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Determining Patient Preferences for Remote Monitoring

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Abstract

This paper presents the patient preferences for an application in remote health monitoring. The data was collected through a mobile service prototype. Analytical Hierarchy Process and Conjoint Analysis were used to extract the patient preferences. The study was limited to diabetes and obesity patients in Istanbul, Turkey. Results indicated that sending users’ data automatically, availability of technical support, and price are key factors impacting patient’s decisions. This implies that e-health service providers and designers should focus on the services that enable users to send measurement results automatically instead of manually.

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References

  1. Ad, S., Barriers to accepting e-prescribing in the U.S.A. Int. J. Health Care Qual. Assur. Inc. Leadersh. Health Serv. 19:158–180, 2006.

    Google Scholar 

  2. Al-Qirim, N., Championing telemedicine adoption and utilization in healthcare organizations in New Zealand. Int. J. Med. Inform. 76:42–54, 2007.

    Article  Google Scholar 

  3. Aubert, B. A., and Hamel, G., Adoption of smart cards in the medical sector: the Canadian experience. Soc. Sci. Med. 53:879–894, 2001.

    Article  Google Scholar 

  4. Basoglu, N., Daim, T., Atesok, H. C., and Pamuk, M., Exploring Health Information Seeking Behaviour. Int. J. Bus. Inf. Syst. 5(3):291–308, 2010.

    Google Scholar 

  5. Basoglu, N., Daim, T., and Kerimoglu, O., Organizational adoption of enterprise resource planning systems: A conceptual framework. J. High Technol. Manage. Res. 18(1):73–97, 2007.

    Article  Google Scholar 

  6. Basoglu, N., Tanoglu, I., and Daim, T., Innovation diffusion: Case of IT products. Int. J. Inf. Technol. Decis. Mak. 9(2):195–222, 2010.

    Article  MATH  Google Scholar 

  7. Berghout, R. M., Eminovic, N., Keizer, N. F., and Birnie, E., Evaluation of general practitioner’s time investment during a store-and-forward teledermatology consultation. Int. J. Med. Inform. 76:384–391, 2007.

    Article  Google Scholar 

  8. Bruner, G. C., and Kumar, A., Explaining consumer acceptance of handheld Internet devices. J. Bus. Res. 58:553–558, 2005.

    Article  Google Scholar 

  9. Chae, Y. M., Lee, J. H., Ho, S. H., Kim, H. J., Jun, K. H., and Won, J. U., Patient satisfaction with telemedicine in home health services for the elderly. Int. J. Med. Inform. 61:167–173, 2001.

    Article  Google Scholar 

  10. Chang, I. C., Hwang, H. G., Hung, M. C., Lin, M. H., and Yen, D. C., Factors affecting the adoption of electronic signature: Executives’ perspective of hospital information department. Decis. Support Syst. 44(1):350–359, 2007.

    Article  Google Scholar 

  11. Chau, P. Y., and Hu, P. J., Investigating healthcare professionals' decisions to accept telemedicine technlogy:an emprical test of competing theories. Inf. Manage. 39:297–311, 2002.

    Article  Google Scholar 

  12. Chen, C., Chang, R., Hung, M., and Lin, M., Assessing the quality of a web-based learning system for nurses. J. Med. Syst. 33:317–325, 2009.

    Article  Google Scholar 

  13. Chen, I. J., Yang, K. F., and Tang, F. I., Applying the technology acceptance model to explore public health nurses' intentions towards web-based learning: A cross-sectional questionnaire survey. Int. J. Nurs. Stud. 45(6):869–878, 2006.

    Article  Google Scholar 

  14. Cusack, C. M., Pan, E., Hook, J. M., Vincent, A., Kaelber, D. C., and Middleton, B., The value proposition in the widespread use of telehealth. J. Telemed. Telecare 14:167–168, 2008.

    Article  Google Scholar 

  15. Daim, T., Abu Taha, R., and Gu, Q., Comparing personal and organizational preferences in the acquisition of information technologies. Int. J. Decis. Sci. Risk Manage. 1(1–2):142–160, 2009.

    Google Scholar 

  16. Daim, T., and Intarode, N., Assessment & acquisition of green technology: Case of a Thai building material company. Energy Sustain. Dev. 13(4):280–286, 2009.

    Article  Google Scholar 

  17. Daim, T., Schweinfort, W., and Kayakutlu, G., Technology assessment of two energy portfolios using a hierarchical decision model. Int. J. Energy Sect. Manage. 4(1):24–43, 2010.

    Article  Google Scholar 

  18. Daim, T., Yates, D., Peng, Y., and Jimenez, B., Technology assessment for clean energy technologies. Technol. Soc. 31(3):232–243, 2009.

    Article  Google Scholar 

  19. Davis, F. D., Perceived usefulness, perceived ease of use, and user acceptance of information technology. MIS Quarterly 13(3):319–340, 1989.

    Article  Google Scholar 

  20. Demiris, G., Speedie, S., and Hicks, L. L., Assessment of patients’ acceptance of and satisfaction with teledermatology. J. Med. Syst. 28(6):575–579, 2004.

    Article  Google Scholar 

  21. Dishaw, M. T., and Strong, D. M., Extending the technology acceptance model with task-technology fit constructs. Inf. Manage. 36:9–21, 1999.

    Article  Google Scholar 

  22. Dixon, D. R., The Behavioral side of information technology. Int. J. Med. Inform. 56:117–123, 1999.

    Article  Google Scholar 

  23. Edvardsson, B., and Olsson, J., Key concepts for new service development. he Serv. Ind. J. 16(2):140–164, 1995.

    Article  Google Scholar 

  24. Essen, A., and Conrick, M., New e-service development in the homecare sector: Beyond implementation a radical technology. Int. J. Med. Inform. 77:679–688, 2008.

    Article  Google Scholar 

  25. Gagnon, M. P., Godin, G., Gagne, C., Fortin, J. P., Lamothe, L., Reinhar, D., et al., An adaptation of the theory of interpersonal behaviour to the study of telemedicine adoption by physicians. Int. J. Med. Inform. 71:103–115, 2003.

    Article  Google Scholar 

  26. Goodhue, D. L., Understanding user evaluations of information systems. Manage. Sci. 19(4):561–570, 1995.

    Google Scholar 

  27. Green, P. E., and Srinivasan, V., Conjoint analysis in consumer research: issues and outlook. J. Consum. Res. 5:103–123, 1978.

    Article  Google Scholar 

  28. Gururajan, R., Factors influencing the intention to use wireless technology in health care: a study in India. J. Telemed. Telecare 13:40–41, 2007.

    Article  Google Scholar 

  29. Hailey, D., Jacobs, P., Simpson, J., and Doze, S., An assessment framework for telemedicine applications. J. Telemed. Telecare 5:162–170, 2010.

    Article  Google Scholar 

  30. Hallum, D., and Daim, T., A hierarchical decision model for optimum design alternative selection. Int. J. Decis. Sci. Risk Manage. 1(1-2):2–23, 2009.

    Google Scholar 

  31. Harrel, G., and Daim, T., HDM modeling as a tool to assist management with employee motivation. Eng. Manage. J. 22(4):74–85, 2010.

    Google Scholar 

  32. Kahen, G., and Sayers, B. M., Health-care technology transfer: Expert and information systems for developing countries. Meth. Inf. Med. 36:69–78, 1997.

    Google Scholar 

  33. Karahanna, E., Straub, D. W., and Chervany, N. L., Information technology adoption across time: a cross-sectional comparison of pre-adoption and post-adoption beliefs. MIS Quarterly 23(2):183–213, 1999.

    Article  Google Scholar 

  34. Kargin, B., Basoglu, N., and Daim, T., Adoption factors of mobile services. Int. J. Inf. Syst. Serv. Sect. 1(1):15–34, 2009.

    Article  Google Scholar 

  35. Kargin, B., Basoglu, N., and Daim, T., Factors affecting the adoption of mobile services. Int. J. Serv. Sci. 1(2):29–52, 2009.

    Google Scholar 

  36. Kerimoglu, O., Basoglu, N., and Daim, T., Organizational adoption of information technologies: Case of enterprise resource planning systems. J. High Technol. Manage. Res. 19(1):21–35, 2008.

    Article  Google Scholar 

  37. Kifle, M., Mbarika, V. W., and Datta, P., Interplay of cost and adoption of tele-medicine in Sub-Saharan Africa: The case of tele-cardiology in Ethiopia. Inf Syst Front 8:211–223, 2006.

    Article  Google Scholar 

  38. Kilic, M., Arslan, M., Leblebici, D. N., Aydin, M. D., and Oktem, M. K., Managerial control Vs professional autonomy: An empirical study on perceptions and xpectations of physicians at teaching hospitals in Turkey. J. Med. Syst. 32(2):157–165, 2008.

    Article  Google Scholar 

  39. Kim, D., and Chang, H., Key functional characteristics in designing and operating health information websites for user satisfaction: An application of the extended technology acceptance model. Int. J. Med. Inform. 76:790–800, 2007.

    Article  Google Scholar 

  40. King, G., Richards, H., and Godden, D., Adoption of telemedicine in Scottish remote and rural general practices: a qualitative study. J. Telemed. Telecare 13:382–386, 2007.

    Article  Google Scholar 

  41. Kuziemsky, C. E., Laul, F., and Leung, R. C., A review on diffusion of personal digital assistants in healthcare. J. Med. Syst. 29(4):335–342, 2005.

    Article  Google Scholar 

  42. Kwak, N. K., McCarthy, K. J., and Parker, G. E., A human resource planning model for hospital/medical technologists: An analytic hierarchy process approach. J. Med. Syst. 21(3):173–187, 1997.

    Article  Google Scholar 

  43. Lee, H. J., Lee, S. H., Ha, K. S., Jang, H. C., Chung, W. Y., Kim, J. Y., et al., Ubiquitous healthcare service using Zigbee and mobile phone for elderly patients. Int. J. Med. Inform. 78(3):193–198, 2009.

    Article  Google Scholar 

  44. Lemire, M., Sicotte, G. P., and Harvey, C., Determinants of Internet use as a preferred source of information on personal health. Int. J. Med. Inform. 77(11):723–734, 2008.

    Article  Google Scholar 

  45. Liu, L., and Ma, Q., The impact of service level on the acceptance of application service oriented medical records. Inf. Manage. 42:1121–1135, 2005.

    Article  Google Scholar 

  46. Liu, L., and Ma, Q., Perceived system performance: A test of an extended technology acceptance model. Database Advences Inf. Syst. 37:51–59, 2006.

    Article  Google Scholar 

  47. Mathieson, K., Peacock, E., and Chin, W. W., Extending the technology acceptance model: The influence of perceived user resources. Databe Base Adv. Inf. Syst. 32(3):86–112, 2001.

    Article  Google Scholar 

  48. Moorman, C., and Matulich, E., A model of consumers’ preventive health behaviors: The role of health motivation and health ability. J. Consum. Res. 20:208–228, 1993.

    Article  Google Scholar 

  49. Pare, G., Sicotte, C., and Jacques, H., The effects of creating psychological ownership on physicians’ acceptance of clinical information systems. J. Am. Med. Inform. Assoc. 13(2):197–205, 2006.

    Article  Google Scholar 

  50. Peterson LT, Ford EW, Eberhardt J, Huerta TR & Menachemi N (2009) Assessing differences between physicians’ realized and anticipated gains from electronic health record adoption. Journal of Medical Systems, in print

  51. Phan, K., Daim, T., Basoglu, N., and Kargin, B., Comparing factors affecting the adoption of mobile services in developed versus developing countries: Case of Turkey versus United States. Int. J. Serv. Sci. 3(2/3):216–231, 2010.

    Google Scholar 

  52. Ramsay, J., Barbesi, A., and Preece, J., A psychological investigation of long retrieval times on the World Wide Web. Interact. Comput. 10(1):77–86, 1998.

    Article  Google Scholar 

  53. Saaty, T. L., A scaling method for priorities in hierarchical structures. J. Math. Psychol. 15:234–281, 1977.

    Article  MathSciNet  MATH  Google Scholar 

  54. Saaty, T. L., The analytic hierarchy process. RWS Publications, Pittsburgh, 1996.

    Google Scholar 

  55. Schaper, L. K., and Pervan, G. P., ICT and OTs: A model of information and communication technology acceptance and utilisation by occupational therapists. Int. J. Med. Inform. 76:212–221, 2007.

    Article  Google Scholar 

  56. Schaupp, C. L., and Bélanger, F., A conjoint analysis of online customer satisfaction. J. Electron. Commer. Res. 6(2):96–111, 2005.

    Google Scholar 

  57. Scheuing, E. E., and Johnson, E. M., A proposed model for new service development. J. Serv. Mark. 3(2):25–34, 1989.

    Article  Google Scholar 

  58. Sears, A., Jacko, J. A., and Dubach, E. M., International aspects of World Wide Web usability and the role of high-end graphical enhancements. Int. J. Hum. Comput. Interact. 12(2):241–261, 2000.

    Article  Google Scholar 

  59. Seneler, C. O., Basoglu, N., and Daim, T., Exploring the contribution of information systems user interface design characteristics to adoption process. Int. J. Bus. Inf. Syst. 4(5):489–508, 2009.

    Google Scholar 

  60. Seneler, C. O., Basoglu, N., and Daim, T., Interface feature prioritization for web services: Case of online flight reservations. Comput. Hum. Behav. 25:862–877, 2009.

    Article  Google Scholar 

  61. Shi, H. J., Nakamura, K., and Takano, T., Health values and health-information-seeking in relation to positive change of health practice among middle-aged urban men. Prev. Med. 39:1164–1171, 2004.

    Article  Google Scholar 

  62. Simon, J. S., Rundall, T. G., and Shortell, S. M., Adoption of order entry with decision support for chronic care by physician organizations. J. Am. Med. Inform. Assoc. 14(4):432–439, 2007.

    Article  Google Scholar 

  63. Spaulding, R. J., Russo, T., Cook, D. J., and Doolittle, G. C., Diffusion theory and telemedicine adoption by Kansas health-care providers: Critical factors in telemedicine adoption for improved patient access. J. Telemed. Telecare 11:107–109, 2005.

    Article  Google Scholar 

  64. Tam, M. C., and Tummala, V. M., An application of the AHP in vendor selection of a telecommunications system. Int. J. Manage. Sci. 29:171–182, 2001.

    Google Scholar 

  65. Taylor, S., and Todd, P., Assessing IT usage: The role of prior experience. MIS Quarterly 19(4):561–570, 1995.

    Article  Google Scholar 

  66. Thompson, R. L., Higgins, C. A., and Howell, J. M., Personal computing: Toward a conceptual model of utilization. MIS Quarterly 15(1):125–143, 1991.

    Article  Google Scholar 

  67. Topacan, U., Basoglu, N., and Daim, T. U., Exploring health information service adoption. Int. J. Inf. Syst. Serv. Sect. 2(1):71–93, 2010.

    Article  Google Scholar 

  68. Topacan, U., Basoglu, N., and Daim, T., AHP Application on evaluation of health information service attributes, technology management in the age of fundamental change, Portland International Conference on Management of Engineering and Technology Proceedings, Portland, Oregon, pp 486–493, 2009.

  69. Topacan, U., Basoglu, N., and Daim, T., Evaluating health information services: A patient perspective analysis, Developments in Healthcare Information Systems and Technologies by J Tan, IGI Global, Hershey New York, pp 1–13, 2011.

  70. Tung, F. C., and Chang, S. C., A new hybrid model for exploring the adoption of online nursing courses. Nurse Educ. Today 28:293–300, 2008.

    Article  Google Scholar 

  71. Tung, F. C., Chang, S. C., and Chou, C. M., An extension of trust and TAM model with IDT in the adoption of the electronic logistic information system in HIS in the medical industry. Int. J. Med. Inform. 77(5):324–335, 2008.

    Article  Google Scholar 

  72. Turi, J. J., Program eases decision making. Health Prog. 69:40–44, 1988.

    Google Scholar 

  73. Vaidya, O. S., and Kumar, S., Analytic hierarchy process: An overview of applications. Eur. J. Oper. Res. 169:1–29, 2006.

    Article  MathSciNet  MATH  Google Scholar 

  74. van den Brink, J. L., Moorman, P. W., de Boer, M. F., Pruyn, J. F., Verwoerd, C. D., and van Bemmel, J. H., Involving the patient: A prospective study on use, appreciation and effectiveness of an information system in head and neck cancer care. Int. J. Med. Inform. 74:839–849, 2005.

    Article  Google Scholar 

  75. Venkatesh, V., and Davis, F. D., A theoretical extension of the technology acceptance model: Four longitudinal field studies. Manage. Sci. 46(2):186–204, 2000.

    Article  Google Scholar 

  76. Venkatesh, V., Morris, M. G., Davis, G. B., and Davis, F. D., User acceptance of information technology: Toward a unified view. MIS Quarterly 27(3):425–478, 2003.

    Google Scholar 

  77. Vuononvirta, T., Timonen, M., Keinänen-Kiukaanniemi, S., Timonen, O., Ylitalo, K., Kanste, O., and Taanila, A., The attitudes of multiprofessional teams to telehealth adoption in northern Finland health centres. J. Telemed. Telecare 15:290–296, 2009.

    Article  Google Scholar 

  78. WHO. (2009). http://apps.who.int/bmi/index.jsp?introPage = intro_3.html. Retrieved 05 30, 2009, from World Health Organization: http://www.who.int

  79. Wilson, V. E., and Lankton, N. K., Modeling patients’ acceptance of provider-delivered E-health. J. Am. Med. Inform. Assoc. 11(4):241–248, 2004.

    Article  Google Scholar 

  80. Yu, P., Li, H., and Gagnon, M. P., Health IT acceptance factors in long-term care facilities: A cross-sectional survey. Int. J. Med. Inform. 78(4):219–229, 2009.

    Article  Google Scholar 

  81. Yusof, M. M., Kuljis, J., Papazafeiropoulou, A., and Stergioulas, L. K., An evaluation framework for Health Information Systems: human, organization, and technology-fit factors (HOT-fit). Int. J. Med. Inform. 77(6):386–398, 2007.

    Article  Google Scholar 

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  1. Bogazici University, Istanbul, Turkey

    Nuri Basoglu & Umit Topacan

  2. Portland State University, Portland, OR, USA

    Tugrul U. Daim

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  1. Nuri Basoglu
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Basoglu, N., Daim, T.U. & Topacan, U. Determining Patient Preferences for Remote Monitoring. J Med Syst 36, 1389–1401 (2012). https://doi.org/10.1007/s10916-010-9601-1

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