National surveys of population health: Big data analytics for mobile health monitors

Bruce R. Schatz

Research output: Contribution to journalReview articlepeer-review


At the core of the healthcare crisis is fundamental lack of actionable data. Such data could stratify individuals within populations to predict which persons have which outcomes. If baselines existed for all variations of all conditions, then managing health could be improved by matching the measuring of individuals to their cohort in the population. The scale required for complete baselines involves effective National Surveys of Population Health (NSPH). Traditionally, these have been focused upon acute medicine, measuring people to contain the spread of epidemics. In recent decades, the focus has moved to chronic conditions as well, which require smaller measures over longer times. NSPH have long utilized quality of life questionnaires. Mobile Health Monitors, where computing technologies eliminate manual administration, provide richer data sets for health measurement. Older technologies of telephone interviews will be replaced by newer technologies of smartphone sensors to provide deeper individual measures at more frequent timings across larger-sized populations. Such continuous data can provide personal health records, supporting treatment guidelines specialized for population cohorts. Evidence-based medicine will become feasible by leveraging hundreds of millions of persons carrying mobile devices interacting with Internet-scale services for Big Data Analytics.

Original languageEnglish (US)
Pages (from-to)219-229
Number of pages11
JournalBig Data
Issue number4
StatePublished - Dec 1 2015


  • big data analytics
  • big data architecture
  • crowdsourcing
  • population health
  • predictive analytics

ASJC Scopus subject areas

  • Information Systems
  • Computer Science Applications
  • Information Systems and Management


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