A Fresh Perspective on Upcoming OpenClinica Events

GrassGuy_KickedBackWhat a great time of year! The sun is out and the flowers, trees, and grass are blooming. There is no better time to spread the news about our fresh perspective on electronic data capture.

What are we up to?

  • We’ll be at SCT – Society for Clinical Trials 34th Annual Meeting in Boston next week, talking with over 650 professionals dedicated to the design, conduct and analysis of clinical trials.
  • Going to Shanghai! We will be holding our Central User training in Shanghai, China from May 28-31. This follows the DIA China Annual meeting, where OpenClinica was featured in numerous presentations.
  • We hope to see you at the OC13 Global Conference in Boston on June 21. We have an exciting lineup of great workshops, sessions, demos and training classes–there is something useful for everyone. We are really looking forward to the Boston Harbor Dinner Cruise for a chance to kick back after the event and visit with our OpenClinica friends. Sign up! You don’t want to miss this.
  • Capping off our spring events and immediately following OC13 is DIA 2013 in Boston, June 23-27. We are bracing ourselves for 7,000 life science professionals converging on our booth to take in our fresh perspective and enjoy some espresso, demonstrations and some very competitive games of cornhole (yes, this is a real game!). We have some great giveaways and prizes in an outdoor-themed space. Will you be there? If so, stop by Booth #122 and have some fun.

OpenClinica Next Generation

EnterpriseDo you want to boldly go where OC is going? Engage! Check out Nick Sophino’s blog on next generation OpenClinica. This is where to find information on prototype design and development for OpenClinica Next Generation. Nick is going to be showing off this work at OC13 so be sure to check out his session!

Throw a few steaks on the grill and kick back and enjoy the season. And, remember to always look for a fresh perspective.

Warm Regards,
Rob

Data Manager Humor

Thanks for making me laugh, Jackie 12182!

Data Management: Queries in clinical trials

 

 

New OpenClinica Developer Release: Revamped Print Module

A new developer release is available for OpenClinica. While it contains a number of significant improvements, one of the more fundamental changes is a reconstruction of OpenClinica’s print CRF functionality. To date, all printable screens resembled the existing web form interface for the eCRF, whereas now, this engine has been completely redesigned to more closely follow industry standard for printable views of web forms.

Why This Matters To Developers

Ok, I get it. You are a developer, so what’s the big deal about being able to send CRFs to the printer?  It is the technology behind this improvement that will hopefully catch your attention. Important changes have been occurring in the sphere of web apps, and I don’t mean just a sprinkling of AJAX here and there along with a UI that looks like Facebook. The real revolution goes much deeper.

Setting a precedent for OpenClinica: Completely Decoupled Client Technology using Web Services

The notion is simple. Create a browser-based client with the same decoupled technology that a iOS or Android mobile client requires. In plain English, this means that only data is sent back and forth between the client and the server. Just as is expected with a native OS mobile client, the browser-based client never relies on the server to generate or send any part of itself except when the URL is first accessed and loaded into the browser. The client is therefore completely decoupled and can be in complete control of their own state. This results in a more reliable, speedier, feature-packed, and easier to maintain platform for both the client and server. Another way to put it … in the not too distant future, our 400 or so JSP pages will be replaced by one or two main HTML templates and about a dozen small (less than 100 lines each) HTML component files.  But for now, take a look at our printable CRF design as an example of the way forward.

Getting to the Point: REST, JSON, JQuery, HTML, and CSS

What follows is a description of the processing path that starts with a REST URL and ends with a printable CRF.

  1. A user will click on a print icon that is part of many of the CRF view forms. The RESTful URL referenced in the link will be in the form of rest/metadata/html/print/{StudyOID}/{StudyEventOID}/{FormDefOID}. Using this combination, a wildcard asterisk character (*) can be placed as a specifier for all studies, all study events, and all CRFs, respectively.
  2. The first path element in the URL named “rest,” indicates that this is handled by our implementation of org.akaza.openclinica.web.restful.ODMMetadataRestResource, our Jersey JAX-WS controller servlet. The “metadata” in the second path element indicates that is for metadata only and no clinical data will be transmitted. The “html” in the third path element indicates that this will result in a rather simple JSP page at /WEB-INF/jsp/printcrf.jsp. This JSP page is the container for the JQuery code that will make a second REST call to the back-end to retrieve the CDISC ODM in JSON form and is also the container for the Javascript and JQuery code that converts the information contained in the ODM JSON into an HTML DIV element with the rendered printable CRF.
  3. The AJAX call that the Javascript method getPrintableContent() in js/app.js references is a URL in the form of rest/metadata/json/view/{StudyOID}/{StudyEventOID}/{FormDefOID}. It is the 3rd path element of “json” which indicates that the same ODMMetadataRestResource servlet will now fetch the relevant ODM XML metadata, convert it to JSON, and send it back to the callback portion of getPrintableContent(). In the callback portion, a call to app_odmRenderer.renderPrintableStudy() kicks off the process by which JavaScript inspects the JSON ODM object returned by the server and builds a DOM element that represents the portion of the metadata that is meant to be displayed as one or more CRFs.
  4. The DOM HTML is rendered with the help of JQuery Templates. This allows HTML fragments such as template/print_item_def.html, which are initially loaded in memory, to be combined with certain extracted key/value pairs to render an individual or list of components.

What’s on the Horizon

This first release extends to printing blank CRFs. Then, we will work to extend this to handle printing CRFs containing clinical data and very large printable form sets. The process described above will be similar, with the exception that all large documents, typically over 100 pages long, will be rendered using a Java rendering class that builds off of Velocity templates. The resulting server-side HTML page will be converted to a downloadable PDF.

- Nick Sophinos, Senior Developer

Click here for Developer Release

OpenClinica to present at DIA China Annual Meeting

There are numerous opportunities to learn about OpenClinica at the upcoming 5th DIA China Annual Meeting <http://www.diahome.org/en/Meetings-and-Training/Find-Meetings-and-Training/Meeting-Details.aspx?ProductID=31144> . The conference, held at the Beijing International Convention Center, runs from May 12-15. The event is expected to attract over 1,200 participants and is the largest annual meeting held by DIA in the Asia and Pacific region.

OpenClinica representatives will be hosting an exhibit as well delivering three poster presentations and one lecture:

  • CDISC Standards to Enhance Clinical Trial Efficiency
  • The Importance of Validated EDC System to Ensure Quality of Data
  • Electronic Data Capture (EDC): Providing A Significant Cost-Efficient Platform In Current Clinical Research Management
  • The Adoption of Electronic Data Capture (EDC) for Clinical Trial Data Management in China – The Case of ATHENA Healthcare Consultancy

Be sure to stop by the OpenClinica booth A18 to learn about new developments with the leading open source clinical trial software.

Coming up soon, OpenClinica will be running a public, open enrollment training class in Shanghai (June 4-7). More information <https://www.openclinica.com/open-enrollment-training> .

Importing OpenClinica Data Into R

R is a powerful open source statistical software package–many people think of it as an open source alternative to SAS. A number of OpenClinica users have been asking about how to bring data from OpenClinica into R. So, we recently published a write-up in the OpenClinica reference guide, providing instructions for importing data into R in three different ways:

  •     using a Tab-delimited file,
  •     using a CSV file, and
  •     using an Excel file.

Feedback and additional ideas are welcome.

- Ben Baumann

Using Patient-centered Technology to Improve Recruitment and Retention

Sponsors of clinical research must increasingly focus on improving patient engagement in order to meet many of today’s research challenges. Promising disruptions are already under way that could define new models for patient recruitment and retention.

In a time when drug development success is becoming scarcer and more expensive, the industry is looking everywhere it can for new, innovative approaches to improving health. Meeting recruitment goals is one of the biggest challenges for traditional clinical research. Less than one-third of people who come in for a screening end up completing a clinical trial.1 Thinking in a more patient-centric manner can help is in recruiting patients. A fundamental idea behind patient-centered research is to “amplify the patient’s role in the research process.”2 Employing new ways to engage patients and physicians while increasing their level of knowledge and trust can improve the sponsor’s ability to meet recruitment goals.

One often overlooked factor for study participation and retention is convenience. Raising the level of convenience for both the investigator and participant can eliminate a huge obstacle to non-participation or non-completion. There are many ways to incorporate increased levels of patient and physician convenience into trial design and execution, particularly using Internet-based technologies. For instance, social media can be an effective recruiting tool and an important way to build trust with targeted populations. Disease-specific online communities are becoming more and more prominent for chronic diseases. Matchmaking tools act as mediators that draw together researchers and participants. “Traditional” social media offers a less targeted, but no less effective, way to engage patients and investigators.

In general, the four key determinants of a person’s likelihood to participate in a trial are prior participation in research, existing relationships with researchers, involvement of trusted leaders, and trust in the organization. Keys to recruiting success in social media should keep these determinants in mind, and engage communities in a thoughtful, ethical way while respecting the norms of the community you are targeting.

Participant retention post-recruitment can be improved by strengthening the connections between participants and researchers, and enhancing communication structures to support these relationships.3 Capturing Patient Reported Outcomes electronically (ePRO), through the web or mobile devices, offers a way to interact with the participant in a meaningful way while also capturing critical data. For instance, offering the ePRO user risk scores and health recommendations based on their data, or using gamification techniques to increase protocol adherence, can enhance the traditional ePRO experience by offering direct, immediate value to the user. Enabling a “Bring Your Own Device” (BYOD) strategy can increase convenience for populations who already own their own smartphones or tablets. Of course, the study design and applicable regulatory considerations should drive when and how these techniques are used.

Increased focus on the patient experience is not a phenomenon unique to research, but something that is rapidly permeating healthcare systems. These rapid changes can enhance research engagement. There is enormous potential to capture far more robust data and have better follow up than ever before as widespread infrastructure is put in place for coordinated team-based care, home-based continuous monitoring, and wireless data reporting from medical devices. The (still elusive) promise of using the Electronic Health Record system in research to identify participants and capture clean, accurate trial data is more critical than ever before. As medical practices become more electronic and less paper-driven, investigators and staff should be engaged by providing them trial-specific information at the points in their workflow when they can best make use of it. Conversely, requiring them to go outside the workflows and systems they use in routine practice creates complexity and hassle that can deter research participation. A new level of integration between research and health data systems, based on standards (which exist) and open interfaces (which are coming, as part of Meaningful Use), will be necessary to make good on this potential.

As difficult research questions drive increased complexity in trial designs, many feel that the answer is to use technology in simple, scalable ways to engage more participants in research and capture more data. Dr. Russ Altman, a physician and Stanford professor recently told the New York Times, “There’s a growing sense in the field of informatics that we’ll take lots of data in exchange for perfectly controlled data. You can deal with the noise if the signal is strong enough.”4

References

1. Getz, Ken, The Gift of Participation: A Guide to Making Informed Decisions About Volunteering for a Clinical Trial, 2007, p40.

2. Pignone, Michael, MD, MPH, Challenges to Implementing Patient-Centered Research, Ann Intern Med. 18 September 2012;157(6):450-451

3. Nicholas Anderson, Caleb Bragg, Andrea Hartzler, Kelly Edwards, Participant-centric initiatives: Tools to facilitate engagement in research, Applied & Translational Genomics, Volume 1, 1 December 2012, Pages 25-29, ISSN 2212-0661, 10.1016/j.atg.2012.07.001.

4. http://www.nytimes.com/2013/01/15/health/mining-electronic-records-for-revealing-health-data.html?ref=health?src=dayp&_r=3&

OpenClinica 3.1.3 Community Version – Performance Test on HDD vs. SSD

Summary of hardware/software used in tests:

  • All tests are performed on Dell Vostro 3360 notebook in order to control identical of hardware
  • Vmware Workstation 8 is used to run both guest VM servers
  • Windows 2008 R2 Datacenter (trial) is used for both guest VM servers
  • One VM guest server is running directly on Dell Vostro 3360 notebook’s HDD to simulate HDD performance (2.5″ 5400 RPM), refer as VM-HDD
  • One VM guest server is running from SSD (connected to Dell Vostro 3360 notebook via external harddisk box with USB 3.0) to simulate SSD performance (2.5″ consumer grade SSD), refer as VM-SSD

Both VM guest servers have been configured as below:

Memory 2GB
Processors 2
Hard Disk (SCSI) 30GB (Pre-allocated)
Network Adapter Host-only (to exclude network latency)
Display Auto Detect
Shared Folders Disabled
  • OC 3.1.3 Community is installed and configured as https access only on both VM guest servers
  • All tests are performed by Firefox 18.0.1 installed on individual VM guest server in order to exclude network latency out of the tests
  • OC 3.1.3 database size is 236MB
  • PostgreSQL’s maintenance commands (VACUUM, Reindex) have been applied on both VM guest servers database before perform the tests
  • OC related components version info: Apache Tomcat 6.0.36, jdk 6u38 (x64) and PostgreSQL 8.4.15

Test Results – Data Entry

Storage Type
Time used in seconds (entry only first page of individual event). Lower is better.
Event 1
Event 2
Event 3
Event 4
Event 5
Event 6
Event 7
Total
VM-HDD
3.497
1.943
1.882
1.404
1.336
1.406
1.397
12.865
VM-SSD
1.893
1.41
1.425
1.225
1.121
1.158
1.099
9.331
SSD Performance Gain %
45.868
27.432
24.283
12.749
16.093
17.639
21.331
27.470

Comment: On average, SSD performance gain over HDD is around 27.47% which clearly shows shorter time to save entries data.

Test Results – Generic Dataset

Dataset File Type [uncompress file size/compressed (.zip) file size]
Time used in seconds. Lower is better.
VM-HDD
VM-SSD
SSD Performance Gain %
CDISC ODM XML 1.3 Full with OpenClinica extensions [4,593KB/25 KB]
948
1019
-7.49
CDISC ODM XML 1.3 Clinical Data with OpenClinica extensions [1,502KB/117KB]
939
1001
-6.60
CDISC ODM XML 1.3 Clinical Data [1,036KB/107KB]
1005
964
4.08
CDISC ODM XML 1.2 Clinical Data with OpenClinica extensions [1,451KB/115KB]
940
966
-2.77
CDISC ODM XML 1.2 Clinical Data [1,035KB/107KB]
970
961
0.93
Excel Spreadsheet [64KB/15KB]
1238
1145
7.51
Tab-delimited Text [64KB/14KB]
1251
1173
6.24
SPSS data and syntax [135KB/24KB]
1224
1180
3.59
Total
8515
8409
1.24

Comment: On average, SSD performance gain over HDD is just 1.24%. SSD does not have much advantage due to CPU usage and file write operations for processing datasets. SSD is even slower than HDD in some tests above.

Additional Test Results Iometer (www.iometer.org)

Details
VM-HDD
VM-SSD SSD Performance Gain % VM-SAS RIAD 10 SAS RAID 10 Performance Gain %
Read I/O per second (higher is better)
277.95
1539.68
553.94
1022.58
367.90
Write I/O per second (higher is better)
272.42
1520.15
558.02
1042.01
382.50
Total I/O per second (higher is better)
550.37
3059.83
559.96
2064.60
375.13
Read MBs per second (higher is better)
3.57
19.75
553.22
13.21
370.03
Write MBs per second (higher is better)
3.48
19.55
561.78
13.37
384.20
Total MBs per second (higher is better)
7.05
39.29
557.30
26.58
377.02
Average Read Response Time / ms (lower is better)
1.809
0.1824
991.78
0.5563
325.18
Average Write Response Time / ms (lower is better)
1.8203
0.4711
386.39
0.4081
446.04
Average I/O Response Time / ms (lower is better)
1.8146
0.3258
556.97
0.4815
376.86
Maximum Read Response Time / ms (lower is better)
384.3666
47.3384
811.96
131.6158
292.03
Maximum Write Response Time / ms (lower is better)
114.2165
50.6832
225.35
206.3535
-55.35
Maximum I/O Response Time / ms (lower is better)
384.3666
50.6832
758.37
206.3535
186.27
Test period 2 minutes, one configuration has been used inside IometerVM-SAS RAID 10, Test on a test server
Average Gain %
589.25
Average Gain %
318.98

Comments:

  • SSD enterprise grade may not give much higher performance over SSD consumer grade, but it provides higher endurance on server type workloads. SSD consumer grade with server type workloads may produce poor results.
  • SSD enterprise grade is much more expensive than SSD consumer grade. If you are planning to use SSD on the server, SSD enterprise grade is highly recommended (however, it’s up to you if you are willing to spend less and accept to risk your data)
  • For people who already used SAS disks with RAID 10 (hardware RAID), switch to SSD (enterprise grade) may not give you greater benefits, especially when looking at cost and space limitations
  • Internet connection speed/network latency is a key factor of for OpenClinica. Due to the inability to control this over test time, it was excluded from this list.
  • Due to organization’s confidential information, I cannot share the actual CRFs used in tests. The CRFs generally had minimal text, calendar, and option box with up to 20-30 items.

Content and Testing Results supplied by:

Montri Ridjaibun
Clinical Trials Database/Software Architect Manager
Mahidol-Oxford Tropical Medicine Research Unit (MORU)
Bangkok/Thailand

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