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Mobile Health Applications for Low Socio-Economic Communities July 2011
Frame Template  Project Overview Applications for Good (A4G) asked Detecon to assess how mobile applications can be leveraged to alleviate obesity-related health issues in underserved communities.  Overview Objective Evaluate how mobile applications can be leveraged to positively impact obesity-related health issues most acutely felt by low-income and minority communities.   Approach Market Overview & Preliminary Gap Analysis ,[object Object]
How can mobile apps be leveraged to combat obesity-related health issues?
What apps are currently available to address prevention and remediation of obesity-related health problems?  How comprehensive are they?
How well do the available offerings meet the unique needs of A4G’s target population?  Where are the gaps?  Potential Next Steps for A4G ,[object Object]
How can A4G play a role in furthering the study of its constituents’ needs and the efficacy of targeted mobile app interventions?
What can A4G do to facilitate successful launch and post-launch consumer uptake of health-focused apps, particularly with regard to marketing, partnerships and monetization?Duration 2 weeks (July 2011) Background ,[object Object]
Detecon is a global consulting company which unites classic management consulting with a high level of information and telecommunication technology expertise.
Serving telecommunications and industry clients around the world, the San Francisco-based Detecon, Inc. team includes experts in the field of telecommunications strategy & innovation and mobile internet products &services.,[object Object]
New sensor technology and algorithms may facilitate advanced and predictive intervention models to help users stay on track and reap long-term health benefits.A4G’s target population faces a unique set of multi-faceted challenges, including lower rates of literacy, numeracy and access to resources.  While existing applications can address some of their needs, there is a dearth of applications targeted to the unique circumstances of low SES communities. ,[object Object]
Superior design and visualization techniques will also expand the appeal and potential benefits of mobile health apps to low literacy and numeracy populations.There is also an opportunity for A4G to broker collaborative efforts among researchers, nonprofits and corporations to develop, promote and distribute applications designed to impact health outcomes among low SES communities.
Contents 1 Obesity and Nutrition in America 2 Low SES Communities and Mobile Technology 3 Mobile Applications as a Health Enabler 4 Mobile Health Apps Overview 5 Preliminary Gap Analysis 6 Conclusions & Next Steps 7 Appendix
Frame Template  1. Obesity and Nutrition in America Obesity has rapidly developed into a major health issue in the United States, affecting virtually all parts of the country and nearly a third of the adult population. Obesity Trend Amongst US Adults (1990 – 2009) ,[object Object]
In 1990, among states participating in the Behavioral Risk Factor Surveillance System, ten states had a prevalence of obesity less than 10% and no states had prevalence equal to or greater than 15%.
In 2009, only one state (Colorado) and the District of Columbia had a prevalence of obesity less than 20%. Thirty-three states had a prevalence equal to or greater than 25%; nine of these states had a prevalence of obesity equal to or greater than 30%.Source: Behavioral Risk Factor Surveillance System, CDC
Frame Template  1. Obesity and Nutrition in America The target audience for A4G anti-obesity initiatives are Americans of low SES.  Higher obesity rates among this population are due to a variety of complex factors. US Obesity Rate by Income US Obesity Rate by Education US Poverty Rate by Ethnicity 33.8% 32.8% 25.8% 25.3% 31.8% 30.4% 29.6% 29.7% 29.5% 24.6% 21.5% 9.4% >$50k $35k-$50k $25k-$35k $15k-$25k <$15k Some college High school graduate only Did not graduate high school College grad African American White Hispanic Low-income individuals are less likely to have access to affordable, nutritious food. Lower levels of education are associated with both lower SES and poorer understanding of health and nutrition. Poverty is significantly more prevalent among African American and Hispanic communities.  US Adult Obesity Rate by Ethnicity US Childhood Obesity Rate by Ethnicity African 
American African 
American 35.7% 23.9% Hispanic 28.7% Hispanic 23.4% White 23.7% White 13.0% Sources: US Census Bureau 2010; CDC 2011; JAMA 2010; The Trust for America's Health and the Robert Wood Johnson Foundation, 2011
Frame Template  1. Obesity and Nutrition in America The recession has exacerbated the hardships faced by many lower SES communities with nearly one in seven Americans now relying on food stamps for their meals. About S.N.A.P.  S.N.A.P. Redemptions by Firm Type  ,[object Object]
Administered by the U.S. Department of Agriculture
 As of June 2009, the average monthly benefit was $133.12 per person
As of May 2011, 44 million Americans get a portion of their meals using food stamps
To be eligible, recipients have to have near-poverty level incomes8.4% Supermarket 3.9% 4.2% Superstore 48.9% Large/Medium Grocery Store Convenience Store 34.6% Other S.N.A.P.  and Quality of Diet “Food Stamp participants were less likely to consume fruits or vegetables than nonparticipants.”  “Over half of all foods consumed by Food Stamp participants came from foods that should be consumed only occasionally.”  “Food Stamp participants were less likely to have adequate intake of vitamins and minerals than higher income individuals.” ,[object Object]
Food stamp usage is typically at supermarkets, superstores and convenience stores which partially impacts dietary quality.Sources: US Department of Agriculture, 2011; Diet Quality of Americans by Food Stamp Participants, July 2008; S.N.A.P. Benefit Redemption Division Annual Report 2010
Frame Template  1. Obesity and Nutrition in America In response to the growing obesity problem, several initiatives have been launched to promote healthy lifestyles, especially among communities of low SES. “Let’s Move” Campaign Healthy Incentives Pilot (HIP) Program ,[object Object]
Hampden County is a mix of twenty-seven urban, suburban and rural cities and towns and approximately 50,000 SNAP households
Objective is to rigorously evaluate the impact of financial incentives provided at point-of-sale for the purchase of fruits, vegetables and other healthy foods on the diet of SNAP participants
Funded by a $20 million grant in the US Farm Bill of 2008
Campaign to end childhood obesity in the United States
Launched by First Lady, Michelle Obama on February 9, 2010
Key components include:
Eating healthier
Being more active
Labeling foods better,[object Object]
In 2008, all obesity-related medical expenses were estimated at $140 billion.Indiana 15.7% Delaware 13.8% Arizona 13.5% 12.9% Louisiana 12.9% Maryland New York 8.5% Wyoming 8.5% Alaska 8.2% All figures in million dollars (2003 dollars) Massachusetts 7.8% 7.7% Rhode Island Sources: RTI, CDC
Contents 1 Obesity and Nutrition in America 2 Low SES Communities and Mobile Technology 3 Mobile Applications as a Health Enabler 4 Mobile Health Apps Overview 5 Preliminary Gap Analysis 6 Conclusions & Next Steps 7 Appendix
Frame Template  2. Low SES Communities and Mobile Technology Ubiquitous wireless connectivity and growing smartphone penetration makes mobile a key potential tool in addressing the needs of low SES communities. US Smartphone Penetration US Wireless Penetration US wireless subscribers in millions (% of population) Smartphones Other Phones 63% 67% 68% 303(96%) 208(69%) +4% 110(38%) 37% 33% 32% 34(13%) 2011* 2010* 2009 2010 2005 2000 1995 ,[object Object]
Smartphone penetration is growing rapidly and this year is estimated to grow by 4 percentage points.Sources: CTIA, eMarketer 2010 * estimates
Frame Template  2. Low SES Communities and Mobile Technology Smartphone ownership in the United States is rising across all communities, with ownership among minorities outstripping that of their white peers. Smartphone Penetration by Ethnicity Hispanic African American White Asian/Pacific Islander 45% 45% 45% 40% 42% 37% 34% 37% 33% 34% 32% 30% 31% 27% 26% 24% 25% 21% 20% 18% Q1 2010 Q4 2009 Q2 2010 Q4 2010 Q3 2010 ,[object Object],Source: Nielsen 2011
Frame Template  2. Low SES Communities and Mobile Technology African Americans and Hispanics use their mobile devices for non-voice functions to a greater extent than white mobile phone owners, indicating a level of comfort with the technology. Mobile Internet Usage by Ethnicity ,[object Object]
The data demonstrated that minorities are comfortable using the mobile internet, making it a legitimate medium for health interventions.Source: Pew Research Center Mobile Access 2010
Frame Template  2. Low SES Communities and Mobile Technology Mobile internet usage among low income communities is growing rapidly, underscoring its potential as a medium for heath interventions. Wireless Internet Usage by Income Levels Smartphone Penetration by Income Levels Do not own phone Own featurephone Own smartphone May-10 Apr-09 80% 3% 72% 12% 13% 23% 67% 63% +31% 38% 55% 53% 50% 48% 46% 55% 35% 59% 39% 38% 23% $30k-$50k $50k-$75k <$30k >$75k $30k-$50k $50k-$75k >$75k <$30k ,[object Object],Source: Pew Research Center, July 2011; Pew Research Center Mobile Access 2010
Frame Template  2. Low SES Communities and Mobile Technology Minorities and low-income mobile phone owners are more likely to rely solely on cell phones for internet access, compared to their white counterparts. Wireless Internet Usage by Device ,[object Object]
The probability of being a cell-only wireless internet user is higher among low SES communities.Source: Pew Research Center

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Mobile health apps for low income communities

  • 1. Mobile Health Applications for Low Socio-Economic Communities July 2011
  • 2.
  • 3. How can mobile apps be leveraged to combat obesity-related health issues?
  • 4. What apps are currently available to address prevention and remediation of obesity-related health problems? How comprehensive are they?
  • 5.
  • 6. How can A4G play a role in furthering the study of its constituents’ needs and the efficacy of targeted mobile app interventions?
  • 7.
  • 8. Detecon is a global consulting company which unites classic management consulting with a high level of information and telecommunication technology expertise.
  • 9.
  • 10.
  • 11. Superior design and visualization techniques will also expand the appeal and potential benefits of mobile health apps to low literacy and numeracy populations.There is also an opportunity for A4G to broker collaborative efforts among researchers, nonprofits and corporations to develop, promote and distribute applications designed to impact health outcomes among low SES communities.
  • 12. Contents 1 Obesity and Nutrition in America 2 Low SES Communities and Mobile Technology 3 Mobile Applications as a Health Enabler 4 Mobile Health Apps Overview 5 Preliminary Gap Analysis 6 Conclusions & Next Steps 7 Appendix
  • 13.
  • 14. In 1990, among states participating in the Behavioral Risk Factor Surveillance System, ten states had a prevalence of obesity less than 10% and no states had prevalence equal to or greater than 15%.
  • 15. In 2009, only one state (Colorado) and the District of Columbia had a prevalence of obesity less than 20%. Thirty-three states had a prevalence equal to or greater than 25%; nine of these states had a prevalence of obesity equal to or greater than 30%.Source: Behavioral Risk Factor Surveillance System, CDC
  • 16. Frame Template 1. Obesity and Nutrition in America The target audience for A4G anti-obesity initiatives are Americans of low SES. Higher obesity rates among this population are due to a variety of complex factors. US Obesity Rate by Income US Obesity Rate by Education US Poverty Rate by Ethnicity 33.8% 32.8% 25.8% 25.3% 31.8% 30.4% 29.6% 29.7% 29.5% 24.6% 21.5% 9.4% >$50k $35k-$50k $25k-$35k $15k-$25k <$15k Some college High school graduate only Did not graduate high school College grad African American White Hispanic Low-income individuals are less likely to have access to affordable, nutritious food. Lower levels of education are associated with both lower SES and poorer understanding of health and nutrition. Poverty is significantly more prevalent among African American and Hispanic communities. US Adult Obesity Rate by Ethnicity US Childhood Obesity Rate by Ethnicity African American African American 35.7% 23.9% Hispanic 28.7% Hispanic 23.4% White 23.7% White 13.0% Sources: US Census Bureau 2010; CDC 2011; JAMA 2010; The Trust for America's Health and the Robert Wood Johnson Foundation, 2011
  • 17.
  • 18. Administered by the U.S. Department of Agriculture
  • 19.  As of June 2009, the average monthly benefit was $133.12 per person
  • 20. As of May 2011, 44 million Americans get a portion of their meals using food stamps
  • 21.
  • 22. Food stamp usage is typically at supermarkets, superstores and convenience stores which partially impacts dietary quality.Sources: US Department of Agriculture, 2011; Diet Quality of Americans by Food Stamp Participants, July 2008; S.N.A.P. Benefit Redemption Division Annual Report 2010
  • 23.
  • 24. Hampden County is a mix of twenty-seven urban, suburban and rural cities and towns and approximately 50,000 SNAP households
  • 25. Objective is to rigorously evaluate the impact of financial incentives provided at point-of-sale for the purchase of fruits, vegetables and other healthy foods on the diet of SNAP participants
  • 26. Funded by a $20 million grant in the US Farm Bill of 2008
  • 27. Campaign to end childhood obesity in the United States
  • 28. Launched by First Lady, Michelle Obama on February 9, 2010
  • 32.
  • 33. In 2008, all obesity-related medical expenses were estimated at $140 billion.Indiana 15.7% Delaware 13.8% Arizona 13.5% 12.9% Louisiana 12.9% Maryland New York 8.5% Wyoming 8.5% Alaska 8.2% All figures in million dollars (2003 dollars) Massachusetts 7.8% 7.7% Rhode Island Sources: RTI, CDC
  • 34. Contents 1 Obesity and Nutrition in America 2 Low SES Communities and Mobile Technology 3 Mobile Applications as a Health Enabler 4 Mobile Health Apps Overview 5 Preliminary Gap Analysis 6 Conclusions & Next Steps 7 Appendix
  • 35.
  • 36. Smartphone penetration is growing rapidly and this year is estimated to grow by 4 percentage points.Sources: CTIA, eMarketer 2010 * estimates
  • 37.
  • 38.
  • 39. The data demonstrated that minorities are comfortable using the mobile internet, making it a legitimate medium for health interventions.Source: Pew Research Center Mobile Access 2010
  • 40.
  • 41.
  • 42. The probability of being a cell-only wireless internet user is higher among low SES communities.Source: Pew Research Center
  • 43.
  • 44. Android is a logical platform choice for developing applications intended to address the needs of low SES communities.Source: Pew Research Center, July 2011
  • 45. Contents 1 Obesity and Nutrition in America 2 Low SES Communities and Mobile Technology 3 Mobile Applications as a Health Enabler 4 Mobile Health Apps Overview 5 Preliminary Gap Analysis 6 Conclusions & Next Steps 7 Appendix
  • 46.
  • 47.
  • 48. “Behavioral Intervention for Overweight Women”, University of California – San Diego: Researchers assessed depressive symptoms in 401 participants in a randomized control trial of a 12-month primary care, phone and internet-based behavioral intervention for overweight women. Results showed that a 1-year primary care-based phone and internet diet and exercise intervention can improve depressive symptoms.Source: “Medication Adherence and m-Health“, George Washington University;“Behavioral Intervention for Overweight Women”, University of California – San Diego
  • 49.
  • 50. Are there free clinics or Medicaid providers nearby?
  • 51.
  • 52. Exercise: How to incorporate more exercise into your daily routine
  • 53.
  • 54.
  • 55.
  • 56.
  • 57.
  • 58. These apps tend to command a higher selling price than the average app.
  • 59. Medical apps tend to be of higher quality than health & fitness apps, as rated by users.Sources: Detecon Analysis, July 2011; www.appbrain.com
  • 60.
  • 61. Relatively few enabling apps available (probably due to lack of appropriate or sufficient data) and relatively few intervening apps available (probably due to complexities of app design involving intervention time, manner etc.)Source: Detecon Analysis, July 2011
  • 62.
  • 63. The most popular obesity-relevant Android apps are informational in nature. However, they are simple and lack the more sophisticated personalization, social and gaming features necessary to motivate people to adopt long-term change.Source: Detecon Analysis, July 2011
  • 64.
  • 65. Based on this criteria, Detecon evaluated the availability and functionality of apps in the Android Market that target:
  • 76. The chart below reflects the current distribution of Android Market apps relevant for obesity-related use cases.
  • 77.
  • 78. Contents 1 Obesity and Nutrition in America 2 Low SES Communities and Mobile Technology 3 Mobile Applications as a Health Enabler 4 Mobile Health Apps Overview 5 Preliminary Gap Analysis 6 Conclusions & Next Steps 7 Appendix
  • 79.
  • 80. Are there other or new strategies we might look to in the future?
  • 81. How can A4G overcome the challenges of app discovery and increase awareness of relevant app resources among its target audience?
  • 82. What app functionality is most needed, or missing, among currently available apps?
  • 87. What types of app features will help improve health outcomes?
  • 88. What types of app features are currently missing among available apps?
  • 89. What considerations, specific to A4G‘s target population, must developers bear in mind?Detecon interviewed healthcare and information design researchers, as well as app developers, to explore the questions above and gain insight into needs, trends and potential solutions.
  • 90. Frame Template 5. Preliminary Gap Analysis Apps targeting low SES communities and obesity consequences are notably missing from the market. Apps that act as enablers or intervention tools are also needed. App Availability by Functionality Intervening Educating Monitoring Enabling Comments Obesity Causes App Availability by Focus Area Obesity Consequences Low SES Groups Comments Source: Detecon Analysis, July 2011 Very few apps; Low quality Many apps; High quality
  • 91.
  • 92. Self-monitoring skills are the most critical (weight, eating, exercise, mood)
  • 93. Skills to set up an environment that is conducive to maintaining healthy habits
  • 96. App usability must be designed to be inclusive of users with low literacy and numeracy.
  • 97. Interventions must balance everyday realities: can users really afford to research, find and follow healthy recipes (from both a time and money perspective)? If not, what are the options?
  • 98.
  • 99. How can we predict when a patient is going to relapse?
  • 100. How do you know when to prompt a patient? When is the optimal time for a reminder (for example, to exercise) to pop up so that the patient is most receptive to the message?
  • 101. Personalization: delivering relevant content (even if personalization options are bucketed into a finite number of options)
  • 102. Customization: patients prefer the ability to tailor the type and frequency of contact they receive from the app
  • 103. Accountability: patients enjoy receiving feedback and feeling accountable, but they want to control how/when the app interacts
  • 104. Human touch: patients enjoy themselves and are more responsive if they believe there is a real person behind the communication.
  • 105. Some programs sign all correspondence (even if the automated ones) with the name of the provider that the patient interacted with during the initial program set-up.
  • 106. Timeliness: Technical interventions need to be a presence and resource for in-the-moment decision-makingEmerging Features for Health-Related Apps Questions for Further Investigation
  • 107.
  • 108. Combining principles of information design with those of persuasion design to better motivate users to adopt and sustain healthy habits. Leveraging:
  • 110. Maslow’s Theory of Human Motivation and hierarchy of needs
  • 111. It is important to offer users small ways to begin a program and ramp incrementally so they do not become overwhelmed and resort to excuses as to why they cannot take on such a daunting undertaking.
  • 112. App usability must be designed to be inclusive of users with low literacy and numeracy.
  • 113. It can be challenging to figure out what the right portion size & nutrient mix is, given the skills required to interpret & utilize label information
  • 114. Use less words, more images.
  • 115.
  • 116. What are the optimal ways to leverage information design and persuasion techniques to achieve behavioral change?
  • 117. Instruction: include tips in games and wherever possible to educate and increase awareness
  • 118. Comprehensive, searchable database: increases the value of the tool and its educational potential (nutritional info, store locations, etc)
  • 119. Fun: entertaining and enjoyable apps increase stickiness
  • 120. Games: are fun but also incorporate other important features:
  • 121. Incentives & rewards (virtual or real): motivate people
  • 123. Social: sense of community and points of comparison are important
  • 124. Multiple data-entry options (type, scan labels, etc): ease of use
  • 125. Consequences: use predictions of future health consequences to build awareness and motivate users to make changes nowEmerging Features for Health-Related Apps Questions for Further Investigation
  • 126.
  • 130. The absence of feedback in this area underscores how little developers are thinking about catering to needs specific to communities with low SES.
  • 131.
  • 132. How do you migrate users from casual to high-value?
  • 133. Simplicity: tasks can’t be too burdensome or people won’t stick with it
  • 134. Usability: must be top notch to stand out and drive retention
  • 135. Social: integration with social networks is important for driving engagement; ‘a sense of community means you’re not alone’
  • 136. One developer reported that adding photo thumbnails to his app made it more personalized and drove up engagement.
  • 137. Personalization: critical for relevance, engagement and stickiness
  • 138. Comprehensiveness: a strong, frequently updated, backend database is needed to power high-quality tools and accurate
  • 139. Fun: fulfills user wishes and contributes to stickiness
  • 140. Feedback loop: app store reviews, comments on community boards, and emails provide helpful sources of user feedback for developersEmerging Features for Health-Related Apps Questions for Further Investigation
  • 141.
  • 142. Promoting and distributing a variety of high-quality applications (by)
  • 143. Gaining traction as a valuable partner among developers
  • 144. One option would be to create a dedicated app store for apps that cater to low SES communities.
  • 145.
  • 146. How will the role of app stores evolve relative to marketing and curating apps?
  • 147. In-app advertising should not be overly intrusive.
  • 148. A paid version of a freemium app has to offer more than just the same app absent advertising. There has to be real value offered to the consumer.
  • 149. Successful apps are well-designed and look nice, in addition to offering valued functionality.
  • 150. While developers have historically been fairly poor marketers, the ability to promote one’s app, stand out and garner attention from users has become increasingly critical to the success of an app.
  • 151. The importance of frictionless payment options (such as carrier billing) is fast increasing.Emerging Features for Health-Related Apps Questions for Further Investigation
  • 152. Contents 1 Obesity and Nutrition in America 2 Low SES Communities and Mobile Technology 3 Mobile Applications as a Health Enabler 4 Mobile Health Apps Overview 5 Preliminary Gap Analysis 6 Conclusions & Next Steps 7 Appendix
  • 153.
  • 154. Monitoring: There is also a need for high-quality monitoring apps that are user-friendly and sticky enough to motivate users to continue using them over long periods of time to maintain healthy regimens.
  • 155. Intervening: Because mobile phones are in close proximity to users at all times, there is tremendous potential for apps to be used as intervening mechanisms to promote good habits and, potentially, discourage bad ones. (For example: reminders to take medication; prompts to exercise at regular intervals, etc) New sensor technologies embedded in phones may further enable the development of apps with targeted behavioral interventions.
  • 156.
  • 157. Initiate market research to better understand the specific challenges, needs, motivators and preferences of the low SES target segment.
  • 158. Partner with developers of market-leading apps to add supplemental enabling functionality targeted to low SES communities.
  • 159. Partner with developers to build new apps designed to meet the needs of low SES communities that offer enabling, monitoring and intervening functionality.Key Findings Next Steps for A4G
  • 160.
  • 161. Next generation apps will differentiate themselves and boost quality by integrating a host of features that will improve their value proposition, stickiness and effectiveness. For example:
  • 163. Social components to increase sense of community;
  • 164. Gaming to leverage users‘ competitiveness and increase fun factor, retention and motivation.
  • 165. Goal-setting can be a powerful technique for behavior change. Apps that help users set realistic goals, develop plans and skills needed to reach those goals, and monitor progress along the way, are positioned to offer formidable tools for instilling healthy habits.
  • 166. Robust apps that offer some of the most valuable tools for both education and behavioral change incorporate comprehensive databases which provide a rich source of information from which users can draw as they improve their own skills and decision-making.
  • 167.
  • 168. Expert knowledge of A4G’s target market preferences, behaviors and challenges will help A4G collaborate with developers to design appropriate solutions, user experiences and applications to drive positive behavioral change.
  • 169. A4G might also consider sponsoring studies to research optimal tactics to overcome the challenges of low literacy and numeracy.
  • 170. Usability and features designed with these users in mind will expand mobile app access to a broader population.Key Findings Next Steps for A4G
  • 171.
  • 172. App discovery is a significant challenge across the mobile ecosystem and even more acute for applications targeting a smaller, often-marginalized group of users.
  • 173. Increasingly, app developers are testing a variety of marketing avenues for efficacy and ROI, including:
  • 174. Mobile advertising (usually a pay-per-download model)
  • 176. PR for apps (which includes everything from building a more attractive app store icon to wrangling press coverage for the app)
  • 177. SEO (search engine optimization) for mobile app stores
  • 178.
  • 179. The Beehive has a health section which is targeted to users of low SES. Market-leading and low SES-targeted apps could be promoted effectively via this outlet.
  • 180. One Economy‘s partners in bringing broadband to underserved communities (particularly in public housing projects) could also be tapped to help promote awareness of leading health apps.
  • 181. Additionally, A4G could create a ‘Featured Apps‘ page on its website and promote the page among target groups to boost awareness. This central clearinghouse could serve as a destination for A4G‘s target audience looking for a curated list of apps well-suited to their needs.
  • 182. A4G could develop a list of marketing guidelines or best practices for developers seeking to serve A4G‘s constituents.
  • 183. A4G could also develop partnerships with corporate entities (such as insurance, pharmaceutical and food companies) to develop co-marketing campaigns.Key Findings Next Steps for A4G
  • 184.
  • 187.
  • 188. Health insurance companies might benefit from subsidizing app development and distribution costs if apps can help reduce other costs such as hospitalizations resulting from drug non-compliance or poor health conditions as a result of unhealthy (nutrition or exercise) choices.
  • 189. Example: State Farm sponsored an app called On the Move that sends automatic text message replies while the user is driving. The company hopes the app will help users avoid distracted driving, thereby saving the company money by reducing the number of accident claims.Key Findings Next Steps for A4G
  • 190. Contents 1 Obesity and Nutrition in America 2 Low SES Communities and Mobile Technology 3 Mobile Applications as a Health Enabler 4 Mobile Health Apps Overview 5 Preliminary Gap Analysis 6 Conclusions & Next Steps 7 Appendix
  • 191.
  • 192. automatically scan a product barcode
  • 193. see product highlights (both good and bad)
  • 195. Fooducate analyzes information found in each product's nutrition panel and ingredient list
  • 196. You get to see the stuff manufacturers don't want you to notice
  • 197. Recipe suggestions personalized for health conditions
  • 198. Links and directions to grocery outlets that carry suggested products and accept food stamps
  • 199. Matching suggested products with store discounts or coupons
  • 200.
  • 201. OnTrack helps diabetics manage their diabetes by tracking various items such as blood glucose, food, medication, blood pressure (BP), pulse, exercise and weight.
  • 203. Add multiple entries simultaneously, for example add glucose and medication at one time quickly and easily & a variety of detailed graphs and reports
  • 204. a detailed log book with tables and graphs suitable for sharing with your doctor
  • 205. activate reminders (e.g. remind yourself to test two hours after eating food)
  • 206. Community forums for diabetics to share tips, support and information
  • 207. Information for low-income diabetics to get medication and treatment ideas
  • 208.
  • 209. Sergey OreshkoCEO, 4Technologies Corporation (MyNetDiary)
  • 211. J. Graham Thomas, PhD Assistant Professor (Research), Weight Control & Diabetes Research Center, The Miriam Hospital & Brown Medical School
  • 212. Hemi WeingartenCo-Founder & CEO, Fooducate
  • 213. Rena Wing, PhDDirector, Weight Control & Diabetes Research Center at the Miriam Hospital, RIProfessor, Department of Psychiatry and Human Behavior, Brown University Medical School