A Meta-Analysis of Mobile Health and Risk Reduction in Patients with Diabetes Mellitus: Challenge and Opportunity

Purpose: To examine scientific evidence on the effectiveness of mobile phone technology in Diabetes Mellitus (DM) care management.

Methods: A systematic review was conducted through literature searches from three electronic databases and was restricted to English-language articles published between January 2002 and March 2012. Studies that used mobile phone intervention and reported changes in diet, physical activity, and blood glucose and /or glycosylated hemoglobin (HbA1c) levels were retrieved. A meta-analysis was conducted for studies with HbA1c measures.

Results: More than 50 articles were screened. Of them, 15 met the review criteria. Of the 15, study sample sizes ranged from 12 to 130 participants aged 8 to 70 years old. Duration of intervention ranged from 1 to 12 months. Overall, significant improvements were observed in blood glucose and/or HbA1c concentration, adherence to medication, healthy lifestyle, and self-efficacy. Twelve of 15 trials, which had serum HbA1c measures, showed an average 0.39% (95%CI: -0.067, -0.721) HbA1c reduction from studies with pre- to post-tests (p=0.018).

Conclusion: Findings from the study provide the evidence that health reminders, disease monitoring and management, and education through mobile phone technology may significantly help improve glycaemic control patients with DM.

Maintaining health lifestyle in patients with DM is fundamental to their health status and welfare. Mobile phone technology may be essential in interventions that target behavioral and lifestyle changes, particularly, those associated with chronic diseases management. Our study reviewed fifteen studies that assessed the effect of mobile phone interventions on the self monitoring and management of DM provides evidence that there is a significant effect on DM management using mobile technique. This result is consistent with existing literature <sup>17-1917. Kim HS and Jeong HS. A nurse short message service by cellular phone in type-2 diabetic patients for six months. J. Clin. Nurs. 2007;16,(6):1082-1087.
18. Kim CS, Park SY, Kang JG, Lee SJ, Ihm SH, Choi MG and Yoo HJ. Insulin dose titration system in diabetes patients using a short messaging service automatically produced by a knowledge matrix. Diabetes Technol. Ther. 2010;12,(8):663-669.
19. Yoon KH and Kim HS. A short message service by cellular phone in type 2 diabetic patients for 12 months. Diabetes Res. Clin. Pract. 2008;79,(2):256-261.</sup>.

The main contribution of the present review provides the most recent evidence of mHealth studies, and the findings are based on studies from different countries. Among the reviewed studies, most applied randomized controlled designs, which enhanced the comparability of the outcomes. Also, most studies applied quantitative measures of key outcomes, including HbA1c, weight loss and serum glucose concentration measurement.

Despite the strengths of mobile phone technology use, several potential limitations should be kept in mind when interpreting these results. First, although findings from the reviewed studies showed promise in mobile phone use and improvement of DM management, some of these studies had small sample sizes. Therefore, future studies that utilize large sample size are needed to determine whether the increased patient-providers’ communication via mHealth have significant impacts on clinical outcomes and public health. Secondly, it is unknown what kind of modalities of mobile technology (SMS, mobile phone calls, application, etc) play a better role in improving outcomes in patients with DM. Thirdly, since most studies had a short period of intervention, the long-term effects of mHealth are still unclear. Fourthly, the current review paper is done by the authors in searching for the relevant literatures. We may have missed some papers during the search. If any, it will cause potential selection bias. Further studies should be continued to confirm the findings. Lastly, as with all systematic reviews, the present study is subject to publication bias ^{31Cole-Lewis H and Kershaw T. Text messaging as a tool for behavior change in disease prevention and management. Epidemiol. Rev. 2010;32,(1):56-69.}.

It should be noted that our present study aims to review the studies in the last decade and to evaluate the feasibility of using mobile phone technology to promote patients’ DM management and improve healthy lifestyle. It is clear that although mHealth techniques may offer new opportunities in disease control, we still face several challenges. First, the application of mHealth is a new approach in real-world practice. Most studies are still in the exploratory stages. Therefore, it is essential to find the link between practice and scientific knowledge, which come from studies with vigorous study designs and a large-scale sample size. Secondly, continuous adherence and compliance to mobile phone technology in DM management is crucial to the outcomes. The mobile phone use intervention relies heavily on behavioral change theory. In other words, the innovation is based on a patient’s willingness to fully participate in every aspect of the intervention. Thus, the intervention may not be suitable for all patients with DM, such as those who may have difficulties operate smart phone. Several studies observed that some patients withdrew from an intervention study due to the inconvenience of using the assigned mobile phones on a regular day-to-day basis. Therefore, findings observed in most studies are based on participants who may be highly motivated ^{1Atienza AA and Patrick K. Mobile health: the killer app for cyberinfrastructure and consumer health. Am. J. Prev. Med. 2011;40,(5 Suppl 2):S151-3.}. Thirdly, mobile phone technology raises important questions about how to protect patients with DM while simultaneously promoting its development and implementation ^{1Atienza AA and Patrick K. Mobile health: the killer app for cyberinfrastructure and consumer health. Am. J. Prev. Med. 2011;40,(5 Suppl 2):S151-3.}. This includes challenges associated with privacy and confidentiality of information collected and stored by mobile devices and/or transmitted to cyber infrastructure databases. For notification and intervention purposes, additional privacy and confidentiality concerns arise when sending health-related data to mobile devices ^{32Kang BS and Ko IY. Effective route maintenance and restoration schemes in mobile ad hoc networks. Sensors (Basel) 2010;10,(1):808-821.}. For example, interventions can be interrupted and privacy may be breached if the mobile phone is lost or stolen. However, similar limitations are present with other communication modes (e.g., postal mail or emails may be delivered to the wrong address) ^{31Cole-Lewis H and Kershaw T. Text messaging as a tool for behavior change in disease prevention and management. Epidemiol. Rev. 2010;32,(1):56-69.}. It is important to ensure that information gathered and transmitted via mobile devices remains secure ^{1Atienza AA and Patrick K. Mobile health: the killer app for cyberinfrastructure and consumer health. Am. J. Prev. Med. 2011;40,(5 Suppl 2):S151-3.}. Fourthly, although mobile phone technology promises unprecedented opportunities to reach DM patients anytime and anywhere, mHealth interventions may result in the marginalization of certain populations, such as illiterates or those without access to a mobile phone ^{31Cole-Lewis H and Kershaw T. Text messaging as a tool for behavior change in disease prevention and management. Epidemiol. Rev. 2010;32,(1):56-69.}. These drawbacks may greatly affect the impact of such interventions in such population. In the United States, mobile handset ownership differs among different ethnic groups and access is lower among those with lower socioeconomic status (defined as those with less than a high school graduate). Similarly, evidence points to disparity between younger and older patients ^{1Atienza AA and Patrick K. Mobile health: the killer app for cyberinfrastructure and consumer health. Am. J. Prev. Med. 2011;40,(5 Suppl 2):S151-3.}. Possible explanations for this disparity might be related to age, urban and rural, and economy; although neither of these reasons has been definitively determined. Fifthly, mobile phones and Internet technology are advancing rapidly and are ubiquitously available worldwide ^{16Liang X, Wang Q, Yang X, Cao J, Chen J, Mo X, Huang J, Wang L and Gu D. Effect of mobile phone intervention for diabetes on glycaemic control: a meta-analysis. Diabet. Med. 2011;28,(4):455-463.}. However, the costs to participants and healthcare providers are still difficult to estimate. Moreover, the question remains as to who will be responsible for covering the attributable costs of this innovation in the real world. Unfortunately, only three studies ^{24Rami B, Popow C, Horn W, Waldhoer T and Schober E. Telemedical support to improve glycemic control in adolescents with type 1 diabetes mellitus. Eur. J. Pediatr. 2006;165,(10):701-705., 28Franklin VL, Waller A, Pagliari C and Greene SA. A randomized controlled trial of Sweet Talk, a text-messaging system to support young people with diabetes. Diabet. Med. 2006;23,(12):1332-1338., 30Rossi MC, Nicolucci A, Di Bartolo P, Bruttomesso D, Girelli A, Ampudia FJ, Kerr D, Ceriello A, Mayor Cde L, Pellegrini F, Horwitz D and Vespasiani G. Diabetes Interactive Diary: a new telemedicine system enabling flexible diet and insulin therapy while improving quality of life: an open-label, international, multicenter, randomized study. Diabetes Care 2010;33,(1):109-115.} in this review had cost/benefit analysis information, in which they reported that self-monitoring and management of diabetes via mobile phone technology would be cost-effective at approximately €4/month, 2 pence/text, and €1.4/month respectively. Nevertheless, the applicability of mobile technology in low resources settings is still questionable in terms of its overall cost (phone, internet and operation). Furthermore, patients with DM are disproportionately distributed in those with low socioeconomic status. The application of mobile technology calls for healthcare system and health policy reforms to meet an urgent need of an increasing trend of DM in the United States and worldwide^{13Liu L. Social connections, diabetes mellitus, and risk of mortality among white and African-American adults aged 70 and older: an eight-year follow-up study. Ann. Epidemiol. 2011;21,(1):26-33., 15L. Liu, X. Yin, S. Morrissey. Global variability in diabetes mellitus and its association with body weight and primary healthcare support in 49 low- and middle-income developing countries: http://onlinelibrary.wiley.com/doi/10.1111/j.1464-5491.2011.03549.x/abstract (Accessed on 12/06, 2011)., 33Kabadi SM, Lee BK and Liu L. Joint Effects of Obesity and Vitamin D Insufficiency on Insulin Resistance and Type 2 Diabetes: Results from the NHANES 2001-2006. Diabetes Care 2012, Epub ahead of print., 34Liu L and Nunez AE. Cardiometabolic syndrome and its association with education, smoking, diet, physical activity, and social support: findings from the Pennsylvania 2007 BRFSS Survey. J. Clin. Hypertens. (Greenwich) 2010;12,(7):556-564.}.

Conclusion

The results from the present study indicate significant improvements in gylcaemic control and self-management with mobile phone intervention methods for DM care. Most reviewed studies demonstrated the promise of mHealth to aid patients and to reduce HbA1c by the use of mobile phone technology.  Further research with a longer duration and larger sample size is needed to examine several key issues including the benefits of mHealth interventions for patients and healthcare providers’ perceptions, and how mHealth integrating appropriately into healthcare practice, and the cost effectiveness of intervention in improving self-management in patents with diabetes.

Acknowledgements

No conflict of interest to report.Authors’ contribution: Longjian Liu, MD, PhD, MSc, contributed to the study design, analysis approach, reviewed, edited and finalized the manuscript. Stella-Maris Ogwu, MPH, participated in the study design, contributed to data collection, analysis and drafted the manuscript when she took the Opening Doors Health Disparities Training Program (February – June, 2012), supervised by Dr. L Liu, at Drexel University School of Public Health. Stella-Maris Ogwu was supported by a grant from the National Institute of Health for the Opening Doors Health Disparities Training Program at Drexel University School of Public Health (NIH Grant # R25 MD006792-01). The present study was presented in abstract form (poster) by SM Ogwu and L Liu at 2012 Public Health Poster Session of the College of Physicians of Philadelphia (May 16).

References

1.   Atienza AA and Patrick K. Mobile health: the killer app for cyberinfrastructure and consumer health. Am. J. Prev. Med. 2011;40,(5 Suppl 2):S151-3. 

2.   Blumberg SJ, Luke JV, Ganesh N, Davern ME, Boudreaux MH and Soderberg K. Wireless substitution: state-level estimates from the National Health Interview Survey, January 2007-June 2010. Natl. Health. Stat. Report 2011;(39),(39):1-26, 28.

3.   International Telecommunication Union. World Telecommunication/ICT Development Report 2010: Monitoring the Wsis targets – A mid-term review: http://www.uis.unesco.org/Communication/Documents/WTDR2010_e.pdf (Accessed on May 16, 2012).

4.   Blake H. Mobile phone technology in chronic disease management. Nurs. Stand. 2008;23,(12):43-46.

5.   Wang DH, Kogashiwa M and Kira S. Development of a new instrument for evaluating individuals’ dietary intakes. J. Am. Diet. Assoc. 2006;106,(10):1588-1593. 

6.   Kubota A, Fujita M and Hatano Y. Development and effects of a health promotion program utilizing the mail function of mobile phones. Nihon Koshu Eisei Zasshi. 2004;51,(10):862-873.

7.   Hurling R, Catt M, Boni MD, Fairley BW, Hurst T, Murray P, Richardson A and Sodhi JS. Using internet and mobile phone technology to deliver an automated physical activity program: randomized controlled trial. J. Med. Internet Res. 2007;9,(2):e7. 

8.   Consolvo, S., Everitt, K., Smith, I., & Landay, J. A. Design requirements for technologies that  encourage physical activity: http://dub.washington.edu/djangosite/media/papers/paper0552-consolvo.pdf  (Accessed on May 16, 2012).

9.   Britto MT, Munafo JK, Schoettker PJ, Vockell AL, Wimberg JA and Yi MS. Pilot and feasibility test of adolescent-controlled text messaging reminders. Clin. Pediatr. (Phila) 2012;51,(2):114-121. 

10. Anhoj J and Moldrup C. Feasibility of collecting diary data from asthma patients through mobile phones and SMS (short message service): response rate analysis and focus group evaluation from a pilot study. J. Med. Internet Res. 2004;6,(4):e42. 

11. Faridi Z, Liberti L, Shuval K, Northrup V, Ali A and Katz DL. Evaluating the impact of mobile telephone technology on type 2 diabetic patients’ self-management: the NICHE pilot study. J. Eval. Clin. Pract. 2008;14,(3):465-469. 

12. Vahatalo, M. A, Virtamo, H. E., Viikari, J. S., and Ronnemaa, T. Cellular phone transferred self-blood glucose  monitoring: prerequisites for positive outcome. Practical Diabetes International 2004;21,(5):192-194. 

13. Liu L. Social connections, diabetes mellitus, and risk of mortality among white and African-American adults aged 70 and older: an eight-year follow-up study. Ann. Epidemiol. 2011;21,(1):26-33. 

14. Liu L. Changes in cardiovascular hospitalization and comorbidity of heart failure in the United States: findings from the National Hospital Discharge Surveys 1980-2006. Int. J. Cardiol. 2011;149,(1):39-45. 

15. L. Liu, X. Yin, S. Morrissey. Global variability in diabetes mellitus and its association with body weight and primary healthcare support in 49 low- and middle-income developing countries: http://onlinelibrary.wiley.com/doi/10.1111/j.1464-5491.2011.03549.x/abstract (Accessed on 12/06, 2011).

16. Liang X, Wang Q, Yang X, Cao J, Chen J, Mo X, Huang J, Wang L and Gu D. Effect of mobile phone intervention for diabetes on glycaemic control: a meta-analysis. Diabet. Med. 2011;28,(4):455-463. 

17. Kim HS and Jeong HS. A nurse short message service by cellular phone in type-2 diabetic patients for six months. J. Clin. Nurs. 2007;16,(6):1082-1087. 

18. Kim CS, Park SY, Kang JG, Lee SJ, Ihm SH, Choi MG and Yoo HJ. Insulin dose titration system in diabetes patients using a short messaging service automatically produced by a knowledge matrix. Diabetes Technol. Ther. 2010;12,(8):663-669. 

19. Yoon KH and Kim HS. A short message service by cellular phone in type 2 diabetic patients for 12 months. Diabetes Res. Clin. Pract. 2008;79,(2):256-261. 

20. Cho JH, Lee HC, Lim DJ, Kwon HS and Yoon KH. Mobile communication using a mobile phone with a glucometer for glucose control in Type 2 patients with diabetes: as effective as an Internet-based glucose monitoring system. J. Telemed. Telecare 2009;15,(2):77-82. 

21. Arsand E, Tatara N, Ostengen G and Hartvigsen G. Mobile phone-based self-management tools for type 2 diabetes: the few touch application. J. Diabetes Sci. Technol. 2010;4,(2):328-336.

22. Dick JJ, Nundy S, Solomon MC, Bishop KN, Chin MH and Peek ME. Feasibility and usability of a text message-based program for diabetes self-management in an urban African-American population. J. Diabetes Sci. Technol. 2011;5,(5):1246-1254.

23. Fischer HH, Moore SL, Ginosar D, Davidson AJ, Rice-Peterson CM, Durfee MJ, Mackenzie TD, Estacio RO and Steele AW. Care by cell phone: text messaging for chronic disease management. Am. J. Manag. Care 2012;18,(2):e42-7.

24. Rami B, Popow C, Horn W, Waldhoer T and Schober E. Telemedical support to improve glycemic control in adolescents with type 1 diabetes mellitus. Eur. J. Pediatr. 2006;165,(10):701-705. 

25. Zolfaghari M, Mousavifar SA, Pedram S and Haghani H. The impact of nurse short message services and telephone follow-ups on diabetic adherence: which one is more effective? J. Clin. Nurs. 2012;. 

26. Farmer A, Gibson O, Hayton P, Bryden K, Dudley C, Neil A and Tarassenko L. A real-time, mobile phone-based telemedicine system to support young adults with type 1 diabetes. Inform. Prim. Care. 2005;13,(3):171-177.

27. Farmer AJ, Gibson OJ, Dudley C, Bryden K, Hayton PM, Tarassenko L and Neil A. A randomized controlled trial of the effect of real-time telemedicine support on glycemic control in young adults with type 1 diabetes (ISRCTN 46889446). Diabetes Care 2005;28,(11):2697-2702. 

28. Franklin VL, Waller A, Pagliari C and Greene SA. A randomized controlled trial of Sweet Talk, a text-messaging system to support young people with diabetes. Diabet. Med. 2006;23,(12):1332-1338. 

29. Turner J, Larsen M, Tarassenko L, Neil A and Farmer A. Implementation of telehealth support for patients with type 2 diabetes using insulin treatment: an exploratory study. Inform. Prim. Care. 2009;17,(1):47-53.

30. Rossi MC, Nicolucci A, Di Bartolo P, Bruttomesso D, Girelli A, Ampudia FJ, Kerr D, Ceriello A, Mayor Cde L, Pellegrini F, Horwitz D and Vespasiani G. Diabetes Interactive Diary: a new telemedicine system enabling flexible diet and insulin therapy while improving quality of life: an open-label, international, multicenter, randomized study. Diabetes Care 2010;33,(1):109-115. 

31. Cole-Lewis H and Kershaw T. Text messaging as a tool for behavior change in disease prevention and management. Epidemiol. Rev. 2010;32,(1):56-69. 

32. Kang BS and Ko IY. Effective route maintenance and restoration schemes in mobile ad hoc networks. Sensors (Basel) 2010;10,(1):808-821. 

33. Kabadi SM, Lee BK and Liu L. Joint Effects of Obesity and Vitamin D Insufficiency on Insulin Resistance and Type 2 Diabetes: Results from the NHANES 2001-2006. Diabetes Care 2012, Epub ahead of print. 

34. Liu L and Nunez AE. Cardiometabolic syndrome and its association with education, smoking, diet, physical activity, and social support: findings from the Pennsylvania 2007 BRFSS Survey. J. Clin. Hypertens. (Greenwich) 2010;12,(7):556-564.