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  • Hao Cai (a1), Egon Toft (a2), Ole Hejlesen (a3), John Hansen (a3), Claus Oestergaard (a4) and Birthe Dinesen (a5)...

Background: The intelligent bed is a medical bed with several home healthcare functions. It includes, among others, an “out of bed” detector, a moisture detector, and a catheter bag detector. The design purpose of the intelligent bed is to assist patients in their daily living, facilitate the work of clinical staff, and improves the quality of care. The aim of this sub-study of the iCare project was to explore how health professionals (HPs) experience and use the intelligent bed in patients’ homes.

Methods: The overall research design is inspired by case study methodology. A triangulation of data collection techniques has been used: log book, documentation study, participant observations (n = 45 hr), and qualitative interviews (n = 23). The data have been analyzed by means of Nvivo 9.0.

Findings: We identified several themes: HP transformation from passive technology recipient to innovator; individualized care; work flow redesign; and sensor technology intruding on patient privacy.

Conclusions: It is suggested that functions of the intelligent bed can result in more individualized care, workflow redesign, and time savings for the health professionals in caring for elderly patients. However, the technology intruded on patients’ privacy.

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1. Yonezawa, Y, Miyamoto, Y, Maki, H, et al. A new intelligent bed care system for hospital and home patients. Biomed Instrum Technol. 2005;39:313319.
2. Jung, JW, Do, JH, Kim, YM, et al. Advanced robotic residence for the elderly/the handicapped: Realization and user evaluation. ICORR 2005: 9th International Conference on Rehabilitation Robotics; 28 June-1 July 5, 2005; Chicago, IL: IEEE; 2005:492–495.
3. Gaddam, A, Kaur, K, Gupta, GS, Mukhopadhyay, SC. Determination of sleep quality of inhabitant in a smart home using an intelligent bed sensing system. I2MTC 2010: Instrumentation and Measurement Technology Conference; May 3–6, 2010; Austin, TX: IEEE; 2010:16131617.
4. Hatler, C. How intelligent are smart beds? Nurs Manage. 2008;39:2026.
5. Kidholm, K, Ekeland, AG, Jensen, LK, et al. A model for assessment of telemedicine applications: Mast. Int J Technol Assess Health Care. 2012;28:4451.
6. Argyris, C, Schon, DA. Organizational learning II: Theory, method, and practice. Reading, MA: FT Press; 1995.
7. Yin, RK. Case study research: Design and methods, 5th ed. Los Angeles: SAGE Publications; 2013.
8. Denzin, NK, Lincoln, YS. The SAGE handbook of qualitative research, 4th ed. New York: SAGE Publications; 2011.
9. Golafshani, N. Understanding reliability and validity in qualitative research. Qual Rep. 2003;8:9.
10. Ritchie, J, Lewis, J, Nicholls, CM. Qualitative research practice: A guide for social science students and researchers, 2nd ed. New York: SAGE Publications; 2013.
11. Kawulich, BB. Participant observation as a data collection method. Forum Qual Soc Res. 2005;6: Art.43.
12. Patton, MQ. Qualitative research & evaluation methods: Integrating theory and practice, 4th ed. Los Angeles: SAGE Publications; 2014.
13. Brinkmann, S, Kvale, S. InterViews: Learning the craft of qualitative research interviewing, 3rd ed. Los Angeles: SAGE Publications; 2014.
14. Ratcliff, D. Qualitative data analysis and the transforming moment. Transformation. 2008;25:116133.
15. Thomas, DR. A general inductive approach for analyzing qualitative evaluation data. Am J Eval. 2006;27:237246.
16. Dinesen, B, Toft, E. Telehomecare challenge collaboration among healthcare professionals. Wireless Pers Commun. 2009;51:711724.
17. Loh, PK, Flicker, L, Horner, B. Attitudes toward information and communication technology (ICT) in residential aged care in Western Australia. J Am Med Dir Assoc. 2009;10:408413.
18. Lee, S, Martinez, G, Ma, GX, et al. Barriers to health care access in 13 Asian American communities. Am J Health Behav. 2010;34:2130.
19. Martinez, I, Escayola, J, Trigo, JD, et al. Recent innovative advances in telemedicine: Standard-based designs for personal health. Int J Biomed Eng Technol. 2011;5:175194.
20. Sixsmith, AJ. An evaluation of an intelligent home monitoring system. J Telemed Telecare. 2000;6:6372.
21. Pietrzak, E, Cotea, C, Pullman, S. Does smart home technology prevent falls in community-dwelling older adults: A literature review. Inform Prim Care. 2014;21:105112.
22. Blozik, E, Wildeisen, IE, Fueglistaler, P, von Overbeck, J. Telemedicine can help to ensure that patients receive timely medical care. J Telemed Telecare. 2012;18:119121.
23. Casey, M, Hayes, PS, Heaney, D, et al. Implementing transnational telemedicine solutions: A connected health project in rural and remote areas of six Northern Periphery countries. Eur J Gen Pract. 2013;19:5258.
24. Boise, L, Wild, K, Mattek, N, et al. Willingness of older adults to share data and privacy concerns after exposure to unobtrusive in-home monitoring. Gerontechnology. 2013;11:428435.
25. Courtney, KL. Privacy and senior willingness to adopt smart home information technology in residential care facilities. Methods Inf Med. 2008;47:7681.
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International Journal of Technology Assessment in Health Care
  • ISSN: 0266-4623
  • EISSN: 1471-6348
  • URL: /core/journals/international-journal-of-technology-assessment-in-health-care
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