Making sense of mobile health data: An open architecture to improve individual- and population-level health

Connie Chen, David Haddad, Joshua Selsky, Julia E. Hoffman, Richard L Kravitz, Deborah E. Estrin, Ida Sim

Research output: Contribution to journalArticle

53 Citations (Scopus)

Abstract

Mobile phones and devices, with their constant presence, data connectivity, and multiple intrinsic sensors, can support around-the-clock chronic disease prevention and management that is integrated with daily life. These mobile health (mHealth) devices can produce tremendous amounts of location-rich, real-time, high-frequency data. Unfortunately, these data are often full of bias, noise, variability, and gaps. Robust tools and techniques have not yet been developed to make mHealth data more meaningful to patients and clinicians. To be most useful, health data should be sharable across multiple mHealth applications and connected to electronic health records. The lack of data sharing and dearth of tools and techniques for making sense of health data are critical bottlenecks limiting the impact of mHealth to improve health outcomes. We describe Open mHealth, a nonprofit organization that is building an open software architecture to address these data sharing and "sense-making" bottlenecks. Our architecture consists of open source software modules with well-defined interfaces using a minimal set of common metadata. An initial set of modules, called InfoVis, has been developed for data analysis and visualization. A second set of modules, our Personal Evidence Architecture, will support scientific inferences from mHealth data. These Personal Evidence Architecture modules will include standardized, validated clinical measures to support novel evaluation methods, such as n-of-1 studies. All of Open mHealth's modules are designed to be reusable across multiple applications, disease conditions, and user populations to maximize impact and flexibility. We are also building an open community of developers and health innovators, modeled after the open approach taken in the initial growth of the Internet, to foster meaningful cross-disciplinary collaboration around new tools and techniques. An open mHealth community and architecture will catalyze increased mHealth efficiency, effectiveness, and innovation.

Original languageEnglish (US)
JournalJournal of Medical Internet Research
Volume14
Issue number4
DOIs
StatePublished - Jul 2012

Fingerprint

Telemedicine
Health Status
Population
Information Dissemination
Health
Software
Nonprofit Organizations
Mobile Applications
Equipment and Supplies
Cell Phones
Electronic Health Records
Disease Management
Internet
Noise
Chronic Disease

Keywords

  • Data analysis
  • Data visualization
  • Evaluation methodology
  • Mobile health
  • Open access to information
  • Open architecture
  • Open source
  • Software engineering
  • Software tools

ASJC Scopus subject areas

  • Health Informatics

Cite this

Making sense of mobile health data : An open architecture to improve individual- and population-level health. / Chen, Connie; Haddad, David; Selsky, Joshua; Hoffman, Julia E.; Kravitz, Richard L; Estrin, Deborah E.; Sim, Ida.

In: Journal of Medical Internet Research, Vol. 14, No. 4, 07.2012.

Research output: Contribution to journalArticle

Chen, Connie ; Haddad, David ; Selsky, Joshua ; Hoffman, Julia E. ; Kravitz, Richard L ; Estrin, Deborah E. ; Sim, Ida. / Making sense of mobile health data : An open architecture to improve individual- and population-level health. In: Journal of Medical Internet Research. 2012 ; Vol. 14, No. 4.
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