mHealth: A paradigm shift in clinical research

Diego Menchaca, CEOteamscope.co

Source: Flickr/Robert Guerra

Early clinical research data management

Electronic Data Capture (EDC) Systems

Was replaced with

CRFweb

Then came the cloud

crfweb.com

Automatic data validation

Monitor progress per patient

Quicker access to data

Study compliance: EU, FDA, GCP, etc.

Benefits of EDC

Automatic data validation

Monitor progress per patient

Quicker access to data

Study compliance: EU, FDA, GCP, etc.

Benefits of EDC“Reduces study cost by 5x

“Cuts study time by 30%

Comparison of Electronic Data Capture with Paper Data Collection – Is There Really an Advantage? by Dr Thomas Bart

Although the benefits of EDC are evident, developing countries have been to slow adopt it

1. Not easy to use

Source : karuna-shechen.org

2. Infrastructure can be limited

Source: Dimagi

3. On-site training and support is needed

If only we could eradicate pen & paper clinical research in developing countries

teamscope.co

teamscope.co

1. Easy to use

2. Works offline

3. GCP compliant

Wajir, Kenya

Source: Capacities for Health

Source: Capacities for Health

Source: Capacities for Health

Bosaso, Somalia

Source: Capacities for Health

Source: Capacities for Health

Source: Capacities for Health

Concepts to understand the EDC transition in developing countries3

Empowerment starts with usability1

Do them a favor, don’t train them…

Apps have a shorter learning curve than software

Rural healthcare is not static2

last but not least

3

Scalability

Examples of mobile scalability in clinical research

mPower Parkinson Study

Participants in one week8.000

The mPower study, Parkinsondisease mobile data collected usingResearchKitBrian M. Bot1, Christine Suver1, Elias Chaibub Neto1, Michael Kellen1, Arno Klein1,Christopher Bare1, Megan Doerr1, Abhishek Pratap1, John Wilbanks1, E. Ray Dorsey2,Stephen H. Friend1 & Andrew D. Trister1

Current measures of health and disease are often insensitive, episodic, and subjective. Further, thesemeasures generally are not designed to provide meaningful feedback to individuals. The impact of high-resolution activity data collected from mobile phones is only beginning to be explored. Here we presentdata from mPower, a clinical observational study about Parkinson disease conducted purely through aniPhone app interface. The study interrogated aspects of this movement disorder through surveys andfrequent sensor-based recordings from participants with and without Parkinson disease. Benefitting fromlarge enrollment and repeated measurements on many individuals, these data may help establish baselinevariability of real-world activity measurement collected via mobile phones, and ultimately may lead toquantification of the ebbs-and-flows of Parkinson symptoms. App source code for these data collectionmodules are available through an open source license for use in studies of other conditions. We hope thatreleasing data contributed by engaged research participants will seed a new community of analysts workingcollaboratively on understanding mobile health data to advance human health.

Design Type(s) observation design • time series design • repeated measure design

Measurement Type(s) disease severity measurement

Technology Type(s) Patient Self-Report

Factor Type(s)

Sample Characteristic(s) Homo sapiens

1Sage Bionetworks, Seattle, Washington 98109, USA. 2Center for Human Experimental Therapeutics, Universityof Rochester Medical Center, Rochester, New York 14642, USA. Correspondence and requests for materialsshould be addressed to A.D.T. (email: trister@sagebase.org).

OPENSUBJECT CATEGORIES

» Research data

» Neurology

» Parkinson’s disease

» Medical research

Received: 07 December 2015

Accepted: 02 February 2016

Published: 3 March 2016

www.nature.com/scientificdata

SCIENTIFIC DATA | 3:160011 | DOI: 10.1038/sdata.2016.11 1

The mPower study, Parkinsondisease mobile data collected usingResearchKitBrian M. Bot1, Christine Suver1, Elias Chaibub Neto1, Michael Kellen1, Arno Klein1,Christopher Bare1, Megan Doerr1, Abhishek Pratap1, John Wilbanks1, E. Ray Dorsey2,Stephen H. Friend1 & Andrew D. Trister1

Current measures of health and disease are often insensitive, episodic, and subjective. Further, thesemeasures generally are not designed to provide meaningful feedback to individuals. The impact of high-resolution activity data collected from mobile phones is only beginning to be explored. Here we presentdata from mPower, a clinical observational study about Parkinson disease conducted purely through aniPhone app interface. The study interrogated aspects of this movement disorder through surveys andfrequent sensor-based recordings from participants with and without Parkinson disease. Benefitting fromlarge enrollment and repeated measurements on many individuals, these data may help establish baselinevariability of real-world activity measurement collected via mobile phones, and ultimately may lead toquantification of the ebbs-and-flows of Parkinson symptoms. App source code for these data collectionmodules are available through an open source license for use in studies of other conditions. We hope thatreleasing data contributed by engaged research participants will seed a new community of analysts workingcollaboratively on understanding mobile health data to advance human health.

Design Type(s) observation design • time series design • repeated measure design

Measurement Type(s) disease severity measurement

Technology Type(s) Patient Self-Report

Factor Type(s)

Sample Characteristic(s) Homo sapiens

1Sage Bionetworks, Seattle, Washington 98109, USA. 2Center for Human Experimental Therapeutics, Universityof Rochester Medical Center, Rochester, New York 14642, USA. Correspondence and requests for materialsshould be addressed to A.D.T. (email: trister@sagebase.org).

OPENSUBJECT CATEGORIES

» Research data

» Neurology

» Parkinson’s disease

» Medical research

Received: 07 December 2015

Accepted: 02 February 2016

Published: 3 March 2016

www.nature.com/scientificdata

SCIENTIFIC DATA | 3:160011 | DOI: 10.1038/sdata.2016.11 1

This is just the tip of the iceberg

$30 USD

Cost of devices is drastically decreasing

+220mAfrica

+130mIndia

Estimated smartphone users by 2020

We think that its restrictions and limitations that we face in low-resource settings what fuels our creativity.

Muchas gracias :-)

dmenchaca15

Diego Menchaca, CEOteamscope.co