Engaging Patients through Mobile Phones: Demonstrator Services, Success Factors, and Future Opportunities in Low and Middle-income Countries

Summary

Objectives: Evolving technology and infrastructure can benefit patients even in the poorest countries through mobile health (mHealth). Yet, what makes mobile-phone-based services succeed in low and middle-income countries (LMIC) and what opportunities does the future hold that still need to be studied. We showcase demonstrator services that leverage mobile phones in the hands of patients to promote health and facilitate health care.

Methods: We surveyed the recent biomedical literature for demonstrator services that illustrate well-considered examples of mobile phone interventions for consumer health. We draw upon those examples to discuss enabling factors, scalability, reach, and potential of mHealth as well as obstacles in LMIC.

Results: Among the 227 articles returned by a PubMed search, we identified 55 articles that describe services targeting health consumers equipped with mobile phones. From those articles, we showcase 19 as demonstrator services across clinical care, prevention, infectious diseases, and population health. Services range from education, reminders, reporting, and peer support, to epidemiologic reporting, and care management with phone communication and messages. Key achievements include timely adherence to treatment and appointments, clinical effectiveness of treatment reminders, increased vaccination coverage and uptake of screening, and capacity for efficient disease surveillance. We discuss methodologies of delivery and evaluation of mobile-phone-based mHealth in LMIC, including service design, social context, and environmental factors to success.

Conclusion: Demonstrated promises using mobile phones in the poorest countries encourage a future in which IMIA takes a lead role in leveraging mHealth for citizen empowerment through Consumer Health Informatics.

Keywords

Consumer Health Informatics - mobile health - low and middle-income countries (LMIC)

 

• References

• 1 Luna D, Otero C, Marcelo A. Health Informatics in Developing Countries: Systematic Review of Reviews. Contribution of the IMIA Working Group Health Informatics for Development.. Yearb Med Inform 2013; 8 (01) 28-33.
• 2 World Health Organization.. mHealth New horizons for health through mobile technologies.. Global Observatory for eHealth series - Volume 3 2011 Retrieved I June 2014 from: http://www.who.int/goe/publications/goe_mhealth_web.pdf
• 3 Klasnja P, Pratt W. Healthcare in the pocket: mapping the space of mobile-phone health interventions.. J Biomed Inform 2012; 45 (01) 184-98.
• 4 Free C, Phillips G, Galli L, Watson L, Felix L, Edwards P. et al. The Effectiveness of Mobile-Health Technology-Based Health Behaviour Change or Disease Management Interventions for Health Care Consumers: A Systematic Review.. PLoS Med 2013; 10 (01) e1001362.
• 5 Tomlinson M, Rotheram-Borus MJ, Swartz L, Tsai AC. Scaling up mHealth: where is the evidence?. PLoS Med 2013; 10 (02) e1001382.
• 6 International Telecommunication Union (ITU).. The world in 2014: ICT Facts and Figures.. Retrieved I June 2014 from: http://www.itu.int/en/ITU-D/Statistics/Documents/facts/ICTFactsFigures2014-e.pdf
• 7 United Nations.. Human development Index (IHDI).. United nations development programme 2013 Accessed June 2014 from: http://hdr.undp.org/en/statistics/ihdi
• 8 The World Bank.. Data: Life expectancy at birth, total (years).. Accessed June 2014 from: http://data.worldbank.org/indicator/SP.DYN.LE00.IN
• 9 The World Bank.. GDP per capita (current US$).. Accessed June 2014 from http://data.world-bank.org/indicator/NY.GDP.PCAP.CD/countries
• 10 International Monetary Fund.. World economic and financial survey.. 2008 Edition.. Accessed June 2014 from: http://www.imf.org/external/pubs/ft/weo/2008/01/weodata/index.aspx
• 11 Kahn JG, Yang JS, Kahn JS. ‘Mobile’ health needs and opportunities in developing countries.. Health Aff (Millwood) 2010; 29 (02) 252-8.
• 12 Ybarra ML, Holtrop JS, Bagci Bosi AT, Emri S. Design considerations in developing a text messaging program aimed at smoking cessation.. J Med Internet Res 2012; 14 (04) e103.
• 13 Bengtsson L, Lu X, Thorson A, Garfield R, von Schreeb J. Improved response to disasters and outbreaks by tracking population movements with mobile phone network data: a post-earthquake geospatial study in Haiti.. PLoS Med 2011; 8 (08) e1001083.
• 14 Ybarra M, Bağcı Bosi AT, Korchmaros J, Emri S. A Text Messaging-Based Smoking Cessation Program for Adult Smokers: Randomized Controlled Trial. J Med Internet Res 2012; Nov-Dec; 14 (06) e172. Published online Dec 27, 2012. doi: 10.2196/jmir.2231
• 15 Bowen DJ, Kreuter M, Spring B, Cofta-Woerpel L, Linnan L, Weiner D. et al. How we design feasibility studies.. Am J Prev Med 2009; May 36 (05) 452-7.
• 16 Lin H, Chen W, Luo L. et al. Effectiveness of a short message reminder in increasing compliance with pediatric cataract treatment: a randomized trial.. Ophthalmology 2012; 119 (12) 2463-70.
• 17 Odigie VI, Yusufu LM, Dawotola DA. et al. The mobile phone as a tool in improving cancer care in Nigeria.. Psychooncology 2012; 21 (03) 332-5.
• 18 Liew SM, Tong SF, Lee VK, Ng CJ, Leong KC, Teng CL. Text messaging reminders to reduce non-attendance in chronic disease follow-up: a clinical trial.. Br J Gen Pract 2009; 59 (569) 916-20.
• 19 Piette JD, Mendoza-Avelares MO, Ganser M, Mohamed M, Marinec N, Krishnan S. A preliminary study of a cloud-computing model for chronic illness self-care support in an underdeveloped country.. Am J Prev Med 2011; 40 (06) 629-32.
• 20 Rotheram-Borus MJ, Tomlinson M, Gwegwe M, Comulada WS, Kaufman N, Keim M. Diabetes buddies: peer support through a mobile phone buddy system.. Diabetes Educ 2012; 38 (03) 357-65.
• 21 Marasinghe RB, Edirippulige S, Kavanagh D, Smith A, Jiffry MT. Effect of mobile phone-based psychotherapy in suicide prevention: a randomized controlled trial in Sri Lanka.. J Telemed Telecare 2012; 18 (03) 151-5.
• 22 Mehran L, Nazeri P, Delshad H, Mirmiran P, Mehrabi Y, Azizi F. Does a text messaging intervention improve knowledge, attitudes and practice regarding iodine deficiency and iodized salt consumption?. Public Health Nutr 2012; 15 (12) 2320-5.
• 23 Wakadha H, Chandir S, Were EV. et al. The feasibility of using mobile-phone based SMS reminders and conditional cash transfers to improve timely immunization in rural Kenya.. Vaccine 2013; 31 (06) 987-93.
• 24 de Tolly K, Skinner D, Nembaware V, Benjamin P. Investigation into the use of short message services to expand uptake of human immunodeficiency virus testing, and whether content and dosage have impact.. Telemed J E Health 2012; 18 (01) 18-23.
• 25 Suwamaru JK. An SMS-based HIV/AIDS education and awareness model for rural areas in Papua New Guinea.. Stud Health Technol Inform 2012; 182: 161-9.
• 26 Bradley J, Ramesh BM, Rajaram S. et al. The feasibility of using mobile phone technology for sexual behaviour research in a population vulnerable to HIV: a prospective survey with female sex workers in South India.. AIDS Care 2012; 24 (06) 695-703.
• 27 L‘Engle KL, Vahdat HL, Ndakidemi E, Lasway C, Zan T. Evaluating feasibility, reach and potential impact of a text message family planning information service in Tanzania.. Contraception 2013; 87 (02) 251-6.
• 28 Pop-Eleches C, Thirumurthy H, Habyarimana JP. et al. Mobile phone technologies improve adherence to antiretroviral treatment in a resource-limited setting: a randomized controlled trial of text message reminders.. AIDS 2011; 25 (06) 825-34.
• 29 Lester RT, Ritvo P, Mills EJ, Kariri A, Karanja S, Chung MH. et al. Effects of a mobile phone short message service on antiretroviral treatment adherence in Kenya (WelTel Kenya1): a randomised trial.. Lancet 2010; 376 9755 1838-45.
• 30 Kunawararak P, Pongpanich S, Chantawong S. et al. Tuberculosis treatment with mobile-phone medication reminders in northern Thailand.. Southeast Asian J Trop Med Public Health 2011; 42 (06) 1444-51.
• 31 Hunchangsith P, Barendregt JJ, Vos T, Bertram M. Cost-effectiveness of various tuberculosis control strategies in Thailand.. Value Health 2012; 15 (01) Suppl S50-5.
• 32 Le Menach A, Tatem AJ, Cohen JM. et al. Travel risk, malaria importation and malaria transmission in Zanzibar.. Sci Rep 2011; 1: 93.
• 33 Kim do K, Chikombero M, Modie-Moroka T. Innate health threat among a visibly hidden immigrant group: a formative field data analysis for HIV/AIDS prevention among Zimbabwean workers in Botswana.. J Health Commun 2013; 18 (02) 146-59.
• 34 Nehl EJ, He N, Wang X, Lin L, Wong FY, Yu F. Feasibility and willingness of using e-technologies for HIV prevention and research targeting Chinese MSM. AIDS Care 2013; 25 (07) 926-30.
• 35 Tran BX, Houston S. Mobile phone-based antiretroviral adherence support in Vietnam: feasibility, patient’s preference, and willingness-to-pay.. AIDS Behav 2012; 16 (07) 1988-92.
• 36 van Kleef E, Fischer AR, Khan M, Frewer LJ. Risk and benefit perceptions of mobile phone and base station technology in Bangladesh.. Risk Anal 2010; 30 (06) 1002-15.
• 37 Gisore P, Shipala E, Otieno K. et al. Community based weighing of newborns and use of mobile phones by village elders in rural settings in Kenya: a decentralised approach to health care provision.. BMC Pregnancy Childbirth 2012; 12: 15.
• 38 Mitchell KJ, Bull S, Kiwanuka J, Ybarra ML. Cell phone usage among adolescents in Uganda: acceptability for relaying health information.. Health Educ Res 2011; 26 (05) 770-81.
• 39 Nilsen W, Riley WT, Heetderks W. News from the NIH: using mobile and wireless technologies to improve health.. Transl Behav Med 2013; 3 (03) 227-8.