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Akaza conf 3.22

Date post: 18-Jun-2015
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OpenClinica OpenClinica Criteria Based Reports Criteria Based Reports Presented by Don Lawson – SilverLining Partners Brian Howard – Molecular NeuroImaging USE SLIDESHOW FOR AUDIO USE SLIDESHOW FOR AUDIO
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Page 1: Akaza conf 3.22

OpenClinicaOpenClinica Criteria Based Reports Criteria Based Reports

Presented by Don Lawson – SilverLining PartnersBrian Howard – Molecular NeuroImaging

USE SLIDESHOW FOR AUDIO

USE SLIDESHOW FOR AUDIO

Page 2: Akaza conf 3.22

MNI's VISIONMNI's VISION

•MNI’s vision evolved from the desire to search data across CRF items.

• It quickly expanded to filtering on the following attributes:

–Study–Subject ID–CRF–Event Definitions

Page 3: Akaza conf 3.22

Vision to Vision to RealityReality

With MNI’s architectural vision and Silverlining’s application development skills, we collaborated in developing a custom solution to meet the following goals:

–Criteria Based Reporting–Time Saving Building Reports–Report Sharing

Page 4: Akaza conf 3.22

WHAT IS THE BIG DEAL?WHAT IS THE BIG DEAL?

• OpenClinica is built on a Entity-Attribute-Value (EAV) database design which is ideal for clinical databases because of its flexibility in dynamically creating eCRFs in the system.

• Main disadvantages– Complicated programming needed to display

data in a conventional layout that the user understands

– Less efficient queries.

Page 5: Akaza conf 3.22

EAV Problems SolvedEAV Problems Solved

• Our application has eliminated the need to know how to construct SQL database instructions which enables administrative personnel to easily create complicated reports

– EAV DB instructions are several times more involved than relational database instructions

– Our application creates SQL instructions that can be exported to report generation software packages

• Response times in retrieving data are equal to relational database schemas

– Even querying small EAV databases performance is many times slower than relational DB schemas

– As the number of attributes increase using an EAV schema the execution time increases exponentially

• Data is transformed for statistical analysis operations using inverse constraint determination techniques

– EAV DB stores information in non searchable formats

Page 6: Akaza conf 3.22

What Makes Our Solution IdealWhat Makes Our Solution Ideal

• The ability to bring up a study with quick generation of CRF’s with OpenClinica

• The ability to generate ad-hoc reports in advance of setting up any SAS generated reports

• The SQL query that is created for each search is available to use with SAS or other reporting programs to query our Relational DB tables directly

• The easy search criteria capability and report generation rivals Relational DB designs for non SQL programmers

Page 7: Akaza conf 3.22

SOLUTIONSOLUTION

•An Excel based application that uses a GUI for easy and familiar access to the OpenClinica database was developed.

•The Reporting Tool was designed to present granular details of the study data by organizing CRF item data into separate columns.

•Over 90 Excel macros were required to complete the desired functionality.

Page 8: Akaza conf 3.22

REPORTING REPORTING CAPABILITYCAPABILITY

• The user may select of any group of 30 CRF item names producing a physical report with up to 600 columns.

• The application formats the returned records• Ability to create personal and shared reports DB• Reports data in the order that was selected• Filter on attributes related to Study, Subject ID, CRF,

Event Definitions• Use any of the following operators: GT, LT, NE, LIKE,

Between, IN, OR, AND, ALL

Page 9: Akaza conf 3.22

WHO COULD BENEFIT FROM THIS?WHO COULD BENEFIT FROM THIS?

Data Managers• Quality Control• Metrics

Study Managers• Progress Reports• Status• Visit Schedules

Researchers• Ad hoc Queries• Data Mining

Page 10: Akaza conf 3.22

Benefits Documented to dateBenefits Documented to date

• Reduces Report Generation Time• Efficient Way to Verify Data Entry • Improves Operations with Shared Reports• Ability to Perform Granular Searches on Data

Page 11: Akaza conf 3.22

Thank You Thank You

We appreciate you taking the time to join us at this meeting, and look forward to ideas for future development.

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