This document summarizes a feasibility study to securely aggregate personal health data from various sources outside of clinical settings. The study aims to demonstrate how individuals can provide access to their health kiosk and wearable device data through an internet-based platform. It conceptualizes using the higi health data aggregation platform to retrieve data from kiosks, devices, and apps and store it in a study management database. The output shows the data was returned securely in JSON format and included measurements, activity histories, and device updates. Some limitations are the lack of detailed sample data and need for alternative approaches for bio-specimen collection.

1. A Novel Approach for Conveniently and
Securely Collecting Personal Health Data
Lew Berman, PhD, MS, ICF
Chuck Akin, BBA, ICF
Jeff Barkoff, MBA, higi
May 21, 2018
2018 International Field Directors and Technology
Conference
Denver, Colorado

2. Agenda
 Motivation, challenges, problem framing
 Alternative approach
 Feasibility study aims, conceptualization, & solution
 Output
 Limitations
2

3. Motivation – National Health Interview
Survey [BERMAN 2012]
Fix: environment & skill level
Vary: equipment
Fix: environment & equipment
Vary: skill level of data collector
Measures
• Anthropometry
• Blood pressure
• Blood (CVD)
Controlling For
• Environment
• Equipment
• Skill level
3
Household
Interview
Mobile Examination
Center
In-Home Exam

4. Challenges in 2012
 National sample in many PSUs
 Equipment logistics & calibration
 Census field staff training and collection
 Costly
 Shipping & handling of bio-specimens
 Declining response rates
4
Source: Selected (& declining) Survey Response Rates [CZAJKA 2016]

5. New Challenges
 Further decline in response rates
  privacy concerns   confidentiality   information control
  use of smartphones   “convenience requirements”
  distrust in government
 “Optional” challenges
 Device integration (e.g., Fitbit, Garmin)
 Longitudinal data collection
5
2014 Compared to 2004
• Commute less
• Sleep more
• More leisure time

6. Approaches to Overcome Challenges
 Incorporate mixed modes for field operations
 Approaches do not overcome all challenges
 Introduces data standardization & harmonization challenges
 EHR platforms and sites not consistent in data structure & coding
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Modes Examples
Web / Internet panels Knowledge Networks, and more recently AmeriSpeak, Mfour
Fixed (clinic) sites National Children’s Study (NCS), Oregon Health Study, Survey of the Health of Wisconsin (SHOW)
Mobile vans NCS, NHANES, Statistics Canada Health Measures Survey, SHOW
In-person exams Health and Retirement Study, NHANES, National Social Life Health and Aging Project
Auxiliary data EHRs, registry data
Wearable devices Build connections to each device

7. Problem
Identify alternative approach to overcome existing and new challenges for
(longitudinal) large-scale national data collection.
7

8. Alternative Approach: Health & Wellness
Kiosks & Related Platforms
higiHealthBot
• BP + risk screening
• Employer driven model
• >5K stations in US/Canada
• FDA approved BP/Pulse, weight, screenings
• Short questionnaires
• Robust WEB-BASED PLATFORM & API
• >11K KIOSKS IN US pharmacies and stores
• 78% of the U.S. population WITHIN 5 MILES of a kiosk
• Integrated with 80+ DEVICES
Pursuant Health / SoloHealth
• BP, weight, vision + risk screening
• Supermarkets, superstores
• ~4K kiosks in US
• 79% of the US population within
10 miles of a kiosk
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9. Specific Aims
 Test the feasibility of using an Internet-based platform to securely
aggregate health kiosk data and wearable device data outside of clinical,
home, and mobiles settings.
 Specific Aim 1: Demonstrate a secure mechanism for individuals to easily provide access to their health kiosk
data and wearable device data.
 Specific Aim 2: Evaluate the accessibility, quality, and structure of the data collected by the Internet-based
platform.
9

10. Conceptual View of Feasibility Study
Solution
10
Some photos by Unknown Author
which are licensed under CC BY
Study participants
provide measurements
at conveniently located
kiosk
Physical activity and
lifestyle data collected
thru devices
Prototype Study
Platform
Uses the access token
to access respondent
data on higi
aggregation platform
higi authorization server issues
ACCESS TOKENS to study
platform with the approval of the
respondent
Authorization Protocol Data Aggregation Platform
Respondents Create Account
with higi and AUTHORIZE and
RESCIND access to their data

11. Solution Architecture
higi Kiosks
Lifestyle / Fitness Devices &
Apps
Participant measurements
higi Proprietary Connection Device OAuth V2 API Device connections
higi API Request functions
AuthenticateStudy
Subscriptions
DataRequests
Study Management Platform User Interface to Study Mgmt (future)
DataManagement&Xfer,
Authorization
DynamoDB Data Storage and Database Services
Lambda Web Services Business Logic to manage higi
responses
API Gateway (RESTful Study Interface) Callback functions
11

12. Participant View on Data Aggregation
Platform
12
Participant Login Most Recent Kiosk Measurement Activity Charts
Activity History
Device & App Authorizations

13. Output
 Data format
 Returned in JavaScript object Notation (JSON) format
 Required parsing into tables for analysis
 “Study Participants”
 Successfully authorized access to kiosk, device and app data
 No reported problems
 Device data
 Device data can be retrieved at high level (e.g., step counts, duration, mileage)
 Devices sampling at different frequencies and sampled data not available
 Updates
– Fitness devices trigger at conclusion of the activity
– Step counting occurring between 22 and 24 times / day
– Kiosk data available immediately after measurements recorded
– App updates immediately triggered at check-in
13

14. Key Takeaways
 higi and kiosk / data access platform
 Potential to provide convenient access to a large proportion of the US population
 Extensible for new devices and apps
 System can be easily configured for secure access under the respondent control
 DAP can integrate data from many sources and provide data feeds
 Data aggregation / retrieval
 Seamless once configured thru the API
 Regular updates at pre-determined intervals
 Platform gamification techniques should be investigated to determine
usefulness in a study environment
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15. Limitations
 Kiosk
 Limited but important set of measurements
 Additional physical measures dependent upon pharmacy / store needs
 Questionnaire instrumentation limited to a handful of questions and pharmacy / store may not allow
 Data access platform
 No access to detailed sample data which may be needed for analyses
 Bio-specimen collection requires alternative approach such as LabCorp &
Quest Diagnostics
15

16. Future ecosystem – data brokering
Prototype Study
Platform Authorization Protocol
Data Aggregation
Platform
16

17. Lew Berman, PhD, MS
Email: lewis.berman@icf.com
Phone: 301-407-6833

18. References
[BERMAN 2012] Berman L. An Approach to Validating Household Physical Measure and Bio-Specimen Collection in
NHANES. Presented at the 46th Annual International Field Directors & Technology Conference. Orlando, FL, May 20-
23, 2012.
[CZAJKA 2016] Czajka JL and Beyler A. Declining response rates in federal surveys: Trends and Implications
(Background Paper)