WebEnabled Research Platform: The SIMS Study

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Web-Enabled Research PlatformThe SIMS Study

• Carolyn Bradner Jasik, MDMichele Mietus-Snyder,
  MDMichael Jarrett
• Department of Pediatrics
• University of California San Francisco

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Source Ogden CL (2006).
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The SIMS Study

• RCT of mindfulness-based program for obese
  children ages 9-12
• Goal recruitment 160
• Intervention 6 weekly sessions reviewing
  mindfulness techniques vs. standard of care
• Sites Childrens Hospital Oakland and San
  Francisco General Hospital
• Status completed pilot phase and 1st
  intervention group

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Our Research Group

• 1 junior faculty mentor (PI), 1 RA, 2
  collaborators (clinical fellows), and our
  contractor.
• Study funded by an American Heart Association
  grant.

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Why we picked QuesGen

• Multiple sites made web-based attractive
• Data available real-time
• The contractor did most of the work
• Required less staff on study days to administer
  survey, etc.
• Less staff needs for data entry/cleaning
• Short time-line for collection to analysis
• Its very cool!

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The SIMS Study Data Management

• Data Collection
• Intake and Follow-up visits (2, 6, 12 mo)
• At each visit
• Parent questionnaire
• Child questionnaire
• Labs
• Nutrition/Physical activity assessment (on-line)
• Provider assessment (history and physical exam)
• Administrative Data
• Demographics/contact information
• Appointment tracking, etc.

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The Reality
Sibling Data Obesity history, etc.
Employment (mult members per fam) Family member
demographic information
Visit (base, 2, 6, 12mo) Provider
Assessment Nursing Assessment Child
questionnaires Parent questionnaires Labs Extra
pilot measures (not used ultimately)
Survey (base only) Administrative
Data Demographics Medical History HPI, social,
family, etc. Parent Intake History
MacArthur SES (parent and child) Answers to
ladder questionnaire
Block (base, 2, 6, 12mo) Nutrition
Assessment Physical Activity Assessment

• Relational approach made sense, but data extract
  is LARGE and hard to manage!

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The Ideal
Provider Visit (base, 2, 6, 12) History Physical
Exam Plan
Sibling Data Obesity history, etc.
Employment (mult members per fam) Family member
demographic information
Nursing Visit (base, 2, 6, 12) Height, weight,
vitals BMI calculator
Survey (base) HPI PMH SH FH
MacArthur SES (parent and child) Answers to
ladder questionnaire
FitnessGram (base, 2, 6, 12)
Child Psych ?s (base, 2, 6, 12) RCMAS CEBQ Perceiv
ed Stress PQL
Disordered eating screen (base, 2, 6, 12)
Sub-study urine creatinine (base, 6)
Parent Psych ?s (base, 2, 6, 12) CEBQ Perceived
Stress PQL
Pilot Data (base)
Block (base, 2, 6, 12mo) Nutrition
Assessment Physical Activity Assessment
Labs (base, 2, 6, 12)
Admin (base) Demographics Recruitment Phone
communication
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What We Did Right

• Did not use EXCEL/ACCESS
• No paper forms
• Web-based vs. desktop/network
• Resisted the urge to get fancy
• Anticipated analysis needs while developing
  database
• Partnered with other researchers ()

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Our Pitfalls

• Allow more time for development
• Allocate more funds
• Be more prepared for contractor meetings
• Take full advantage of the technology
• Trust the technology
• Trust our participants less (more data input
  checks)
• Anticipate report/extract needs earlier
• Collect less data
• First extract 6 months after data collection
  started
• Mentor actually used it for the first time this
  month

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The Cost (financial and personal)

• 10,000 for contractor fees
• Real cost likely much higher
• I spent 100 hours on development
• I needed to be available via page during all data
  collection days to triage issues/questions

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Words of Wisdom

• For your first time, try and work within a larger
  team to learn from experience
• Over-estimate how much time it will take and the
  cost
• Use, dont abuse, your contractor
• Identify a primary database guru in the team
• Understand the technology before you start to
  create your database and data collection
• Encourage input from your data programmer, RAs,
  and study coordinator
• Always have back-ups and paper just in case

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Demonstration
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Future Directions

• Make the technology part of the study itself!

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Future Directions

• Adapt tool for research and clinical use
• Integrate clinical assessment and research data
  collection
• Pilot study in UCSF obesity clinic
• Pie in the skycreate shared research database
  for regional obesity clinics

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I have 30 min to spend
AMA
Jane Doe, MD FAAP Obesity Specialist
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If you build it, he will come.
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Acknowledgments

• Michele Mietus-Snyder, MD
• Robert H. Lustig, MD
• Zoe Foster
• Andrea Garber, PhD
• Kris Madsen, MD
• Charles Irwin, MD
• Mary-Ann Shafer, MD
• Michael Kohn, MD

• Michael JarrettFounder and CEO