Data-driven Health Behavior Change and mHealth
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Transcript of Data-driven Health Behavior Change and mHealth
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Data-driven Health Behavior Change and mHealth
M. Courtney Hughes, PhD
mHealth ConferenceChicago, IL
March 30-31, 2011
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Introduction
• Approach Health helps companies:– Drive behavior change– Incorporate evidence-based research and industry best practices– Lower medical costs & increase productivity– Demonstrate ROI
• Background:– Experience with health IT companies, health plans, PBMs, program
vendors– Published studies in health behavior change, workplace health – PhD, University of Washington; MS, University of Michigan; BBA,
University of Notre Dame
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The Time Has Never Been Better…
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Challenges Opportunities
Rising healthcare costs 75% due to unhealthy, modifiable behaviors
Engaging membersUbiquitous mobile devices
Strong interest in improving health behaviors
Cost-effective customization Readily available data
Effective communication algorithms
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Capturing PopulationMore patient data is available than ever before.
EMR, PHR
Pharma Claims
Survey(HRA, QoL)
Medical Claims
mDevices(Events, ODLs)
Lab Values
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Health Behavior: Medication Adherence
• 30-50% patients are nonadherent with
medication
• Medication nonadherence costs our nation over
$100B / year
• Mobile devices can help improve adherence
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Identification & Targeting
• Current poor adherers
- missed refills, no med response, missed appts
• Individuals at risk for future poor adherence- psych problems, side effects, asymptomatic disease, cost,
treatment complexity
• Prioritize participants within target groups
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Preventable disease, death Chronic Costly Dependent
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Tailored Message for High-Impact
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Drug-specific
• Emphasizes value of drug/regimen
• Explains effect of adherence
Elicit patient feelings
• Costs often a concern (direct & indirect)
• Psych meaning of med (stigma, addiction)
Customize regimen
• According to patient’s wishes
• Suggest therapeutic interchange
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Optimizing Delivery
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Optimal combination
modes
Patient Spouse
Care Manager
Parent
Target Optimal Recipient
Timing should be immediate
Start Med times
Days
1 2 43
1 2
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Example 1: Diabetes Patients
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• Multiple meds: 1 message or several?
• Time of day: weekday vs. weekends
Source: CareSpeak Communications
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Example 2: MI Patient Text, Day 1:“Heart attack patients may benefit from taking a beta blocker like Atenolol. These drugs assist in the healing process and help prevent another heart attack.”
Optional Reminder Text, Daily:“Please remember to take your Atenolol today.”
Call, Day 6: How do you feel about taking Atenolol?
Text, Day 28:“Congratulations on refilling your Atenolol. You are helping yourself stay healthy and prevent another heart attack.”
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Where to Focus for Greatest Impact
Behaviors
• Smoking
• Medication Adherence
• Prev Care
• Physical Activity
• Diet
Conditions
• Heart Disease
• Cancer
• Diabetes
• Hypertension
• High Cholesterol
• Obesity
• Depression
Characteristics
• Age
• Gender
• Education
• Income
• Prior behavior
• Readiness for change
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*Cost information from Medical Expenditure Panel Survey, 2008
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Behavior Change Cost Impact
BehaviorPrevalence
Rate
Annual Cost / Afflicted
IndividualCost
Reference
Population Medical
Costs
Medication Nonadherence
30.0% $1500 Med Care, 2005Allergy, 2007
$4.5M
Obesity 38.9 1700 JOEM, 2010 6.6M
Smoking 19.6* 2432 CDC, 2007 4.8M
*Hughes et al., Am J Health Prom, 2010**Conservative estimate based on articles in Health Psych, 2011, Am J Prev Med 2009, J Am Coll Health 2008
Population: 10,000
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Smoking prevalence drops 5% to 18.6** --> Population savings = $243,200
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What’s Next?
• Determining optimal level of interactivity
• Patient or provider initiation?
• Activity feedback
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Source: Halo Monitoring, DePaul University