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Importance of Mobile Technology in Successful Adoption and Sustainability of a Chronic Disease Support System

Authors: Reza Ariaeinejad, Norm Archer


Self-management is becoming a new emphasis for healthcare systems around the world. But there are many different problems with adoption of new health-related intervention systems. The situation is even more complicated for chronically ill patients with disabilities, illiteracy, and impairment in judgment in addition to their conditions, or having multiple co-morbidities. Providing online decision support to manage patient health and to provide better support for chronically ill patients is a new way of dealing with chronic disease management. In this study, the importance of mobile technology through an m-Health system that supports self-management interventions including the care provider, family and social support, education and training, decision support, recreation, and ongoing patient motivation to promote adherence and sustainability of the intervention are discussed. A proposed theoretical model for adoption and sustainability of system use is developed, based on UTAUT2 and IS Continuance of Use models, both of which have been pre-validated through longitudinal studies. The objective of this paper is to show the importance of using mobile technology in adoption and sustainability of use of an m-Health system which will result in commercially sustainable self-management support for chronically ill patients.

Keywords: e-Health, Disease, Self-management, m-health

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[1] L. Lhotska, O. Stepankova, and M. Pechoucek, "ICT and eHealth Projects,” in Telecom World Technical Symposium, 2011, pp. 57–62.
[2] M. Mirolla, "The cost of chronic disease in Canada,” Chronic Dis. Prev. Alliance Canada, 2004.
[3] T. Bodenheimer, E. H. Wagner, and K. Grumbach, "Improving primary care for patients with chronic illness, the chronic care model, part 2,” October, vol. 288, no. 15, pp. 1909–1914, 2002.
[4] D. M. Taylor, J. I. Cameron, L. Walsh, S. McEwen, A. Kagan, D. L. Streiner, and M. P. Huijbregts, "Exploring the feasibility of videoconference delivery of a self-management program to rural participants with stroke.,” Telemed. eHealth, vol. 15, no. 7, pp. 646–654, 2009.
[5] B. Riegel, D. K. Moser, S. D. Anker, L. J. Appel, S. B. Dunbar, K. L. Grady, and D. J. Whellan, "State of the science: Promoting self-care in persons with heart failure: A scientific statement from the American Heart Association,” J. Am. Heart Assoc., vol. 120, no. 12, pp. 1141–1163, 2009.
[6] P. S. Roshanov, S. Misra, H. C. Gerstein, A. X. Garg, R. J. Sebaldt, J. a Mackay, L. Weise-Kelly, T. Navarro, N. L. Wilczynski, and R. B. Haynes, "Computerized clinical decision support systems for chronic disease management: A decision-maker-researcher partnership systematic review,” Implement. Sci., vol. 6, no. 1, p. 92, 2011.
[7] C. L. Overby, P. Tarczy-hornoch, J. Hoath, J. W. Smith, and E. B. Devine, "An evaluation of functional and user interface requirements for pharmacogenomic clinical decision support,” in Healthcare Informatics, Imaging and Systems Biology, 2011, no. 9.
[8] F. Cleveringa, P. Welsing, M. Donk, K. Gorter, L. Niessen, G. Rutten, and W. Redekop, "Cost-effectiveness of the diabetes care protocol , a multifaceted computerized,” Diabetes Care, vol. 33, no. 2, 2010.
[9] D. F. Sittig, A. Wright, J. a Osheroff, B. Middleton, J. M. Teich, J. S. Ash, E. Campbell, and D. W. Bates, "Grand challenges in clinical decision support.,” J. Biomed. Inform, vol. 41, no. 2, pp. 387–92, Apr. 2008.
[10] G. L. MacIntyre, L. Thabane, A. Cranney, R. Cook, and A. Papaioannou, "Exercise for improving outcomes after osteoporotic vertebral fracture (Protocol),” Statistics (Ber)., no. 7, pp. 1–10, 2010.
[11] J. Pogue, L. Thabane, P. J. Devereaux, and S. Yusuf, "Testing for heterogeneity among the components of a binary composite outcome in a clinical trial,” BMC Med. Res. Methodol., vol. 10, p. 49, Jan. 2010.
[12] B. Riegel, D. K. Moser, S. D. Anker, L. J. Appel, S. B. Dunbar, K. L. Grady, M. Z. Gurvitz, E. P. Havranek, C. S. Lee, J. Lindenfeld, P. N. Peterson, S. J. Pressler, D. D. Schocken, and D. J. Whellan, "State of the science: promoting self-care in persons with heart failure: a scientific statement from the American Heart Association,” J. Am. Heart Assoc., vol. 120, no. 12, pp. 1141–63, Sep. 2009.
[13] R. J. McManus, P. Glasziou, A. Hayen, J. Mant, P. Padfield, J. Potter, E. P. Bray, and D. Mant, "Blood pressure self-monitoring: questions and answers from a national conference,” Bmj, vol. 338, pp. 38–42, Dec. 2009.
[14] J. Sidel, K. Ryan, and J. Nemis-White, "Shaping the healthcare environment through evidence-based medicine: A case study of the ICONS project,” Hosp. Q., vol. 2, no. 1, pp. 29–33, 1998.
[15] C. Wahl, J. Gregoire, and K. Teo, "Concordance, compliance and adherence in health care : closing gaps and improving outcomes,” Healthc. Q., vol. 8, no. 1, pp. 65–70, 2005.
[16] E. S. Berner, Clinical decision support systems: theory and practice. Springer Science + Business Media, 2007.
[17] M. Hartmann, E. Bäzner, B. Wild, I. Eisler, and W. Herzog, "Effects of interventions involving the family in the treatment of adult patients with chronic physical diseases: a meta-analysis,” Psychother. Psychosom., vol. 79, no. 3, pp. 136–48, Jan. 2010.
[18] M. P. Gallant, "The influence of social support on chronic illness self-management: a review and directions for research,” Heal. Educ. Behav., vol. 30, no. 2, pp. 170–195, Apr. 2003.
[19] Y. Tang, S. Pang, M. Chan, G. Yeung, and V. Yeung, "Health literacy, complication awareness, and diabetic control in patients with type 2 diabetes mellitus.,” J. Adv. Nurs., vol. 62, no. 1, pp. 74–83, Apr. 2008.
[20] A. S. Levey and N. R. Powe, "Patient awareness of chronic kidney disease,” Methods, vol. 168, no. 20, pp. 2268–2275, 2008.
[21] S. L. Loman, B. J. Rodriguez, and R. H. Horner, "Sustainability of a targeted intervention package: first step to success in Oregon,” J. Emot. Behav. Disord., vol. 18, no. 3, pp. 178–191, Mar. 2010.
[22] G. M. Russell, S. Dabrouge, W. Hogg, R. Geneau, L. Muldoon, and M. Tuna, "Managing chronic disease in ontario primary care: the impact of organiza- tional factors,” Ann. Fam. Med., vol. 7, no. 4, pp. 309–318, 2009.
[23] A. C. Tsai, S. C. Morton, C. M. Mangione, and E. B. Keeler, "A Meta-Analysis of Interventions to Improve Care for Chronic Illnesses,” Am. J. Manag Care, vol. 11, no. 8, pp. 478–488, 2005.
[24] L. a. Palinkas, K. Ell, M. Hansen, L. Cabassa, and A. Wells, "Sustainability of collaborative care interventions in primary care settings,” J. Soc. Work, vol. 11, no. 1, pp. 99–117, Dec. 2010.
[25] S. Fox and S. Jones, "The Social Life of Health Information,” 2011.
[26] L. Sauvé, L. Renaud, and D. Kaufman, "The efficacy of games and simulations for learning,” Sci. York, pp. 252–254, 2010.
[27] C. Frederico, "Results of a dietitian survey about nutrition games,” Games Health J., vol. 1, no. 1, pp. 51–57, 2012.
[28] R. Ariaeinejad, K. Sayyedi Viand, C. Demers, and N. Archer, "Personal decision support for chronic disease self- anagement,” in Advances in Health Informatics Conference (AHIC), 2012.
[29] L. Dawkins, J. H. Powell, A. Pickering, J. Powell, and R. West, "Patterns of change in withdrawal symptoms, desire to smoke, reward motivation and response inhibition across 3 months of smoking abstinence,” Addiction, vol. 104, no. 5, pp. 850–8, May 2009.
[30] W. Mason, W. Street, and D. J. Watts, "Financial incentives and the performance of crowds,” SIGKDD Explor., vol. 11, no. 2, pp. 100–108, 2010.
[31] H. Garavan and K. Weierstall, "The neurobiology of reward and cognitive control systems and their role in incentivizing health behavior,” Prev. Med. (Baltim)., vol. 55, pp. 17–23, Nov. 2012.
[32] V. Venkatesh and F. D. Davis, "A theoretical extension of the technology acceptance model: four longitudinal field studies,” Manage. Sci., vol. 46, no. 2, pp. 186–204, Feb. 2000.
[33] V. Venkatesh, M. G. Morris, G. B. Davis, and F. D. Davis, "User acceptance of information technology: towards a unified theory,” MIS Q., vol. 27, no. 3, pp. 425–478, 2003.
[34] V. Venkatesh and H. Bala, "Technology acceptance model 3 and a research agenda on interventions,” Decis. Sci., vol. 39, no. 2, pp. 273–315, May 2008.
[35] V. Venkatesh, J. Y. L. Thong, and X. Xu, "Consumer acceptance and use of information technology: extending the unified theory,” MIS Q., vol. 36, no. 1, pp. 157–178, 2012.
[36] S. Tylor and P. A. Todd, "Understanding information technology usage: a test of competing Models,” Inf. Syst. Res., vol. 6, no. 2, pp. 144–176, 1995.
[37] A. Bhattacherjee, "Understanding information systems continuance : an expectation - confirmation model,” MIS Q., vol. 25, no. 3, pp. 351–370, 2001.
[38] S. Brown, A. Dennis, and V. Venkatesh, "Predicting collaboration technology use : integrating technology adoption and collaboration research,” J. Manag. Inf. Syst., vol. 27, no. 2, pp. 9–53, 2010.
[39] B. Smedley and L. Syme, "Promoting Health: Intervention strategies from social and behavioral research,” Am. J. Heal. Promot., vol. 15, no. 3, pp. 149–166, 2001.
[40] J. Tufano and B. Karras, "Mobile eHealth Interventions for Obesity: A timely opportunity to leverage convergence trends,” J Med Lib Assoc, vol. 7, no. 5, pp. 58–66, 2005.
[41] K. E. Heron and J. M. Smyth, "Ecological momentary interventions: Incorporating mobile technology into psychosocial and health behavior treatments,” Br. J. Health Psychol., vol. 15, pp. 1–39, 2010.