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Social Media, Internet of Things, and the Future of Public Health

Social Media, Internet of Things, and the Future of Public Health

Public health is "the science and art of preventing disease, prolonging life and promoting health through the organized efforts and informed choices of society, organizations, public and private, communities and individuals." It is concerned with threats to health based on population health analysis. This definition highlights the role played by members of the community in improving health and in defining what is socially and publicly acceptable.

There are three main features of public health that define the field and also provide a contrast to the related field of medicine. Public health and medicine often have the similar goals of reducing the impact of disease and improving health and quality of life, but there are some notable differences between the two in the methods of reaching these goals. The primary features of public health are a (1) a view that all people should have healthcare access, regardless of social position, (2) a focus on the health of populations rather than individuals, and (3) a focus on prevention.

The use of social media in public health is taking shape as Twitter and other forms of social media are leveraged to identify potential outbreaks. Public health data is rapidly increasing from all sources. Sensors, formerly found only in hospital ICUs, are now portable and be used at home, and even sometimes while walking. The potential for persistent public health monitoring may be realized through introduction of machine-to-machine (M2M) communications, embedded computing/wireless, and related technologies.

This report evaluates the impact of social media, Big Data and analytics, and the so called “Internet of Things (IoT)” on public healthcare. The report evaluates specific companies, solutions, and applications. The report includes analysis of Big Data and its anticipated use in public health.

Report Benefits:

  • Identify the tenants of “Public Health 2.0”
  • Identify specific companies, solutions, and applications
  • Identify the role of Participatory Epidemiology in public health
  • Understand the confluence of Infodemiology and Infoveillance
  • Understand the role of data-mining, Big Data, and public health
  • Understand the role and importance of social media in public health
  • Understand the evolution and future direction of healthcare technology
Companies and Organizations in Report:
  • Abbott Laboratories
  • Adidas miCoach
  • Airstrip Technologies
  • Al Bawaba
  • AliveCor
  • Asthmapolis
  • AstraZeneca
  • BioCaster Global Health Monitor
  • Blue Shield of California
  • CardioNet
  • Centers for Disease Control and Prevention (CDC)
  • Centers for Medicare & Medicaid Services (CMS)
  • Central Intelligence Agency
  • DexCom
  • EpiSPIDER
  • Facebook Inc.
  • Factiva
  • Flu Detector
  • Food and Drug Administration (FDA)
  • FrontlineSMS
  • GeoChat
  • Geonames
  • Global Public Health Intelligence Network (GPHIN)
  • Google Dengue Trend
  • Google Flu Trends
  • Google Maps
  • HealthConnect
  • HealthCore
  • HealthMap
  • IMS Health
  • iRhythm
  • Kaiser Permanente
  • Life Watch
  • Medtronic Inc.
  • Microsoft Research
  • Mood of the Nation
  • NantHealth
  • National Cancer Institute (NCI)
  • National Institutes of Health (NIH)
  • Nike+
  • Philips Electronics iPill
  • Proteus Digital Health
  • Prudential Insurance Company of America
  • Sickweather
  • Skin Scan
  • Sotera Wireless
  • Twitter Inc.
  • U.S. Department of Health and Human Services
  • UK Health Protection Agency
  • United Nations
  • United States Public Health Service (PHS)
  • U.S. Department of Agriculture
  • U.S. Department of Homeland Security
  • U.S. Director for National Intelligence
  • Ushahidi
  • Vitality
  • Withings
  • World Health Organization (WHO)
  • Yahoo Maps
Target Audience:
  • Healthcare service providers
  • Healthcare insurance providers
  • Healthcare technology companies
  • Social media and networking companies
  • Policy makers, regulatory bodies, and government
  • Consultants and systems integrators for healthcare technology
  • M2M, Internet of Things (IoT), and general telecommunications companies
  • Public health institutions including CDC, NIH, FDA, CMS, NRHA, WHO, and others


General Methodology

Mind Commerce Publishing's research methodology encompasses input from a wide variety of sources.

We rely heavily upon our Subject Matter Experts (SME) in terms of their market knowledge, unique perspective, and vision. We utilize SME industry contacts as well as previous customers and participants in our market surveys and interactive interviews.

In addition, we rely upon our extensive internal database, which contains modeling, qualitative analysis, and quantitative data. We review secondary sources and compare to our primary sources to update previous findings (for prior version reports) and/or compile baseline information for technology and market modeling.

We share preliminary models with industry contacts (select previous clients, experts, and thought leaders) to verify the veracity of initial modeling. Prior to final report production (analysis, findings, and conclusions), we engage in an internal review with internal SMEs as well as cross-expertise, senior staff members to challenge results.

We believe that forecasts should be prepared as part of an integrated process which involves both quantitative as well as qualitative factors. We follow the following 3-step process for forecasting.

Forecasting Methodology

Step 1 - Forecasts Input: The inputs for the present and historical revenues are derived from industry players. Financial and other quantitative data for individual sub-market categories are derived from original research and tested with interviews with major industry constituents.

Step 2 - Forecasting of Future Years: Mind Commerce extends forecasts based on a variety of factors including demand drivers as well as supply side data. Key success factors and assumptions are considered.

Step 3 - Validation of Data: The final step is to validate projections, which is accomplished in consultation with both internal and external industry experts, including both topic and regional experts. Adjustments are made to the forecasts based on factors identified throughout this process.


1 EXECUTIVE SUMMARY
2 INTRODUCTION
3 HISTORY OF PUBLIC HEALTH
4 PUBLIC HEALTH PRACTICE
4.1 The U.S. Public Health System
4.2 Public Health at the Federal Level
4.2.1 Centers for Disease Control and Prevention (CDC)
4.2.2 National Institutes of Health (NIH)
4.2.3 Food and Drug Administration (FDA)
4.2.4 Centers for Medicare & Medicaid Services (CMS)
4.3 Public Health at the State and Local Levels
5 PUBLIC HEALTH DATA
5.1 Surveillance
5.2 Secondary Data
5.2.1 The Census
5.2.2 Vital Statistics
5.2.3 Survey Data
5.2.4 Registries
5.2.5 Reporting Systems
5.2.6 Medicare and Medicaid
5.3 Studies
5.3.1 Observational Studies
5.3.2 Experimental Studies
5.3.3 Screening
5.4 Epidemiology
5.4.1 Basic Epidemiological Measures
6 DATAMINING SOCIAL MEDIA, THE INTERNET OF THINGS AND BIG DATA
6.1 Data Mining
6.1.1 Preprocessing
6.1.2 Data Mining and Analysis
6.1.3 Text Mining
6.2 The Internet of Things
6.3 Big Data
7 SOCIAL MEDIA, DATAMINING, AND BIG DATA IN PUBLIC HEALTH
7.1 Public Health 2.0
7.2 Twitter
7.2.1 Influenza and Food Poisoning in New York
7.2.2 Post-Partum Depression
7.2.3 H1N1 in Germany
7.2.4 Seasonal Allergies
7.3 Mining the Web
7.3.1 Datamining News Stories to Predict Cholera Outbreaks
7.3.2 Data Mining Downloaded Recipes to Study Dietary Habits
7.3.3 Datamining Online Web Searchs to Predict Influenza Outbreaks
7.3.4 Online Physician Ratings
7.4 Participatory Epidemiology
7.4.1 FrontlineSMS
7.4.2 Ushahidi
7.4.3 GeoChat
7.4.4 Asthmapolis
7.4.5 The GPHIN Project
7.4.6 The HealthMap Project
7.4.7 Outbreaks Near Me
7.4.8 Biocaster
7.4.9 Sickweather
7.4.10 The EpiSPIDER Project
7.5 Reality Mining
7.6 Infodemiology and Infosurveillance
7.6.1 Google Flu Trends
7.6.2 Google Dengue Trend
7.6.3 Flu Detector
7.6.4 Mood of the Nation
7.7 Big Data and Public Health
7.7.1 Kaiser Permanente HealthConnect
7.7.2 Blue Shield of California and NantHealth
7.7.3 AstraZeneca and HealthCore
8 THE INTERNET OF THINGS AND THE MOVE TO INDIVIDUALS IN PUBLIC HEALTH
8.1 Population vs. Individual Thinking
8.2 Internet of Things
8.2.1 Diabetes
8.2.2 ECG and Heart Monitoring
8.2.3 Vital Signs
8.2.4 Asthma
8.2.5 Medical Compliance
8.2.6 Smartphone Lab
9 CONCLUSIONS AND RECOMMENDATIONS

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