Research

Investigating the role of digital mHealth technologies for assistance in diabetes self-management

Overview

For over 30 years, mobile digital devices, in the form of portable blood glucose monitoring systems, have assisted diabetics in living healthier, more fulfilling lives.  Today, new consumer technologies such as mobile computing, sensors, big data, social networking, and location services are being widely and rapidly adopted. These tools have the potential to bring about new methods of personalized, contextualized health care services. I would like to study how the adoption of digital technology is changing the ways people self-manage diabetes; how users relate to these products; and if users are finding increased motivation and improvements in quality of life.

mHealth

mHealth can be defined as the use of mobile devices in supporting public and individual health care. Some potential applications of mHealth include education, remote diagnosis, mapping of health issues, patient data collection, remote monitoring of patients, and networking of health care workers. [http://mhealthalliance.org/about/faq]

Devices can include tablets, laptops, or specialized devices, but do the affordability and prevalence of the mobile phone, this has become and especially interesting device for establishing mHealth services. Cellphones, and more recently smartphones, have rapidly become an established part of life for much of the world’s population. Currently, there are an estimated 1 billion smartphone users worldwide; this number is expected to double by 2015. [1]

Smartphone users have in their pockets a powerful sensor-enhanced computer that connects seamlessly to the entire knowledge base of the Internet, communicates using diverse modalities, and knows precisely where on the planet they are located, all at a relatively affordable cost.  The smartphone and related technologies make technically possible a world where more and more of our objects are network capable, share sensor based information and are remotely accessible.

The interest and investment in mHealth is being driven by the spread of these devices combined with factors such as overstressed medical systems, aging populations, rising health care costs, expanding global health databases, and potentially scalable, contextually-aware medical support.

 mHealth has already proven itself to be effective for certain uses. Positive results have been achieved using SMS reminders for medication adherence, telemedicine in locations with insufficient medical resources, and HIV education. [2]

One booming area in mHealth is the development of smartphone apps, with thousands to choose from. Many are focused on chronic health maintenance issues such as weight loss, exercise, and medication tracking, while others interface directly with medical devices.  Despite the potential medical usage of apps, the U.S. Food and Drug Administration has stated that it will not regulate the majority of these products. [3] Exempt from regulation are apps that help with self-management without giving specific medical advice; offer ways to track data and log data; give access to standard health information; or allow interaction with health record systems.

Lack of government regulation will certainly encourage the development of many more medical apps in addition to the thousands that are now freely distributed without medical approval.  There are enormously more apps in release than there are clinical studies to measure their effectiveness. [4] One study noted that the majority of the diabetes-related apps did not follow standard evidence-based priorities in diabetes care. [5] Privacy issues and the expense of clinical trials make testing difficult and expensive. In effect, the user has taken on the role of unregulated tester, sidestepping the carefully monitored trials used with medications and medical devices. [4]

 

Diabetes as a case study

Diabetes management is one of the biggest sectors in world health, in both human and financial costs. In 2012, approximately 370 million people worldwide were believed to have diabetes, with 4.8 million diabetes-related deaths. [6] This figure is predicted to grow dramatically in the next 20 years. Diabetes can usually be managed, and the long-term complications mitigated, through a combination of medication, diet, and exercise. However, for various reasons, ideal management of the condition is both extremely challenging and discouraging for many individuals. Long-term elevation of blood sugar can lead to serious complications such as impaired kidney function, nerve damage, decreased vision, and amputation of limbs.

Current methods of diabetes management

There are two common types of diabetes: type 1, in which individuals do not produce insulin, and type 2, in which individuals either do not produce sufficient insulin or are unable to properly use the insulin they produce. It is estimated that more than 90% of diabetics have the type 2 form of the disease. Core treatment for both types is the same: management of blood glucose levels through exercise, careful attention to diet, and correct use of prescribed medication.

For type 1 diabetics, who are always insulin-dependent, proper control of blood glucose levels depends on taking multiple blood glucose measurements per day, plus carefully balancing caloric intake with insulin dosage and caloric expenditure.

Type 2 diabetes is often, but not always, lifestyle-related, and thus treatment often involves lifestyle changes such as weight loss, regular exercise, and careful attention to diet, sometimes in combination with oral medication. Type 2 usually affects adults, many find it difficult to change long-term lifestyle patterns. In many cases, insulin therapy will be required as the condition progresses. [7]

Patient adherence to recommended best practices is highly variable, with some estimates as low as 50%. [8].  Even defining diabetes adherence is difficult, since many individuals do better in certain areas than others, for example taking recommended medication while not following their doctor’s recommendations on exercise. [8] One approach to adherence is to embrace the idea that the patient must take central responsibility for disease management, and that self-management is a fluid system based on context. In this model, the relationship between doctor and patient should be viewed as cooperative not paternalistic, and the treatment regime must be based on the goals and realistic abilities of each individual. [9]

 

Current uses of digital technology in diabetes self-management

 Diabetics were early adopters of consumer-focused digital technology, with the portable blood glucose meter becoming a standard tool for self-management more than 25 years ago. The resulting ability to obtain accurate and near-instant blood sugar measurements allows diabetics to fluidly adjust insulin dosages, caloric intake, and exercise, rather than attempting to follow an inflexible medication schedule.

With the rise of the smartphone, literally hundreds of apps are now available to assist diabetics in a multitude of aspects of self-management. Popular approaches include digital logbooks, dietary trackers, dosage calculators, social networking, gamification, and education. With advances in contextual computing, sensors, and other mobile technologies, there will certainly be more diabetes-specific technology and apps.

Qualitative and quantitative studies as to how effective these systems truly are, and for whom, are lagging behind the introduction of new products. [4] Some studies have shown modest but significant results with mobile phone-based intervention. [10]

A study on the Few Touch simplified digital logging system found a motivational effect. [11].  The developers of the Bant app showed increases in blood testing frequency in juvenile diabetics, which is known to be associated with improved health maintenance [12].

One interesting new product is the Esysta system from Emperra. This system includes a wireless transmitting insulin injection pen and blood glucose meter.  Both automatically interface with a base station, which uses a SIM card to share data with a centralized server.  This system also includes an app to ease information access.  In this way caregivers and individual can seamlessly review progress. Many studies have found that self-reported blood sugar measurement and dosage logs are often inaccurate, although one study using meters where the subjects knew that all readings were recorded found reasonable accuracy. [13]. Replacement of human measurement with continual automatic measurement systems holds the potential for access to higher-quality data by patients and care providers alike. [9].

Several continuous glucose-monitoring systems are already on the market. Current consumer products, such as the Dexcom G4, do not measure blood glucose directly, but rather interstitial fluid, creating a lag time between readings and actual blood glucose levels, and accuracy is far below direct blood sugar readings. [14] This device is not approved for determining insulin dosages, but instead is marketed as a supplemental warning for hypo- or hyperglycemia. [14] Despite these shortcomings, it would be potentially useful to gather more information on how diabetics feel about incorporating these products into their daily lives.

Future potential developments in digital technology

 Products on the horizon include systems capable of true continuous glucose monitoring [CGM], smarter software that can assimilate various sensor data to offer improved real-time advice in blood glucose management, and ultimately, an artificial pancreas that automatically delivers insulin or glucose as needed.

The role of motivation in diabetes self-management

 Due to the tremendous worldwide increase in the prevalence of diabetes, as well as the associated financial burdens, diabetes care will continue to attract major investment in new products. However, the solution to the diabetes epidemic is not just in technology. These new tools have a big role to play, but they must be integrated with the demands and  inconsistencies of a huge and varied population. In order to maximize their utility, we must understand how, and even whether, different individuals are using them successfully.

Even if technology can ensure that diabetics receive ideal medication dosages, a proper balance of diet and exercise will still be essential their for long-term health. Diabetes care is a complicated regime, requiring constant effort and commitment.  Many diabetics are more successful in certain areas than in others, and the process of self-management requires continuous attention to balancing needs. [9]

 The collection of data alone does not in itself lead to better outcomes, it is the ability to analyze this data, and make then make informed choices in daily life that lead to improved self-management. Individuals who lose motivation and become discouraged have much more difficulty in following the steps necessary for optimal control. [15]

 Proposal for Project

 The front end of the project will be a publicly accessible technology review website featuring reviews of digital products and tools that could potentially aid diabetics in self-management. Of particular interest will be products that allow the sharing of information between devices; various sensors; databanks that encourage the dissemination of advice and self-help; social networking systems; and new technologies.

The site will also include information on the role of digital technology in aiding diabetes self-management, with links to pertinent articles, clinical studies, and other evidence-based information.

Content will focus on daily and long-term relationships between the user and these new technologies: how are these new products helping people meet their goals, and in what ways are they being used in daily health maintenance?  For example, how do users feel about their daily measurements being automatically shared with care providers? Does this motivate or discourage personal responsibility? Is CGM associated with people feeling more in control of their condition, or overburdened with data?

Method of research

 The second part of the site will feature a set of questionnaires and diaries that can only be accessed by login. This section will seek to gather and correlate information about people’s experiences and results with diabetes management products they are using and testing on a daily basis. The focus will be on usability issues and on attempting to ascertain how these technologies influence the ways that people relate to their own self-management practices. The site will be designed to gather information not just about technical function, but rather focusing on quality of life, motivational impact and other human factors.

Product testers will be recruited through the website, diabetes clinics, and diabetic meeting groups. Ideally they will represent a variety of social, economic, and cultural backgrounds. Particular emphasis will be placed on recruiting people who are not early technology adopters. Since many older diabetics have vision impairment, it might be useful to investigate which apps are most readable with different degrees of retinopathy. The best app is of no use to the older individual who cannot read the interface.

Goal of project

 The goal of this project is to facilitate understanding of how, and even whether, digital technologies are assisting diabetics with their self-management goals.  The NIH notes that the enormous number of apps and new products currently being introduced is far outpacing the ability of the medical establishment to test the effectiveness of these products. They state that on researchers will have to study the full aspects of these technologies in order to implement useful solutions. [4]

The website will aim to create an active community of contributors and reviewers who will have the opportunity to test many products and see how they work in different combinations and over extended periods. Hopefully we can find out which products motivate users over extended periods, and why. While this method will not have the rigor of a clinical study, it might allow more agility.  If the site could establish over time a large group of user, the collected data could help to understand more details about which technologies are useful for which populations and personality types, and how these devices are effectively implemented.

 Steps and Milestones for Program of Study

  • Conduct literature review of existing studies on the effectiveness of diabetes related technology.
  • Interviews with diabetics in various socio-economic groups as to their current use of digital products and interest in trying new products.
  • Conduct research to determine which products should be further investigated.
  • Set up website/blog, with information about these products.
  • Recruit and distribute questionnaire to potential study participants about their experiences with chosen product.
  • Conduct follow-up qualitative interviews.
  • Tally results and analyze data.
  • Write up final results.

 

Summary

The development of effective diabetes self-management tools will require a multidisciplinary approach. Product development should take into account usability issues, such as vision impairment and the limited computer experience of many older users. Products should be based on solid medical evidence and a thorough knowledge of diabetes care. It is possible, and highly likely, that there is not a single ideal solution for all users.  All of this requires study and investigation.

 

The use of apps and other digital technologies to assist in health management is still in its infancy. New advances in sensor systems, such as continuous glucose monitoring, and new forms of wearable computing, such as smart watches and headsets, will most likely lead to tremendous growth in the use of mobile computing for health management.  One can easily imagine an implanted glucose monitoring system, continuously sending data to a watch, which then notifies the user whenever blood sugar is out of normal boundary, or directly interfacing with an insulin pump.

 

mHealth is providing new tools and tactics for health management, but technology is not a magic bullet. It must be integrated into a social dynamic, be sensitive to the needs and goals of users, and support them in their efforts.

 

Human Centered Computing, which combines computer system design, psychology, and real world testing, seems to be an ideal realm in which to research and suggest solutions to this critical issue.  I am hopeful that through this project, and with further study, I can contribute to finding new ways of addressing public health needs and participate in implementing these new technologies.

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References

 

  1. Yang, J. Smartphones in Use Surpass 1 Billion, Will Double by 2015, Bloomberg Technology. Retrieved December 20, 2013, from Bloomberg: http://www.bloomberg.com/news/2012-10-17/smartphones-in-use-surpass-1-billion-will-double-by-2015.html

 

  1. Kamel Boulos, M., Wheeler, S., Tavares, C., Jones, R. How smartphones are changing the face of mobile and participatory healthcare: an overview, with example from eCAALYX. BioMedicalEngineering OnLine. 10. Retrieved December 20, 2013, from BioMedicalEngineering OnLine:

http://www.biomedical-engineering-online.com/content/10/1/24

 

  1. Mobile Medical Applications Guidance for Industry and Food and Drug Aministration Staff, Issued on September 25, 2013. Retrieved December 20, 2013, from the FDA:

http://www.fda.gov/downloads/MedicalDevices/DeviceRegulationandGuidance/GuidanceDocuments/UCM263366.pdf

 

4.   mHealth – Mobile Health Technologies. Retrieved December 20, 2013, from the National Institutes of Health:

http://obssr.od.nih.gov/scientific_areas/methodology/mhealth/

 

5.   Chomutare, T., Fernandez-Luque, L., Årsand, E. and Hartvigsen, G. Features of mobile diabetes applications: review of the literature and analysis of current applications compared against evidence-based guidelines. Journal of Medical Internet Research, 13 (3).  Retrieved October 24, 2013 from the Journal of Medical Internet Research:

http://www.jmir.org/2011/3/e65/

 

6.  IDF Diabetes Atlas, Fifth Edition 2012. Retrieved October 24, 2013 from the International Diabetes Foundation:

http://www.idf.org/diabetesatlas

 

  1. National Diabetes Fact Sheet, 2011. Retrieved October 24, 2013 from the International Diabetes Foundation: http://www.cdc.gov/diabetes/pubs/pdf/ndfs_2011.pdf

 

8.   Delamater, A. Improving Patient Adherence. Clinical Diabetes, 24 (2). 71-77. Retrieved December 20, 2013, from Clinical Diabetes:

http://clinical.diabetesjournals.org/content/24/2/71.full

 

9.  McNabb, W. Adherence in Diabetes: Can We Define It and Can We Measure It? Diabetes Care, 20 (2). 215-218. Retrieved November 24, 2013 from the Diabetes Care:

http://care.diabetesjournals.org/content/20/2/215.full.pdf

 

10.  Pal, K., Eastwood, S.V., Michie, S., Farmer, A.J., Barnard, M.L., Peacock, R., Wood, B., et al.  Computer-based diabetes self-management interventions for adults with type 2 diabetes mellitus. PubMed. Retrieved October 24, 2013 from the National Center of Biotechnology Information:

http://www.ncbi.nlm.nih.gov/pubmed/23543567

 

11.   Arsand, E., Tatara, N., Østengen, G. and Hartvigsen, G. Mobile phone-based self-management tools for type 2 diabetes: the few touch application. Journal of Diabetes Science and Technology, 4 (2). 328. Retrieved October 24, 2013 from the National Center of Biotechnology:

http://www.ncbi.nlm.nih.gov/pmc/articles/PMC2864168/pdf/dst-04-0328.pdf

 

12.   Cafazzo, J., et al. Design of an mHealth App for the Self-management of Adolescent Type 1 Diabetes: A Pilot Study. Journal of Medical Internet Research, 14 (3).  Retrieved November 24, 2013 from the Journal of Medical Internet Research:

http://www.jmir.org/2012/3/e70/

 

13.   Gonder-Frederick, L. et al. Self-Measurement of Blood Glucose

Accuracy of Self-Reported Data and Adherence to Recommended Regimen.

Diabetes Care, 11 (7). 579-585. Retrieved November 24, 2013 from the Diabetes Care:

http://care.diabetesjournals.org/content/11/7/579.full.pdf

 

14.   Summary of Safety and Effectiveness Data (SSED) October 5, 2012. Retrieved December 20, 2013, from the FDA:

http://www.accessdata.fda.gov/cdrh_docs/pdf12/P120005b.pdf

 

15.   Mamykina, L., Mynatt, E., and Kaufman, D. 2006. Investigating health management practices of individuals with diabetes.  In Proceedings of the SIGCHI Conference on Human Factors in Computing Systems (CHI ’06), 927-936.

http://doi.acm.org/10.1145/1124772.1124910

 

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