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Using Foucault to Understand Self-Monitoring in Chronic Disease Management

  • Nilmini Wickramasinghe
  • Steve Goldberg
Chapter
Part of the Healthcare Delivery in the Information Age book series (Healthcare Delivery Inform. Age)

Abstract

In today’s twenty-first century healthcare environment, the interaction of patients with information and communication technologies (ICTs) is a particularly interesting dynamic to researchers who study changes in related behavioral phenomena. One such phenomenon is self-monitoring. In the management of noncommunicable chronic disease, self-monitoring is considered a critical enabler for the attainment and maintaining of a better healthcare state. This paper examines the behavioral change of self-monitoring and the integral role of ICTs in enabling patients to self-monitor.

Keywords

Diabetes Pervasive Mobile solution Self-monitoring Power/knowledge 

References

  1. AIHW. (2007). National indicators for monitoring diabetes: Report of the Diabetes Indicators Review Subcommittee of the National Diabetes Data Working Group in diabetes series 2007. Canberra: The Australian Institute of Health and Welfare.Google Scholar
  2. AIHW. (2008). Australian facts 2008. Canberra: Australian Institute of Health and Welfare.Google Scholar
  3. Balas, E. A., Krishna, S., Kretschmer, R. A., Cheek, T. R., Lobach, D. F., & Boren, S. A. (2004). Computerized knowledge management in diabetes care. Medical Care, 42, 610–621.CrossRefPubMedGoogle Scholar
  4. Bodenheimer, T., Lorig, K., Holman, H., & Grumbach, K. (2002). Patient self-management of chronic disease in primary care. JAMA, 288(19), 2469–2475.CrossRefPubMedGoogle Scholar
  5. Bourdieu, P. (1990). The logic of practice. Stanford, CA: Stanford University Press.Google Scholar
  6. Britt, H., Miller, G. C., Henderson, J., Bayram, C., Valenti, L., Harrison, C., et al. (2009). General practice activity in Australia 2008-09. Sydney: Australian Institute of Health and Welfare, and University of Sydney.Google Scholar
  7. Catanzariti, L., Faulks, K., & Waters, A.-M. (2007). National diabetes register: A statistical profile 1999-2005. Canberra: Australian Institute of Health and Welfare.Google Scholar
  8. Chittleborough, C. R., Grant, J. F., Phillips, P. J., & Taylor, A. W. (2007). The increasing prevalence of diabetes in South Australia: The relationship with population ageing and obesity. Public Health, 121(2), 92–99.CrossRefPubMedGoogle Scholar
  9. Colagiuri, S., Colagiuri, R., Grainger, D., Graham-Clarke, P., Davey, P., FitzGerald, P., et al. (2002). DiabCost Australia-assessing the burden of Type 2 diabetes in Australia. In Diabetologia. New York, NY: Springer.Google Scholar
  10. Colagiuri, S., Colagiuri, R., & Ward, J. (1998). National diabetes strategy and implementation plan (pp. 1–281). Canberra: Diabetes.Google Scholar
  11. Crowther, C. A., Hiller, J. E., Moss, J. R., McPhee, A. J., Jeffries, W. S., Robinson, J. S., et al. (2005). Effect of treatment of gestational diabetes mellitus on pregnancy outcomes. New England Journal of Medicine, 352(24), 2477–2486.CrossRefPubMedGoogle Scholar
  12. Diabetes Australia. (2016, April 11). Diabetes in Australia. Available from https://www.diabetesaustralia.com.au/diabetes-in-australia
  13. Doolin, B. (2004). Power and resistance in the implementation of a medical management information system. Information Systems Journal, 14(4), 343–362.CrossRefGoogle Scholar
  14. Foucault, M. (1980). Power/knowledge: Selected interviews and other writings, 1972-1977. New York: Pantheon.Google Scholar
  15. Foucault, M. (1998). The will to knowledge: The history of sexuality (Vol. I). London: Penguin.Google Scholar
  16. Geisler, E., & Wickramasinghe, N. (2005). The role and use of wireless technology in the management and monitoring of chronic diseases. Paper presented at the IBM Center for The Business of Government, DC.Google Scholar
  17. Goldberg, S. (2002a). HTA presentation rendering component summary. Internal INET documentation.Google Scholar
  18. Goldberg, S. (2002b). HTA presentational selection and aggregation component summary. Internal documentation.Google Scholar
  19. Goldberg, S. (2002c). Wireless POC device component summary. Internal INET documentation.Google Scholar
  20. Goldberg, S. (2002d). Building the evidence for a standardized mobile internet (wireless) environment in Ontario, Canada. January Update, Internal INET Documentation, Ontario, Canada, INET.Google Scholar
  21. Help4Diabetes. (2012). Diabetes: A world wide epidemic. [cited 2012 September 2012]. Available from http://www.hope4diabetes.info/general-information/diabetes-a-worldwide-epidemic.html
  22. Hoffman, L., Nolan, C., Wilson, J. D., Oats, J. J., & Simmons, D. (1998). Gestational diabetes mellitus-management guidelines. The Australasian Diabetes in Pregnancy Society. Medical Journal of Australia, 169(2), 93–97.PubMedPubMedCentralGoogle Scholar
  23. ICIC. (2008). Improving chronic illness care: The chronic care model.Google Scholar
  24. International Diabetes Federation. (2015). IDF diabetes atlas (7th ed.). Brussels: IDF.Google Scholar
  25. Kelley, R. E. (1990). Managing the new workforce. Machine Design, 62(9), 109–113.Google Scholar
  26. Kirsch, L. J., Sambamurthy, V., Ko, D.-G., & Purvis, R. L. (2002). Controlling information systems development projects: The view from the client. Management Science, 48(4), 484–498.CrossRefGoogle Scholar
  27. Kleinwechter, H., Schäfer-Graf, U., Bührer, C., Hoesli, I., Kainer, F., Kautzky-Willer, A., et al. (2011). Gestationsdiabetes mellitus (GDM). Evidenzbasierte Leitlinie zu Diagnostik, Therapie u. Nachsorge der Deutschen Diabetes-Gesellschaft (DDG) und der Deutschen Gesellschaft für Gynäkologie und Geburtshilfe (DGGG). www.deutsche-diabetes-gesellschaft.de
  28. Kohli, R., & Kettinger, W. J. (2004). Informating the clan: Controlling physicians’ costs and outcomes. MIS Quarterly, 28, 363–394.CrossRefGoogle Scholar
  29. Metzger, B. E., Lowe, L. P., Dyer, A. R., Trimble, E. R., Chaovarindr, U., Coustan, D. R., et al. (2008). Hyperglycemia and adverse pregnancy outcomes. The New England Journal of Medicine, 358(19), 1991–2002.CrossRefPubMedGoogle Scholar
  30. Poster, M. (1990). The mode of information: Poststructuralism and social context. Chicago: University of Chicago Press.Google Scholar
  31. Poulton, B. C. (1999). User involvement in identifying health needs and shaping and evaluating services: Is it being realised? Journal of Advanced Nursing, 30(6), 1289–1296.CrossRefPubMedGoogle Scholar
  32. Rabinow, P. (1991). The Foucault reader. London: Penguin.Google Scholar
  33. Rachlis, M. (2006). Key to sustainable healthcare system (p. 2008), vol. 21. Retrieved June, 2006.Google Scholar
  34. Rasmussen, B., Wellard, S., & Nankervis, A. (2001). Consumer issues in navigating health care services for type I diabetes. Journal of Clinical Nursing, 10(5), 628–634.CrossRefPubMedGoogle Scholar
  35. Reach, G., Zerrouki, A., Leclercq, D., & d’Ivernois, J. F. (2005). Adjusting insulin doses: From knowledge to decision. Patient Education and Counseling, 56(1), 98–103.CrossRefPubMedGoogle Scholar
  36. Rudi, R., & Celler, B. G. (2006). Design and implementation of expert-telemedicine system for diabetes management at home. In Biomedical and Pharmaceutical Engineering, 2006. ICBPE 2006. International Conference on. Singapore: IEEE.Google Scholar
  37. Rumbold, A. R., & Crowther, C. A. (2001). Guideline use for gestational diabetes mellitus and current screening, diagnostic and management practices in Australian hospitals. Australian and New Zealand Journal of Obstetrics and Gynaecology, 41(1), 86–90.CrossRefPubMedGoogle Scholar
  38. Townley, B. (1993). Foucault, power/knowledge, and its relevance for human resource management. Academy of Management Review, 18(3), 518–545.CrossRefGoogle Scholar
  39. Van Eyk, H., & Baum, F. (2002). Learning about interagency collaboration: Trialling collaborative projects between hospitals and community health services. Health & Social Care in the Community, 10(4), 262–269.CrossRefGoogle Scholar
  40. Wellard, S. J., Rennie, S., & King, R. (2008). Perceptions of people with type 2 diabetes about self-management and the efficacy of community based services. Contemporary Nurse, 29(2), 218–226.CrossRefPubMedGoogle Scholar
  41. Wickramasinghe, N., & S. Goldberg. (2003). The wireless panacea for healthcare. In Proceedings of 36th Hawaii international conference on system sciences, Hawaii.Google Scholar
  42. Wickramasinghe, N., & Goldberg, S. (2004). How M = EC2 in healthcare. International Journal of Mobile Communications, 2(2), 140–156.CrossRefGoogle Scholar
  43. Wickramasinghe, N., & Goldberg, S. (2007). The Wi-INET model for achieving M-Health success. In D. Taniar (Ed.), Encyclopedia of Mobile Computing and Commerce (pp. 1004–1010). Hershey, PA: Information Science Reference.  https://doi.org/10.4018/978-1-59904-002-8.ch168.
  44. Wickramasinghe, N., Troshani, I., Rao, S., Hague, W., & Goldberg, S. (2013). A transaction cost assessment of a pervasive technology solution for gestational diabetes. In Healthcare information technology innovation and sustainability: Frontiers and adoption (p. 109). Hershey, PA: IGI Global.CrossRefGoogle Scholar
  45. Zgibor, J. C., & Songer, T. J. (2001). External barries to diabetes care: Addressing personal and health systems issues. Diabetes Spectrum: A Publication of the American Diabetes Association, 14(1), 23.CrossRefGoogle Scholar
  46. Zhang, F., et al. (2011). Increasing prevalence of gestational diabetes mellitus in Chinese women from 1999 to 2008. Diabetic Medicine, 28(6), 652–657.CrossRefPubMedGoogle Scholar

Copyright information

© Springer International Publishing AG, part of Springer Nature 2018

Authors and Affiliations

  • Nilmini Wickramasinghe
    • 1
    • 2
  • Steve Goldberg
    • 3
  1. 1.Deakin UniversityMelbourneAustralia
  2. 2.Epworth HealthCareRichmondAustralia
  3. 3.Inet International Inc.ThornhillCanada

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