This study evaluated a mobile diabetes management platform used by 8 pediatric patients over 2 months. The platform combined mobile tracking of health metrics, social networking, and gaming. Key findings from analysis of usage data, comments, and surveys include:
1) Users regularly tracked health data and engaged with social features, indicating the platform successfully encouraged engagement in self-management.
2) Usage patterns stabilized over time and aligned with best practices of pre- and post-meal tracking, though full alignment with clinical guidelines was not achieved.
3) Preliminary results suggest the platform has potential to effectively leverage mobile and social features to support pediatric self-management and provide useful insights.
Usability Guidance for Improving the User Interface and Adoption of Online P...GfK User Centric
During December 2008 and January 2009, the user experience research firm User Centric conducted an independent comparative usability study of two existing online personal health record applications,
Google Health and Microsoft HealthVault. (Neither Google nor Microsoft commissioned or participated in this study in any manner.) During this study, 30 participants completed key tasks using each PHR application and provided qualitative feedback, ratings and preference data on five specific dimensions:
Overall usability, utility (usefulness of features), security, privacy and trust. Participants performed up to seven tasks on both Google Health and Microsoft HealthVault, which included three tasks that explored each application’s unique features. Midway through the study, a third PHR application, MyMedicalRecords.com, was added to gather additional qualitative data.
The majority of study participants found PHRs to be useful and stated that they had an interest in building their own PHRs after the study. Overall, participants indicated that they found Google Health more usable
because navigation and data entry of health information was easier than on the other applications.
Participants said that the Google Health application utilized more familiar medical terminology and provided a persistent health information profile summary.
User Centric has identified trends based on an analysis of the study data.
1) Home and specialty infusion professionals widely embrace mobile health technology, with 83% using apps to reference drug or clinical information and 40% using apps to communicate with coworkers.
2) Popular clinical apps used include Epocrates, Lexicomp, Medscape, and Micromedex for drug information, and effective app features include leveraging smartphone capabilities, linking to external sensors, and securely transmitting data.
3) While apps can help improve patient engagement and care delivery, barriers remain around evidence, integration, privacy, and reimbursement, though the mobile health market is expected to reach $31 billion by 2020.
The document discusses risk management strategies for Scranton Medicare, a mobile healthcare institution. It identifies three main risks: data confidentiality issues from sharing patient information via mobile devices, volatility in the mobile health market as technologies change, and challenges integrating mobile services with existing IT systems. The document recommends Scranton Medicare thoroughly research new mobile health technologies, provide training to users on mobile apps, and establish clear policies for handling protected health information to mitigate these risks. Education and policy are key to ensuring risks do not materialize that could harm patients, providers, or the institution.
The explosion in the number of applications (apps) designed for the medical and wellness sectors has been noted by many. Recently we have seen increased presence of truly medical apps, in addition to consumer health and wellbeing apps, designed for clinical professionals and patients with medical conditions.
Consumer based mHealth apps typically allow people to do old things in new ways, such as recording health measures digitally rather than on paper. We see this also with medical apps, where increases in the quality and efficiency of existing health care models provide clinical staff with digital tools that replace paper based documentation. In rare and exciting cases we are also seeing mHealth applications that are doing things in entirely new ways to drive real innovation in health care delivery through mobile devices.
The aim of the tutorial is to highlight real world, high impact mobile research that is relevant to the key discipline of Mobile HCI. Thus, the tutorial will be application rather than academically focused. The tutorial will highlight the wide range of mHealth applications available that go far beyond trackers and behavior change tools and encourage researchers to look beyond consumer applications in their research. Four key areas of mHealth applications will be covered including Apps for the HealthyWell, mHealth in Hospitals, Practice and Clinical Apps and Patient Apps and will cover applications for health assessment, treatment and triage, behavior change, chronic illness, mental health, adolescent health, rehabilitation and age care with a focus on the need for rigorous evaluation and efficacy analysis.
Ict project management question one risk management in mobile health care i...SkypeID_virtualbraininc
Scranton Medicare is implementing a mobile health (mHealth) program to improve patient care. Key risks include protecting patient data confidentiality, adapting to fast-changing mobile technology markets, and integrating mHealth with existing IT systems. To mitigate these risks, Scranton must research mHealth technologies, educate medical staff on new apps, and establish clear policies for mobile device use and data handling. Addressing these risks upfront through stakeholder research and training programs can help ensure a successful mHealth rollout at Scranton Medicare.
The document examines Duke University Hospital's (DUH) current and future use of digital technology and social media. It discusses DUH's existing online presence, considerations for digital security, and technologies like cloud-based software that could enhance DUH's digital presence. The implications of the internet and social media for DUH are explored, including opportunities to share knowledge but also threats like ransomware. Strategies are recommended for DUH to encourage provider social media use without damaging its brand, such as bolstering policies and aligning social media goals with engagement tactics.
mHealth: Transforming Healthcare and Driving Business for Pharmaceutical Comp...Merqurio
Get exclusive access to our brand new Whitepaper "mHealth: Transforming Healthcare and Driving Business for Pharmaceutical Companies." Click here:
http://bit.ly/1x21JaM
It’s free.
Usability Guidance for Improving the User Interface and Adoption of Online P...GfK User Centric
During December 2008 and January 2009, the user experience research firm User Centric conducted an independent comparative usability study of two existing online personal health record applications,
Google Health and Microsoft HealthVault. (Neither Google nor Microsoft commissioned or participated in this study in any manner.) During this study, 30 participants completed key tasks using each PHR application and provided qualitative feedback, ratings and preference data on five specific dimensions:
Overall usability, utility (usefulness of features), security, privacy and trust. Participants performed up to seven tasks on both Google Health and Microsoft HealthVault, which included three tasks that explored each application’s unique features. Midway through the study, a third PHR application, MyMedicalRecords.com, was added to gather additional qualitative data.
The majority of study participants found PHRs to be useful and stated that they had an interest in building their own PHRs after the study. Overall, participants indicated that they found Google Health more usable
because navigation and data entry of health information was easier than on the other applications.
Participants said that the Google Health application utilized more familiar medical terminology and provided a persistent health information profile summary.
User Centric has identified trends based on an analysis of the study data.
1) Home and specialty infusion professionals widely embrace mobile health technology, with 83% using apps to reference drug or clinical information and 40% using apps to communicate with coworkers.
2) Popular clinical apps used include Epocrates, Lexicomp, Medscape, and Micromedex for drug information, and effective app features include leveraging smartphone capabilities, linking to external sensors, and securely transmitting data.
3) While apps can help improve patient engagement and care delivery, barriers remain around evidence, integration, privacy, and reimbursement, though the mobile health market is expected to reach $31 billion by 2020.
The document discusses risk management strategies for Scranton Medicare, a mobile healthcare institution. It identifies three main risks: data confidentiality issues from sharing patient information via mobile devices, volatility in the mobile health market as technologies change, and challenges integrating mobile services with existing IT systems. The document recommends Scranton Medicare thoroughly research new mobile health technologies, provide training to users on mobile apps, and establish clear policies for handling protected health information to mitigate these risks. Education and policy are key to ensuring risks do not materialize that could harm patients, providers, or the institution.
The explosion in the number of applications (apps) designed for the medical and wellness sectors has been noted by many. Recently we have seen increased presence of truly medical apps, in addition to consumer health and wellbeing apps, designed for clinical professionals and patients with medical conditions.
Consumer based mHealth apps typically allow people to do old things in new ways, such as recording health measures digitally rather than on paper. We see this also with medical apps, where increases in the quality and efficiency of existing health care models provide clinical staff with digital tools that replace paper based documentation. In rare and exciting cases we are also seeing mHealth applications that are doing things in entirely new ways to drive real innovation in health care delivery through mobile devices.
The aim of the tutorial is to highlight real world, high impact mobile research that is relevant to the key discipline of Mobile HCI. Thus, the tutorial will be application rather than academically focused. The tutorial will highlight the wide range of mHealth applications available that go far beyond trackers and behavior change tools and encourage researchers to look beyond consumer applications in their research. Four key areas of mHealth applications will be covered including Apps for the HealthyWell, mHealth in Hospitals, Practice and Clinical Apps and Patient Apps and will cover applications for health assessment, treatment and triage, behavior change, chronic illness, mental health, adolescent health, rehabilitation and age care with a focus on the need for rigorous evaluation and efficacy analysis.
Ict project management question one risk management in mobile health care i...SkypeID_virtualbraininc
Scranton Medicare is implementing a mobile health (mHealth) program to improve patient care. Key risks include protecting patient data confidentiality, adapting to fast-changing mobile technology markets, and integrating mHealth with existing IT systems. To mitigate these risks, Scranton must research mHealth technologies, educate medical staff on new apps, and establish clear policies for mobile device use and data handling. Addressing these risks upfront through stakeholder research and training programs can help ensure a successful mHealth rollout at Scranton Medicare.
The document examines Duke University Hospital's (DUH) current and future use of digital technology and social media. It discusses DUH's existing online presence, considerations for digital security, and technologies like cloud-based software that could enhance DUH's digital presence. The implications of the internet and social media for DUH are explored, including opportunities to share knowledge but also threats like ransomware. Strategies are recommended for DUH to encourage provider social media use without damaging its brand, such as bolstering policies and aligning social media goals with engagement tactics.
mHealth: Transforming Healthcare and Driving Business for Pharmaceutical Comp...Merqurio
Get exclusive access to our brand new Whitepaper "mHealth: Transforming Healthcare and Driving Business for Pharmaceutical Companies." Click here:
http://bit.ly/1x21JaM
It’s free.
Managing Binge Eating Disorder with iTakeControliTakeControl
Mobile health applications are still in their infancy but present a great opportunity for the healthcare industry. They enable patients to have a greater role in their health, empower providers to make data-driven decisions, allow researchers to gain greater insight into patient and disease populations, and give payers a new window into how patients are doing on treatment.
In this paper, we dive into iTakeControl’s Binge application and look into some of the data we have gathered so far.
mHealth Israel_Ralf Jahns_Research2Guidance_The EU Countries’ mHealth App Mar...Levi Shapiro
The EU Countries’ mHealth App Market Ranking 2015, by Ralf Gordon Jahns, CEO of Research2Guidance. Presentation made at the mHealth Israel Investors Summit, June, 2015
Mobile technology can help bridge health systems gaps and improve reproductive, maternal, newborn and child health outcomes. It has the potential to give every family access to information and services, support health workers, and create a more accountable health system. There are now over 137 mHealth projects at Johns Hopkins using mobile tools in various ways, such as providing education and referrals to communities, decision support and monitoring for health workers, and improving data collection and reporting across the health system. Rigorous evaluation is still needed to demonstrate the impact of mHealth on health outcomes and health systems strengthening.
MEDICATION REMINDER AND HEALTHCARE – AN ANDROID APPLICATIONijmpict
This is an Android-based application in which an automatic alarm ringing system is implemented. It
focuses on doctor and patient interaction. Patients need not remember their medicine dosage timings as
they can set an alarm on their dosage timings. The alarm can be set for multiple medicines and timings
including date, time and medicine description. A notification will be sent to them through email or message
inside the system preferably chosen by the patients. They can search doctor disease wise. The patients will
get the contact details of doctors as per their availability. Also the users can see different articles related to
medical fields and health care tips. The system focuses on easy navigation and good user interface. Many
such Medical Reminder Systems have been developed where a new hardware is required but in our work
we have made an attempt to develop a system which is economical, time-saving and supports medication
adherence.
This lecture discusses strategies for designing patient-centered behavior change interventions. It provides an overview of tools and sources for patient engagement, including community programs, organizational strategies, healthcare team approaches, and individual-level activities. The lecture also covers areas to measure patient engagement and the role of mobile technologies and patient portals in supporting chronic disease management and population health improvement.
Digital Health: Medicine at the CroosroadsSteven Peskin
This document discusses the implications of mobile health and social media in clinical practice. It describes the three components of digital health as applications, devices, and infrastructure. Mobile technologies and social media have tremendous potential to improve care delivery, patient safety, information dissemination, and chronic disease management. The document outlines how physician communities on social media can facilitate knowledge sharing and discusses the growth of medical apps. It predicts that mobile health and social media will become integrated into everyday healthcare through digital tools and communities.
The rise of digital technologies has transformed healthcare by empowering patients through greater access to information via social media and mobile devices. While social media usage among older patients and those with chronic conditions still lags, it is growing rapidly. Social media plays a critical role throughout a patient's healthcare journey by expanding their ability to discuss health issues with others. However, more investigation is needed to fully understand the impact of social media on healthcare decisions and outcomes.
Mobile health applications risk management frameworkKipkoech Benard
This document discusses risks associated with mobile health applications and proposes a framework for managing these risks. It investigates the risks users are exposed to from using health apps, such as security/privacy breaches, reputation damage, fraud, poor clinical decisions, and loss of doctor-patient assessment. The proposed risk management framework consists of four domains: objective setting, identifying threats/vulnerabilities, identifying risks, and implementing risk control/prevention measures. The framework aims to provide guidelines for stakeholders to better manage risks in the health apps industry and allow it to reach its full potential.
Pharma must change the ways it deals with physicians and patients. These three digital health technology companies will revolutionize the way Pharma does business.
Mobile healthcare apps and programs are growing rapidly due to increased smartphone usage and a focus on patient-centric care. The market for healthcare apps is expected to more than double from $25 billion in 2017 to over $58 billion in 2020. Healthcare apps allow people to conveniently monitor their health and schedule appointments. Successful healthcare apps include features like user profiles, doctor profiles, appointment booking, payments, geo-location services, telemedicine, medical records storage, and medication reminders. Developing a healthcare app costs between $30,000 to $70,000 depending on features. The global market for healthcare apps is projected to reach $1 billion by 2022.
A new survey from UnitedHealthCare finds that 1 in 5 people consult the internet or a mobile app as the first source for information on specific diseases or symptoms. Here’s more from the consumer health survey:
•Technology use: 30% of millennials surveyed said they relied on the internet or a mobile app for health information. Some 45% of all respondents said they’d be interested in having their physician use AI to help with diagnoses.
•Transparency: Nearly two-thirds of people said they “never” knew the cost of medications before leaving a doctor’s office. More than a third said they used the internet to compare health costs.
•Insurance: More than half of people knew what a “premium” and “deductible” were in terms of health plans. Some 75% of people said they felt prepared to select a plan during the upcoming insurance enrollment season.
Patient Access to Personal Health Information Across Health Care Settingsthe Health Advocate
The study aimed to characterize patient experiences accessing personal health information across different healthcare settings and understand barriers to meaningful use of electronic health records from the patient perspective. In-depth interviews and focus groups with patients found that in 2012, access times ranged from 3-30 days, with academic medical centers providing information fastest. Community hospitals relied on slower mail/fax delivery. Participants reported physical, financial, and attitudinal barriers. The findings suggest a need for improved health data access policies and technologies to better support patient self-management of chronic conditions.
Consumer facing digital health technologies such as apps, wearables, and websites have grown rapidly in popularity. However, obesity and diabetes rates continue to rise in the US. While many users say technologies help them track health and ask doctors new questions, the overall health of populations has not improved proportionately. Barriers to the success of these technologies include a lack of standards, concerns over privacy of personal health data, and low adoption rates by healthcare providers. Health literacy may be needed to help users apply insights from technologies effectively and drive meaningful behavior changes for better health outcomes.
Engaging patients through social media imshealth 2014Georgi Daskalov
The document discusses the rise of social media in healthcare and its impact. It notes that while social media usage is growing, it still lags among older patient populations. Regulators have been slow to provide guidance on social media. Pharmaceutical companies have also been slow to embrace social media, but smaller companies and those in consumer healthcare are leading the way. Further investigation is needed to fully understand the impact of social media on healthcare decisions and outcomes.
Wilhide, Peeples, & Anthony Kouyate (2015) Evidence-Based mHealth Chronic Dis...Robin Anthony Kouyate, PhD
This document discusses the development of a framework for designing evidence-based mobile health (mHealth) apps to support chronic disease management. The framework was developed over two years through an iterative process of applying the framework to design mHealth apps for different diseases. The final framework includes 7 domains to guide app development: 3 strategic domains to identify value drivers, outcomes, and program objectives, 3 intervention domains to design clinical and behavioral interventions, and 1 domain focused on app features and content. The framework is intended to facilitate the systematic development of scalable, replicable mHealth interventions that can be evaluated for their effectiveness.
Perficient Perspectives: The Evolution of Social Media in HealthcarePerficient, Inc.
Healthcare organizations continue to navigate the transforming healthcare industry and identify new avenues to engage with consumers outside of the facility walls. In a fast-paced, information-dominated world, successfully interacting with consumers may seem like a daunting task. The key is to connect with consumers where they are and provide them with actionable health and wellness information they need to live a healthier life.
When you think of social media in healthcare you might think it is a tool for marketing, but it goes much farther than that. Sure, social media can be used to attract and retain consumers, but social media can also be a powerful tool to reduce healthcare costs and help with chronic disease and population health management.
Healthcare organizations are in varying stages of becoming social enterprises, from social innovators like Mayo Clinic to those beginning the journey to developing a comprehensive social media strategy.
In this perspective, we take a look at the evolution of social media in healthcare and discuss what social media in healthcare will look like in the future.
Social Media by the Numbers: How Social Media Impacts Healthcare and How Phys...RefluxMD
Social media use has grown significantly with over 70% of adults now using sites like Facebook and Twitter. Healthcare social media use is also increasing, with around 40% of consumers using sites to research health topics, find communities, and learn about procedures. Physicians can benefit from social media by using it to establish their brand, connect with potential new patients, and expand their role in managing existing patients outside of the office. This allows for more continuous education and support that can improve outcomes, especially for chronic conditions.
Dilli Arts Junction is an arts festival in Delhi, India organized by students of IMT Ghaziabad to promote various art forms. It aims to provide a platform for amateur and professional artists to learn, compete and enjoy the arts. The festival will feature competitions and performances across five art forms - cinema, drama, music, photography and literature. Workshops, seminars and exhibitions will also be held to promote learning. Winners will get opportunities to work with established artists and production houses. The objectives are to augment arts culture in Delhi and India and provide emerging artists a stage.
The document discusses the benefits of exercise for mental health. Regular physical activity can help reduce anxiety and depression and improve mood and cognitive functioning. Exercise causes chemical changes in the brain that may help protect against mental illness and improve symptoms.
Managing Binge Eating Disorder with iTakeControliTakeControl
Mobile health applications are still in their infancy but present a great opportunity for the healthcare industry. They enable patients to have a greater role in their health, empower providers to make data-driven decisions, allow researchers to gain greater insight into patient and disease populations, and give payers a new window into how patients are doing on treatment.
In this paper, we dive into iTakeControl’s Binge application and look into some of the data we have gathered so far.
mHealth Israel_Ralf Jahns_Research2Guidance_The EU Countries’ mHealth App Mar...Levi Shapiro
The EU Countries’ mHealth App Market Ranking 2015, by Ralf Gordon Jahns, CEO of Research2Guidance. Presentation made at the mHealth Israel Investors Summit, June, 2015
Mobile technology can help bridge health systems gaps and improve reproductive, maternal, newborn and child health outcomes. It has the potential to give every family access to information and services, support health workers, and create a more accountable health system. There are now over 137 mHealth projects at Johns Hopkins using mobile tools in various ways, such as providing education and referrals to communities, decision support and monitoring for health workers, and improving data collection and reporting across the health system. Rigorous evaluation is still needed to demonstrate the impact of mHealth on health outcomes and health systems strengthening.
MEDICATION REMINDER AND HEALTHCARE – AN ANDROID APPLICATIONijmpict
This is an Android-based application in which an automatic alarm ringing system is implemented. It
focuses on doctor and patient interaction. Patients need not remember their medicine dosage timings as
they can set an alarm on their dosage timings. The alarm can be set for multiple medicines and timings
including date, time and medicine description. A notification will be sent to them through email or message
inside the system preferably chosen by the patients. They can search doctor disease wise. The patients will
get the contact details of doctors as per their availability. Also the users can see different articles related to
medical fields and health care tips. The system focuses on easy navigation and good user interface. Many
such Medical Reminder Systems have been developed where a new hardware is required but in our work
we have made an attempt to develop a system which is economical, time-saving and supports medication
adherence.
This lecture discusses strategies for designing patient-centered behavior change interventions. It provides an overview of tools and sources for patient engagement, including community programs, organizational strategies, healthcare team approaches, and individual-level activities. The lecture also covers areas to measure patient engagement and the role of mobile technologies and patient portals in supporting chronic disease management and population health improvement.
Digital Health: Medicine at the CroosroadsSteven Peskin
This document discusses the implications of mobile health and social media in clinical practice. It describes the three components of digital health as applications, devices, and infrastructure. Mobile technologies and social media have tremendous potential to improve care delivery, patient safety, information dissemination, and chronic disease management. The document outlines how physician communities on social media can facilitate knowledge sharing and discusses the growth of medical apps. It predicts that mobile health and social media will become integrated into everyday healthcare through digital tools and communities.
The rise of digital technologies has transformed healthcare by empowering patients through greater access to information via social media and mobile devices. While social media usage among older patients and those with chronic conditions still lags, it is growing rapidly. Social media plays a critical role throughout a patient's healthcare journey by expanding their ability to discuss health issues with others. However, more investigation is needed to fully understand the impact of social media on healthcare decisions and outcomes.
Mobile health applications risk management frameworkKipkoech Benard
This document discusses risks associated with mobile health applications and proposes a framework for managing these risks. It investigates the risks users are exposed to from using health apps, such as security/privacy breaches, reputation damage, fraud, poor clinical decisions, and loss of doctor-patient assessment. The proposed risk management framework consists of four domains: objective setting, identifying threats/vulnerabilities, identifying risks, and implementing risk control/prevention measures. The framework aims to provide guidelines for stakeholders to better manage risks in the health apps industry and allow it to reach its full potential.
Pharma must change the ways it deals with physicians and patients. These three digital health technology companies will revolutionize the way Pharma does business.
Mobile healthcare apps and programs are growing rapidly due to increased smartphone usage and a focus on patient-centric care. The market for healthcare apps is expected to more than double from $25 billion in 2017 to over $58 billion in 2020. Healthcare apps allow people to conveniently monitor their health and schedule appointments. Successful healthcare apps include features like user profiles, doctor profiles, appointment booking, payments, geo-location services, telemedicine, medical records storage, and medication reminders. Developing a healthcare app costs between $30,000 to $70,000 depending on features. The global market for healthcare apps is projected to reach $1 billion by 2022.
A new survey from UnitedHealthCare finds that 1 in 5 people consult the internet or a mobile app as the first source for information on specific diseases or symptoms. Here’s more from the consumer health survey:
•Technology use: 30% of millennials surveyed said they relied on the internet or a mobile app for health information. Some 45% of all respondents said they’d be interested in having their physician use AI to help with diagnoses.
•Transparency: Nearly two-thirds of people said they “never” knew the cost of medications before leaving a doctor’s office. More than a third said they used the internet to compare health costs.
•Insurance: More than half of people knew what a “premium” and “deductible” were in terms of health plans. Some 75% of people said they felt prepared to select a plan during the upcoming insurance enrollment season.
Patient Access to Personal Health Information Across Health Care Settingsthe Health Advocate
The study aimed to characterize patient experiences accessing personal health information across different healthcare settings and understand barriers to meaningful use of electronic health records from the patient perspective. In-depth interviews and focus groups with patients found that in 2012, access times ranged from 3-30 days, with academic medical centers providing information fastest. Community hospitals relied on slower mail/fax delivery. Participants reported physical, financial, and attitudinal barriers. The findings suggest a need for improved health data access policies and technologies to better support patient self-management of chronic conditions.
Consumer facing digital health technologies such as apps, wearables, and websites have grown rapidly in popularity. However, obesity and diabetes rates continue to rise in the US. While many users say technologies help them track health and ask doctors new questions, the overall health of populations has not improved proportionately. Barriers to the success of these technologies include a lack of standards, concerns over privacy of personal health data, and low adoption rates by healthcare providers. Health literacy may be needed to help users apply insights from technologies effectively and drive meaningful behavior changes for better health outcomes.
Engaging patients through social media imshealth 2014Georgi Daskalov
The document discusses the rise of social media in healthcare and its impact. It notes that while social media usage is growing, it still lags among older patient populations. Regulators have been slow to provide guidance on social media. Pharmaceutical companies have also been slow to embrace social media, but smaller companies and those in consumer healthcare are leading the way. Further investigation is needed to fully understand the impact of social media on healthcare decisions and outcomes.
Wilhide, Peeples, & Anthony Kouyate (2015) Evidence-Based mHealth Chronic Dis...Robin Anthony Kouyate, PhD
This document discusses the development of a framework for designing evidence-based mobile health (mHealth) apps to support chronic disease management. The framework was developed over two years through an iterative process of applying the framework to design mHealth apps for different diseases. The final framework includes 7 domains to guide app development: 3 strategic domains to identify value drivers, outcomes, and program objectives, 3 intervention domains to design clinical and behavioral interventions, and 1 domain focused on app features and content. The framework is intended to facilitate the systematic development of scalable, replicable mHealth interventions that can be evaluated for their effectiveness.
Perficient Perspectives: The Evolution of Social Media in HealthcarePerficient, Inc.
Healthcare organizations continue to navigate the transforming healthcare industry and identify new avenues to engage with consumers outside of the facility walls. In a fast-paced, information-dominated world, successfully interacting with consumers may seem like a daunting task. The key is to connect with consumers where they are and provide them with actionable health and wellness information they need to live a healthier life.
When you think of social media in healthcare you might think it is a tool for marketing, but it goes much farther than that. Sure, social media can be used to attract and retain consumers, but social media can also be a powerful tool to reduce healthcare costs and help with chronic disease and population health management.
Healthcare organizations are in varying stages of becoming social enterprises, from social innovators like Mayo Clinic to those beginning the journey to developing a comprehensive social media strategy.
In this perspective, we take a look at the evolution of social media in healthcare and discuss what social media in healthcare will look like in the future.
Social Media by the Numbers: How Social Media Impacts Healthcare and How Phys...RefluxMD
Social media use has grown significantly with over 70% of adults now using sites like Facebook and Twitter. Healthcare social media use is also increasing, with around 40% of consumers using sites to research health topics, find communities, and learn about procedures. Physicians can benefit from social media by using it to establish their brand, connect with potential new patients, and expand their role in managing existing patients outside of the office. This allows for more continuous education and support that can improve outcomes, especially for chronic conditions.
Dilli Arts Junction is an arts festival in Delhi, India organized by students of IMT Ghaziabad to promote various art forms. It aims to provide a platform for amateur and professional artists to learn, compete and enjoy the arts. The festival will feature competitions and performances across five art forms - cinema, drama, music, photography and literature. Workshops, seminars and exhibitions will also be held to promote learning. Winners will get opportunities to work with established artists and production houses. The objectives are to augment arts culture in Delhi and India and provide emerging artists a stage.
The document discusses the benefits of exercise for mental health. Regular physical activity can help reduce anxiety and depression and improve mood and cognitive functioning. Exercise causes chemical changes in the brain that may help protect against mental illness and improve symptoms.
El documento presenta ideas sobre el aprendizaje móvil (mlearning) y su evolución hacia un aprendizaje accesible en cualquier lugar y momento. También discute sobre la incorporación de realidad virtual y contenidos MOOC, así como cuestiones sobre la población objetivo, contextos de uso y el carácter abierto y compartido del conocimiento.
The document describes a series of artworks by Margaret Ann Withers. It includes the titles and dimensions of 14 pieces, each consisting of combinations of materials like resin, pigment, oil, string, and painted vellum. It also provides copyright information for Margaret Ann Withers and contact details if one wants to purchase her artwork or request a price sheet. It concludes with a brief biography of the artist and description of her artistic technique called "compound lyrical expressionism."
A brief overview of what Google Analytics can do for a website, the current status of the VacationBetter.org website, and how in the coming months we will improve site traffic.
Dilli Arts Junction is an arts festival in Delhi organized by students of IMT Ghaziabad to showcase diverse artistic talents in India. It aims to promote arts culture through workshops, competitions, and performances across 5 verticals - cinema, drama, music, photography, and literature. Winners will receive prizes and opportunities to work with established artists and production houses. The festival hopes to augment arts in India by allowing artists to learn, compete and enjoy various art forms.
Playing bridge improves cognitive abilities such as memory, reasoning, and problem-solving. The document analyzes the probabilities of different contract bids between partners and opponents in a bridge game, finding a 2 spades bid to have a 37.5% probability of success based on the given opponent bids.
Learn how to take event marketing programs to the next level, leveraging social media to maximize the impact of all event efforts--from planning and promotion, to execution and follow-up. This presentation from Constant Contact and HubSpot explores:
• Where to promote events to increase registration
• How to inject social media marketing into events
• How to brand an event for maximum exposure
• What to include in the event follow-up
The document provides step-by-step instructions for creating a simple VB6 application with a MySQL database. It describes creating a new VB application project, adding an MDI form with menus and submenus, and creating child MDI forms using a wizard to display and manage data from the MySQL database. The instructions conclude by explaining how to call the child forms from the menu to complete and run the basic VB6 and MySQL application.
This document provides an overview of an exploratory visual approach to abstraction called "Imagining Data". It includes examples of 10 different artworks that visualize or abstractly represent various types of data through different mediums such as paintings, network diagrams, printed documents, and installations. The document serves to illustrate how data can be creatively interpreted and imagined through non-traditional visual forms.
Automation in the Digital World - Keynote 2013Jim Pinto
The document discusses major changes coming to industrial automation due to new digital technologies. It notes that globalization, faster production, and consumption-based markets require smaller, customized, distributed production. New automation technologies like wireless networks, mobile devices, cloud computing, the internet of things, machine-to-machine communication, and smart robots will transform automation by making it more connected, data-driven, and productive. The new leaders in automation will be those able to significantly improve productivity and meet rapidly changing global demands through innovative use of these digital technologies.
This document provides information on various biology topics in outline form:
- Insulin and glucose regulation in the liver
- Aerobic and anaerobic respiration and their differences
- Factors that affect pulse rate and blood pressure during exercise
- The roles of carbohydrates, fats, proteins, vitamins and fiber in digestion
- Calculation of Body Mass Index (BMI)
- The process of digestion and the roles of enzymes
- Types of immune responses against pathogens
- Structure and function of the eye, including accommodation and common vision defects
- Structure and function of neurons, synapses, and reflex arcs
- Effects and risks of stimulant and depressant drugs
- Negative feedback loops to maintain
Prototype design of a mobile app oriented to adults with obesityIJECEIAES
Obesity in adults is a worldwide problem, which is why different countries, through their health-related agencies, implement policies to fight this disease. One of the tools is the use of a mobile application that controls obesity. In this sense, the prototype was designed taking into account different items such as physical activities, body mass index, calorie intake, and food options, among others. The objective of the research is to design a mobile app that allows us to control of obesity in adults. The methodology used is design thinking which allows us to use a systematic approach to reach the objective. An interview was conducted to identify the needs of the user and obtain information regarding their essential needs. In addition, a survey was carried out, the outcome shows satisfaction with a 58% acceptance rate. The beneficiaries of this research are adults who suffer from obesity and healthcare centers. Likewise, research has a positive impact since it focuses on solving problems directly related to health issues.
This document proposes a framework for evaluating mental health smartphone applications. It notes that while such apps have potential to extend mental health services, most have not been rigorously evaluated for efficacy, safety, or quality. The framework suggests apps be evaluated based on three dimensions: usefulness, usability, and integration/infrastructure. Specific criteria are outlined for each dimension to allow clinicians and patients to assess apps.
The use of mobile applications, through smart phones, smartphones, has been considered by many to be the technological revolution of greatest repercussion in recent times. Compared to a handheld computer and with access to millions of applications, its main feature is unlimited mobility, accompanying its user at all times and in any place. In health, it is known that professionals are constantly moving outside of the institutions in which they work, so mobility is fundamental, which contributes to the interoperability of mobile technologies. This study aims to identify the research involving mobile technology applied to the vaccination being used. The methodology used is of the type integrative review of the literature. The final sample had 14 papers.
Development of a web based social networking system for self-management of di...ijma
This paper presents the design and development of a web-based social networking system for selfmanagement
of diabetes mellitus. The objectives of this development are twofold. First is to enable diabetic
patients to record and monitor their blood glucose levels by using short message service (SMS) or through
a website. Second is to provide social networking functionalities for diabetic patients, healthcare workers,
and other related parties to form online communities for information sharing, support, and collaboration.
With responsive design, the website aims to provide the best possible user experience across devices from
desktops and notebooks to tablets and smart phones.
Empowering Healthcare: The Evolution of Healthcare App Development ServicesElina619459
In today's digital age, healthcare is no longer limited to traditional brick-and-mortar clinics and hospitals. The advent of healthcare app development services has ushered in a new era of accessible, efficient, and patient-centric healthcare solutions. These applications have transformed the way patients interact with healthcare providers, manage their health, and access vital medical information.
This paper examines the opportunities and benefits of using apps to help manage diabetes, as well as limitations and concerns. Apps can help patients track key areas of care, enable personalized self-management through data sharing with providers, and provide decision support. However, many apps focus only on parts of care and few use evidence-based practices or offer comprehensive education. After analyzing the top diabetes apps against criteria for effective features, the author concludes that Diabetes App is currently the best option due to its coverage of important data areas and education. Overall, apps show promise for improving outcomes but development needs to address gaps versus clinical guidelines.
A retrospective review of the Honduras AIN-C program guided by a community he...HFG Project
Factors that influence performance of community health workers (CHWs) delivering health services are not well understood. A recent logic model proposed categories of support from both health sector and communities influence CHW performance and program outcomes. This logic model has been used to review a growth monitoring program delivered by CHWs in Honduras, known as Atención Integral a la Niñez en la Comunidad (AIN-C). A retrospective review of AIN-C was conducted through a document desk review and supplemented with in-depth interviews. Documents were systematically coded using the categories from the logic model, and gaps were addressed through interviews. Authors reviewed coded data for each category to analyze program details and outcomes as well as identify potential issues and gaps in the logic model.
Assessing the Utility of Consumer Surveysfor Improving the Q.docxfredharris32
Assessing the Utility of Consumer Surveys
for Improving the Quality of Behavioral
Health Care Services
J. Randy Koch, PhD
Alison B. Breland, PhD
Mary Nash, PhD
Karen Cropsey, PsyD
Abstract
The development and implementation of provider performance and consumer outcome measures
for behavioral health care have been growing over the last decade, presumably because they are
useful tools for improving service quality. However, the extent to which providers have successfully
used performance measurement results has not been adequately determined. To this end, two
methods were used to better understand the use of data obtained from an annual survey of
behavioral health care consumers: a cross-sectional survey of executive directors, clinical program
directors, and quality improvement directors and follow-up interviews with a subsample of survey
respondents. Results revealed information about the use of consumer survey data, factors that
facilitate and hinder the use of results, as well as respondents’ opinions about consumer survey
administration procedures. These findings provide valuable information for the application of
performance measures and, ultimately, improving consumer outcomes.
Address correspondence to Alison B. Breland, PhD, Institute for Drug and Alcohol Studies, Virginia Commonwealth
University, McGuire Hall, Rm. B08, 1112 East Clay Street( P.O. Box 980310, Richmond, VA 23298, USA. Phone: +1-804-
6282300; Fax: +1-804-8287862; E-mail: [email protected]
J. Randy Koch, PhD, Institute for Drug and Alcohol Studies, Virginia Commonwealth University, P.O. Box 980310,
Richmond, VA, USA. Phone: +1-804-8288633; Fax: +1-804-8287862; E-mail: [email protected]
Mary Nash, PhD, School of Human and Organization Development, Fielding Graduate University, Santa Barbara, CA,
USA. Phone: +1-757-4356589; Fax: +1-757-4356589; E-mail: [email protected]
Karen Cropsey, PsyD, Department of Psychiatry and Behavioral Neurobiology, University of Alabama School of
Medicine, Birmingham, AL, USA. Phone: +1-205-9160135; Fax: +1-205-9409258; E-mail: [email protected]
This research was performed at the Virginia Commonwealth University, Institute for Drug and Alcohol Studies, 1112 East
Clay Street, Suite B-08, Richmond, VA 23298.
Journal of Behavioral Health Services & Research, 2010. c) 2010 National Council for Community Behavioral
Healthcare.
234 The Journal of Behavioral Health Services & Research 38:2 April 2011
Introduction
Over the past decade, there has been significant growth in the development and implementation
of provider performance and consumer outcome measures for the behavioral health care field. The
Federal Substance Abuse and Mental Health Services Administration has been at the forefront in
the development of performance measures for the public behavioral health care system and has
sponsored several initiatives that have facilitated the acceptance of performance measurement as an
essential business practice, including the Mental Health ...
Amplework, a leading mobile app development company in Los Angeles offers a step-by-step guide on developing a healthcare app for the post-pandemic era. We empower healthcare providers to embrace digital transformation, ensuring efficient remote consultations, streamlined data management, and enhanced service delivery.
The document discusses mobile health (mHealth), which uses mobile devices like phones and monitors to improve healthcare delivery and outcomes. It defines mHealth and notes there are over 165,000 mHealth apps available, mainly for patients, with top categories including disease and wellness management. mHealth aims to enhance self-management of chronic illnesses like diabetes and reduce hospital stays through remote monitoring. While mHealth has potential, challenges include regulatory issues, privacy, reliability and integration into healthcare systems. The document evaluates mHealth applications and provides examples of how mHealth is used for diabetes management, wellness tracking, diagnostics and distance learning.
This document discusses design considerations for healthcare applications related to diabetes. It covers interface design for mobile devices, ensuring usefulness and usability of applications, managing healthcare data integrity, and recommendations. The conclusion emphasizes that good information design for small screens, functional and performance testing, maintaining data quality, and centralized management approaches are important for effective diabetes management applications.
Mobile Health Application Framework for an Ideal User Experience: A User-Cent...CrimsonpublishersTTEH
rom the literature, it is evident that clinicians would use a mobile application only if they are motivated to do so, and lack of clinical and end-user engagement is one of the most common barriers affecting broader mobile health (mHealth) app adoption.This research aims to answer two questions related to mHealth apps in hospitals:A. How to provide the best user-experience for clinicians in daily routine bases andB. How to create a clinician-centric framework for wider mHealth apps adoption in hospitals?We propose a 6S framework focused on clinician-as-a-user, by analysing current mobile apps available for clinicians in hospitals with some level of clinical decision support. Based on the analysis and market review, we found that the best number of main screens required for a successful healthcare app is six. Finally, the app design/framework was evaluated for user engagement, ease of use and adoption by a broader user group consisting of researchers, clinicians and Health IT engineers
This document discusses a study of consumer healthcare apps and barriers to their broader use. It finds that while there are tens of thousands of apps available, most focus on wellness and few do more than provide information. Fewer than 500 downloads is typical for over 50% of apps. Barriers to greater use include a lack of guidance for patients, lack of evidence demonstrating benefits, and lack of integration into healthcare systems. Moving apps mainstream will require recognition of their role by payers and providers, addressing privacy and security, evaluating apps to guide patients and doctors, and integrating apps with care delivery.
This document summarizes research on mobile applications that promote healthy lifestyles. It reviews 8 sources that examine the design, features, effectiveness and challenges of such apps. The literature emphasizes using behavior change techniques, personalization, self-monitoring and feedback to engage users and facilitate long-term behavior change. While mobile apps show promise in health promotion, challenges remain around privacy, usability and integrating apps with healthcare systems. Emerging technologies may further impact app-based health promotion.
Revolutionizing Healthcare: mHealth App Development SolutionsChetu
mHealth app development solutions have revolutionized the healthcare industry by providing extensive benefits to both patients and healthcare providers. These applications are designed to help individuals manage their health and wellness by providing easy access to medical information, tracking health data, and connecting with healthcare professionals.
Original PaperWho Uses Mobile Phone Health Apps and Does U.docxvannagoforth
Original Paper
Who Uses Mobile Phone Health Apps and Does Use Matter? A
Secondary Data Analytics Approach
Jennifer K Carroll1, MPH, MD; Anne Moorhead2, MSc, MA, MICR, CSci, FNutr (Public Health), PhD; Raymond
Bond3, PhD; William G LeBlanc1, PhD; Robert J Petrella4, MD, PhD, FCFP, FACSM; Kevin Fiscella5, MPH, MD
1Department of Family Medicine, University of Colorado, Aurora, CO, United States
2School of Communication, Ulster University, Newtownabbey, United Kingdom
3School of Computing & Maths, University of Ulster, Newtownabbey, United Kingdom
4Lawson Health Research Institute, Family Medicine, Kinesiology and Cardiology, Western University, London, ON, Canada
5Family Medicine, Public Health Sciences and Community Health, University of Rochester Medical Center, Rochester, NY, United States
Corresponding Author:
Jennifer K Carroll, MPH, MD
Department of Family Medicine
University of Colorado
Mail Stop F496
12631 E. 17th Ave
Aurora, CO, 80045
United States
Phone: 1 303 724 9232
Fax: 1 303 724 9747
Email: [email protected]
Abstract
Background: Mobile phone use and the adoption of healthy lifestyle software apps (“health apps”) are rapidly proliferating.
There is limited information on the users of health apps in terms of their social demographic and health characteristics, intentions
to change, and actual health behaviors.
Objective: The objectives of our study were to (1) to describe the sociodemographic characteristics associated with health app
use in a recent US nationally representative sample; (2) to assess the attitudinal and behavioral predictors of the use of health
apps for health promotion; and (3) to examine the association between the use of health-related apps and meeting the recommended
guidelines for fruit and vegetable intake and physical activity.
Methods: Data on users of mobile devices and health apps were analyzed from the National Cancer Institute’s 2015 Health
Information National Trends Survey (HINTS), which was designed to provide nationally representative estimates for health
information in the United States and is publicly available on the Internet. We used multivariable logistic regression models to
assess sociodemographic predictors of mobile device and health app use and examine the associations between app use, intentions
to change behavior, and actual behavioral change for fruit and vegetable consumption, physical activity, and weight loss.
Results: From the 3677 total HINTS respondents, older individuals (45-64 years, odds ratio, OR 0.56, 95% CI 0.47-68; 65+
years, OR 0.19, 95% CI 0.14-0.24), males (OR 0.80, 95% CI 0.66-0.94), and having degree (OR 2.83, 95% CI 2.18-3.70) or less
than high school education (OR 0.43, 95% CI 0.24-0.72) were all significantly associated with a reduced likelihood of having
adopted health apps. Similarly, both age and education were significant variables for predicting whether a person had adopted a
mobile device, especially if that person was a college graduate (OR 3.30). Ind ...
Original PaperWho Uses Mobile Phone Health Apps and Does U.docxhoney690131
Original Paper
Who Uses Mobile Phone Health Apps and Does Use Matter? A
Secondary Data Analytics Approach
Jennifer K Carroll1, MPH, MD; Anne Moorhead2, MSc, MA, MICR, CSci, FNutr (Public Health), PhD; Raymond
Bond3, PhD; William G LeBlanc1, PhD; Robert J Petrella4, MD, PhD, FCFP, FACSM; Kevin Fiscella5, MPH, MD
1Department of Family Medicine, University of Colorado, Aurora, CO, United States
2School of Communication, Ulster University, Newtownabbey, United Kingdom
3School of Computing & Maths, University of Ulster, Newtownabbey, United Kingdom
4Lawson Health Research Institute, Family Medicine, Kinesiology and Cardiology, Western University, London, ON, Canada
5Family Medicine, Public Health Sciences and Community Health, University of Rochester Medical Center, Rochester, NY, United States
Corresponding Author:
Jennifer K Carroll, MPH, MD
Department of Family Medicine
University of Colorado
Mail Stop F496
12631 E. 17th Ave
Aurora, CO, 80045
United States
Phone: 1 303 724 9232
Fax: 1 303 724 9747
Email: [email protected]
Abstract
Background: Mobile phone use and the adoption of healthy lifestyle software apps (“health apps”) are rapidly proliferating.
There is limited information on the users of health apps in terms of their social demographic and health characteristics, intentions
to change, and actual health behaviors.
Objective: The objectives of our study were to (1) to describe the sociodemographic characteristics associated with health app
use in a recent US nationally representative sample; (2) to assess the attitudinal and behavioral predictors of the use of health
apps for health promotion; and (3) to examine the association between the use of health-related apps and meeting the recommended
guidelines for fruit and vegetable intake and physical activity.
Methods: Data on users of mobile devices and health apps were analyzed from the National Cancer Institute’s 2015 Health
Information National Trends Survey (HINTS), which was designed to provide nationally representative estimates for health
information in the United States and is publicly available on the Internet. We used multivariable logistic regression models to
assess sociodemographic predictors of mobile device and health app use and examine the associations between app use, intentions
to change behavior, and actual behavioral change for fruit and vegetable consumption, physical activity, and weight loss.
Results: From the 3677 total HINTS respondents, older individuals (45-64 years, odds ratio, OR 0.56, 95% CI 0.47-68; 65+
years, OR 0.19, 95% CI 0.14-0.24), males (OR 0.80, 95% CI 0.66-0.94), and having degree (OR 2.83, 95% CI 2.18-3.70) or less
than high school education (OR 0.43, 95% CI 0.24-0.72) were all significantly associated with a reduced likelihood of having
adopted health apps. Similarly, both age and education were significant variables for predicting whether a person had adopted a
mobile device, especially if that person was a college graduate (OR 3.30). Ind.
2. this information. The data is transferred to a cloud-based data
repository and the children can instantly view and track their
overall progress. To maintain high engagement among pediatric
users, the app has integrated game mechanics and social media.
Users can “friend” other diabetic users and together, they
compete to earn special badges to highlight their
accomplishments. A key feature is to enables a user to Share
and Compare™ his or her results. In addition, the user is able to
comment on other users’ profiles.
Figure 1 - Screenshots of the application: data entry (check-in),
gaming, social networking
The pilot study began in September 2011, concluded in
December 2011, and was limited to the Android platform. Eight
users and their parents were recruited, with informed consent
and disclosures about how the data will be used in analyzing
trends and patterns of usage, from the Type 1 pediatric diabetes
population around Western Pennsylvania, ranging in age from
10 years to 18 years. The mobile application was provided free
of charge, with limited instructions about its use in order to
observe the degree of intuitiveness of the application. User data
was stored on a cloud-based server and downloaded for analysis
on a weekly basis. In particular, three specific types of data
were used to evaluate the effectiveness of the application:
Health metrics data – “Check-in” data came from users keeping
track of various pieces of health information over time. This
was logged as one of four types: Activity, Carbs, Insulin and
Glucose. The data type and its corresponding value (with
appropriate units -mg/dL, g, or number of hours), the user’s ID
and the date and time of check-in were also recorded.
Comments data – The application had a feature that allowed
users to add other users to a private network through which a
user could keep track of the health progress of his or her
friends. As a supplement to this feature, a user could comment
on a friend’s check-in data, depicted in a plot of the different
data types over time, to potentially motivate the friend to
improve adherence to self-management guidelines. The
application tracked users’ interactions with each other, number
of different check-in data points on which different users
interacted, and text of the actual comments exchanged. Click-
stream data – Logs were maintained of how users interacted
with the application over time, recording the features users
tended to utilize, how much time users spent using specific
features, and the time of day when specific features were used.
Methods
Figure 2 - Evaluation framework
We applied a three-pronged evaluation framework, as shown in
Figure 2 which has been used successfully in other domains [8].
Product evaluation assessed the usability and functionality of
the application via benchmarking and technology assessment.
The evaluation also utilized surveys and conducted an analysis
of the user comments to assess the application’s usability and
functionality expressed via these comments. The benchmark
analysis focused on the features of the product and how well
they were aligned with the requirements for diabetes self-
management, particularly with the needs of children. These
needs include but are not limited to: easy, direct and simple data
capture, results reporting, usability and friendliness, and peer
support. A user satisfaction survey was created based on
usability principles and tailored to pediatric patients to gauge
usability and user friendliness of the application, but could not
be executed due to privacy and logistical challenges.
Process evaluation mapped the current and desired process
models underlying the use of PHRQL and measured impact of
the application on the self-management habits of a user, while
also developing a "best-practice" use model for future users.
The process evaluation then compared user behaviors with best
practice models. This evaluation approach had two distinct
segments. The first was the creation of a best practice process
model for diabetes self-management. Drawing on national
standards and direct interviews with diabetes educators, the best
practice process model shows the optimal self-management
pathway with the highest potential for improvement in diabetes
management and health outcomes. The second component
analyzed how users in the pilot study were interacting with and
using the application via several different approaches such as
visualizing these interactions and analysis using Markov Chain
model and statistical summaries. Results from the analyses were
compared to best practice model to identify useful feedback and
suggestions to improve patient self-management habits.
Program evaluation assessed the overall value of the
application in controlling diabetes along two different
dimensions - user engagement and effectiveness at lowering
blood glucose variability. User data was aggregated and
analyzed to understand usage patterns, engagement, and
adherence to best practices. We analyzed click-stream data of
user interactions with the application, their documentations of
key metrics and sharing of this information with peers via social
networking and gaming using descriptive statistics, and
multidimensional scaling and annealing methods.
Results
Product Evaluation
Our benchmarking analysis showed that the app has robust data
capture and user engagement features, aligning well with the
target market (i.e. diabetic children) [7]. Data capture and
results reporting are simple and almost instantaneous. The Drag
and Drop™ data entry made it easier for users to register their
health information. In addition, the Share and Compare™
feature enabled users to track other users’ progress. Together,
these two features generated greater opportunities for user
engagement because it was easier to enter accurate data, and
compare with peer users. The analysis also showed that
discussions about functionality were limited, but health
information was exchanged frequently, and the comments were,
in fact, facilitating user engagement through peer support. Most
of the users utilized the comments feature to notify their friends
on what they ate, blood glucose level, mood, and the activities
they participated in, as shown in Figure 3. Overall, these
comments were exchanged regularly; it was clear that the users
wanted others to know of their progress and receive feedback,
R. Padman et al. / An Evaluation Framework and a Pilot Study of a Mobile Platform for Diabetes Self-Management334
3. so users actively used the application because they were
anticipating a response from one of their friends. This evidence
of peer support is encouraging given that studies have shown
that peer supported interventions can “improve patients’ health
behavior, metabolic control, and quality of life [4, 5].”
Figure 3 - Sample of comments exchanged by users
Process Evaluation
The goal of the process evaluation was to provide insights into
the impact of the application on the self-management process
for users and to show a potential positive impact on user’s
compliance with diabetes self-management standards. The
management of Type 1 diabetes on a daily basis varies based on
the type of insulin administered. Insulin therapy is classified
based on the duration of action into rapid acting, short acting,
and long acting insulin [3, 4]. Daily management of the disease
varies based on the patient (newly diagnosed vs. established
patient). Research has shown that newly diagnosed patients
tend to have blood glucose levels above 250mg/dl and are
therefore instructed to take an additional dose of insulin in the
night before sleeping which a normal patient can forgo [3, 4].
The process models were developed to incorporate these
standards along with insights from diabetes educators in order
to create a best practice standard against which to compare
users' actual interactions with the application. Figure 4 shows
the best practice process models for diabetes self-management
for a patient on fast/rapid acting insulin. The nodes in the model
were color coded for each type of check-in. Blue blocks
represent blood glucose check-ins. Green represents an insulin
check-in. Yellow denotes a carb check-in and a red block
indicates that an activity check-in has occurred. Additional
process models developed for the other types of insulin therapy
are summarized in [7].
Figure 4- Fast/Rapid acting insulin process model
Visualization of the user interaction data (Figure 5) through
check-ins (blood glucose, activity, carbs, and insulin) was
developed on the same scale of the best practice model i.e.
management of the disease over a day. Visualization of user’s
interactions with the app showed that patients were developing
consistent interaction habits and patterns with the application
toward the end of our study period, suggesting that check-in
frequency had stabilized. It was encouraging to observe that the
app usage had not decreased or ceased, and instead had become
an important part of the user’s self-management routine.
Figure 5- Sample user interaction process model
However, our analysis also showed that usage was not always
in accordance with best practices but there was evidence that
users were capturing important aspects of the clinical
management guideline, specifically their pre and post prandial
blood glucose levels. The process model (Figure 6) shows the
check-in data for all eight users for days 1, 10, 20 and 40 that
have been stacked on top of each other to create a single,
unified visualization. The x-axis depicts the hour of day when
the check-in occurred and y-axis indicates each user's check-in
with his/her own color code. We observed that from midnight to
6AM, user 5 (brown) has a number of check-in activities, and a
few by users 1, 6 and 8 as well. Over the rest of the day, users 1,
5 and 6 are consistent in checking in their data on all key
measures around breakfast, lunch and dinner hours, but the
remaining users have sporadic and limited data entry. These
techniques thus provided opportunities for gleaning insights
into the habits of users, such as clustering of check-in data
around meal times, and increasing check-in compliance rates
over time.
Figure 6- Process model depicting users' interactions with the
application
In addition to the data visualization techniques, a Markov Chain
analysis of the check-in data assessed navigational pathways
and popular check-in patterns for the application across all users
[9]. Figure 7 shows the transition probability matrix on a graph.
Each circle represents a distinct check-in type and the size of
the circle is relative to the frequency of its use. The arcs
represent the direction of the transition probability. For example
the probability that an Activity check-in is followed by a
Glucose check-in is 85%, while the probability that a Glucose
check-in follows an Activity check-in is 2%, and the probability
of a Carbs check-in following a Glucose check-in is 47%. Bold
arcs represent probabilities that are greater than 50%.
Transitions from one state to the same state, for example a
Glucose check in followed by another Glucose check-in, can be
R. Padman et al. / An Evaluation Framework and a Pilot Study of a Mobile Platform for Diabetes Self-Management 335
4. calculated by subtracting all the other transitional probabilities
for the initial check-in from 1.
Key:
Figure 7 - Graph of transition probability matrix
The initial probability distribution of states (Glucose, Activity,
Carbs, Insulin) for the first check-in is shown in Table 1 with
Glucose having the highest probability of being the first check-
in, and all other types with a low probability of occurrence. The
Markov model converged in 6 steps, likely due to the small
number of check-in states and the high frequency of Glucose
check-in. It should also be noted that the probability of activity
check-in fell significantly as the number of check-ins increased.
This suggests that the Activity check-in will mostly likely be
used early on or it will not be used at all. Finally, once steady
state was reached, we observed that the probability of having a
Carbs or Insulin check-in is about the same, shown in Table 2.
Table 1 - Initial probability vector
Table 2 - Markov chain probabilities
The Markov Chain analysis was also used to identify high
frequency check-in patterns [7]. The most popular sequential
feature combination was Glucose, Carbs, Insulin, Glucose
(GCIG) pattern. This is not the optimal sequence identified in
the best practices process model which was GICG pattern, but it
does show that patients are capturing their pre- and post-
prandial Blood Glucose levels which are vital for successful
diabetes self-management.
Program Evaluation
The program evaluation is intended to measure how successful
the application is in enabling its users to better manage their
diabetes, by looking at both the engagement of its users and the
effectiveness of the application in improving health outcomes.
We measured engagement by investigating utilization patterns
of the different features over a period of time. Effectiveness was
measured by observing variability and trends in health metrics
checked in over a period of time, with special attention given to
users’ blood glucose levels. From the various analyses
conducted, it was evident that the application is very robust in
collecting different types of data ranging from health metrics to
social interactions and user activity.
Health Metrics
In order to get a better sense of user engagement with the
application, the health metrics data was analyzed. The study
observed the total number check-ins per day and per hour
within a day across all users to identify patterns in check-in
activity with blood glucose, insulin, carbohydrates, and activity
measurements. Adherence to best practice check-in times was
studied in the process evaluation. The frequency of check-ins
by users over the course of the study was explored to see
whether there was a significant increase or decrease in the user
engagement with the application. Figure 8 indicates steady use.
Figure 8-User Engagement over the study period
To analyze the effectiveness of the app, summary statistics with
variance in the four different types of check-ins measured
consistency in the values each user entered, implying that
greater variability suggested less successful diabetes
management. Time series modeling of users' blood glucose
levels over the span of the study tested correlation of blood
glucose variability with check-in data aggregated by day,
month, and time period. Given the study's limited duration and
number of participants, a statistically significant conclusion
could not be reached, but positive trends were observed.
Comments Data
The comments data indicated which users interacted with each
other and their usage frequency of the Share and Compare™
feature. A graphical depiction of the structure of the social
network used two methods: multi-dimensional scaling (MDS)
which shows users with similar features (i.e., the number of
connections) in closer proximity with each other, and annealing
which optimized the shortest path between all nodes and
ultimately put nodes with the most connections at the center [8].
Connections between the nodes were weighted based on the
number of interactions between each node to signify how
strongly each pair of nodes was related.
Figure 9-Social network using annealing at mid-point of study
Glucose Activity Carbs Insulin
R. Padman et al. / An Evaluation Framework and a Pilot Study of a Mobile Platform for Diabetes Self-Management336
5. Figure 9, with 2-4 connections per user node, all nodes within
reasonable proximity of each other, and users 37 and 42 as most
connected, illustrates the network based on user comments from
the initial half of the study period. Figure 10, with 3-5
connections per node and user 38 as the most connected at the
center by the end of the study, depicts the major changes in the
interactions amongst the users over a short duration. This
analysis captured which users were most connected to others as
well as users who were most active in utilizing the commenting
feature. Both of these criteria can be compared to health metrics
data in order to measure the effectiveness of social networking
in promoting adherence to the program. However, due to
limited data, this comparison did not produce useful insights.
Figure 10-Social network using annealing at end of the study
A qualitative analysis of user comments was conducted to
observe the number of different words, word frequency and
occurrence, sentence length, complexity, and readability of the
comment text. 180 different words that included 'good', 'high',
'low', and 'A1c' provide some indications of the content of the
exchanges. This qualitative analysis provided a better idea of
how effective different types of relationships and messages
were in encouraging users to adhere to the application.
Click-stream Data
Finally, click-stream data was used to tabulate how often the
different subsets of all application features were used in a given
time period (see Figure 11 for user 38). This type of analysis is
useful for identifying application features that correlate with
successful diabetes self-management. In addition, utilization
patterns of application features can help determine the features
that should be enhanced in future developments. Information
garnered from this analysis can also be used to understand if
users were adhering to best practices for entering health metrics
data and if features like commenting or gaming mechanisms
were contributing to increased user engagement.
Figure 11- Feature usage breakdown for user 38
Conclusions
This study evaluated a mobile health app along three
dimensions – product, process, and program. Product evaluation
examined the functionality and usability of the app and
compared it with other similar applications in the market. This
evaluation identified game mechanics and social media features
as key factors driving user engagement. Process evaluation
examined the impact of the app on users’ diabetes self-
management habits, detecting high variability in users'
interactions with the application and a lack of compliance with
best practices but a reassuring trend towards better self-
management habits over the duration of the study. Program
evaluation conducted data analytics on different types of log
data to understand the overall value of the app in controlling
diabetes and engaging users. Due to the limited number of study
participants, program evaluation could not conclusively
demonstrate that app usage decreased users' blood glucose
levels. However, positive trends were observed in user
engagement and blood glucose variability and increased
satisfaction with diabetes management. Ongoing studies with a
larger user population will use this framework to draw
actionable insights about the use of mobile health as an
intervention and self-management tool with pediatric as well as
adult users. Privacy and security issues, particularly important
in the pediatric setting, also need to be addressed using a
consistent and comprehensive approach.
Acknowledgements
We are grateful to the entire PHRQL team for the opportunity
to study this innovative platform.
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Address for correspondence:
Rema Padman, The H. John Heinz III College, Carnegie Mellon
University, Pittsburgh, PA 15213, USA, Email: rpadman@cmu.edu
R. Padman et al. / An Evaluation Framework and a Pilot Study of a Mobile Platform for Diabetes Self-Management 337