caBIG project and OpenClinica together illustrate the broad impact open source is having on clinical trials.

The conference program extends along three tracks with case studies, panel discussions, tutorials, and presentations from clinical trial sponsors, CROs, academic groups, and IT services companies. Content is oriented towards both technical and non-technical audiences. Selected topics include:

  • An unveiling of the new OpenClinica CRF Library, a curated repository of standards-based eCRFs for OpenClinica
  • Case studies from sponsors and CROs showing how they have used OpenClinica
  • Presentations of tools and extensions developed around OpenClinica
  • Tutorial for installing OpenClinica
  • Tools, tips, and techniques for using OpenClinica data in SAS
  • Live demonstration of automated data interchange with OpenClinica
  • Automating the data import process
  • Validating OpenClinica for 21 CFR Part 11 compliance
  • Generating ad hoc reports
  • Modularization of the OpenClinica source code and introduction to the OpenClinica Developer Network

A full suite of training classes for data managers, biostatisticans, project managers, system administrators, and developers are also being offered immediately preceding and following the conference.

There is still time to register for this event. See www.openclinicaconference.org for more program information and registration details.

We look forward to seeing you next week!

OpenClinica CRF Library

UPDATE (03-May-2010): The CRF Library is now live at library.openclinica.org.

Our vision at Akaza Research is to accelerate clinical research through open technology infrastructure. We do this through an open source software license, supporting a participatory community, and adhering to published open standards.

We are nearing another milestone that will further this vision. The OpenClinica CRF Library, currently in the final stages of development, will allow users to find, share, and re-use case report forms (CRFs) for OpenClinica. By utilizing the OpenClinica CRF Library, users will be able to:

  • Enable faster study startup by accessing a well organized, searchable database of OpenClinica CRF templates
  • Promote data standardization within their organization through re-use of CRFs that adhere to open industry standards
  • Derive customized versions from standardized CRF templates simply by editing the OpenClinica CRF Templates
  • Minimize time and cost spent on study training, testing, and validation by accessing value-added resources and documentation (including implementation guides, CRF Completion Guidelines, and test scripts) associated with the CRF templates in the library.

The library will be searchable by keyword and browsable by CRF type. Most CRFs are derived from authoritative, public standards sources such as the CDISC Clinical Data Acquisition Standards Harmonization (CDASH) initiative and the National Cancer Institute’s Cancer Data Standards Repository (caDSR).

In keeping with our vision, the CRF Library is the product of a participatory community and is based on open source software. Last April, we assembled a volunteer Steering Committee to guide development of the library. Committee members Liz Watts of Starfire Research, Lori Brix of Silent Partners, Derek Wimmer of Wimmer Clinical, and Elisa Priest of Baylor Research Institute have worked scrupulously to identify content, develop supporting materials for the CRFs, and implement workflows that will ensure quality resources. Their substantial knowledge of the CDASH standard and data management expertise has been invaluable. The broader community has also had a hand in building out this resource, through the user mailing list and at meetings of the OpenClinica Community Virtual Forum.

Content & Quality

One of the first questions the Steering Committee asked was, ‘How do we manage quality of content and metadata?’ There are many community-driven, peer-review, and commercial validation models that could work, from a loose ‘wikipedia’-style structure to more rigid frameworks for curation and standardization. We needed to adopt the right mix for our content and our community. The Committee emphasized the need for a high-quality ‘core’ set of CRFs that have broad applicability across studies, align to leading standards, and are accompanied by detailed resources which aid in implementation. At the same time, a larger, more diverse repository of CRF content would make the library useful to many in the OpenClinica community.

The result of this has been to create two broad classes of CRFs in the library, Curated CRFs and and Non-Curated CRFs.

Curated CRFs have gone through a rigorous peer review, testing, and annotation process. They include enhanced metadata, detailed specifications, validation test scripts, enhanced edit checks, and reference documentation such as an Implementation Guide and CRF Completion Guidelines. The initial collection of Curated CRFs in the library will be aligned with the CDASH Domains. The intent is to make it as easy as possible to implement these CRFs into a study, in ‘as-is’ or customized form, with confidence in the quality and accuracy of the CRF.

Non-Curated CRFs will be contributed by members of the community who wish to share their CRFs with others, or will be derived from existing non-proprietary electronic sources such as the National Cancer Institute’s Cancer Data Standards Repository (caDSR). These CRFs undergo less formal review and testing and have fewer supporting materials, instead will rely more heavily on community feedback and annotations.

Because of the significant investment made in annotation, review, and testing, full access to Curated CRFs and all the associated metadata, documentation, and associated resources will be available only to OpenClinica Enterprise Edition Subscribers. Non-Curated CRFs, and limited versions of Curated CRFs without detailed metadata or documentation will be freely available to all members of the OpenClinica community.

Contribution

Based on past discussions on the OpenClinica mailing lists and the Community Virtual Forum, we see substantial interest among community members in contributing and sharing CRFs. This is a very exciting prospect, and we will need community members to contribute enough quality CRF content to make the approach viable. Many community members have expressed interest in sharing their CRFs for others’ benefit, but also identified it as a way to get feedback and improve the forms for their own purposes. To provide a foundation for such contributions, the CRF Library will adhere to the following principles:

1) Contributors will be appropriately attributed and recognized for their contributions. Creative Commons (http://creativecommons.org/) provides widely used guidelines and license agreements to enable this type of sharing. CRFs in the library or derived therefrom will be made available under the Creative Commons Attribution 3.0 License. Contributors must represent that they (or their organization) have the legal right to contribute a CRF, and are not infringing on someone else’s copyright. When featuring the most popular or most highly rated CRFs, the CRF Library will highlight the identity of the contributor (at least by screen name).

2) Members of the community will be empowered to build on and improve others’ contributions for the benefit of all. All community-contributed CRFs will also be freely available to community members, and we will put into place popularity, versioning, and annotation features to allow users of a CRF to provide feedback and/or modifications to the original author.

Next Steps

As I mentioned at the start of the post, we are approaching roll-out of the CRF Library within initial CDASH-based content, and starting acceptance of community contributions. The roll-out will be aligned with the OpenClinica Global Conference (March 22nd in Bethesda, MD USA) and the CRF Library will be a featured topic at the event. It’s been a long time in development and we are excited to be nearing this milestone!

OpenClinica 3.0.1 Features Improved CRF Save Times

Akaza Research will be releasing a maintenance update of OpenClinica 3.0, which by itself probably does not illicit much excitement.  Usually maintenance releases only fix small bugs and offer little noticeable improvements to a user’s overall experience.  However,  3.0.1 will offer a dramatic improvement for a user’s experience with regards to the amount of time it takes Rules to run on a CRF.

Users of previous versions of OpenClinica would reach pain points when trying to save data entered onto certain CRFs if the study build had applied very complex Rules on a particular CRF section. For example, if the system had to check more than 10 variables to ensure one particular field had accurate data, the user might experience a save time of 2 or even 3 minutes in some circumstances.  In a test environment, we were actually able to create a scenario where the CRF save time took 19 minutes!

As part of 3.0.1, among other things, we have dramatically improved the save time of a CRF with complex Rules.  For instance, in the extreme scenario utilized in our test environment, we were able to cut the save time from 19 minutes down to 10 seconds.  That is about a 11,400% improvement!  For more typical users who were experiencing 2 or 3 minute save times, this has been cut to 3-5 seconds.

We are committed to improving the performance of OpenClinica, and can even offer faster experiences to the users of the OpenClinica Enterprise Edition.  Please see our website for the differences between the Enterprise and Community versions of OpenClinica.

OpenClinica 3.0.1 will be out next week!

Rapid Deployment of New Functionality in OpenClinica Using MirthConnect

In a previous article, we describe how we at Geneuity Clinical Research Services exploit OpenClinica’s new web services feature to automate the entry of lab data keyed to accession numbers.  Here, we describe more fully how and why we use MirthConnect.

Started in 2006, MirthConnect is an open source project sponsored by the Mirth Corporation of Irvine, CA.  It is middleware designed to transform, route and deliver data.  It supports HL7, X12, XML, DICOM, EDI, NCPDP and plain old delimited text.  It can route via MLLP, TCP/IP, HTTP, files, databases, S/FTP, Email, JMS, Web Services, PDF/RTF Documents and custom Java/JavaScript.  MirthConnect has been likened to a Swiss army knife and justifiably so.

Channels are the heart and soul of a MirthConnect installation.  A channel is user defined and has a source and a destination.  A source may be a flat file residing on a remote server or a web service call or a database query or even another channel—whatever you like, it doesn’t matter. A destination may be to write a PDF document, email somebody an attachment or enter data into a database.  Again, whatever!

To illustrate, say you want to poll a database and generate a weekly report.  No sweat! Using MirthConnect’s easy-to-use drag-and-drop template-based editor, define a channel with a database reader as a source, and a document writer as a destination, fill in details like user names, passwords and machine names, define which database fields you want to retrieve and how you want to display the data, and you’re done!  MirthConnect’s daemon handles the rest based on your channel’s configuration.

Once defined, a channel can be exported as XML for later import into another MirthConnect installation.  This is all done with the point and a click of a mouse.

At Geneuity, we use MirthConnect to get data in and out of OpenClinica.  Originally, we used custom JAVA code to do this.  But once we found MirthConnect, we quickly realized we were reinventing the wheel.  Why do that?

Here’s a concrete example.  Consider the very simple CRF from a mock OpenClinica installation shown in Figure 1.  It has three groups of items: accessioning, results and reportage.  When a specimen arrives at Geneuity, the lab tech looks up the patient and event pairing in the subject matrix as specified by the requisition and types into the CRF the accession number, the receipt date and any shipping deviations.  This is done by hand and is indicated as step 1 of Figure 2.

Then, as shown in step 2 of Figure 2, the tech tests the specimen at the testing platform.  In step 3, the platform spits out the data whereupon a collection of MirthConnect channels operating in tandem parses the results, transforms them into SOAP messages and sends them to the EventDataInsertEndpoint web service feature of OpenClinica for upload into the CRF fields designated ‘Assay date’ and ‘Analyte concentration’.

After the tech reviews the data and marks it complete, another collection of channels polls the database for results newly marked complete, generates and delivers PDF reports of the corresponding data (step 4) and then reports back to OpenClinica (step 5) via EventDataInsert the details of the reportage, including status, time and any errors (see the third and last item grouping labeled ‘REPORTAGE’ in Figure 1).

The scenario outlined above requires NO CUSTOM CODE beyond the channel configurations and these are encapsulated and standardized by design.  As such, you don’t need an army of coders on staff to develop and maintain them.

Both OpenClinica and MirthConnect are great as standalone products.  Linked together, however, they really sizzle.

Figure 1: A simple CRF from a mock OpenClinica installation
Figure 1: A simple CRF from a mock OpenClinica installation
Figure 2: This shows how the different item groupings in the CRF depicted in Figure 1 are populated.  Values for items under ACCESSIONING are entered manually by the lab tech.  Values for items under RESULTS are populated by the Mirth channels continuously listening for in-coming data from the clinical testing platform.  Values for items under REPORTAGE are populated by a distinct set of  Mirth channels responsible for polling and reporting newly completed results.
Figure 2: This shows how the different item groupings in the CRF depicted in Figure 1 are populated. Values for items under ACCESSIONING are entered manually by the lab tech. Values for items under RESULTS are populated by the Mirth channels continuously listening for in-coming data from the clinical testing platform. Values for items under REPORTAGE are populated by a distinct set of Mirth channels responsible for polling and reporting newly completed results.

OpenClinica and the Paper Chase: A Case Study

The developers of OpenClinica like to say they are ‘powering the electronic data capture (EDC) revolution’ in clinical data management and indeed that’s the case.  However, sometimes there’s no substitute for paper, especially when it comes to tracking and handling laboratory specimens.  We at Geneuity should know: testing lab specimens for clinical trials is our business.  This article shows how OpenClinica and paper records can augment one another through the use of URL-encoding barcodes.

Readers of this blog probably already know the drill:  a specimen is collected, a paper requisition is attached and the whole kit and kaboodle is mailed to a laboratory for testing.  When a specimen arrives at Geneuity, we log into OpenClinica’s web interface, look up the patient and event pairing in the subject matrix as specified by the requisition and then finally type in the values for items like accession number, receipt date, shipping deviations, freezer location and the like.  When one or two specimens arrive, this process (called ‘accessioning’) is no problem; when 20 to 60 arrive, it rapidly becomes tedious.

In a more perfect world, things would be easier and more automated.  Here’s one potential scenario to help achieve this.  In addition to all the necessary information in human-readable form, also print on the requisition a QR barcode that encodes the URL corresponding to the appropriate event case report form (CRF) in the study’s OpenClinica installation.  For instance, consider the example shown in Figure 1.

It encodes: “https://myOpenClinicaInstall.com/InitialDataEntry?eventCRFId=1” (for illustration only, not intended to link anywhere for real).  Upon being scanned with an appropriate hand-held reader (or smart-phone even), this would automatically direct the lab technician’s browser to the correct screen to input the attendant accessioning information for study event number one.  This would eliminate the manual look-up step described above and would reduce tedium and errors as a consequence.

Implementing this idea would require enabling OpenClinica to print out requisitions.  While challenging, this would not be impossible.  Indeed, middle-ware like MirthConnect may make it relatively easy.

Here’s another example of paper and OpenClinica working together, one that Geneuity actually implements currently to facilitate quality control.  Prior to testing a batch of specimens, lab technicians here use a custom Mirth channel to print out details of the samples to be tested.  A dummy example is shown in Figure 2.  As shown, it includes a simple linear barcode of the accession number, the principle means of tracking specimens in a clinical lab.  Scanning this saves the technician from having to type it into the testing platform during set-up.  It also contains a QR barcode specifying the event-specific URL that directs the technician where to go to review the data upon automatic upload into OpenClinica.  Having this URL handy means the technician doesn’t have to look it up in the subject matrix table which oftentimes has hundreds or even thousands of entries.

URL-encoding barcodes are a cheap and reliable way of linking physical objects with on-line databases, and nowhere is this link more critical than when tracking clinical specimens.  Thanks to Akaza’s commitment to open source, it’s easy to incorporate this technology into OpenClinica and to realize the myriad of benefits.

Figure 1: a QR barcode encoding an event-specific URL in a mock OpenClinica installation
Figure 1: a QR barcode encoding an event-specific URL in a mock OpenClinica installation
Figure 2: A list of specimens to be tested reported by a Mirth channel extracting from a mock OpenClinica installation.  The linear barcode helps with data entry at the testing platform while the 2D QR barcode is used to direct the lab tech's browser to the appropriate URL in OpenClinica for subsequent data review after testing is complete.
Figure 2: A list of specimens to be tested reported by a Mirth channel extracting from a mock OpenClinica installation. The linear barcode helps with data entry at the testing platform while the 2D QR barcode is used to direct the lab tech's browser to the appropriate URL in OpenClinica for subsequent data review after testing is complete.

OpenClinica 3.0 Features Preview: Part III

Welcome to the 3rd and final installment of the OpenClinica 3.0 features preview!  This post covers the new Web Services interface that is part of 3.0 and the job scheduler that can be used to automate Data Import and Data Export jobs.

OpenClinica 3.0 allows for programmatic interaction with external applications to reduce manual data entry and facilitate real-time data interchange with other systems.  The OpenClinica web services interface uses a SOAP-based API to allow the registering of a subject and scheduling of an event for a study subject.

OpenClinica provides a WSDL (Web Service Definition Language) that defines a structured format which allows OpenClinica to accept “messages” from an external system. For example, an EHR system could register subjects for a study in OpenClinica without direct human intervention. At the same time, the EHR could also be programmatically scheduling study events for these subjects. More information about the OpenClinica API can be found on the OpenClinica developer wiki.

An early reference implementation conducted by clinical lab Geneuity used the API to create a web service which inserts data programmatically into OpenClinica CRFs directly from laboratory devices. See the post by Geneuity’s Colton Smith below.

Another major productivity tool in 3.0 is the introduction of a Job Scheduler for automating bulk data import and export.  With this feature users can define a job that will generate an export at a specified time interval.  The Jobs Scheduler can also be configured to regularly scan a specific location for CDISC ODM files and run data imports when a new file is available. This feature can be particularly helpful in automating routing functions, such as the incorporation of lab data into OpenClinica from an external system.  The lab data does need to be in a valid CDISC ODM format (this can be accomplished via another great open source tool called Mirth), but it does save a person from entering data in two applications separately.

At time of this post, OpenClinica 3.0 is currently released as a beta3, but the production ready application is soon to follow. The application is passing through the highly rigorous strictures of our quality system (think Navy Seals training for software) and the output will be fully validated and ready of use in roughly a month. Needless to say, I, and everyone else here at Akaza is very excited to be so close to releasing 3.0. It is already quite clear that this release will have a momentous, positive impact on the community.

Facilitated Data Entry of Lab Results Using OpenClinica’s New Web Services Feature

As mentioned previously, we at Geneuity Clinical Research Services are big fans of OpenClinica and are even more so now with the upcoming release of version 3.0 with its new web services capability.  This article describes how we exploit this new feature to help automate entry of lab results, a particularly important topic given that we do lots of batch testing of specimens and oftentimes test the same specimen for many different analytes.

Prior to 3.0, you had three options when it came to CRF data entry.  The first was to log into OpenClinica’s web interface and manually enter your data.  This was no problem so long as you didn’t have lots and lots of data.  But we did.

Alternatively, you could upload a flat file of your data as long as it was formatted in XML and associated with the appropriate subject id’s and visit descriptions.  Assembling this file wasn’t trivial though and manually looking up each specimen’s subject and event nearly defeated the purpose of the procedure, which was to save time and effort.

Finally, you could do what we did: write custom code to automate the job.  Lab data is amenable to this sort of approach because it is always tagged with something called an accession number that uniquely identifies it.  When designing CRF’s, we always make sure to include a field for the event’s accession number, and when a specimen first arrives through our door the first thing we do is to log into OpenClinica and enter the specimen’s accession number in the appropriate event’s CRF.  Because the number is unique to the study, this entry effectively tags the event and provides a ‘hook’ inside the database so that the event_crf_id of any data item subsequently  annotated with the accession number can be easily looked up using a database query like so: ‘SELECT event_crf_id FROM item_data WHERE value = ‘<accession_number>’.  This, in turn, gives you the requisite information to insert the lab data thusly: ‘INSERT INTO item_data VALUES (‘event_crf_id’, ‘value’ …’ provided you also know the item_id.

To implement this strategy, we wrote custom servlets that operated within the context of our OpenClinica installations.  More recently, we configured MirthConnect channels to do the same.   They worked well and data entry was greatly expedited, but the coding was complex and had to be refactored over and over again for each study and for every CRF change.  While helpful, this strategy wasn’t sustainable in the long run.

Luckily, the latest version of OpenClinica provides a way out.  It incorporates the Spring WS Framework which allows programmers to write something called a ‘web service.’  A web service digests and acts upon XML data sent to it on an on-demand basis over a network.  The source need not be a human being uploading data on a web form, but, more usefully, it can be, say, a clinical testing platform automatically spitting out HL7 messages.  This, of course, is ideal in our case.  So we wrote a web service called ‘EventDataInsert’ that parses XML containing lab data values annotated with accession numbers and item names, looks up the corresponding event_crf_id’s and item_id’s, and inserts the data into item_data accordingly.  The service is generic enough so that it doesn’t have to be refactored for each and every study, but it does make some critical assumptions.  Namely, it assumes that both accession numbers and item names are unique.  So care has to be taken to ensure both these preconditions are met.

The power of EventDataInsert doesn’t just lie in the fact that it handles inserts on an unattended basis, but also in that, like most web services, it requires only simple XML as input.  The latter makes the source of the data irrelevant as long as it can be correctly mapped and transformed into XML.  We often use MirthConnect to do this, using it’s easy-to-use graphical interface to configure channels between incoming raw data and OpenClinica’s web-service interfaces.

The figure below shows a typical deployment of OpenClinica at Geneuity.  MirthConnect is used not only to get data into OpenClinica but also to generate canned PDF reports of the results.  This scenario works for us and gets easier and easier to maintain as OpenClinica evolves new electronic data capture features and makes old ones ever more robust.

Diagram of OpenClinica at Genuity Clinical Research Services
Diagram of OpenClinica at Genuity Clinical Research Services

How a Busy Research Clinical Laboratory Deploys OpenClinica as a Laboratory Information System (LIS)

Here at Geneuity Research Services, we do laboratory tests for clients
conducting clinical trials. We are a one-­stop shop, handling everything
from routine clinical assays to esoteric molecular analyses. We use
OpenClinica as an in-­house LIS to keep track of work­flow and to help
with administrative tasks like billing and specimen archiving. This isn’t
exactly what the developers of OpenClinica had in mind originally. The
application was designed from the point of view of trial sponsors, not their
subcontractors. But it works very well for us nonetheless. In this article,
we briefly describe how we do it.

As everybody who uses OpenClinica knows, defining your event x
CRF matrix is the most important step in configuring a trial. When a
client comes to us with a new trial, we do just that. We are careful
to reproduce the anticipated flow of events and patient groupings
just as designated by the trial’s specifications. “Why bother?”
you’re probably asking. “You’re just a subcontractor. That’s not your
concern.” But it is. Invariably, specimens get mislabeled and
inappropriate tests get ordered, and we’re able to detect many such
mistakes by doing a quick visual inspection of OpenClinica’s patient
x event dashboard with its easy-­to-­take-­in iconification. We feel
that this double-checking is part of our service to the sponsor.

CRF design is our next consideration. In this case, we don’t
try to reproduce everything required from the sponsor’s point of
view. Instead, we design a set of CRF’s that reflects just our role
as a contract clinical laboratory. This means that our CRF’s are far
more narrowly focused and less complicated. But it also means we
include some unique types of fields for pricing, specimen archiving
and the like, items that a trial sponsor usually doesn’t need to
address in their CRF’s but which are very helpful to us.

We are very careful how we name our items when crafting our
CRF’s. Specifically, we use the same terminology across our trials
whenever possible. For instance, the field for a specimen’s accession
number is always named ‘accession_number‘. Likewise, we consistently
use the names ‘freezer‘, ‘received_date‘, ‘price‘, ‘shipping_deviation
and ‘%assay_date‘ (where % is the wildcard string).

Using such a controlled vocabulary is vital in our case because
we use a separate installation of OpenClinica for each study and
employ the postgresql contrib module ‘dblink’ to federate their
attendant databases for querying. A helter­skeleter vocabulary would
render the latter problematic, to say the very least.

For example, we wrote a federated database procedure we call
accessions(). When executed, it consults the accession_number field
in all our installations and returns the number of accessioned
specimens broken down by trial name. This table lists some of the
federated procedures we’ve developed and their functionality.
Collectively, they provide us with a real­time, global snap­shot of
our work­flow and freezer contents.

Because OpenClinica is web­-based and has finely grained user
roles, our clients can remotely log into their respective
installations at our site with read­-only privileges and see the
status of their specimens whenever they want. Conversely, when we
think a specimen has been mislabeled or have some other issue, we can
call a client and direct them to a particular URL displaying the
pertinent information and seek clarification. OpenClinica thus
becomes a shareable laboratory notebook between us and our clients.

The bottom­line: OpenClinica works for Geneuity. Because
OpenClinica is open source, elegantly designed and well documented,
we are able to tailor the application to our needs. In the spirit of
mutual collaboration and aid fostered by OpenClinica’s lead
developers at Akaza Research, we’re making our federated procedures
freely available. They can be downloaded here.

Adventures in Web-Based Electronic Data Capture (EDC) – An OpenClinica Case Study

A recent issue of Applied Clinical Trials Online features a case study of OpenClinica Electronic Data Capture (EDC) adoption by German device company, Retina Implant, AG. Here’s a short excerpt:

“Last summer, Retina Implant started using OpenClinica for its latest trial, which is comprised of 11 studies. Currently, five of those studies have acquired subjects and are up and running with the OpenClinica CRF process. Randomization of study subjects are done outside OpenClinica, as it doesn’t have this feature. So far, Hekmat is appreciative of the flexibility of the platform, its ease of use among the global site staff, and the ability to view data in real-time via the Web browser.”

Click here for the full article.