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A Qualitative Study on Implementation of the Intelligent Bed: Findings from a Rehabilitation Ward at a Large Chinese Tertiary Hospital

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Abstract

The intelligent bed, a mechanical hospital bed equipped with several electronic sensor functions, is an assistive healthcare solution intended to reduce the manual workload of health professionals by providing valuable real-time and non-vital information about patients. Implementation of the intelligent bed in the Chinese health care context has not been fully studied. The aim of this study was to explore the experiences of Chinese health professionals during a 12-month implementation period of the intelligent bed in a rehabilitation department at a large tertiary hospital in Guangzhou. A documentary study was carried out 3 months prior to implementation. Participant observation totalling 35 h and qualitative semi-structured interviews with 9 h and 50 min were conducted over a 12-month testing period. Findings in this study highlighted the improved working ergonomics of the intelligent bed in comparison with regular hospital mechanical beds. The bed’s other advanced functions, however, were either not used by the staff, quickly abandoned after a month, or never fully implemented. Barriers to full implementation of the bed’s functions were the Chinese hierarchical organizational culture, inadequate training of the health professionals on the implementation of the intelligent bed, lack of user-friendliness, and insufficient technical support.

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References

  1. Li, J. (2010). Research on work satisfaction and willing of leaving jobs of nursing staffs. Shanghai Nursing, 10(2), 83–87.

    Google Scholar 

  2. Yang, T., & Zhang, X. (2011). Investigation and analysis on nurses’ feeling of accomplishments in China. Work Secures the World, (1), 53–55.

  3. Hesketh, T., Wu, D., Mao, L., & Ma, N. (2012). Violence against doctors in China. BMJ, 345, e5730. doi:10.1136/bmj.e5730.

    Article  Google Scholar 

  4. Chinese Medical Doctor Association. (2011). The fourth time inquiry on the careers of doctors. http://www.cmda.net/gongzuodongtai/zhinengbumen/2011-08-08/9778.html. Accessed April 18, 2016.

  5. Yang, J., & Gao, L. (2015). The investigation on health care staffs’ attitudes towards their children choosing nursing as a career. Education Teaching Forum (3), 73–74.

  6. The National Office on Elders. (2006). The prediction of aging population trend in China. http://news.xinhuanet.com/video/2006-10/11/content_5467909.htm. Accessed April 17, 2016.

  7. Liao, Y. (2013). The development and trend of the intelligent bed. Medical Equipment, 2(10), 5–7.

    Google Scholar 

  8. Ge, X. (2014). Developments on smart home intelligent bed and health status monitoring system based on the internet of things. Management and Technology of Small and Medium Size Enterprise, (9), 241–242.

  9. Pu, W., Li, M., Yu, H., Shen, L., Chen, R., & Ding, H. (2007). Design of an intelligent nursing bed with fall-proof function. Journal of Clinical Rehabilitative Tissue Engineering Research, 11(48), 9765–9767.

    Google Scholar 

  10. MacNeill, V., Sanders, C., Fitzpatrick, R., Hendy, J., Barlow, J., Knapp, M., et al. (2014). Experiences of front-line health professionals in the delivery of telehealth: A qualitative study. The British Journal of General Practice: The Journal of the Royal College of General Practitioners, 64(624), e401–e407. doi:10.3399/bjgp14X680485.

    Article  Google Scholar 

  11. Hu, P. J., Chau, P. Y. K., Sheng, O. R. L., & Tam, K. Y. (1999). Examining the technology acceptance model using physician acceptance of telemedicine technology. Journal of Management Information Systems, 16(2), 91–112. doi:10.2307/40398433.

    Article  Google Scholar 

  12. Menachemi, N., Burke, D., & Ayers, D. (2004). Factors affecting the adoption of telemedicine—A multiple adopter perspective. Journal of Medical Systems, 28(6), 617–632. doi:10.1023/B:JOMS.0000044964.49821.df.

    Article  Google Scholar 

  13. Cai, H., Toft, E., & Dinesen, B. (2015). A conceptual framework for the effect evaluation of the intelligent bed. Wireless Personal Communications, 80(4), 1405–1414. doi:10.1007/s11277-014-2090-7.

    Article  Google Scholar 

  14. Venkatesh, V., & Davis, F. D. (2000). A theoretical extension of the technology acceptance model: Four longitudinal field studies. Management Science, 46(2), 186–204. doi:10.1287/mnsc.46.2.186.11926.

    Article  Google Scholar 

  15. Davis, F. D., Bagozzi, R. P., & Warshaw, P. R. (1989). User acceptance of computer technology: A comparison of two theoretical models. Management Science, 35(8), 982–1003. doi:10.1287/mnsc.35.8.982.

    Article  Google Scholar 

  16. Davis, F. D., & Venkatesh, V. (1996). A critical assessment of potential measurement biases in the technology acceptance model: Three experiments. International Journal of Human–Computer Studies, 45(1), 19–45. doi:10.1006/ijhc.1996.0040.

    Article  Google Scholar 

  17. Davis, F. D. (1989). Perceived usefulness, perceived ease of use, and user acceptance of information technology. MIS Quarterly, 13(3), 319. doi:10.2307/249008.

    Article  Google Scholar 

  18. Cai, H., Toft, E., Hejlesen, O., Hansen, J., Oestergaard, C., & Dinesen, B. (2015). Health Professionals’ User Experience of the intelligent bed in patients’ homes. International Journal of Technology Assessment in Health Care, First View,. doi:10.1017/S0266462315000380.

    Google Scholar 

  19. Yin, R. K. (2013). Case study research-design and methods (5th ed.). Los Angeles: SAGE Publications.

    Google Scholar 

  20. Yin, R. K. (1999). Enhancing the quality of case studies in health services research. Health Services Research, 34(5 Pt 2), 1209–1224.

    Google Scholar 

  21. Mays, N., & Pope, C. (2000). Qualitative research in health care. Assessing Quality in Qualitative Research. BMJ, 320(7226), 50–52. doi:10.1136/bmj.320.7226.50.

    Article  Google Scholar 

  22. Ammenwerth, E., Iller, C., & Mansmann, U. (2003). Can evaluation studies benefit from triangulation? A case study. International Journal of Medical Informatics, 70(2–3), 237–248. doi:10.1016/S1386-5056(03)00059-5.

    Article  Google Scholar 

  23. Noor, K. B. M. (2008). Case study: A strategic research methodology. American Journal of Applied Sciences, 5(11), 1602–1604. doi:10.3844/ajassp.2008.1602.1604.

    Article  Google Scholar 

  24. Patton, M. Q. (1999). Enhancing the quality and credibility of qualitative analysis. Health Services Research, 34(5 Pt 2), 1189–1208.

    Google Scholar 

  25. Britten, N. (1995). Qualitative research: Qualitative interviews in medical research. BMJ, 311(6999), 251–253. doi:10.1136/bmj.311.6999.251.

    Article  Google Scholar 

  26. Cleary, M., Horsfall, J., & Hayter, M. (2014). Data collection and sampling in qualitative research: Does size matter? Journal of Advanced Nursing, 70(3), 473–475. doi:10.1111/jan.12163.

    Article  Google Scholar 

  27. Rogers, E. M. (2003). Diffusion of innovations (5th ed.). New York: Free Press.

    Google Scholar 

  28. Brinkmann, S., & Kvale, S. (2014). Interviews: Learning the craft of qualitative research interviewing (3rd ed.). Los Angeles: SAGE Publications.

    Google Scholar 

  29. DiCicco-Bloom, B., & Crabtree, B. F. (2006). The qualitative research interview. Medical Education, 40(4), 314–321. doi:10.1111/j.1365-2929.2006.02418.x.

    Article  Google Scholar 

  30. Dinesen, B., & Toft, E. (2009). Telehomecare challenge collaboration among healthcare professionals. Wireless Personal Communications, 51(4), 711–724. doi:10.1007/s11277-009-9767-3.

    Article  Google Scholar 

  31. Dinesen, B., Huniche, L., & Toft, E. (2013). Attitudes of COPD patients towards tele-rehabilitation: A cross-sector case study. International Journal of Environmental Research and Public Health, 10(11), 6184–6198. doi:10.3390/ijerph10116184.

    Article  Google Scholar 

  32. Zhang, L. (2013). Invention of intelligent assistive devices in China: Today and future. Chinese Journal of Rehabilitation Theory and Practice, 19(5), 401–403. doi:10.3969/j.issn.1006-9771.2013.05.001.

    Google Scholar 

  33. Zhai, J., Xu, X., Liu, C., & Xie, C. (2010). Design study of a novel intelligent health care and monitoring bed. Journal of Machine Design, 27(8), 35–37, 82, doi:10.13841/j.cnki.jxsj.2010.08.022.

  34. Cooke, F. L., & Zhan, C. (2013). Between market and bureaucracy: Public healthcare reforms in China and nurses’ terms and conditions. The International Journal of Human Resource Management, 24(16), 3178–3195. doi:10.1080/09585192.2013.775034.

    Article  Google Scholar 

  35. Sirois, P., Fournier, H., Lebouthilier, A., Guerette-Daigle, L., Robichaud, S., Leblanc-Cormier, G., et al. (2013). Nurses’ perceptions and attitudes towards new ADU technology and use. Technology and Health Care, 21(1), 41–47. doi:10.3233/Thc-120708.

    Google Scholar 

  36. Gagnon, M. P., Orruno, E., Asua, J., Abdeljelil, A. B., & Emparanza, J. (2012). Using a modified technology acceptance model to evaluate healthcare professionals’ adoption of a new telemonitoring system. Telemedicine and e-Health, 18(1), 54–59. doi:10.1089/tmj.2011.0066.

    Article  Google Scholar 

  37. Brewer, E., Demmer, M., Ho, M., Honicky, R. J., Pal, J., Plauche, M., et al. (2006). The challenges of technology research for developing regions. Pervasive Computing, IEEE, 5(2), 15–23. doi:10.1109/MPRV.2006.40.

    Article  Google Scholar 

  38. Broens, T. H. F., Huis in’t Veld, R. M. H. A., Vollenbroek-Hutten, M. M. R., Hermens, H. J., van Halteren, A. T., & Nieuwenhuis, L. J. M. (2007). Determinants of successful telemedicine implementations: A literature study. Journal of Telemedicine and Telecare, 13(6), 303–309. doi:10.1258/135763307781644951.

    Article  Google Scholar 

  39. Knibbe, J. J., & Friele, R. D. (1996). Prevalence of back pain and characteristics of the physical workload of community nurses. Ergonomics, 39(2), 186–198. doi:10.1080/00140139608964450.

    Article  Google Scholar 

  40. Yip, Y. B. (2001). A study of work stress, patient handling activities and the risk of low back pain among nurses in Hong Kong. Journal of Advanced Nursing, 36(6), 794–804. doi:10.1046/j.1365-2648.2001.02037.x.

    Article  Google Scholar 

  41. Rufo, R. (2011). Behind the scenes with integrated telemedicine. Nursing Management (Springhouse), 42, 6–9. doi:10.1097/01.numa.0000406582.33874.16.

    Article  Google Scholar 

  42. Kocher, R., & Sahni, N. R. (2011). Rethinking Health Care Labor. New England Journal of Medicine, 365(15), 1370–1372. doi:10.1056/NEJMp1109649.

    Article  Google Scholar 

  43. Kidholm, K., Ekeland, A. G., Jensen, L. K., Rasmussen, J., Pedersen, C. D., Bowes, A., et al. (2012). A model for assessment of telemedicine applications: Mast. International Journal of Technology Assessment in Health Care, 28(1), 44–51. doi:10.1017/S0266462311000638.

    Article  Google Scholar 

  44. Karsh, B. T. (2004). Beyond usability: Designing effective technology implementation systems to promote patient safety. Quality and Safety in Health Care, 13(5), 388–394. doi:10.1136/qhc.13.5.388.

    Article  Google Scholar 

  45. Aggelidis, V. P., & Chatzoglou, P. D. (2009). Using a modified technology acceptance model in hospitals. International Journal of Medical Informatics, 78(2), 115–126. doi:10.1016/j.ijmedinf.2008.06.006.

    Article  Google Scholar 

  46. Stowe, S., & Harding, S. (2010). Telecare, telehealth and telemedicine. European Geriatric Medicine, 1(3), 193–197. doi:10.1016/j.eurger.2010.04.002.

    Article  Google Scholar 

  47. Demiris, G., Charness, N., Krupinski, E., Ben-Arieh, D., Washington, K., Wu, J., et al. (2010). The role of human factors in telehealth. Telemedicine and e-Health, 16(4), 446–453. doi:10.1089/tmj.2009.0114.

    Article  Google Scholar 

  48. Koumaditis, K., Themistocleous, M., & Cunha, P. R. D. (2013). SOA implementation critical success factors in healthcare. Journal of Enterprise Information Management, 26(4), 343–362. doi:10.1108/JEIM-06-2012-0036.

    Article  Google Scholar 

  49. Yao, W., Chu, C. H., & Li, Z. (2012). The adoption and implementation of RFID technologies in healthcare: A literature review. Journal of Medical Systems, 36(6), 3507–3525. doi:10.1007/s10916-011-9789-8.

    Article  Google Scholar 

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Acknowledgments

The authors would like to thank Mr. Hjalte Holm Andersen and Ms. Ida Munk Petersen for their comments on the article. We also wish to thank the Department of Health at Guangdong Province, the Royal Danish Consulate General in Guangzhou, and Guangdong Provincial Hospital of Chinese Medicine for their cooperation. We thank Linak A/S for providing five IBs to the study. We especially thank Mr. Ole Lindholm, Mr. Karsten Westermann, Mr. Simon Jenkinson, Ms. Grethe Koudal, Mr. Long Zhao, Mr. Xiang Gao, Mr. Shengwang Wan, Mr. Rongyuan Yang and the rest of staffs from the Chinese hospital for their support.

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Authors and Affiliations

  1. Medical Informatics Group (MI), Department of Health Science and Technology, Aalborg University, Aalborg, Denmark

    Hao Cai & John Hansen

  2. Laboratory of Assistive Technologies, Telehealth and Telerehabilitation at Center for Sensory-Motor Interaction (SMI), Department of Health Science and Technology, Aalborg University, Fredrik Bajers Vej 7C1, 9220, Aalborg, Denmark

    Hao Cai, Hans Jørgen Krebs & Birthe Dinesen

  3. School of Automation, Guangdong University of Technology, Guangzhou, China

    Yingshan Tao & Yanguang Cai

  4. The 2nd Affiliated Hospital, Guangzhou University of Chinese Medicine, Guangzhou, China

    Ruihuan Pan

  5. College of Medicine, Qatar University, Doha, Qatar

    Egon Toft

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  1. Hao Cai
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Correspondence to Hao Cai.

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Cai, H., Krebs, H.J., Tao, Y. et al. A Qualitative Study on Implementation of the Intelligent Bed: Findings from a Rehabilitation Ward at a Large Chinese Tertiary Hospital. Wireless Pers Commun 90, 399–420 (2016). https://doi.org/10.1007/s11277-016-3375-9

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