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National Surveys of Population Health: Big Data Analytics for Mobile Health Monitors
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 measuri...
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Formato: | Online Artículo Texto |
Lenguaje: | English |
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Mary Ann Liebert, Inc.
2015
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Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4722603/ https://www.ncbi.nlm.nih.gov/pubmed/26858915 http://dx.doi.org/10.1089/big.2015.0021 |
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author | Schatz, Bruce R. |
author_facet | Schatz, Bruce R. |
author_sort | Schatz, Bruce R. |
collection | PubMed |
description | 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. |
format | Online Article Text |
id | pubmed-4722603 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2015 |
publisher | Mary Ann Liebert, Inc. |
record_format | MEDLINE/PubMed |
spelling | pubmed-47226032016-02-08 National Surveys of Population Health: Big Data Analytics for Mobile Health Monitors Schatz, Bruce R. Big Data 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. Mary Ann Liebert, Inc. 2015-12-01 /pmc/articles/PMC4722603/ /pubmed/26858915 http://dx.doi.org/10.1089/big.2015.0021 Text en © Bruce R. Schatz 2016; Published by Mary Ann Liebert, Inc. This Open Access article is distributed under the terms of the Creative Commons License (http://creativecommons.org/licenses/by/4.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly credited. |
spellingShingle | Review Schatz, Bruce R. National Surveys of Population Health: Big Data Analytics for Mobile Health Monitors |
title | National Surveys of Population Health: Big Data Analytics for Mobile Health Monitors |
title_full | National Surveys of Population Health: Big Data Analytics for Mobile Health Monitors |
title_fullStr | National Surveys of Population Health: Big Data Analytics for Mobile Health Monitors |
title_full_unstemmed | National Surveys of Population Health: Big Data Analytics for Mobile Health Monitors |
title_short | National Surveys of Population Health: Big Data Analytics for Mobile Health Monitors |
title_sort | national surveys of population health: big data analytics for mobile health monitors |
topic | Review |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4722603/ https://www.ncbi.nlm.nih.gov/pubmed/26858915 http://dx.doi.org/10.1089/big.2015.0021 |
work_keys_str_mv | AT schatzbrucer nationalsurveysofpopulationhealthbigdataanalyticsformobilehealthmonitors |