Online Resources, Databases and Clinical Data Management
Dr Miles Benton
Genomics Research Centre, School of Biomedical Sciences, Institute of Health and Biomedical Innovation, Queensland University of Technology, Brisbane, QLD, Australia
I'm a bioinformatician
My passions
I'm lucky enough to have freedom to work with a wide-range of people/institutes.
"The best thing about being a
statisticianbioinformatician is that you get to play in everybody's backyard."
John Wilder Tukey (ammended by me)
- data
- repoducible research
- collaborative research
- visualisation
Using all of the above to bring research and data back to 'the people'
Data collection and storage is critical
Go in with a well-defined strategy
1. Identify issues and/or opportunities for collecting data
2. Select issue(s) and/or opportunity(ies) and set goals
3. Plan an approach and methods
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Consider:
- Who will the data be collected about?
- Who will the group of interest be compared to?
- What locations or geographical areas will the data be gathered from?
- What categories will be used to identify the group of interest and comparator group?
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How should data be collected?
- Qualitative Data
- Quantitative Data
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What sources of data should be used to collect information?
- Pre-existing or official data
- Survey data
- Interviews and focus groups
- Observed data
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How long will the data be collected (the scope of data collection)?
4. Collect data
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Determining who will collect the data (e.g., experts or trained employees).
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Identifying the logistics, resources, technology and people needed to develop and implement a data collection initiative.
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Designing a communication and consultation strategy that will explain the data collection initiative and encourage the highest possible participation rate.
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Protecting privacy and personal information by using carefully controlled procedures for collecting, storing and accessing data that comply with privacy, human rights and other legislation.
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Minimizing the impact and inconvenience for the people affected in the workplace or service environment, which includes choosing the best time to collect the data.
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Aiming for flexibility to allow for changes without great expense or inconvenience.
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Considering a test period or a pilot phase to allow you to improve and modify data collection methods, as may be needed.
5. Analyze and interpret data
If you were starting out now what would you use?
How many people thought Excel? ...
Why excel is the devil…
... when considering databases ...
Excel is a spreadsheet aplication constantly used for things it wasn't designed for.
- Time waster: You spend WAY too much time doing manual data entry and manipulation
- this is deadly and potentially costly
- Fragmentation: sharing of spreadsheets/workbooks - different versions!
- Lack of security
- No collaboration
- No options for reconciliation
- No website integration
- Can’t track relationships
- Backup solution?
At the end of the day Excel is a good tool for certain things (though I hope to convince you otherwise), but please don't use it as a database!
Well, are there alternatives?
YES!
REDCap Overview
REDCap is a secure web application for building and managing online surveys and databases. While REDCap can be used to collect virtually any type of data, it is specifically geared to support online or offline data capture for research studies and operations.
Advantages of REDCap:
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Secure and web-based. Input data from anywhere in the world with secure web authentication, data logging, and Secure Sockets Layer (SSL) encryption.
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Fast and flexible. Conception to production-level database in less than one day.
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Multisite access. Projects can be used by researchers from multiple sites and institutions.
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Fully customizable. You are in total control of shaping your database or survey.
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Advanced question features. Auto-validation, branching logic, and stop actions.
Advantages of REDCap:
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Mid-study modifications. You may modify the database or survey at any time during the study.
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Data import functions. Data may be imported from external data sources to begin a study or to provide mid-study data uploads.
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Data comparison functions. Double data entry / Blinded data entry.
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Export survey results to common data analysis packages. Export your data to Microsoft Excel, SAS, STATA, R, or SPSS for analysis.
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Save your survey or forms as PDFs. Generate a PDF version for printing in order to collect responses offline.
Some real-world examples:
Jeremy Krebs - online questionnaire
Max Berry - no more issues with paper in the lab
Kirsty Danielson (live demo)
'Playing' with data once it's there
Some real-time examples of front-end applications interfacing with well-managed databases
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MS-view (multiple sclerosis clinical data)
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WESTARC (making genome sequence data accessible and interpretable to clinicians)
Slight tangent…
but I heard a few people are interested in R
Packages make R/RStudio great!
How do I begin to learn any of this?!
Coursera (www.coursera.org)
An excellent online learning tool
Coursera (www.coursera.org)
Searched for clinical research: https://www.coursera.org/courses?languages=en&query=clinical+research
A few look very good:
- Design and Interpretation of Clinical Trials (https://www.coursera.org/learn/clinical-trials)
- Data Management for Clinical Research (https://www.coursera.org/learn/clinical-data-management)
Coursera (www.coursera.org)
Statistics and R: https://www.coursera.org/courses?languages=en&query=r
- Basic Statistics (https://www.coursera.org/learn/basic-statistics)
- Understanding Clinical Research: Behind the Statistics (https://www.coursera.org/learn/clinical-research)
- Master Statistics with R (https://www.coursera.org/specializations/statistics)
Shameless plug…
I run different workshops covering many of these topics and more